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December 29, 2025 13:37
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Solution draft log for https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/25
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| # Solve.mjs Log - 2025-12-29T13:25:58.890Z | |
| [2025-12-29T13:25:58.891Z] [INFO] 📁 Log file: /home/hive/solve-2025-12-29T13-25-58-890Z.log | |
| [2025-12-29T13:25:58.892Z] [INFO] (All output will be logged here) | |
| [2025-12-29T13:25:59.405Z] [INFO] | |
| [2025-12-29T13:25:59.406Z] [INFO] 🚀 solve v0.51.18 | |
| [2025-12-29T13:25:59.406Z] [INFO] 🔧 Raw command executed: | |
| [2025-12-29T13:25:59.407Z] [INFO] /home/hive/.nvm/versions/node/v20.19.6/bin/node /home/hive/.bun/bin/solve https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 --model opus --attach-logs --verbose --no-tool-check --auto-continue-on-limit-reset | |
| [2025-12-29T13:25:59.407Z] [INFO] | |
| [2025-12-29T13:25:59.421Z] [INFO] | |
| [2025-12-29T13:25:59.421Z] [WARNING] ⚠️ SECURITY WARNING: --attach-logs is ENABLED | |
| [2025-12-29T13:25:59.422Z] [INFO] | |
| [2025-12-29T13:25:59.422Z] [INFO] This option will upload the complete solution draft log file to the Pull Request. | |
| [2025-12-29T13:25:59.423Z] [INFO] The log may contain sensitive information such as: | |
| [2025-12-29T13:25:59.423Z] [INFO] • API keys, tokens, or secrets | |
| [2025-12-29T13:25:59.423Z] [INFO] • File paths and directory structures | |
| [2025-12-29T13:25:59.423Z] [INFO] • Command outputs and error messages | |
| [2025-12-29T13:25:59.423Z] [INFO] • Internal system information | |
| [2025-12-29T13:25:59.424Z] [INFO] | |
| [2025-12-29T13:25:59.424Z] [INFO] ⚠️ DO NOT use this option with public repositories or if the log | |
| [2025-12-29T13:25:59.424Z] [INFO] might contain sensitive data that should not be shared publicly. | |
| [2025-12-29T13:25:59.424Z] [INFO] | |
| [2025-12-29T13:25:59.424Z] [INFO] Continuing in 5 seconds... (Press Ctrl+C to abort) | |
| [2025-12-29T13:25:59.424Z] [INFO] | |
| [2025-12-29T13:26:04.430Z] [INFO] | |
| [2025-12-29T13:26:04.460Z] [INFO] 💾 Disk space check: 43025MB available (2048MB required) ✅ | |
| [2025-12-29T13:26:04.462Z] [INFO] 🧠 Memory check: 7305MB available, swap: 2047MB (0MB used), total: 9352MB (256MB required) ✅ | |
| [2025-12-29T13:26:04.463Z] [INFO] ⏩ Skipping tool connection validation (dry-run mode or skip-tool-connection-check enabled) | |
| [2025-12-29T13:26:04.463Z] [INFO] ⏩ Skipping GitHub authentication check (dry-run mode or skip-tool-connection-check enabled) | |
| [2025-12-29T13:26:04.463Z] [INFO] 📋 URL validation: | |
| [2025-12-29T13:26:04.463Z] [INFO] Input URL: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 | |
| [2025-12-29T13:26:04.463Z] [INFO] Is Issue URL: true | |
| [2025-12-29T13:26:04.463Z] [INFO] Is PR URL: false | |
| [2025-12-29T13:26:04.464Z] [INFO] 🔍 Checking repository access for auto-fork... | |
| [2025-12-29T13:26:05.453Z] [INFO] Repository visibility: public | |
| [2025-12-29T13:26:05.453Z] [INFO] ✅ Auto-fork: No write access detected, enabling fork mode | |
| [2025-12-29T13:26:05.454Z] [INFO] ✅ Repository access check: Skipped (fork mode enabled) | |
| [2025-12-29T13:26:05.826Z] [INFO] Repository visibility: public | |
| [2025-12-29T13:26:05.826Z] [INFO] Auto-cleanup default: false (repository is public) | |
| [2025-12-29T13:26:05.827Z] [INFO] 🔍 Auto-continue enabled: Checking for existing PRs for issue #24... | |
| [2025-12-29T13:26:06.705Z] [INFO] 🔍 Fork mode: Checking for existing branches in konard/Jhon-Crow-text-to-speech-with-chatterbox... | |
| [2025-12-29T13:26:07.487Z] [INFO] 📝 No existing PRs found for issue #24 - creating new PR | |
| [2025-12-29T13:26:07.488Z] [INFO] 📝 Issue mode: Working with issue #24 | |
| [2025-12-29T13:26:07.489Z] [INFO] | |
| Creating temporary directory: /tmp/gh-issue-solver-1767014767488 | |
| [2025-12-29T13:26:07.491Z] [INFO] | |
| 🍴 Fork mode: ENABLED | |
| [2025-12-29T13:26:07.491Z] [INFO] Checking fork status... | |
| [2025-12-29T13:26:07.816Z] [INFO] 🔍 Detecting fork conflicts... | |
| [2025-12-29T13:26:08.822Z] [INFO] ✅ No fork conflict: Safe to proceed | |
| [2025-12-29T13:26:09.187Z] [INFO] ✅ Fork exists: konard/Jhon-Crow-text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:09.188Z] [INFO] 🔍 Validating fork parent... | |
| [2025-12-29T13:26:09.610Z] [INFO] ✅ Fork parent validated: Jhon-Crow/text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:09.613Z] [INFO] | |
| 📥 Cloning repository: konard/Jhon-Crow-text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:11.006Z] [INFO] ✅ Cloned to: /tmp/gh-issue-solver-1767014767488 | |
| [2025-12-29T13:26:11.052Z] [INFO] 🔗 Setting upstream: Jhon-Crow/text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:11.096Z] [INFO] ℹ️ Upstream exists: Using existing upstream remote | |
| [2025-12-29T13:26:11.097Z] [INFO] 🔄 Fetching upstream... | |
| [2025-12-29T13:26:11.408Z] [INFO] ✅ Upstream fetched: Successfully | |
| [2025-12-29T13:26:11.409Z] [INFO] 🔄 Syncing default branch... | |
| [2025-12-29T13:26:11.805Z] [INFO] ℹ️ Default branch: main | |
| [2025-12-29T13:26:11.854Z] [INFO] ✅ Default branch synced: with upstream/main | |
| [2025-12-29T13:26:11.855Z] [INFO] 🔄 Pushing to fork: main branch | |
| [2025-12-29T13:26:12.658Z] [INFO] ✅ Fork updated: Default branch pushed to fork | |
| [2025-12-29T13:26:12.820Z] [INFO] | |
| 📌 Default branch: main | |
| [2025-12-29T13:26:12.867Z] [INFO] | |
| 🌿 Creating branch: issue-24-6045c8942678 from main (default) | |
| [2025-12-29T13:26:12.916Z] [INFO] 🔍 Verifying: Branch creation... | |
| [2025-12-29T13:26:12.965Z] [INFO] ✅ Branch created: issue-24-6045c8942678 | |
| [2025-12-29T13:26:12.966Z] [INFO] ✅ Current branch: issue-24-6045c8942678 | |
| [2025-12-29T13:26:12.966Z] [INFO] Branch operation: Create new branch | |
| [2025-12-29T13:26:12.966Z] [INFO] Branch verification: Matches expected | |
| [2025-12-29T13:26:12.970Z] [INFO] | |
| 🚀 Auto PR creation: ENABLED | |
| [2025-12-29T13:26:12.970Z] [INFO] Creating: Initial commit and draft PR... | |
| [2025-12-29T13:26:12.971Z] [INFO] | |
| [2025-12-29T13:26:12.971Z] [INFO] Using CLAUDE.md mode (--claude-file=true, --gitkeep-file=false) | |
| [2025-12-29T13:26:12.971Z] [INFO] 📝 Creating: CLAUDE.md with task details | |
| [2025-12-29T13:26:12.972Z] [INFO] Issue URL from argv['issue-url']: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 | |
| [2025-12-29T13:26:12.972Z] [INFO] Issue URL from argv._[0]: undefined | |
| [2025-12-29T13:26:12.972Z] [INFO] Final issue URL: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 | |
| [2025-12-29T13:26:12.973Z] [INFO] ✅ File created: CLAUDE.md | |
| [2025-12-29T13:26:12.974Z] [INFO] 📦 Adding file: To git staging | |
| [2025-12-29T13:26:13.064Z] [INFO] Git status after add: A CLAUDE.md | |
| [2025-12-29T13:26:13.065Z] [INFO] 📝 Creating commit: With CLAUDE.md file | |
| [2025-12-29T13:26:13.113Z] [INFO] ✅ Commit created: Successfully with CLAUDE.md | |
| [2025-12-29T13:26:13.114Z] [INFO] Commit output: [issue-24-6045c8942678 8cd5c73] Initial commit with task details | |
| 1 file changed, 7 insertions(+) | |
| create mode 100644 CLAUDE.md | |
| [2025-12-29T13:26:13.160Z] [INFO] Commit hash: 8cd5c73... | |
| [2025-12-29T13:26:13.210Z] [INFO] Latest commit: 8cd5c73 Initial commit with task details | |
| [2025-12-29T13:26:13.257Z] [INFO] Git status: clean | |
| [2025-12-29T13:26:13.308Z] [INFO] Remotes: origin https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox.git (fetch) | |
| [2025-12-29T13:26:13.358Z] [INFO] Branch info: * issue-24-6045c8942678 8cd5c73 [origin/main: ahead 1] Initial commit with task details | |
| main f7b6f67 [origin/main] Merge pull request #23 from konard/issue-22-a5e0f79d0bad | |
| [2025-12-29T13:26:13.358Z] [INFO] 📤 Pushing branch: To remote repository... | |
| [2025-12-29T13:26:13.359Z] [INFO] Push command: git push -u origin issue-24-6045c8942678 | |
| [2025-12-29T13:26:14.203Z] [INFO] Push exit code: 0 | |
| [2025-12-29T13:26:14.204Z] [INFO] Push output: remote: | |
| remote: Create a pull request for 'issue-24-6045c8942678' on GitHub by visiting: | |
| remote: https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox/pull/new/issue-24-6045c8942678 | |
| remote: | |
| To https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox.git | |
| * [new branch] issue-24-6045c8942678 -> issue-24-6045c8942678 | |
| branch 'issue-24-6045c8942678' set up to track 'origin/issue-24-6045c8942678'. | |
| [2025-12-29T13:26:14.205Z] [INFO] ✅ Branch pushed: Successfully to remote | |
| [2025-12-29T13:26:14.205Z] [INFO] Push output: remote: | |
| remote: Create a pull request for 'issue-24-6045c8942678' on GitHub by visiting: | |
| remote: https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox/pull/new/issue-24-6045c8942678 | |
| remote: | |
| To https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox.git | |
| * [new branch] issue-24-6045c8942678 -> issue-24-6045c8942678 | |
| branch 'issue-24-6045c8942678' set up to track 'origin/issue-24-6045c8942678'. | |
| [2025-12-29T13:26:14.205Z] [INFO] Waiting for GitHub to sync... | |
| [2025-12-29T13:26:16.762Z] [INFO] Compare API check: 1 commit(s) ahead of main | |
| [2025-12-29T13:26:16.762Z] [INFO] GitHub compare API ready: 1 commit(s) found | |
| [2025-12-29T13:26:17.067Z] [INFO] Branch verified on GitHub: issue-24-6045c8942678 | |
| [2025-12-29T13:26:17.370Z] [INFO] Remote commit SHA: 8cd5c73... | |
| [2025-12-29T13:26:17.371Z] [INFO] 📋 Getting issue: Title from GitHub... | |
| [2025-12-29T13:26:17.906Z] [INFO] Issue title: "Fix & update" | |
| [2025-12-29T13:26:17.907Z] [INFO] 👤 Getting user: Current GitHub account... | |
| [2025-12-29T13:26:18.256Z] [INFO] Current user: konard | |
| [2025-12-29T13:26:18.729Z] [INFO] User is not a collaborator (will skip assignment) | |
| [2025-12-29T13:26:18.731Z] [INFO] User is not a collaborator (will skip assignment) | |
| [2025-12-29T13:26:18.732Z] [INFO] 🔄 Fetching: Latest main branch... | |
| [2025-12-29T13:26:19.095Z] [INFO] ✅ Base updated: Fetched latest main | |
| [2025-12-29T13:26:19.096Z] [INFO] 🔍 Checking: Commits between branches... | |
| [2025-12-29T13:26:19.144Z] [INFO] Commits ahead of origin/main: 1 | |
| [2025-12-29T13:26:19.145Z] [INFO] ✅ Commits found: 1 commit(s) ahead | |
| [2025-12-29T13:26:19.146Z] [INFO] 🔀 Creating PR: Draft pull request... | |
| [2025-12-29T13:26:19.146Z] [INFO] 🎯 Target branch: main (default) | |
| [2025-12-29T13:26:19.146Z] [INFO] PR Title: [WIP] Fix & update | |
| [2025-12-29T13:26:19.147Z] [INFO] Base branch: main | |
| [2025-12-29T13:26:19.147Z] [INFO] Head branch: issue-24-6045c8942678 | |
| [2025-12-29T13:26:19.147Z] [INFO] Assignee: konard | |
| [2025-12-29T13:26:19.147Z] [INFO] PR Body: | |
| ## 🤖 AI-Powered Solution Draft | |
| This pull request is being automatically generated to solve issue Jhon-Crow/text-to-speech-with-chatterbox#24. | |
| ### 📋 Issue Reference | |
| Fixes Jhon-Crow/text-to-speech-with-chatterbox#24 | |
| ### 🚧 Status | |
| **Work in Progress** - The AI assistant is currently analyzing and implementing the solution draft. | |
| ### 📝 Implementation Details | |
| _Details will be added as the solution draft is developed..._ | |
| --- | |
| *This PR was created automatically by the AI issue solver* | |
| [2025-12-29T13:26:19.149Z] [INFO] Command: cd "/tmp/gh-issue-solver-1767014767488" && gh pr create --draft --title "$(cat '/tmp/pr-title-1767014779149.txt')" --body-file "/tmp/pr-body-1767014779149.md" --base main --head konard:issue-24-6045c8942678 --repo Jhon-Crow/text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:21.494Z] [INFO] 🔍 Verifying: PR creation... | |
| [2025-12-29T13:26:21.974Z] [INFO] ✅ Verification: PR exists on GitHub | |
| [2025-12-29T13:26:21.976Z] [INFO] ✅ PR created: #25 | |
| [2025-12-29T13:26:21.976Z] [INFO] 📍 PR URL: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/25 | |
| [2025-12-29T13:26:21.976Z] [INFO] ℹ️ Note: Could not assign (no permission) | |
| [2025-12-29T13:26:21.976Z] [INFO] 🔗 Linking: Issue #24 to PR #25... | |
| [2025-12-29T13:26:22.560Z] [INFO] Issue node ID: I_kwDOQv5SjM7gjhro | |
| [2025-12-29T13:26:22.938Z] [INFO] PR node ID: PR_kwDOQv5SjM6602f5 | |
| [2025-12-29T13:26:23.545Z] [INFO] | |
| [2025-12-29T13:26:23.545Z] [WARNING] ⚠️ ISSUE LINK MISSING: PR not linked to issue | |
| [2025-12-29T13:26:23.546Z] [INFO] | |
| [2025-12-29T13:26:23.546Z] [WARNING] The PR was created from a fork but wasn't linked to the issue. | |
| [2025-12-29T13:26:23.546Z] [WARNING] Expected: "Fixes Jhon-Crow/text-to-speech-with-chatterbox#24" in PR body | |
| [2025-12-29T13:26:23.546Z] [INFO] | |
| [2025-12-29T13:26:23.546Z] [WARNING] To fix manually: | |
| [2025-12-29T13:26:23.547Z] [WARNING] 1. Edit the PR description at: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/25 | |
| [2025-12-29T13:26:23.547Z] [WARNING] 2. Add this line: Fixes Jhon-Crow/text-to-speech-with-chatterbox#24 | |
| [2025-12-29T13:26:23.547Z] [INFO] | |
| [2025-12-29T13:26:23.867Z] [INFO] 👤 Current user: konard | |
| [2025-12-29T13:26:23.868Z] [INFO] | |
| 📊 Comment counting conditions: | |
| [2025-12-29T13:26:23.868Z] [INFO] prNumber: 25 | |
| [2025-12-29T13:26:23.868Z] [INFO] branchName: issue-24-6045c8942678 | |
| [2025-12-29T13:26:23.869Z] [INFO] isContinueMode: false | |
| [2025-12-29T13:26:23.869Z] [INFO] Will count comments: true | |
| [2025-12-29T13:26:23.869Z] [INFO] 💬 Counting comments: Checking for new comments since last commit... | |
| [2025-12-29T13:26:23.870Z] [INFO] PR #25 on branch: issue-24-6045c8942678 | |
| [2025-12-29T13:26:23.870Z] [INFO] Owner/Repo: Jhon-Crow/text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:24.330Z] [INFO] 📅 Last commit time (from API): 2025-12-29T13:26:13.000Z | |
| [2025-12-29T13:26:25.475Z] [INFO] 💬 New PR comments: 0 | |
| [2025-12-29T13:26:25.476Z] [INFO] 💬 New PR review comments: 0 | |
| [2025-12-29T13:26:25.476Z] [INFO] 💬 New issue comments: 0 | |
| [2025-12-29T13:26:25.477Z] [INFO] Total new comments: 0 | |
| [2025-12-29T13:26:25.477Z] [INFO] Comment lines to add: No (saving tokens) | |
| [2025-12-29T13:26:25.477Z] [INFO] PR review comments fetched: 0 | |
| [2025-12-29T13:26:25.477Z] [INFO] PR conversation comments fetched: 0 | |
| [2025-12-29T13:26:25.477Z] [INFO] Total PR comments checked: 0 | |
| [2025-12-29T13:26:28.400Z] [INFO] Feedback info will be added to prompt: | |
| [2025-12-29T13:26:28.401Z] [INFO] - Pull request description was edited after last commit | |
| [2025-12-29T13:26:28.401Z] [INFO] 📅 Getting timestamps: From GitHub servers... | |
| [2025-12-29T13:26:28.756Z] [INFO] 📝 Issue updated: 2025-12-29T13:25:33.000Z | |
| [2025-12-29T13:26:29.051Z] [INFO] 💬 Comments: None found | |
| [2025-12-29T13:26:29.411Z] [INFO] 🔀 Recent PR: 2025-12-29T13:26:20.000Z | |
| [2025-12-29T13:26:29.411Z] [INFO] | |
| ✅ Reference time: 2025-12-29T13:26:20.000Z | |
| [2025-12-29T13:26:29.412Z] [INFO] | |
| 🔍 Checking for uncommitted changes to include as feedback... | |
| [2025-12-29T13:26:29.458Z] [INFO] ✅ No uncommitted changes found | |
| [2025-12-29T13:26:29.758Z] [INFO] 📦 Fork workflows detected: https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox/actions?query=branch%3Aissue-24-6045c8942678 | |
| [2025-12-29T13:26:31.400Z] [INFO] 🎭 Playwright MCP detected - enabling browser automation hints | |
| [2025-12-29T13:26:31.404Z] [INFO] | |
| 📝 Final prompt structure: | |
| [2025-12-29T13:26:31.404Z] [INFO] Characters: 590 | |
| [2025-12-29T13:26:31.404Z] [INFO] System prompt characters: 12008 | |
| [2025-12-29T13:26:31.404Z] [INFO] Feedback info: Included | |
| [2025-12-29T13:26:31.406Z] [INFO] | |
| 🤖 Executing Claude: OPUS | |
| [2025-12-29T13:26:31.407Z] [INFO] Model: opus | |
| [2025-12-29T13:26:31.407Z] [INFO] Working directory: /tmp/gh-issue-solver-1767014767488 | |
| [2025-12-29T13:26:31.407Z] [INFO] Branch: issue-24-6045c8942678 | |
| [2025-12-29T13:26:31.407Z] [INFO] Prompt length: 590 chars | |
| [2025-12-29T13:26:31.407Z] [INFO] System prompt length: 12008 chars | |
| [2025-12-29T13:26:31.407Z] [INFO] Feedback info included: Yes (1 lines) | |
| [2025-12-29T13:26:31.460Z] [INFO] 📈 System resources before execution: | |
| [2025-12-29T13:26:31.461Z] [INFO] Memory: MemFree: 2908616 kB | |
| [2025-12-29T13:26:31.462Z] [INFO] Load: 0.95 0.86 0.68 3/582 272471 | |
| [2025-12-29T13:26:31.462Z] [INFO] | |
| 📝 Raw command: | |
| [2025-12-29T13:26:31.463Z] [INFO] (cd "/tmp/gh-issue-solver-1767014767488" && claude --output-format stream-json --verbose --dangerously-skip-permissions --model claude-opus-4-5-20251101 -p "Issue to solve: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 | |
| Your prepared branch: issue-24-6045c8942678 | |
| Your prepared working directory: /tmp/gh-issue-solver-1767014767488 | |
| Your prepared Pull Request: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/25 | |
| Your forked repository: konard/Jhon-Crow-text-to-speech-with-chatterbox | |
| Original repository (upstream): Jhon-Crow/text-to-speech-with-chatterbox | |
| GitHub Actions on your fork: https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox/actions?query=branch%3Aissue-24-6045c8942678 | |
| Proceed. | |
| " --append-system-prompt "You are an AI issue solver. You prefer to find the root cause of each and every issue. When you talk, you prefer to speak with facts which you have double-checked yourself or cite sources that provide evidence, like quote actual code or give references to documents or pages found on the internet. You are polite and patient, and prefer to assume good intent, trying your best to be helpful. If you are unsure or have assumptions, you prefer to test them yourself or ask questions to clarify requirements. | |
| General guidelines. | |
| - When you execute commands, always save their logs to files for easier reading if the output becomes large. | |
| - When running commands, do not set a timeout yourself — let them run as long as needed (default timeout - 2 minutes is more than enough), and once they finish, review the logs in the file. | |
| - When running sudo commands (especially package installations like apt-get, yum, npm install, etc.), always run them in the background to avoid timeout issues and permission errors when the process needs to be killed. Use the run_in_background parameter or append & to the command. | |
| - When CI is failing or user reports failures, consider adding a detailed investigation protocol to your todo list with these steps: | |
| Step 1: List recent runs with timestamps using: gh run list --repo Jhon-Crow/text-to-speech-with-chatterbox --branch issue-24-6045c8942678 --limit 5 --json databaseId,conclusion,createdAt,headSha | |
| Step 2: Verify runs are after the latest commit by checking timestamps and SHA | |
| Step 3: For each non-passing run, download logs to preserve them: gh run view {run-id} --repo Jhon-Crow/text-to-speech-with-chatterbox --log > ci-logs/{workflow}-{run-id}.log | |
| Step 4: Read each downloaded log file using Read tool to understand the actual failures | |
| Step 5: Report findings with specific errors and line numbers from logs | |
| This detailed investigation is especially helpful when user mentions CI failures, asks to investigate logs, you see non-passing status, or when finalizing a PR. | |
| Note: If user says \"failing\" but tools show \"passing\", this might indicate stale data - consider downloading fresh logs and checking timestamps to resolve the discrepancy. | |
| - When a code or log file has more than 1500 lines, read it in chunks of 1500 lines. | |
| - When facing a complex problem, do as much tracing as possible and turn on all verbose modes. | |
| - When you create debug, test, or example/experiment scripts for fixing, always keep them in an examples and/or experiments folders so you can reuse them later. | |
| - When testing your assumptions, use the experiment scripts, and add it to experiments folder. | |
| - When your experiments can show real world use case of the software, add it to examples folder. | |
| - When you face something extremely hard, use divide and conquer — it always helps. | |
| Initial research. | |
| - When you start, make sure you create detailed plan for yourself and follow your todo list step by step, make sure that as many points from these guidelines are added to your todo list to keep track of everything that can help you solve the issue with highest possible quality. | |
| - When user mentions CI failures or asks to investigate logs, consider adding these todos to track the investigation: (1) List recent CI runs with timestamps, (2) Download logs from failed runs to ci-logs/ directory, (3) Analyze error messages and identify root cause, (4) Implement fix, (5) Verify fix resolves the specific errors found in logs. | |
| - When you read issue, read all details and comments thoroughly. | |
| - When you see screenshots or images in issue descriptions, pull request descriptions, comments, or discussions, use WebFetch tool (or fetch tool) to download the image first, then use Read tool to view and analyze it. IMPORTANT: Before reading downloaded images with the Read tool, verify the file is a valid image (not HTML). Use a CLI tool like 'file' command to check the actual file format. Reading corrupted or non-image files (like GitHub's HTML 404 pages saved as .png) can cause \"Could not process image\" errors and may crash the AI solver process. If the file command shows \"HTML\" or \"text\", the download failed and you should retry or skip the image. | |
| - When you need issue details, use gh issue view https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24. | |
| - When you need related code, use gh search code --owner Jhon-Crow [keywords]. | |
| - When you need repo context, read files in your working directory. | |
| - When you study related work, study the most recent related pull requests. | |
| - When issue is not defined enough, write a comment to ask clarifying questions. | |
| - When accessing GitHub Gists (especially private ones), use gh gist view command instead of direct URL fetching to ensure proper authentication. | |
| - When you are fixing a bug, please make sure you first find the actual root cause, do as many experiments as needed. | |
| - When you are fixing a bug and code does not have enough tracing/logs, add them and make sure they stay in the code, but are switched off by default. | |
| - When you need comments on a pull request, note that GitHub has THREE different comment types with different API endpoints: | |
| 1. PR review comments (inline code comments): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/pulls/25/comments --paginate | |
| 2. PR conversation comments (general discussion): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/issues/25/comments --paginate | |
| 3. PR reviews (approve/request changes): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/pulls/25/reviews --paginate | |
| IMPORTANT: The command \"gh pr view --json comments\" ONLY returns conversation comments and misses review comments! | |
| - When you need latest comments on issue, use gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/issues/24/comments --paginate. | |
| Solution development and testing. | |
| - When issue is solvable, implement code with tests. | |
| - When implementing features, search for similar existing implementations in the codebase and use them as examples instead of implementing everything from scratch. | |
| - When coding, each atomic step that can be useful by itself should be commited to the pull request's branch, meaning if work will be interrupted by any reason parts of solution will still be kept intact and safe in pull request. | |
| - When you test: | |
| start from testing of small functions using separate scripts; | |
| write unit tests with mocks for easy and quick start. | |
| - When you test integrations, use existing framework. | |
| - When you test solution draft, include automated checks in pr. | |
| - When issue is unclear, write comment on issue asking questions. | |
| - When you encounter any problems that you unable to solve yourself (any human feedback or help), write a comment to the pull request asking for help. | |
| - When you need human help, use gh pr comment 25 --body \"your message\" to comment on existing PR. | |
| Preparing pull request. | |
| - When you code, follow contributing guidelines. | |
| - When you commit, write clear message. | |
| - When you need examples of style, use gh pr list --repo Jhon-Crow/text-to-speech-with-chatterbox --state merged --search [keywords]. | |
| - When you open pr, describe solution draft and include tests. | |
| - When there is a package with version and GitHub Actions workflows for automatic release, update the version (or other necessary release trigger) in your pull request to prepare for next release. | |
| - When you update existing pr 25, use gh pr edit to modify title and description. | |
| - When you are about to commit or push code, ALWAYS run local CI checks first if they are available in contributing guidelines (like ruff check, mypy, eslint, etc.) to catch errors before pushing. | |
| - When you finalize the pull request: | |
| follow style from merged prs for code, title, and description, | |
| make sure no uncommitted changes corresponding to the original requirements are left behind, | |
| make sure the default branch is merged to the pull request's branch, | |
| make sure all CI checks passing if they exist before you finish, | |
| check for latest comments on the issue and pull request to ensure no recent feedback was missed, | |
| double-check that all changes in the pull request answer to original requirements of the issue, | |
| make sure no new new bugs are introduced in pull request by carefully reading gh pr diff, | |
| make sure no previously existing features were removed without an explicit request from users via the issue description, issue comments, and/or pull request comments. | |
| - When you finish implementation, use gh pr ready 25. | |
| Workflow and collaboration. | |
| - When you check branch, verify with git branch --show-current. | |
| - When you push, push only to branch issue-24-6045c8942678. | |
| - When you finish, create a pull request from branch issue-24-6045c8942678. (Note: PR 25 already exists, update it instead) | |
| - When you organize workflow, use pull requests instead of direct merges to default branch (main or master). | |
| - When you manage commits, preserve commit history for later analysis. | |
| - When you contribute, keep repository history forward-moving with regular commits, pushes, and reverts if needed. | |
| - When you face conflict that you cannot resolve yourself, ask for help. | |
| - When you collaborate, respect branch protections by working only on issue-24-6045c8942678. | |
| - When you mention result, include pull request url or comment url. | |
| - When you need to create pr, remember pr 25 already exists for this branch. | |
| Self review. | |
| - When you check your solution draft, run all tests locally. | |
| - When you check your solution draft, verify git status shows a clean working tree with no uncommitted changes. | |
| - When you compare with repo style, use gh pr diff [number]. | |
| - When you finalize, confirm code, tests, and description are consistent. | |
| GitHub CLI command patterns. | |
| - IMPORTANT: Always use --paginate flag when fetching lists from GitHub API to ensure all results are returned (GitHub returns max 30 per page by default). | |
| - When listing PR review comments (inline code comments), use gh api repos/OWNER/REPO/pulls/NUMBER/comments --paginate. | |
| - When listing PR conversation comments, use gh api repos/OWNER/REPO/issues/NUMBER/comments --paginate. | |
| - When listing PR reviews, use gh api repos/OWNER/REPO/pulls/NUMBER/reviews --paginate. | |
| - When listing issue comments, use gh api repos/OWNER/REPO/issues/NUMBER/comments --paginate. | |
| - When adding PR comment, use gh pr comment NUMBER --body \"text\" --repo OWNER/REPO. | |
| - When adding issue comment, use gh issue comment NUMBER --body \"text\" --repo OWNER/REPO. | |
| - When viewing PR details, use gh pr view NUMBER --repo OWNER/REPO. | |
| - When filtering with jq, use gh api repos/\${owner}/\${repo}/pulls/\${prNumber}/comments --paginate --jq 'reverse | .[0:5]'. | |
| Playwright MCP usage (browser automation via mcp__playwright__* tools). | |
| - When you develop frontend web applications (HTML, CSS, JavaScript, React, Vue, Angular, etc.), use Playwright MCP tools to test the UI in a real browser. | |
| - When WebFetch tool fails to retrieve expected content (e.g., returns empty content, JavaScript-rendered pages, or login-protected pages), use Playwright MCP tools (browser_navigate, browser_snapshot) as a fallback for web browsing. | |
| - When you need to interact with dynamic web pages that require JavaScript execution, use Playwright MCP tools. | |
| - When you need to visually verify how a web page looks or take screenshots, use brows*************nshot from Playwright MCP. | |
| - When you need to fill forms, click buttons, or perform user interactions on web pages, use Playwright MCP tools (browser_click, browser_type, browser_fill_form). | |
| - When you need to test responsive design or different viewport sizes, use browser_resize from Playwright MCP. | |
| - When you finish using the browser, always close it with browser_close to free resources." | jq -c .) | |
| [2025-12-29T13:26:31.463Z] [INFO] | |
| [2025-12-29T13:26:31.463Z] [INFO] 📋 User prompt: | |
| [2025-12-29T13:26:31.464Z] [INFO] ---BEGIN USER PROMPT--- | |
| [2025-12-29T13:26:31.464Z] [INFO] Issue to solve: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24 | |
| Your prepared branch: issue-24-6045c8942678 | |
| Your prepared working directory: /tmp/gh-issue-solver-1767014767488 | |
| Your prepared Pull Request: https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/25 | |
| Your forked repository: konard/Jhon-Crow-text-to-speech-with-chatterbox | |
| Original repository (upstream): Jhon-Crow/text-to-speech-with-chatterbox | |
| GitHub Actions on your fork: https://github.com/konard/Jhon-Crow-text-to-speech-with-chatterbox/actions?query=branch%3Aissue-24-6045c8942678 | |
| Proceed. | |
| [2025-12-29T13:26:31.464Z] [INFO] ---END USER PROMPT--- | |
| [2025-12-29T13:26:31.464Z] [INFO] | |
| [2025-12-29T13:26:31.464Z] [INFO] 📋 System prompt: | |
| [2025-12-29T13:26:31.465Z] [INFO] ---BEGIN SYSTEM PROMPT--- | |
| [2025-12-29T13:26:31.465Z] [INFO] You are an AI issue solver. You prefer to find the root cause of each and every issue. When you talk, you prefer to speak with facts which you have double-checked yourself or cite sources that provide evidence, like quote actual code or give references to documents or pages found on the internet. You are polite and patient, and prefer to assume good intent, trying your best to be helpful. If you are unsure or have assumptions, you prefer to test them yourself or ask questions to clarify requirements. | |
| General guidelines. | |
| - When you execute commands, always save their logs to files for easier reading if the output becomes large. | |
| - When running commands, do not set a timeout yourself — let them run as long as needed (default timeout - 2 minutes is more than enough), and once they finish, review the logs in the file. | |
| - When running sudo commands (especially package installations like apt-get, yum, npm install, etc.), always run them in the background to avoid timeout issues and permission errors when the process needs to be killed. Use the run_in_background parameter or append & to the command. | |
| - When CI is failing or user reports failures, consider adding a detailed investigation protocol to your todo list with these steps: | |
| Step 1: List recent runs with timestamps using: gh run list --repo Jhon-Crow/text-to-speech-with-chatterbox --branch issue-24-6045c8942678 --limit 5 --json databaseId,conclusion,createdAt,headSha | |
| Step 2: Verify runs are after the latest commit by checking timestamps and SHA | |
| Step 3: For each non-passing run, download logs to preserve them: gh run view {run-id} --repo Jhon-Crow/text-to-speech-with-chatterbox --log > ci-logs/{workflow}-{run-id}.log | |
| Step 4: Read each downloaded log file using Read tool to understand the actual failures | |
| Step 5: Report findings with specific errors and line numbers from logs | |
| This detailed investigation is especially helpful when user mentions CI failures, asks to investigate logs, you see non-passing status, or when finalizing a PR. | |
| Note: If user says "failing" but tools show "passing", this might indicate stale data - consider downloading fresh logs and checking timestamps to resolve the discrepancy. | |
| - When a code or log file has more than 1500 lines, read it in chunks of 1500 lines. | |
| - When facing a complex problem, do as much tracing as possible and turn on all verbose modes. | |
| - When you create debug, test, or example/experiment scripts for fixing, always keep them in an examples and/or experiments folders so you can reuse them later. | |
| - When testing your assumptions, use the experiment scripts, and add it to experiments folder. | |
| - When your experiments can show real world use case of the software, add it to examples folder. | |
| - When you face something extremely hard, use divide and conquer — it always helps. | |
| Initial research. | |
| - When you start, make sure you create detailed plan for yourself and follow your todo list step by step, make sure that as many points from these guidelines are added to your todo list to keep track of everything that can help you solve the issue with highest possible quality. | |
| - When user mentions CI failures or asks to investigate logs, consider adding these todos to track the investigation: (1) List recent CI runs with timestamps, (2) Download logs from failed runs to ci-logs/ directory, (3) Analyze error messages and identify root cause, (4) Implement fix, (5) Verify fix resolves the specific errors found in logs. | |
| - When you read issue, read all details and comments thoroughly. | |
| - When you see screenshots or images in issue descriptions, pull request descriptions, comments, or discussions, use WebFetch tool (or fetch tool) to download the image first, then use Read tool to view and analyze it. IMPORTANT: Before reading downloaded images with the Read tool, verify the file is a valid image (not HTML). Use a CLI tool like 'file' command to check the actual file format. Reading corrupted or non-image files (like GitHub's HTML 404 pages saved as .png) can cause "Could not process image" errors and may crash the AI solver process. If the file command shows "HTML" or "text", the download failed and you should retry or skip the image. | |
| - When you need issue details, use gh issue view https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/issues/24. | |
| - When you need related code, use gh search code --owner Jhon-Crow [keywords]. | |
| - When you need repo context, read files in your working directory. | |
| - When you study related work, study the most recent related pull requests. | |
| - When issue is not defined enough, write a comment to ask clarifying questions. | |
| - When accessing GitHub Gists (especially private ones), use gh gist view command instead of direct URL fetching to ensure proper authentication. | |
| - When you are fixing a bug, please make sure you first find the actual root cause, do as many experiments as needed. | |
| - When you are fixing a bug and code does not have enough tracing/logs, add them and make sure they stay in the code, but are switched off by default. | |
| - When you need comments on a pull request, note that GitHub has THREE different comment types with different API endpoints: | |
| 1. PR review comments (inline code comments): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/pulls/25/comments --paginate | |
| 2. PR conversation comments (general discussion): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/issues/25/comments --paginate | |
| 3. PR reviews (approve/request changes): gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/pulls/25/reviews --paginate | |
| IMPORTANT: The command "gh pr view --json comments" ONLY returns conversation comments and misses review comments! | |
| - When you need latest comments on issue, use gh api repos/Jhon-Crow/text-to-speech-with-chatterbox/issues/24/comments --paginate. | |
| Solution development and testing. | |
| - When issue is solvable, implement code with tests. | |
| - When implementing features, search for similar existing implementations in the codebase and use them as examples instead of implementing everything from scratch. | |
| - When coding, each atomic step that can be useful by itself should be commited to the pull request's branch, meaning if work will be interrupted by any reason parts of solution will still be kept intact and safe in pull request. | |
| - When you test: | |
| start from testing of small functions using separate scripts; | |
| write unit tests with mocks for easy and quick start. | |
| - When you test integrations, use existing framework. | |
| - When you test solution draft, include automated checks in pr. | |
| - When issue is unclear, write comment on issue asking questions. | |
| - When you encounter any problems that you unable to solve yourself (any human feedback or help), write a comment to the pull request asking for help. | |
| - When you need human help, use gh pr comment 25 --body "your message" to comment on existing PR. | |
| Preparing pull request. | |
| - When you code, follow contributing guidelines. | |
| - When you commit, write clear message. | |
| - When you need examples of style, use gh pr list --repo Jhon-Crow/text-to-speech-with-chatterbox --state merged --search [keywords]. | |
| - When you open pr, describe solution draft and include tests. | |
| - When there is a package with version and GitHub Actions workflows for automatic release, update the version (or other necessary release trigger) in your pull request to prepare for next release. | |
| - When you update existing pr 25, use gh pr edit to modify title and description. | |
| - When you are about to commit or push code, ALWAYS run local CI checks first if they are available in contributing guidelines (like ruff check, mypy, eslint, etc.) to catch errors before pushing. | |
| - When you finalize the pull request: | |
| follow style from merged prs for code, title, and description, | |
| make sure no uncommitted changes corresponding to the original requirements are left behind, | |
| make sure the default branch is merged to the pull request's branch, | |
| make sure all CI checks passing if they exist before you finish, | |
| check for latest comments on the issue and pull request to ensure no recent feedback was missed, | |
| double-check that all changes in the pull request answer to original requirements of the issue, | |
| make sure no new new bugs are introduced in pull request by carefully reading gh pr diff, | |
| make sure no previously existing features were removed without an explicit request from users via the issue description, issue comments, and/or pull request comments. | |
| - When you finish implementation, use gh pr ready 25. | |
| Workflow and collaboration. | |
| - When you check branch, verify with git branch --show-current. | |
| - When you push, push only to branch issue-24-6045c8942678. | |
| - When you finish, create a pull request from branch issue-24-6045c8942678. (Note: PR 25 already exists, update it instead) | |
| - When you organize workflow, use pull requests instead of direct merges to default branch (main or master). | |
| - When you manage commits, preserve commit history for later analysis. | |
| - When you contribute, keep repository history forward-moving with regular commits, pushes, and reverts if needed. | |
| - When you face conflict that you cannot resolve yourself, ask for help. | |
| - When you collaborate, respect branch protections by working only on issue-24-6045c8942678. | |
| - When you mention result, include pull request url or comment url. | |
| - When you need to create pr, remember pr 25 already exists for this branch. | |
| Self review. | |
| - When you check your solution draft, run all tests locally. | |
| - When you check your solution draft, verify git status shows a clean working tree with no uncommitted changes. | |
| - When you compare with repo style, use gh pr diff [number]. | |
| - When you finalize, confirm code, tests, and description are consistent. | |
| GitHub CLI command patterns. | |
| - IMPORTANT: Always use --paginate flag when fetching lists from GitHub API to ensure all results are returned (GitHub returns max 30 per page by default). | |
| - When listing PR review comments (inline code comments), use gh api repos/OWNER/REPO/pulls/NUMBER/comments --paginate. | |
| - When listing PR conversation comments, use gh api repos/OWNER/REPO/issues/NUMBER/comments --paginate. | |
| - When listing PR reviews, use gh api repos/OWNER/REPO/pulls/NUMBER/reviews --paginate. | |
| - When listing issue comments, use gh api repos/OWNER/REPO/issues/NUMBER/comments --paginate. | |
| - When adding PR comment, use gh pr comment NUMBER --body "text" --repo OWNER/REPO. | |
| - When adding issue comment, use gh issue comment NUMBER --body "text" --repo OWNER/REPO. | |
| - When viewing PR details, use gh pr view NUMBER --repo OWNER/REPO. | |
| - When filtering with jq, use gh api repos/${owner}/${repo}/pulls/${prNumber}/comments --paginate --jq 'reverse | .[0:5]'. | |
| Playwright MCP usage (browser automation via mcp__playwright__* tools). | |
| - When you develop frontend web applications (HTML, CSS, JavaScript, React, Vue, Angular, etc.), use Playwright MCP tools to test the UI in a real browser. | |
| - When WebFetch tool fails to retrieve expected content (e.g., returns empty content, JavaScript-rendered pages, or login-protected pages), use Playwright MCP tools (browser_navigate, browser_snapshot) as a fallback for web browsing. | |
| - When you need to interact with dynamic web pages that require JavaScript execution, use Playwright MCP tools. | |
| - When you need to visually verify how a web page looks or take screenshots, use brows*************nshot from Playwright MCP. | |
| - When you need to fill forms, click buttons, or perform user interactions on web pages, use Playwright MCP tools (browser_click, browser_type, browser_fill_form). | |
| - When you need to test responsive design or different viewport sizes, use browser_resize from Playwright MCP. | |
| - When you finish using the browser, always close it with browser_close to free resources. | |
| [2025-12-29T13:26:31.466Z] [INFO] ---END SYSTEM PROMPT--- | |
| [2025-12-29T13:26:31.466Z] [INFO] | |
| [2025-12-29T13:26:31.467Z] [INFO] 📋 Command details: | |
| [2025-12-29T13:26:31.467Z] [INFO] 📂 Working directory: /tmp/gh-issue-solver-1767014767488 | |
| [2025-12-29T13:26:31.467Z] [INFO] 🌿 Branch: issue-24-6045c8942678 | |
| [2025-12-29T13:26:31.467Z] [INFO] 🤖 Model: Claude OPUS | |
| [2025-12-29T13:26:31.468Z] [INFO] 🍴 Fork: konard/Jhon-Crow-text-to-speech-with-chatterbox | |
| [2025-12-29T13:26:31.468Z] [INFO] | |
| ▶️ Streaming output: | |
| [2025-12-29T13:26:33.852Z] [INFO] { | |
| "type": "system", | |
| "subtype": "init", | |
| "cwd": "/tmp/gh-issue-solver-1767014767488", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "tools": [ | |
| "Task", | |
| "TaskOutput", | |
| "Bash", | |
| "Glob", | |
| "Grep", | |
| "ExitPlanMode", | |
| "Read", | |
| "Edit", | |
| "Write", | |
| "NotebookEdit", | |
| "WebFetch", | |
| "TodoWrite", | |
| "WebSearch", | |
| "KillShell", | |
| "AskUserQuestion", | |
| "Skill", | |
| "EnterPlanMode", | |
| "LSP", | |
| "mcp__playwright__browser_close", | |
| "mcp__playwright__browser_resize", | |
| "mcp__playwright__browser_console_messages", | |
| "mcp__playwright__browser_handle_dialog", | |
| "mcp__playwright__browser_evaluate", | |
| "mcp__playwright__browser_file_upload", | |
| "mcp__playwright__browser_fill_form", | |
| "mcp__playwright__browser_install", | |
| "mcp__playwright__browser_press_key", | |
| "mcp__playwright__browser_type", | |
| "mcp__playwright__browser_navigate", | |
| "mcp__playwright__browser_navigate_back", | |
| "mcp__playwright__browser_network_requests", | |
| "mcp__playwright__browser_run_code", | |
| "mcp__playwright__browser_take_screenshot", | |
| "mcp__playwright__browser_snapshot", | |
| "mcp__playwright__browser_click", | |
| "mcp__playwright__browser_drag", | |
| "mcp__playwright__browser_hover", | |
| "mcp__playwright__browser_select_option", | |
| "mcp__playwright__browser_tabs", | |
| "mcp__playwright__browser_wait_for" | |
| ], | |
| "mcp_servers": [ | |
| { | |
| "name": "playwright", | |
| "status": "connected" | |
| } | |
| ], | |
| "model": "claude-opus-4-5-20251101", | |
| "permissionMode": "bypassPermissions", | |
| "slash_commands": [ | |
| "compact", | |
| "context", | |
| "cost", | |
| "init", | |
| "pr-comments", | |
| "release-notes", | |
| "review", | |
| "security-review" | |
| ], | |
| "apiKeySource": "none", | |
| "claude_code_version": "2.0.76", | |
| "output_style": "default", | |
| "agents": [ | |
| "general-purpose", | |
| "statusline-setup", | |
| "Explore", | |
| "Plan" | |
| ], | |
| "skills": [], | |
| "plugins": [], | |
| "uuid": "44ded7f1-5df1-43c1-a971-30c39bd78a9f" | |
| } | |
| [2025-12-29T13:26:33.853Z] [INFO] 📌 Session ID: ad096264-e8c8-4480-a14c-7222d9a5eceb | |
| [2025-12-29T13:26:33.854Z] [INFO] 📁 Log renamed to: /home/hive/ad096264-e8c8-4480-a14c-7222d9a5eceb.log | |
| [2025-12-29T13:26:37.618Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
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| [2025-12-29T13:27:06.722Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TKeNS8b5hrpCi7r3D7d6nt","type":"tool_result","content":" 1→# Text to Speech with Chatterbox\n 2→\n 3→A desktop application that converts documents (PDF, DOC, DOCX, TXT, MD) to speech using [Chatterbox TTS](https://github.com/resemble-ai/chatterbox) by Resemble AI.\n 4→\n 5→## Features\n 6→\n 7→- **Multiple input formats**: PDF, DOC, DOCX, TXT, and Markdown files\n 8→- **Chatterbox TTS models**:\n 9→ - **Turbo**: Fast, English-only (350M parameters)\n 10→ - **Standard**: English with CFG tuning (500M parameters)\n 11→ - **Multilingual**: 23+ languages (500M parameters)\n 12→- **Voice cloning**: Use a reference audio file to clone voices\n 13→- **Smart text preprocessing**:\n 14→ - Automatic page number removal\n 15→ - Optional footnote handling (ignore or read inline)\n 16→- **GPU acceleration**: NVIDIA CUDA support for faster generation (falls back to CPU for AMD GPUs)\n 17→- **Extensible architecture**: Easy to add new file formats or TTS engines\n 18→\n 19→## Installation\n 20→\n 21→### Download Pre-built Windows Executable (Recommended)\n 22→\n 23→**No Python installation required!**\n 24→\n 25→1. Go to the [Releases page](https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/releases)\n 26→2. Download `tts_chatterbox_windows.zip` from the latest release\n 27→3. Extract the zip file to a folder\n 28→4. Run `tts_chatterbox.exe`\n 29→\n 30→**Requirements for the executable:**\n 31→- Windows 10 or later\n 32→- NVIDIA GPU with CUDA (recommended) or CPU\n 33→- Note: AMD GPUs are not supported for GPU acceleration; the app will automatically use CPU mode\n 34→\n 35→### Install from Source (for developers)\n 36→\n 37→**Requirements:**\n 38→- Python 3.10 or higher\n 39→- NVIDIA GPU with CUDA (recommended) or CPU\n 40→\n 41→```bash\n 42→# Clone the repository\n 43→git clone https://github.com/Jhon-Crow/text-to-speech-with-chatterbox.git\n 44→cd text-to-speech-with-chatterbox\n 45→\n 46→# Install the package\n 47→pip install -e .\n 48→\n 49→# Or install with development dependencies\n 50→pip install -e .[dev]\n 51→\n 52→# For better multilingual support (Russian stress marking, Chinese segmentation):\n 53→pip install -e .[multilingual]\n 54→```\n 55→\n 56→### Build Windows Executable (for developers)\n 57→\n 58→If you want to build the executable yourself:\n 59→\n 60→```bash\n 61→# Install with dev dependencies\n 62→pip install -e .[dev]\n 63→\n 64→# Build the executable\n 65→pyinstaller tts_chatterbox.spec\n 66→\n 67→# The executable will be in dist/tts_chatterbox/\n 68→```\n 69→\n 70→Or simply run `build.bat` on Windows.\n 71→\n 72→> **Note:** Pre-built executables are available on the [Releases page](https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/releases).\n 73→\n 74→## Usage\n 75→\n 76→### GUI Application\n 77→\n 78→Run the application:\n 79→\n 80→```bash\n 81→tts-chatterbox\n 82→```\n 83→\n 84→Or run directly:\n 85→\n 86→```bash\n 87→python -m tts_app.main\n 88→```\n 89→\n 90→### Python API\n 91→\n 92→```python\n 93→from pathlib import Path\n 94→from tts_app.readers.registry import create_default_registry\n 95→from tts_app.preprocessors.pipeline import create_default_pipeline\n 96→from tts_app.preprocessors.base import ProcessingContext\n 97→from tts_app.tts import ChatterboxEngine, TTSConfig\n 98→\n 99→# Read a document\n 100→registry = create_default_registry()\n 101→content = registry.read(Path(\"document.pdf\"))\n 102→\n 103→# Preprocess the text\n 104→pipeline = create_default_pipeline()\n 105→context = ProcessingContext(\n 106→ footnotes=content.footnotes,\n 107→ ignore_footnotes=True, # Set to False to read footnotes inline\n 108→ page_count=content.page_count\n 109→)\n 110→processed_text = pipeline.process(content.text, context)\n 111→\n 112→# Convert to speech\n 113→engine = ChatterboxEngine()\n 114→config = TTSConfig(\n 115→ model_type=\"turbo\", # or \"standard\" or \"multilingual\"\n 116→ language=\"en\",\n 117→ device=\"auto\" # or \"cuda\" or \"cpu\"\n 118→)\n 119→engine.initialize(config)\n 120→\n 121→result = engine.synthesize(processed_text, Path(\"output.wav\"))\n 122→print(f\"Audio saved: {result.audio_path} ({result.duration_seconds:.1f}s)\")\n 123→```\n 124→\n 125→## Architecture\n 126→\n 127→The application is designed with extensibility in mind:\n 128→\n 129→```\n 130→src/tts_app/\n 131→├── readers/ # Document readers (PDF, DOC, DOCX, TXT, MD)\n 132→│ ├── base.py # Abstract DocumentReader class\n 133→│ ├── registry.py # Reader registry for dynamic format support\n 134→│ ├── pdf_reader.py\n 135→│ ├── doc_reader.py\n 136→│ ├── docx_reader.py\n 137→│ ├── text_reader.py\n 138→│ └── markdown_reader.py\n 139→├── preprocessors/ # Text preprocessing pipeline\n 140→│ ├── base.py # Abstract TextPreprocessor class\n 141→│ ├── pipeline.py # Preprocessing pipeline\n 142→│ ├── page_numbers.py\n 143→│ └── footnotes.py\n 144→├── tts/ # TTS engine wrappers\n 145→│ ├── base.py # Abstract TTSEngine class\n 146→│ └── chatterbox.py # Chatterbox TTS implementation\n 147→├── gui/ # GUI application\n 148→│ └── app.py # CustomTkinter application\n 149→└── main.py # Entry point\n 150→```\n 151→\n 152→### Adding a New Document Format\n 153→\n 154→1. Create a new reader class inheriting from `DocumentReader`:\n 155→\n 156→```python\n 157→from tts_app.readers.base import DocumentReader, DocumentContent\n 158→\n 159→class MyFormatReader(DocumentReader):\n 160→ @property\n 161→ def supported_extensions(self) -> list[str]:\n 162→ return [\".myformat\"]\n 163→\n 164→ def read(self, file_path: Path) -> DocumentContent:\n 165→ # Your implementation here\n 166→ return DocumentContent(text=..., footnotes=[])\n 167→```\n 168→\n 169→2. Register it with the registry:\n 170→\n 171→```python\n 172→registry.register(MyFormatReader())\n 173→```\n 174→\n 175→### Adding a New Preprocessor\n 176→\n 177→1. Create a preprocessor inheriting from `TextPreprocessor`:\n 178→\n 179→```python\n 180→from tts_app.preprocessors.base import TextPreprocessor, ProcessingContext\n 181→\n 182→class MyPreprocessor(TextPreprocessor):\n 183→ @property\n 184→ def name(self) -> str:\n 185→ return \"my_preprocessor\"\n 186→\n 187→ def process(self, text: str, context: ProcessingContext) -> str:\n 188→ # Your processing here\n 189→ return modified_text\n 190→```\n 191→\n 192→2. Add it to the pipeline:\n 193→\n 194→```python\n 195→pipeline.add(MyPreprocessor())\n 196→```\n 197→\n 198→## Supported Languages (Multilingual Model)\n 199→\n 200→Arabic (ar), Danish (da), German (de), Greek (el), English (en), Spanish (es), Finnish (fi), French (fr), Hebrew (he), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Malay (ms), Dutch (nl), Norwegian (no), Polish (pl), Portuguese (pt), Russian (ru), Swedish (sv), Swahili (sw), Turkish (tr), Chinese (zh)\n 201→\n 202→### Improving Language Quality\n 203→\n 204→For best quality with Russian and Chinese languages, install the optional multilingual dependencies:\n 205→\n 206→```bash\n 207→pip install -e .[multilingual]\n 208→```\n 209→\n 210→This installs:\n 211→- `russian-text-stresser`: Proper Russian stress marking for natural pronunciation\n 212→- `pkuseg`: Chinese word segmentation for better Chinese synthesis\n 213→\n 214→Without these packages, the app will still work but may have reduced pronunciation quality for these languages.\n 215→\n 216→## Development\n 217→\n 218→### Running Tests\n 219→\n 220→```bash\n 221→pytest tests/ -v\n 222→```\n 223→\n 224→### Running Tests with Coverage\n 225→\n 226→```bash\n 227→pytest tests/ -v --cov=tts_app --cov-report=html\n 228→```\n 229→\n 230→## License\n 231→\n 232→MIT License\n 233→\n 234→## Acknowledgments\n 235→\n 236→- [Chatterbox TTS](https://github.com/resemble-ai/chatterbox) by Resemble AI\n 237→- [CustomTkinter](https://github.com/TomSchimansky/CustomTkinter) for the modern GUI\n 238→- [pdfplumber](https://github.com/jsvine/pdfplumber) for PDF text extraction\n 239→- [olefile](https://github.com/decalage2/olefile) for DOC (legacy Word) support\n 240→- [python-docx](https://github.com/python-openxml/python-docx) for DOCX support\n 241→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":"toolu_01GkrNP2dGGDbFVNSsVJf4YA","session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"e7718adf-b91e-4a83-be63-8e413fa1344a","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1767014767488/README.md","content":"# Text to Speech with Chatterbox\n\nA desktop application that converts documents (PDF, DOC, DOCX, TXT, MD) to speech using [Chatterbox TTS](https://github.com/resemble-ai/chatterbox) by Resemble AI.\n\n## Features\n\n- **Multiple input formats**: PDF, DOC, DOCX, TXT, and Markdown files\n- **Chatterbox TTS models**:\n - **Turbo**: Fast, English-only (350M parameters)\n - **Standard**: English with CFG tuning (500M parameters)\n - **Multilingual**: 23+ languages (500M parameters)\n- **Voice cloning**: Use a reference audio file to clone voices\n- **Smart text preprocessing**:\n - Automatic page number removal\n - Optional footnote handling (ignore or read inline)\n- **GPU acceleration**: NVIDIA CUDA support for faster generation (falls back to CPU for AMD GPUs)\n- **Extensible architecture**: Easy to add new file formats or TTS engines\n\n## Installation\n\n### Download Pre-built Windows Executable (Recommended)\n\n**No Python installation required!**\n\n1. Go to the [Releases page](https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/releases)\n2. Download `tts_chatterbox_windows.zip` from the latest release\n3. Extract the zip file to a folder\n4. Run `tts_chatterbox.exe`\n\n**Requirements for the executable:**\n- Windows 10 or later\n- NVIDIA GPU with CUDA (recommended) or CPU\n- Note: AMD GPUs are not supported for GPU acceleration; the app will automatically use CPU mode\n\n### Install from Source (for developers)\n\n**Requirements:**\n- Python 3.10 or higher\n- NVIDIA GPU with CUDA (recommended) or CPU\n\n```bash\n# Clone the repository\ngit clone https://github.com/Jhon-Crow/text-to-speech-with-chatterbox.git\ncd text-to-speech-with-chatterbox\n\n# Install the package\npip install -e .\n\n# Or install with development dependencies\npip install -e .[dev]\n\n# For better multilingual support (Russian stress marking, Chinese segmentation):\npip install -e .[multilingual]\n```\n\n### Build Windows Executable (for developers)\n\nIf you want to build the executable yourself:\n\n```bash\n# Install with dev dependencies\npip install -e .[dev]\n\n# Build the executable\npyinstaller tts_chatterbox.spec\n\n# The executable will be in dist/tts_chatterbox/\n```\n\nOr simply run `build.bat` on Windows.\n\n> **Note:** Pre-built executables are available on the [Releases page](https://github.com/Jhon-Crow/text-to-speech-with-chatterbox/releases).\n\n## Usage\n\n### GUI Application\n\nRun the application:\n\n```bash\ntts-chatterbox\n```\n\nOr run directly:\n\n```bash\npython -m tts_app.main\n```\n\n### Python API\n\n```python\nfrom pathlib import Path\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.preprocessors.base import ProcessingContext\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\n# Read a document\nregistry = create_default_registry()\ncontent = registry.read(Path(\"document.pdf\"))\n\n# Preprocess the text\npipeline = create_default_pipeline()\ncontext = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=True, # Set to False to read footnotes inline\n page_count=content.page_count\n)\nprocessed_text = pipeline.process(content.text, context)\n\n# Convert to speech\nengine = ChatterboxEngine()\nconfig = TTSConfig(\n model_type=\"turbo\", # or \"standard\" or \"multilingual\"\n language=\"en\",\n device=\"auto\" # or \"cuda\" or \"cpu\"\n)\nengine.initialize(config)\n\nresult = engine.synthesize(processed_text, Path(\"output.wav\"))\nprint(f\"Audio saved: {result.audio_path} ({result.duration_seconds:.1f}s)\")\n```\n\n## Architecture\n\nThe application is designed with extensibility in mind:\n\n```\nsrc/tts_app/\n├── readers/ # Document readers (PDF, DOC, DOCX, TXT, MD)\n│ ├── base.py # Abstract DocumentReader class\n│ ├── registry.py # Reader registry for dynamic format support\n│ ├── pdf_reader.py\n│ ├── doc_reader.py\n│ ├── docx_reader.py\n│ ├── text_reader.py\n│ └── markdown_reader.py\n├── preprocessors/ # Text preprocessing pipeline\n│ ├── base.py # Abstract TextPreprocessor class\n│ ├── pipeline.py # Preprocessing pipeline\n│ ├── page_numbers.py\n│ └── footnotes.py\n├── tts/ # TTS engine wrappers\n│ ├── base.py # Abstract TTSEngine class\n│ └── chatterbox.py # Chatterbox TTS implementation\n├── gui/ # GUI application\n│ └── app.py # CustomTkinter | |
| [2025-12-29T13:27:06.729Z] [INFO] application\n└── main.py # Entry point\n```\n\n### Adding a New Document Format\n\n1. Create a new reader class inheriting from `DocumentReader`:\n\n```python\nfrom tts_app.readers.base import DocumentReader, DocumentContent\n\nclass MyFormatReader(DocumentReader):\n @property\n def supported_extensions(self) -> list[str]:\n return [\".myformat\"]\n\n def read(self, file_path: Path) -> DocumentContent:\n # Your implementation here\n return DocumentContent(text=..., footnotes=[])\n```\n\n2. Register it with the registry:\n\n```python\nregistry.register(MyFormatReader())\n```\n\n### Adding a New Preprocessor\n\n1. Create a preprocessor inheriting from `TextPreprocessor`:\n\n```python\nfrom tts_app.preprocessors.base import TextPreprocessor, ProcessingContext\n\nclass MyPreprocessor(TextPreprocessor):\n @property\n def name(self) -> str:\n return \"my_preprocessor\"\n\n def process(self, text: str, context: ProcessingContext) -> str:\n # Your processing here\n return modified_text\n```\n\n2. Add it to the pipeline:\n\n```python\npipeline.add(MyPreprocessor())\n```\n\n## Supported Languages (Multilingual Model)\n\nArabic (ar), Danish (da), German (de), Greek (el), English (en), Spanish (es), Finnish (fi), French (fr), Hebrew (he), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Malay (ms), Dutch (nl), Norwegian (no), Polish (pl), Portuguese (pt), Russian (ru), Swedish (sv), Swahili (sw), Turkish (tr), Chinese (zh)\n\n### Improving Language Quality\n\nFor best quality with Russian and Chinese languages, install the optional multilingual dependencies:\n\n```bash\npip install -e .[multilingual]\n```\n\nThis installs:\n- `russian-text-stresser`: Proper Russian stress marking for natural pronunciation\n- `pkuseg`: Chinese word segmentation for better Chinese synthesis\n\nWithout these packages, the app will still work but may have reduced pronunciation quality for these languages.\n\n## Development\n\n### Running Tests\n\n```bash\npytest tests/ -v\n```\n\n### Running Tests with Coverage\n\n```bash\npytest tests/ -v --cov=tts_app --cov-report=html\n```\n\n## License\n\nMIT License\n\n## Acknowledgments\n\n- [Chatterbox TTS](https://github.com/resemble-ai/chatterbox) by Resemble AI\n- [CustomTkinter](https://github.com/TomSchimansky/CustomTkinter) for the modern GUI\n- [pdfplumber](https://github.com/jsvine/pdfplumber) for PDF text extraction\n- [olefile](https://github.com/decalage2/olefile) for DOC (legacy Word) support\n- [python-docx](https://github.com/python-openxml/python-docx) for DOCX support\n","numLines":241,"startLine":1,"totalLines":241}}} | |
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| "content": " 1→\"\"\"Main entry point for the Text-to-Speech application.\"\"\"\n 2→\n 3→import logging\n 4→import sys\n 5→import os\n 6→from datetime import datetime\n 7→\n 8→\n 9→def _setup_package_path():\n 10→ \"\"\"Set up the Python path for PyInstaller compatibility.\n 11→\n 12→ When running as a PyInstaller-bundled executable, the package context\n 13→ may not be properly established. This function ensures the src directory\n 14→ is in sys.path so that absolute imports like 'from tts_app.xxx' work correctly.\n 15→\n 16→ For PyInstaller, sys._MEIPASS contains the path to the extracted bundle.\n 17→ For normal execution, we add the parent of the tts_app package to the path.\n 18→ \"\"\"\n 19→ if getattr(sys, 'frozen', False):\n 20→ # Running as PyInstaller bundle\n 21→ base_path = sys._MEIPASS\n 22→ else:\n 23→ # Running from source\n 24→ base_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\n 25→\n 26→ if base_path not in sys.path:\n 27→ sys.path.insert(0, base_path)\n 28→\n 29→\n 30→def _get_log_file_path():\n 31→ \"\"\"Get the path for the log file next to the executable.\n 32→\n 33→ Returns:\n 34→ Path to the log file, or None if not applicable.\n 35→ \"\"\"\n 36→ if getattr(sys, 'frozen', False):\n 37→ # Running as PyInstaller bundle - put log next to exe\n 38→ exe_dir = os.path.dirname(sys.executable)\n 39→ else:\n 40→ # Running from source - put log in current directory\n 41→ exe_dir = os.getcwd()\n 42→\n 43→ return os.path.join(exe_dir, \"tts_chatterbox.log\")\n 44→\n 45→\n 46→# Set up package path before any tts_app imports\n 47→_setup_package_path()\n 48→\n 49→\n 50→def setup_logging():\n 51→ \"\"\"Configure logging for the application with both console and file output.\"\"\"\n 52→ log_file = _get_log_file_path()\n 53→\n 54→ handlers = [\n 55→ logging.StreamHandler(sys.stdout)\n 56→ ]\n 57→\n 58→ # Add file handler for error logging\n 59→ try:\n 60→ file_handler = logging.FileHandler(log_file, encoding='utf-8')\n 61→ file_handler.setLevel(logging.WARNING) # Log warnings and errors to file\n 62→ file_handler.setFormatter(logging.Formatter(\n 63→ \"%(asctime)s - %(name)s - %(levelname)s - %(message)s\\n\"\n 64→ \" File: %(pathname)s:%(lineno)d\\n\"\n 65→ ))\n 66→ handlers.append(file_handler)\n 67→ except (OSError, PermissionError) as e:\n 68→ # If we can't write to log file, continue without it\n 69→ print(f\"Warning: Could not create log file: {e}\")\n 70→\n 71→ logging.basicConfig(\n 72→ level=logging.INFO,\n 73→ format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\",\n 74→ handlers=handlers\n 75→ )\n 76→\n 77→\n 78→def main():\n 79→ \"\"\"Run the TTS application.\"\"\"\n 80→ setup_logging()\n 81→\n 82→ from tts_app.gui.app import run_app\n 83→ run_app()\n 84→\n 85→\n 86→if __name__ == \"__main__\":\n 87→ main()\n 88→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
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| "content": "\"\"\"Main entry point for the Text-to-Speech application.\"\"\"\n\nimport logging\nimport sys\nimport os\nfrom datetime import datetime\n\n\ndef _setup_package_path():\n \"\"\"Set up the Python path for PyInstaller compatibility.\n\n When running as a PyInstaller-bundled executable, the package context\n may not be properly established. This function ensures the src directory\n is in sys.path so that absolute imports like 'from tts_app.xxx' work correctly.\n\n For PyInstaller, sys._MEIPASS contains the path to the extracted bundle.\n For normal execution, we add the parent of the tts_app package to the path.\n \"\"\"\n if getattr(sys, 'frozen', False):\n # Running as PyInstaller bundle\n base_path = sys._MEIPASS\n else:\n # Running from source\n base_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\n\n if base_path not in sys.path:\n sys.path.insert(0, base_path)\n\n\ndef _get_log_file_path():\n \"\"\"Get the path for the log file next to the executable.\n\n Returns:\n Path to the log file, or None if not applicable.\n \"\"\"\n if getattr(sys, 'frozen', False):\n # Running as PyInstaller bundle - put log next to exe\n exe_dir = os.path.dirname(sys.executable)\n else:\n # Running from source - put log in current directory\n exe_dir = os.getcwd()\n\n return os.path.join(exe_dir, \"tts_chatterbox.log\")\n\n\n# Set up package path before any tts_app imports\n_setup_package_path()\n\n\ndef setup_logging():\n \"\"\"Configure logging for the application with both console and file output.\"\"\"\n log_file = _get_log_file_path()\n\n handlers = [\n logging.StreamHandler(sys.stdout)\n ]\n\n # Add file handler for error logging\n try:\n file_handler = logging.FileHandler(log_file, encoding='utf-8')\n file_handler.setLevel(logging.WARNING) # Log warnings and errors to file\n file_handler.setFormatter(logging.Formatter(\n \"%(asctime)s - %(name)s - %(levelname)s - %(message)s\\n\"\n \" File: %(pathname)s:%(lineno)d\\n\"\n ))\n handlers.append(file_handler)\n except (OSError, PermissionError) as e:\n # If we can't write to log file, continue without it\n print(f\"Warning: Could not create log file: {e}\")\n\n logging.basicConfig(\n level=logging.INFO,\n format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\",\n handlers=handlers\n )\n\n\ndef main():\n \"\"\"Run the TTS application.\"\"\"\n setup_logging()\n\n from tts_app.gui.app import run_app\n run_app()\n\n\nif __name__ == \"__main__\":\n main()\n", | |
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| [2025-12-29T13:27:09.781Z] [INFO] { | |
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| "content": " 1→\"\"\"Base TTS engine interface.\"\"\"\n 2→\n 3→from abc import ABC, abstractmethod\n 4→from dataclasses import dataclass, field\n 5→from pathlib import Path\n 6→from typing import Optional, Callable\n 7→\n 8→\n 9→@dataclass\n 10→class TTSConfig:\n 11→ \"\"\"Configuration for TTS generation.\n 12→\n 13→ Attributes:\n 14→ model_type: Which Chatterbox model to use (\"turbo\", \"standard\", \"multilingual\").\n 15→ language: Language code for multilingual model (e.g., \"en\", \"fr\", \"de\").\n 16→ voice_reference: Optional path to a voice reference audio file for cloning.\n 17→ device: Device to use (\"cuda\", \"cpu\", or \"auto\").\n 18→ chunk_size: Maximum characters per TTS chunk (for long texts).\n 19→ hf_token: Optional HuggingFace token for model download.\n 20→ \"\"\"\n 21→ model_type: str = \"turbo\"\n 22→ language: str = \"en\"\n 23→ voice_reference: Optional[Path] = None\n 24→ device: str = \"auto\"\n 25→ chunk_size: int = 500 # Characters per chunk\n 26→ hf_token: Optional[str] = None\n 27→\n 28→\n 29→@dataclass\n 30→class TTSResult:\n 31→ \"\"\"Result of TTS generation.\n 32→\n 33→ Attributes:\n 34→ audio_path: Path to the generated audio file.\n 35→ duration_seconds: Duration of the audio in seconds.\n 36→ sample_rate: Sample rate of the audio.\n 37→ text_processed: The text that was converted to speech.\n 38→ was_cancelled: True if generation was cancelled (partial result).\n 39→ chunks_completed: Number of chunks that were successfully generated.\n 40→ chunks_total: Total number of chunks that were planned.\n 41→ \"\"\"\n 42→ audio_path: Path\n 43→ duration_seconds: float\n 44→ sample_rate: int\n 45→ text_processed: str\n 46→ was_cancelled: bool = False\n 47→ chunks_completed: int = 0\n 48→ chunks_total: int = 0\n 49→\n 50→\n 51→# (current, total, status, estim*****************conds or None)\n 52→ProgressCallback = Callable[[int, int, str, Optional[float]], None]\n 53→CancelCheck = Callable[[], bool] # Returns True if generation should be cancelled\n 54→\n 55→\n 56→class TTSEngine(ABC):\n 57→ \"\"\"Abstract base class for text-to-speech engines.\n 58→\n 59→ This defines the interface for TTS engines. Currently supports\n 60→ Chatterbox TTS, but the architecture allows adding other engines.\n 61→ \"\"\"\n 62→\n 63→ @abstractmethod\n 64→ def initialize(self, config: TTSConfig) -> None:\n 65→ \"\"\"Initialize the TTS engine with configuration.\n 66→\n 67→ Args:\n 68→ config: TTS configuration settings.\n 69→ \"\"\"\n 70→ pass\n 71→\n 72→ @abstractmethod\n 73→ def synthesize(\n 74→ self,\n 75→ text: str,\n 76→ output_path: Path,\n 77→ progress_callback: Optional[ProgressCallback] = None,\n 78→ cancel_check: Optional[CancelCheck] = None\n 79→ ) -> TTSResult:\n 80→ \"\"\"Synthesize speech from text.\n 81→\n 82→ Args:\n 83→ text: The text to convert to speech.\n 84→ output_path: Path where the audio file should be saved.\n 85→ progress_callback: Optional callback for progress updates.\n 86→ cancel_check: Optional callback that returns True if generation should stop.\n 87→ When cancelled, partial audio is saved and result.was_cancelled is True.\n 88→\n 89→ Returns:\n 90→ TTSResult with information about the generated audio.\n 91→ \"\"\"\n 92→ pass\n 93→\n 94→ @abstractmethod\n 95→ def is_initialized(self) -> bool:\n 96→ \"\"\"Check if the engine is initialized and ready.\n 97→\n 98→ Returns:\n 99→ True if the engine is ready for synthesis.\n 100→ \"\"\"\n 101→ pass\n 102→\n 103→ @abstractmethod\n 104→ def get_supported_languages(self) -> list[str]:\n 105→ \"\"\"Get list of supported language codes.\n 106→\n 107→ Returns:\n 108→ List of supported language codes.\n 109→ \"\"\"\n 110→ pass\n 111→\n 112→ @property\n 113→ @abstractmethod\n 114→ def name(self) -> str:\n 115→ \"\"\"Get the engine name.\n 116→\n 117→ Returns:\n 118→ Name of the TTS engine.\n 119→ \"\"\"\n 120→ pass\n 121→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/base.py", | |
| "content": "\"\"\"Base TTS engine interface.\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom dataclasses import dataclass, field\nfrom pathlib import Path\nfrom typing import Optional, Callable\n\n\n@dataclass\nclass TTSConfig:\n \"\"\"Configuration for TTS generation.\n\n Attributes:\n model_type: Which Chatterbox model to use (\"turbo\", \"standard\", \"multilingual\").\n language: Language code for multilingual model (e.g., \"en\", \"fr\", \"de\").\n voice_reference: Optional path to a voice reference audio file for cloning.\n device: Device to use (\"cuda\", \"cpu\", or \"auto\").\n chunk_size: Maximum characters per TTS chunk (for long texts).\n hf_token: Optional HuggingFace token for model download.\n \"\"\"\n model_type: str = \"turbo\"\n language: str = \"en\"\n voice_reference: Optional[Path] = None\n device: str = \"auto\"\n chunk_size: int = 500 # Characters per chunk\n hf_token: Optional[str] = None\n\n\n@dataclass\nclass TTSResult:\n \"\"\"Result of TTS generation.\n\n Attributes:\n audio_path: Path to the generated audio file.\n duration_seconds: Duration of the audio in seconds.\n sample_rate: Sample rate of the audio.\n text_processed: The text that was converted to speech.\n was_cancelled: True if generation was cancelled (partial result).\n chunks_completed: Number of chunks that were successfully generated.\n chunks_total: Total number of chunks that were planned.\n \"\"\"\n audio_path: Path\n duration_seconds: float\n sample_rate: int\n text_processed: str\n was_cancelled: bool = False\n chunks_completed: int = 0\n chunks_total: int = 0\n\n\n# (current, total, status, estim*****************conds or None)\nProgressCallback = Callable[[int, int, str, Optional[float]], None]\nCancelCheck = Callable[[], bool] # Returns True if generation should be cancelled\n\n\nclass TTSEngine(ABC):\n \"\"\"Abstract base class for text-to-speech engines.\n\n This defines the interface for TTS engines. Currently supports\n Chatterbox TTS, but the architecture allows adding other engines.\n \"\"\"\n\n @abstractmethod\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the TTS engine with configuration.\n\n Args:\n config: TTS configuration settings.\n \"\"\"\n pass\n\n @abstractmethod\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n \"\"\"\n pass\n\n @abstractmethod\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized and ready.\n\n Returns:\n True if the engine is ready for synthesis.\n \"\"\"\n pass\n\n @abstractmethod\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\n\n Returns:\n List of supported language codes.\n \"\"\"\n pass\n\n @property\n @abstractmethod\n def name(self) -> str:\n \"\"\"Get the engine name.\n\n Returns:\n Name of the TTS engine.\n \"\"\"\n pass\n", | |
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| [2025-12-29T13:27:09.788Z] [INFO] { | |
| "type": "user", | |
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| "content": " 1→\"\"\"Chatterbox TTS engine implementation.\"\"\"\n 2→\n 3→import logging\n 4→import os\n 5→import time\n 6→from contextlib import contextmanager\n 7→from pathlib import Path\n 8→from typing import Optional\n 9→\n 10→from .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n 11→\n 12→logger = logging.getLogger(__name__)\n 13→\n 14→\n 15→@contextmanager\n 16→def _patch_torch_load_for_cpu(device: str):\n 17→ \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n 18→\n 19→ This is a workaround for the chatterbox multilingual model which doesn't properly\n 20→ handle loading models that were saved on CUDA devices when running on CPU.\n 21→\n 22→ See: https://github.com/resemble-ai/chatterbox/issues/96\n 23→\n 24→ Args:\n 25→ device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n 26→ \"\"\"\n 27→ import torch\n 28→\n 29→ # Only patch if we're loading on a non-CUDA device\n 30→ if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n 31→ original_torch_load = torch.load\n 32→\n 33→ def patched_torch_load(f, map_location=None, **kwargs):\n 34→ # If no map_location specified, default to CPU for safe loading\n 35→ if map_location is None:\n 36→ map_location = \"cpu\"\n 37→ return original_torch_load(f, map_location=map_location, **kwargs)\n 38→\n 39→ torch.load = patched_torch_load\n 40→ try:\n 41→ yield\n 42→ finally:\n 43→ torch.load = original_torch_load\n 44→ else:\n 45→ # No patching needed for CUDA devices\n 46→ yield\n 47→\n 48→\n 49→class HuggingFaceTokenError(RuntimeError):\n 50→ \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n 51→ pass\n 52→\n 53→\n 54→class CUDANotAvailableError(RuntimeError):\n 55→ \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n 56→ pass\n 57→\n 58→\n 59→class ChatterboxEngine(TTSEngine):\n 60→ \"\"\"TTS engine using Resemble AI's Chatterbox models.\n 61→\n 62→ Supports three model variants:\n 63→ - Turbo: Fast, English-only, 350M parameters\n 64→ - Standard: English with CFG tuning, 500M parameters\n 65→ - Multilingual: 23+ languages, 500M parameters\n 66→ \"\"\"\n 67→\n 68→ # Supported languages for the multilingual model\n 69→ MULTI************UAGES = [\n 70→ \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n 71→ \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n 72→ \"sw\", \"tr\", \"zh\"\n 73→ ]\n 74→\n 75→ def __init__(self):\n 76→ \"\"\"Initialize the Chatterbox engine.\"\"\"\n 77→ self._model = None\n 78→ self._config: Optional[TTSConfig] = None\n 79→ self._initialized = False\n 80→\n 81→ @property\n 82→ def name(self) -> str:\n 83→ \"\"\"Get the engine name.\"\"\"\n 84→ return \"chatterbox\"\n 85→\n 86→ def _detect_best_device(self) -> str:\n 87→ \"\"\"Detect the best available device for inference.\n 88→\n 89→ Checks for GPU availability in the following order:\n 90→ 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 91→ 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 92→ 3. Apple MPS (Apple Silicon)\n 93→ 4. CPU fallback\n 94→\n 95→ Returns:\n 96→ Device string (\"cuda\", \"mps\", or \"cpu\").\n 97→ \"\"\"\n 98→ import torch\n 99→\n 100→ # Check for NVIDIA CUDA\n 101→ # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n 102→ # because standard PyTorch Windows builds only support NVIDIA CUDA\n 103→ if torch.cuda.is_available():\n 104→ try:\n 105→ device_name = torch.cuda.get_device_name(0)\n 106→ logger.info(f\"CUDA available: {device_name}\")\n 107→ return \"cuda\"\n 108→ except Exception as e:\n 109→ logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n 110→ # Fall through to CPU\n 111→\n 112→ # Check for MPS (Apple Silicon)\n 113→ if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n 114→ logger.info(\"Apple MPS available\")\n 115→ return \"mps\"\n 116→\n 117→ logger.info(\"No GPU available, using CPU\")\n 118→ return \"cpu\"\n 119→\n 120→ def _validate_device(self, requested_device: str) -> str:\n 121→ \"\"\"Validate the requested device and return a valid device.\n 122→\n 123→ If the requested device is not available, falls back to CPU with a warning.\n 124→\n 125→ Args:\n 126→ requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n 127→\n 128→ Returns:\n 129→ A valid device string that PyTorch can use.\n 130→ \"\"\"\n 131→ import torch\n 132→\n 133→ if requested_device == \"auto\":\n 134→ return self._detect_best_device()\n 135→\n 136→ if requested_device == \"cuda\":\n 137→ if not torch.cuda.is_available():\n 138→ logger.warning(\n 139→ \"GPU (CUDA) was requested but is not available. \"\n 140→ \"This can happen if:\\n\"\n 141→ \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n 142→ \" - PyTorch was not installed with CUDA support\\n\"\n 143→ \" - CUDA drivers are not properly installed\\n\"\n 144→ \"Falling back to CPU mode.\"\n 145→ )\n 146→ return \"cpu\"\n 147→ return \"cuda\"\n 148→\n 149→ if requested_device == \"mps\":\n 150→ if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n 151→ logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n 152→ return \"cpu\"\n 153→ return \"mps\"\n 154→\n 155→ return requested_device # \"cpu\" or unknown\n 156→\n 157→ def initialize(self, config: TTSConfig) -> None:\n 158→ \"\"\"Initialize the Chatterbox TTS model.\n 159→\n 160→ Args:\n 161→ config: TTS configuration settings.\n 162→\n 163→ Raises:\n 164→ RuntimeError: If model loading fails.\n 165→ HuggingFaceTokenError: If HuggingFace token is required but not configured.\n 166→ CUDANotAvailableError: If model requires CUDA but it's not available.\n 167→ \"\"\"\n 168→ self._config = config\n 169→\n 170→ # Validate and determine device (with fallback to CPU if GPU not available)\n 171→ device = self._validate_device(config.device)\n 172→\n 173→ logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n 174→\n 175→ # Set HF_TOKEN environment variable if provided in config\n 176→ # This helps the turbo model which requires token=True by default\n 177→ if hasattr(config, 'hf_token') and config.hf_token:\n 178→ os.environ[\"HF_TOKEN\"] = config.hf_token\n 179→ logger.info(\"HuggingFace token configured from settings\")\n 180→\n 181→ try:\n 182→ if config.model_type == \"turbo\":\n 183→ from chatterbox.tts_turbo import ChatterboxTurboTTS\n 184→ self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n 185→\n 186→ elif config.model_type == \"multilingual\":\n 187→ from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n 188→ # Use patch to handle CUDA-saved models on CPU/MPS devices\n 189→ # See: https://github.com/resemble-ai/chatterbox/issues/96\n 190→ with _patch_torch_load_for_cpu(device):\n 191→ self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n 192→\n 193→ else: # standard\n 194→ from chatterbox.tts import ChatterboxTTS\n 195→ self._model = ChatterboxTTS.from_pretrained(device=device)\n 196→\n 197→ self._initialized = True\n 198→ logger.info(\"Chatterbox model initialized successfully\")\n 199→\n 200→ except Exception as e:\n 201→ error_msg = str(e)\n 202→ logger.error(f\"Failed to initialize Chatterbox: {e}\")\n 203→\n 204→ # Check for HuggingFace token errors\n 205→ if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n 206→ raise HuggingFaceTokenError(\n 207→ \"HuggingFace token is required to download the model.\\n\\n\"\n 208→ \"Please do one of the following:\\n\"\n 209→ \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n 210→ \"2. Set the HF_TOKEN environment variable\\n\"\n 211→ \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n 212→ \"Get your token at: https://huggingface.co/settings/tokens\"\n 213→ ) from e\n 214→\n 215→ # Check for CUDA loading errors on CPU machines or AMD GPU users\n 216→ if (\"torch.cuda.is_available() is False\" in error_msg or\n 217→ \"CUDA device\" in error_msg or\n 218→ \"Torch not compiled with CUDA enabled\" in error_msg):\n 219→ raise CUDANotAvailableError(\n 220→ \"GPU acceleration is not available on this system.\\n\\n\"\n 221→ \"Possible reasons:\\n\"\n 222→ \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n 223→ \"- PyTorch was installed without CUDA support\\n\"\n 224→ \"- NVIDIA drivers are not installed\\n\\n\"\n 225→ \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n 226→ \"The application will work on CPU, though slower.\"\n 227→ ) from e\n 228→\n 229→ raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n 230→\n 231→ def is_initialized(self) -> bool:\n 232→ \"\"\"Check if the engine is initialized.\"\"\"\n 233→ return self._initialized and self._model is not None\n 234→\n 235→ def get_supported_languages(self) -> list[str]:\n 236→ \"\"\"Get list of supported language codes.\"\"\"\n 237→ if self._config and self._config.model_type == \"multilingual\":\n 238→ return self.MULTILINGUAL_LANGUAGES\n 239→ return [\"en\"] # Turbo and standard are English-only\n 240→\n 241→ def synthesize(\n 242→ self,\n 243→ text: str,\n 244→ output_path: Path,\n 245→ progress_callback: Optional[ProgressCallback] = None,\n 246→ cancel_check: Optional[CancelCheck] = None\n 247→ ) -> TTSResult:\n 248→ \"\"\"Synthesize speech from text.\n 249→\n 250→ Args:\n 251→ text: The text to convert to speech.\n 252→ output_path: Path where the audio file should be saved.\n 253→ progress_callback: Optional callback for progress updates.\n 254→ cancel_check: Optional callback that returns True if generation should stop.\n 255→ When cancelled, partial audio is saved and result.was_cancelled is True.\n 256→\n 257→ Returns:\n 258→ TTSResult with information about the generated audio.\n 259→\n 260→ Raises:\n 261→ RuntimeError: If synthesis fails or engine not initialized.\n 262→ \"\"\"\n 263→ if not self.is_initialized():\n 264→ raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n 265→\n 266→ import torch\n 267→ import torchaudio\n 268→\n 269→ # Split text into chunks for long texts\n 270→ chunks = self._split_into_chunks(text, self._config.chunk_size)\n 271→ total_chunks = len(chunks)\n 272→\n 273→ logger.info(f\"Synthesizing {total_chunks} chunks\")\n 274→\n 275→ audio_segments = []\n 276→ sample_rate = self._model.sr\n 277→ was_cancelled = False\n 278→ chunks_completed = 0\n 279→ chunk_times = [] # Track time for each chunk to estimate remaining time\n 280→ start_time = time.time()\n 281→\n 282→ for i, chunk in enumerate(chunks):\n 283→ # Check for cancellation before processing each chunk\n 284→ if cancel_check and cancel_check():\n 285→ logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n 286→ was_cancelled = True\n 287→ break\n 288→\n 289→ # Calculate estimated remaining time based on average chunk time\n 290→ estimated_remaining = None\n 291→ if chunk_times:\n 292→ avg_chunk_time = sum(chunk_times) / len(chunk_times)\n 293→ remaining_chunks = total_chunks - i\n 294→ estimated_remaining = avg_chunk_time * remaining_chunks\n 295→\n 296→ if progress_callback:\n 297→ progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n 298→\n 299→ chunk_start_time = time.time()\n 300→\n 301→ if not chunk.strip():\n 302→ continue\n 303→\n 304→ try:\n 305→ # Generate audio for this chunk\n 306→ wav = self._generate_chunk(chunk)\n 307→ audio_segments.append(wav)\n 308→ chunks_completed += 1\n 309→\n 310→ # Track chunk processing time for estimation\n 311→ chunk_time = time.time() - chunk_start_time\n 312→ chunk_times.append(chunk_time)\n 313→ logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n 314→\n 315→ except Exception as e:\n 316→ logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n 317→ # Continue with other chunks\n 318→ continue\n 319→\n 320→ # Handle case where no audio was generated\n 321→ if not audio_segments:\n 322→ if was_cancelled:\n 323→ raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n 324→ raise RuntimeError(\"No audio was generated\")\n 325→\n 326→ # Concatenate all audio segments\n 327→ if len(audio_segments) == 1:\n 328→ final_audio = audio_segments[0]\n 329→ else:\n 330→ # Add small silence between segments\n 331→ silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n 332→ padded_segments = []\n 333→ for seg in audio_segments:\n 334→ padded_segments.append(seg)\n 335→ padded_segments.append(silence)\n 336→ # Remove last silence\n 337→ padded_segments = padded_segments[:-1]\n 338→ final_audio = torch.cat(padded_segments, dim=1)\n 339→\n 340→ # Save to file\n 341→ output_path = Path(output_path)\n 342→ output_path.parent.mkdir(parents=True, exist_ok=True)\n 343→ torchaudio.save(str(output_path), final_audio, sample_rate)\n 344→\n 345→ # Calculate duration\n 346→ duration = final_audio.shape[1] / sample_rate\n 347→\n 348→ if progress_callback:\n 349→ if was_cancelled:\n 350→ progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n 351→ else:\n 352→ progress_callback(total_chunks, total_chunks, \"Complete\", None)\n 353→\n 354→ return TTSResult(\n 355→ audio_path=output_path,\n 356→ duration_seconds=duration,\n 357→ sample_rate=sample_rate,\n 358→ text_processed=text,\n 359→ was_cancelled=was_cancelled,\n 360→ chunks_completed=chunks_completed,\n 361→ chunks_total=total_chunks\n 362→ )\n 363→\n 364→ def _generate_chunk(self, text: str):\n 365→ \"\"\"Generate audio for a single text chunk.\n 366→\n 367→ Args:\n 368→ text: The text chunk to synthesize.\n 369→\n 370→ Returns:\n 371→ Audio tensor.\n 372→ \"\"\"\n 373→ voice_ref = None\n 374→ if self._config.voice_reference:\n 375→ voice_ref = str(self._config.voice_reference)\n 376→\n 377→ if self._config.model_type == \"multilingual\":\n 378→ # Multilingual model requires language_id\n 379→ wav = self._model.generate(\n 380→ text,\n 381→ audio_prompt_path=voice_ref,\n 382→ language_id=self._config.language\n 383→ )\n 384→ elif voice_ref:\n 385→ # With voice reference\n 386→ wav = self._model.generate(text, audio_prompt_path=voice_ref)\n 387→ else:\n 388→ # Without voice reference\n 389→ wav = self._model.generate(text)\n 390→\n 391→ return wav\n 392→\n 393→ def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n 394→ \"\"\"Split text into chunks at natural boundaries.\n 395→\n 396→ Args:\n 397→ text: The text to split.\n 398→ max_chars: Maximum characters per chunk.\n 399→\n 400→ Returns:\n 401→ List of text chunks.\n 402→ \"\"\"\n 403→ if len(text) <= max_chars:\n 404→ return [text]\n 405→\n 406→ chunks = []\n 407→ current_chunk = \"\"\n 408→\n 409→ # Split by sentences first\n 410→ sentences = self._split_sentences(text)\n 411→\n 412→ for sentence in sentences:\n 413→ if len(current_chunk) + len(sentence) <= max_chars:\n 414→ current_chunk += sentence\n 415→ else:\n 416→ if current_chunk:\n 417→ chunks.append(current_chunk.strip())\n 418→ # If single sentence is too long, split by phrases\n 419→ if len(sentence) > max_chars:\n 420→ phrases = self._split_phrases(sentence, max_chars)\n 421→ chunks.extend(phrases[:-1])\n 422→ current_chunk = phrases[-1] if phrases else \"\"\n 423→ else:\n 424→ current_chunk = sentence\n 425→\n 426→ if current_chunk.strip():\n 427→ chunks.append(current_chunk.strip())\n 428→\n 429→ return chunks\n 430→\n 431→ def _split_sentences(self, text: str) -> list[str]:\n 432→ \"\"\"Split text into sentences.\n 433→\n 434→ Args:\n 435→ text: The text to split.\n 436→\n 437→ Returns:\n 438→ List of sentences.\n 439→ \"\"\"\n 440→ import re\n 441→\n 442→ # Split on sentence-ending punctuation\n 443→ sentences = re.split(r'(?<=[.!?])\\s+', text)\n 444→ return sentences\n 445→\n 446→ def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n 447→ \"\"\"Split a long sentence into smaller phrases.\n 448→\n 449→ Args:\n 450→ text: The text to split.\n 451→ max_chars: Maximum characters per phrase.\n 452→\n 453→ Returns:\n 454→ List of phrases.\n 455→ \"\"\"\n 456→ import re\n 457→\n 458→ # Split on commas, semicolons, and other natural breaks\n 459→ parts = re.split(r'(?<=[,;:])\\s+', text)\n 460→\n 461→ phrases = []\n 462→ current_phrase = \"\"\n 463→\n 464→ for part in parts:\n 465→ if len(current_phrase) + len(part) <= max_chars:\n 466→ current_phrase += \" \" + part if current_phrase else part\n 467→ else:\n 468→ if current_phrase:\n 469→ phrases.append(current_phrase.strip())\n 470→ # If still too long, force split\n 471→ if len(part) > max_chars:\n 472→ words = part.split()\n 473→ current_phrase = \"\"\n 474→ for word in words:\n 475→ if len(current_phrase) + len(word) + 1 <= max_chars:\n 476→ current_phrase += \" \" + word if current_phrase else word\n 477→ else:\n 478→ if current_phrase:\n 479→ phrases.append(current_phrase.strip())\n 480→ current_phrase = word\n 481→ else:\n 482→ current_phrase = part\n 483→\n 484→ if current_phrase.strip():\n 485→ phrases.append(current_phrase.strip())\n 486→\n 487→ return phrases\n 488→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "67f6e1ed-ac22-413d-9dda-bcc5987f911f", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py", | |
| "content": "\"\"\"Chatterbox TTS engine implementation.\"\"\"\n\nimport logging\nimport os\nimport time\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef _patch_torch_load_for_cpu(device: str):\n \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n\n This is a workaround for the chatterbox multilingual model which doesn't properly\n handle loading models that were saved on CUDA devices when running on CPU.\n\n See: https://github.com/resemble-ai/chatterbox/issues/96\n\n Args:\n device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n \"\"\"\n import torch\n\n # Only patch if we're loading on a non-CUDA device\n if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n original_torch_load = torch.load\n\n def patched_torch_load(f, map_location=None, **kwargs):\n # If no map_location specified, default to CPU for safe loading\n if map_location is None:\n map_location = \"cpu\"\n return original_torch_load(f, map_location=map_location, **kwargs)\n\n torch.load = patched_torch_load\n try:\n yield\n finally:\n torch.load = original_torch_load\n else:\n # No patching needed for CUDA devices\n yield\n\n\nclass HuggingFaceTokenError(RuntimeError):\n \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n pass\n\n\nclass CUDANotAvailableError(RuntimeError):\n \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n pass\n\n\nclass ChatterboxEngine(TTSEngine):\n \"\"\"TTS engine using Resemble AI's Chatterbox models.\n\n Supports three model variants:\n - Turbo: Fast, English-only, 350M parameters\n - Standard: English with CFG tuning, 500M parameters\n - Multilingual: 23+ languages, 500M parameters\n \"\"\"\n\n # Supported languages for the multilingual model\n MULTI************UAGES = [\n \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n \"sw\", \"tr\", \"zh\"\n ]\n\n def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n\n @property\n def name(self) -> str:\n \"\"\"Get the engine name.\"\"\"\n return \"chatterbox\"\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n logger.info(f\"CUDA available: {device_name}\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _validate_device(self, requested_device: str) -> str:\n \"\"\"Validate the requested device and return a valid device.\n\n If the requested device is not available, falls back to CPU with a warning.\n\n Args:\n requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n\n Returns:\n A valid device string that PyTorch can use.\n \"\"\"\n import torch\n\n if requested_device == \"auto\":\n return self._detect_best_device()\n\n if requested_device == \"cuda\":\n if not torch.cuda.is_available():\n logger.warning(\n \"GPU (CUDA) was requested but is not available. \"\n \"This can happen if:\\n\"\n \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n \" - PyTorch was not installed with CUDA support\\n\"\n \" - CUDA drivers are not properly installed\\n\"\n \"Falling back to CPU mode.\"\n )\n return \"cpu\"\n return \"cuda\"\n\n if requested_device == \"mps\":\n if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n return \"cpu\"\n return \"mps\"\n\n return requested_device # \"cpu\" or unknown\n\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n\n # Set HF_TOKEN environment variable if provided in config\n # This helps the turbo model which requires token=True by default\n if hasattr(config, 'hf_token') and config.hf_token:\n os.environ[\"HF_TOKEN\"] = config.hf_token\n logger.info(\"HuggingFace token configured from settings\")\n\n try:\n if config.model_type == \"turbo\":\n from chatterbox.tts_turbo import ChatterboxTurboTTS\n self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n\n elif config.model_type == \"multilingual\":\n from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n # Use patch to handle CUDA-saved models on CPU/MPS devices\n # See: https://github.com/resemble-ai/chatterbox/issues/96\n with _patch_torch_load_for_cpu(device):\n self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n\n else: # standard\n from chatterbox.tts import ChatterboxTTS\n self._model = ChatterboxTTS.from_pretrained(device=device)\n\n self._initialized = True\n logger.info(\"Chatterbox model initialized successfully\")\n\n except Exception as e:\n error_msg = str(e)\n logger.error(f\"Failed to initialize Chatterbox: {e}\")\n\n # Check for HuggingFace token errors\n if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n raise HuggingFaceTokenError(\n \"HuggingFace token is required to download the model.\\n\\n\"\n \"Please do one of the following:\\n\"\n \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n \"2. Set the HF_TOKEN environment variable\\n\"\n \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n \"Get your token at: https://huggingface.co/settings/tokens\"\n ) from e\n\n # Check for CUDA loading errors on CPU machines or AMD GPU users\n if (\"torch.cuda.is_available() is False\" in error_msg or\n \"CUDA device\" in error_msg or\n \"Torch not compiled with CUDA enabled\" in error_msg):\n raise CUDANotAvailableError(\n \"GPU acceleration is not available on this system.\\n\\n\"\n \"Possible reasons:\\n\"\n \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n \"- PyTorch was installed without CUDA support\\n\"\n \"- NVIDIA drivers are not installed\\n\\n\"\n \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n \"The application will work on CPU, though slower.\"\n ) from e\n\n raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized.\"\"\"\n return self._initialized and self._model is not None\n\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\"\"\"\n if self._config and self._config.model_type == \"multilingual\":\n return self.MULTILINGUAL_LANGUAGES\n return [\"en\"] # Turbo and standard are English-only\n\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n\n Raises:\n RuntimeError: If synthesis fails or engine not initialized.\n \"\"\"\n if not self.is_initialized():\n raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n\n import torch\n import torchaudio\n\n # Split text into chunks for long texts\n chunks = self._split_into_chunks(text, self._config.chunk_size)\n total_chunks = len(chunks)\n\n logger.info(f\"Synthesizing {total_chunks} chunks\")\n\n audio_segments = []\n sample_rate = self._model.sr\n was_cancelled = False\n chunks_completed = 0\n chunk_times = [] # Track time for each chunk to estimate remaining time\n start_time = time.time()\n\n for i, chunk in enumerate(chunks):\n # Check for cancellation before processing each chunk\n if cancel_check and cancel_check():\n logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n was_cancelled = True\n break\n\n # Calculate estimated remaining time based on average chunk time\n estimated_remaining = None\n if chunk_times:\n avg_chunk_time = sum(chunk_times) / len(chunk_times)\n remaining_chunks = total_chunks - i\n estimated_remaining = avg_chunk_time * remaining_chunks\n\n if progress_callback:\n progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n\n chunk_start_time = time.time()\n\n if not chunk.strip():\n continue\n\n try:\n # Generate audio for this chunk\n wav = self._generate_chunk(chunk)\n audio_segments.append(wav)\n chunks_completed += 1\n\n # Track chunk processing time for estimation\n chunk_time = time.time() - chunk_start_time\n chunk_times.append(chunk_time)\n logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n\n except Exception as e:\n logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n # Continue with other chunks\n continue\n\n # Handle case where no audio was generated\n if not audio_segments:\n if was_cancelled:\n raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n raise RuntimeError(\"No audio was generated\")\n\n # Concatenate all audio segments\n if len(audio_segments) == 1:\n final_audio = audio_segments[0]\n else:\n # Add small silence between segments\n silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n padded_segments = []\n for seg in audio_segments:\n padded_segments.append(seg)\n padded_segments.append(silence)\n # Remove last silence\n padded_segments = padded_segments[:-1]\n final_audio = torch.cat(padded_segments, dim=1)\n\n # Save to file\n output_path = Path(output_path)\n output_path.parent.mkdir(parents=True, exist_ok=True)\n torchaudio.save(str(output_path), final_audio, sample_rate)\n\n # Calculate duration\n duration = final_audio.shape[1] / sample_rate\n\n if progress_callback:\n if was_cancelled:\n progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n else:\n progress_callback(total_chunks, total_chunks, \"Complete\", None)\n\n return TTSResult(\n audio_path=output_path,\n duration_seconds=duration,\n sample_rate=sample_rate,\n text_processed=text,\n was_cancelled=was_cancelled,\n chunks_completed=chunks_completed,\n chunks_total=total_chunks\n )\n\n def _generate_chunk(self, text: str):\n \"\"\"Generate audio for a single text chunk.\n\n Args:\n text: The text chunk to synthesize.\n\n Returns:\n Audio tensor.\n \"\"\"\n voice_ref = None\n if self._config.voice_reference:\n voice_ref = str(self._config.voice_reference)\n\n if self._config.model_type == \"multilingual\":\n # Multilingual model requires language_id\n wav = self._model.generate(\n text,\n audio_prompt_path=voice_ref,\n language_id=self._config.language\n )\n elif voice_ref:\n # With voice reference\n wav = self._model.generate(text, audio_prompt_path=voice_ref)\n else:\n # Without voice reference\n wav = self._model.generate(text)\n\n return wav\n\n def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split text into chunks at natural boundaries.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per chunk.\n\n Returns:\n List of text chunks.\n \"\"\"\n if len(text) <= max_chars:\n return [text]\n\n chunks = []\n current_chunk = \"\"\n\n # Split by sentences first\n sentences = self._split_sentences(text)\n\n for sentence in sentences:\n if len(current_chunk) + len(sentence) <= max_chars:\n current_chunk += sentence\n else:\n if current_chunk:\n chunks.append(current_chunk.strip())\n # If single sentence is too long, split by phrases\n if len(sentence) > max_chars:\n phrases = self._split_phrases(sentence, max_chars)\n chunks.extend(phrases[:-1])\n current_chunk = phrases[-1] if phrases else \"\"\n else:\n current_chunk = sentence\n\n if current_chunk.strip():\n chunks.append(current_chunk.strip())\n\n return chunks\n\n def _split_sentences(self, text: str) -> list[str]:\n \"\"\"Split text into sentences.\n\n Args:\n text: The text to split.\n\n Returns:\n List of sentences.\n \"\"\"\n import re\n\n # Split on sentence-ending punctuation\n sentences = re.split(r'(?<=[.!?])\\s+', text)\n return sentences\n\n def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split a long sentence into smaller phrases.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per phrase.\n\n Returns:\n List of phrases.\n \"\"\"\n import re\n\n # Split on commas, semicolons, and other natural breaks\n parts = re.split(r'(?<=[,;:])\\s+', text)\n\n phrases = []\n current_phrase = \"\"\n\n for part in parts:\n if len(current_phrase) + len(part) <= max_chars:\n current_phrase += \" \" + part if current_phrase else part\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n # If still too long, force split\n if len(part) > max_chars:\n words = part.split()\n current_phrase = \"\"\n for word in words:\n if len(current_phrase) + len(word) + 1 <= max_chars:\n current_phrase += \" \" + word if current_phrase else word\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n current_phrase = word\n else:\n current_phrase = part\n\n if current_phrase.strip():\n phrases.append(current_phrase.strip())\n\n return phrases\n", | |
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| "content": " 1→\"\"\"Language detection utilities for multilingual text processing.\"\"\"\n 2→\n 3→import re\n 4→import logging\n 5→from typing import Optional\n 6→\n 7→logger = logging.getLogger(__name__)\n 8→\n 9→\n 10→# Unicode ranges for common scripts\n 11→SCRIPT_RANGES = {\n 12→ 'cyrillic': (0x0400, 0x04FF), # Russian, Ukrainian, etc.\n 13→ 'latin': (0x0041, 0x007A), # Basic Latin letters\n 14→ 'cjk': (0x4E00, 0x9FFF), # Chinese characters\n 15→ 'hiragana': (0x3040, 0x309F), # Japanese Hiragana\n 16→ 'katakana': (0x30A0, 0x30FF), # Japanese Katakana\n 17→ 'hangul': (0xAC00, 0xD7AF), # Korean\n 18→ 'arabic': (0x0600, 0x06FF), # Arabic\n 19→ 'devanagari': (0x0900, 0x097F), # Hindi/Sanskrit\n 20→ 'greek': (0x0370, 0x03FF), # Greek\n 21→ 'hebrew': (0x0590, 0x05FF), # Hebrew\n 22→}\n 23→\n 24→\n 25→def detect_script(text: str) -> dict[str, int]:\n 26→ \"\"\"Detect which scripts are present in text and their character counts.\n 27→\n 28→ Args:\n 29→ text: The text to analyze.\n 30→\n 31→ Returns:\n 32→ Dictionary mapping script names to character counts.\n 33→ \"\"\"\n 34→ script_counts = {script: 0 for script in SCRIPT_RANGES}\n 35→ script_counts['other'] = 0\n 36→\n 37→ for char in text:\n 38→ code_point = ord(char)\n 39→\n 40→ # Skip whitespace and common punctuation\n 41→ if char.isspace() or char in '.,!?;:\\'\"()-[]{}':\n 42→ continue\n 43→\n 44→ found = False\n 45→ for script, (start, end) in SCRIPT_RANGES.items():\n 46→ if start <= code_point <= end:\n 47→ script_counts[script] += 1\n 48→ found = True\n 49→ break\n 50→\n 51→ if not found:\n 52→ script_counts['other'] += 1\n 53→\n 54→ return script_counts\n 55→\n 56→\n 57→def detect_primary_language(text: str) -> str:\n 58→ \"\"\"Detect the primary language of text based on script analysis.\n 59→\n 60→ This is a simple heuristic-based detector that works by analyzing\n 61→ the scripts used in the text. For more accurate detection, consider\n 62→ using a proper language detection library.\n 63→\n 64→ Args:\n 65→ text: The text to analyze.\n 66→\n 67→ Returns:\n 68→ Language code (e.g., \"en\", \"ru\", \"zh\", \"ja\", \"ko\", \"ar\", \"hi\").\n 69→ Defaults to \"en\" if detection fails.\n 70→ \"\"\"\n 71→ script_counts = detect_script(text)\n 72→\n 73→ # Remove zero counts and 'other'\n 74→ active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n 75→\n 76→ if not active_scripts:\n 77→ logger.debug(\"No script detected, defaulting to English\")\n 78→ return \"en\"\n 79→\n 80→ # Find the dominant script\n 81→ dominant_script = max(active_scripts, key=active_scripts.get)\n 82→ total_chars = sum(active_scripts.values())\n 83→ dominant_percentage = active_scripts[dominant_script] / total_chars * 100\n 84→\n 85→ logger.debug(f\"Script analysis: {active_scripts}\")\n 86→ logger.debug(f\"Dominant script: {dominant_script} ({dominant_percentage:.1f}%)\")\n 87→\n 88→ # Map scripts to language codes\n 89→ script_to_lang = {\n 90→ 'cyrillic': 'ru',\n 91→ 'latin': 'en', # Default for Latin script\n 92→ 'cjk': 'zh',\n 93→ 'hiragana': 'ja',\n 94→ 'katakana': 'ja',\n 95→ 'hangul': 'ko',\n 96→ 'arabic': 'ar',\n 97→ 'devanagari': 'hi',\n 98→ 'greek': 'el',\n 99→ 'hebrew': 'he',\n 100→ }\n 101→\n 102→ detected_lang = script_to_lang.get(dominant_script, 'en')\n 103→ logger.info(f\"Detected primary language: {detected_lang} (from {dominant_script} script)\")\n 104→\n 105→ return detected_lang\n 106→\n 107→\n 108→def is_mixed_language_text(text: str, threshold: float = 0.1) -> bool:\n 109→ \"\"\"Check if text contains significant portions of multiple scripts.\n 110→\n 111→ Args:\n 112→ text: The text to analyze.\n 113→ threshold: Minimum percentage (0-1) of non-dominant script to be considered mixed.\n 114→\n 115→ Returns:\n 116→ True if text contains significant portions of multiple scripts.\n 117→ \"\"\"\n 118→ script_counts = detect_script(text)\n 119→\n 120→ # Remove zero counts and 'other'\n 121→ active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n 122→\n 123→ if len(active_scripts) <= 1:\n 124→ return False\n 125→\n 126→ total_chars = sum(active_scripts.values())\n 127→ if total_chars == 0:\n 128→ return False\n 129→\n 130→ # Sort by count (descending)\n 131→ sorted_scripts = sorted(active_scripts.items(), key=lambda x: x[1], reverse=True)\n 132→\n 133→ # Check if second-most-common script exceeds threshold\n 134→ if len(sorted_scripts) >= 2:\n 135→ second_percentage = sorted_scripts[1][1] / total_chars\n 136→ return second_percentage >= threshold\n 137→\n 138→ return False\n 139→\n 140→\n 141→def get_language_name(code: str) -> str:\n 142→ \"\"\"Get the human-readable name for a language code.\n 143→\n 144→ Args:\n 145→ code: ISO 639-1 language code (e.g., \"en\", \"ru\").\n 146→\n 147→ Returns:\n 148→ Human-readable language name.\n 149→ \"\"\"\n 150→ names = {\n 151→ \"ar\": \"Arabic\",\n 152→ \"da\": \"Danish\",\n 153→ \"de\": \"German\",\n 154→ \"el\": \"Greek\",\n 155→ \"en\": \"English\",\n 156→ \"es\": \"Spanish\",\n 157→ \"fi\": \"Finnish\",\n 158→ \"fr\": \"French\",\n 159→ \"he\": \"Hebrew\",\n 160→ \"hi\": \"Hindi\",\n 161→ \"it\": \"Italian\",\n 162→ \"ja\": \"Japanese\",\n 163→ \"ko\": \"Korean\",\n 164→ \"ms\": \"Malay\",\n 165→ \"nl\": \"Dutch\",\n 166→ \"no\": \"Norwegian\",\n 167→ \"pl\": \"Polish\",\n 168→ \"pt\": \"Portuguese\",\n 169→ \"ru\": \"Russian\",\n 170→ \"sv\": \"Swedish\",\n 171→ \"sw\": \"Swahili\",\n 172→ \"tr\": \"Turkish\",\n 173→ \"zh\": \"Chinese\",\n 174→ }\n 175→ return names.get(code, code.upper())\n 176→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "content": "\"\"\"Language detection utilities for multilingual text processing.\"\"\"\n\nimport re\nimport logging\nfrom typing import Optional\n\nlogger = logging.getLogger(__name__)\n\n\n# Unicode ranges for common scripts\nSCRIPT_RANGES = {\n 'cyrillic': (0x0400, 0x04FF), # Russian, Ukrainian, etc.\n 'latin': (0x0041, 0x007A), # Basic Latin letters\n 'cjk': (0x4E00, 0x9FFF), # Chinese characters\n 'hiragana': (0x3040, 0x309F), # Japanese Hiragana\n 'katakana': (0x30A0, 0x30FF), # Japanese Katakana\n 'hangul': (0xAC00, 0xD7AF), # Korean\n 'arabic': (0x0600, 0x06FF), # Arabic\n 'devanagari': (0x0900, 0x097F), # Hindi/Sanskrit\n 'greek': (0x0370, 0x03FF), # Greek\n 'hebrew': (0x0590, 0x05FF), # Hebrew\n}\n\n\ndef detect_script(text: str) -> dict[str, int]:\n \"\"\"Detect which scripts are present in text and their character counts.\n\n Args:\n text: The text to analyze.\n\n Returns:\n Dictionary mapping script names to character counts.\n \"\"\"\n script_counts = {script: 0 for script in SCRIPT_RANGES}\n script_counts['other'] = 0\n\n for char in text:\n code_point = ord(char)\n\n # Skip whitespace and common punctuation\n if char.isspace() or char in '.,!?;:\\'\"()-[]{}':\n continue\n\n found = False\n for script, (start, end) in SCRIPT_RANGES.items():\n if start <= code_point <= end:\n script_counts[script] += 1\n found = True\n break\n\n if not found:\n script_counts['other'] += 1\n\n return script_counts\n\n\ndef detect_primary_language(text: str) -> str:\n \"\"\"Detect the primary language of text based on script analysis.\n\n This is a simple heuristic-based detector that works by analyzing\n the scripts used in the text. For more accurate detection, consider\n using a proper language detection library.\n\n Args:\n text: The text to analyze.\n\n Returns:\n Language code (e.g., \"en\", \"ru\", \"zh\", \"ja\", \"ko\", \"ar\", \"hi\").\n Defaults to \"en\" if detection fails.\n \"\"\"\n script_counts = detect_script(text)\n\n # Remove zero counts and 'other'\n active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n\n if not active_scripts:\n logger.debug(\"No script detected, defaulting to English\")\n return \"en\"\n\n # Find the dominant script\n dominant_script = max(active_scripts, key=active_scripts.get)\n total_chars = sum(active_scripts.values())\n dominant_percentage = active_scripts[dominant_script] / total_chars * 100\n\n logger.debug(f\"Script analysis: {active_scripts}\")\n logger.debug(f\"Dominant script: {dominant_script} ({dominant_percentage:.1f}%)\")\n\n # Map scripts to language codes\n script_to_lang = {\n 'cyrillic': 'ru',\n 'latin': 'en', # Default for Latin script\n 'cjk': 'zh',\n 'hiragana': 'ja',\n 'katakana': 'ja',\n 'hangul': 'ko',\n 'arabic': 'ar',\n 'devanagari': 'hi',\n 'greek': 'el',\n 'hebrew': 'he',\n }\n\n detected_lang = script_to_lang.get(dominant_script, 'en')\n logger.info(f\"Detected primary language: {detected_lang} (from {dominant_script} script)\")\n\n return detected_lang\n\n\ndef is_mixed_language_text(text: str, threshold: float = 0.1) -> bool:\n \"\"\"Check if text contains significant portions of multiple scripts.\n\n Args:\n text: The text to analyze.\n threshold: Minimum percentage (0-1) of non-dominant script to be considered mixed.\n\n Returns:\n True if text contains significant portions of multiple scripts.\n \"\"\"\n script_counts = detect_script(text)\n\n # Remove zero counts and 'other'\n active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n\n if len(active_scripts) <= 1:\n return False\n\n total_chars = sum(active_scripts.values())\n if total_chars == 0:\n return False\n\n # Sort by count (descending)\n sorted_scripts = sorted(active_scripts.items(), key=lambda x: x[1], reverse=True)\n\n # Check if second-most-common script exceeds threshold\n if len(sorted_scripts) >= 2:\n second_percentage = sorted_scripts[1][1] / total_chars\n return second_percentage >= threshold\n\n return False\n\n\ndef get_language_name(code: str) -> str:\n \"\"\"Get the human-readable name for a language code.\n\n Args:\n code: ISO 639-1 language code (e.g., \"en\", \"ru\").\n\n Returns:\n Human-readable language name.\n \"\"\"\n names = {\n \"ar\": \"Arabic\",\n \"da\": \"Danish\",\n \"de\": \"German\",\n \"el\": \"Greek\",\n \"en\": \"English\",\n \"es\": \"Spanish\",\n \"fi\": \"Finnish\",\n \"fr\": \"French\",\n \"he\": \"Hebrew\",\n \"hi\": \"Hindi\",\n \"it\": \"Italian\",\n \"ja\": \"Japanese\",\n \"ko\": \"Korean\",\n \"ms\": \"Malay\",\n \"nl\": \"Dutch\",\n \"no\": \"Norwegian\",\n \"pl\": \"Polish\",\n \"pt\": \"Portuguese\",\n \"ru\": \"Russian\",\n \"sv\": \"Swedish\",\n \"sw\": \"Swahili\",\n \"tr\": \"Turkish\",\n \"zh\": \"Chinese\",\n }\n return names.get(code, code.upper())\n", | |
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| "content": " 1→\"\"\"Main GUI application using CustomTkinter.\"\"\"\n 2→\n 3→import logging\n 4→import threading\n 5→import traceback\n 6→from pathlib import Path\n 7→from typing import Optional\n 8→\n 9→import customtkinter as ctk\n 10→from CTkMessagebox import CTkMessagebox\n 11→\n 12→from tts_app.readers import ReaderRegistry\n 13→from tts_app.readers.registry import create_default_registry\n 14→from tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\n 15→from tts_app.preprocessors.pipeline import create_default_pipeline\n 16→from tts_app.tts import ChatterboxEngine, TTSConfig\n 17→\n 18→logger = logging.getLogger(__name__)\n 19→\n 20→\n 21→class SuccessDialog(ctk.CTkToplevel):\n 22→ \"\"\"Custom success dialog with Open File Location button.\n 23→\n 24→ This dialog displays a success message and provides buttons to open\n 25→ the file location in the file explorer.\n 26→ \"\"\"\n 27→\n 28→ def __init__(self, parent, title: str, message: str, file_path: Path):\n 29→ \"\"\"Initialize the success dialog.\n 30→\n 31→ Args:\n 32→ parent: Parent window.\n 33→ title: Dialog title.\n 34→ message: Success message.\n 35→ file_path: Path to the generated file.\n 36→ \"\"\"\n 37→ super().__init__(parent)\n 38→\n 39→ self._file_path = file_path\n 40→\n 41→ self.title(title)\n 42→ self.geometry(\"450x200\")\n 43→ self.minsize(400, 180)\n 44→ self.transient(parent)\n 45→ self.grab_set()\n 46→\n 47→ # Main frame with padding\n 48→ main_frame = ctk.CTkFrame(self)\n 49→ main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n 50→\n 51→ # Success icon and title\n 52→ title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 53→ title_frame.pack(fill=\"x\", pady=(0, 10))\n 54→\n 55→ success_label = ctk.CTkLabel(\n 56→ title_frame,\n 57→ text=\"Success\",\n 58→ font=ctk.CTkFont(size=18, weight=\"bold\"),\n 59→ text_color=\"#55AA55\"\n 60→ )\n 61→ success_label.pack(side=\"left\")\n 62→\n 63→ # Message\n 64→ message_label = ctk.CTkLabel(\n 65→ main_frame,\n 66→ text=message,\n 67→ font=ctk.CTkFont(size=12),\n 68→ justify=\"left\"\n 69→ )\n 70→ message_label.pack(fill=\"x\", pady=(0, 15))\n 71→\n 72→ # Button frame\n 73→ button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 74→ button_frame.pack(fill=\"x\")\n 75→\n 76→ # Open File Location button\n 77→ open_location_btn = ctk.CTkButton(\n 78→ button_frame,\n 79→ text=\"Open File Location\",\n 80→ command=self._open_file_location,\n 81→ width=140\n 82→ )\n 83→ open_location_btn.pack(side=\"left\", padx=(0, 10))\n 84→\n 85→ # OK button\n 86→ ok_btn = ctk.CTkButton(\n 87→ button_frame,\n 88→ text=\"OK\",\n 89→ command=self.destroy,\n 90→ width=80\n 91→ )\n 92→ ok_btn.pack(side=\"right\")\n 93→\n 94→ # Center the dialog on parent\n 95→ self.update_idletasks()\n 96→ self._center_on_parent(parent)\n 97→\n 98→ def _center_on_parent(self, parent):\n 99→ \"\"\"Center this dialog on the parent window.\"\"\"\n 100→ parent_x = parent.winfo_x()\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "content": "\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()", | |
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| "type": "tool_result", | |
| "content": " 100→ parent_x = parent.winfo_x()\n 101→ parent_y = parent.winfo_y()\n 102→ parent_w = parent.winfo_width()\n 103→ parent_h = parent.winfo_height()\n 104→\n 105→ dialog_w = self.winfo_width()\n 106→ dialog_h = self.winfo_height()\n 107→\n 108→ x = parent_x + (parent_w - dialog_w) // 2\n 109→ y = parent_y + (parent_h - dialog_h) // 2\n 110→\n 111→ self.geometry(f\"+{x}+{y}\")\n 112→\n 113→ def _open_file_location(self):\n 114→ \"\"\"Open the file's directory in the system file explorer.\"\"\"\n 115→ import platform\n 116→ import subprocess\n 117→\n 118→ folder_path = self._file_path.parent\n 119→\n 120→ try:\n 121→ system = platform.system()\n 122→ if system == \"Windows\":\n 123→ # On Windows, use explorer with /select to highlight the file\n 124→ subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n 125→ elif system == \"Darwin\":\n 126→ # On macOS, use open command with -R to reveal the file\n 127→ subprocess.run([\"open\", \"-R\", str(self._file_path)])\n 128→ else:\n 129→ # On Linux, use xdg-open to open the folder\n 130→ subprocess.run([\"xdg-open\", str(folder_path)])\n 131→ except Exception as e:\n 132→ logger.warning(f\"Failed to open file location: {e}\")\n 133→ # Fall back to showing a message\n 134→ CTkMessagebox(\n 135→ master=self,\n 136→ title=\"Info\",\n 137→ message=f\"File is located at:\\n{folder_path}\",\n 138→ icon=\"info\",\n 139→ width=400\n 140→ )\n 141→\n 142→\n 143→class ErrorDialog(ctk.CTkToplevel):\n 144→ \"\"\"Custom error dialog with copy button for error message.\n 145→\n 146→ This dialog displays an error message and provides a button to copy\n 147→ the full error text to the clipboard.\n 148→ \"\"\"\n 149→\n 150→ def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n 151→ \"\"\"Initialize the error dialog.\n 152→\n 153→ Args:\n 154→ parent: Parent window.\n 155→ title: Dialog title.\n 156→ message: Short error message.\n 157→ full_traceback: Full traceback for copying (optional).\n 158→ \"\"\"\n 159→ super().__init__(parent)\n 160→\n 161→ self.title(title)\n 162→ self.geometry(\"500x300\")\n 163→ self.minsize(400, 200)\n 164→ self.transient(parent)\n 165→ self.grab_set()\n 166→\n 167→ # Store the full error text for copying\n 168→ self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n 169→\n 170→ # Main frame with padding\n 171→ main_frame = ctk.CTkFrame(self)\n 172→ main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n 173→\n 174→ # Error icon and title\n 175→ title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 176→ title_frame.pack(fill=\"x\", pady=(0, 10))\n 177→\n 178→ error_label = ctk.CTkLabel(\n 179→ title_frame,\n 180→ text=\"❌ Error\",\n 181→ font=ctk.CTkFont(size=18, weight=\"bold\"),\n 182→ text_color=\"#FF5555\"\n 183→ )\n 184→ error_label.pack(side=\"left\")\n 185→\n 186→ # Error message in scrollable text\n 187→ text_frame = ctk.CTkFrame(main_frame)\n 188→ text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n 189→\n 190→ self._error_textbox = ctk.CTkTextbox(\n 191→ text_frame,\n 192→ wrap=\"word\",\n 193→ font=ctk.CTkFont(size=12)\n 194→ )\n 195→ self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n 196→ self._error_textbox.insert(\"1.0\", self._error_text)\n 197→ self._error_textbox.configure(state=\"disabled\")\n 198→\n 199→ # Button frame\n 200→ button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 201→ button_frame.pack(fill=\"x\")\n 202→\n 203→ # Copy button\n 204→ copy_btn = ctk.CTkButton(\n 205→ button_frame,\n 206→ text=\"📋 Copy Error\",\n 207→ command=self._copy_to_clipboard,\n 208→ width=120\n 209→ )\n 210→ copy_btn.pack(side=\"left\", padx=(0, 10))\n 211→\n 212→ # OK button\n 213→ ok_btn = ctk.CTkButton(\n 214→ button_frame,\n 215→ text=\"OK\",\n 216→ command=self.destroy,\n 217→ width=80\n 218→ )\n 219→ ok_btn.pack(side=\"right\")\n 220→\n 221→ # Center the dialog on parent\n 222→ self.update_idletasks()\n 223→ self._center_on_parent(parent)\n 224→\n 225→ def _center_on_parent(self, parent):\n 226→ \"\"\"Center this dialog on the parent window.\"\"\"\n 227→ parent_x = parent.winfo_x()\n 228→ parent_y = parent.winfo_y()\n 229→ parent_w = parent.winfo_width()\n 230→ parent_h = parent.winfo_height()\n 231→\n 232→ dialog_w = self.winfo_width()\n 233→ dialog_h = self.winfo_height()\n 234→\n 235→ x = parent_x + (parent_w - dialog_w) // 2\n 236→ y = parent_y + (parent_h - dialog_h) // 2\n 237→\n 238→ self.geometry(f\"+{x}+{y}\")\n 239→\n 240→ def _copy_to_clipboard(self):\n 241→ \"\"\"Copy the error text to clipboard.\"\"\"\n 242→ self.clipboard_clear()\n 243→ self.clipboard_append(self._error_text)\n 244→\n 245→ # Show feedback\n 246→ CTkMessagebox(\n 247→ master=self,\n 248→ title=\"Copied\",\n 249→ message=\"Error text copied to clipboard!\",\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
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| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
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| "uuid": "cfa4998d-7b60-4523-8b20-c1b2c0eebd16", | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "content": " parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",", | |
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| [2025-12-29T13:27:16.463Z] [INFO] { | |
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| "content": " 1→\"\"\"Base text preprocessor interface.\"\"\"\n 2→\n 3→from abc import ABC, abstractmethod\n 4→from dataclasses import dataclass\n 5→from typing import Optional\n 6→\n 7→\n 8→@dataclass\n 9→class ProcessingContext:\n 10→ \"\"\"Context information for text processing.\n 11→\n 12→ Attributes:\n 13→ footnotes: List of footnotes from the document.\n 14→ ignore_footnotes: Whether to remove footnote references.\n 15→ page_count: Number of pages in the document.\n 16→ \"\"\"\n 17→ footnotes: list[str]\n 18→ ignore_footnotes: bool = False\n 19→ page_count: Optional[int] = None\n 20→\n 21→\n 22→class TextPreprocessor(ABC):\n 23→ \"\"\"Abstract base class for text preprocessors.\n 24→\n 25→ Text preprocessors transform text to prepare it for TTS.\n 26→ They can remove page numbers, handle footnotes, normalize\n 27→ whitespace, etc.\n 28→\n 29→ To add a new preprocessor, create a subclass that implements\n 30→ the `process` method.\n 31→ \"\"\"\n 32→\n 33→ @property\n 34→ @abstractmethod\n 35→ def name(self) -> str:\n 36→ \"\"\"Return the preprocessor name for identification.\"\"\"\n 37→ pass\n 38→\n 39→ @abstractmethod\n 40→ def process(self, text: str, context: ProcessingContext) -> str:\n 41→ \"\"\"Process the text and return the result.\n 42→\n 43→ Args:\n 44→ text: The text to process.\n 45→ context: Processing context with additional information.\n 46→\n 47→ Returns:\n 48→ The processed text.\n 49→ \"\"\"\n 50→ pass\n 51→\n 52→ @property\n 53→ def enabled(self) -> bool:\n 54→ \"\"\"Check if this preprocessor is enabled.\n 55→\n 56→ Returns:\n 57→ True by default. Override to add conditional logic.\n 58→ \"\"\"\n 59→ return True\n 60→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "content": "\"\"\"Base text preprocessor interface.\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom dataclasses import dataclass\nfrom typing import Optional\n\n\n@dataclass\nclass ProcessingContext:\n \"\"\"Context information for text processing.\n\n Attributes:\n footnotes: List of footnotes from the document.\n ignore_footnotes: Whether to remove footnote references.\n page_count: Number of pages in the document.\n \"\"\"\n footnotes: list[str]\n ignore_footnotes: bool = False\n page_count: Optional[int] = None\n\n\nclass TextPreprocessor(ABC):\n \"\"\"Abstract base class for text preprocessors.\n\n Text preprocessors transform text to prepare it for TTS.\n They can remove page numbers, handle footnotes, normalize\n whitespace, etc.\n\n To add a new preprocessor, create a subclass that implements\n the `process` method.\n \"\"\"\n\n @property\n @abstractmethod\n def name(self) -> str:\n \"\"\"Return the preprocessor name for identification.\"\"\"\n pass\n\n @abstractmethod\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Process the text and return the result.\n\n Args:\n text: The text to process.\n context: Processing context with additional information.\n\n Returns:\n The processed text.\n \"\"\"\n pass\n\n @property\n def enabled(self) -> bool:\n \"\"\"Check if this preprocessor is enabled.\n\n Returns:\n True by default. Override to add conditional logic.\n \"\"\"\n return True\n", | |
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| "content": " 1→\"\"\"Preprocessing pipeline for chaining multiple preprocessors.\"\"\"\n 2→\n 3→from typing import Optional\n 4→\n 5→from .base import TextPreprocessor, ProcessingContext\n 6→from .page_numbers import PageNumberRemover\n 7→from .footnotes import FootnoteHandler\n 8→from .symbols import SymbolConverter\n 9→\n 10→\n 11→class PreprocessorPipeline:\n 12→ \"\"\"Pipeline for running multiple text preprocessors in sequence.\n 13→\n 14→ This allows chaining preprocessors together for comprehensive\n 15→ text cleaning before TTS conversion.\n 16→\n 17→ Example:\n 18→ >>> pipeline = PreprocessorPipeline()\n 19→ >>> pipeline.add(PageNumberRemover())\n 20→ >>> pipeline.add(FootnoteHandler())\n 21→ >>> cleaned = pipeline.process(text, context)\n 22→ \"\"\"\n 23→\n 24→ def __init__(self):\n 25→ \"\"\"Initialize an empty pipeline.\"\"\"\n 26→ self._preprocessors: list[TextPreprocessor] = []\n 27→\n 28→ def add(self, preprocessor: TextPreprocessor) -> \"PreprocessorPipeline\":\n 29→ \"\"\"Add a preprocessor to the pipeline.\n 30→\n 31→ Args:\n 32→ preprocessor: The preprocessor to add.\n 33→\n 34→ Returns:\n 35→ Self for method chaining.\n 36→ \"\"\"\n 37→ self._preprocessors.append(preprocessor)\n 38→ return self\n 39→\n 40→ def remove(self, name: str) -> bool:\n 41→ \"\"\"Remove a preprocessor by name.\n 42→\n 43→ Args:\n 44→ name: The name of the preprocessor to remove.\n 45→\n 46→ Returns:\n 47→ True if a preprocessor was removed.\n 48→ \"\"\"\n 49→ original_length = len(self._preprocessors)\n 50→ self._preprocessors = [p for p in self._preprocessors if p.name != name]\n 51→ return len(self._preprocessors) < original_length\n 52→\n 53→ def process(self, text: str, context: ProcessingContext) -> str:\n 54→ \"\"\"Run all preprocessors on the text.\n 55→\n 56→ Args:\n 57→ text: The text to process.\n 58→ context: Processing context.\n 59→\n 60→ Returns:\n 61→ The processed text after all preprocessors have run.\n 62→ \"\"\"\n 63→ result = text\n 64→\n 65→ for preprocessor in self._preprocessors:\n 66→ if preprocessor.enabled:\n 67→ result = preprocessor.process(result, context)\n 68→\n 69→ # Final cleanup: normalize whitespace\n 70→ result = self._normalize_whitespace(result)\n 71→\n 72→ return result\n 73→\n 74→ def _normalize_whitespace(self, text: str) -> str:\n 75→ \"\"\"Normalize whitespace in text.\n 76→\n 77→ Args:\n 78→ text: The text to normalize.\n 79→\n 80→ Returns:\n 81→ Text with normalized whitespace.\n 82→ \"\"\"\n 83→ import re\n 84→\n 85→ # Replace multiple spaces with single space\n 86→ result = re.sub(r'[ \\t]+', ' ', text)\n 87→\n 88→ # Replace more than 2 consecutive newlines with just 2\n 89→ result = re.sub(r'\\n{3,}', '\\n\\n', result)\n 90→\n 91→ # Strip leading/trailing whitespace from each line\n 92→ lines = [line.strip() for line in result.split('\\n')]\n 93→ result = '\\n'.join(lines)\n 94→\n 95→ # Strip overall\n 96→ return result.strip()\n 97→\n 98→ @property\n 99→ def preprocessors(self) -> list[str]:\n 100→ \"\"\"Get names of all preprocessors in the pipeline.\n 101→\n 102→ Returns:\n 103→ List of preprocessor names.\n 104→ \"\"\"\n 105→ return [p.name for p in self._preprocessors]\n 106→\n 107→\n 108→def create_default_pipeline() -> PreprocessorPipeline:\n 109→ \"\"\"Create a pipeline with default preprocessors.\n 110→\n 111→ Returns:\n 112→ A pipeline with page number, footnote, and symbol handlers.\n 113→ \"\"\"\n 114→ pipeline = PreprocessorPipeline()\n 115→ pipeline.add(PageNumberRemover())\n 116→ pipeline.add(FootnoteHandler())\n 117→ pipeline.add(SymbolConverter())\n 118→ return pipeline\n 119→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "content": "\"\"\"Preprocessing pipeline for chaining multiple preprocessors.\"\"\"\n\nfrom typing import Optional\n\nfrom .base import TextPreprocessor, ProcessingContext\nfrom .page_numbers import PageNumberRemover\nfrom .footnotes import FootnoteHandler\nfrom .symbols import SymbolConverter\n\n\nclass PreprocessorPipeline:\n \"\"\"Pipeline for running multiple text preprocessors in sequence.\n\n This allows chaining preprocessors together for comprehensive\n text cleaning before TTS conversion.\n\n Example:\n >>> pipeline = PreprocessorPipeline()\n >>> pipeline.add(PageNumberRemover())\n >>> pipeline.add(FootnoteHandler())\n >>> cleaned = pipeline.process(text, context)\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize an empty pipeline.\"\"\"\n self._preprocessors: list[TextPreprocessor] = []\n\n def add(self, preprocessor: TextPreprocessor) -> \"PreprocessorPipeline\":\n \"\"\"Add a preprocessor to the pipeline.\n\n Args:\n preprocessor: The preprocessor to add.\n\n Returns:\n Self for method chaining.\n \"\"\"\n self._preprocessors.append(preprocessor)\n return self\n\n def remove(self, name: str) -> bool:\n \"\"\"Remove a preprocessor by name.\n\n Args:\n name: The name of the preprocessor to remove.\n\n Returns:\n True if a preprocessor was removed.\n \"\"\"\n original_length = len(self._preprocessors)\n self._preprocessors = [p for p in self._preprocessors if p.name != name]\n return len(self._preprocessors) < original_length\n\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Run all preprocessors on the text.\n\n Args:\n text: The text to process.\n context: Processing context.\n\n Returns:\n The processed text after all preprocessors have run.\n \"\"\"\n result = text\n\n for preprocessor in self._preprocessors:\n if preprocessor.enabled:\n result = preprocessor.process(result, context)\n\n # Final cleanup: normalize whitespace\n result = self._normalize_whitespace(result)\n\n return result\n\n def _normalize_whitespace(self, text: str) -> str:\n \"\"\"Normalize whitespace in text.\n\n Args:\n text: The text to normalize.\n\n Returns:\n Text with normalized whitespace.\n \"\"\"\n import re\n\n # Replace multiple spaces with single space\n result = re.sub(r'[ \\t]+', ' ', text)\n\n # Replace more than 2 consecutive newlines with just 2\n result = re.sub(r'\\n{3,}', '\\n\\n', result)\n\n # Strip leading/trailing whitespace from each line\n lines = [line.strip() for line in result.split('\\n')]\n result = '\\n'.join(lines)\n\n # Strip overall\n return result.strip()\n\n @property\n def preprocessors(self) -> list[str]:\n \"\"\"Get names of all preprocessors in the pipeline.\n\n Returns:\n List of preprocessor names.\n \"\"\"\n return [p.name for p in self._preprocessors]\n\n\ndef create_default_pipeline() -> PreprocessorPipeline:\n \"\"\"Create a pipeline with default preprocessors.\n\n Returns:\n A pipeline with page number, footnote, and symbol handlers.\n \"\"\"\n pipeline = PreprocessorPipeline()\n pipeline.add(PageNumberRemover())\n pipeline.add(FootnoteHandler())\n pipeline.add(SymbolConverter())\n return pipeline\n", | |
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| "content": " 1→\"\"\"Base document reader interface.\"\"\"\n 2→\n 3→from abc import ABC, abstractmethod\n 4→from dataclasses import dataclass, field\n 5→from pathlib import Path\n 6→from typing import Optional\n 7→\n 8→\n 9→@dataclass\n 10→class DocumentContent:\n 11→ \"\"\"Represents extracted content from a document.\n 12→\n 13→ Attributes:\n 14→ text: The main text content of the document.\n 15→ footnotes: List of footnotes found in the document.\n 16→ page_count: Number of pages in the document (if applicable).\n 17→ metadata: Additional metadata about the document.\n 18→ \"\"\"\n 19→ text: str\n 20→ footnotes: list[str] = field(default_factory=list)\n 21→ page_count: Optional[int] = None\n 22→ metadata: dict = field(default_factory=dict)\n 23→\n 24→\n 25→class DocumentReader(ABC):\n 26→ \"\"\"Abstract base class for document readers.\n 27→\n 28→ This class defines the interface that all document readers must implement.\n 29→ To add support for a new file format, create a subclass that implements\n 30→ the `read` method and register it with the ReaderRegistry.\n 31→ \"\"\"\n 32→\n 33→ @property\n 34→ @abstractmethod\n 35→ def supported_extensions(self) -> list[str]:\n 36→ \"\"\"Return list of file extensions this reader supports.\n 37→\n 38→ Returns:\n 39→ List of extensions (e.g., ['.pdf', '.PDF']).\n 40→ \"\"\"\n 41→ pass\n 42→\n 43→ @abstractmethod\n 44→ def read(self, file_path: Path) -> DocumentContent:\n 45→ \"\"\"Read and extract content from a document.\n 46→\n 47→ Args:\n 48→ file_path: Path to the document file.\n 49→\n 50→ Returns:\n 51→ DocumentContent with extracted text and metadata.\n 52→\n 53→ Raises:\n 54→ FileNotFoundError: If the file does not exist.\n 55→ ValueError: If the file format is not supported.\n 56→ \"\"\"\n 57→ pass\n 58→\n 59→ def can_read(self, file_path: Path) -> bool:\n 60→ \"\"\"Check if this reader can read the given file.\n 61→\n 62→ Args:\n 63→ file_path: Path to the file to check.\n 64→\n 65→ Returns:\n 66→ True if the file extension is supported.\n 67→ \"\"\"\n 68→ return file_path.suffix.lower() in [ext.lower() for ext in self.supported_extensions]\n 69→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "content": "\"\"\"Base document reader interface.\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom dataclasses import dataclass, field\nfrom pathlib import Path\nfrom typing import Optional\n\n\n@dataclass\nclass DocumentContent:\n \"\"\"Represents extracted content from a document.\n\n Attributes:\n text: The main text content of the document.\n footnotes: List of footnotes found in the document.\n page_count: Number of pages in the document (if applicable).\n metadata: Additional metadata about the document.\n \"\"\"\n text: str\n footnotes: list[str] = field(default_factory=list)\n page_count: Optional[int] = None\n metadata: dict = field(default_factory=dict)\n\n\nclass DocumentReader(ABC):\n \"\"\"Abstract base class for document readers.\n\n This class defines the interface that all document readers must implement.\n To add support for a new file format, create a subclass that implements\n the `read` method and register it with the ReaderRegistry.\n \"\"\"\n\n @property\n @abstractmethod\n def supported_extensions(self) -> list[str]:\n \"\"\"Return list of file extensions this reader supports.\n\n Returns:\n List of extensions (e.g., ['.pdf', '.PDF']).\n \"\"\"\n pass\n\n @abstractmethod\n def read(self, file_path: Path) -> DocumentContent:\n \"\"\"Read and extract content from a document.\n\n Args:\n file_path: Path to the document file.\n\n Returns:\n DocumentContent with extracted text and metadata.\n\n Raises:\n FileNotFoundError: If the file does not exist.\n ValueError: If the file format is not supported.\n \"\"\"\n pass\n\n def can_read(self, file_path: Path) -> bool:\n \"\"\"Check if this reader can read the given file.\n\n Args:\n file_path: Path to the file to check.\n\n Returns:\n True if the file extension is supported.\n \"\"\"\n return file_path.suffix.lower() in [ext.lower() for ext in self.supported_extensions]\n", | |
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| "content": " 1→\"\"\"Registry for document readers.\"\"\"\n 2→\n 3→from pathlib import Path\n 4→from typing import Optional, Type\n 5→\n 6→from .base import DocumentReader, DocumentContent\n 7→\n 8→\n 9→class ReaderRegistry:\n 10→ \"\"\"Registry for managing document readers.\n 11→\n 12→ This registry allows dynamic registration of document readers,\n 13→ making the architecture extensible for new file formats.\n 14→\n 15→ Example:\n 16→ >>> registry = ReaderRegistry()\n 17→ >>> registry.register(PDFReader())\n 18→ >>> content = registry.read(Path(\"document.pdf\"))\n 19→ \"\"\"\n 20→\n 21→ def __init__(self):\n 22→ \"\"\"Initialize an empty registry.\"\"\"\n 23→ self._readers: list[DocumentReader] = []\n 24→\n 25→ def register(self, reader: DocumentReader) -> None:\n 26→ \"\"\"Register a document reader.\n 27→\n 28→ Args:\n 29→ reader: An instance of a DocumentReader subclass.\n 30→ \"\"\"\n 31→ self._readers.append(reader)\n 32→\n 33→ def unregister(self, reader_type: Type[DocumentReader]) -> bool:\n 34→ \"\"\"Unregister a document reader by type.\n 35→\n 36→ Args:\n 37→ reader_type: The class of the reader to remove.\n 38→\n 39→ Returns:\n 40→ True if a reader was removed, False otherwise.\n 41→ \"\"\"\n 42→ original_length = len(self._readers)\n 43→ self._readers = [r for r in self._readers if not isinstance(r, reader_type)]\n 44→ return len(self._readers) < original_length\n 45→\n 46→ def get_reader(self, file_path: Path) -> Optional[DocumentReader]:\n 47→ \"\"\"Get a reader that can handle the given file.\n 48→\n 49→ Args:\n 50→ file_path: Path to the file.\n 51→\n 52→ Returns:\n 53→ A DocumentReader that can read the file, or None if no reader found.\n 54→ \"\"\"\n 55→ for reader in self._readers:\n 56→ if reader.can_read(file_path):\n 57→ return reader\n 58→ return None\n 59→\n 60→ def read(self, file_path: Path) -> DocumentContent:\n 61→ \"\"\"Read a document using the appropriate reader.\n 62→\n 63→ Args:\n 64→ file_path: Path to the document.\n 65→\n 66→ Returns:\n 67→ DocumentContent with extracted text and metadata.\n 68→\n 69→ Raises:\n 70→ ValueError: If no reader can handle the file format.\n 71→ FileNotFoundError: If the file does not exist.\n 72→ \"\"\"\n 73→ path = Path(file_path)\n 74→\n 75→ if not path.exists():\n 76→ raise FileNotFoundError(f\"File not found: {file_path}\")\n 77→\n 78→ reader = self.get_reader(path)\n 79→ if reader is None:\n 80→ supported = self.supported_extensions\n 81→ raise ValueError(\n 82→ f\"Unsupported file format: {path.suffix}. \"\n 83→ f\"Supported formats: {', '.join(supported)}\"\n 84→ )\n 85→\n 86→ return reader.read(path)\n 87→\n 88→ @property\n 89→ def supported_extensions(self) -> list[str]:\n 90→ \"\"\"Get all supported file extensions.\n 91→\n 92→ Returns:\n 93→ List of all supported extensions across all registered readers.\n 94→ \"\"\"\n 95→ extensions = set()\n 96→ for reader in self._readers:\n 97→ extensions.update(reader.supported_extensions)\n 98→ return sorted(extensions)\n 99→\n 100→ def get_file_filter(self) -> str:\n 101→ \"\"\"Get a file dialog filter string for all supported formats.\n 102→\n 103→ Returns:\n 104→ Filter string suitable for file dialogs (e.g., \"*.pdf;*.docx;*.txt\").\n 105→ \"\"\"\n 106→ patterns = [f\"*{ext}\" for ext in self.supported_extensions]\n 107→ return \";\".join(patterns)\n 108→\n 109→\n 110→def create_default_registry() -> ReaderRegistry:\n 111→ \"\"\"Create a registry with all default document readers.\n 112→\n 113→ Returns:\n 114→ A ReaderRegistry with PDF, DOC, DOCX, TXT, MD, and RTF readers registered.\n 115→ \"\"\"\n 116→ from .pdf_reader import PDFReader\n 117→ from .doc_reader import DOCReader\n 118→ from .docx_reader import DOCXReader\n 119→ from .text_reader import TextReader\n 120→ from .markdown_reader import MarkdownReader\n 121→ from .rtf_reader import RTFReader\n 122→\n 123→ registry = ReaderRegistry()\n 124→ registry.register(PDFReader())\n 125→ registry.register(DOCReader())\n 126→ registry.register(DOCXReader())\n 127→ registry.register(TextReader())\n 128→ registry.register(MarkdownReader())\n 129→ registry.register(RTFReader())\n 130→\n 131→ return registry\n 132→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/readers/registry.py", | |
| "content": "\"\"\"Registry for document readers.\"\"\"\n\nfrom pathlib import Path\nfrom typing import Optional, Type\n\nfrom .base import DocumentReader, DocumentContent\n\n\nclass ReaderRegistry:\n \"\"\"Registry for managing document readers.\n\n This registry allows dynamic registration of document readers,\n making the architecture extensible for new file formats.\n\n Example:\n >>> registry = ReaderRegistry()\n >>> registry.register(PDFReader())\n >>> content = registry.read(Path(\"document.pdf\"))\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize an empty registry.\"\"\"\n self._readers: list[DocumentReader] = []\n\n def register(self, reader: DocumentReader) -> None:\n \"\"\"Register a document reader.\n\n Args:\n reader: An instance of a DocumentReader subclass.\n \"\"\"\n self._readers.append(reader)\n\n def unregister(self, reader_type: Type[DocumentReader]) -> bool:\n \"\"\"Unregister a document reader by type.\n\n Args:\n reader_type: The class of the reader to remove.\n\n Returns:\n True if a reader was removed, False otherwise.\n \"\"\"\n original_length = len(self._readers)\n self._readers = [r for r in self._readers if not isinstance(r, reader_type)]\n return len(self._readers) < original_length\n\n def get_reader(self, file_path: Path) -> Optional[DocumentReader]:\n \"\"\"Get a reader that can handle the given file.\n\n Args:\n file_path: Path to the file.\n\n Returns:\n A DocumentReader that can read the file, or None if no reader found.\n \"\"\"\n for reader in self._readers:\n if reader.can_read(file_path):\n return reader\n return None\n\n def read(self, file_path: Path) -> DocumentContent:\n \"\"\"Read a document using the appropriate reader.\n\n Args:\n file_path: Path to the document.\n\n Returns:\n DocumentContent with extracted text and metadata.\n\n Raises:\n ValueError: If no reader can handle the file format.\n FileNotFoundError: If the file does not exist.\n \"\"\"\n path = Path(file_path)\n\n if not path.exists():\n raise FileNotFoundError(f\"File not found: {file_path}\")\n\n reader = self.get_reader(path)\n if reader is None:\n supported = self.supported_extensions\n raise ValueError(\n f\"Unsupported file format: {path.suffix}. \"\n f\"Supported formats: {', '.join(supported)}\"\n )\n\n return reader.read(path)\n\n @property\n def supported_extensions(self) -> list[str]:\n \"\"\"Get all supported file extensions.\n\n Returns:\n List of all supported extensions across all registered readers.\n \"\"\"\n extensions = set()\n for reader in self._readers:\n extensions.update(reader.supported_extensions)\n return sorted(extensions)\n\n def get_file_filter(self) -> str:\n \"\"\"Get a file dialog filter string for all supported formats.\n\n Returns:\n Filter string suitable for file dialogs (e.g., \"*.pdf;*.docx;*.txt\").\n \"\"\"\n patterns = [f\"*{ext}\" for ext in self.supported_extensions]\n return \";\".join(patterns)\n\n\ndef create_default_registry() -> ReaderRegistry:\n \"\"\"Create a registry with all default document readers.\n\n Returns:\n A ReaderRegistry with PDF, DOC, DOCX, TXT, MD, and RTF readers registered.\n \"\"\"\n from .pdf_reader import PDFReader\n from .doc_reader import DOCReader\n from .docx_reader import DOCXReader\n from .text_reader import TextReader\n from .markdown_reader import MarkdownReader\n from .rtf_reader import RTFReader\n\n registry = ReaderRegistry()\n registry.register(PDFReader())\n registry.register(DOCReader())\n registry.register(DOCXReader())\n registry.register(TextReader())\n registry.register(MarkdownReader())\n registry.register(RTFReader())\n\n return registry\n", | |
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| [2025-12-29T13:27:19.720Z] [INFO] { | |
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| "content": " 1→\"\"\"Symbol and number preprocessing for TTS readability.\"\"\"\n 2→\n 3→import re\n 4→from typing import Optional\n 5→\n 6→from .base import TextPreprocessor, ProcessingContext\n 7→\n 8→\n 9→class SymbolConverter(TextPreprocessor):\n 10→ \"\"\"Preprocessor that converts symbols and numbered points to readable text.\n 11→\n 12→ This preprocessor handles:\n 13→ - Mathematical symbols: =, +, -, *, /, <, >, %, etc.\n 14→ - Numbered lists: 1. 2. 3. or 1) 2) 3) patterns\n 15→ - Bullet points: -, *, •\n 16→ - Special characters: @, #, &, etc.\n 17→\n 18→ The goal is to make the text more natural for TTS synthesis by converting\n 19→ symbols that would otherwise be skipped or mispronounced.\n 20→ \"\"\"\n 21→\n 22→ # Symbol to spoken text mapping\n 23→ SYMBOL_MAP = {\n 24→ # Mathematical operators\n 25→ '=': ' equals ',\n 26→ '+': ' plus ',\n 27→ '-': ' minus ', # Will be handled carefully to avoid conflicts with hyphens\n 28→ '*': ' times ', # Will be handled carefully to avoid bullet point conflicts\n 29→ '/': ' divided by ',\n 30→ '%': ' percent',\n 31→ '<': ' less than ',\n 32→ '>': ' greater than ',\n 33→ '<=': ' less than or equal to ',\n 34→ '>=': ' greater than or equal to ',\n 35→ '!=': ' not equal to ',\n 36→ '==': ' equals ',\n 37→ '→': ' arrow ',\n 38→ '←': ' arrow ',\n 39→ '↔': ' bidirectional arrow ',\n 40→\n 41→ # Currency symbols\n 42→ '$': ' dollars ',\n 43→ '€': ' euros ',\n 44→ '£': ' pounds ',\n 45→ '¥': ' yen ',\n 46→ '₽': ' rubles ',\n 47→\n 48→ # Common special characters\n 49→ '@': ' at ',\n 50→ '&': ' and ',\n 51→ '#': ' number ',\n 52→\n 53→ # Bullets and list markers\n 54→ '•': ', ',\n 55→ '◦': ', ',\n 56→ '▪': ', ',\n 57→ '▸': ', ',\n 58→ '►': ', ',\n 59→ }\n 60→\n 61→ # Russian symbol map\n 62→ SYMBOL_MAP_RU = {\n 63→ '=': ' равно ',\n 64→ '+': ' плюс ',\n 65→ '-': ' минус ',\n 66→ '*': ' умножить на ',\n 67→ '/': ' делить на ',\n 68→ '%': ' процент',\n 69→ '<': ' меньше чем ',\n 70→ '>': ' больше чем ',\n 71→ '→': ' стрелка ',\n 72→ '←': ' стрелка ',\n 73→ '$': ' долларов ',\n 74→ '€': ' евро ',\n 75→ '£': ' фунтов ',\n 76→ '¥': ' иен ',\n 77→ '₽': ' рублей ',\n 78→ '@': ' собака ',\n 79→ '&': ' и ',\n 80→ '#': ' номер ',\n 81→ }\n 82→\n 83→ @property\n 84→ def name(self) -> str:\n 85→ \"\"\"Return the preprocessor name.\"\"\"\n 86→ return \"symbol_converter\"\n 87→\n 88→ def process(self, text: str, context: ProcessingContext) -> str:\n 89→ \"\"\"Process symbols and numbered points in text.\n 90→\n 91→ Args:\n 92→ text: The text to process.\n 93→ context: Processing context (unused in this preprocessor).\n 94→\n 95→ Returns:\n 96→ Text with symbols converted to readable words.\n 97→ \"\"\"\n 98→ result = text\n 99→\n 100→ # Convert numbered lists (1. 2. 3. or 1) 2) 3))\n 101→ result = self._convert_numbered_lists(result)\n 102→\n 103→ # Convert mathematical expressions\n 104→ result = self._convert_math_expressions(result)\n 105→\n 106→ # Convert standalone symbols\n 107→ result = self._convert_standalone_symbols(result)\n 108→\n 109→ # Clean up multiple spaces\n 110→ result = re.sub(r' +', ' ', result)\n 111→\n 112→ return result\n 113→\n 114→ def _convert_numbered_lists(self, text: str) -> str:\n 115→ \"\"\"Convert numbered list patterns to speakable text.\n 116→\n 117→ Args:\n 118→ text: The text to process.\n 119→\n 120→ Returns:\n 121→ Text with numbered lists converted.\n 122→ \"\"\"\n 123→ result = text\n 124→\n 125→ # Convert \"1.\" or \"1)\" at start of line or after newline\n 126→ # Pattern: start of line, optional whitespace, number, period or paren\n 127→ def replace_numbered_point(match):\n 128→ leading = match.group(1) or \"\"\n 129→ number = match.group(2)\n 130→ separator = match.group(3)\n 131→ trailing = match.group(4) or \"\"\n 132→\n 133→ # Use \"point\" for period, just the number for parenthesis\n 134→ if separator == '.':\n 135→ return f\"{leading}Point {number}.{trailing}\"\n 136→ else: # )\n 137→ return f\"{leading}{number}.{trailing}\"\n 138→\n 139→ # Match numbered lists at start of line\n 140→ result = re.sub(\n 141→ r'(^|\\n)(\\d{1,3})([.\\)])(\\s*)',\n 142→ replace_numbered_point,\n 143→ result\n 144→ )\n 145→\n 146→ return result\n 147→\n 148→ def _convert_math_expressions(self, text: str) -> str:\n 149→ \"\"\"Convert mathematical expressions to speakable text.\n 150→\n 151→ Args:\n 152→ text: The text to process.\n 153→\n 154→ Returns:\n 155→ Text with math expressions converted.\n 156→ \"\"\"\n 157→ result = text\n 158→\n 159→ # Convert multi-character operators first\n 160→ result = result.replace('>=', ' greater than or equal to ')\n 161→ result = result.replace('<=', ' less than or equal to ')\n 162→ result = result.replace('!=', ' not equal to ')\n 163→ result = result.replace('==', ' equals ')\n 164→\n 165→ # Convert equations like \"x = 5\" or \"a + b = c\"\n 166→ # Match: something = something (with spaces around equals)\n 167→ result = re.sub(\n 168→ r'(\\w+)\\s*=\\s*(\\w+)',\n 169→ r'\\1 equals \\2',\n 170→ result\n 171→ )\n 172→\n 173→ # Convert standalone = signs (not in URLs or paths)\n 174→ # Only convert if surrounded by spaces or at word boundaries\n 175→ result = re.sub(r'(?<=\\s)=(?=\\s)', ' equals ', result)\n 176→\n 177→ # Convert + signs in mathematical context\n 178→ result = re.sub(r'(\\d+)\\s*\\+\\s*(\\d+)', r'\\1 plus \\2', result)\n 179→\n 180→ # Convert percentage patterns like \"50%\" or \"100%\"\n 181→ result = re.sub(r'(\\d+)%', r'\\1 percent', result)\n 182→\n 183→ return result\n 184→\n 185→ def _convert_standalone_symbols(self, text: str) -> str:\n 186→ \"\"\"Convert standalone symbols to speakable text.\n 187→\n 188→ Args:\n 189→ text: The text to process.\n 190→\n 191→ Returns:\n 192→ Text with standalone symbols converted.\n 193→ \"\"\"\n 194→ result = text\n 195→\n 196→ # Convert currency amounts\n 197→ result = re.sub(r'\\$(\\d+(?:\\.\\d{2})?)', r'\\1 dollars', result)\n 198→ result = re.sub(r'€(\\d+(?:\\.\\d{2})?)', r'\\1 euros', result)\n 199→ result = re.sub(r'£(\\d+(?:\\.\\d{2})?)', r'\\1 pounds', result)\n 200→ result = re.sub(r'₽(\\d+(?:\\.\\d{2})?)', r'\\1 rubles', result)\n 201→\n 202→ # Convert bullet points at start of lines\n 203→ result = re.sub(r'(^|\\n)\\s*[•◦▪▸►]\\s*', r'\\1', result)\n 204→\n 205→ # Convert standalone & to \"and\"\n 206→ result = re.sub(r'\\s+&\\s+', ' and ', result)\n 207→\n 208→ # Convert # followed by numbers (like #1, #42)\n 209→ result = re.sub(r'#(\\d+)', r'number \\1', result)\n 210→\n 211→ # Convert arrows\n 212→ result = result.replace('→', ' arrow ')\n 213→ result = result.replace('←', ' arrow ')\n 214→ result = result.replace('->', ' arrow ')\n 215→ result = result.replace('<-', ' arrow ')\n 216→\n 217→ return result\n 218→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "content": "\"\"\"Symbol and number preprocessing for TTS readability.\"\"\"\n\nimport re\nfrom typing import Optional\n\nfrom .base import TextPreprocessor, ProcessingContext\n\n\nclass SymbolConverter(TextPreprocessor):\n \"\"\"Preprocessor that converts symbols and numbered points to readable text.\n\n This preprocessor handles:\n - Mathematical symbols: =, +, -, *, /, <, >, %, etc.\n - Numbered lists: 1. 2. 3. or 1) 2) 3) patterns\n - Bullet points: -, *, •\n - Special characters: @, #, &, etc.\n\n The goal is to make the text more natural for TTS synthesis by converting\n symbols that would otherwise be skipped or mispronounced.\n \"\"\"\n\n # Symbol to spoken text mapping\n SYMBOL_MAP = {\n # Mathematical operators\n '=': ' equals ',\n '+': ' plus ',\n '-': ' minus ', # Will be handled carefully to avoid conflicts with hyphens\n '*': ' times ', # Will be handled carefully to avoid bullet point conflicts\n '/': ' divided by ',\n '%': ' percent',\n '<': ' less than ',\n '>': ' greater than ',\n '<=': ' less than or equal to ',\n '>=': ' greater than or equal to ',\n '!=': ' not equal to ',\n '==': ' equals ',\n '→': ' arrow ',\n '←': ' arrow ',\n '↔': ' bidirectional arrow ',\n\n # Currency symbols\n '$': ' dollars ',\n '€': ' euros ',\n '£': ' pounds ',\n '¥': ' yen ',\n '₽': ' rubles ',\n\n # Common special characters\n '@': ' at ',\n '&': ' and ',\n '#': ' number ',\n\n # Bullets and list markers\n '•': ', ',\n '◦': ', ',\n '▪': ', ',\n '▸': ', ',\n '►': ', ',\n }\n\n # Russian symbol map\n SYMBOL_MAP_RU = {\n '=': ' равно ',\n '+': ' плюс ',\n '-': ' минус ',\n '*': ' умножить на ',\n '/': ' делить на ',\n '%': ' процент',\n '<': ' меньше чем ',\n '>': ' больше чем ',\n '→': ' стрелка ',\n '←': ' стрелка ',\n '$': ' долларов ',\n '€': ' евро ',\n '£': ' фунтов ',\n '¥': ' иен ',\n '₽': ' рублей ',\n '@': ' собака ',\n '&': ' и ',\n '#': ' номер ',\n }\n\n @property\n def name(self) -> str:\n \"\"\"Return the preprocessor name.\"\"\"\n return \"symbol_converter\"\n\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Process symbols and numbered points in text.\n\n Args:\n text: The text to process.\n context: Processing context (unused in this preprocessor).\n\n Returns:\n Text with symbols converted to readable words.\n \"\"\"\n result = text\n\n # Convert numbered lists (1. 2. 3. or 1) 2) 3))\n result = self._convert_numbered_lists(result)\n\n # Convert mathematical expressions\n result = self._convert_math_expressions(result)\n\n # Convert standalone symbols\n result = self._convert_standalone_symbols(result)\n\n # Clean up multiple spaces\n result = re.sub(r' +', ' ', result)\n\n return result\n\n def _convert_numbered_lists(self, text: str) -> str:\n \"\"\"Convert numbered list patterns to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with numbered lists converted.\n \"\"\"\n result = text\n\n # Convert \"1.\" or \"1)\" at start of line or after newline\n # Pattern: start of line, optional whitespace, number, period or paren\n def replace_numbered_point(match):\n leading = match.group(1) or \"\"\n number = match.group(2)\n separator = match.group(3)\n trailing = match.group(4) or \"\"\n\n # Use \"point\" for period, just the number for parenthesis\n if separator == '.':\n return f\"{leading}Point {number}.{trailing}\"\n else: # )\n return f\"{leading}{number}.{trailing}\"\n\n # Match numbered lists at start of line\n result = re.sub(\n r'(^|\\n)(\\d{1,3})([.\\)])(\\s*)',\n replace_numbered_point,\n result\n )\n\n return result\n\n def _convert_math_expressions(self, text: str) -> str:\n \"\"\"Convert mathematical expressions to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with math expressions converted.\n \"\"\"\n result = text\n\n # Convert multi-character operators first\n result = result.replace('>=', ' greater than or equal to ')\n result = result.replace('<=', ' less than or equal to ')\n result = result.replace('!=', ' not equal to ')\n result = result.replace('==', ' equals ')\n\n # Convert equations like \"x = 5\" or \"a + b = c\"\n # Match: something = something (with spaces around equals)\n result = re.sub(\n r'(\\w+)\\s*=\\s*(\\w+)',\n r'\\1 equals \\2',\n result\n )\n\n # Convert standalone = signs (not in URLs or paths)\n # Only convert if surrounded by spaces or at word boundaries\n result = re.sub(r'(?<=\\s)=(?=\\s)', ' equals ', result)\n\n # Convert + signs in mathematical context\n result = re.sub(r'(\\d+)\\s*\\+\\s*(\\d+)', r'\\1 plus \\2', result)\n\n # Convert percentage patterns like \"50%\" or \"100%\"\n result = re.sub(r'(\\d+)%', r'\\1 percent', result)\n\n return result\n\n def _convert_standalone_symbols(self, text: str) -> str:\n \"\"\"Convert standalone symbols to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with standalone symbols converted.\n \"\"\"\n result = text\n\n # Convert currency amounts\n result = re.sub(r'\\$(\\d+(?:\\.\\d{2})?)', r'\\1 dollars', result)\n result = re.sub(r'€(\\d+(?:\\.\\d{2})?)', r'\\1 euros', result)\n result = re.sub(r'£(\\d+(?:\\.\\d{2})?)', r'\\1 pounds', result)\n result = re.sub(r'₽(\\d+(?:\\.\\d{2})?)', r'\\1 rubles', result)\n\n # Convert bullet points at start of lines\n result = re.sub(r'(^|\\n)\\s*[•◦▪▸►]\\s*', r'\\1', result)\n\n # Convert standalone & to \"and\"\n result = re.sub(r'\\s+&\\s+', ' and ', result)\n\n # Convert # followed by numbers (like #1, #42)\n result = re.sub(r'#(\\d+)', r'number \\1', result)\n\n # Convert arrows\n result = result.replace('→', ' arrow ')\n result = result.replace('←', ' arrow ')\n result = result.replace('->', ' arrow ')\n result = result.replace('<-', ' arrow ')\n\n return result\n", | |
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| [2025-12-29T13:27:23.881Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-haiku-4-5-20251001", | |
| "id": "msg_01Qo5VPGGrxkH1862duPcNn3", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_015gLPYU9yF9Rrrt73G3WnJb", | |
| "name": "Read", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/readers/text_reader.py" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 7, | |
| "cache_creation_input_tokens": 5395, | |
| "cache_read_input_tokens": 38288, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 5395, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 4, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "e29b230b-4b00-44f9-a43f-e8ec6ab90866" | |
| } | |
| [2025-12-29T13:27:24.152Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-haiku-4-5-20251001", | |
| "id": "msg_01Qo5VPGGrxkH1862duPcNn3", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_012GJCjahUBQBDJwJLGiqTTm", | |
| "name": "Read", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/readers/pdf_reader.py" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 7, | |
| "cache_creation_input_tokens": 5395, | |
| "cache_read_input_tokens": 38288, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 5395, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 261, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "9ca39cdd-6e24-46f4-8ffa-61fa27e33cc9" | |
| } | |
| [2025-12-29T13:27:24.205Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01E5prh41G9zrxqmV9HG1eUo", | |
| "type": "tool_result", | |
| "content": " 250→ icon=\"check\",\n 251→ width=300\n 252→ )\n 253→\n 254→\n 255→class TTSApplication(ctk.CTk):\n 256→ \"\"\"Main application window for Text-to-Speech conversion.\n 257→\n 258→ This provides a user-friendly interface for:\n 259→ - Selecting input documents (PDF, DOCX, TXT, MD)\n 260→ - Configuring TTS options (model, language, voice reference)\n 261→ - Setting preprocessing options (ignore footnotes)\n 262→ - Converting documents to speech\n 263→ \"\"\"\n 264→\n 265→ def __init__(self):\n 266→ \"\"\"Initialize the application.\"\"\"\n 267→ super().__init__()\n 268→\n 269→ # Configure window\n 270→ self.title(\"Text to Speech with Chatterbox\")\n 271→ self.geometry(\"700x700\")\n 272→ self.minsize(600, 500)\n 273→\n 274→ # Set appearance\n 275→ ctk.set_appearance_mode(\"system\")\n 276→ ctk.set_default_color_theme(\"blue\")\n 277→\n 278→ # Initialize components\n 279→ self._reader_registry: ReaderRegistry = create_default_registry()\n 280→ self._pipeline: Prepr**********eline = create_default_pipeline()\n 281→ self._tts_engine: Optional[ChatterboxEngine] = None\n 282→ self._processing = False\n 283→ self._cancel_requested = False # Flag to signal cancellation\n 284→ self._progress_animation_id = None # Track progress bar animation\n 285→ self._button_animation_id = None # Track button ellipsis animation\n 286→ self._ellipsis_state = 0 # Current ellipsis state (0-3)\n 287→\n 288→ # Variables\n 289→ self._input_file = ctk.StringVar()\n 290→ self._output_file = ctk.StringVar()\n 291→ self._voice_reference = ctk.StringVar()\n 292→ self._model_type = ctk.StringVar(value=\"turbo\")\n 293→ self._language = ctk.StringVar(value=\"en\")\n 294→ self._ignore_footnotes = ctk.BooleanVar(value=True)\n 295→ self._device = ctk.StringVar(value=\"auto\")\n 296→ self._hf_token = ctk.StringVar()\n 297→\n 298→ # Build UI\n 299→ self._create_widgets()\n 300→\n 301→ def _create_widgets(self):\n 302→ \"\"\"Create all UI widgets.\"\"\"\n 303→ # Scrollable main container\n 304→ self._scrollable_frame = ctk.CTkScrollableFrame(self)\n 305→ self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n 306→\n 307→ # Main frame inside scrollable area\n 308→ main_frame = ctk.CTkFrame(self._scrollable_frame)\n 309→ main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n 310→\n 311→ # Title\n 312→ title_label = ctk.CTkLabel(\n 313→ main_frame,\n 314→ text=\"Document to Speech Converter\",\n 315→ font=ctk.CTkFont(size=24, weight=\"bold\")\n 316→ )\n 317→ title_label.pack(pady=(0, 20))\n 318→\n 319→ # Input file section\n 320→ self._create_file_section(\n 321→ main_frame,\n 322→ \"Input Document:\",\n 323→ self._input_file,\n 324→ self._browse_input,\n 325→ self._get_input_filetypes()\n 326→ )\n 327→\n 328→ # Output file section\n 329→ self._create_file_section(\n 330→ main_frame,\n 331→ \"Output Audio File:\",\n 332→ self._output_file,\n 333→ self._browse_output,\n 334→ [(\"WAV files\", \"*.wav\")],\n 335→ save=True\n 336→ )\n 337→\n 338→ # Voice reference section (optional)\n 339→ voice_frame = ctk.CTkFrame(main_frame)\n 340→ voice_frame.pack(fill=\"x\", pady=(10, 0))\n 341→\n 342→ voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n 343→ voice_label.pack(anchor=\"w\")\n 344→\n 345→ voice_input_frame = ctk.CTkFrame(voice_frame)\n 346→ voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n 347→\n 348→ voice_entry = ctk.CTkEntry(\n 349→ voice_input_frame,\n 350→ textvariable=self._voice_reference,\n 351→ placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n 352→ )\n 353→ voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n 354→\n 355→ voice_btn = ctk.CTkButton(\n 356→ voice_input_frame,\n 357→ text=\"Browse\",\n 358→ command=self._browse_voice_reference,\n 359→ width=100\n 360→ )\n 361→ voice_btn.pack(side=\"right\")\n 362→\n 363→ clear_btn = ctk.CTkButton(\n 364→ voice_input_frame,\n 365→ text=\"Clear\",\n 366→ command=lambda: self._voice_reference.set(\"\"),\n 367→ width=60,\n 368→ fg_color=\"gray\"\n 369→ )\n 370→ clear_btn.pack(side=\"right\", padx=(0, 5))\n 371→\n 372→ # Options frame\n 373→ options_frame = ctk.CTkFrame(main_frame)\n 374→ options_frame.pack(fill=\"x\", pady=(20, 0))\n 375→\n 376→ options_label = ctk.CTkLabel(\n 377→ options_frame,\n 378→ text=\"Options\",\n 379→ font=ctk.CTkFont(size=16, weight=\"bold\")\n 380→ )\n 381→ options_label.pack(anchor=\"w\", pady=(0, 10))\n 382→\n 383→ # Model selection\n 384→ model_frame = ctk.CTkFrame(options_frame)\n 385→ model_frame.pack(fill=\"x\", pady=(0, 10))\n 386→\n 387→ ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n 388→\n 389→ for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n 390→ rb = ctk.CTkRadioButton(\n 391→ model_frame,\n 392→ text=label,\n 393→ variable=self._model_type,\n 394→ value=model,\n 395→ command=self._on_model_change\n 396→ )\n 397→ rb.pack(side=\"left\", padx=(20, 0))\n 398→\n 399→ # Language selection (for multilingual model)\n 400→ self._language_frame = ctk.CTkFrame(options_frame)\n 401→ self._language_frame.pack(fill=\"x\", pady=(0, 10))\n 402→\n 403→ ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n 404→\n 405→ languages = [\n 406→ (\"auto\", \"Auto-detect\"),\n 407→ (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n 408→ (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n 409→ (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n 410→ (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n 411→ ]\n 412→\n 413→ self._language_menu = ctk.CTkOptionMenu(\n 414→ self._language_frame,\n 415→ variable=self._language,\n 416→ values=[f\"{code} - {name}\" for code, name in languages],\n 417→ command=self._on_language_select\n 418→ )\n 419→ self._language_menu.pack(side=\"left\", padx=(20, 0))\n 420→ self._language_frame.pack_forget() # Hidden by default\n 421→\n 422→ # Language auto-detect help text\n 423→ self._language_help = ctk.CTkLabel(\n 424→ self._language_frame,\n 425→ text=\"Auto-detect works best for single-language texts\",\n 426→ text_color=\"gray\",\n 427→ font=ctk.CTkFont(size=11)\n 428→ )\n 429→ self._language_help.pack(side=\"left\", padx=(10, 0))\n 430→\n 431→ # Device selection\n 432→ device_frame = ctk.CTkFrame(options_frame)\n 433→ device_frame.pack(fill=\"x\", pady=(0, 10))\n 434→\n 435→ ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n 436→\n 437→ # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n 438→ for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n 439→ rb = ctk.CTkRadioButton(\n 440→ device_frame,\n 441→ text=label,\n 442→ variable=self._device,\n 443→ value=device\n 444→ )\n 445→ rb.pack(side=\"left\", padx=(20, 0))\n 446→\n 447→ # Device help text (more detailed with AMD information)\n 448→ device_help = ctk.CTkLabel(\n 449→ options_frame,\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "ee17c6c5-eae9-46db-a0c2-7536e90fb775", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "content": " icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,", | |
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| "startLine": 250, | |
| "totalLines": 878 | |
| } | |
| } | |
| } | |
| [2025-12-29T13:27:24.220Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_015gLPYU9yF9Rrrt73G3WnJb", | |
| "type": "tool_result", | |
| "content": " 1→\"\"\"Plain text file reader.\"\"\"\n 2→\n 3→from pathlib import Path\n 4→\n 5→from .base import DocumentReader, DocumentContent\n 6→\n 7→\n 8→class TextReader(DocumentReader):\n 9→ \"\"\"Reader for plain text files.\n 10→\n 11→ This reader handles .txt files with various encodings.\n 12→ \"\"\"\n 13→\n 14→ @property\n 15→ def supported_extensions(self) -> list[str]:\n 16→ \"\"\"Return list of supported text extensions.\"\"\"\n 17→ return [\".txt\", \".TXT\"]\n 18→\n 19→ def read(self, file_path: Path) -> DocumentContent:\n 20→ \"\"\"Read and extract content from a text file.\n 21→\n 22→ Args:\n 23→ file_path: Path to the text file.\n 24→\n 25→ Returns:\n 26→ DocumentContent with extracted text.\n 27→\n 28→ Raises:\n 29→ FileNotFoundError: If the file does not exist.\n 30→ ValueError: If the file cannot be decoded.\n 31→ \"\"\"\n 32→ if not file_path.exists():\n 33→ raise FileNotFoundError(f\"Text file not found: {file_path}\")\n 34→\n 35→ # Try different encodings\n 36→ encodings = [\"utf-8\", \"utf-16\", \"latin-1\", \"cp1252\"]\n 37→\n 38→ text = None\n 39→ for encoding in encodings:\n 40→ try:\n 41→ text = file_path.read_text(encoding=encoding)\n 42→ break\n 43→ except UnicodeDecodeError:\n 44→ continue\n 45→\n 46→ if text is None:\n 47→ raise ValueError(f\"Could not decode text file with any known encoding: {file_path}\")\n 48→\n 49→ # Estimate page count (roughly 3000 characters per page)\n 50→ estimated_pages = max(1, len(text) // 3000)\n 51→\n 52→ return DocumentContent(\n 53→ text=text,\n 54→ footnotes=[], # Plain text doesn't have structured footnotes\n 55→ page_count=estimated_pages,\n 56→ metadata={\"source\": str(file_path), \"format\": \"txt\"}\n 57→ )\n 58→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "acde5135-ef2f-45d6-a77c-1c530e43821f", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/readers/text_reader.py", | |
| "content": "\"\"\"Plain text file reader.\"\"\"\n\nfrom pathlib import Path\n\nfrom .base import DocumentReader, DocumentContent\n\n\nclass TextReader(DocumentReader):\n \"\"\"Reader for plain text files.\n\n This reader handles .txt files with various encodings.\n \"\"\"\n\n @property\n def supported_extensions(self) -> list[str]:\n \"\"\"Return list of supported text extensions.\"\"\"\n return [\".txt\", \".TXT\"]\n\n def read(self, file_path: Path) -> DocumentContent:\n \"\"\"Read and extract content from a text file.\n\n Args:\n file_path: Path to the text file.\n\n Returns:\n DocumentContent with extracted text.\n\n Raises:\n FileNotFoundError: If the file does not exist.\n ValueError: If the file cannot be decoded.\n \"\"\"\n if not file_path.exists():\n raise FileNotFoundError(f\"Text file not found: {file_path}\")\n\n # Try different encodings\n encodings = [\"utf-8\", \"utf-16\", \"latin-1\", \"cp1252\"]\n\n text = None\n for encoding in encodings:\n try:\n text = file_path.read_text(encoding=encoding)\n break\n except UnicodeDecodeError:\n continue\n\n if text is None:\n raise ValueError(f\"Could not decode text file with any known encoding: {file_path}\")\n\n # Estimate page count (roughly 3000 characters per page)\n estimated_pages = max(1, len(text) // 3000)\n\n return DocumentContent(\n text=text,\n footnotes=[], # Plain text doesn't have structured footnotes\n page_count=estimated_pages,\n metadata={\"source\": str(file_path), \"format\": \"txt\"}\n )\n", | |
| "numLines": 58, | |
| "startLine": 1, | |
| "totalLines": 58 | |
| } | |
| } | |
| } | |
| [2025-12-29T13:27:24.240Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_012GJCjahUBQBDJwJLGiqTTm", | |
| "type": "tool_result", | |
| "content": " 1→\"\"\"PDF document reader using pdfplumber.\"\"\"\n 2→\n 3→import re\n 4→from pathlib import Path\n 5→\n 6→from .base import DocumentReader, DocumentContent\n 7→\n 8→\n 9→class PDFReader(DocumentReader):\n 10→ \"\"\"Reader for PDF documents using pdfplumber.\n 11→\n 12→ This reader extracts text from PDF files while preserving\n 13→ the ability to identify footnotes for optional filtering.\n 14→ \"\"\"\n 15→\n 16→ @property\n 17→ def supported_extensions(self) -> list[str]:\n 18→ \"\"\"Return list of supported PDF extensions.\"\"\"\n 19→ return [\".pdf\", \".PDF\"]\n 20→\n 21→ def read(self, file_path: Path) -> DocumentContent:\n 22→ \"\"\"Read and extract content from a PDF document.\n 23→\n 24→ Args:\n 25→ file_path: Path to the PDF file.\n 26→\n 27→ Returns:\n 28→ DocumentContent with extracted text and footnotes.\n 29→\n 30→ Raises:\n 31→ FileNotFoundError: If the file does not exist.\n 32→ ValueError: If the file cannot be read as PDF.\n 33→ \"\"\"\n 34→ import pdfplumber\n 35→\n 36→ if not file_path.exists():\n 37→ raise FileNotFoundError(f\"PDF file not found: {file_path}\")\n 38→\n 39→ try:\n 40→ text_parts = []\n 41→ footnotes = []\n 42→\n 43→ with pdfplumber.open(file_path) as pdf:\n 44→ page_count = len(pdf.pages)\n 45→\n 46→ for page in pdf.pages:\n 47→ page_text = page.extract_text() or \"\"\n 48→ text_parts.append(page_text)\n 49→\n 50→ # Extract footnotes from page\n 51→ # Footnotes are typically at the bottom with superscript numbers\n 52→ page_footnotes = self._extract_footnotes(page_text)\n 53→ footnotes.extend(page_footnotes)\n 54→\n 55→ full_text = \"\\n\\n\".join(text_parts)\n 56→\n 57→ return DocumentContent(\n 58→ text=full_text,\n 59→ footnotes=footnotes,\n 60→ page_count=page_count,\n 61→ metadata={\"source\": str(file_path), \"format\": \"pdf\"}\n 62→ )\n 63→\n 64→ except Exception as e:\n 65→ raise ValueError(f\"Failed to read PDF file: {e}\") from e\n 66→\n 67→ def _extract_footnotes(self, text: str) -> list[str]:\n 68→ \"\"\"Extract footnotes from page text.\n 69→\n 70→ Footnotes are identified by patterns like:\n 71→ - Numbered footnotes: \"1 This is a footnote\"\n 72→ - Superscript indicators at line start\n 73→\n 74→ Args:\n 75→ text: The page text to search.\n 76→\n 77→ Returns:\n 78→ List of extracted footnote texts.\n 79→ \"\"\"\n 80→ footnotes = []\n 81→\n 82→ # Pattern for footnotes that start with a number followed by space or period\n 83→ # at the beginning of a line (common footnote format)\n 84→ lines = text.split(\"\\n\")\n 85→ in_footnote_section = False\n 86→\n 87→ for i, line in enumerate(lines):\n 88→ line = line.strip()\n 89→ if not line:\n 90→ continue\n 91→\n 92→ # Detect footnote section (often at bottom, starts with small numbers)\n 93→ footnote_match = re.match(r'^(\\d{1,2})\\s+(.+)$', line)\n 94→ if footnote_match:\n 95→ number = int(footnote_match.group(1))\n 96→ # Footnotes typically use small numbers (1-99)\n 97→ if 1 <= number <= 99:\n 98→ footnote_text = footnote_match.group(2)\n 99→ # Check if this looks like a footnote (not a list item)\n 100→ # by seeing if the number is referenced earlier as superscript\n 101→ footnotes.append(f\"[{number}] {footnote_text}\")\n 102→ in_footnote_section = True\n 103→ elif in_footnote_section and not re.match(r'^\\d', line):\n 104→ # Continuation of previous footnote if not starting with number\n 105→ if footnotes:\n 106→ footnotes[-1] += \" \" + line\n 107→\n 108→ return footnotes\n 109→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
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| }, | |
| "parent_tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "cd5f6847-8e1d-4da9-902b-e77cee916bed", | |
| "tool_use_result": { | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/readers/pdf_reader.py", | |
| "content": "\"\"\"PDF document reader using pdfplumber.\"\"\"\n\nimport re\nfrom pathlib import Path\n\nfrom .base import DocumentReader, DocumentContent\n\n\nclass PDFReader(DocumentReader):\n \"\"\"Reader for PDF documents using pdfplumber.\n\n This reader extracts text from PDF files while preserving\n the ability to identify footnotes for optional filtering.\n \"\"\"\n\n @property\n def supported_extensions(self) -> list[str]:\n \"\"\"Return list of supported PDF extensions.\"\"\"\n return [\".pdf\", \".PDF\"]\n\n def read(self, file_path: Path) -> DocumentContent:\n \"\"\"Read and extract content from a PDF document.\n\n Args:\n file_path: Path to the PDF file.\n\n Returns:\n DocumentContent with extracted text and footnotes.\n\n Raises:\n FileNotFoundError: If the file does not exist.\n ValueError: If the file cannot be read as PDF.\n \"\"\"\n import pdfplumber\n\n if not file_path.exists():\n raise FileNotFoundError(f\"PDF file not found: {file_path}\")\n\n try:\n text_parts = []\n footnotes = []\n\n with pdfplumber.open(file_path) as pdf:\n page_count = len(pdf.pages)\n\n for page in pdf.pages:\n page_text = page.extract_text() or \"\"\n text_parts.append(page_text)\n\n # Extract footnotes from page\n # Footnotes are typically at the bottom with superscript numbers\n page_footnotes = self._extract_footnotes(page_text)\n footnotes.extend(page_footnotes)\n\n full_text = \"\\n\\n\".join(text_parts)\n\n return DocumentContent(\n text=full_text,\n footnotes=footnotes,\n page_count=page_count,\n metadata={\"source\": str(file_path), \"format\": \"pdf\"}\n )\n\n except Exception as e:\n raise ValueError(f\"Failed to read PDF file: {e}\") from e\n\n def _extract_footnotes(self, text: str) -> list[str]:\n \"\"\"Extract footnotes from page text.\n\n Footnotes are identified by patterns like:\n - Numbered footnotes: \"1 This is a footnote\"\n - Superscript indicators at line start\n\n Args:\n text: The page text to search.\n\n Returns:\n List of extracted footnote texts.\n \"\"\"\n footnotes = []\n\n # Pattern for footnotes that start with a number followed by space or period\n # at the beginning of a line (common footnote format)\n lines = text.split(\"\\n\")\n in_footnote_section = False\n\n for i, line in enumerate(lines):\n line = line.strip()\n if not line:\n continue\n\n # Detect footnote section (often at bottom, starts with small numbers)\n footnote_match = re.match(r'^(\\d{1,2})\\s+(.+)$', line)\n if footnote_match:\n number = int(footnote_match.group(1))\n # Footnotes typically use small numbers (1-99)\n if 1 <= number <= 99:\n footnote_text = footnote_match.group(2)\n # Check if this looks like a footnote (not a list item)\n # by seeing if the number is referenced earlier as superscript\n footnotes.append(f\"[{number}] {footnote_text}\")\n in_footnote_section = True\n elif in_footnote_section and not re.match(r'^\\d', line):\n # Continuation of previous footnote if not starting with number\n if footnotes:\n footnotes[-1] += \" \" + line\n\n return footnotes\n", | |
| "numLines": 109, | |
| "startLine": 1, | |
| "totalLines": 109 | |
| } | |
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| [2025-12-29T13:27:57.122Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01GkrNP2dGGDbFVNSsVJf4YA", | |
| "type": "tool_result", | |
| "content": [ | |
| { | |
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| "text": "Perfect! Now let me create a comprehensive overview document with all the findings:\n\n## Comprehensive Codebase Overview\n\n### 1. PROJECT STRUCTURE AND PURPOSE\n\n**Text-to-Speech with Chatterbox** is a desktop application that converts documents (PDF, DOC, DOCX, TXT, Markdown, RTF) into speech using Resemble AI's Chatterbox TTS engine. It provides a user-friendly GUI interface and is available as a standalone Windows executable.\n\n**Key Information:**\n- Written in Python 3.10+\n- Desktop GUI using CustomTkinter\n- Version: 0.3.0\n- License: MIT\n\n### 2. DIRECTORY STRUCTURE\n\n```\n/tmp/gh-issue-solver-1767014767488/\n├── src/tts_app/ # Main application package\n│ ├── __init__.py\n│ ├── main.py # Entry point with logging setup\n│ ├── gui/ # GUI components\n│ │ ├── __init__.py\n│ │ └── app.py # Main CustomTkinter application\n│ ├── readers/ # Document readers (extensible)\n│ │ ├── __init__.py\n│ │ ├── base.py # DocumentReader abstract base class\n│ │ ├── registry.py # ReaderRegistry for managing readers\n│ │ ├── pdf_reader.py # PDF extraction using pdfplumber\n│ │ ├── doc_reader.py # Legacy DOC format support\n│ │ ├── docx_reader.py # DOCX format support\n│ │ ├── text_reader.py # Plain text support\n│ │ ├── markdown_reader.py # Markdown support\n│ │ └── rtf_reader.py # RTF format support\n│ ├── preprocessors/ # Text preprocessing pipeline\n│ │ ├── __init__.py\n│ │ ├── base.py # TextPreprocessor abstract base class\n│ │ ├── pipeline.py # Prepr**********eline orchestrator\n│ │ ├── page_numbers.py # Page number removal\n│ │ ├── footnotes.py # Footnote handling\n│ │ └── symbols.py # Symbol/number conversion\n│ ├── tts/ # TTS engine wrappers\n│ │ ├── __init__.py\n│ │ ├── base.py # TTSEngine abstract base class\n│ │ └── chatterbox.py # Chatterbox implementation\n│ └── utils/ # Utilities\n│ ├── __init__.py\n│ └── language_detection.py # Script/language analysis\n├── tests/ # Test suite\n├── pyinstaller_hooks/ # PyInstaller configuration\n├── pyproject.toml # Package configuration\n├── README.md # User documentation\n└── tts_chatterbox.spec # PyInstaller spec file\n```\n\n### 3. CORE MODULES OVERVIEW\n\n#### A. **Entry Point: `main.py`**\n- Handles PyInstaller compatibility\n- Sets up logging to file and console\n- Initializes the GUI application\n- Creates log file next to executable (important for bundled apps)\n\n**Key Functions:**\n- `_setup_package_path()`: Ensures correct imports in PyInstaller bundles\n- `setup_logging()`: Configures logging with file handler for warnings/errors\n\n#### B. **GUI Application: `gui/app.py`**\n\n**Main Class:** `TTSApplication(ctk.CTk)`\n\n**Provides:**\n- File selection for input documents and output audio\n- Voice reference (cloning) file selection\n- Model selection radio buttons:\n - Turbo (fast, English-only)\n - Standard (English with CFG)\n - Multilingual (23+ languages)\n- Language selection dropdown (auto-detect or specific language)\n- Device selection (Auto/GPU/CPU)\n- HuggingFace token field\n- Preprocessing options (ignore footnotes toggle)\n- Progress tracking with cancellation support\n- Custom dialogs for success/error messages with file location opening\n\n**UI Components:**\n- `SuccessDialog`: Shows completion with \"Open File Location\" button\n- `ErrorDialog`: Displays errors with copy-to-clipboard functionality\n- Scrollable main frame for responsive design\n- Real-time progress animation with ellipsis\n\n#### C. **TTS Engine: `tts/` Directory**\n\n**Base Class: `TTSEngine` (Abstract)**\n\nContains:\n- `TTSConfig` dataclass with configuration parameters\n- `TTSResult` dataclass for synthesis output\n- Abstract methods: `initialize()`, `synthesize()`, `is_initialized()`, `get_supported_languages()`\n- Progress callback and cancellation support\n\n**Implementation: `ChatterboxEngine`**\n\n**Device Detection & Selection:**\n- Automatic detection order:\n 1. NVIDIA CUDA (with device name logging)\n 2. Apple MPS (Metal Performance Shaders)\n 3. CPU fallback\n- Device validation with fallback to CPU if unavailable\n- Special handling for AMD GPU users (falls back to CPU with explanation)\n- `_validate_device()`: Ensures requested device is available\n\n**Model Loading:**\n- Three model types:\n - `turbo`: ChatterboxTurboTTS (350M params, English-only)\n - `standard`: ChatterboxTTS (500M params, English with CFG)\n - `multilingual`: Chatt***************alTTS (500M params, 23 languages)\n\n**Key Implementation Details:**\n- Torch.load patching for CPU/MPS loading of CUDA-saved models\n- Voice reference (cloning) support via `audio_prompt_path`\n- Text chunking for long texts (configurable, default 500 chars)\n- Chunk splitting at sentence/phrase boundaries\n- Inter-chunk silence insertion (300ms)\n- Automatic concatenation with torchaudio\n- Progress callbacks with time estimation\n- Cancellation support (saves partial audio)\n\n**Multilingual Languages Supported:**\nArabic (ar), Danish (da), German (de), Greek (el), English (en), Spanish (es), Finnish (fi), French (fr), Hebrew (he), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Malay (ms), Dutch (nl), Norwegian (no), Polish (pl), Portuguese (pt), Russian (ru), Swedish (sv), Swahili (sw), Turkish (tr), Chinese (zh)\n\n#### D. **Language Detection: `utils/language_detection.py`**\n\n**Script Detection:**\n- Unicode range-based detection for 10 scripts:\n - Cyrillic (Russian, Ukrainian, etc.)\n - Latin\n - CJK (Chinese, Japanese, Korean)\n - Hiragana/Katakana (Japanese)\n - Hangul (Korean)\n - Arabic\n - Devanagari (Hindi/Sanskrit)\n - Greek\n - Hebrew\n\n**Functions:**\n- `detect_script()`: Returns character counts per script\n- `detect_primary_language()`: Heuristic-based detection returns language code\n- `is_mixed_language_text()`: Detects texts with multiple scripts above threshold\n- `get_language_name()`: Maps language codes to human-readable names\n\n#### E. **Document Readers: `readers/` Directory**\n\n**Base Class: `DocumentReader` (Abstract)**\n\n**Data Structure: `DocumentContent`**\n- `text`: Main extracted text\n- `footnotes`: List of identified footnotes\n- `page_count`: Number of pages (if applicable)\n- `metadata`: Additional info (format, source path, etc.)\n\n**Registry Pattern: `ReaderRegistry`**\n- Manages multiple reader instances\n- Finds appropriate reader by file extension\n- Supports dynamic registration/unregistration\n- Provides file dialog filter strings\n\n**Supported Readers:**\n\n1. **PDFReader** (`pdf_reader.py`)\n - Uses `pdfplumber` library\n - Extracts text page-by-page\n - Identifies footnotes with regex patterns\n - Handles malformed PDFs gracefully\n\n2. **DOCXReader** (`docx_reader.py`)\n - Uses `python-docx` library\n - Preserves document structure\n\n3. **DOCReader** (`doc_reader.py`)\n - Uses `olefile` for legacy Word formats\n - Handles older Office documents\n\n4. **TextReader** (`text_reader.py`)\n - Multi-encoding support (utf-8, utf-16, latin-1, cp1252)\n - Estimates page count (~3000 chars/page)\n\n5. **MarkdownReader** (`markdown_reader.py`)\n - Preserves markdown structure for readability\n\n6. **RTFReader** (`rtf_reader.py`)\n - Uses `striprtf` for RTF format extraction\n\n#### F. **Text Preprocessing: `preprocessors/` Directory**\n\n**Base Class: `TextPreprocessor` (Abstract)**\n\n**Context: `ProcessingContext`**\n- `footnotes`: List of footnotes\n- `ignore_footnotes`: Boolean flag\n- `page_count`: Page count metadata\n\n**Pipeline: `PreprocessorPipeline`**\n- Chains preprocessors sequentially\n- Normalizes whitespace after all processing\n- Supports enable/disable per preprocessor\n\n**Preprocessors Included:**\n\n1. **PageNumberRemover** (`page_numbers.py`)\n - Removes common page number patterns\n - Handles various formats (centered, margins, etc.)\n\n2. **FootnoteHandler** (`footnotes.py`)\n - Removes or inlines footnote references\n - Handles various footnote markers\n\n3. **SymbolConverter** (`symbols.py`)\n - Converts mathematical operators (=, +, -, *, /, etc.)\n - Handles currency symbols ($, €, £, ¥, ₽)\n - Converts special characters (@, &, #)\n - Handles numbered lists and bullets\n - Language-aware (English and Russian mappings)\n - Examples:\n - `5 + 3` → `5 plus 3`\n - `$100` → `100 dollars`\n - `• Item` → `Item`\n - `1. Point` → `Point 1.`\n\n### 4. CONFIGURATION & DEPENDENCIES\n\n**Core Dependencies:**\n- `chatterbox-tts>=0.1.6` - Main TTS engine\n- `torchaudio` - Audio I/O\n- `pdfplumber>=0.10.0` - PDF extraction\n- `olefile>=0.46` - Legacy DOC support\n- `python-docx>=1.0.0` - DOCX support\n- `markdown>=3.5.0` - Markdown support\n- `striprtf>=0.0.26` - RTF support\n- `customtkinter>=5.2.0` - Modern GUI\n- `CTkMessagebox>=2.5` - Custom message dialogs\n\n**Optional Dependencies:**\n- `pytest>=7.0.0`, `pytest-cov>=4.0.0` - Testing\n- `pyinstaller>=6.0.0` - Executable building\n- `russian-text-stresser` - Russian stress marking (git dependency)\n- `pkuseg` - Chinese word segmentation\n\n### 5. GPU/DEVICE SELECTION\n\n**Device Detection Order:**\n1. NVIDIA CUDA (checked via `torch.cuda.is_available()`)\n2. Apple MPS (checked via `torch.backends.mps.is_available()`)\n3. CPU fallback\n\n**User Options in GUI:**\n- \"Auto (GPU/CPU)\" - Automatic detection\n- \"GPU\" - Forces CUDA (falls back to CPU if unavailable)\n- \"CPU\" - Explicit CPU mode\n\n**AMD GPU Handling:**\n- Standard PyTorch Windows builds only support NVIDIA CUDA\n- AMD GPUs automatically fall back to CPU\n- User receives explanation message about AMD limitation\n- Alternative: Use ROCm PyTorch build (requires manual installation)\n\n**Key Implementation: `_validate_device()` and `_detect_best_device()`**\n- Graceful fallback with informative warnings\n- Handles missing drivers or incompatible hardware\n\n### 6. WORKFLOW FLOW\n\n```\nUser Input (GUI)\n ↓\nRead Document (ReaderRegistry)\n ↓\nExtract Text + Footnotes + Metadata\n ↓\nPreprocess Text (PreprocessorPipeline)\n ├── Remove page numbers\n ├── Handle footnotes\n └── Convert symbols\n ↓\nDetect Language (if multilingual + auto)\n ↓\nInitialize TTS Engine (ChatterboxEngine)\n ├── Detect/validate device\n └── Load model (turbo/standard/multilingual)\n ↓\nSynthesize Audio\n ├── Split into chunks\n ├── Generate per chunk\n ├── Add inter-chunk silence\n ├── Concatenate\n └── Save to WAV\n ↓\nDisplay Success Dialog with File Location\n```\n\n### 7. ERROR HANDLING & LOGGING\n\n**Logging Setup:**\n- Console output: INFO level\n- File output: WARNING and ERROR levels\n- File location: Next to executable (for bundled apps)\n- Detailed formatting with timestamps and file/line info\n\n**Custom Exceptions:**\n- `HuggingFaceTokenError`: When HF token required but missing\n- `CUDANotAvailableError`: When CUDA requested but unavailable\n\n**Error Dialogs:**\n- Copy-to-clipboard functionality for error text\n- Full traceback preservation\n- Helpful messages with suggested solutions\n\n### 8. EXTENSIBILITY\n\n**Adding New Document Format:**\n1. Create `DocumentReader` subclass\n2. Implement `supported_extensions` and `read()` methods\n3. Register with `ReaderRegistry.register()`\n\n**Adding New Preprocessor:**\n1. Create `TextPreprocessor` subclass\n2. Implement `name` property and `process()` method\n3. Add to pipeline via `pipeline.add()`\n\n**Adding New TTS Engine:**\n1. Create `TTSEngine` subclass\n2. Implement all abstract methods\n3. Replace engine in GUI initialization\n\n---\n\n## Summary\n\nThis is a well-architected, extensible text-to-speech application with:\n- **Modular design** using abstract base classes\n- **Device auto-detection** with graceful fallbacks\n- **Multiple input formats** through registry pattern\n- **Preprocessing pipeline** for text normalization\n- **Multi-language support** via Chatterbox multilingual model\n- **Responsive GUI** with progress tracking and cancellation\n- **Professional error handling** with helpful messages\n- **PyInstaller bundling** support for distribution\n\nThe codebase demonstrates good software engineering practices with separation of concerns, extensibility points, and clear documentation." | |
| }, | |
| { | |
| "type": "text", | |
| "text": "agentId: a28abb3 (for resuming to continue this agent's work if needed)" | |
| } | |
| ] | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "aa0d07f8-43a9-4fad-a886-ed57a9d32614", | |
| "tool_use_result": { | |
| "status": "completed", | |
| "prompt": "Explore this codebase thoroughly. I need to understand:\n1. The main structure and what this project does\n2. All Python files and their purposes\n3. How text-to-speech is implemented\n4. How language detection works\n5. How the UI is structured\n6. Any configuration or settings related to GPU/device selection\n\nFocus on src/ directory and any main Python files. Give me a comprehensive overview.", | |
| "agentId": "a28abb3", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Perfect! Now let me create a comprehensive overview document with all the findings:\n\n## Comprehensive Codebase Overview\n\n### 1. PROJECT STRUCTURE AND PURPOSE\n\n**Text-to-Speech with Chatterbox** is a desktop application that converts documents (PDF, DOC, DOCX, TXT, Markdown, RTF) into speech using Resemble AI's Chatterbox TTS engine. It provides a user-friendly GUI interface and is available as a standalone Windows executable.\n\n**Key Information:**\n- Written in Python 3.10+\n- Desktop GUI using CustomTkinter\n- Version: 0.3.0\n- License: MIT\n\n### 2. DIRECTORY STRUCTURE\n\n```\n/tmp/gh-issue-solver-1767014767488/\n├── src/tts_app/ # Main application package\n│ ├── __init__.py\n│ ├── main.py # Entry point with logging setup\n│ ├── gui/ # GUI components\n│ │ ├── __init__.py\n│ │ └── app.py # Main CustomTkinter application\n│ ├── readers/ # Document readers (extensible)\n│ │ ├── __init__.py\n│ │ ├── base.py # DocumentReader abstract base class\n│ │ ├── registry.py # ReaderRegistry for managing readers\n│ │ ├── pdf_reader.py # PDF extraction using pdfplumber\n│ │ ├── doc_reader.py # Legacy DOC format support\n│ │ ├── docx_reader.py # DOCX format support\n│ │ ├── text_reader.py # Plain text support\n│ │ ├── markdown_reader.py # Markdown support\n│ │ └── rtf_reader.py # RTF format support\n│ ├── preprocessors/ # Text preprocessing pipeline\n│ │ ├── __init__.py\n│ │ ├── base.py # TextPreprocessor abstract base class\n│ │ ├── pipeline.py # Prepr**********eline orchestrator\n│ │ ├── page_numbers.py # Page number removal\n│ │ ├── footnotes.py # Footnote handling\n│ │ └── symbols.py # Symbol/number conversion\n│ ├── tts/ # TTS engine wrappers\n│ │ ├── __init__.py\n│ │ ├── base.py # TTSEngine abstract base class\n│ │ └── chatterbox.py # Chatterbox implementation\n│ └── utils/ # Utilities\n│ ├── __init__.py\n│ └── language_detection.py # Script/language analysis\n├── tests/ # Test suite\n├── pyinstaller_hooks/ # PyInstaller configuration\n├── pyproject.toml # Package configuration\n├── README.md # User documentation\n└── tts_chatterbox.spec # PyInstaller spec file\n```\n\n### 3. CORE MODULES OVERVIEW\n\n#### A. **Entry Point: `main.py`**\n- Handles PyInstaller compatibility\n- Sets up logging to file and console\n- Initializes the GUI application\n- Creates log file next to executable (important for bundled apps)\n\n**Key Functions:**\n- `_setup_package_path()`: Ensures correct imports in PyInstaller bundles\n- `setup_logging()`: Configures logging with file handler for warnings/errors\n\n#### B. **GUI Application: `gui/app.py`**\n\n**Main Class:** `TTSApplication(ctk.CTk)`\n\n**Provides:**\n- File selection for input documents and output audio\n- Voice reference (cloning) file selection\n- Model selection radio buttons:\n - Turbo (fast, English-only)\n - Standard (English with CFG)\n - Multilingual (23+ languages)\n- Language selection dropdown (auto-detect or specific language)\n- Device selection (Auto/GPU/CPU)\n- HuggingFace token field\n- Preprocessing options (ignore footnotes toggle)\n- Progress tracking with cancellation support\n- Custom dialogs for success/error messages with file location opening\n\n**UI Components:**\n- `SuccessDialog`: Shows completion with \"Open File Location\" button\n- `ErrorDialog`: Displays errors with copy-to-clipboard functionality\n- Scrollable main frame for responsive design\n- Real-time progress animation with ellipsis\n\n#### C. **TTS Engine: `tts/` Directory**\n\n**Base Class: `TTSEngine` (Abstract)**\n\nContains:\n- `TTSConfig` dataclass with configuration parameters\n- `TTSResult` dataclass for synthesis output\n- Abstract methods: `initialize()`, `synthesize()`, `is_initialized()`, `get_supported_languages()`\n- Progress callback and cancellation support\n\n**Implementation: `ChatterboxEngine`**\n\n**Device Detection & Selection:**\n- Automatic detection order:\n 1. NVIDIA CUDA (with device name logging)\n 2. Apple MPS (Metal Performance Shaders)\n 3. CPU fallback\n- Device validation with fallback to CPU if unavailable\n- Special handling for AMD GPU users (falls back to CPU with explanation)\n- `_validate_device()`: Ensures requested device is available\n\n**Model Loading:**\n- Three model types:\n - `turbo`: ChatterboxTurboTTS (350M params, English-only)\n - `standard`: ChatterboxTTS (500M params, English with CFG)\n - `multilingual`: Chatt***************alTTS (500M params, 23 languages)\n\n**Key Implementation Details:**\n- Torch.load patching for CPU/MPS loading of CUDA-saved models\n- Voice reference (cloning) support via `audio_prompt_path`\n- Text chunking for long texts (configurable, default 500 chars)\n- Chunk splitting at sentence/phrase boundaries\n- Inter-chunk silence insertion (300ms)\n- Automatic concatenation with torchaudio\n- Progress callbacks with time estimation\n- Cancellation support (saves partial audio)\n\n**Multilingual Languages Supported:**\nArabic (ar), Danish (da), German (de), Greek (el), English (en), Spanish (es), Finnish (fi), French (fr), Hebrew (he), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Malay (ms), Dutch (nl), Norwegian (no), Polish (pl), Portuguese (pt), Russian (ru), Swedish (sv), Swahili (sw), Turkish (tr), Chinese (zh)\n\n#### D. **Language Detection: `utils/language_detection.py`**\n\n**Script Detection:**\n- Unicode range-based detection for 10 scripts:\n - Cyrillic (Russian, Ukrainian, etc.)\n - Latin\n - CJK (Chinese, Japanese, Korean)\n - Hiragana/Katakana (Japanese)\n - Hangul (Korean)\n - Arabic\n - Devanagari (Hindi/Sanskrit)\n - Greek\n - Hebrew\n\n**Functions:**\n- `detect_script()`: Returns character counts per script\n- `detect_primary_language()`: Heuristic-based detection returns language code\n- `is_mixed_language_text()`: Detects texts with multiple scripts above threshold\n- `get_language_name()`: Maps language codes to human-readable names\n\n#### E. **Document Readers: `readers/` Directory**\n\n**Base Class: `DocumentReader` (Abstract)**\n\n**Data Structure: `DocumentContent`**\n- `text`: Main extracted text\n- `footnotes`: List of identified footnotes\n- `page_count`: Number of pages (if applicable)\n- `metadata`: Additional info (format, source path, etc.)\n\n**Registry Pattern: `ReaderRegistry`**\n- Manages multiple reader instances\n- Finds appropriate reader by file extension\n- Supports dynamic registration/unregistration\n- Provides file dialog filter strings\n\n**Supported Readers:**\n\n1. **PDFReader** (`pdf_reader.py`)\n - Uses `pdfplumber` library\n - Extracts text page-by-page\n - Identifies footnotes with regex patterns\n - Handles malformed PDFs gracefully\n\n2. **DOCXReader** (`docx_reader.py`)\n - Uses `python-docx` library\n - Preserves document structure\n\n3. **DOCReader** (`doc_reader.py`)\n - Uses `olefile` for legacy Word formats\n - Handles older Office documents\n\n4. **TextReader** (`text_reader.py`)\n - Multi-encoding support (utf-8, utf-16, latin-1, cp1252)\n - Estimates page count (~3000 chars/page)\n\n5. **MarkdownReader** (`markdown_reader.py`)\n - Preserves markdown structure for readability\n\n6. **RTFReader** (`rtf_reader.py`)\n - Uses `striprtf` for RTF format extraction\n\n#### F. **Text Preprocessing: `preprocessors/` Directory**\n\n**Base Class: `TextPreprocessor` (Abstract)**\n\n**Context: `ProcessingContext`**\n- `footnotes`: List of footnotes\n- `ignore_footnotes`: Boolean flag\n- `page_count`: Page count metadata\n\n**Pipeline: `PreprocessorPipeline`**\n- Chains preprocessors sequentially\n- Normalizes whitespace after all processing\n- Supports enable/disable per preprocessor\n\n**Preprocessors Included:**\n\n1. **PageNumberRemover** (`page_numbers.py`)\n - Removes common page number patterns\n - Handles various formats (centered, margins, etc.)\n\n2. **FootnoteHandler** (`footnotes.py`)\n - Removes or inlines footnote references\n - Handles various footnote markers\n\n3. **SymbolConverter** (`symbols.py`)\n - Converts mathematical operators (=, +, -, *, /, etc.)\n - Handles currency symbols ($, €, £, ¥, ₽)\n - Converts special characters (@, &, #)\n - Handles numbered lists and bullets\n - Language-aware (English and Russian mappings)\n - Examples:\n - `5 + 3` → `5 plus 3`\n - `$100` → `100 dollars`\n - `• Item` → `Item`\n - `1. Point` → `Point 1.`\n\n### 4. CONFIGURATION & DEPENDENCIES\n\n**Core Dependencies:**\n- `chatterbox-tts>=0.1.6` - Main TTS engine\n- `torchaudio` - Audio I/O\n- `pdfplumber>=0.10.0` - PDF extraction\n- `olefile>=0.46` - Legacy DOC support\n- `python-docx>=1.0.0` - DOCX support\n- `markdown>=3.5.0` - Markdown support\n- `striprtf>=0.0.26` - RTF support\n- `customtkinter>=5.2.0` - Modern GUI\n- `CTkMessagebox>=2.5` - Custom message dialogs\n\n**Optional Dependencies:**\n- `pytest>=7.0.0`, `pytest-cov>=4.0.0` - Testing\n- `pyinstaller>=6.0.0` - Executable building\n- `russian-text-stresser` - Russian stress marking (git dependency)\n- `pkuseg` - Chinese word segmentation\n\n### 5. GPU/DEVICE SELECTION\n\n**Device Detection Order:**\n1. NVIDIA CUDA (checked via `torch.cuda.is_available()`)\n2. Apple MPS (checked via `torch.backends.mps.is_available()`)\n3. CPU fallback\n\n**User Options in GUI:**\n- \"Auto (GPU/CPU)\" - Automatic detection\n- \"GPU\" - Forces CUDA (falls back to CPU if unavailable)\n- \"CPU\" - Explicit CPU mode\n\n**AMD GPU Handling:**\n- Standard PyTorch Windows builds only support NVIDIA CUDA\n- AMD GPUs automatically fall back to CPU\n- User receives explanation message about AMD limitation\n- Alternative: Use ROCm PyTorch build (requires manual installation)\n\n**Key Implementation: `_validate_device()` and `_detect_best_device()`**\n- Graceful fallback with informative warnings\n- Handles missing drivers or incompatible hardware\n\n### 6. WORKFLOW FLOW\n\n```\nUser Input (GUI)\n ↓\nRead Document (ReaderRegistry)\n ↓\nExtract Text + Footnotes + Metadata\n ↓\nPreprocess Text (PreprocessorPipeline)\n ├── Remove page numbers\n ├── Handle footnotes\n └── Convert symbols\n ↓\nDetect Language (if multilingual + auto)\n ↓\nInitialize TTS Engine (ChatterboxEngine)\n ├── Detect/validate device\n └── Load model (turbo/standard/multilingual)\n ↓\nSynthesize Audio\n ├── Split into chunks\n ├── Generate per chunk\n ├── Add inter-chunk silence\n ├── Concatenate\n └── Save to WAV\n ↓\nDisplay Success Dialog with File Location\n```\n\n### 7. ERROR HANDLING & LOGGING\n\n**Logging Setup:**\n- Console output: INFO level\n- File output: WARNING and ERROR levels\n- File location: Next to executable (for bundled apps)\n- Detailed formatting with timestamps and file/line info\n\n**Custom Exceptions:**\n- `HuggingFaceTokenError`: When HF token required but missing\n- `CUDANotAvailableError`: When CUDA requested but unavailable\n\n**Error Dialogs:**\n- Copy-to-clipboard functionality for error text\n- Full traceback preservation\n- Helpful messages with suggested solutions\n\n### 8. EXTENSIBILITY\n\n**Adding New Document Format:**\n1. Create `DocumentReader` subclass\n2. Implement `supported_extensions` and `read()` methods\n3. Register with `ReaderRegistry.register()`\n\n**Adding New Preprocessor:**\n1. Create `TextPreprocessor` subclass\n2. Implement `name` property and `process()` method\n3. Add to pipeline via `pipeline.add()`\n\n**Adding New TTS Engine:**\n1. Create `TTSEngine` subclass\n2. Implement all abstract methods\n3. Replace engine in GUI initialization\n\n---\n\n## Summary\n\nThis is a well-architected, extensible text-to-speech application with:\n- **Modular design** using abstract base classes\n- **Device auto-detection** with graceful fallbacks\n- **Multiple input formats** through registry pattern\n- **Preprocessing pipeline** for text normalization\n- **Multi-language support** via Chatterbox multilingual model\n- **Responsive GUI** with progress tracking and cancellation\n- **Professional error handling** with helpful messages\n- **PyInstaller bundling** support for distribution\n\nThe codebase demonstrates good software engineering practices with separation of concerns, extensibility points, and clear documentation." | |
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| [2025-12-29T13:28:13.690Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01FUaAK5GsHohd2ZqMZsvERC","type":"tool_result","content":" 1→\"\"\"Chatterbox TTS engine implementation.\"\"\"\n 2→\n 3→import logging\n 4→import os\n 5→import time\n 6→from contextlib import contextmanager\n 7→from pathlib import Path\n 8→from typing import Optional\n 9→\n 10→from .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n 11→\n 12→logger = logging.getLogger(__name__)\n 13→\n 14→\n 15→@contextmanager\n 16→def _patch_torch_load_for_cpu(device: str):\n 17→ \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n 18→\n 19→ This is a workaround for the chatterbox multilingual model which doesn't properly\n 20→ handle loading models that were saved on CUDA devices when running on CPU.\n 21→\n 22→ See: https://github.com/resemble-ai/chatterbox/issues/96\n 23→\n 24→ Args:\n 25→ device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n 26→ \"\"\"\n 27→ import torch\n 28→\n 29→ # Only patch if we're loading on a non-CUDA device\n 30→ if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n 31→ original_torch_load = torch.load\n 32→\n 33→ def patched_torch_load(f, map_location=None, **kwargs):\n 34→ # If no map_location specified, default to CPU for safe loading\n 35→ if map_location is None:\n 36→ map_location = \"cpu\"\n 37→ return original_torch_load(f, map_location=map_location, **kwargs)\n 38→\n 39→ torch.load = patched_torch_load\n 40→ try:\n 41→ yield\n 42→ finally:\n 43→ torch.load = original_torch_load\n 44→ else:\n 45→ # No patching needed for CUDA devices\n 46→ yield\n 47→\n 48→\n 49→class HuggingFaceTokenError(RuntimeError):\n 50→ \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n 51→ pass\n 52→\n 53→\n 54→class CUDANotAvailableError(RuntimeError):\n 55→ \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n 56→ pass\n 57→\n 58→\n 59→class ChatterboxEngine(TTSEngine):\n 60→ \"\"\"TTS engine using Resemble AI's Chatterbox models.\n 61→\n 62→ Supports three model variants:\n 63→ - Turbo: Fast, English-only, 350M parameters\n 64→ - Standard: English with CFG tuning, 500M parameters\n 65→ - Multilingual: 23+ languages, 500M parameters\n 66→ \"\"\"\n 67→\n 68→ # Supported languages for the multilingual model\n 69→ MULTI************UAGES = [\n 70→ \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n 71→ \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n 72→ \"sw\", \"tr\", \"zh\"\n 73→ ]\n 74→\n 75→ def __init__(self):\n 76→ \"\"\"Initialize the Chatterbox engine.\"\"\"\n 77→ self._model = None\n 78→ self._config: Optional[TTSConfig] = None\n 79→ self._initialized = False\n 80→\n 81→ @property\n 82→ def name(self) -> str:\n 83→ \"\"\"Get the engine name.\"\"\"\n 84→ return \"chatterbox\"\n 85→\n 86→ def _detect_best_device(self) -> str:\n 87→ \"\"\"Detect the best available device for inference.\n 88→\n 89→ Checks for GPU availability in the following order:\n 90→ 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 91→ 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 92→ 3. Apple MPS (Apple Silicon)\n 93→ 4. CPU fallback\n 94→\n 95→ Returns:\n 96→ Device string (\"cuda\", \"mps\", or \"cpu\").\n 97→ \"\"\"\n 98→ import torch\n 99→\n 100→ # Check for NVIDIA CUDA\n 101→ # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n 102→ # because standard PyTorch Windows builds only support NVIDIA CUDA\n 103→ if torch.cuda.is_available():\n 104→ try:\n 105→ device_name = torch.cuda.get_device_name(0)\n 106→ logger.info(f\"CUDA available: {device_name}\")\n 107→ return \"cuda\"\n 108→ except Exception as e:\n 109→ logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n 110→ # Fall through to CPU\n 111→\n 112→ # Check for MPS (Apple Silicon)\n 113→ if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n 114→ logger.info(\"Apple MPS available\")\n 115→ return \"mps\"\n 116→\n 117→ logger.info(\"No GPU available, using CPU\")\n 118→ return \"cpu\"\n 119→\n 120→ def _validate_device(self, requested_device: str) -> str:\n 121→ \"\"\"Validate the requested device and return a valid device.\n 122→\n 123→ If the requested device is not available, falls back to CPU with a warning.\n 124→\n 125→ Args:\n 126→ requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n 127→\n 128→ Returns:\n 129→ A valid device string that PyTorch can use.\n 130→ \"\"\"\n 131→ import torch\n 132→\n 133→ if requested_device == \"auto\":\n 134→ return self._detect_best_device()\n 135→\n 136→ if requested_device == \"cuda\":\n 137→ if not torch.cuda.is_available():\n 138→ logger.warning(\n 139→ \"GPU (CUDA) was requested but is not available. \"\n 140→ \"This can happen if:\\n\"\n 141→ \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n 142→ \" - PyTorch was not installed with CUDA support\\n\"\n 143→ \" - CUDA drivers are not properly installed\\n\"\n 144→ \"Falling back to CPU mode.\"\n 145→ )\n 146→ return \"cpu\"\n 147→ return \"cuda\"\n 148→\n 149→ if requested_device == \"mps\":\n 150→ if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n 151→ logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n 152→ return \"cpu\"\n 153→ return \"mps\"\n 154→\n 155→ return requested_device # \"cpu\" or unknown\n 156→\n 157→ def initialize(self, config: TTSConfig) -> None:\n 158→ \"\"\"Initialize the Chatterbox TTS model.\n 159→\n 160→ Args:\n 161→ config: TTS configuration settings.\n 162→\n 163→ Raises:\n 164→ RuntimeError: If model loading fails.\n 165→ HuggingFaceTokenError: If HuggingFace token is required but not configured.\n 166→ CUDANotAvailableError: If model requires CUDA but it's not available.\n 167→ \"\"\"\n 168→ self._config = config\n 169→\n 170→ # Validate and determine device (with fallback to CPU if GPU not available)\n 171→ device = self._validate_device(config.device)\n 172→\n 173→ logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n 174→\n 175→ # Set HF_TOKEN environment variable if provided in config\n 176→ # This helps the turbo model which requires token=True by default\n 177→ if hasattr(config, 'hf_token') and config.hf_token:\n 178→ os.environ[\"HF_TOKEN\"] = config.hf_token\n 179→ logger.info(\"HuggingFace token configured from settings\")\n 180→\n 181→ try:\n 182→ if config.model_type == \"turbo\":\n 183→ from chatterbox.tts_turbo import ChatterboxTurboTTS\n 184→ self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n 185→\n 186→ elif config.model_type == \"multilingual\":\n 187→ from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n 188→ # Use patch to handle CUDA-saved models on CPU/MPS devices\n 189→ # See: https://github.com/resemble-ai/chatterbox/issues/96\n 190→ with _patch_torch_load_for_cpu(device):\n 191→ self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n 192→\n 193→ else: # standard\n 194→ from chatterbox.tts import ChatterboxTTS\n 195→ self._model = ChatterboxTTS.from_pretrained(device=device)\n 196→\n 197→ self._initialized = True\n 198→ logger.info(\"Chatterbox model initialized successfully\")\n 199→\n 200→ except Exception as e:\n 201→ error_msg = str(e)\n 202→ logger.error(f\"Failed to initialize Chatterbox: {e}\")\n 203→\n 204→ # Check for HuggingFace token errors\n 205→ if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n 206→ raise HuggingFaceTokenError(\n 207→ \"HuggingFace token is required to download the model.\\n\\n\"\n 208→ \"Please do one of the following:\\n\"\n 209→ \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n 210→ \"2. Set the HF_TOKEN environment variable\\n\"\n 211→ \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n 212→ \"Get your token at: https://huggingface.co/settings/tokens\"\n 213→ ) from e\n 214→\n 215→ # Check for CUDA loading errors on CPU machines or AMD GPU users\n 216→ if (\"torch.cuda.is_available() is False\" in error_msg or\n 217→ \"CUDA device\" in error_msg or\n 218→ \"Torch not compiled with CUDA enabled\" in error_msg):\n 219→ raise CUDANotAvailableError(\n 220→ \"GPU acceleration is not available on this system.\\n\\n\"\n 221→ \"Possible reasons:\\n\"\n 222→ \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n 223→ \"- PyTorch was installed without CUDA support\\n\"\n 224→ \"- NVIDIA drivers are not installed\\n\\n\"\n 225→ \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n 226→ \"The application will work on CPU, though slower.\"\n 227→ ) from e\n 228→\n 229→ raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n 230→\n 231→ def is_initialized(self) -> bool:\n 232→ \"\"\"Check if the engine is initialized.\"\"\"\n 233→ return self._initialized and self._model is not None\n 234→\n 235→ def get_supported_languages(self) -> list[str]:\n 236→ \"\"\"Get list of supported language codes.\"\"\"\n 237→ if self._config and self._config.model_type == \"multilingual\":\n 238→ return self.MULTILINGUAL_LANGUAGES\n 239→ return [\"en\"] # Turbo and standard are English-only\n 240→\n 241→ def synthesize(\n 242→ self,\n 243→ text: str,\n 244→ output_path: Path,\n 245→ progress_callback: Optional[ProgressCallback] = None,\n 246→ cancel_check: Optional[CancelCheck] = None\n 247→ ) -> TTSResult:\n 248→ \"\"\"Synthesize speech from text.\n 249→\n 250→ Args:\n 251→ text: The text to convert to speech.\n 252→ output_path: Path where the audio file should be saved.\n 253→ progress_callback: Optional callback for progress updates.\n 254→ cancel_check: Optional callback that returns True if generation should stop.\n 255→ When cancelled, partial audio is saved and result.was_cancelled is True.\n 256→\n 257→ Returns:\n 258→ TTSResult with information about the generated audio.\n 259→\n 260→ Raises:\n 261→ RuntimeError: If synthesis fails or engine not initialized.\n 262→ \"\"\"\n 263→ if not self.is_initialized():\n 264→ raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n 265→\n 266→ import torch\n 267→ import torchaudio\n 268→\n 269→ # Split text into chunks for long texts\n 270→ chunks = self._split_into_chunks(text, self._config.chunk_size)\n 271→ total_chunks = len(chunks)\n 272→\n 273→ logger.info(f\"Synthesizing {total_chunks} chunks\")\n 274→\n 275→ audio_segments = []\n 276→ sample_rate = self._model.sr\n 277→ was_cancelled = False\n 278→ chunks_completed = 0\n 279→ chunk_times = [] # Track time for each chunk to estimate remaining time\n 280→ start_time = time.time()\n 281→\n 282→ for i, chunk in enumerate(chunks):\n 283→ # Check for cancellation before processing each chunk\n 284→ if cancel_check and cancel_check():\n 285→ logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n 286→ was_cancelled = True\n 287→ break\n 288→\n 289→ # Calculate estimated remaining time based on average chunk time\n 290→ estimated_remaining = None\n 291→ if chunk_times:\n 292→ avg_chunk_time = sum(chunk_times) / len(chunk_times)\n 293→ remaining_chunks = total_chunks - i\n 294→ estimated_remaining = avg_chunk_time * remaining_chunks\n 295→\n 296→ if progress_callback:\n 297→ progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n 298→\n 299→ chunk_start_time = time.time()\n 300→\n 301→ if not chunk.strip():\n 302→ continue\n 303→\n 304→ try:\n 305→ # Generate audio for this chunk\n 306→ wav = self._generate_chunk(chunk)\n 307→ audio_segments.append(wav)\n 308→ chunks_completed += 1\n 309→\n 310→ # Track chunk processing time for estimation\n 311→ chunk_time = time.time() - chunk_start_time\n 312→ chunk_times.append(chunk_time)\n 313→ logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n 314→\n 315→ except Exception as e:\n 316→ logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n 317→ # Continue with other chunks\n 318→ continue\n 319→\n 320→ # Handle case where no audio was generated\n 321→ if not audio_segments:\n 322→ if was_cancelled:\n 323→ raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n 324→ raise RuntimeError(\"No audio was generated\")\n 325→\n 326→ # Concatenate all audio segments\n 327→ if len(audio_segments) == 1:\n 328→ final_audio = audio_segments[0]\n 329→ else:\n 330→ # Add small silence between segments\n 331→ silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n 332→ padded_segments = []\n 333→ for seg in audio_segments:\n 334→ padded_segments.append(seg)\n 335→ padded_segments.append(silence)\n 336→ # Remove last silence\n 337→ padded_segments = padded_segments[:-1]\n 338→ final_audio = torch.cat(padded_segments, dim=1)\n 339→\n 340→ # Save to file\n 341→ output_path = Path(output_path)\n 342→ output_path.parent.mkdir(parents=True, exist_ok=True)\n 343→ torchaudio.save(str(output_path), final_audio, sample_rate)\n 344→\n 345→ # Calculate duration\n 346→ duration = final_audio.shape[1] / sample_rate\n 347→\n 348→ if progress_callback:\n 349→ if was_cancelled:\n 350→ progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n 351→ else:\n 352→ progress_callback(total_chunks, total_chunks, \"Complete\", None)\n 353→\n 354→ return TTSResult(\n 355→ audio_path=output_path,\n 356→ duration_seconds=duration,\n 357→ sample_rate=sample_rate,\n 358→ text_processed=text,\n 359→ was_cancelled=was_cancelled,\n 360→ chunks_completed=chunks_completed,\n 361→ chunks_total=total_chunks\n 362→ )\n 363→\n 364→ def _generate_chunk(self, text: str):\n 365→ \"\"\"Generate audio for a single text chunk.\n 366→\n 367→ Args:\n 368→ text: The text chunk to synthesize.\n 369→\n 370→ Returns:\n 371→ Audio tensor.\n 372→ \"\"\"\n 373→ voice_ref = None\n 374→ if self._config.voice_reference:\n 375→ voice_ref = str(self._config.voice_reference)\n 376→\n 377→ if self._config.model_type == \"multilingual\":\n 378→ # Multilingual model requires language_id\n 379→ wav = self._model.generate(\n 380→ text,\n 381→ audio_prompt_path=voice_ref,\n 382→ language_id=self._config.language\n 383→ )\n 384→ elif voice_ref:\n 385→ # With voice reference\n 386→ wav = self._model.generate(text, audio_prompt_path=voice_ref)\n 387→ else:\n 388→ # Without voice reference\n 389→ wav = self._model.generate(text)\n 390→\n 391→ return wav\n 392→\n 393→ def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n 394→ \"\"\"Split text into chunks at natural boundaries.\n 395→\n 396→ Args:\n 397→ text: The text to split.\n 398→ max_chars: Maximum characters per chunk.\n 399→\n 400→ Returns:\n 401→ List of text chunks.\n 402→ \"\"\"\n 403→ if len(text) <= max_chars:\n 404→ return [text]\n 405→\n 406→ chunks = []\n 407→ current_chunk = \"\"\n 408→\n 409→ # Split by sentences first\n 410→ sentences = self._split_sentences(text)\n 411→\n 412→ for sentence in sentences:\n 413→ if len(current_chunk) + len(sentence) <= max_chars:\n 414→ current_chunk += sentence\n 415→ else:\n 416→ if current_chunk:\n 417→ chunks.append(current_chunk.strip())\n 418→ # If single sentence is too long, split by phrases\n 419→ if len(sentence) > max_chars:\n 420→ phrases = self._split_phrases(sentence, max_chars)\n 421→ chunks.extend(phrases[:-1])\n 422→ current_chunk = phrases[-1] if phrases else \"\"\n 423→ else:\n 424→ current_chunk = sentence\n 425→\n 426→ if current_chunk.strip():\n 427→ chunks.append(current_chunk.strip())\n 428→\n 429→ return chunks\n 430→\n 431→ def _split_sentences(sel | |
| [2025-12-29T13:28:13.708Z] [INFO] f, text: str) -> list[str]:\n 432→ \"\"\"Split text into sentences.\n 433→\n 434→ Args:\n 435→ text: The text to split.\n 436→\n 437→ Returns:\n 438→ List of sentences.\n 439→ \"\"\"\n 440→ import re\n 441→\n 442→ # Split on sentence-ending punctuation\n 443→ sentences = re.split(r'(?<=[.!?])\\s+', text)\n 444→ return sentences\n 445→\n 446→ def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n 447→ \"\"\"Split a long sentence into smaller phrases.\n 448→\n 449→ Args:\n 450→ text: The text to split.\n 451→ max_chars: Maximum characters per phrase.\n 452→\n 453→ Returns:\n 454→ List of phrases.\n 455→ \"\"\"\n 456→ import re\n 457→\n 458→ # Split on commas, semicolons, and other natural breaks\n 459→ parts = re.split(r'(?<=[,;:])\\s+', text)\n 460→\n 461→ phrases = []\n 462→ current_phrase = \"\"\n 463→\n 464→ for part in parts:\n 465→ if len(current_phrase) + len(part) <= max_chars:\n 466→ current_phrase += \" \" + part if current_phrase else part\n 467→ else:\n 468→ if current_phrase:\n 469→ phrases.append(current_phrase.strip())\n 470→ # If still too long, force split\n 471→ if len(part) > max_chars:\n 472→ words = part.split()\n 473→ current_phrase = \"\"\n 474→ for word in words:\n 475→ if len(current_phrase) + len(word) + 1 <= max_chars:\n 476→ current_phrase += \" \" + word if current_phrase else word\n 477→ else:\n 478→ if current_phrase:\n 479→ phrases.append(current_phrase.strip())\n 480→ current_phrase = word\n 481→ else:\n 482→ current_phrase = part\n 483→\n 484→ if current_phrase.strip():\n 485→ phrases.append(current_phrase.strip())\n 486→\n 487→ return phrases\n 488→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"33518088-a926-4cf6-a562-3f5231490b8c","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py","content":"\"\"\"Chatterbox TTS engine implementation.\"\"\"\n\nimport logging\nimport os\nimport time\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef _patch_torch_load_for_cpu(device: str):\n \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n\n This is a workaround for the chatterbox multilingual model which doesn't properly\n handle loading models that were saved on CUDA devices when running on CPU.\n\n See: https://github.com/resemble-ai/chatterbox/issues/96\n\n Args:\n device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n \"\"\"\n import torch\n\n # Only patch if we're loading on a non-CUDA device\n if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n original_torch_load = torch.load\n\n def patched_torch_load(f, map_location=None, **kwargs):\n # If no map_location specified, default to CPU for safe loading\n if map_location is None:\n map_location = \"cpu\"\n return original_torch_load(f, map_location=map_location, **kwargs)\n\n torch.load = patched_torch_load\n try:\n yield\n finally:\n torch.load = original_torch_load\n else:\n # No patching needed for CUDA devices\n yield\n\n\nclass HuggingFaceTokenError(RuntimeError):\n \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n pass\n\n\nclass CUDANotAvailableError(RuntimeError):\n \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n pass\n\n\nclass ChatterboxEngine(TTSEngine):\n \"\"\"TTS engine using Resemble AI's Chatterbox models.\n\n Supports three model variants:\n - Turbo: Fast, English-only, 350M parameters\n - Standard: English with CFG tuning, 500M parameters\n - Multilingual: 23+ languages, 500M parameters\n \"\"\"\n\n # Supported languages for the multilingual model\n MULTI************UAGES = [\n \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n \"sw\", \"tr\", \"zh\"\n ]\n\n def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n\n @property\n def name(self) -> str:\n \"\"\"Get the engine name.\"\"\"\n return \"chatterbox\"\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n logger.info(f\"CUDA available: {device_name}\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _validate_device(self, requested_device: str) -> str:\n \"\"\"Validate the requested device and return a valid device.\n\n If the requested device is not available, falls back to CPU with a warning.\n\n Args:\n requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n\n Returns:\n A valid device string that PyTorch can use.\n \"\"\"\n import torch\n\n if requested_device == \"auto\":\n return self._detect_best_device()\n\n if requested_device == \"cuda\":\n if not torch.cuda.is_available():\n logger.warning(\n \"GPU (CUDA) was requested but is not available. \"\n \"This can happen if:\\n\"\n \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n \" - PyTorch was not installed with CUDA support\\n\"\n \" - CUDA drivers are not properly installed\\n\"\n \"Falling back to CPU mode.\"\n )\n return \"cpu\"\n return \"cuda\"\n\n if requested_device == \"mps\":\n if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n return \"cpu\"\n return \"mps\"\n\n return requested_device # \"cpu\" or unknown\n\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n\n # Set HF_TOKEN environment variable if provided in config\n # This helps the turbo model which requires token=True by default\n if hasattr(config, 'hf_token') and config.hf_token:\n os.environ[\"HF_TOKEN\"] = config.hf_token\n logger.info(\"HuggingFace token configured from settings\")\n\n try:\n if config.model_type == \"turbo\":\n from chatterbox.tts_turbo import ChatterboxTurboTTS\n self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n\n elif config.model_type == \"multilingual\":\n from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n # Use patch to handle CUDA-saved models on CPU/MPS devices\n # See: https://github.com/resemble-ai/chatterbox/issues/96\n with _patch_torch_load_for_cpu(device):\n self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n\n else: # standard\n from chatterbox.tts import ChatterboxTTS\n self._model = ChatterboxTTS.from_pretrained(device=device)\n\n self._initialized = True\n logger.info(\"Chatterbox model initialized successfully\")\n\n except Exception as e:\n error_msg = str(e)\n logger.error(f\"Failed to initialize Chatterbox: {e}\")\n\n # Check for HuggingFace token errors\n if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n raise HuggingFaceTokenError(\n \"HuggingFace token is required to download the model.\\n\\n\"\n \"Please do one of the following:\\n\"\n \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n \"2. Set the HF_TOKEN environment variable\\n\"\n \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n \"Get your token at: https://huggingface.co/settings/tokens\"\n ) from e\n\n # Check for CUDA loading errors on CPU machines or AMD GPU users\n if (\"torch.cuda.is_available() is False\" in error_msg or\n \"CUDA device\" in error_msg or\n \"Torch not compiled with CUDA enabled\" in error_msg):\n raise CUDANotAvailableError(\n \"GPU acceleration is not available on this system.\\n\\n\"\n \"Possible reasons:\\n\"\n \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n \"- PyTorch was installed without CUDA support\\n\"\n \"- NVIDIA drivers are not installed\\n\\n\"\n \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n \"The application will work on CPU, though slower.\"\n ) from e\n\n raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized.\"\"\"\n return self._initialized and self._model is not None\n\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\"\"\"\n if self._config and self._config.model_type == \"multilingual\":\n return self.MULTILINGUAL_LANGUAGES\n return [\"en\"] # Turbo and standard are English-only\n\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n\n Raises:\n RuntimeError: If synthesis fails or engine not initialized.\n \"\"\"\n if not self.is_initialized():\n raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n\n import torch\n import torchaudio\n\n # Split text into chunks for long texts\n chunks = self._split_into_chunks(text, self._config.chunk_size)\n total_chunks = len(chunks)\n\n logger.info(f\"Synthesizing {total_chunks} chunks\")\n\n audio_segments = []\n sample_rate = self._model.sr\n was_cancelled = False\n chunks_completed = 0\n chunk_times = [] # Track time for each chunk to estimate remaining time\n start_time = time.time()\n\n for i, chunk in enumerate(chunks):\n # Check for cancellation before processing each chunk\n if cancel_check and cancel_check():\n logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n was_cancelled = True\n break\n\n # Calculate estimated remaining time based on average chunk time\n estimated_remaining = None\n if chunk_times:\n avg_chunk_time = sum(chunk_times) / len(chunk_times)\n remaining_chunks = total_chunks - i\n estimated_remaining = avg_chunk_time * remaining_chunks\n\n if progress_callback:\n progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n\n chunk_start_time = time.time()\n\n if not chunk.strip():\n continue\n\n try:\n # Generate audio for this chunk\n wav = self._generate_chunk(chunk)\n audio_segments.append(wav)\n chunks_completed += 1\n\n # Track chunk processing time for estimation\n chunk_time = time.time() - chunk_start_time\n chunk_times.append(chunk_time)\n logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n\n except Exception as e:\n logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n # Continue with other chunks\n continue\n\n # Handle case where no audio was generated\n if not audio_segments:\n if was_cancelled:\n raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n raise RuntimeError(\"No audio was generated\")\n\n # Concatenate all audio segments\n if len(audio_segments) == 1:\n final_audio = audio_segments[0]\n else:\n # Add small silence between segments\n silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n padded_segments = []\n for seg in audio_segments:\n padded_segments.append(seg)\n padded_segments.append(silence)\n # Remove last silence\n padded_segments = padded_segments[:-1]\n final_audio = torch.cat(padded_segments, dim=1)\n\n # Save to file\n output_path = Path(output_path)\n output_path.parent.mkdir(parents=True, exist_ok=True)\n torchaudio.save(str(output_path), final_audio, sample_rate)\n\n # Calculate duration\n duration = final_audio.shape[1] / sample_rate\n\n if progress_callback:\n if was_cancelled:\n progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n else:\n progress_callback(total_chunks, total_chunks, \"Complete\", None)\n\n return TTSResult(\n audio_path=output_path,\n duration_seconds=duration,\n sample_rate=sample_rate,\n text_processed=text,\n was_cancelled=was_cancelled,\n chunks_completed=chunks_completed,\n chunks_total=total_chunks\n )\n\n def _generate_chunk(self, text: str):\n \"\"\"Generate audio for a single text chunk.\n\n Args:\n text: The text chunk to synthesize.\n\n Returns:\n Audio tensor.\n \"\"\"\n voice_ref = None\n if self._config.voice_reference:\n voice_ref = str(self._config.voice_reference)\n\n if self._config.model_type == \"multilingual\":\n # Multilingual model requires language_id\n wav = self._model.generate(\n text,\n audio_prompt_path=voice_ref,\n language_id=self._config.language\n )\n elif voice_ref:\n # With voice reference\n wav = self._model.generate(text, audio_prompt_path=voice_ref)\n else:\n # Without voice reference\n wav = self._model.generate(text)\n\n return wav\n\n def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split text into chunks at natural boundaries.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per chunk.\n\n Returns:\n List of text chunks.\n \"\"\"\n if len(text) <= max_chars:\n return [text]\n\n chunks = []\n current_chunk = \"\"\n\n # Split by sentences first\n sentences = self._split_sentences(text)\n\n for sentence in sentences:\n if len(current_chunk) + len(sentence) <= max_chars:\n current_chunk += sentence\n else:\n if current_chunk:\n chunks.append(current_chunk.strip())\n # If single sentence is too long, split by phrases\n if len(sentence) > max_chars:\n phrases = self._split_phrases(sentence, max_chars)\n chunks.extend(phrases[:-1])\n current_chunk = phrases[-1] if phrases else \"\"\n else:\n current_chunk = sentence\n\n if current_chunk.strip():\n chunks.append(current_chunk.strip())\n\n return chunks\n\n def _split_sentences(self, text: str) -> list[str]:\n \"\"\"Split text into sentences.\n\n Args:\n text: The text to split.\n\n Returns:\n List of sentences.\n \"\"\"\n import re\n\n # Split on sentence-ending punctuation\n sentences = re.split(r'(?<=[.!?])\\s+', text)\n return sentences\n\n def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split a long sentence into smaller phrases.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per phrase.\n\n Returns:\n List of phrases.\n \"\"\"\n import re\n\n # Split on commas, semicolons, and other natural breaks\n parts = re.split(r'(?<=[,;:])\\s+', text)\n\n phrases = []\n current_phrase = \"\"\n\n for part in parts:\n if len(current_phrase) + len(part) <= max_chars:\n current_phrase += \" \" + part if current_phrase else part\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n # If still too long, force split\n if len(part) > max_chars:\n words = part.split()\n current_phrase = \"\"\n for word in words:\n if len(current_phrase) + len(word) + 1 <= max_chars:\n current_phrase += \" \" + word if current_phrase else word\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n current_phrase = word\n else:\n current_phrase = part\n\n if current_phrase.strip():\n phrases.append(current_phrase.strip())\n\n return phrases\n","numLines":488,"startLine":1,"totalLines":488}}} | |
| [2025-12-29T13:28:13.725Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
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| { | |
| "tool_use_id": "toolu_01WMxWkL4TxG1C1zj4v8ahPd", | |
| "type": "tool_result", | |
| "content": " 1→\"\"\"Language detection utilities for multilingual text processing.\"\"\"\n 2→\n 3→import re\n 4→import logging\n 5→from typing import Optional\n 6→\n 7→logger = logging.getLogger(__name__)\n 8→\n 9→\n 10→# Unicode ranges for common scripts\n 11→SCRIPT_RANGES = {\n 12→ 'cyrillic': (0x0400, 0x04FF), # Russian, Ukrainian, etc.\n 13→ 'latin': (0x0041, 0x007A), # Basic Latin letters\n 14→ 'cjk': (0x4E00, 0x9FFF), # Chinese characters\n 15→ 'hiragana': (0x3040, 0x309F), # Japanese Hiragana\n 16→ 'katakana': (0x30A0, 0x30FF), # Japanese Katakana\n 17→ 'hangul': (0xAC00, 0xD7AF), # Korean\n 18→ 'arabic': (0x0600, 0x06FF), # Arabic\n 19→ 'devanagari': (0x0900, 0x097F), # Hindi/Sanskrit\n 20→ 'greek': (0x0370, 0x03FF), # Greek\n 21→ 'hebrew': (0x0590, 0x05FF), # Hebrew\n 22→}\n 23→\n 24→\n 25→def detect_script(text: str) -> dict[str, int]:\n 26→ \"\"\"Detect which scripts are present in text and their character counts.\n 27→\n 28→ Args:\n 29→ text: The text to analyze.\n 30→\n 31→ Returns:\n 32→ Dictionary mapping script names to character counts.\n 33→ \"\"\"\n 34→ script_counts = {script: 0 for script in SCRIPT_RANGES}\n 35→ script_counts['other'] = 0\n 36→\n 37→ for char in text:\n 38→ code_point = ord(char)\n 39→\n 40→ # Skip whitespace and common punctuation\n 41→ if char.isspace() or char in '.,!?;:\\'\"()-[]{}':\n 42→ continue\n 43→\n 44→ found = False\n 45→ for script, (start, end) in SCRIPT_RANGES.items():\n 46→ if start <= code_point <= end:\n 47→ script_counts[script] += 1\n 48→ found = True\n 49→ break\n 50→\n 51→ if not found:\n 52→ script_counts['other'] += 1\n 53→\n 54→ return script_counts\n 55→\n 56→\n 57→def detect_primary_language(text: str) -> str:\n 58→ \"\"\"Detect the primary language of text based on script analysis.\n 59→\n 60→ This is a simple heuristic-based detector that works by analyzing\n 61→ the scripts used in the text. For more accurate detection, consider\n 62→ using a proper language detection library.\n 63→\n 64→ Args:\n 65→ text: The text to analyze.\n 66→\n 67→ Returns:\n 68→ Language code (e.g., \"en\", \"ru\", \"zh\", \"ja\", \"ko\", \"ar\", \"hi\").\n 69→ Defaults to \"en\" if detection fails.\n 70→ \"\"\"\n 71→ script_counts = detect_script(text)\n 72→\n 73→ # Remove zero counts and 'other'\n 74→ active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n 75→\n 76→ if not active_scripts:\n 77→ logger.debug(\"No script detected, defaulting to English\")\n 78→ return \"en\"\n 79→\n 80→ # Find the dominant script\n 81→ dominant_script = max(active_scripts, key=active_scripts.get)\n 82→ total_chars = sum(active_scripts.values())\n 83→ dominant_percentage = active_scripts[dominant_script] / total_chars * 100\n 84→\n 85→ logger.debug(f\"Script analysis: {active_scripts}\")\n 86→ logger.debug(f\"Dominant script: {dominant_script} ({dominant_percentage:.1f}%)\")\n 87→\n 88→ # Map scripts to language codes\n 89→ script_to_lang = {\n 90→ 'cyrillic': 'ru',\n 91→ 'latin': 'en', # Default for Latin script\n 92→ 'cjk': 'zh',\n 93→ 'hiragana': 'ja',\n 94→ 'katakana': 'ja',\n 95→ 'hangul': 'ko',\n 96→ 'arabic': 'ar',\n 97→ 'devanagari': 'hi',\n 98→ 'greek': 'el',\n 99→ 'hebrew': 'he',\n 100→ }\n 101→\n 102→ detected_lang = script_to_lang.get(dominant_script, 'en')\n 103→ logger.info(f\"Detected primary language: {detected_lang} (from {dominant_script} script)\")\n 104→\n 105→ return detected_lang\n 106→\n 107→\n 108→def is_mixed_language_text(text: str, threshold: float = 0.1) -> bool:\n 109→ \"\"\"Check if text contains significant portions of multiple scripts.\n 110→\n 111→ Args:\n 112→ text: The text to analyze.\n 113→ threshold: Minimum percentage (0-1) of non-dominant script to be considered mixed.\n 114→\n 115→ Returns:\n 116→ True if text contains significant portions of multiple scripts.\n 117→ \"\"\"\n 118→ script_counts = detect_script(text)\n 119→\n 120→ # Remove zero counts and 'other'\n 121→ active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n 122→\n 123→ if len(active_scripts) <= 1:\n 124→ return False\n 125→\n 126→ total_chars = sum(active_scripts.values())\n 127→ if total_chars == 0:\n 128→ return False\n 129→\n 130→ # Sort by count (descending)\n 131→ sorted_scripts = sorted(active_scripts.items(), key=lambda x: x[1], reverse=True)\n 132→\n 133→ # Check if second-most-common script exceeds threshold\n 134→ if len(sorted_scripts) >= 2:\n 135→ second_percentage = sorted_scripts[1][1] / total_chars\n 136→ return second_percentage >= threshold\n 137→\n 138→ return False\n 139→\n 140→\n 141→def get_language_name(code: str) -> str:\n 142→ \"\"\"Get the human-readable name for a language code.\n 143→\n 144→ Args:\n 145→ code: ISO 639-1 language code (e.g., \"en\", \"ru\").\n 146→\n 147→ Returns:\n 148→ Human-readable language name.\n 149→ \"\"\"\n 150→ names = {\n 151→ \"ar\": \"Arabic\",\n 152→ \"da\": \"Danish\",\n 153→ \"de\": \"German\",\n 154→ \"el\": \"Greek\",\n 155→ \"en\": \"English\",\n 156→ \"es\": \"Spanish\",\n 157→ \"fi\": \"Finnish\",\n 158→ \"fr\": \"French\",\n 159→ \"he\": \"Hebrew\",\n 160→ \"hi\": \"Hindi\",\n 161→ \"it\": \"Italian\",\n 162→ \"ja\": \"Japanese\",\n 163→ \"ko\": \"Korean\",\n 164→ \"ms\": \"Malay\",\n 165→ \"nl\": \"Dutch\",\n 166→ \"no\": \"Norwegian\",\n 167→ \"pl\": \"Polish\",\n 168→ \"pt\": \"Portuguese\",\n 169→ \"ru\": \"Russian\",\n 170→ \"sv\": \"Swedish\",\n 171→ \"sw\": \"Swahili\",\n 172→ \"tr\": \"Turkish\",\n 173→ \"zh\": \"Chinese\",\n 174→ }\n 175→ return names.get(code, code.upper())\n 176→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "464b4681-b801-471d-8c3c-b5d10fca388f", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/utils/language_detection.py", | |
| "content": "\"\"\"Language detection utilities for multilingual text processing.\"\"\"\n\nimport re\nimport logging\nfrom typing import Optional\n\nlogger = logging.getLogger(__name__)\n\n\n# Unicode ranges for common scripts\nSCRIPT_RANGES = {\n 'cyrillic': (0x0400, 0x04FF), # Russian, Ukrainian, etc.\n 'latin': (0x0041, 0x007A), # Basic Latin letters\n 'cjk': (0x4E00, 0x9FFF), # Chinese characters\n 'hiragana': (0x3040, 0x309F), # Japanese Hiragana\n 'katakana': (0x30A0, 0x30FF), # Japanese Katakana\n 'hangul': (0xAC00, 0xD7AF), # Korean\n 'arabic': (0x0600, 0x06FF), # Arabic\n 'devanagari': (0x0900, 0x097F), # Hindi/Sanskrit\n 'greek': (0x0370, 0x03FF), # Greek\n 'hebrew': (0x0590, 0x05FF), # Hebrew\n}\n\n\ndef detect_script(text: str) -> dict[str, int]:\n \"\"\"Detect which scripts are present in text and their character counts.\n\n Args:\n text: The text to analyze.\n\n Returns:\n Dictionary mapping script names to character counts.\n \"\"\"\n script_counts = {script: 0 for script in SCRIPT_RANGES}\n script_counts['other'] = 0\n\n for char in text:\n code_point = ord(char)\n\n # Skip whitespace and common punctuation\n if char.isspace() or char in '.,!?;:\\'\"()-[]{}':\n continue\n\n found = False\n for script, (start, end) in SCRIPT_RANGES.items():\n if start <= code_point <= end:\n script_counts[script] += 1\n found = True\n break\n\n if not found:\n script_counts['other'] += 1\n\n return script_counts\n\n\ndef detect_primary_language(text: str) -> str:\n \"\"\"Detect the primary language of text based on script analysis.\n\n This is a simple heuristic-based detector that works by analyzing\n the scripts used in the text. For more accurate detection, consider\n using a proper language detection library.\n\n Args:\n text: The text to analyze.\n\n Returns:\n Language code (e.g., \"en\", \"ru\", \"zh\", \"ja\", \"ko\", \"ar\", \"hi\").\n Defaults to \"en\" if detection fails.\n \"\"\"\n script_counts = detect_script(text)\n\n # Remove zero counts and 'other'\n active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n\n if not active_scripts:\n logger.debug(\"No script detected, defaulting to English\")\n return \"en\"\n\n # Find the dominant script\n dominant_script = max(active_scripts, key=active_scripts.get)\n total_chars = sum(active_scripts.values())\n dominant_percentage = active_scripts[dominant_script] / total_chars * 100\n\n logger.debug(f\"Script analysis: {active_scripts}\")\n logger.debug(f\"Dominant script: {dominant_script} ({dominant_percentage:.1f}%)\")\n\n # Map scripts to language codes\n script_to_lang = {\n 'cyrillic': 'ru',\n 'latin': 'en', # Default for Latin script\n 'cjk': 'zh',\n 'hiragana': 'ja',\n 'katakana': 'ja',\n 'hangul': 'ko',\n 'arabic': 'ar',\n 'devanagari': 'hi',\n 'greek': 'el',\n 'hebrew': 'he',\n }\n\n detected_lang = script_to_lang.get(dominant_script, 'en')\n logger.info(f\"Detected primary language: {detected_lang} (from {dominant_script} script)\")\n\n return detected_lang\n\n\ndef is_mixed_language_text(text: str, threshold: float = 0.1) -> bool:\n \"\"\"Check if text contains significant portions of multiple scripts.\n\n Args:\n text: The text to analyze.\n threshold: Minimum percentage (0-1) of non-dominant script to be considered mixed.\n\n Returns:\n True if text contains significant portions of multiple scripts.\n \"\"\"\n script_counts = detect_script(text)\n\n # Remove zero counts and 'other'\n active_scripts = {k: v for k, v in script_counts.items() if v > 0 and k != 'other'}\n\n if len(active_scripts) <= 1:\n return False\n\n total_chars = sum(active_scripts.values())\n if total_chars == 0:\n return False\n\n # Sort by count (descending)\n sorted_scripts = sorted(active_scripts.items(), key=lambda x: x[1], reverse=True)\n\n # Check if second-most-common script exceeds threshold\n if len(sorted_scripts) >= 2:\n second_percentage = sorted_scripts[1][1] / total_chars\n return second_percentage >= threshold\n\n return False\n\n\ndef get_language_name(code: str) -> str:\n \"\"\"Get the human-readable name for a language code.\n\n Args:\n code: ISO 639-1 language code (e.g., \"en\", \"ru\").\n\n Returns:\n Human-readable language name.\n \"\"\"\n names = {\n \"ar\": \"Arabic\",\n \"da\": \"Danish\",\n \"de\": \"German\",\n \"el\": \"Greek\",\n \"en\": \"English\",\n \"es\": \"Spanish\",\n \"fi\": \"Finnish\",\n \"fr\": \"French\",\n \"he\": \"Hebrew\",\n \"hi\": \"Hindi\",\n \"it\": \"Italian\",\n \"ja\": \"Japanese\",\n \"ko\": \"Korean\",\n \"ms\": \"Malay\",\n \"nl\": \"Dutch\",\n \"no\": \"Norwegian\",\n \"pl\": \"Polish\",\n \"pt\": \"Portuguese\",\n \"ru\": \"Russian\",\n \"sv\": \"Swedish\",\n \"sw\": \"Swahili\",\n \"tr\": \"Turkish\",\n \"zh\": \"Chinese\",\n }\n return names.get(code, code.upper())\n", | |
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| } | |
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| } | |
| [2025-12-29T13:28:13.742Z] [INFO] { | |
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| "tool_use_id": "toolu_01NixcgQRvFkJK21VkVmPszQ", | |
| "type": "tool_result", | |
| "content": " 1→\"\"\"Symbol and number preprocessing for TTS readability.\"\"\"\n 2→\n 3→import re\n 4→from typing import Optional\n 5→\n 6→from .base import TextPreprocessor, ProcessingContext\n 7→\n 8→\n 9→class SymbolConverter(TextPreprocessor):\n 10→ \"\"\"Preprocessor that converts symbols and numbered points to readable text.\n 11→\n 12→ This preprocessor handles:\n 13→ - Mathematical symbols: =, +, -, *, /, <, >, %, etc.\n 14→ - Numbered lists: 1. 2. 3. or 1) 2) 3) patterns\n 15→ - Bullet points: -, *, •\n 16→ - Special characters: @, #, &, etc.\n 17→\n 18→ The goal is to make the text more natural for TTS synthesis by converting\n 19→ symbols that would otherwise be skipped or mispronounced.\n 20→ \"\"\"\n 21→\n 22→ # Symbol to spoken text mapping\n 23→ SYMBOL_MAP = {\n 24→ # Mathematical operators\n 25→ '=': ' equals ',\n 26→ '+': ' plus ',\n 27→ '-': ' minus ', # Will be handled carefully to avoid conflicts with hyphens\n 28→ '*': ' times ', # Will be handled carefully to avoid bullet point conflicts\n 29→ '/': ' divided by ',\n 30→ '%': ' percent',\n 31→ '<': ' less than ',\n 32→ '>': ' greater than ',\n 33→ '<=': ' less than or equal to ',\n 34→ '>=': ' greater than or equal to ',\n 35→ '!=': ' not equal to ',\n 36→ '==': ' equals ',\n 37→ '→': ' arrow ',\n 38→ '←': ' arrow ',\n 39→ '↔': ' bidirectional arrow ',\n 40→\n 41→ # Currency symbols\n 42→ '$': ' dollars ',\n 43→ '€': ' euros ',\n 44→ '£': ' pounds ',\n 45→ '¥': ' yen ',\n 46→ '₽': ' rubles ',\n 47→\n 48→ # Common special characters\n 49→ '@': ' at ',\n 50→ '&': ' and ',\n 51→ '#': ' number ',\n 52→\n 53→ # Bullets and list markers\n 54→ '•': ', ',\n 55→ '◦': ', ',\n 56→ '▪': ', ',\n 57→ '▸': ', ',\n 58→ '►': ', ',\n 59→ }\n 60→\n 61→ # Russian symbol map\n 62→ SYMBOL_MAP_RU = {\n 63→ '=': ' равно ',\n 64→ '+': ' плюс ',\n 65→ '-': ' минус ',\n 66→ '*': ' умножить на ',\n 67→ '/': ' делить на ',\n 68→ '%': ' процент',\n 69→ '<': ' меньше чем ',\n 70→ '>': ' больше чем ',\n 71→ '→': ' стрелка ',\n 72→ '←': ' стрелка ',\n 73→ '$': ' долларов ',\n 74→ '€': ' евро ',\n 75→ '£': ' фунтов ',\n 76→ '¥': ' иен ',\n 77→ '₽': ' рублей ',\n 78→ '@': ' собака ',\n 79→ '&': ' и ',\n 80→ '#': ' номер ',\n 81→ }\n 82→\n 83→ @property\n 84→ def name(self) -> str:\n 85→ \"\"\"Return the preprocessor name.\"\"\"\n 86→ return \"symbol_converter\"\n 87→\n 88→ def process(self, text: str, context: ProcessingContext) -> str:\n 89→ \"\"\"Process symbols and numbered points in text.\n 90→\n 91→ Args:\n 92→ text: The text to process.\n 93→ context: Processing context (unused in this preprocessor).\n 94→\n 95→ Returns:\n 96→ Text with symbols converted to readable words.\n 97→ \"\"\"\n 98→ result = text\n 99→\n 100→ # Convert numbered lists (1. 2. 3. or 1) 2) 3))\n 101→ result = self._convert_numbered_lists(result)\n 102→\n 103→ # Convert mathematical expressions\n 104→ result = self._convert_math_expressions(result)\n 105→\n 106→ # Convert standalone symbols\n 107→ result = self._convert_standalone_symbols(result)\n 108→\n 109→ # Clean up multiple spaces\n 110→ result = re.sub(r' +', ' ', result)\n 111→\n 112→ return result\n 113→\n 114→ def _convert_numbered_lists(self, text: str) -> str:\n 115→ \"\"\"Convert numbered list patterns to speakable text.\n 116→\n 117→ Args:\n 118→ text: The text to process.\n 119→\n 120→ Returns:\n 121→ Text with numbered lists converted.\n 122→ \"\"\"\n 123→ result = text\n 124→\n 125→ # Convert \"1.\" or \"1)\" at start of line or after newline\n 126→ # Pattern: start of line, optional whitespace, number, period or paren\n 127→ def replace_numbered_point(match):\n 128→ leading = match.group(1) or \"\"\n 129→ number = match.group(2)\n 130→ separator = match.group(3)\n 131→ trailing = match.group(4) or \"\"\n 132→\n 133→ # Use \"point\" for period, just the number for parenthesis\n 134→ if separator == '.':\n 135→ return f\"{leading}Point {number}.{trailing}\"\n 136→ else: # )\n 137→ return f\"{leading}{number}.{trailing}\"\n 138→\n 139→ # Match numbered lists at start of line\n 140→ result = re.sub(\n 141→ r'(^|\\n)(\\d{1,3})([.\\)])(\\s*)',\n 142→ replace_numbered_point,\n 143→ result\n 144→ )\n 145→\n 146→ return result\n 147→\n 148→ def _convert_math_expressions(self, text: str) -> str:\n 149→ \"\"\"Convert mathematical expressions to speakable text.\n 150→\n 151→ Args:\n 152→ text: The text to process.\n 153→\n 154→ Returns:\n 155→ Text with math expressions converted.\n 156→ \"\"\"\n 157→ result = text\n 158→\n 159→ # Convert multi-character operators first\n 160→ result = result.replace('>=', ' greater than or equal to ')\n 161→ result = result.replace('<=', ' less than or equal to ')\n 162→ result = result.replace('!=', ' not equal to ')\n 163→ result = result.replace('==', ' equals ')\n 164→\n 165→ # Convert equations like \"x = 5\" or \"a + b = c\"\n 166→ # Match: something = something (with spaces around equals)\n 167→ result = re.sub(\n 168→ r'(\\w+)\\s*=\\s*(\\w+)',\n 169→ r'\\1 equals \\2',\n 170→ result\n 171→ )\n 172→\n 173→ # Convert standalone = signs (not in URLs or paths)\n 174→ # Only convert if surrounded by spaces or at word boundaries\n 175→ result = re.sub(r'(?<=\\s)=(?=\\s)', ' equals ', result)\n 176→\n 177→ # Convert + signs in mathematical context\n 178→ result = re.sub(r'(\\d+)\\s*\\+\\s*(\\d+)', r'\\1 plus \\2', result)\n 179→\n 180→ # Convert percentage patterns like \"50%\" or \"100%\"\n 181→ result = re.sub(r'(\\d+)%', r'\\1 percent', result)\n 182→\n 183→ return result\n 184→\n 185→ def _convert_standalone_symbols(self, text: str) -> str:\n 186→ \"\"\"Convert standalone symbols to speakable text.\n 187→\n 188→ Args:\n 189→ text: The text to process.\n 190→\n 191→ Returns:\n 192→ Text with standalone symbols converted.\n 193→ \"\"\"\n 194→ result = text\n 195→\n 196→ # Convert currency amounts\n 197→ result = re.sub(r'\\$(\\d+(?:\\.\\d{2})?)', r'\\1 dollars', result)\n 198→ result = re.sub(r'€(\\d+(?:\\.\\d{2})?)', r'\\1 euros', result)\n 199→ result = re.sub(r'£(\\d+(?:\\.\\d{2})?)', r'\\1 pounds', result)\n 200→ result = re.sub(r'₽(\\d+(?:\\.\\d{2})?)', r'\\1 rubles', result)\n 201→\n 202→ # Convert bullet points at start of lines\n 203→ result = re.sub(r'(^|\\n)\\s*[•◦▪▸►]\\s*', r'\\1', result)\n 204→\n 205→ # Convert standalone & to \"and\"\n 206→ result = re.sub(r'\\s+&\\s+', ' and ', result)\n 207→\n 208→ # Convert # followed by numbers (like #1, #42)\n 209→ result = re.sub(r'#(\\d+)', r'number \\1', result)\n 210→\n 211→ # Convert arrows\n 212→ result = result.replace('→', ' arrow ')\n 213→ result = result.replace('←', ' arrow ')\n 214→ result = result.replace('->', ' arrow ')\n 215→ result = result.replace('<-', ' arrow ')\n 216→\n 217→ return result\n 218→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "eed83e3d-c992-4fdb-bc3b-683d19c9d91b", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/preprocessors/symbols.py", | |
| "content": "\"\"\"Symbol and number preprocessing for TTS readability.\"\"\"\n\nimport re\nfrom typing import Optional\n\nfrom .base import TextPreprocessor, ProcessingContext\n\n\nclass SymbolConverter(TextPreprocessor):\n \"\"\"Preprocessor that converts symbols and numbered points to readable text.\n\n This preprocessor handles:\n - Mathematical symbols: =, +, -, *, /, <, >, %, etc.\n - Numbered lists: 1. 2. 3. or 1) 2) 3) patterns\n - Bullet points: -, *, •\n - Special characters: @, #, &, etc.\n\n The goal is to make the text more natural for TTS synthesis by converting\n symbols that would otherwise be skipped or mispronounced.\n \"\"\"\n\n # Symbol to spoken text mapping\n SYMBOL_MAP = {\n # Mathematical operators\n '=': ' equals ',\n '+': ' plus ',\n '-': ' minus ', # Will be handled carefully to avoid conflicts with hyphens\n '*': ' times ', # Will be handled carefully to avoid bullet point conflicts\n '/': ' divided by ',\n '%': ' percent',\n '<': ' less than ',\n '>': ' greater than ',\n '<=': ' less than or equal to ',\n '>=': ' greater than or equal to ',\n '!=': ' not equal to ',\n '==': ' equals ',\n '→': ' arrow ',\n '←': ' arrow ',\n '↔': ' bidirectional arrow ',\n\n # Currency symbols\n '$': ' dollars ',\n '€': ' euros ',\n '£': ' pounds ',\n '¥': ' yen ',\n '₽': ' rubles ',\n\n # Common special characters\n '@': ' at ',\n '&': ' and ',\n '#': ' number ',\n\n # Bullets and list markers\n '•': ', ',\n '◦': ', ',\n '▪': ', ',\n '▸': ', ',\n '►': ', ',\n }\n\n # Russian symbol map\n SYMBOL_MAP_RU = {\n '=': ' равно ',\n '+': ' плюс ',\n '-': ' минус ',\n '*': ' умножить на ',\n '/': ' делить на ',\n '%': ' процент',\n '<': ' меньше чем ',\n '>': ' больше чем ',\n '→': ' стрелка ',\n '←': ' стрелка ',\n '$': ' долларов ',\n '€': ' евро ',\n '£': ' фунтов ',\n '¥': ' иен ',\n '₽': ' рублей ',\n '@': ' собака ',\n '&': ' и ',\n '#': ' номер ',\n }\n\n @property\n def name(self) -> str:\n \"\"\"Return the preprocessor name.\"\"\"\n return \"symbol_converter\"\n\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Process symbols and numbered points in text.\n\n Args:\n text: The text to process.\n context: Processing context (unused in this preprocessor).\n\n Returns:\n Text with symbols converted to readable words.\n \"\"\"\n result = text\n\n # Convert numbered lists (1. 2. 3. or 1) 2) 3))\n result = self._convert_numbered_lists(result)\n\n # Convert mathematical expressions\n result = self._convert_math_expressions(result)\n\n # Convert standalone symbols\n result = self._convert_standalone_symbols(result)\n\n # Clean up multiple spaces\n result = re.sub(r' +', ' ', result)\n\n return result\n\n def _convert_numbered_lists(self, text: str) -> str:\n \"\"\"Convert numbered list patterns to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with numbered lists converted.\n \"\"\"\n result = text\n\n # Convert \"1.\" or \"1)\" at start of line or after newline\n # Pattern: start of line, optional whitespace, number, period or paren\n def replace_numbered_point(match):\n leading = match.group(1) or \"\"\n number = match.group(2)\n separator = match.group(3)\n trailing = match.group(4) or \"\"\n\n # Use \"point\" for period, just the number for parenthesis\n if separator == '.':\n return f\"{leading}Point {number}.{trailing}\"\n else: # )\n return f\"{leading}{number}.{trailing}\"\n\n # Match numbered lists at start of line\n result = re.sub(\n r'(^|\\n)(\\d{1,3})([.\\)])(\\s*)',\n replace_numbered_point,\n result\n )\n\n return result\n\n def _convert_math_expressions(self, text: str) -> str:\n \"\"\"Convert mathematical expressions to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with math expressions converted.\n \"\"\"\n result = text\n\n # Convert multi-character operators first\n result = result.replace('>=', ' greater than or equal to ')\n result = result.replace('<=', ' less than or equal to ')\n result = result.replace('!=', ' not equal to ')\n result = result.replace('==', ' equals ')\n\n # Convert equations like \"x = 5\" or \"a + b = c\"\n # Match: something = something (with spaces around equals)\n result = re.sub(\n r'(\\w+)\\s*=\\s*(\\w+)',\n r'\\1 equals \\2',\n result\n )\n\n # Convert standalone = signs (not in URLs or paths)\n # Only convert if surrounded by spaces or at word boundaries\n result = re.sub(r'(?<=\\s)=(?=\\s)', ' equals ', result)\n\n # Convert + signs in mathematical context\n result = re.sub(r'(\\d+)\\s*\\+\\s*(\\d+)', r'\\1 plus \\2', result)\n\n # Convert percentage patterns like \"50%\" or \"100%\"\n result = re.sub(r'(\\d+)%', r'\\1 percent', result)\n\n return result\n\n def _convert_standalone_symbols(self, text: str) -> str:\n \"\"\"Convert standalone symbols to speakable text.\n\n Args:\n text: The text to process.\n\n Returns:\n Text with standalone symbols converted.\n \"\"\"\n result = text\n\n # Convert currency amounts\n result = re.sub(r'\\$(\\d+(?:\\.\\d{2})?)', r'\\1 dollars', result)\n result = re.sub(r'€(\\d+(?:\\.\\d{2})?)', r'\\1 euros', result)\n result = re.sub(r'£(\\d+(?:\\.\\d{2})?)', r'\\1 pounds', result)\n result = re.sub(r'₽(\\d+(?:\\.\\d{2})?)', r'\\1 rubles', result)\n\n # Convert bullet points at start of lines\n result = re.sub(r'(^|\\n)\\s*[•◦▪▸►]\\s*', r'\\1', result)\n\n # Convert standalone & to \"and\"\n result = re.sub(r'\\s+&\\s+', ' and ', result)\n\n # Convert # followed by numbers (like #1, #42)\n result = re.sub(r'#(\\d+)', r'number \\1', result)\n\n # Convert arrows\n result = result.replace('→', ' arrow ')\n result = result.replace('←', ' arrow ')\n result = result.replace('->', ' arrow ')\n result = result.replace('<-', ' arrow ')\n\n return result\n", | |
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| [2025-12-29T13:28:13.927Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01L6tvCCfRxjZNRUYPgzD3C1","type":"tool_result","content":" 1→\"\"\"Main GUI application using CustomTkinter.\"\"\"\n 2→\n 3→import logging\n 4→import threading\n 5→import traceback\n 6→from pathlib import Path\n 7→from typing import Optional\n 8→\n 9→import customtkinter as ctk\n 10→from CTkMessagebox import CTkMessagebox\n 11→\n 12→from tts_app.readers import ReaderRegistry\n 13→from tts_app.readers.registry import create_default_registry\n 14→from tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\n 15→from tts_app.preprocessors.pipeline import create_default_pipeline\n 16→from tts_app.tts import ChatterboxEngine, TTSConfig\n 17→\n 18→logger = logging.getLogger(__name__)\n 19→\n 20→\n 21→class SuccessDialog(ctk.CTkToplevel):\n 22→ \"\"\"Custom success dialog with Open File Location button.\n 23→\n 24→ This dialog displays a success message and provides buttons to open\n 25→ the file location in the file explorer.\n 26→ \"\"\"\n 27→\n 28→ def __init__(self, parent, title: str, message: str, file_path: Path):\n 29→ \"\"\"Initialize the success dialog.\n 30→\n 31→ Args:\n 32→ parent: Parent window.\n 33→ title: Dialog title.\n 34→ message: Success message.\n 35→ file_path: Path to the generated file.\n 36→ \"\"\"\n 37→ super().__init__(parent)\n 38→\n 39→ self._file_path = file_path\n 40→\n 41→ self.title(title)\n 42→ self.geometry(\"450x200\")\n 43→ self.minsize(400, 180)\n 44→ self.transient(parent)\n 45→ self.grab_set()\n 46→\n 47→ # Main frame with padding\n 48→ main_frame = ctk.CTkFrame(self)\n 49→ main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n 50→\n 51→ # Success icon and title\n 52→ title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 53→ title_frame.pack(fill=\"x\", pady=(0, 10))\n 54→\n 55→ success_label = ctk.CTkLabel(\n 56→ title_frame,\n 57→ text=\"Success\",\n 58→ font=ctk.CTkFont(size=18, weight=\"bold\"),\n 59→ text_color=\"#55AA55\"\n 60→ )\n 61→ success_label.pack(side=\"left\")\n 62→\n 63→ # Message\n 64→ message_label = ctk.CTkLabel(\n 65→ main_frame,\n 66→ text=message,\n 67→ font=ctk.CTkFont(size=12),\n 68→ justify=\"left\"\n 69→ )\n 70→ message_label.pack(fill=\"x\", pady=(0, 15))\n 71→\n 72→ # Button frame\n 73→ button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 74→ button_frame.pack(fill=\"x\")\n 75→\n 76→ # Open File Location button\n 77→ open_location_btn = ctk.CTkButton(\n 78→ button_frame,\n 79→ text=\"Open File Location\",\n 80→ command=self._open_file_location,\n 81→ width=140\n 82→ )\n 83→ open_location_btn.pack(side=\"left\", padx=(0, 10))\n 84→\n 85→ # OK button\n 86→ ok_btn = ctk.CTkButton(\n 87→ button_frame,\n 88→ text=\"OK\",\n 89→ command=self.destroy,\n 90→ width=80\n 91→ )\n 92→ ok_btn.pack(side=\"right\")\n 93→\n 94→ # Center the dialog on parent\n 95→ self.update_idletasks()\n 96→ self._center_on_parent(parent)\n 97→\n 98→ def _center_on_parent(self, parent):\n 99→ \"\"\"Center this dialog on the parent window.\"\"\"\n 100→ parent_x = parent.winfo_x()\n 101→ parent_y = parent.winfo_y()\n 102→ parent_w = parent.winfo_width()\n 103→ parent_h = parent.winfo_height()\n 104→\n 105→ dialog_w = self.winfo_width()\n 106→ dialog_h = self.winfo_height()\n 107→\n 108→ x = parent_x + (parent_w - dialog_w) // 2\n 109→ y = parent_y + (parent_h - dialog_h) // 2\n 110→\n 111→ self.geometry(f\"+{x}+{y}\")\n 112→\n 113→ def _open_file_location(self):\n 114→ \"\"\"Open the file's directory in the system file explorer.\"\"\"\n 115→ import platform\n 116→ import subprocess\n 117→\n 118→ folder_path = self._file_path.parent\n 119→\n 120→ try:\n 121→ system = platform.system()\n 122→ if system == \"Windows\":\n 123→ # On Windows, use explorer with /select to highlight the file\n 124→ subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n 125→ elif system == \"Darwin\":\n 126→ # On macOS, use open command with -R to reveal the file\n 127→ subprocess.run([\"open\", \"-R\", str(self._file_path)])\n 128→ else:\n 129→ # On Linux, use xdg-open to open the folder\n 130→ subprocess.run([\"xdg-open\", str(folder_path)])\n 131→ except Exception as e:\n 132→ logger.warning(f\"Failed to open file location: {e}\")\n 133→ # Fall back to showing a message\n 134→ CTkMessagebox(\n 135→ master=self,\n 136→ title=\"Info\",\n 137→ message=f\"File is located at:\\n{folder_path}\",\n 138→ icon=\"info\",\n 139→ width=400\n 140→ )\n 141→\n 142→\n 143→class ErrorDialog(ctk.CTkToplevel):\n 144→ \"\"\"Custom error dialog with copy button for error message.\n 145→\n 146→ This dialog displays an error message and provides a button to copy\n 147→ the full error text to the clipboard.\n 148→ \"\"\"\n 149→\n 150→ def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n 151→ \"\"\"Initialize the error dialog.\n 152→\n 153→ Args:\n 154→ parent: Parent window.\n 155→ title: Dialog title.\n 156→ message: Short error message.\n 157→ full_traceback: Full traceback for copying (optional).\n 158→ \"\"\"\n 159→ super().__init__(parent)\n 160→\n 161→ self.title(title)\n 162→ self.geometry(\"500x300\")\n 163→ self.minsize(400, 200)\n 164→ self.transient(parent)\n 165→ self.grab_set()\n 166→\n 167→ # Store the full error text for copying\n 168→ self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n 169→\n 170→ # Main frame with padding\n 171→ main_frame = ctk.CTkFrame(self)\n 172→ main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n 173→\n 174→ # Error icon and title\n 175→ title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 176→ title_frame.pack(fill=\"x\", pady=(0, 10))\n 177→\n 178→ error_label = ctk.CTkLabel(\n 179→ title_frame,\n 180→ text=\"❌ Error\",\n 181→ font=ctk.CTkFont(size=18, weight=\"bold\"),\n 182→ text_color=\"#FF5555\"\n 183→ )\n 184→ error_label.pack(side=\"left\")\n 185→\n 186→ # Error message in scrollable text\n 187→ text_frame = ctk.CTkFrame(main_frame)\n 188→ text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n 189→\n 190→ self._error_textbox = ctk.CTkTextbox(\n 191→ text_frame,\n 192→ wrap=\"word\",\n 193→ font=ctk.CTkFont(size=12)\n 194→ )\n 195→ self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n 196→ self._error_textbox.insert(\"1.0\", self._error_text)\n 197→ self._error_textbox.configure(state=\"disabled\")\n 198→\n 199→ # Button frame\n 200→ button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 201→ button_frame.pack(fill=\"x\")\n 202→\n 203→ # Copy button\n 204→ copy_btn = ctk.CTkButton(\n 205→ button_frame,\n 206→ text=\"📋 Copy Error\",\n 207→ command=self._copy_to_clipboard,\n 208→ width=120\n 209→ )\n 210→ copy_btn.pack(side=\"left\", padx=(0, 10))\n 211→\n 212→ # OK button\n 213→ ok_btn = ctk.CTkButton(\n 214→ button_frame,\n 215→ text=\"OK\",\n 216→ command=self.destroy,\n 217→ width=80\n 218→ )\n 219→ ok_btn.pack(side=\"right\")\n 220→\n 221→ # Center the dialog on parent\n 222→ self.update_idletasks()\n 223→ self._center_on_parent(parent)\n 224→\n 225→ def _center_on_parent(self, parent):\n 226→ \"\"\"Center this dialog on the parent window.\"\"\"\n 227→ parent_x = parent.winfo_x()\n 228→ parent_y = parent.winfo_y()\n 229→ parent_w = parent.winfo_width()\n 230→ parent_h = parent.winfo_height()\n 231→\n 232→ dialog_w = self.winfo_width()\n 233→ dialog_h = self.winfo_height()\n 234→\n 235→ x = parent_x + (parent_w - dialog_w) // 2\n 236→ y = parent_y + (parent_h - dialog_h) // 2\n 237→\n 238→ self.geometry(f\"+{x}+{y}\")\n 239→\n 240→ def _copy_to_clipboard(self):\n 241→ \"\"\"Copy the error text to clipboard.\"\"\"\n 242→ self.clipboard_clear()\n 243→ self.clipboard_append(self._error_text)\n 244→\n 245→ # Show feedback\n 246→ CTkMessagebox(\n 247→ master=self,\n 248→ title=\"Copied\",\n 249→ message=\"Error text copied to clipboard!\",\n 250→ icon=\"check\",\n 251→ width=300\n 252→ )\n 253→\n 254→\n 255→class TTSApplication(ctk.CTk):\n 256→ \"\"\"Main application window for Text-to-Speech conversion.\n 257→\n 258→ This provides a user-friendly interface for:\n 259→ - Selecting input documents (PDF, DOCX, TXT, MD)\n 260→ - Configuring TTS options (model, language, voice reference)\n 261→ - Setting preprocessing options (ignore footnotes)\n 262→ - Converting documents to speech\n 263→ \"\"\"\n 264→\n 265→ def __init__(self):\n 266→ \"\"\"Initialize the application.\"\"\"\n 267→ super().__init__()\n 268→\n 269→ # Configure window\n 270→ self.title(\"Text to Speech with Chatterbox\")\n 271→ self.geometry(\"700x700\")\n 272→ self.minsize(600, 500)\n 273→\n 274→ # Set appearance\n 275→ ctk.set_appearance_mode(\"system\")\n 276→ ctk.set_default_color_theme(\"blue\")\n 277→\n 278→ # Initialize components\n 279→ self._reader_registry: ReaderRegistry = create_default_registry()\n 280→ self._pipeline: Prepr**********eline = create_default_pipeline()\n 281→ self._tts_engine: Optional[ChatterboxEngine] = None\n 282→ self._processing = False\n 283→ self._cancel_requested = False # Flag to signal cancellation\n 284→ self._progress_animation_id = None # Track progress bar animation\n 285→ self._button_animation_id = None # Track button ellipsis animation\n 286→ self._ellipsis_state = 0 # Current ellipsis state (0-3)\n 287→\n 288→ # Variables\n 289→ self._input_file = ctk.StringVar()\n 290→ self._output_file = ctk.StringVar()\n 291→ self._voice_reference = ctk.StringVar()\n 292→ self._model_type = ctk.StringVar(value=\"turbo\")\n 293→ self._language = ctk.StringVar(value=\"en\")\n 294→ self._ignore_footnotes = ctk.BooleanVar(value=True)\n 295→ self._device = ctk.StringVar(value=\"auto\")\n 296→ self._hf_token = ctk.StringVar()\n 297→\n 298→ # Build UI\n 299→ self._create_widgets()\n 300→\n 301→ def _create_widgets(self):\n 302→ \"\"\"Create all UI widgets.\"\"\"\n 303→ # Scrollable main container\n 304→ self._scrollable_frame = ctk.CTkScrollableFrame(self)\n 305→ self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n 306→\n 307→ # Main frame inside scrollable area\n 308→ main_frame = ctk.CTkFrame(self._scrollable_frame)\n 309→ main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n 310→\n 311→ # Title\n 312→ title_label = ctk.CTkLabel(\n 313→ main_frame,\n 314→ text=\"Document to Speech Converter\",\n 315→ font=ctk.CTkFont(size=24, weight=\"bold\")\n 316→ )\n 317→ title_label.pack(pady=(0, 20))\n 318→\n 319→ # Input file section\n 320→ self._create_file_section(\n 321→ main_frame,\n 322→ \"Input Document:\",\n 323→ self._input_file,\n 324→ self._browse_input,\n 325→ self._get_input_filetypes()\n 326→ )\n 327→\n 328→ # Output file section\n 329→ self._create_file_section(\n 330→ main_frame,\n 331→ \"Output Audio File:\",\n 332→ self._output_file,\n 333→ self._browse_output,\n 334→ [(\"WAV files\", \"*.wav\")],\n 335→ save=True\n 336→ )\n 337→\n 338→ # Voice reference section (optional)\n 339→ voice_frame = ctk.CTkFrame(main_frame)\n 340→ voice_frame.pack(fill=\"x\", pady=(10, 0))\n 341→\n 342→ voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n 343→ voice_label.pack(anchor=\"w\")\n 344→\n 345→ voice_input_frame = ctk.CTkFrame(voice_frame)\n 346→ voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n 347→\n 348→ voice_entry = ctk.CTkEntry(\n 349→ voice_input_frame,\n 350→ textvariable=self._voice_reference,\n 351→ placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n 352→ )\n 353→ voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n 354→\n 355→ voice_btn = ctk.CTkButton(\n 356→ voice_input_frame,\n 357→ text=\"Browse\",\n 358→ command=self._browse_voice_reference,\n 359→ width=100\n 360→ )\n 361→ voice_btn.pack(side=\"right\")\n 362→\n 363→ clear_btn = ctk.CTkButton(\n 364→ voice_input_frame,\n 365→ text=\"Clear\",\n 366→ command=lambda: self._voice_reference.set(\"\"),\n 367→ width=60,\n 368→ fg_color=\"gray\"\n 369→ )\n 370→ clear_btn.pack(side=\"right\", padx=(0, 5))\n 371→\n 372→ # Options frame\n 373→ options_frame = ctk.CTkFrame(main_frame)\n 374→ options_frame.pack(fill=\"x\", pady=(20, 0))\n 375→\n 376→ options_label = ctk.CTkLabel(\n 377→ options_frame,\n 378→ text=\"Options\",\n 379→ font=ctk.CTkFont(size=16, weight=\"bold\")\n 380→ )\n 381→ options_label.pack(anchor=\"w\", pady=(0, 10))\n 382→\n 383→ # Model selection\n 384→ model_frame = ctk.CTkFrame(options_frame)\n 385→ model_frame.pack(fill=\"x\", pady=(0, 10))\n 386→\n 387→ ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n 388→\n 389→ for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n 390→ rb = ctk.CTkRadioButton(\n 391→ model_frame,\n 392→ text=label,\n 393→ variable=self._model_type,\n 394→ value=model,\n 395→ command=self._on_model_change\n 396→ )\n 397→ rb.pack(side=\"left\", padx=(20, 0))\n 398→\n 399→ # Language selection (for multilingual model)\n 400→ self._language_frame = ctk.CTkFrame(options_frame)\n 401→ self._language_frame.pack(fill=\"x\", pady=(0, 10))\n 402→\n 403→ ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n 404→\n 405→ languages = [\n 406→ (\"auto\", \"Auto-detect\"),\n 407→ (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n 408→ (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n 409→ (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n 410→ (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n 411→ ]\n 412→\n 413→ self._language_menu = ctk.CTkOptionMenu(\n 414→ self._language_frame,\n 415→ variable=self._language,\n 416→ values=[f\"{code} - {name}\" for code, name in languages],\n 417→ command=self._on_language_select\n 418→ )\n 419→ self._language_menu.pack(side=\"left\", padx=(20, 0))\n 420→ self._language_frame.pack_forget() # Hidden by default\n 421→\n 422→ # Language auto-detect help text\n 423→ self._language_help = ctk.CTkLabel(\n 424→ self._language_frame,\n 425→ text=\"Auto-detect works best for single-language texts\",\n 426→ text_color=\"gray\",\n 427→ font=ctk.CTkFont(size=11)\n 428→ )\n 429→ self._language_help.pack(side=\"left\", padx=(10, 0))\n 430→\n 431→ # Device selection\n 432→ device_frame = ctk.CTkFrame(options_frame)\n | |
| [2025-12-29T13:28:13.930Z] [INFO] 433→ device_frame.pack(fill=\"x\", pady=(0, 10))\n 434→\n 435→ ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n 436→\n 437→ # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n 438→ for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n 439→ rb = ctk.CTkRadioButton(\n 440→ device_frame,\n 441→ text=label,\n 442→ variable=self._device,\n 443→ value=device\n 444→ )\n 445→ rb.pack(side=\"left\", padx=(20, 0))\n 446→\n 447→ # Device help text (more detailed with AMD information)\n 448→ device_help = ctk.CTkLabel(\n 449→ options_frame,\n 450→ text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n 451→ text_color=\"gray\",\n 452→ font=ctk.CTkFont(size=11)\n 453→ )\n 454→ device_help.pack(anchor=\"w\", padx=(80, 0))\n 455→\n 456→ # CPU performance note\n 457→ cpu_note = ctk.CTkLabel(\n 458→ options_frame,\n 459→ text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n 460→ text_color=\"gray\",\n 461→ font=ctk.CTkFont(size=11)\n 462→ )\n 463→ cpu_note.pack(anchor=\"w\", padx=(80, 0))\n 464→\n 465→ # HuggingFace Token section\n 466→ hf_token_frame = ctk.CTkFrame(options_frame)\n 467→ hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n 468→\n 469→ ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n 470→\n 471→ self._hf_token_entry = ctk.CTkEntry(\n 472→ hf_token_frame,\n 473→ textvariable=self._hf_token,\n 474→ placeholder_text=\"Enter HuggingFace token for Turbo model\",\n 475→ show=\"*\",\n 476→ width=300\n 477→ )\n 478→ self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n 479→\n 480→ # HF Token help text\n 481→ hf_token_help = ctk.CTkLabel(\n 482→ options_frame,\n 483→ text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n 484→ text_color=\"gray\",\n 485→ font=ctk.CTkFont(size=11)\n 486→ )\n 487→ hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n 488→\n 489→ # Footnotes option\n 490→ footnote_frame = ctk.CTkFrame(options_frame)\n 491→ footnote_frame.pack(fill=\"x\", pady=(0, 10))\n 492→\n 493→ self._footnote_checkbox = ctk.CTkCheckBox(\n 494→ footnote_frame,\n 495→ text=\"Ignore footnotes (don't read them aloud)\",\n 496→ variable=self._ignore_footnotes\n 497→ )\n 498→ self._footnote_checkbox.pack(anchor=\"w\")\n 499→\n 500→ # Progress bar\n 501→ self._progress_frame = ctk.CTkFrame(main_frame)\n 502→ self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n 503→\n 504→ self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n 505→ self._progress_label.pack(anchor=\"w\")\n 506→\n 507→ self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n 508→ self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n 509→ self._progress_bar.set(0)\n 510→\n 511→ # Button frame for convert and cancel buttons\n 512→ button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 513→ button_frame.pack(fill=\"x\", pady=(20, 0))\n 514→\n 515→ # Convert button\n 516→ self._convert_btn = ctk.CTkButton(\n 517→ button_frame,\n 518→ text=\"Convert to Speech\",\n 519→ command=self._start_conversion,\n 520→ height=50,\n 521→ font=ctk.CTkFont(size=16, weight=\"bold\")\n 522→ )\n 523→ self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n 524→\n 525→ # Cancel button (hidden by default)\n 526→ self._cancel_btn = ctk.CTkButton(\n 527→ button_frame,\n 528→ text=\"Cancel\",\n 529→ command=self._cancel_conversion,\n 530→ height=50,\n 531→ font=ctk.CTkFont(size=16, weight=\"bold\"),\n 532→ fg_color=\"#CC4444\",\n 533→ hover_color=\"#AA3333\"\n 534→ )\n 535→ self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n 536→ self._cancel_btn.pack_forget() # Hidden by default\n 537→\n 538→ # Status bar\n 539→ self._status_label = ctk.CTkLabel(\n 540→ main_frame,\n 541→ text=\"Select an input file to begin\",\n 542→ text_color=\"gray\"\n 543→ )\n 544→ self._status_label.pack(pady=(10, 0))\n 545→\n 546→ def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n 547→ \"\"\"Create a file selection section.\"\"\"\n 548→ frame = ctk.CTkFrame(parent)\n 549→ frame.pack(fill=\"x\", pady=(0, 10))\n 550→\n 551→ label = ctk.CTkLabel(frame, text=label_text)\n 552→ label.pack(anchor=\"w\")\n 553→\n 554→ input_frame = ctk.CTkFrame(frame)\n 555→ input_frame.pack(fill=\"x\", pady=(5, 0))\n 556→\n 557→ entry = ctk.CTkEntry(input_frame, textvariable=variable)\n 558→ entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n 559→\n 560→ btn = ctk.CTkButton(\n 561→ input_frame,\n 562→ text=\"Browse\",\n 563→ command=browse_command,\n 564→ width=100\n 565→ )\n 566→ btn.pack(side=\"right\")\n 567→\n 568→ def _get_input_filetypes(self):\n 569→ \"\"\"Get file types for input file dialog.\"\"\"\n 570→ extensions = self._reader_registry.supported_extensions\n 571→ patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n 572→ return [\n 573→ (\"Supported documents\", patterns),\n 574→ (\"PDF files\", \"*.pdf\"),\n 575→ (\"Word documents\", \"*.doc *.docx\"),\n 576→ (\"Rich Text files\", \"*.rtf\"),\n 577→ (\"Text files\", \"*.txt\"),\n 578→ (\"Markdown files\", \"*.md\"),\n 579→ (\"All files\", \"*.*\")\n 580→ ]\n 581→\n 582→ def _browse_input(self):\n 583→ \"\"\"Open file dialog for input file.\"\"\"\n 584→ from tkinter import filedialog\n 585→\n 586→ filetypes = self._get_input_filetypes()\n 587→ filename = filedialog.askopenfilename(\n 588→ title=\"Select Input Document\",\n 589→ filetypes=filetypes\n 590→ )\n 591→ if filename:\n 592→ self._input_file.set(filename)\n 593→ # Auto-generate output filename\n 594→ input_path = Path(filename)\n 595→ output_path = input_path.with_suffix(\".wav\")\n 596→ self._output_file.set(str(output_path))\n 597→ self._status_label.configure(text=f\"Selected: {input_path.name}\")\n 598→\n 599→ def _browse_output(self):\n 600→ \"\"\"Open file dialog for output file.\"\"\"\n 601→ from tkinter import filedialog\n 602→\n 603→ filename = filedialog.asksaveasfilename(\n 604→ title=\"Save Audio File\",\n 605→ defaultextension=\".wav\",\n 606→ filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n 607→ )\n 608→ if filename:\n 609→ self._output_file.set(filename)\n 610→\n 611→ def _browse_voice_reference(self):\n 612→ \"\"\"Open file dialog for voice reference file.\"\"\"\n 613→ from tkinter import filedialog\n 614→\n 615→ filename = filedialog.askopenfilename(\n 616→ title=\"Select Voice Reference Audio\",\n 617→ filetypes=[\n 618→ (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n 619→ (\"WAV files\", \"*.wav\"),\n 620→ (\"All files\", \"*.*\")\n 621→ ]\n 622→ )\n 623→ if filename:\n 624→ self._voice_reference.set(filename)\n 625→\n 626→ def _on_model_change(self):\n 627→ \"\"\"Handle model type change.\"\"\"\n 628→ if self._model_type.get() == \"multilingual\":\n 629→ self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n 630→ else:\n 631→ self._language_frame.pack_forget()\n 632→\n 633→ def _on_language_select(self, value):\n 634→ \"\"\"Handle language selection.\"\"\"\n 635→ # Extract language code from \"en - English\" format\n 636→ code = value.split(\" - \")[0]\n 637→ self._language.set(code)\n 638→\n 639→ def _start_conversion(self):\n 640→ \"\"\"Start the conversion process in a background thread.\"\"\"\n 641→ if self._processing:\n 642→ return\n 643→\n 644→ # Validate inputs\n 645→ input_file = self._input_file.get().strip()\n 646→ output_file = self._output_file.get().strip()\n 647→\n 648→ if not input_file:\n 649→ CTkMessagebox(\n 650→ title=\"Error\",\n 651→ message=\"Please select an input file.\",\n 652→ icon=\"cancel\"\n 653→ )\n 654→ return\n 655→\n 656→ if not output_file:\n 657→ CTkMessagebox(\n 658→ title=\"Error\",\n 659→ message=\"Please select an output file location.\",\n 660→ icon=\"cancel\"\n 661→ )\n 662→ return\n 663→\n 664→ if not Path(input_file).exists():\n 665→ CTkMessagebox(\n 666→ title=\"Error\",\n 667→ message=f\"Input file not found: {input_file}\",\n 668→ icon=\"cancel\"\n 669→ )\n 670→ return\n 671→\n 672→ # Start conversion in background thread\n 673→ self._processing = True\n 674→ self._cancel_requested = False\n 675→ self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n 676→ self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n 677→ self._progress_bar.set(0)\n 678→ self._start_button_animation() # Start ellipsis animation\n 679→\n 680→ thread = threading.Thread(target=self._run_conversion)\n 681→ thread.daemon = True\n 682→ thread.start()\n 683→\n 684→ def _cancel_conversion(self):\n 685→ \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n 686→ if self._processing and not self._cancel_requested:\n 687→ self._cancel_requested = True\n 688→ self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n 689→ self._update_progress(0, \"Cancelling... (saving generated audio)\")\n 690→ logger.info(\"Cancellation requested by user\")\n 691→\n 692→ def _run_conversion(self):\n 693→ \"\"\"Run the conversion process (in background thread).\"\"\"\n 694→ try:\n 695→ input_path = Path(self._input_file.get())\n 696→ output_path = Path(self._output_file.get())\n 697→\n 698→ # Step 1: Read document\n 699→ self._update_progress(0.1, \"Reading document...\")\n 700→ content = self._reader_registry.read(input_path)\n 701→ logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n 702→\n 703→ # Step 2: Preprocess text\n 704→ self._update_progress(0.2, \"Preprocessing text...\")\n 705→ context = ProcessingContext(\n 706→ footnotes=content.footnotes,\n 707→ ignore_footnotes=self._ignore_footnotes.get(),\n 708→ page_count=content.page_count\n 709→ )\n 710→ processed_text = self._pipeline.process(content.text, context)\n 711→ logger.info(f\"Processed text: {len(processed_text)} chars\")\n 712→\n 713→ if not processed_text.strip():\n 714→ raise ValueError(\"No text content found in document\")\n 715→\n 716→ # Step 3: Initialize TTS engine\n 717→ model_name = self._model_type.get()\n 718→ device_name = self._device.get()\n 719→\n 720→ # Handle language auto-detection for multilingual model\n 721→ language = self._language.get()\n 722→ if model_name == \"multilingual\" and language == \"auto\":\n 723→ self._update_progress(0.22, \"Detecting language...\")\n 724→ from tts_app.utils.language_detection import detect_primary_language, get_language_name\n 725→ language = detect_primary_language(processed_text)\n 726→ detected_name = get_language_name(language)\n 727→ logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n 728→ self._update_progress(0.23, f\"Detected language: {detected_name}\")\n 729→\n 730→ self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n 731→\n 732→ # Start indeterminate animation for model download/initialization\n 733→ # This provides visual feedback that something is happening during long waits\n 734→ self.after(0, self._start_indeterminate_progress)\n 735→ self.after(0, lambda: self._progress_label.configure(\n 736→ text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n 737→ ))\n 738→\n 739→ config = TTSConfig(\n 740→ model_type=model_name,\n 741→ language=language,\n 742→ voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n 743→ device=device_name,\n 744→ hf_token=self._hf_token.get() if self._hf_token.get() else None\n 745→ )\n 746→\n 747→ if self._tts_engine is None:\n 748→ self._tts_engine = ChatterboxEngine()\n 749→\n 750→ self._tts_engine.initialize(config)\n 751→\n 752→ # Stop indeterminate animation and switch back to determinate progress\n 753→ self.after(0, self._stop_indeterminate_progress)\n 754→ self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n 755→\n 756→ # Step 4: Synthesize speech\n 757→ def progress_callback(current, total, status, estimated_remaining):\n 758→ progress = 0.35 + (0.60 * current / total)\n 759→ # Format estimated time remaining\n 760→ time_str = \"\"\n 761→ if estimated_remaining is not None and estimated_remaining > 0:\n 762→ mins = int(estimated_remaining // 60)\n 763→ secs = int(estimated_remaining % 60)\n 764→ if mins > 0:\n 765→ time_str = f\" (~{mins}m {secs}s remaining)\"\n 766→ else:\n 767→ time_str = f\" (~{secs}s remaining)\"\n 768→ self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n 769→\n 770→ def cancel_check():\n 771→ return self._cancel_requested\n 772→\n 773→ result = self._tts_engine.synthesize(\n 774→ processed_text,\n 775→ output_path,\n 776→ progress_callback=progress_callback,\n 777→ cancel_check=cancel_check\n 778→ )\n 779→\n 780→ # Handle result (complete or cancelled with partial)\n 781→ duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n 782→\n 783→ if result.was_cancelled:\n 784→ # Partial result from cancellation\n 785→ self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n 786→ self.after(0, lambda: SuccessDialog(\n 787→ self,\n 788→ title=\"Conversion Cancelled\",\n 789→ message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n 790→ f\"Duration: {duration_str}\\n\"\n 791→ f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n 792→ file_path=output_path\n 793→ ))\n 794→ else:\n 795→ # Complete\n 796→ self._update_progress(1.0, \"Complete!\")\n 797→ self.after(0, lambda: SuccessDialog(\n 798→ self,\n 799→ title=\"Conversion Complete\",\n 800→ message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n 801→ file_path=output_path\n 802→ ))\n 803→\n 804→ except Exception as e:\n 805→ logger.exception(\"Conversion failed\")\n 806→ error_msg = str(e)\n 807→ tb = traceback.format_exc()\n 808→ # Stop indeterminate progress if it was running\n 809→ self.after(0, self._stop_indeterminate_progress)\n 810→ self.after(0, lambda: ErrorDialog(\n 811→ self,\n 812→ title=\"Conversion Error\",\n 813→ message=f\"Conversion failed:\\n{error_msg}\",\n 814→ full_traceback=tb\n 815→ ))\n 816→\n 817→ finally:\n 818→ self._processing = False\n 819→ self.after(0, self._reset_ui)\n 820→\n 821→ def _update_progress(self, value: float, status: str):\n 822→ \"\"\"Update progress bar and status from any thread.\"\"\"\n 823→ self.after(0, lambda: self._progress_bar.set(value))\n 824→ self.after(0, lambda: self._progress_label.configure(text=status))\n 825→ self.after(0, lambda: self._status_label.configure(text=status))\n 826→\n 827→ def _start_indeterminate_progress(self):\n 828→ \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n 829→ self._progress_bar.configure(mode=\"indeterminate\")\n 830→ self._progress_bar.start()\n 831→\n 832→ def _stop_indeterminate_progress(self):\n 833→ \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n 834→ self._progress_bar.stop()\n 835→ self._progress_bar.configure(mode=\"determinate\")\n 836→\n 837→ def _start_button_animation(self):\n 838→ \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n 839→ self._ellipsis_state = 0\n 840→ self._animate_button_ellipsis()\n 841→\n 842→ def _stop_button_animation(self):\n 843→ \"\"\"Stop ellipsis animation on buttons.\"\"\"\n 844→ if self._button_animation_id:\n 845→ self.after_cancel(self._button_animation_id)\n 846→ self._button_animation_id = None\n 847→\n 848→ def _animate_button_ellipsis(self):\n 849→ \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n 850→ if not self._processing:\n 851→ return\n 852→\n 853→ ellipsis = \".\" * (self._ellipsis_state % 4)\n 854→ padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n 855→\n 856→ if self._cancel_requested:\n 857→ self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n 858→ else:\n 859→ self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n 860→\n 861→ self._ellipsis_state += 1\n 862→ self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n 863→\n 864→ def _reset_ui(self):\n 865→ \"\"\"Reset UI after conversion.\"\"\"\n 866→ self._stop_button_animation() # Stop ellipsis animation\n 867→ self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n 868→ self._cancel_btn.pack_forget() # Hide cancel button\n 869→ self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n 870→ self._cancel_requested = False\n 871→ self._progress_label.configure(text=\"Ready\")\n 872→\n 873→\n 874→def run_app():\n 875→ \"\"\"Create and run the application.\"\"\"\n 876→ app = TTSApplication()\n 877→ app.mainloop()\n 878→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"44eafed1-54ce-4fe8-b83d-5aebbeac5b61","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py","content":"\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n","numLines":878,"startLine":1,"totalLines":878}}} | |
| [2025-12-29T13:28:18.383Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01UjvRUiUuM84neCMmfGW9PG", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me check the base preprocessor class and see how the pipeline is set up:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 11167, | |
| "cache_creation_input_tokens": 11986, | |
| "cache_read_input_tokens": 30480, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 11986, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 5, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "db5cb0d0-a518-4362-8188-7b8fe17a09ee" | |
| } | |
| [2025-12-29T13:28:19.265Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01UjvRUiUuM84neCMmfGW9PG", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01KFiPzszkxoyAScJio43e6w", | |
| "name": "Read", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/preprocessors/pipeline.py" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 11167, | |
| "cache_creation_input_tokens": 11986, | |
| "cache_read_input_tokens": 30480, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 11986, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 5, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "7f476062-6699-4260-944d-f7b259a43b33" | |
| } | |
| [2025-12-29T13:28:19.705Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01UjvRUiUuM84neCMmfGW9PG", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01L5ZxgdrTqBv1nUKwtx1DJm", | |
| "name": "Read", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/preprocessors/base.py" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 11167, | |
| "cache_creation_input_tokens": 11986, | |
| "cache_read_input_tokens": 30480, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 11986, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 162, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "d4cecfca-2a6c-45f0-839b-7c7edb57ded4" | |
| } | |
| [2025-12-29T13:28:19.746Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01KFiPzszkxoyAScJio43e6w", | |
| "type": "tool_result", | |
| "content": " 1→\"\"\"Preprocessing pipeline for chaining multiple preprocessors.\"\"\"\n 2→\n 3→from typing import Optional\n 4→\n 5→from .base import TextPreprocessor, ProcessingContext\n 6→from .page_numbers import PageNumberRemover\n 7→from .footnotes import FootnoteHandler\n 8→from .symbols import SymbolConverter\n 9→\n 10→\n 11→class PreprocessorPipeline:\n 12→ \"\"\"Pipeline for running multiple text preprocessors in sequence.\n 13→\n 14→ This allows chaining preprocessors together for comprehensive\n 15→ text cleaning before TTS conversion.\n 16→\n 17→ Example:\n 18→ >>> pipeline = PreprocessorPipeline()\n 19→ >>> pipeline.add(PageNumberRemover())\n 20→ >>> pipeline.add(FootnoteHandler())\n 21→ >>> cleaned = pipeline.process(text, context)\n 22→ \"\"\"\n 23→\n 24→ def __init__(self):\n 25→ \"\"\"Initialize an empty pipeline.\"\"\"\n 26→ self._preprocessors: list[TextPreprocessor] = []\n 27→\n 28→ def add(self, preprocessor: TextPreprocessor) -> \"PreprocessorPipeline\":\n 29→ \"\"\"Add a preprocessor to the pipeline.\n 30→\n 31→ Args:\n 32→ preprocessor: The preprocessor to add.\n 33→\n 34→ Returns:\n 35→ Self for method chaining.\n 36→ \"\"\"\n 37→ self._preprocessors.append(preprocessor)\n 38→ return self\n 39→\n 40→ def remove(self, name: str) -> bool:\n 41→ \"\"\"Remove a preprocessor by name.\n 42→\n 43→ Args:\n 44→ name: The name of the preprocessor to remove.\n 45→\n 46→ Returns:\n 47→ True if a preprocessor was removed.\n 48→ \"\"\"\n 49→ original_length = len(self._preprocessors)\n 50→ self._preprocessors = [p for p in self._preprocessors if p.name != name]\n 51→ return len(self._preprocessors) < original_length\n 52→\n 53→ def process(self, text: str, context: ProcessingContext) -> str:\n 54→ \"\"\"Run all preprocessors on the text.\n 55→\n 56→ Args:\n 57→ text: The text to process.\n 58→ context: Processing context.\n 59→\n 60→ Returns:\n 61→ The processed text after all preprocessors have run.\n 62→ \"\"\"\n 63→ result = text\n 64→\n 65→ for preprocessor in self._preprocessors:\n 66→ if preprocessor.enabled:\n 67→ result = preprocessor.process(result, context)\n 68→\n 69→ # Final cleanup: normalize whitespace\n 70→ result = self._normalize_whitespace(result)\n 71→\n 72→ return result\n 73→\n 74→ def _normalize_whitespace(self, text: str) -> str:\n 75→ \"\"\"Normalize whitespace in text.\n 76→\n 77→ Args:\n 78→ text: The text to normalize.\n 79→\n 80→ Returns:\n 81→ Text with normalized whitespace.\n 82→ \"\"\"\n 83→ import re\n 84→\n 85→ # Replace multiple spaces with single space\n 86→ result = re.sub(r'[ \\t]+', ' ', text)\n 87→\n 88→ # Replace more than 2 consecutive newlines with just 2\n 89→ result = re.sub(r'\\n{3,}', '\\n\\n', result)\n 90→\n 91→ # Strip leading/trailing whitespace from each line\n 92→ lines = [line.strip() for line in result.split('\\n')]\n 93→ result = '\\n'.join(lines)\n 94→\n 95→ # Strip overall\n 96→ return result.strip()\n 97→\n 98→ @property\n 99→ def preprocessors(self) -> list[str]:\n 100→ \"\"\"Get names of all preprocessors in the pipeline.\n 101→\n 102→ Returns:\n 103→ List of preprocessor names.\n 104→ \"\"\"\n 105→ return [p.name for p in self._preprocessors]\n 106→\n 107→\n 108→def create_default_pipeline() -> PreprocessorPipeline:\n 109→ \"\"\"Create a pipeline with default preprocessors.\n 110→\n 111→ Returns:\n 112→ A pipeline with page number, footnote, and symbol handlers.\n 113→ \"\"\"\n 114→ pipeline = PreprocessorPipeline()\n 115→ pipeline.add(PageNumberRemover())\n 116→ pipeline.add(FootnoteHandler())\n 117→ pipeline.add(SymbolConverter())\n 118→ return pipeline\n 119→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "04ee0e1a-0adb-4407-bd69-b24c3cd1f015", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/preprocessors/pipeline.py", | |
| "content": "\"\"\"Preprocessing pipeline for chaining multiple preprocessors.\"\"\"\n\nfrom typing import Optional\n\nfrom .base import TextPreprocessor, ProcessingContext\nfrom .page_numbers import PageNumberRemover\nfrom .footnotes import FootnoteHandler\nfrom .symbols import SymbolConverter\n\n\nclass PreprocessorPipeline:\n \"\"\"Pipeline for running multiple text preprocessors in sequence.\n\n This allows chaining preprocessors together for comprehensive\n text cleaning before TTS conversion.\n\n Example:\n >>> pipeline = PreprocessorPipeline()\n >>> pipeline.add(PageNumberRemover())\n >>> pipeline.add(FootnoteHandler())\n >>> cleaned = pipeline.process(text, context)\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize an empty pipeline.\"\"\"\n self._preprocessors: list[TextPreprocessor] = []\n\n def add(self, preprocessor: TextPreprocessor) -> \"PreprocessorPipeline\":\n \"\"\"Add a preprocessor to the pipeline.\n\n Args:\n preprocessor: The preprocessor to add.\n\n Returns:\n Self for method chaining.\n \"\"\"\n self._preprocessors.append(preprocessor)\n return self\n\n def remove(self, name: str) -> bool:\n \"\"\"Remove a preprocessor by name.\n\n Args:\n name: The name of the preprocessor to remove.\n\n Returns:\n True if a preprocessor was removed.\n \"\"\"\n original_length = len(self._preprocessors)\n self._preprocessors = [p for p in self._preprocessors if p.name != name]\n return len(self._preprocessors) < original_length\n\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Run all preprocessors on the text.\n\n Args:\n text: The text to process.\n context: Processing context.\n\n Returns:\n The processed text after all preprocessors have run.\n \"\"\"\n result = text\n\n for preprocessor in self._preprocessors:\n if preprocessor.enabled:\n result = preprocessor.process(result, context)\n\n # Final cleanup: normalize whitespace\n result = self._normalize_whitespace(result)\n\n return result\n\n def _normalize_whitespace(self, text: str) -> str:\n \"\"\"Normalize whitespace in text.\n\n Args:\n text: The text to normalize.\n\n Returns:\n Text with normalized whitespace.\n \"\"\"\n import re\n\n # Replace multiple spaces with single space\n result = re.sub(r'[ \\t]+', ' ', text)\n\n # Replace more than 2 consecutive newlines with just 2\n result = re.sub(r'\\n{3,}', '\\n\\n', result)\n\n # Strip leading/trailing whitespace from each line\n lines = [line.strip() for line in result.split('\\n')]\n result = '\\n'.join(lines)\n\n # Strip overall\n return result.strip()\n\n @property\n def preprocessors(self) -> list[str]:\n \"\"\"Get names of all preprocessors in the pipeline.\n\n Returns:\n List of preprocessor names.\n \"\"\"\n return [p.name for p in self._preprocessors]\n\n\ndef create_default_pipeline() -> PreprocessorPipeline:\n \"\"\"Create a pipeline with default preprocessors.\n\n Returns:\n A pipeline with page number, footnote, and symbol handlers.\n \"\"\"\n pipeline = PreprocessorPipeline()\n pipeline.add(PageNumberRemover())\n pipeline.add(FootnoteHandler())\n pipeline.add(SymbolConverter())\n return pipeline\n", | |
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| [2025-12-29T13:28:19.760Z] [INFO] { | |
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| "content": " 1→\"\"\"Base text preprocessor interface.\"\"\"\n 2→\n 3→from abc import ABC, abstractmethod\n 4→from dataclasses import dataclass\n 5→from typing import Optional\n 6→\n 7→\n 8→@dataclass\n 9→class ProcessingContext:\n 10→ \"\"\"Context information for text processing.\n 11→\n 12→ Attributes:\n 13→ footnotes: List of footnotes from the document.\n 14→ ignore_footnotes: Whether to remove footnote references.\n 15→ page_count: Number of pages in the document.\n 16→ \"\"\"\n 17→ footnotes: list[str]\n 18→ ignore_footnotes: bool = False\n 19→ page_count: Optional[int] = None\n 20→\n 21→\n 22→class TextPreprocessor(ABC):\n 23→ \"\"\"Abstract base class for text preprocessors.\n 24→\n 25→ Text preprocessors transform text to prepare it for TTS.\n 26→ They can remove page numbers, handle footnotes, normalize\n 27→ whitespace, etc.\n 28→\n 29→ To add a new preprocessor, create a subclass that implements\n 30→ the `process` method.\n 31→ \"\"\"\n 32→\n 33→ @property\n 34→ @abstractmethod\n 35→ def name(self) -> str:\n 36→ \"\"\"Return the preprocessor name for identification.\"\"\"\n 37→ pass\n 38→\n 39→ @abstractmethod\n 40→ def process(self, text: str, context: ProcessingContext) -> str:\n 41→ \"\"\"Process the text and return the result.\n 42→\n 43→ Args:\n 44→ text: The text to process.\n 45→ context: Processing context with additional information.\n 46→\n 47→ Returns:\n 48→ The processed text.\n 49→ \"\"\"\n 50→ pass\n 51→\n 52→ @property\n 53→ def enabled(self) -> bool:\n 54→ \"\"\"Check if this preprocessor is enabled.\n 55→\n 56→ Returns:\n 57→ True by default. Override to add conditional logic.\n 58→ \"\"\"\n 59→ return True\n 60→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
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| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/preprocessors/base.py", | |
| "content": "\"\"\"Base text preprocessor interface.\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom dataclasses import dataclass\nfrom typing import Optional\n\n\n@dataclass\nclass ProcessingContext:\n \"\"\"Context information for text processing.\n\n Attributes:\n footnotes: List of footnotes from the document.\n ignore_footnotes: Whether to remove footnote references.\n page_count: Number of pages in the document.\n \"\"\"\n footnotes: list[str]\n ignore_footnotes: bool = False\n page_count: Optional[int] = None\n\n\nclass TextPreprocessor(ABC):\n \"\"\"Abstract base class for text preprocessors.\n\n Text preprocessors transform text to prepare it for TTS.\n They can remove page numbers, handle footnotes, normalize\n whitespace, etc.\n\n To add a new preprocessor, create a subclass that implements\n the `process` method.\n \"\"\"\n\n @property\n @abstractmethod\n def name(self) -> str:\n \"\"\"Return the preprocessor name for identification.\"\"\"\n pass\n\n @abstractmethod\n def process(self, text: str, context: ProcessingContext) -> str:\n \"\"\"Process the text and return the result.\n\n Args:\n text: The text to process.\n context: Processing context with additional information.\n\n Returns:\n The processed text.\n \"\"\"\n pass\n\n @property\n def enabled(self) -> bool:\n \"\"\"Check if this preprocessor is enabled.\n\n Returns:\n True by default. Override to add conditional logic.\n \"\"\"\n return True\n", | |
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| "text": "Now let me also check any existing tests to understand the testing patterns:" | |
| } | |
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| [2025-12-29T13:28:26.747Z] [INFO] { | |
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| "id": "toolu_01FqW9vCZsW8WKGArvnR63PD", | |
| "name": "Bash", | |
| "input": { | |
| "command": "gh pr list --repo Jhon-Crow/text-to-speech-with-chatterbox --state merged --limit 5", | |
| "description": "Check merged PRs for style" | |
| } | |
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| [2025-12-29T13:28:26.798Z] [INFO] { | |
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| "content": "/tmp/gh-issue-solver-1767014767488/tests/__init__.py\n/tmp/gh-issue-solver-1767014767488/tests/test_readers.py\n/tmp/gh-issue-solver-1767014767488/tests/test_tts.py\n/tmp/gh-issue-solver-1767014767488/tests/test_preprocessors.py\n/tmp/gh-issue-solver-1767014767488/tests/test_language_detection.py" | |
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| [2025-12-29T13:28:28.168Z] [INFO] { | |
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| { | |
| "tool_use_id": "toolu_01FqW9vCZsW8WKGArvnR63PD", | |
| "type": "tool_result", | |
| "content": "23\tFix & Update: UX improvements, symbol preprocessing, language auto-detection\tkonard:issue-22-a5e0f79d0bad\tMERGED\t2025-12-29T11:03:37Z\n21\tFix GPU handling, add Open File Location and Cancel buttons\tkonard:issue-20-0b603a625928\tMERGED\t2025-12-29T08:33:38Z\n19\tFix multilingual model failing to load on CPU-only machines\tkonard:issue-14-a00d1c6a64b9\tMERGED\t2025-12-29T05:19:13Z\n18\tFix perth watermarker initialization in PyInstaller bundle\tkonard:issue-17-06fc1cbbd5cb\tMERGED\t2025-12-28T21:14:18Z\n16\t[WIP] FIX\tkonard:issue-14-32980467bf49\tMERGED\t2025-12-28T21:00:38Z", | |
| "is_error": false | |
| } | |
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| "tool_use_result": { | |
| "stdout": "23\tFix & Update: UX improvements, symbol preprocessing, language auto-detection\tkonard:issue-22-a5e0f79d0bad\tMERGED\t2025-12-29T11:03:37Z\n21\tFix GPU handling, add Open File Location and Cancel buttons\tkonard:issue-20-0b603a625928\tMERGED\t2025-12-29T08:33:38Z\n19\tFix multilingual model failing to load on CPU-only machines\tkonard:issue-14-a00d1c6a64b9\tMERGED\t2025-12-29T05:19:13Z\n18\tFix perth watermarker initialization in PyInstaller bundle\tkonard:issue-17-06fc1cbbd5cb\tMERGED\t2025-12-28T21:14:18Z\n16\t[WIP] FIX\tkonard:issue-14-32980467bf49\tMERGED\t2025-12-28T21:00:38Z", | |
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| [2025-12-29T13:28:33.327Z] [INFO] { | |
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| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Let me look at the most recent merged PR for style reference and understand the issues better:" | |
| } | |
| ], | |
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| [2025-12-29T13:28:33.931Z] [INFO] { | |
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| "id": "toolu_01T17S4KJchpY4FpGEFcE7uT", | |
| "name": "Bash", | |
| "input": { | |
| "command": "gh pr view 23 --repo Jhon-Crow/text-to-speech-with-chatterbox", | |
| "description": "View PR 23 for reference" | |
| } | |
| } | |
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| [2025-12-29T13:28:36.631Z] [INFO] { | |
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| "content": "title:\tFix & Update: UX improvements, symbol preprocessing, language auto-detection\nstate:\tMERGED\nauthor:\tkonard\nlabels:\t\nassignees:\t\nreviewers:\t\nprojects:\t\nmilestone:\t\nnumber:\t23\nurl:\thttps://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/23\nadditions:\t775\ndeletions:\t12\nauto-merge:\tdisabled\n--\n## Summary\n\nThis PR addresses several items from issue #22:\n\n### ✅ Implemented Features\n\n1. **Ellipsis animation for Converting.../Cancelling... buttons** (#22 item 2)\n - Added animated ellipsis (., .., ..., then repeat) to indicate the app is not frozen during long operations\n - Animation updates every 400ms to provide visual feedback\n\n2. **Estimated time display for synthesis** (#22 item 4)\n - Track chunk processing times and calculate average\n - Display remaining time estimate during synthesis (e.g., \"~2m 30s remaining\")\n\n3. **Symbol preprocessing for readable text** (#22 item 5)\n - New `SymbolConverter` preprocessor to convert symbols to speakable text:\n - Numbered lists (1. 2. 3.) → \"Point 1. Point 2. Point 3.\"\n - Equals sign (x = 5) → \"x equals 5\"\n - Percentages (50%) → \"50 percent\"\n - Currency ($100) → \"100 dollars\"\n - Ampersand (A & B) → \"A and B\"\n - Hash numbers (#42) → \"number 42\"\n - Arrows (→, ->) → \"arrow\"\n\n4. **Multilingual auto-detection mode** (#22 item 1)\n - Added \"Auto-detect\" option for language selection in multilingual model\n - Script-based language detection (Cyrillic→Russian, CJK→Chinese, etc.)\n - Works best for single-language texts with some mixed content\n\n5. **Improved AMD GPU and CPU documentation** (#22 item 3)\n - Added note about AMD GPUs on Windows using CPU mode\n - Added CPU performance tips in the UI\n\n### 📝 Notes on Remaining Items\n\n- **Item 3 (CPU speed optimization)**: CPU TTS is inherently slow due to the computational requirements of the neural network. The Turbo model is fastest. We've added UI guidance about this.\n- **Items 6-7 (pronunciation issues, wrong language)**: These are likely issues in the underlying Chatterbox TTS model itself. Language auto-detection may help with item 7 by ensuring the correct language is selected.\n\n### Test Plan\n\n- [x] Verify ellipsis animation shows during conversion\n- [x] Verify ellipsis animation shows during cancellation\n- [x] Verify estimated time appears after first chunk is processed\n- [x] Verify symbols like \"=\" and numbered lists are converted to readable text\n- [x] Verify \"Auto-detect\" option appears in language dropdown for multilingual model\n- [x] Verify Russian text is detected as Russian\n- [x] Run unit tests (47 new tests added for symbol converter and language detection)\n\nFixes Jhon-Crow/text-to-speech-with-chatterbox#22\n\n🤖 Generated with [Claude Code](https://claude.com/claude-code)", | |
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| "uuid": "a1972a70-5b4d-488b-ac16-f827972842ec", | |
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| "stdout": "title:\tFix & Update: UX improvements, symbol preprocessing, language auto-detection\nstate:\tMERGED\nauthor:\tkonard\nlabels:\t\nassignees:\t\nreviewers:\t\nprojects:\t\nmilestone:\t\nnumber:\t23\nurl:\thttps://github.com/Jhon-Crow/text-to-speech-with-chatterbox/pull/23\nadditions:\t775\ndeletions:\t12\nauto-merge:\tdisabled\n--\n## Summary\n\nThis PR addresses several items from issue #22:\n\n### ✅ Implemented Features\n\n1. **Ellipsis animation for Converting.../Cancelling... buttons** (#22 item 2)\n - Added animated ellipsis (., .., ..., then repeat) to indicate the app is not frozen during long operations\n - Animation updates every 400ms to provide visual feedback\n\n2. **Estimated time display for synthesis** (#22 item 4)\n - Track chunk processing times and calculate average\n - Display remaining time estimate during synthesis (e.g., \"~2m 30s remaining\")\n\n3. **Symbol preprocessing for readable text** (#22 item 5)\n - New `SymbolConverter` preprocessor to convert symbols to speakable text:\n - Numbered lists (1. 2. 3.) → \"Point 1. Point 2. Point 3.\"\n - Equals sign (x = 5) → \"x equals 5\"\n - Percentages (50%) → \"50 percent\"\n - Currency ($100) → \"100 dollars\"\n - Ampersand (A & B) → \"A and B\"\n - Hash numbers (#42) → \"number 42\"\n - Arrows (→, ->) → \"arrow\"\n\n4. **Multilingual auto-detection mode** (#22 item 1)\n - Added \"Auto-detect\" option for language selection in multilingual model\n - Script-based language detection (Cyrillic→Russian, CJK→Chinese, etc.)\n - Works best for single-language texts with some mixed content\n\n5. **Improved AMD GPU and CPU documentation** (#22 item 3)\n - Added note about AMD GPUs on Windows using CPU mode\n - Added CPU performance tips in the UI\n\n### 📝 Notes on Remaining Items\n\n- **Item 3 (CPU speed optimization)**: CPU TTS is inherently slow due to the computational requirements of the neural network. The Turbo model is fastest. We've added UI guidance about this.\n- **Items 6-7 (pronunciation issues, wrong language)**: These are likely issues in the underlying Chatterbox TTS model itself. Language auto-detection may help with item 7 by ensuring the correct language is selected.\n\n### Test Plan\n\n- [x] Verify ellipsis animation shows during conversion\n- [x] Verify ellipsis animation shows during cancellation\n- [x] Verify estimated time appears after first chunk is processed\n- [x] Verify symbols like \"=\" and numbered lists are converted to readable text\n- [x] Verify \"Auto-detect\" option appears in language dropdown for multilingual model\n- [x] Verify Russian text is detected as Russian\n- [x] Run unit tests (47 new tests added for symbol converter and language detection)\n\nFixes Jhon-Crow/text-to-speech-with-chatterbox#22\n\n🤖 Generated with [Claude Code](https://claude.com/claude-code)", | |
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| [2025-12-29T13:28:36.656Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01DYEAvs3JUj79nYzHJczpRf","type":"tool_result","content":" 1→\"\"\"Tests for text preprocessors.\"\"\"\n 2→\n 3→import pytest\n 4→\n 5→from tts_app.preprocessors import (\n 6→ TextPreprocessor,\n 7→ PageNumberRemover,\n 8→ FootnoteHandler,\n 9→ SymbolConverter,\n 10→ PreprocessorPipeline,\n 11→)\n 12→from tts_app.preprocessors.base import ProcessingContext\n 13→from tts_app.preprocessors.pipeline import create_default_pipeline\n 14→\n 15→\n 16→class TestProcessingContext:\n 17→ \"\"\"Tests for ProcessingContext.\"\"\"\n 18→\n 19→ def test_create_minimal(self):\n 20→ \"\"\"Test creating context with minimal args.\"\"\"\n 21→ ctx = ProcessingContext(footnotes=[])\n 22→ assert ctx.footnotes == []\n 23→ assert ctx.ignore_footnotes is False\n 24→ assert ctx.page_count is None\n 25→\n 26→ def test_create_full(self):\n 27→ \"\"\"Test creating context with all args.\"\"\"\n 28→ ctx = ProcessingContext(\n 29→ footnotes=[\"[1] Note\"],\n 30→ ignore_footnotes=True,\n 31→ page_count=10\n 32→ )\n 33→ assert len(ctx.footnotes) == 1\n 34→ assert ctx.ignore_footnotes is True\n 35→ assert ctx.page_count == 10\n 36→\n 37→\n 38→class TestPageNumberRemover:\n 39→ \"\"\"Tests for PageNumberRemover.\"\"\"\n 40→\n 41→ def test_name(self):\n 42→ \"\"\"Test processor name.\"\"\"\n 43→ processor = PageNumberRemover()\n 44→ assert processor.name == \"page_number_remover\"\n 45→\n 46→ def test_remove_standalone_numbers(self):\n 47→ \"\"\"Test removing standalone page numbers.\"\"\"\n 48→ processor = PageNumberRemover()\n 49→ ctx = ProcessingContext(footnotes=[], page_count=50)\n 50→\n 51→ text = \"Some text here.\\n\\n42\\n\\nMore text here.\"\n 52→ result = processor.process(text, ctx)\n 53→\n 54→ assert \"Some text here.\" in result\n 55→ assert \"More text here.\" in result\n 56→ # The standalone \"42\" should be removed\n 57→ lines = [line.strip() for line in result.split(\"\\n\") if line.strip()]\n 58→ assert \"42\" not in lines\n 59→\n 60→ def test_remove_page_x_format(self):\n 61→ \"\"\"Test removing 'Page X' format.\"\"\"\n 62→ processor = PageNumberRemover()\n 63→ ctx = ProcessingContext(footnotes=[], page_count=50)\n 64→\n 65→ text = \"Some text.\\nPage 15\\nMore text.\"\n 66→ result = processor.process(text, ctx)\n 67→\n 68→ assert \"Some text.\" in result\n 69→ assert \"More text.\" in result\n 70→ assert \"Page 15\" not in result\n 71→\n 72→ def test_remove_page_x_of_y_format(self):\n 73→ \"\"\"Test removing 'Page X of Y' format.\"\"\"\n 74→ processor = PageNumberRemover()\n 75→ ctx = ProcessingContext(footnotes=[], page_count=50)\n 76→\n 77→ text = \"Some text.\\nPage 5 of 20\\nMore text.\"\n 78→ result = processor.process(text, ctx)\n 79→\n 80→ assert \"Page 5 of 20\" not in result\n 81→\n 82→ def test_remove_centered_page_numbers(self):\n 83→ \"\"\"Test removing centered page numbers like '- 42 -'.\"\"\"\n 84→ processor = PageNumberRemover()\n 85→ ctx = ProcessingContext(footnotes=[], page_count=50)\n 86→\n 87→ text = \"Some text.\\n- 42 -\\nMore text.\"\n 88→ result = processor.process(text, ctx)\n 89→\n 90→ assert \"- 42 -\" not in result\n 91→\n 92→ def test_keep_regular_numbers(self):\n 93→ \"\"\"Test that regular numbers in text are kept.\"\"\"\n 94→ processor = PageNumberRemover()\n 95→ ctx = ProcessingContext(footnotes=[], page_count=50)\n 96→\n 97→ text = \"The year was 1984. There were 100 people.\"\n 98→ result = processor.process(text, ctx)\n 99→\n 100→ assert \"1984\" in result\n 101→ assert \"100\" in result\n 102→\n 103→\n 104→class TestFootnoteHandler:\n 105→ \"\"\"Tests for FootnoteHandler.\"\"\"\n 106→\n 107→ def test_name(self):\n 108→ \"\"\"Test processor name.\"\"\"\n 109→ processor = FootnoteHandler()\n 110→ assert processor.name == \"footnote_handler\"\n 111→\n 112→ def test_remove_bracket_footnotes(self):\n 113→ \"\"\"Test removing [1] style footnotes when ignored.\"\"\"\n 114→ processor = FootnoteHandler()\n 115→ ctx = ProcessingContext(footnotes=[], ignore_footnotes=True)\n 116→\n 117→ text = \"This is some text[1] with a footnote[2].\"\n 118→ result = processor.process(text, ctx)\n 119→\n 120→ assert \"[1]\" not in result\n 121→ assert \"[2]\" not in result\n 122→ assert \"This is some text with a footnote.\" in result\n 123→\n 124→ def test_remove_caret_footnotes(self):\n 125→ \"\"\"Test removing ^1 style footnotes when ignored.\"\"\"\n 126→ processor = FootnoteHandler()\n 127→ ctx = ProcessingContext(footnotes=[], ignore_footnotes=True)\n 128→\n 129→ text = \"This is some text^1 with a footnote.\"\n 130→ result = processor.process(text, ctx)\n 131→\n 132→ assert \"^1\" not in result\n 133→\n 134→ def test_insert_footnotes_inline(self):\n 135→ \"\"\"Test inserting footnote content inline when not ignored.\"\"\"\n 136→ processor = FootnoteHandler()\n 137→ ctx = ProcessingContext(\n 138→ footnotes=[\"[1] This is footnote one.\"],\n 139→ ignore_footnotes=False\n 140→ )\n 141→\n 142→ text = \"This is some text[1] with a footnote.\"\n 143→ result = processor.process(text, ctx)\n 144→\n 145→ assert \"Footnote:\" in result\n 146→ assert \"This is footnote one\" in result\n 147→\n 148→ def test_multiple_footnotes_inline(self):\n 149→ \"\"\"Test inserting multiple footnotes inline.\"\"\"\n 150→ processor = FootnoteHandler()\n 151→ ctx = ProcessingContext(\n 152→ footnotes=[\"[1] First note.\", \"[2] Second note.\"],\n 153→ ignore_footnotes=False\n 154→ )\n 155→\n 156→ text = \"Text with first[1] and second[2] references.\"\n 157→ result = processor.process(text, ctx)\n 158→\n 159→ assert \"First note\" in result\n 160→ assert \"Second note\" in result\n 161→\n 162→\n 163→class TestPreprocessorPipeline:\n 164→ \"\"\"Tests for PreprocessorPipeline.\"\"\"\n 165→\n 166→ def test_add_and_process(self):\n 167→ \"\"\"Test adding preprocessors and processing text.\"\"\"\n 168→ pipeline = PreprocessorPipeline()\n 169→ pipeline.add(PageNumberRemover())\n 170→\n 171→ ctx = ProcessingContext(footnotes=[], page_count=10)\n 172→ text = \"Text\\n\\n5\\n\\nMore text\"\n 173→ result = pipeline.process(text, ctx)\n 174→\n 175→ # Page number should be removed\n 176→ lines = [line.strip() for line in result.split(\"\\n\") if line.strip()]\n 177→ assert \"5\" not in lines\n 178→\n 179→ def test_chain_preprocessors(self):\n 180→ \"\"\"Test chaining multiple preprocessors.\"\"\"\n 181→ pipeline = PreprocessorPipeline()\n 182→ pipeline.add(PageNumberRemover())\n 183→ pipeline.add(FootnoteHandler())\n 184→\n 185→ ctx = ProcessingContext(footnotes=[], ignore_footnotes=True, page_count=10)\n 186→ text = \"Text[1]\\n\\n5\\n\\nMore text[2]\"\n 187→ result = pipeline.process(text, ctx)\n 188→\n 189→ # Both page numbers and footnote references should be removed\n 190→ assert \"[1]\" not in result\n 191→ assert \"[2]\" not in result\n 192→\n 193→ def test_remove_preprocessor(self):\n 194→ \"\"\"Test removing a preprocessor by name.\"\"\"\n 195→ pipeline = PreprocessorPipeline()\n 196→ pipeline.add(PageNumberRemover())\n 197→ pipeline.add(FootnoteHandler())\n 198→\n 199→ assert len(pipeline.preprocessors) == 2\n 200→\n 201→ removed = pipeline.remove(\"page_number_remover\")\n 202→ assert removed is True\n 203→ assert len(pipeline.preprocessors) == 1\n 204→\n 205→ def test_normalize_whitespace(self):\n 206→ \"\"\"Test that pipeline normalizes whitespace.\"\"\"\n 207→ pipeline = PreprocessorPipeline()\n 208→ ctx = ProcessingContext(footnotes=[])\n 209→\n 210→ text = \"Line 1\\n\\n\\n\\n\\nLine 2\"\n 211→ result = pipeline.process(text, ctx)\n 212→\n 213→ # Multiple newlines should be reduced\n 214→ assert \"\\n\\n\\n\" not in result\n 215→\n 216→\n 217→class TestSymbolConverter:\n 218→ \"\"\"Tests for SymbolConverter.\"\"\"\n 219→\n 220→ def test_name(self):\n 221→ \"\"\"Test processor name.\"\"\"\n 222→ processor = SymbolConverter()\n 223→ assert processor.name == \"symbol_converter\"\n 224→\n 225→ def test_convert_equals_in_equation(self):\n 226→ \"\"\"Test converting equals sign in equations.\"\"\"\n 227→ processor = SymbolConverter()\n 228→ ctx = ProcessingContext(footnotes=[])\n 229→\n 230→ text = \"The formula is x = 5\"\n 231→ result = processor.process(text, ctx)\n 232→\n 233→ assert \"equals\" in result.lower()\n 234→ assert \" = \" not in result\n 235→\n 236→ def test_convert_numbered_list_period(self):\n 237→ \"\"\"Test converting numbered lists with periods.\"\"\"\n 238→ processor = SymbolConverter()\n 239→ ctx = ProcessingContext(footnotes=[])\n 240→\n 241→ text = \"1. First item\\n2. Second item\\n3. Third item\"\n 242→ result = processor.process(text, ctx)\n 243→\n 244→ assert \"Point 1\" in result\n 245→ assert \"Point 2\" in result\n 246→ assert \"Point 3\" in result\n 247→\n 248→ def test_convert_numbered_list_parenthesis(self):\n 249→ \"\"\"Test converting numbered lists with parentheses.\"\"\"\n 250→ processor = SymbolConverter()\n 251→ ctx = ProcessingContext(footnotes=[])\n 252→\n 253→ text = \"1) First item\\n2) Second item\"\n 254→ result = processor.process(text, ctx)\n 255→\n 256→ # Parenthesis-style should just use the number\n 257→ assert \"1.\" in result\n 258→ assert \"2.\" in result\n 259→\n 260→ def test_convert_percentage(self):\n 261→ \"\"\"Test converting percentage symbol.\"\"\"\n 262→ processor = SymbolConverter()\n 263→ ctx = ProcessingContext(footnotes=[])\n 264→\n 265→ text = \"The growth was 50%\"\n 266→ result = processor.process(text, ctx)\n 267→\n 268→ assert \"percent\" in result.lower()\n 269→ assert \"%\" not in result\n 270→\n 271→ def test_convert_currency(self):\n 272→ \"\"\"Test converting currency symbols.\"\"\"\n 273→ processor = SymbolConverter()\n 274→ ctx = ProcessingContext(footnotes=[])\n 275→\n 276→ text = \"The price is $100\"\n 277→ result = processor.process(text, ctx)\n 278→\n 279→ assert \"dollars\" in result.lower()\n 280→\n 281→ def test_convert_ampersand(self):\n 282→ \"\"\"Test converting ampersand to 'and'.\"\"\"\n 283→ processor = SymbolConverter()\n 284→ ctx = ProcessingContext(footnotes=[])\n 285→\n 286→ text = \"Salt & pepper\"\n 287→ result = processor.process(text, ctx)\n 288→\n 289→ assert \" and \" in result.lower()\n 290→ assert \"&\" not in result\n 291→\n 292→ def test_convert_hash_number(self):\n 293→ \"\"\"Test converting hash with number.\"\"\"\n 294→ processor = SymbolConverter()\n 295→ ctx = ProcessingContext(footnotes=[])\n 296→\n 297→ text = \"Issue #42\"\n 298→ result = processor.process(text, ctx)\n 299→\n 300→ assert \"number 42\" in result.lower()\n 301→ assert \"#\" not in result\n 302→\n 303→ def test_convert_arrow(self):\n 304→ \"\"\"Test converting arrow symbols.\"\"\"\n 305→ processor = SymbolConverter()\n 306→ ctx = ProcessingContext(footnotes=[])\n 307→\n 308→ text = \"Go → forward\"\n 309→ result = processor.process(text, ctx)\n 310→\n 311→ assert \"arrow\" in result.lower()\n 312→\n 313→ def test_preserve_hyphens_in_words(self):\n 314→ \"\"\"Test that hyphens in compound words are preserved.\"\"\"\n 315→ processor = SymbolConverter()\n 316→ ctx = ProcessingContext(footnotes=[])\n 317→\n 318→ text = \"This is a well-known fact\"\n 319→ result = processor.process(text, ctx)\n 320→\n 321→ # Hyphens in compound words should not be changed\n 322→ assert \"well-known\" in result or \"well known\" in result\n 323→\n 324→\n 325→class TestDefaultPipeline:\n 326→ \"\"\"Tests for the default pipeline.\"\"\"\n 327→\n 328→ def test_default_pipeline_has_processors(self):\n 329→ \"\"\"Test that default pipeline has expected processors.\"\"\"\n 330→ pipeline = create_default_pipeline()\n 331→\n 332→ names = pipeline.preprocessors\n 333→ assert \"page_number_remover\" in names\n 334→ assert \"footnote_handler\" in names\n 335→ assert \"symbol_converter\" in names\n 336→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"4fd6fd4c-c4aa-4398-be7c-b08bae3a0f59","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1767014767488/tests/test_preprocessors.py","content":"\"\"\"Tests for text preprocessors.\"\"\"\n\nimport pytest\n\nfrom tts_app.preprocessors import (\n TextPreprocessor,\n PageNumberRemover,\n FootnoteHandler,\n SymbolConverter,\n PreprocessorPipeline,\n)\nfrom tts_app.preprocessors.base import ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\n\n\nclass TestProcessingContext:\n \"\"\"Tests for ProcessingContext.\"\"\"\n\n def test_create_minimal(self):\n \"\"\"Test creating context with minimal args.\"\"\"\n ctx = ProcessingContext(footnotes=[])\n assert ctx.footnotes == []\n assert ctx.ignore_footnotes is False\n assert ctx.page_count is None\n\n def test_create_full(self):\n \"\"\"Test creating context with all args.\"\"\"\n ctx = ProcessingContext(\n footnotes=[\"[1] Note\"],\n ignore_footnotes=True,\n page_count=10\n )\n assert len(ctx.footnotes) == 1\n assert ctx.ignore_footnotes is True\n assert ctx.page_count == 10\n\n\nclass TestPageNumberRemover:\n \"\"\"Tests for PageNumberRemover.\"\"\"\n\n def test_name(self):\n \"\"\"Test processor name.\"\"\"\n processor = PageNumberRemover()\n assert processor.name == \"page_number_remover\"\n\n def test_remove_standalone_numbers(self):\n \"\"\"Test removing standalone page numbers.\"\"\"\n processor = PageNumberRemover()\n ctx = ProcessingContext(footnotes=[], page_count=50)\n\n text = \"Some text here.\\n\\n42\\n\\nMore text here.\"\n result = processor.process(text, ctx)\n\n assert \"Some text here.\" in result\n assert \"More text here.\" in result\n # The standalone \"42\" should be removed\n lines = [line.strip() for line in result.split(\"\\n\") if line.strip()]\n assert \"42\" not in lines\n\n def test_remove_page_x_format(self):\n \"\"\"Test removing 'Page X' format.\"\"\"\n processor = PageNumberRemover()\n ctx = ProcessingContext(footnotes=[], page_count=50)\n\n text = \"Some text.\\nPage 15\\nMore text.\"\n result = processor.process(text, ctx)\n\n assert \"Some text.\" in result\n assert \"More text.\" in result\n assert \"Page 15\" not in result\n\n def test_remove_page_x_of_y_format(self):\n \"\"\"Test removing 'Page X of Y' format.\"\"\"\n processor = PageNumberRemover()\n ctx = ProcessingContext(footnotes=[], page_count=50)\n\n text = \"Some text.\\nPage 5 of 20\\nMore text.\"\n result = processor.process(text, ctx)\n\n assert \"Page 5 of 20\" not in result\n\n def test_remove_centered_page_numbers(self):\n \"\"\"Test removing centered page numbers like '- 42 -'.\"\"\"\n processor = PageNumberRemover()\n ctx = ProcessingContext(footnotes=[], page_count=50)\n\n text = \"Some text.\\n- 42 -\\nMore text.\"\n result = processor.process(text, ctx)\n\n assert \"- 42 -\" not in result\n\n def test_keep_regular_numbers(self):\n \"\"\"Test that regular numbers in text are kept.\"\"\"\n processor = PageNumberRemover()\n ctx = ProcessingContext(footnotes=[], page_count=50)\n\n text = \"The year was 1984. There were 100 people.\"\n result = processor.process(text, ctx)\n\n assert \"1984\" in result\n assert \"100\" in result\n\n\nclass TestFootnoteHandler:\n \"\"\"Tests for FootnoteHandler.\"\"\"\n\n def test_name(self):\n \"\"\"Test processor name.\"\"\"\n processor = FootnoteHandler()\n assert processor.name == \"footnote_handler\"\n\n def test_remove_bracket_footnotes(self):\n \"\"\"Test removing [1] style footnotes when ignored.\"\"\"\n processor = FootnoteHandler()\n ctx = ProcessingContext(footnotes=[], ignore_footnotes=True)\n\n text = \"This is some text[1] with a footnote[2].\"\n result = processor.process(text, ctx)\n\n assert \"[1]\" not in result\n assert \"[2]\" not in result\n assert \"This is some text with a footnote.\" in result\n\n def test_remove_caret_footnotes(self):\n \"\"\"Test removing ^1 style footnotes when ignored.\"\"\"\n processor = FootnoteHandler()\n ctx = ProcessingContext(footnotes=[], ignore_footnotes=True)\n\n text = \"This is some text^1 with a footnote.\"\n result = processor.process(text, ctx)\n\n assert \"^1\" not in result\n\n def test_insert_footnotes_inline(self):\n \"\"\"Test inserting footnote content inline when not ignored.\"\"\"\n processor = FootnoteHandler()\n ctx = ProcessingContext(\n footnotes=[\"[1] This is footnote one.\"],\n ignore_footnotes=False\n )\n\n text = \"This is some text[1] with a footnote.\"\n result = processor.process(text, ctx)\n\n assert \"Footnote:\" in result\n assert \"This is footnote one\" in result\n\n def test_multiple_footnotes_inline(self):\n \"\"\"Test inserting multiple footnotes inline.\"\"\"\n processor = FootnoteHandler()\n ctx = ProcessingContext(\n footnotes=[\"[1] First note.\", \"[2] Second note.\"],\n ignore_footnotes=False\n )\n\n text = \"Text with firs | |
| [2025-12-29T13:28:36.660Z] [INFO] t[1] and second[2] references.\"\n result = processor.process(text, ctx)\n\n assert \"First note\" in result\n assert \"Second note\" in result\n\n\nclass TestPreprocessorPipeline:\n \"\"\"Tests for PreprocessorPipeline.\"\"\"\n\n def test_add_and_process(self):\n \"\"\"Test adding preprocessors and processing text.\"\"\"\n pipeline = PreprocessorPipeline()\n pipeline.add(PageNumberRemover())\n\n ctx = ProcessingContext(footnotes=[], page_count=10)\n text = \"Text\\n\\n5\\n\\nMore text\"\n result = pipeline.process(text, ctx)\n\n # Page number should be removed\n lines = [line.strip() for line in result.split(\"\\n\") if line.strip()]\n assert \"5\" not in lines\n\n def test_chain_preprocessors(self):\n \"\"\"Test chaining multiple preprocessors.\"\"\"\n pipeline = PreprocessorPipeline()\n pipeline.add(PageNumberRemover())\n pipeline.add(FootnoteHandler())\n\n ctx = ProcessingContext(footnotes=[], ignore_footnotes=True, page_count=10)\n text = \"Text[1]\\n\\n5\\n\\nMore text[2]\"\n result = pipeline.process(text, ctx)\n\n # Both page numbers and footnote references should be removed\n assert \"[1]\" not in result\n assert \"[2]\" not in result\n\n def test_remove_preprocessor(self):\n \"\"\"Test removing a preprocessor by name.\"\"\"\n pipeline = PreprocessorPipeline()\n pipeline.add(PageNumberRemover())\n pipeline.add(FootnoteHandler())\n\n assert len(pipeline.preprocessors) == 2\n\n removed = pipeline.remove(\"page_number_remover\")\n assert removed is True\n assert len(pipeline.preprocessors) == 1\n\n def test_normalize_whitespace(self):\n \"\"\"Test that pipeline normalizes whitespace.\"\"\"\n pipeline = PreprocessorPipeline()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"Line 1\\n\\n\\n\\n\\nLine 2\"\n result = pipeline.process(text, ctx)\n\n # Multiple newlines should be reduced\n assert \"\\n\\n\\n\" not in result\n\n\nclass TestSymbolConverter:\n \"\"\"Tests for SymbolConverter.\"\"\"\n\n def test_name(self):\n \"\"\"Test processor name.\"\"\"\n processor = SymbolConverter()\n assert processor.name == \"symbol_converter\"\n\n def test_convert_equals_in_equation(self):\n \"\"\"Test converting equals sign in equations.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"The formula is x = 5\"\n result = processor.process(text, ctx)\n\n assert \"equals\" in result.lower()\n assert \" = \" not in result\n\n def test_convert_numbered_list_period(self):\n \"\"\"Test converting numbered lists with periods.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"1. First item\\n2. Second item\\n3. Third item\"\n result = processor.process(text, ctx)\n\n assert \"Point 1\" in result\n assert \"Point 2\" in result\n assert \"Point 3\" in result\n\n def test_convert_numbered_list_parenthesis(self):\n \"\"\"Test converting numbered lists with parentheses.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"1) First item\\n2) Second item\"\n result = processor.process(text, ctx)\n\n # Parenthesis-style should just use the number\n assert \"1.\" in result\n assert \"2.\" in result\n\n def test_convert_percentage(self):\n \"\"\"Test converting percentage symbol.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"The growth was 50%\"\n result = processor.process(text, ctx)\n\n assert \"percent\" in result.lower()\n assert \"%\" not in result\n\n def test_convert_currency(self):\n \"\"\"Test converting currency symbols.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"The price is $100\"\n result = processor.process(text, ctx)\n\n assert \"dollars\" in result.lower()\n\n def test_convert_ampersand(self):\n \"\"\"Test converting ampersand to 'and'.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"Salt & pepper\"\n result = processor.process(text, ctx)\n\n assert \" and \" in result.lower()\n assert \"&\" not in result\n\n def test_convert_hash_number(self):\n \"\"\"Test converting hash with number.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"Issue #42\"\n result = processor.process(text, ctx)\n\n assert \"number 42\" in result.lower()\n assert \"#\" not in result\n\n def test_convert_arrow(self):\n \"\"\"Test converting arrow symbols.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"Go → forward\"\n result = processor.process(text, ctx)\n\n assert \"arrow\" in result.lower()\n\n def test_preserve_hyphens_in_words(self):\n \"\"\"Test that hyphens in compound words are preserved.\"\"\"\n processor = SymbolConverter()\n ctx = ProcessingContext(footnotes=[])\n\n text = \"This is a well-known fact\"\n result = processor.process(text, ctx)\n\n # Hyphens in compound words should not be changed\n assert \"well-known\" in result or \"well known\" in result\n\n\nclass TestDefaultPipeline:\n \"\"\"Tests for the default pipeline.\"\"\"\n\n def test_default_pipeline_has_processors(self):\n \"\"\"Test that default pipeline has expected processors.\"\"\"\n pipeline = create_default_pipeline()\n\n names = pipeline.preprocessors\n assert \"page_number_remover\" in names\n assert \"footnote_handler\" in names\n assert \"symbol_converter\" in names\n","numLines":336,"startLine":1,"totalLines":336}}} | |
| [2025-12-29T13:28:41.969Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_0163jseT7EtKqkto5ashNpHM", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
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| "text": "Now I have a complete understanding of the codebase. Let me update the todo list and start working on the issues:" | |
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| "content": "Finalize PR with proper description", | |
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| }, | |
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| }, | |
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| "content": "Run tests and verify changes", | |
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| }, | |
| { | |
| "content": "Finalize PR with proper description", | |
| "status": "pending", | |
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| } | |
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| [2025-12-29T13:28:55.893Z] [INFO] { | |
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| { | |
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| "text": "Let me analyze the issues from the GitHub issue more carefully:\n\n**Issue #24 Analysis:**\n1. **GT 740 freezing on first chunk (Multilingual ru Auto)** - Likely due to the old GPU having limited VRAM (1-2GB). The multilingual model is 500M parameters which requires significant memory.\n2. **Russian text not read in Russian** - This could be a language detection issue or model issue.\n3. **Audio artifacts** - Likely a model limitation, but could be related to chunking or silence insertion.\n4. **Add collapsible text input field** - This is a UI feature request.\n5. **Symbol pronunciation should use dominant language** - The SymbolConverter currently uses hardcoded English. Should use the detected language.\n6. **Strange Russian intonation** - Likely model limitation.\n\nLet me start implementing the fixes. First, let me address the main technical issues:" | |
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| "status": "pending", | |
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| }, | |
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| "content": "Investigate audio artifacts (likely model limitation)", | |
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| "content": "Finalize PR with proper description", | |
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| } | |
| [2025-12-29T13:29:04.409Z] [INFO] { | |
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| "text": "Now let me implement the solutions. I'll start with the most impactful changes:\n\n### 1. Add GPU VRAM check and warning for old GPUs like GT 740" | |
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| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py", | |
| "old_string": " def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n logger.info(f\"CUDA available: {device_name}\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"", | |
| "new_string": " # Minimum VRAM recommended for models (in GB)\n # Multilingual and Standard models are ~500M params, Turbo is ~350M params\n MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings\n MIN_V**********RD_GB = 2.5\n MIN_VRAM_TURBO_GB = 2.0\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n vram_gb = self._get_gpu_vram_gb()\n logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _get_gpu_vram_gb(self) -> float:\n \"\"\"Get the total VRAM of the GPU in gigabytes.\n\n Returns:\n VRAM in GB, or 0.0 if unable to detect.\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return 0.0\n\n try:\n props = torch.cuda.get_device_properties(0)\n vram_bytes = props.total_memory\n return vram_bytes / (1024 ** 3)\n except Exception as e:\n logger.warning(f\"Failed to get GPU VRAM: {e}\")\n return 0.0\n\n def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:\n \"\"\"Check if GPU has enough VRAM for the selected model.\n\n Args:\n model_type: The model type (\"turbo\", \"standard\", \"multilingual\").\n\n Returns:\n Tuple of (is_sufficient, warning_message).\n If VRAM is sufficient or can't be detected, returns (True, \"\").\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return True, \"\"\n\n vram_gb = self._get_gpu_vram_gb()\n if vram_gb == 0.0:\n return True, \"\" # Can't detect, proceed anyway\n\n # Determine minimum VRAM for model\n min_vram = {\n \"turbo\": self.MIN_VRAM_TURBO_GB,\n \"standard\": self.MIN_VRAM_STANDARD_GB,\n \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,\n }.get(model_type, self.MIN_VRAM_STANDARD_GB)\n\n if vram_gb < min_vram:\n device_name = torch.cuda.get_device_name(0)\n warning = (\n f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"\n f\"but {model_type} model needs ~{min_vram:.1f} GB. \"\n f\"This may cause freezing or out-of-memory errors. \"\n f\"Consider using CPU mode or the Turbo model for better stability.\"\n )\n return False, warning\n\n return True, \"\"" | |
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| } | |
| [2025-12-29T13:29:36.257Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TCNUnVuzQtGFBFnmnFhgZC","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 82→ def name(self) -> str:\n 83→ \"\"\"Get the engine name.\"\"\"\n 84→ return \"chatterbox\"\n 85→\n 86→ # Minimum VRAM recommended for models (in GB)\n 87→ # Multilingual and Standard models are ~500M params, Turbo is ~350M params\n 88→ MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings\n 89→ MIN_V**********RD_GB = 2.5\n 90→ MIN_VRAM_TURBO_GB = 2.0\n 91→\n 92→ def _detect_best_device(self) -> str:\n 93→ \"\"\"Detect the best available device for inference.\n 94→\n 95→ Checks for GPU availability in the following order:\n 96→ 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 97→ 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 98→ 3. Apple MPS (Apple Silicon)\n 99→ 4. CPU fallback\n 100→\n 101→ Returns:\n 102→ Device string (\"cuda\", \"mps\", or \"cpu\").\n 103→ \"\"\"\n 104→ import torch\n 105→\n 106→ # Check for NVIDIA CUDA\n 107→ # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n 108→ # because standard PyTorch Windows builds only support NVIDIA CUDA\n 109→ if torch.cuda.is_available():\n 110→ try:\n 111→ device_name = torch.cuda.get_device_name(0)\n 112→ vram_gb = self._get_gpu_vram_gb()\n 113→ logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")\n 114→ return \"cuda\"\n 115→ except Exception as e:\n 116→ logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n 117→ # Fall through to CPU\n 118→\n 119→ # Check for MPS (Apple Silicon)\n 120→ if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n 121→ logger.info(\"Apple MPS available\")\n 122→ return \"mps\"\n 123→\n 124→ logger.info(\"No GPU available, using CPU\")\n 125→ return \"cpu\"\n 126→\n 127→ def _get_gpu_vram_gb(self) -> float:\n 128→ \"\"\"Get the total VRAM of the GPU in gigabytes.\n 129→\n 130→ Returns:\n 131→ VRAM in GB, or 0.0 if unable to detect.\n 132→ \"\"\"\n 133→ import torch\n 134→\n 135→ if not torch.cuda.is_available():\n 136→ return 0.0\n 137→\n 138→ try:\n 139→ props = torch.cuda.get_device_properties(0)\n 140→ vram_bytes = props.total_memory\n 141→ return vram_bytes / (1024 ** 3)\n 142→ except Exception as e:\n 143→ logger.warning(f\"Failed to get GPU VRAM: {e}\")\n 144→ return 0.0\n 145→\n 146→ def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:\n 147→ \"\"\"Check if GPU has enough VRAM for the selected model.\n 148→\n 149→ Args:\n 150→ model_type: The model type (\"turbo\", \"standard\", \"multilingual\").\n 151→\n 152→ Returns:\n 153→ Tuple of (is_sufficient, warning_message).\n 154→ If VRAM is sufficient or can't be detected, returns (True, \"\").\n 155→ \"\"\"\n 156→ import torch\n 157→\n 158→ if not torch.cuda.is_available():\n 159→ return True, \"\"\n 160→\n 161→ vram_gb = self._get_gpu_vram_gb()\n 162→ if vram_gb == 0.0:\n 163→ return True, \"\" # Can't detect, proceed anyway\n 164→\n 165→ # Determine minimum VRAM for model\n 166→ min_vram = {\n 167→ \"turbo\": self.MIN_VRAM_TURBO_GB,\n 168→ \"standard\": self.MIN_VRAM_STANDARD_GB,\n 169→ \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,\n 170→ }.get(model_type, self.MIN_VRAM_STANDARD_GB)\n 171→\n 172→ if vram_gb < min_vram:\n 173→ device_name = torch.cuda.get_device_name(0)\n 174→ warning = (\n 175→ f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"\n 176→ f\"but {model_type} model needs ~{min_vram:.1f} GB. \"\n 177→ f\"This may cause freezing or out-of-memory errors. \"\n 178→ f\"Consider using CPU mode or the Turbo model for better stability.\"\n 179→ )\n 180→ return False, warning\n 181→\n 182→ return True, \"\"\n 183→\n 184→ def _validate_device(self, requested_device: str) -> str:\n 185→ \"\"\"Validate the requested device and return a valid device.\n 186→"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"7109bb87-448a-4e82-abf8-55ac5214be05","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py","oldString":" def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n logger.info(f\"CUDA available: {device_name}\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"","newString":" # Minimum VRAM recommended for models (in GB)\n # Multilingual and Standard models are ~500M params, Turbo is ~350M params\n MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings\n MIN_V**********RD_GB = 2.5\n MIN_VRAM_TURBO_GB = 2.0\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n vram_gb = self._get_gpu_vram_gb()\n logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _get_gpu_vram_gb(self) -> float:\n \"\"\"Get the total VRAM of the GPU in gigabytes.\n\n Returns:\n VRAM in GB, or 0.0 if unable to detect.\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return 0.0\n\n try:\n props = torch.cuda.get_device_properties(0)\n vram_bytes = props.total_memory\n return vram_bytes / (1024 ** 3)\n except Exception as e:\n logger.warning(f\"Failed to get GPU VRAM: {e}\")\n return 0.0\n\n def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:\n \"\"\"Check if GPU has enough VRAM for the selected model.\n\n Args:\n model_type: The model type (\"turbo\", \"standard\", \"multilingual\").\n\n Returns:\n Tuple of (is_sufficient, warning_message).\n If VRAM is sufficient or can't be detected, returns (True, \"\").\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return True, \"\"\n\n vram_gb = self._get_gpu_vram_gb()\n if vram_gb == 0.0:\n return True, \"\" # Can't detect, proceed anyway\n\n # Determine minimum VRAM for model\n min_vram = {\n \"turbo\": self.MIN_VRAM_TURBO_GB,\n \"standard\": self.MIN_VRAM_STANDARD_GB,\n \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,\n }.get(model_type, self.MIN_VRAM_STANDARD_GB)\n\n if vram_gb < min_vram:\n device_name = torch.cuda.get_device_name(0)\n warning = (\n f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"\n f\"but {model_type} model needs ~{min_vram:.1f} GB. \"\n f\"This may cause freezing or out-of-memory errors. \"\n f\"Consider using CPU mode or the Turbo model for better stability.\"\n )\n return False, warning\n\n return True, \"\"","originalFile":"\"\"\"Chatterbox TTS engine implementation.\"\"\"\n\nimport logging\nimport os\nimport time\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef _patch_torch_load_for_cpu(device: str):\n \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n\n This is a workaround for the chatterbox multilingual model which doesn't properly\n handle loading models that were saved on CUDA devices when running on CPU.\n\n See: https://github.com/resemble-ai/chatterbox/issues/96\n\n Args:\n device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n \"\"\"\n import torch\n\n # Only patch if we're loading on a non-CUDA device\n if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n original_torch_load = torch.load\n\n def patched_torch_load(f, map_location=None, **kwargs):\n # If no map_location specified, default to CPU for safe loading\n if map_location is None:\n map_location = \"cpu\"\n return original_torch_load(f, map_location=map_location, **kwargs)\n\n torch.load = patched_torch_load\n try:\n yield\n finally:\n torch.load = original_torch_load\n else:\n # No patching needed for CUDA devices\n yield\n\n\nclass HuggingFaceTokenError(RuntimeError):\n \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n pass\n\n\nclass CUDANotAvailableError(RuntimeError):\n \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n pass\n\n\nclass ChatterboxEngine(TTSEngine):\n \"\"\"TTS engine using Resemble AI's Chatterbox models.\n\n Supports three model variants:\n - Turbo: Fast, English-only, 350M parameters\n - Standard: English with CFG tuning, 500M parameters\n - Multilingual: 23+ languages, 500M parameters\n \"\"\"\n\n # Supported languages for the multilingual model\n MULTI************UAGES = [\n \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n \"sw\", \"tr\", \"zh\"\n ]\n\n def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n\n @property\n def name(self) -> str:\n \"\"\"Get the engine name.\"\"\"\n return \"chatterbox\"\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n logger.info(f\"CUDA available: {device_name}\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _validate_device(self, requested_device: str) -> str:\n \"\"\"Validate the requested device and return a valid device.\n\n If the requested device is not available, falls back to CPU with a warning.\n\n Args:\n requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n\n Returns:\n A valid device string that PyTorch can use.\n \"\"\"\n import torch\n\n if requested_device == \"auto\":\n return self._detect_best_device()\n\n if requested_device == \"cuda\":\n if not torch.cuda.is_available():\n logger.warning(\n \"GPU (CUDA) was requested but is not available. \"\n \"This can happen if:\\n\"\n \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n \" - PyTorch was not installed with CUDA support\\n\"\n \" - CUDA drivers are not properly installed\\n\"\n \"Falling back to CPU mode.\"\n )\n return \"cpu\"\n return \"cuda\"\n\n if requested_device == \"mps\":\n if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n return \"cpu\"\n return \"mps\"\n\n return requested_device # \"cpu\" or unknown\n\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n\n # Set HF_TOKEN environment variable if provided in config\n # This helps the turbo model which requires token=True by default\n if hasattr(config, 'hf_token') and config.hf_token:\n os.environ[\"HF_TOKEN\"] = config.hf_token\n logger.info(\"HuggingFace token configured from settings\")\n\n try:\n if config.model_type == \"turbo\":\n from chatterbox.tts_turbo import ChatterboxTurboTTS\n self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n\n elif config.model_type == \"multilingual\":\n from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n # Use patch to handle CUDA-saved models on CPU/MPS devices\n # See: https://github.com/resemble-ai/chatterbox/issues/96\n with _patch_torch_load_for_cpu(device):\n self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n\n else: # standard\n from chatterbox.tts import ChatterboxTTS\n self._model = ChatterboxTTS.from_pretrained(device=device)\n\n self._initialized = True\n logger.info(\"Chatterbox model initialized successfully\")\n\n except Exception as e:\n error_msg = str(e)\n logger.error(f\"Failed to initialize Chatterbox: {e}\")\n\n # Check for HuggingFace token errors\n if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n raise HuggingFaceTokenError(\n \"HuggingFace token is required to download the model.\\n\\n\"\n \"Please do one of the following:\\n\"\n \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n \"2. Set the HF_TOKEN environment variable\\n\"\n \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n \"Get your token at: https://huggingface.co/settings/tokens\"\n ) from e\n\n # Check for CUDA loading errors on CPU machines or AMD GPU users\n if (\"torch.cuda.is_available() is False\" in error_msg or\n \"CUDA device\" in error_msg or\n \"Torch not compiled with CUDA enabled\" in error_msg):\n raise CUDANotAvailableError(\n \"GPU acceleration is not available on this system.\\n\\n\"\n \"Possible reasons:\\n\"\n \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n \"- PyTorch was installed without CUDA support\\n\"\n \"- NVIDIA drivers are not installed\\n\\n\"\n \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n \"The application will work on CPU, though slower.\"\n ) from e\n\n raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized.\"\"\"\n return self._initialized and self._model is not None\n\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\"\"\"\n if self._config and self._config.model_type == \"multilingual\":\n return self.MULTILINGUAL_LANGUAGES\n return [\"en\"] # Turbo and standard are English-only\n\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n\n Raises:\n RuntimeError: If synthesis fails or engine not initialized.\n \"\"\"\n if not self.is_initialized():\n raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n\n import torch\n import torchaudio\n\n # Split text into chunks for long texts\n chunks = self._split_into_chunks(text, self._config.chunk_size)\n total_chunks = len(chunks)\n\n logger.info(f\"Synthesizing {total_chunks} chunks\")\n\n audio_segments = []\n sample_rate = self._model.sr\n was_cancelled = False\n chunks_completed = 0\n chunk_times = [] # Track time for each chunk to estimate remaining time\n start_time = time.time()\n\n for i, chunk in enumerate(chunks):\n # Check for cancellation before processing each chunk\n if cancel_check and cancel_check():\n logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n was_cancelled = True\n break\n\n # Calculate estimated remaining time based on average chunk time\n estimated_remaining = None\n if chunk_times:\n avg_chunk_time = sum(chunk_times) / len(chunk_times)\n remaining_chunks = total_chunks - i\n estimated_remaining = avg_chunk_time * remaining_chunks\n\n if progress_callback:\n progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n\n chunk_start_time = time.time()\n\n if not chunk.strip():\n continue\n\n try:\n # Generate audio for this chunk\n wav = self._generate_chunk(chunk)\n audio_segments.append(wav)\n chunks_completed += 1\n\n # Track chunk processing time for estimation\n chunk_time = time.time() - chunk_start_time\n chunk_times.append(chunk_time)\n logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n\n except Exception as e:\n logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n # Continue with other chunks\n continue\n\n # Handle case where no audio was generated\n if not audio_segments:\n if was_cancelled:\n raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n raise RuntimeError(\"No audio was generated\")\n\n # Concatenate all audio segments\n if len(audio_segments) == 1:\n final_audio = audio_segments[0]\n else:\n # Add small silence between segments\n silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n padded_segments = []\n for seg in audio_segments:\n padded_segments.append(seg)\n padded_segments.append(silence)\n # Remove last silence\n padded_segments = padded_segments[:-1]\n final_audio = torch.cat(padded_segments, dim=1)\n\n # Save to file\n output_path = Path(output_path)\n output_path.parent.mkdir(parents=True, exist_ok=True)\n torchaudio.save(str(output_path), final_audio, sample_rate)\n\n # Calculate duration\n duration = final_audio.shape[1] / sample_rate\n\n if progress_callback:\n if was_cancelled:\n progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n else:\n progress_callback(total_chunks, total_chunks, \"Complete\", None)\n\n return TTSResult(\n audio_path=output_path,\n duration_seconds=duration,\n sample_rate=sample_rate,\n text_processed=text,\n was_cancelled=was_cancelled,\n chunks_completed=chunks_completed,\n chunks_total=total_chunks\n )\n\n def _generate_chunk(self, text: str):\n \"\"\"Generate audio for a single text chunk.\n\n Args:\n text: The text chunk to synthesize.\n\n Returns:\n Audio tensor.\n \"\"\"\n voice_ref = None\n if self._config.voice_reference:\n voice_ref = str(self._config.voice_reference)\n\n if self._config.model_type == \"multilingual\":\n # Multilingual model requires language_id\n wav = self._model.generate(\n text,\n audio_prompt_path=voice_ref,\n language_id=self._config.language\n )\n elif voice_ref:\n # With voice reference\n wav = self._model.generate(text, audio_prompt_path=voice_ref)\n else:\n # Without voice reference\n wav = self._model.generate(text)\n\n return wav\n\n def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split text into chunks at natural boundaries.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per chunk.\n\n Returns:\n List of text chunks.\n \"\"\"\n if len(text) <= max_chars:\n return [text]\n\n chunks = []\n current_chunk = \"\"\n\n # Split by sentences first\n sentences = self._split_sentences(text)\n\n for sentence in sentences:\n if len(current_chunk) + len(sentence) <= max_chars:\n current_chunk += sentence\n else:\n if current_chunk:\n chunks.append(current_chunk.strip())\n # If single sentence is too long, split by phrases\n if len(sentence) > max_chars:\n phrases = self._split_phrases(sentence, max_chars)\n chunks.extend(phrases[:-1])\n current_chunk = phrases[-1] if phrases else \"\"\n else:\n current_chunk = sentence\n\n if current_chunk.strip():\n chunks.append(current_chunk.strip())\n\n return chunks\n\n def _split_sentences(self, text: str) -> list[str]:\n \"\"\"Split text into sentences.\n\n Args:\n text: The text to split.\n\n Returns:\n List of sentences.\n \"\"\"\n import re\n\n # Split on sentence-ending punctuation\n sentences = re.split(r'(?<=[.!?])\\s+', text)\n return sentences\n\n def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split a long sentence into smaller phrases.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per phrase.\n\n Returns:\n List of phrases.\n \"\"\"\n import re\n\n # Split on commas, semicolons, and other natural breaks\n parts = re.split(r'(?<=[,;:])\\s+', text)\n\n phrases = []\n current_phrase = \"\"\n\n | |
| [2025-12-29T13:29:36.270Z] [INFO] for part in parts:\n if len(current_phrase) + len(part) <= max_chars:\n current_phrase += \" \" + part if current_phrase else part\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n # If still too long, force split\n if len(part) > max_chars:\n words = part.split()\n current_phrase = \"\"\n for word in words:\n if len(current_phrase) + len(word) + 1 <= max_chars:\n current_phrase += \" \" + word if current_phrase else word\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n current_phrase = word\n else:\n current_phrase = part\n\n if current_phrase.strip():\n phrases.append(current_phrase.strip())\n\n return phrases\n","structuredPatch":[{"oldStart":83,"oldLines":6,"newStart":83,"newLines":12,"lines":[" \"\"\"Get the engine name.\"\"\""," return \"chatterbox\""," ","+ # Minimum VRAM recommended for models (in GB)","+ # Multilingual and Standard models are ~500M params, Turbo is ~350M params","+ MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings","+ MIN_V**********RD_GB = 2.5","+ MIN_VRAM_TURBO_GB = 2.0","+"," def _detect_best_device(self) -> str:"," \"\"\"Detect the best available device for inference."," "]},{"oldStart":103,"oldLines":7,"newStart":109,"newLines":8,"lines":[" if torch.cuda.is_available():"," try:"," device_name = torch.cuda.get_device_name(0)","- logger.info(f\"CUDA available: {device_name}\")","+ vram_gb = self._get_gpu_vram_gb()","+ logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")"," return \"cuda\""," except Exception as e:"," logger.warning(f\"CUDA detected but failed to get device info: {e}\")"]},{"oldStart":117,"oldLines":6,"newStart":124,"newLines":63,"lines":[" logger.info(\"No GPU available, using CPU\")"," return \"cpu\""," ","+ def _get_gpu_vram_gb(self) -> float:","+ \"\"\"Get the total VRAM of the GPU in gigabytes.","+","+ Returns:","+ VRAM in GB, or 0.0 if unable to detect.","+ \"\"\"","+ import torch","+","+ if not torch.cuda.is_available():","+ return 0.0","+","+ try:","+ props = torch.cuda.get_device_properties(0)","+ vram_bytes = props.total_memory","+ return vram_bytes / (1024 ** 3)","+ except Exception as e:","+ logger.warning(f\"Failed to get GPU VRAM: {e}\")","+ return 0.0","+","+ def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:","+ \"\"\"Check if GPU has enough VRAM for the selected model.","+","+ Args:","+ model_type: The model type (\"turbo\", \"standard\", \"multilingual\").","+","+ Returns:","+ Tuple of (is_sufficient, warning_message).","+ If VRAM is sufficient or can't be detected, returns (True, \"\").","+ \"\"\"","+ import torch","+","+ if not torch.cuda.is_available():","+ return True, \"\"","+","+ vram_gb = self._get_gpu_vram_gb()","+ if vram_gb == 0.0:","+ return True, \"\" # Can't detect, proceed anyway","+","+ # Determine minimum VRAM for model","+ min_vram = {","+ \"turbo\": self.MIN_VRAM_TURBO_GB,","+ \"standard\": self.MIN_VRAM_STANDARD_GB,","+ \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,","+ }.get(model_type, self.MIN_VRAM_STANDARD_GB)","+","+ if vram_gb < min_vram:","+ device_name = torch.cuda.get_device_name(0)","+ warning = (","+ f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"","+ f\"but {model_type} model needs ~{min_vram:.1f} GB. \"","+ f\"This may cause freezing or out-of-memory errors. \"","+ f\"Consider using CPU mode or the Turbo model for better stability.\"","+ )","+ return False, warning","+","+ return True, \"\"","+"," def _validate_device(self, requested_device: str) -> str:"," \"\"\"Validate the requested device and return a valid device."," "]}],"userModified":false,"replaceAll":false}} | |
| [2025-12-29T13:29:40.957Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01FH6gaGKdqYPmJUB129b6Cu", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me update the `initialize` method to use the VRAM check and also add a method to get the warning:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 3070, | |
| "cache_read_input_tokens": 63186, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 3070, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 3, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "09ae3725-9188-4362-90af-3dec06a22ab9" | |
| } | |
| [2025-12-29T13:29:51.900Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01FH6gaGKdqYPmJUB129b6Cu", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01GkVSuKWpKFnyf81W7PRYxp", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py", | |
| "old_string": " def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")", | |
| "new_string": " def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n # Check VRAM for GPU devices and warn if insufficient\n if device == \"cuda\":\n is_sufficient, warning = self._check_vram_for_model(config.model_type)\n if not is_sufficient:\n logger.warning(warning)\n # Store warning for UI to display\n self._vram_warning = warning\n else:\n self._vram_warning = None\n else:\n self._vram_warning = None\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 3070, | |
| "cache_read_input_tokens": 63186, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 3070, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 599, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "517b63eb-26d4-4c5b-982b-644a2c9644a3" | |
| } | |
| [2025-12-29T13:29:51.935Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GkVSuKWpKFnyf81W7PRYxp","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 217→ return \"mps\"\n 218→\n 219→ return requested_device # \"cpu\" or unknown\n 220→\n 221→ def initialize(self, config: TTSConfig) -> None:\n 222→ \"\"\"Initialize the Chatterbox TTS model.\n 223→\n 224→ Args:\n 225→ config: TTS configuration settings.\n 226→\n 227→ Raises:\n 228→ RuntimeError: If model loading fails.\n 229→ HuggingFaceTokenError: If HuggingFace token is required but not configured.\n 230→ CUDANotAvailableError: If model requires CUDA but it's not available.\n 231→ \"\"\"\n 232→ self._config = config\n 233→\n 234→ # Validate and determine device (with fallback to CPU if GPU not available)\n 235→ device = self._validate_device(config.device)\n 236→\n 237→ # Check VRAM for GPU devices and warn if insufficient\n 238→ if device == \"cuda\":\n 239→ is_sufficient, warning = self._check_vram_for_model(config.model_type)\n 240→ if not is_sufficient:\n 241→ logger.warning(warning)\n 242→ # Store warning for UI to display\n 243→ self._vram_warning = warning\n 244→ else:\n 245→ self._vram_warning = None\n 246→ else:\n 247→ self._vram_warning = None\n 248→\n 249→ logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n 250→\n 251→ # Set HF_TOKEN environment variable if provided in config\n 252→ # This helps the turbo model which requires token=True by default\n 253→ if hasattr(config, 'hf_token') and config.hf_token:"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"7980177e-6711-491c-b4c2-ec856489dd3f","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py","oldString":" def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")","newString":" def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n # Check VRAM for GPU devices and warn if insufficient\n if device == \"cuda\":\n is_sufficient, warning = self._check_vram_for_model(config.model_type)\n if not is_sufficient:\n logger.warning(warning)\n # Store warning for UI to display\n self._vram_warning = warning\n else:\n self._vram_warning = None\n else:\n self._vram_warning = None\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")","originalFile":"\"\"\"Chatterbox TTS engine implementation.\"\"\"\n\nimport logging\nimport os\nimport time\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef _patch_torch_load_for_cpu(device: str):\n \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n\n This is a workaround for the chatterbox multilingual model which doesn't properly\n handle loading models that were saved on CUDA devices when running on CPU.\n\n See: https://github.com/resemble-ai/chatterbox/issues/96\n\n Args:\n device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n \"\"\"\n import torch\n\n # Only patch if we're loading on a non-CUDA device\n if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n original_torch_load = torch.load\n\n def patched_torch_load(f, map_location=None, **kwargs):\n # If no map_location specified, default to CPU for safe loading\n if map_location is None:\n map_location = \"cpu\"\n return original_torch_load(f, map_location=map_location, **kwargs)\n\n torch.load = patched_torch_load\n try:\n yield\n finally:\n torch.load = original_torch_load\n else:\n # No patching needed for CUDA devices\n yield\n\n\nclass HuggingFaceTokenError(RuntimeError):\n \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n pass\n\n\nclass CUDANotAvailableError(RuntimeError):\n \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n pass\n\n\nclass ChatterboxEngine(TTSEngine):\n \"\"\"TTS engine using Resemble AI's Chatterbox models.\n\n Supports three model variants:\n - Turbo: Fast, English-only, 350M parameters\n - Standard: English with CFG tuning, 500M parameters\n - Multilingual: 23+ languages, 500M parameters\n \"\"\"\n\n # Supported languages for the multilingual model\n MULTI************UAGES = [\n \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n \"sw\", \"tr\", \"zh\"\n ]\n\n def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n\n @property\n def name(self) -> str:\n \"\"\"Get the engine name.\"\"\"\n return \"chatterbox\"\n\n # Minimum VRAM recommended for models (in GB)\n # Multilingual and Standard models are ~500M params, Turbo is ~350M params\n MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings\n MIN_V**********RD_GB = 2.5\n MIN_VRAM_TURBO_GB = 2.0\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n vram_gb = self._get_gpu_vram_gb()\n logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _get_gpu_vram_gb(self) -> float:\n \"\"\"Get the total VRAM of the GPU in gigabytes.\n\n Returns:\n VRAM in GB, or 0.0 if unable to detect.\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return 0.0\n\n try:\n props = torch.cuda.get_device_properties(0)\n vram_bytes = props.total_memory\n return vram_bytes / (1024 ** 3)\n except Exception as e:\n logger.warning(f\"Failed to get GPU VRAM: {e}\")\n return 0.0\n\n def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:\n \"\"\"Check if GPU has enough VRAM for the selected model.\n\n Args:\n model_type: The model type (\"turbo\", \"standard\", \"multilingual\").\n\n Returns:\n Tuple of (is_sufficient, warning_message).\n If VRAM is sufficient or can't be detected, returns (True, \"\").\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return True, \"\"\n\n vram_gb = self._get_gpu_vram_gb()\n if vram_gb == 0.0:\n return True, \"\" # Can't detect, proceed anyway\n\n # Determine minimum VRAM for model\n min_vram = {\n \"turbo\": self.MIN_VRAM_TURBO_GB,\n \"standard\": self.MIN_VRAM_STANDARD_GB,\n \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,\n }.get(model_type, self.MIN_VRAM_STANDARD_GB)\n\n if vram_gb < min_vram:\n device_name = torch.cuda.get_device_name(0)\n warning = (\n f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"\n f\"but {model_type} model needs ~{min_vram:.1f} GB. \"\n f\"This may cause freezing or out-of-memory errors. \"\n f\"Consider using CPU mode or the Turbo model for better stability.\"\n )\n return False, warning\n\n return True, \"\"\n\n def _validate_device(self, requested_device: str) -> str:\n \"\"\"Validate the requested device and return a valid device.\n\n If the requested device is not available, falls back to CPU with a warning.\n\n Args:\n requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n\n Returns:\n A valid device string that PyTorch can use.\n \"\"\"\n import torch\n\n if requested_device == \"auto\":\n return self._detect_best_device()\n\n if requested_device == \"cuda\":\n if not torch.cuda.is_available():\n logger.warning(\n \"GPU (CUDA) was requested but is not available. \"\n \"This can happen if:\\n\"\n \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n \" - PyTorch was not installed with CUDA support\\n\"\n \" - CUDA drivers are not properly installed\\n\"\n \"Falling back to CPU mode.\"\n )\n return \"cpu\"\n return \"cuda\"\n\n if requested_device == \"mps\":\n if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n return \"cpu\"\n return \"mps\"\n\n return requested_device # \"cpu\" or unknown\n\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n\n # Set HF_TOKEN environment variable if provided in config\n # This helps the turbo model which requires token=True by default\n if hasattr(config, 'hf_token') and config.hf_token:\n os.environ[\"HF_TOKEN\"] = config.hf_token\n logger.info(\"HuggingFace token configured from settings\")\n\n try:\n if config.model_type == \"turbo\":\n from chatterbox.tts_turbo import ChatterboxTurboTTS\n self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n\n elif config.model_type == \"multilingual\":\n from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n # Use patch to handle CUDA-saved models on CPU/MPS devices\n # See: https://github.com/resemble-ai/chatterbox/issues/96\n with _patch_torch_load_for_cpu(device):\n self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n\n else: # standard\n from chatterbox.tts import ChatterboxTTS\n self._model = ChatterboxTTS.from_pretrained(device=device)\n\n self._initialized = True\n logger.info(\"Chatterbox model initialized successfully\")\n\n except Exception as e:\n error_msg = str(e)\n logger.error(f\"Failed to initialize Chatterbox: {e}\")\n\n # Check for HuggingFace token errors\n if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n raise HuggingFaceTokenError(\n \"HuggingFace token is required to download the model.\\n\\n\"\n \"Please do one of the following:\\n\"\n \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n \"2. Set the HF_TOKEN environment variable\\n\"\n \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n \"Get your token at: https://huggingface.co/settings/tokens\"\n ) from e\n\n # Check for CUDA loading errors on CPU machines or AMD GPU users\n if (\"torch.cuda.is_available() is False\" in error_msg or\n \"CUDA device\" in error_msg or\n \"Torch not compiled with CUDA enabled\" in error_msg):\n raise CUDANotAvailableError(\n \"GPU acceleration is not available on this system.\\n\\n\"\n \"Possible reasons:\\n\"\n \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n \"- PyTorch was installed without CUDA support\\n\"\n \"- NVIDIA drivers are not installed\\n\\n\"\n \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n \"The application will work on CPU, though slower.\"\n ) from e\n\n raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized.\"\"\"\n return self._initialized and self._model is not None\n\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\"\"\"\n if self._config and self._config.model_type == \"multilingual\":\n return self.MULTILINGUAL_LANGUAGES\n return [\"en\"] # Turbo and standard are English-only\n\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n\n Raises:\n RuntimeError: If synthesis fails or engine not initialized.\n \"\"\"\n if not self.is_initialized():\n raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n\n import torch\n import torchaudio\n\n # Split text into chunks for long texts\n chunks = self._split_into_chunks(text, self._config.chunk_size)\n total_chunks = len(chunks)\n\n logger.info(f\"Synthesizing {total_chunks} chunks\")\n\n audio_segments = []\n sample_rate = self._model.sr\n was_cancelled = False\n chunks_completed = 0\n chunk_times = [] # Track time for each chunk to estimate remaining time\n start_time = time.time()\n\n for i, chunk in enumerate(chunks):\n # Check for cancellation before processing each chunk\n if cancel_check and cancel_check():\n logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n was_cancelled = True\n break\n\n # Calculate estimated remaining time based on average chunk time\n estimated_remaining = None\n if chunk_times:\n avg_chunk_time = sum(chunk_times) / len(chunk_times)\n remaining_chunks = total_chunks - i\n estimated_remaining = avg_chunk_time * remaining_chunks\n\n if progress_callback:\n progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n\n chunk_start_time = time.time()\n\n if not chunk.strip():\n continue\n\n try:\n # Generate audio for this chunk\n wav = self._generate_chunk(chunk)\n audio_segments.append(wav)\n chunks_completed += 1\n\n # Track chunk processing time for estimation\n chunk_time = time.time() - chunk_start_time\n chunk_times.append(chunk_time)\n logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n\n except Exception as e:\n logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n # Continue with other chunks\n continue\n\n # Handle case where no audio was generated\n if not audio_segments:\n if was_cancelled:\n raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n raise RuntimeError(\"No audio was generated\")\n\n # Concatenate all audio segments\n if len(audio_segments) == 1:\n final_audio = audio_segments[0]\n else:\n # Add small silence between segments\n silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n padded_segments = []\n for seg in audio_segments:\n padded | |
| [2025-12-29T13:29:51.938Z] [INFO] _segments.append(seg)\n padded_segments.append(silence)\n # Remove last silence\n padded_segments = padded_segments[:-1]\n final_audio = torch.cat(padded_segments, dim=1)\n\n # Save to file\n output_path = Path(output_path)\n output_path.parent.mkdir(parents=True, exist_ok=True)\n torchaudio.save(str(output_path), final_audio, sample_rate)\n\n # Calculate duration\n duration = final_audio.shape[1] / sample_rate\n\n if progress_callback:\n if was_cancelled:\n progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n else:\n progress_callback(total_chunks, total_chunks, \"Complete\", None)\n\n return TTSResult(\n audio_path=output_path,\n duration_seconds=duration,\n sample_rate=sample_rate,\n text_processed=text,\n was_cancelled=was_cancelled,\n chunks_completed=chunks_completed,\n chunks_total=total_chunks\n )\n\n def _generate_chunk(self, text: str):\n \"\"\"Generate audio for a single text chunk.\n\n Args:\n text: The text chunk to synthesize.\n\n Returns:\n Audio tensor.\n \"\"\"\n voice_ref = None\n if self._config.voice_reference:\n voice_ref = str(self._config.voice_reference)\n\n if self._config.model_type == \"multilingual\":\n # Multilingual model requires language_id\n wav = self._model.generate(\n text,\n audio_prompt_path=voice_ref,\n language_id=self._config.language\n )\n elif voice_ref:\n # With voice reference\n wav = self._model.generate(text, audio_prompt_path=voice_ref)\n else:\n # Without voice reference\n wav = self._model.generate(text)\n\n return wav\n\n def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split text into chunks at natural boundaries.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per chunk.\n\n Returns:\n List of text chunks.\n \"\"\"\n if len(text) <= max_chars:\n return [text]\n\n chunks = []\n current_chunk = \"\"\n\n # Split by sentences first\n sentences = self._split_sentences(text)\n\n for sentence in sentences:\n if len(current_chunk) + len(sentence) <= max_chars:\n current_chunk += sentence\n else:\n if current_chunk:\n chunks.append(current_chunk.strip())\n # If single sentence is too long, split by phrases\n if len(sentence) > max_chars:\n phrases = self._split_phrases(sentence, max_chars)\n chunks.extend(phrases[:-1])\n current_chunk = phrases[-1] if phrases else \"\"\n else:\n current_chunk = sentence\n\n if current_chunk.strip():\n chunks.append(current_chunk.strip())\n\n return chunks\n\n def _split_sentences(self, text: str) -> list[str]:\n \"\"\"Split text into sentences.\n\n Args:\n text: The text to split.\n\n Returns:\n List of sentences.\n \"\"\"\n import re\n\n # Split on sentence-ending punctuation\n sentences = re.split(r'(?<=[.!?])\\s+', text)\n return sentences\n\n def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split a long sentence into smaller phrases.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per phrase.\n\n Returns:\n List of phrases.\n \"\"\"\n import re\n\n # Split on commas, semicolons, and other natural breaks\n parts = re.split(r'(?<=[,;:])\\s+', text)\n\n phrases = []\n current_phrase = \"\"\n\n for part in parts:\n if len(current_phrase) + len(part) <= max_chars:\n current_phrase += \" \" + part if current_phrase else part\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n # If still too long, force split\n if len(part) > max_chars:\n words = part.split()\n current_phrase = \"\"\n for word in words:\n if len(current_phrase) + len(word) + 1 <= max_chars:\n current_phrase += \" \" + word if current_phrase else word\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n current_phrase = word\n else:\n current_phrase = part\n\n if current_phrase.strip():\n phrases.append(current_phrase.strip())\n\n return phrases\n","structuredPatch":[{"oldStart":234,"oldLines":6,"newStart":234,"newLines":18,"lines":[" # Validate and determine device (with fallback to CPU if GPU not available)"," device = self._validate_device(config.device)"," ","+ # Check VRAM for GPU devices and warn if insufficient","+ if device == \"cuda\":","+ is_sufficient, warning = self._check_vram_for_model(config.model_type)","+ if not is_sufficient:","+ logger.warning(warning)","+ # Store warning for UI to display","+ self._vram_warning = warning","+ else:","+ self._vram_warning = None","+ else:","+ self._vram_warning = None","+"," logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")"," "," # Set HF_TOKEN environment variable if provided in config"]}],"userModified":false,"replaceAll":false}} | |
| [2025-12-29T13:29:57.302Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01PDXxysJ4oymzEHHNv8WULY", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me add a method to get the VRAM warning and update the init:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1140, | |
| "cache_read_input_tokens": 66256, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1140, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 2, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "31dab956-0295-4ca6-96ca-59ea7bee95af" | |
| } | |
| [2025-12-29T13:30:01.289Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01PDXxysJ4oymzEHHNv8WULY", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_015gji5NnxoXViU5aGwe13bx", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py", | |
| "old_string": " def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False", | |
| "new_string": " def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n self._vram_warning: Optional[str] = None\n\n def get_vram_warning(self) -> Optional[str]:\n \"\"\"Get any VRAM warning message from initialization.\n\n Returns:\n Warning message if GPU VRAM is insufficient, None otherwise.\n \"\"\"\n return self._vram_warning" | |
| } | |
| } | |
| ], | |
| "stop_reason": "tool_use", | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1140, | |
| "cache_read_input_tokens": 66256, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1140, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 305, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": { | |
| "applied_edits": [] | |
| } | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "0b86f664-81f9-4833-a33d-6c5ffe30c3c0" | |
| } | |
| [2025-12-29T13:30:01.334Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_015gji5NnxoXViU5aGwe13bx", | |
| "type": "tool_result", | |
| "content": "The file /tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 71→ \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n 72→ \"sw\", \"tr\", \"zh\"\n 73→ ]\n 74→\n 75→ def __init__(self):\n 76→ \"\"\"Initialize the Chatterbox engine.\"\"\"\n 77→ self._model = None\n 78→ self._config: Optional[TTSConfig] = None\n 79→ self._initialized = False\n 80→ self._vram_warning: Optional[str] = None\n 81→\n 82→ def get_vram_warning(self) -> Optional[str]:\n 83→ \"\"\"Get any VRAM warning message from initialization.\n 84→\n 85→ Returns:\n 86→ Warning message if GPU VRAM is insufficient, None otherwise.\n 87→ \"\"\"\n 88→ return self._vram_warning\n 89→\n 90→ @property\n 91→ def name(self) -> str:\n 92→ \"\"\"Get the engine name.\"\"\"" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "b189360d-1851-47ba-9919-99e4568cf70e", | |
| "tool_use_result": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/tts/chatterbox.py", | |
| "oldString": " def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False", | |
| "newString": " def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n self._vram_warning: Optional[str] = None\n\n def get_vram_warning(self) -> Optional[str]:\n \"\"\"Get any VRAM warning message from initialization.\n\n Returns:\n Warning message if GPU VRAM is insufficient, None otherwise.\n \"\"\"\n return self._vram_warning", | |
| "originalFile": "\"\"\"Chatterbox TTS engine implementation.\"\"\"\n\nimport logging\nimport os\nimport time\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Optional\n\nfrom .base import TTSEngine, TTSConfig, TTSResult, ProgressCallback, CancelCheck\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef _patch_torch_load_for_cpu(device: str):\n \"\"\"Context manager that patches torch.load to use map_location for CPU/MPS devices.\n\n This is a workaround for the chatterbox multilingual model which doesn't properly\n handle loading models that were saved on CUDA devices when running on CPU.\n\n See: https://github.com/resemble-ai/chatterbox/issues/96\n\n Args:\n device: The target device (\"cpu\", \"cuda\", \"mps\", etc.)\n \"\"\"\n import torch\n\n # Only patch if we're loading on a non-CUDA device\n if device in (\"cpu\", \"mps\") or (device == \"cuda\" and not torch.cuda.is_available()):\n original_torch_load = torch.load\n\n def patched_torch_load(f, map_location=None, **kwargs):\n # If no map_location specified, default to CPU for safe loading\n if map_location is None:\n map_location = \"cpu\"\n return original_torch_load(f, map_location=map_location, **kwargs)\n\n torch.load = patched_torch_load\n try:\n yield\n finally:\n torch.load = original_torch_load\n else:\n # No patching needed for CUDA devices\n yield\n\n\nclass HuggingFaceTokenError(RuntimeError):\n \"\"\"Error raised when HuggingFace token is required but not configured.\"\"\"\n pass\n\n\nclass CUDANotAvailableError(RuntimeError):\n \"\"\"Error raised when model requires CUDA but it's not available.\"\"\"\n pass\n\n\nclass ChatterboxEngine(TTSEngine):\n \"\"\"TTS engine using Resemble AI's Chatterbox models.\n\n Supports three model variants:\n - Turbo: Fast, English-only, 350M parameters\n - Standard: English with CFG tuning, 500M parameters\n - Multilingual: 23+ languages, 500M parameters\n \"\"\"\n\n # Supported languages for the multilingual model\n MULTI************UAGES = [\n \"ar\", \"da\", \"de\", \"el\", \"en\", \"es\", \"fi\", \"fr\", \"he\", \"hi\",\n \"it\", \"ja\", \"ko\", \"ms\", \"nl\", \"no\", \"pl\", \"pt\", \"ru\", \"sv\",\n \"sw\", \"tr\", \"zh\"\n ]\n\n def __init__(self):\n \"\"\"Initialize the Chatterbox engine.\"\"\"\n self._model = None\n self._config: Optional[TTSConfig] = None\n self._initialized = False\n\n @property\n def name(self) -> str:\n \"\"\"Get the engine name.\"\"\"\n return \"chatterbox\"\n\n # Minimum VRAM recommended for models (in GB)\n # Multilingual and Standard models are ~500M params, Turbo is ~350M params\n MIN_V**************AL_GB = 3.0 # Multilingual needs more for language embeddings\n MIN_V**********RD_GB = 2.5\n MIN_VRAM_TURBO_GB = 2.0\n\n def _detect_best_device(self) -> str:\n \"\"\"Detect the best available device for inference.\n\n Checks for GPU availability in the following order:\n 1. NVIDIA CUDA (requires CUDA-enabled PyTorch build)\n 2. AMD ROCm (via HIP backend in PyTorch - requires ROCm PyTorch build)\n 3. Apple MPS (Apple Silicon)\n 4. CPU fallback\n\n Returns:\n Device string (\"cuda\", \"mps\", or \"cpu\").\n \"\"\"\n import torch\n\n # Check for NVIDIA CUDA\n # Note: torch.cuda.is_available() can return False for AMD GPUs on Windows\n # because standard PyTorch Windows builds only support NVIDIA CUDA\n if torch.cuda.is_available():\n try:\n device_name = torch.cuda.get_device_name(0)\n vram_gb = self._get_gpu_vram_gb()\n logger.info(f\"CUDA available: {device_name} ({vram_gb:.1f} GB VRAM)\")\n return \"cuda\"\n except Exception as e:\n logger.warning(f\"CUDA detected but failed to get device info: {e}\")\n # Fall through to CPU\n\n # Check for MPS (Apple Silicon)\n if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():\n logger.info(\"Apple MPS available\")\n return \"mps\"\n\n logger.info(\"No GPU available, using CPU\")\n return \"cpu\"\n\n def _get_gpu_vram_gb(self) -> float:\n \"\"\"Get the total VRAM of the GPU in gigabytes.\n\n Returns:\n VRAM in GB, or 0.0 if unable to detect.\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return 0.0\n\n try:\n props = torch.cuda.get_device_properties(0)\n vram_bytes = props.total_memory\n return vram_bytes / (1024 ** 3)\n except Exception as e:\n logger.warning(f\"Failed to get GPU VRAM: {e}\")\n return 0.0\n\n def _check_vram_for_model(self, model_type: str) -> tuple[bool, str]:\n \"\"\"Check if GPU has enough VRAM for the selected model.\n\n Args:\n model_type: The model type (\"turbo\", \"standard\", \"multilingual\").\n\n Returns:\n Tuple of (is_sufficient, warning_message).\n If VRAM is sufficient or can't be detected, returns (True, \"\").\n \"\"\"\n import torch\n\n if not torch.cuda.is_available():\n return True, \"\"\n\n vram_gb = self._get_gpu_vram_gb()\n if vram_gb == 0.0:\n return True, \"\" # Can't detect, proceed anyway\n\n # Determine minimum VRAM for model\n min_vram = {\n \"turbo\": self.MIN_VRAM_TURBO_GB,\n \"standard\": self.MIN_VRAM_STANDARD_GB,\n \"multilingual\": self.MIN_VRAM_MULTILINGUAL_GB,\n }.get(model_type, self.MIN_VRAM_STANDARD_GB)\n\n if vram_gb < min_vram:\n device_name = torch.cuda.get_device_name(0)\n warning = (\n f\"Your GPU ({device_name}) has {vram_gb:.1f} GB VRAM, \"\n f\"but {model_type} model needs ~{min_vram:.1f} GB. \"\n f\"This may cause freezing or out-of-memory errors. \"\n f\"Consider using CPU mode or the Turbo model for better stability.\"\n )\n return False, warning\n\n return True, \"\"\n\n def _validate_device(self, requested_device: str) -> str:\n \"\"\"Validate the requested device and return a valid device.\n\n If the requested device is not available, falls back to CPU with a warning.\n\n Args:\n requested_device: The device requested by the user (\"cuda\", \"cpu\", \"mps\", \"auto\").\n\n Returns:\n A valid device string that PyTorch can use.\n \"\"\"\n import torch\n\n if requested_device == \"auto\":\n return self._detect_best_device()\n\n if requested_device == \"cuda\":\n if not torch.cuda.is_available():\n logger.warning(\n \"GPU (CUDA) was requested but is not available. \"\n \"This can happen if:\\n\"\n \" - You have an AMD GPU (standard PyTorch only supports NVIDIA CUDA)\\n\"\n \" - PyTorch was not installed with CUDA support\\n\"\n \" - CUDA drivers are not properly installed\\n\"\n \"Falling back to CPU mode.\"\n )\n return \"cpu\"\n return \"cuda\"\n\n if requested_device == \"mps\":\n if not (hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()):\n logger.warning(\"MPS was requested but is not available. Falling back to CPU.\")\n return \"cpu\"\n return \"mps\"\n\n return requested_device # \"cpu\" or unknown\n\n def initialize(self, config: TTSConfig) -> None:\n \"\"\"Initialize the Chatterbox TTS model.\n\n Args:\n config: TTS configuration settings.\n\n Raises:\n RuntimeError: If model loading fails.\n HuggingFaceTokenError: If HuggingFace token is required but not configured.\n CUDANotAvailableError: If model requires CUDA but it's not available.\n \"\"\"\n self._config = config\n\n # Validate and determine device (with fallback to CPU if GPU not available)\n device = self._validate_device(config.device)\n\n # Check VRAM for GPU devices and warn if insufficient\n if device == \"cuda\":\n is_sufficient, warning = self._check_vram_for_model(config.model_type)\n if not is_sufficient:\n logger.warning(warning)\n # Store warning for UI to display\n self._vram_warning = warning\n else:\n self._vram_warning = None\n else:\n self._vram_warning = None\n\n logger.info(f\"Initializing Chatterbox {config.model_type} on {device}\")\n\n # Set HF_TOKEN environment variable if provided in config\n # This helps the turbo model which requires token=True by default\n if hasattr(config, 'hf_token') and config.hf_token:\n os.environ[\"HF_TOKEN\"] = config.hf_token\n logger.info(\"HuggingFace token configured from settings\")\n\n try:\n if config.model_type == \"turbo\":\n from chatterbox.tts_turbo import ChatterboxTurboTTS\n self._model = ChatterboxTurboTTS.from_pretrained(device=device)\n\n elif config.model_type == \"multilingual\":\n from chatterbox.mtl_tts import ChatterboxMultilingualTTS\n # Use patch to handle CUDA-saved models on CPU/MPS devices\n # See: https://github.com/resemble-ai/chatterbox/issues/96\n with _patch_torch_load_for_cpu(device):\n self._model = ChatterboxMultilingualTTS.from_pretrained(device=device)\n\n else: # standard\n from chatterbox.tts import ChatterboxTTS\n self._model = ChatterboxTTS.from_pretrained(device=device)\n\n self._initialized = True\n logger.info(\"Chatterbox model initialized successfully\")\n\n except Exception as e:\n error_msg = str(e)\n logger.error(f\"Failed to initialize Chatterbox: {e}\")\n\n # Check for HuggingFace token errors\n if \"Token is required\" in error_msg or \"LocalTokenNotFoundError\" in error_msg:\n raise HuggingFaceTokenError(\n \"HuggingFace token is required to download the model.\\n\\n\"\n \"Please do one of the following:\\n\"\n \"1. Enter your HuggingFace token in the 'HF Token' field in the Options section\\n\"\n \"2. Set the HF_TOKEN environment variable\\n\"\n \"3. Run 'huggingface-cli login' in your terminal\\n\\n\"\n \"Get your token at: https://huggingface.co/settings/tokens\"\n ) from e\n\n # Check for CUDA loading errors on CPU machines or AMD GPU users\n if (\"torch.cuda.is_available() is False\" in error_msg or\n \"CUDA device\" in error_msg or\n \"Torch not compiled with CUDA enabled\" in error_msg):\n raise CUDANotAvailableError(\n \"GPU acceleration is not available on this system.\\n\\n\"\n \"Possible reasons:\\n\"\n \"- You have an AMD GPU (PyTorch Windows builds only support NVIDIA CUDA)\\n\"\n \"- PyTorch was installed without CUDA support\\n\"\n \"- NVIDIA drivers are not installed\\n\\n\"\n \"Solution: Select 'Auto (GPU/CPU)' or 'CPU' in Device options.\\n\"\n \"The application will work on CPU, though slower.\"\n ) from e\n\n raise RuntimeError(f\"Failed to initialize TTS model: {e}\") from e\n\n def is_initialized(self) -> bool:\n \"\"\"Check if the engine is initialized.\"\"\"\n return self._initialized and self._model is not None\n\n def get_supported_languages(self) -> list[str]:\n \"\"\"Get list of supported language codes.\"\"\"\n if self._config and self._config.model_type == \"multilingual\":\n return self.MULTILINGUAL_LANGUAGES\n return [\"en\"] # Turbo and standard are English-only\n\n def synthesize(\n self,\n text: str,\n output_path: Path,\n progress_callback: Optional[ProgressCallback] = None,\n cancel_check: Optional[CancelCheck] = None\n ) -> TTSResult:\n \"\"\"Synthesize speech from text.\n\n Args:\n text: The text to convert to speech.\n output_path: Path where the audio file should be saved.\n progress_callback: Optional callback for progress updates.\n cancel_check: Optional callback that returns True if generation should stop.\n When cancelled, partial audio is saved and result.was_cancelled is True.\n\n Returns:\n TTSResult with information about the generated audio.\n\n Raises:\n RuntimeError: If synthesis fails or engine not initialized.\n \"\"\"\n if not self.is_initialized():\n raise RuntimeError(\"TTS engine not initialized. Call initialize() first.\")\n\n import torch\n import torchaudio\n\n # Split text into chunks for long texts\n chunks = self._split_into_chunks(text, self._config.chunk_size)\n total_chunks = len(chunks)\n\n logger.info(f\"Synthesizing {total_chunks} chunks\")\n\n audio_segments = []\n sample_rate = self._model.sr\n was_cancelled = False\n chunks_completed = 0\n chunk_times = [] # Track time for each chunk to estimate remaining time\n start_time = time.time()\n\n for i, chunk in enumerate(chunks):\n # Check for cancellation before processing each chunk\n if cancel_check and cancel_check():\n logger.info(f\"Generation cancelled at chunk {i + 1}/{total_chunks}\")\n was_cancelled = True\n break\n\n # Calculate estimated remaining time based on average chunk time\n estimated_remaining = None\n if chunk_times:\n avg_chunk_time = sum(chunk_times) / len(chunk_times)\n remaining_chunks = total_chunks - i\n estimated_remaining = avg_chunk_time * remaining_chunks\n\n if progress_callback:\n progress_callback(i + 1, total_chunks, f\"Processing chunk {i + 1}/{total_chunks}\", estimated_remaining)\n\n chunk_start_time = time.time()\n\n if not chunk.strip():\n continue\n\n try:\n # Generate audio for this chunk\n wav = self._generate_chunk(chunk)\n audio_segments.append(wav)\n chunks_completed += 1\n\n # Track chunk processing time for estimation\n chunk_time = time.time() - chunk_start_time\n chunk_times.append(chunk_time)\n logger.debug(f\"Chunk {i + 1} took {chunk_time:.1f}s\")\n\n except Exception as e:\n logger.warning(f\"Failed to synthesize chunk {i + 1}: {e}\")\n # Continue with other chunks\n continue\n\n # Handle case where no audio was generated\n if not audio_segments:\n if was_cancelled:\n raise RuntimeError(\"Generation was cancelled before any audio was generated\")\n raise RuntimeError(\"No audio was generated\")\n\n # Concatenate all audio segments\n if len(audio_segments) == 1:\n final_audio = audio_segments[0]\n else:\n # Add small silence between segments\n silence = torch.zeros(1, int(sample_rate * 0.3)) # 300ms silence\n padded_segments = []\n for seg in audio_segments:\n padded_segments.append(seg)\n padded_segments.append(silence)\n # Remove last silence\n padded_segments = padded_segments[:-1]\n final_audio = torch.cat(padded_segments, dim=1)\n\n # Save to file\n output_path = Path(output_path)\n output_path.parent.mkdir(parents=True, exist_ok=True)\n torchaudio.save(str(output_path), final_audio, sample_rate)\n\n # Calculate duration\n duration = final_audio.shape[1] / sample_rate\n\n if progress_callback:\n if was_cancelled:\n progress_callback(chunks_completed, total_chunks, f\"Cancelled - saved {chunks_completed}/{total_chunks} chunks\", None)\n else:\n progress_callback(total_chunks, total_chunks, \"Complete\", None)\n\n return TTSResult(\n audio_path=output_path,\n duration_seconds=duration,\n sample_rate=sample_rate,\n text_processed=text,\n was_cancelled=was_cancelled,\n chunks_completed=chunks_completed,\n chunks_total=total_chunks\n )\n\n def _generate_chunk(self, text: str):\n \"\"\"Generate audio for a single text chunk.\n\n Args:\n text: The text chunk to synthesize.\n\n Returns:\n Audio tensor.\n \"\"\"\n voice_ref = None\n if self._config.voice_reference:\n voice_ref = str(self._config.voice_reference)\n\n if self._config.model_type == \"multilingual\":\n # Multilingual model requires language_id\n wav = self._model.generate(\n text,\n audio_prompt_path=voice_ref,\n language_id=self._config.language\n )\n elif voice_ref:\n # With voice reference\n wav = self._model.generate(text, audio_prompt_path=voice_ref)\n else:\n # Without voice reference\n wav = self._model.generate(text)\n\n return wav\n\n def _split_into_chunks(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split text into chunks at natural boundaries.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per chunk.\n\n Returns:\n List of text chunks.\n \"\"\"\n if len(text) <= max_chars:\n return [text]\n\n chunks = []\n current_chunk = \"\"\n\n # Split by sentences first\n sentences = self._split_sentences(text)\n\n for sentence in sentences:\n if len(current_chunk) + len(sentence) <= max_chars:\n current_chunk += sentence\n else:\n if current_chunk:\n chunks.append(current_chunk.strip())\n # If single sentence is too long, split by phrases\n if len(sentence) > max_chars:\n phrases = self._split_phrases(sentence, max_chars)\n chunks.extend(phrases[:-1])\n current_chunk = phrases[-1] if phrases else \"\"\n else:\n current_chunk = sentence\n\n if current_chunk.strip():\n chunks.append(current_chunk.strip())\n\n return chunks\n\n def _split_sentences(self, text: str) -> list[str]:\n \"\"\"Split text into sentences.\n\n Args:\n text: The text to split.\n\n Returns:\n List of sentences.\n \"\"\"\n import re\n\n # Split on sentence-ending punctuation\n sentences = re.split(r'(?<=[.!?])\\s+', text)\n return sentences\n\n def _split_phrases(self, text: str, max_chars: int) -> list[str]:\n \"\"\"Split a long sentence into smaller phrases.\n\n Args:\n text: The text to split.\n max_chars: Maximum characters per phrase.\n\n Returns:\n List of phrases.\n \"\"\"\n import re\n\n # Split on commas, semicolons, and other natural breaks\n parts = re.split(r'(?<=[,;:])\\s+', text)\n\n phrases = []\n current_phrase = \"\"\n\n for part in parts:\n if len(current_phrase) + len(part) <= max_chars:\n current_phrase += \" \" + part if current_phrase else part\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n # If still too long, force split\n if len(part) > max_chars:\n words = part.split()\n current_phrase = \"\"\n for word in words:\n if len(current_phrase) + len(word) + 1 <= max_chars:\n current_phrase += \" \" + word if current_phrase else word\n else:\n if current_phrase:\n phrases.append(current_phrase.strip())\n current_phrase = word\n else:\n current_phrase = part\n\n if current_phrase.strip():\n phrases.append(current_phrase.strip())\n\n return phrases\n", | |
| "structuredPatch": [ | |
| { | |
| "oldStart": 77, | |
| "oldLines": 7, | |
| "newStart": 77, | |
| "newLines": 16, | |
| "lines": [ | |
| " self._model = None", | |
| " self._config: Optional[TTSConfig] = None", | |
| " self._initialized = False", | |
| "+ self._vram_warning: Optional[str] = None", | |
| " ", | |
| "+ def get_vram_warning(self) -> Optional[str]:", | |
| "+ \"\"\"Get any VRAM warning message from initialization.", | |
| "+", | |
| "+ Returns:", | |
| "+ Warning message if GPU VRAM is insufficient, None otherwise.", | |
| "+ \"\"\"", | |
| "+ return self._vram_warning", | |
| "+", | |
| " @property", | |
| " def name(self) -> str:", | |
| " \"\"\"Get the engine name.\"\"\"" | |
| ] | |
| } | |
| ], | |
| "userModified": false, | |
| "replaceAll": false | |
| } | |
| } | |
| [2025-12-29T13:30:04.649Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01Y1AEhFfTyvJi8baTYcZhn8", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me update the GUI to display VRAM warnings. First, let me update the todo and then modify the app.py:" | |
| } | |
| ], | |
| "stop_reason": null, | |
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| } | |
| [2025-12-29T13:30:09.079Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01Y1AEhFfTyvJi8baTYcZhn8", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_013DbsKWfqi1HgpRTAHkbWgv", | |
| "name": "TodoWrite", | |
| "input": { | |
| "todos": [ | |
| { | |
| "content": "Investigate GT 740 freezing - likely VRAM limitation on old GPU", | |
| "status": "completed", | |
| "activeForm": "Investigating GT 740 freezing issue" | |
| }, | |
| { | |
| "content": "Add low VRAM warning/fallback for old GPUs", | |
| "status": "completed", | |
| "activeForm": "Adding low VRAM warning" | |
| }, | |
| { | |
| "content": "Fix Russian text not being read in Russian (language detection issue)", | |
| "status": "pending", | |
| "activeForm": "Fixing Russian text language detection" | |
| }, | |
| { | |
| "content": "Add collapsible text input field as alternative to file selection", | |
| "status": "in_progress", | |
| "activeForm": "Adding collapsible text input field" | |
| }, | |
| { | |
| "content": "Fix symbol pronunciation to use dominant language in text", | |
| "status": "pending", | |
| "activeForm": "Fixing symbol language detection" | |
| }, | |
| { | |
| "content": "Investigate audio artifacts (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating audio artifacts" | |
| }, | |
| { | |
| "content": "Investigate Russian intonation issues (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating Russian intonation" | |
| }, | |
| { | |
| "content": "Run tests and verify changes", | |
| "status": "pending", | |
| "activeForm": "Running tests and verification" | |
| }, | |
| { | |
| "content": "Finalize PR with proper description", | |
| "status": "pending", | |
| "activeForm": "Finalizing pull request" | |
| } | |
| ] | |
| } | |
| } | |
| ], | |
| "stop_reason": "tool_use", | |
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| "uuid": "b2ac2013-de81-43d3-b02a-6731e329a1bf" | |
| } | |
| [2025-12-29T13:30:09.102Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_013DbsKWfqi1HgpRTAHkbWgv", | |
| "type": "tool_result", | |
| "content": "Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
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| { | |
| "content": "Investigate GT 740 freezing - likely VRAM limitation on old GPU", | |
| "status": "completed", | |
| "activeForm": "Investigating GT 740 freezing issue" | |
| }, | |
| { | |
| "content": "Add low VRAM warning/fallback for old GPUs", | |
| "status": "in_progress", | |
| "activeForm": "Adding low VRAM warning" | |
| }, | |
| { | |
| "content": "Fix Russian text not being read in Russian (language detection issue)", | |
| "status": "pending", | |
| "activeForm": "Fixing Russian text language detection" | |
| }, | |
| { | |
| "content": "Add collapsible text input field as alternative to file selection", | |
| "status": "pending", | |
| "activeForm": "Adding collapsible text input field" | |
| }, | |
| { | |
| "content": "Fix symbol pronunciation to use dominant language in text", | |
| "status": "pending", | |
| "activeForm": "Fixing symbol language detection" | |
| }, | |
| { | |
| "content": "Investigate audio artifacts (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating audio artifacts" | |
| }, | |
| { | |
| "content": "Investigate Russian intonation issues (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating Russian intonation" | |
| }, | |
| { | |
| "content": "Run tests and verify changes", | |
| "status": "pending", | |
| "activeForm": "Running tests and verification" | |
| }, | |
| { | |
| "content": "Finalize PR with proper description", | |
| "status": "pending", | |
| "activeForm": "Finalizing pull request" | |
| } | |
| ], | |
| "newTodos": [ | |
| { | |
| "content": "Investigate GT 740 freezing - likely VRAM limitation on old GPU", | |
| "status": "completed", | |
| "activeForm": "Investigating GT 740 freezing issue" | |
| }, | |
| { | |
| "content": "Add low VRAM warning/fallback for old GPUs", | |
| "status": "completed", | |
| "activeForm": "Adding low VRAM warning" | |
| }, | |
| { | |
| "content": "Fix Russian text not being read in Russian (language detection issue)", | |
| "status": "pending", | |
| "activeForm": "Fixing Russian text language detection" | |
| }, | |
| { | |
| "content": "Add collapsible text input field as alternative to file selection", | |
| "status": "in_progress", | |
| "activeForm": "Adding collapsible text input field" | |
| }, | |
| { | |
| "content": "Fix symbol pronunciation to use dominant language in text", | |
| "status": "pending", | |
| "activeForm": "Fixing symbol language detection" | |
| }, | |
| { | |
| "content": "Investigate audio artifacts (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating audio artifacts" | |
| }, | |
| { | |
| "content": "Investigate Russian intonation issues (likely model limitation)", | |
| "status": "pending", | |
| "activeForm": "Investigating Russian intonation" | |
| }, | |
| { | |
| "content": "Run tests and verify changes", | |
| "status": "pending", | |
| "activeForm": "Running tests and verification" | |
| }, | |
| { | |
| "content": "Finalize PR with proper description", | |
| "status": "pending", | |
| "activeForm": "Finalizing pull request" | |
| } | |
| ] | |
| } | |
| } | |
| [2025-12-29T13:30:12.028Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01JSdBVKKRppb7yDvavfjPDp", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me add the collapsible text input field feature. I need to add a collapsible section in the GUI for direct text input:" | |
| } | |
| ], | |
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| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 4, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "db71af81-1ed9-461f-a6b1-f7369d1e1079" | |
| } | |
| [2025-12-29T13:30:17.691Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01JSdBVKKRppb7yDvavfjPDp", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01SBTCjrft3wPKvu2egcycUp", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()", | |
| "new_string": " # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 433, | |
| "cache_read_input_tokens": 68298, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 433, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 454, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "e48a7958-33e1-43ba-a1d9-3d1a618c4e6f" | |
| } | |
| [2025-12-29T13:30:17.721Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SBTCjrft3wPKvu2egcycUp","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 284→ self._progress_animation_id = None # Track progress bar animation\n 285→ self._button_animation_id = None # Track button ellipsis animation\n 286→ self._ellipsis_state = 0 # Current ellipsis state (0-3)\n 287→\n 288→ # Variables\n 289→ self._input_file = ctk.StringVar()\n 290→ self._output_file = ctk.StringVar()\n 291→ self._voice_reference = ctk.StringVar()\n 292→ self._model_type = ctk.StringVar(value=\"turbo\")\n 293→ self._language = ctk.StringVar(value=\"en\")\n 294→ self._ignore_footnotes = ctk.BooleanVar(value=True)\n 295→ self._device = ctk.StringVar(value=\"auto\")\n 296→ self._hf_token = ctk.StringVar()\n 297→ self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n 298→ self._direct_text = \"\" # Store direct text input\n 299→\n 300→ # Build UI\n 301→ self._create_widgets()\n 302→"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"bb2ea998-d280-410a-ba1a-8ab37c6fdef2","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py","oldString":" # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()","newString":" # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input","originalFile":"\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animati | |
| [2025-12-29T13:30:17.724Z] [INFO] on\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n","structuredPatch":[{"oldStart":294,"oldLines":6,"newStart":294,"newLines":8,"lines":[" self._ignore_footnotes = ctk.BooleanVar(value=True)"," self._device = ctk.StringVar(value=\"auto\")"," self._hf_token = ctk.StringVar()","+ self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode","+ self._direct_text = \"\" # Store direct text input"," "," # Build UI"," self._create_widgets()"]}],"userModified":false,"replaceAll":false}} | |
| [2025-12-29T13:30:23.215Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01VPaYXfVQX969sz546cprsJ", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me add the collapsible text input section after the input file section:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 828, | |
| "cache_read_input_tokens": 68731, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 828, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 1, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "24fa355e-4871-4b10-a5cd-793d48b83294" | |
| } | |
| [2025-12-29T13:30:30.051Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01VPaYXfVQX969sz546cprsJ", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01XwwK2AmtLDRBULhxPcq7sW", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section", | |
| "new_string": " # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section" | |
| } | |
| } | |
| ], | |
| "stop_reason": "tool_use", | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 828, | |
| "cache_read_input_tokens": 68731, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 828, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 708, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": { | |
| "applied_edits": [] | |
| } | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "17304708-ba9b-4437-abf3-737090ec582c" | |
| } | |
| [2025-12-29T13:30:30.089Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01XwwK2AmtLDRBULhxPcq7sW","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 317→ font=ctk.CTkFont(size=24, weight=\"bold\")\n 318→ )\n 319→ title_label.pack(pady=(0, 20))\n 320→\n 321→ # Input file section\n 322→ self._input_file_frame = ctk.CTkFrame(main_frame)\n 323→ self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n 324→ self._create_file_section_in_frame(\n 325→ self._input_file_frame,\n 326→ \"Input Document:\",\n 327→ self._input_file,\n 328→ self._browse_input,\n 329→ self._get_input_filetypes()\n 330→ )\n 331→\n 332→ # Text input toggle\n 333→ text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n 334→ text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n 335→\n 336→ self._text_toggle_checkbox = ctk.CTkCheckBox(\n 337→ text_toggle_frame,\n 338→ text=\"Use text input instead of file\",\n 339→ variable=self._use_text_input,\n 340→ command=self._on_text_input_toggle\n 341→ )\n 342→ self._text_toggle_checkbox.pack(anchor=\"w\")\n 343→\n 344→ # Collapsible text input section (hidden by default)\n 345→ self._text_input_frame = ctk.CTkFrame(main_frame)\n 346→ # Don't pack yet - will be shown when checkbox is toggled\n 347→\n 348→ text_input_label = ctk.CTkLabel(\n 349→ self._text_input_frame,\n 350→ text=\"Enter text to convert to speech:\"\n 351→ )\n 352→ text_input_label.pack(anchor=\"w\", pady=(0, 5))\n 353→\n 354→ self._text_input_box = ctk.CTkTextbox(\n 355→ self._text_input_frame,\n 356→ height=150,\n 357→ wrap=\"word\"\n 358→ )\n 359→ self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n 360→\n 361→ text_input_help = ctk.CTkLabel(\n 362→ self._text_input_frame,\n 363→ text=\"Paste or type your text here. Supports multiple paragraphs.\",\n 364→ text_color=\"gray\",\n 365→ font=ctk.CTkFont(size=11)\n 366→ )\n 367→ text_input_help.pack(anchor=\"w\")\n 368→\n 369→ # Output file section\n 370→ self._create_file_section(\n 371→ main_frame,\n 372→ \"Output Audio File:\",\n 373→ self._output_file,"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"f79ff81a-9b7a-4487-9c41-1dd35c2041e7","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py","oldString":" # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section","newString":" # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section","originalFile":"\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._create_file_section(\n main_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._outpu | |
| [2025-12-29T13:30:30.092Z] [INFO] t_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n","structuredPatch":[{"oldStart":319,"oldLines":14,"newStart":319,"newLines":53,"lines":[" title_label.pack(pady=(0, 20))"," "," # Input file section","- self._create_file_section(","- main_frame,","+ self._input_file_frame = ctk.CTkFrame(main_frame)","+ self._input_file_frame.pack(fill=\"x\", pady=(0, 10))","+ self._create_file_section_in_frame(","+ self._input_file_frame,"," \"Input Document:\","," self._input_file,"," self._browse_input,"," self._get_input_filetypes()"," )"," ","+ # Text input toggle","+ text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")","+ text_toggle_frame.pack(fill=\"x\", pady=(0, 5))","+","+ self._text_toggle_checkbox = ctk.CTkCheckBox(","+ text_toggle_frame,","+ text=\"Use text input instead of file\",","+ variable=self._use_text_input,","+ command=self._on_text_input_toggle","+ )","+ self._text_toggle_checkbox.pack(anchor=\"w\")","+","+ # Collapsible text input section (hidden by default)","+ self._text_input_frame = ctk.CTkFrame(main_frame)","+ # Don't pack yet - will be shown when checkbox is toggled","+","+ text_input_label = ctk.CTkLabel(","+ self._text_input_frame,","+ text=\"Enter text to convert to speech:\"","+ )","+ text_input_label.pack(anchor=\"w\", pady=(0, 5))","+","+ self._text_input_box = ctk.CTkTextbox(","+ self._text_input_frame,","+ height=150,","+ wrap=\"word\"","+ )","+ self._text_input_box.pack(fill=\"x\", pady=(0, 5))","+","+ text_input_help = ctk.CTkLabel(","+ self._text_input_frame,","+ text=\"Paste or type your text here. Supports multiple paragraphs.\",","+ text_color=\"gray\",","+ font=ctk.CTkFont(size=11)","+ )","+ text_input_help.pack(anchor=\"w\")","+"," # Output file section"," self._create_file_section("," main_frame,"]}],"userModified":false,"replaceAll":false}} | |
| [2025-12-29T13:30:34.099Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01QaTeimB53FN1aAE3ckTqvR", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now I need to add the helper method and toggle handler. Let me first update the `_create_file_section` method to add a variant that works within an existing frame:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1531, | |
| "cache_read_input_tokens": 69559, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1531, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 1, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "1173e68a-52d1-4def-8630-ff4a1f67a167" | |
| } | |
| [2025-12-29T13:30:43.103Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01QaTeimB53FN1aAE3ckTqvR", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01NfUobUiFBiVvkkedeSZf8y", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")", | |
| "new_string": " def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n\n def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1531, | |
| "cache_read_input_tokens": 69559, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1531, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 693, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "f927ee4c-e881-4ef4-aa83-8dbe18f3e02c" | |
| } | |
| [2025-12-29T13:30:43.137Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01NfUobUiFBiVvkkedeSZf8y", | |
| "type": "tool_result", | |
| "content": "The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 583→ text_color=\"gray\"\n 584→ )\n 585→ self._status_label.pack(pady=(10, 0))\n 586→\n 587→ def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n 588→ \"\"\"Create a file selection section.\"\"\"\n 589→ frame = ctk.CTkFrame(parent)\n 590→ frame.pack(fill=\"x\", pady=(0, 10))\n 591→\n 592→ self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n 593→\n 594→ def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n 595→ \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n 596→ label = ctk.CTkLabel(frame, text=label_text)\n 597→ label.pack(anchor=\"w\")\n 598→\n 599→ input_frame = ctk.CTkFrame(frame)\n 600→ input_frame.pack(fill=\"x\", pady=(5, 0))\n 601→\n 602→ entry = ctk.CTkEntry(input_frame, textvariable=variable)\n 603→ entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n 604→\n 605→ btn = ctk.CTkButton(\n 606→ input_frame,\n 607→ text=\"Browse\",\n 608→ command=browse_command,\n 609→ width=100\n 610→ )\n 611→ btn.pack(side=\"right\")\n 612→\n 613→ def _get_input_filetypes(self):\n 614→ \"\"\"Get file types for input file dialog.\"\"\"\n 615→ extensions = self._reader_registry.supported_extensions" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "217d3329-c4c2-4c61-ba7b-c9d54d6e72a6", | |
| "tool_use_result": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "oldString": " def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")", | |
| "newString": " def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n\n def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")", | |
| "originalFile": "\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n", | |
| "structuredPatch": [ | |
| { | |
| "oldStart": 589, | |
| "oldLines": 6, | |
| "newStart": 589, | |
| "newLines": 10, | |
| "lines": [ | |
| " frame = ctk.CTkFrame(parent)", | |
| " frame.pack(fill=\"x\", pady=(0, 10))", | |
| " ", | |
| "+ self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)", | |
| "+", | |
| "+ def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):", | |
| "+ \"\"\"Create file selection widgets inside an existing frame.\"\"\"", | |
| " label = ctk.CTkLabel(frame, text=label_text)", | |
| " label.pack(anchor=\"w\")", | |
| " " | |
| ] | |
| } | |
| ], | |
| "userModified": false, | |
| "replaceAll": false | |
| } | |
| } | |
| [2025-12-29T13:30:48.757Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01GqYzt4wz3J2hWYdY2KEoWr", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me add the toggle handler method. Let me find where to add it:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1509, | |
| "cache_read_input_tokens": 71090, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1509, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 2, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "a75c860f-d3ce-45c0-bb39-aba4c4f94c19" | |
| } | |
| [2025-12-29T13:30:49.419Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01GqYzt4wz3J2hWYdY2KEoWr", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01WmhP156TiPotsmKUwkM2X9", | |
| "name": "Read", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "offset": 660, | |
| "limit": 100 | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1509, | |
| "cache_read_input_tokens": 71090, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1509, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 2, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "cfb32c1e-7e27-437d-9774-e6d3180f9f29" | |
| } | |
| [2025-12-29T13:30:49.521Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01WmhP156TiPotsmKUwkM2X9", | |
| "type": "tool_result", | |
| "content": " 660→ filename = filedialog.askopenfilename(\n 661→ title=\"Select Voice Reference Audio\",\n 662→ filetypes=[\n 663→ (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n 664→ (\"WAV files\", \"*.wav\"),\n 665→ (\"All files\", \"*.*\")\n 666→ ]\n 667→ )\n 668→ if filename:\n 669→ self._voice_reference.set(filename)\n 670→\n 671→ def _on_model_change(self):\n 672→ \"\"\"Handle model type change.\"\"\"\n 673→ if self._model_type.get() == \"multilingual\":\n 674→ self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n 675→ else:\n 676→ self._language_frame.pack_forget()\n 677→\n 678→ def _on_language_select(self, value):\n 679→ \"\"\"Handle language selection.\"\"\"\n 680→ # Extract language code from \"en - English\" format\n 681→ code = value.split(\" - \")[0]\n 682→ self._language.set(code)\n 683→\n 684→ def _start_conversion(self):\n 685→ \"\"\"Start the conversion process in a background thread.\"\"\"\n 686→ if self._processing:\n 687→ return\n 688→\n 689→ # Validate inputs\n 690→ input_file = self._input_file.get().strip()\n 691→ output_file = self._output_file.get().strip()\n 692→\n 693→ if not input_file:\n 694→ CTkMessagebox(\n 695→ title=\"Error\",\n 696→ message=\"Please select an input file.\",\n 697→ icon=\"cancel\"\n 698→ )\n 699→ return\n 700→\n 701→ if not output_file:\n 702→ CTkMessagebox(\n 703→ title=\"Error\",\n 704→ message=\"Please select an output file location.\",\n 705→ icon=\"cancel\"\n 706→ )\n 707→ return\n 708→\n 709→ if not Path(input_file).exists():\n 710→ CTkMessagebox(\n 711→ title=\"Error\",\n 712→ message=f\"Input file not found: {input_file}\",\n 713→ icon=\"cancel\"\n 714→ )\n 715→ return\n 716→\n 717→ # Start conversion in background thread\n 718→ self._processing = True\n 719→ self._cancel_requested = False\n 720→ self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n 721→ self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n 722→ self._progress_bar.set(0)\n 723→ self._start_button_animation() # Start ellipsis animation\n 724→\n 725→ thread = threading.Thread(target=self._run_conversion)\n 726→ thread.daemon = True\n 727→ thread.start()\n 728→\n 729→ def _cancel_conversion(self):\n 730→ \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n 731→ if self._processing and not self._cancel_requested:\n 732→ self._cancel_requested = True\n 733→ self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n 734→ self._update_progress(0, \"Cancelling... (saving generated audio)\")\n 735→ logger.info(\"Cancellation requested by user\")\n 736→\n 737→ def _run_conversion(self):\n 738→ \"\"\"Run the conversion process (in background thread).\"\"\"\n 739→ try:\n 740→ input_path = Path(self._input_file.get())\n 741→ output_path = Path(self._output_file.get())\n 742→\n 743→ # Step 1: Read document\n 744→ self._update_progress(0.1, \"Reading document...\")\n 745→ content = self._reader_registry.read(input_path)\n 746→ logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n 747→\n 748→ # Step 2: Preprocess text\n 749→ self._update_progress(0.2, \"Preprocessing text...\")\n 750→ context = ProcessingContext(\n 751→ footnotes=content.footnotes,\n 752→ ignore_footnotes=self._ignore_footnotes.get(),\n 753→ page_count=content.page_count\n 754→ )\n 755→ processed_text = self._pipeline.process(content.text, context)\n 756→ logger.info(f\"Processed text: {len(processed_text)} chars\")\n 757→\n 758→ if not processed_text.strip():\n 759→ raise ValueError(\"No text content found in document\")\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "9741a19f-a71e-4655-b9fa-497a2221c6c9", | |
| "tool_use_result": { | |
| "type": "text", | |
| "file": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "content": " filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")", | |
| "numLines": 100, | |
| "startLine": 660, | |
| "totalLines": 923 | |
| } | |
| } | |
| } | |
| [2025-12-29T13:30:54.776Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01BSbxCRtebanUjXCjW6Qk6B", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "I need to add the toggle handler and update the `_start_conversion` method to handle text input mode. Let me add the toggle handler first:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1487, | |
| "cache_read_input_tokens": 72599, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1487, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 1, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "f27c8f4e-50e3-4579-abca-1fd246ebcbf7" | |
| } | |
| [2025-12-29T13:31:02.509Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01BSbxCRtebanUjXCjW6Qk6B", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01TuxYJE7TUnBVeGj7amQLWw", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):", | |
| "new_string": " def _on_text_input_toggle(self):\n \"\"\"Handle toggle between file input and text input mode.\"\"\"\n if self._use_text_input.get():\n # Show text input, hide file input\n self._input_file_frame.pack_forget()\n self._text_input_frame.pack(fill=\"x\", pady=(0, 10), after=self._text_toggle_checkbox.master)\n else:\n # Show file input, hide text input\n self._text_input_frame.pack_forget()\n # Re-pack file input frame in the correct position\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10), before=self._text_toggle_checkbox.master)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):" | |
| } | |
| } | |
| ], | |
| "stop_reason": "tool_use", | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1487, | |
| "cache_read_input_tokens": 72599, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1487, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 528, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": { | |
| "applied_edits": [] | |
| } | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "d67ed118-1355-4f0f-88a7-02405ae7bb86" | |
| } | |
| [2025-12-29T13:31:02.547Z] [INFO] { | |
| "type": "user", | |
| "message": { | |
| "role": "user", | |
| "content": [ | |
| { | |
| "tool_use_id": "toolu_01TuxYJE7TUnBVeGj7amQLWw", | |
| "type": "tool_result", | |
| "content": "The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 667→ )\n 668→ if filename:\n 669→ self._voice_reference.set(filename)\n 670→\n 671→ def _on_text_input_toggle(self):\n 672→ \"\"\"Handle toggle between file input and text input mode.\"\"\"\n 673→ if self._use_text_input.get():\n 674→ # Show text input, hide file input\n 675→ self._input_file_frame.pack_forget()\n 676→ self._text_input_frame.pack(fill=\"x\", pady=(0, 10), after=self._text_toggle_checkbox.master)\n 677→ else:\n 678→ # Show file input, hide text input\n 679→ self._text_input_frame.pack_forget()\n 680→ # Re-pack file input frame in the correct position\n 681→ self._input_file_frame.pack(fill=\"x\", pady=(0, 10), before=self._text_toggle_checkbox.master)\n 682→\n 683→ def _on_model_change(self):\n 684→ \"\"\"Handle model type change.\"\"\"\n 685→ if self._model_type.get() == \"multilingual\":\n 686→ self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n 687→ else:\n 688→ self._language_frame.pack_forget()\n 689→\n 690→ def _on_language_select(self, value):\n 691→ \"\"\"Handle language selection.\"\"\"\n 692→ # Extract language code from \"en - English\" format\n 693→ code = value.split(\" - \")[0]\n 694→ self._language.set(code)" | |
| } | |
| ] | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "d7020e2f-4ee1-4535-ae90-ea84740c21ae", | |
| "tool_use_result": { | |
| "filePath": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "oldString": " def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):", | |
| "newString": " def _on_text_input_toggle(self):\n \"\"\"Handle toggle between file input and text input mode.\"\"\"\n if self._use_text_input.get():\n # Show text input, hide file input\n self._input_file_frame.pack_forget()\n self._text_input_frame.pack(fill=\"x\", pady=(0, 10), after=self._text_toggle_checkbox.master)\n else:\n # Show file input, hide text input\n self._text_input_frame.pack_forget()\n # Re-pack file input frame in the correct position\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10), before=self._text_toggle_checkbox.master)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):", | |
| "originalFile": "\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n\n def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n", | |
| "structuredPatch": [ | |
| { | |
| "oldStart": 668, | |
| "oldLines": 6, | |
| "newStart": 668, | |
| "newLines": 18, | |
| "lines": [ | |
| " if filename:", | |
| " self._voice_reference.set(filename)", | |
| " ", | |
| "+ def _on_text_input_toggle(self):", | |
| "+ \"\"\"Handle toggle between file input and text input mode.\"\"\"", | |
| "+ if self._use_text_input.get():", | |
| "+ # Show text input, hide file input", | |
| "+ self._input_file_frame.pack_forget()", | |
| "+ self._text_input_frame.pack(fill=\"x\", pady=(0, 10), after=self._text_toggle_checkbox.master)", | |
| "+ else:", | |
| "+ # Show file input, hide text input", | |
| "+ self._text_input_frame.pack_forget()", | |
| "+ # Re-pack file input frame in the correct position", | |
| "+ self._input_file_frame.pack(fill=\"x\", pady=(0, 10), before=self._text_toggle_checkbox.master)", | |
| "+", | |
| " def _on_model_change(self):", | |
| " \"\"\"Handle model type change.\"\"\"", | |
| " if self._model_type.get() == \"multilingual\":" | |
| ] | |
| } | |
| ], | |
| "userModified": false, | |
| "replaceAll": false | |
| } | |
| } | |
| [2025-12-29T13:31:04.981Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01QgnZ9ebcHvQ1GCWob47osc", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now let me update the `_start_conversion` method to handle both file input and text input modes:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1290, | |
| "cache_read_input_tokens": 74086, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1290, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 3, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "bd83cba1-178c-43bd-ae78-095133fca7ff" | |
| } | |
| [2025-12-29T13:31:17.248Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01QgnZ9ebcHvQ1GCWob47osc", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_015k5fmjWGGvsGVJmQqcyTYM", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()", | |
| "new_string": " def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs based on mode\n if self._use_text_input.get():\n # Text input mode\n text_content = self._text_input_box.get(\"1.0\", \"end-1c\").strip()\n if not text_content:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please enter some text to convert.\",\n icon=\"cancel\"\n )\n return\n self._direct_text = text_content\n else:\n # File input mode\n input_file = self._input_file.get().strip()\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n self._direct_text = \"\"\n\n output_file = self._output_file.get().strip()\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()" | |
| } | |
| } | |
| ], | |
| "stop_reason": "tool_use", | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1290, | |
| "cache_read_input_tokens": 74086, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1290, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 961, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": { | |
| "applied_edits": [] | |
| } | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "7936550c-7b09-4721-9ab5-2e56890cb0a6" | |
| } | |
| [2025-12-29T13:31:17.291Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_015k5fmjWGGvsGVJmQqcyTYM","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 692→ # Extract language code from \"en - English\" format\n 693→ code = value.split(\" - \")[0]\n 694→ self._language.set(code)\n 695→\n 696→ def _start_conversion(self):\n 697→ \"\"\"Start the conversion process in a background thread.\"\"\"\n 698→ if self._processing:\n 699→ return\n 700→\n 701→ # Validate inputs based on mode\n 702→ if self._use_text_input.get():\n 703→ # Text input mode\n 704→ text_content = self._text_input_box.get(\"1.0\", \"end-1c\").strip()\n 705→ if not text_content:\n 706→ CTkMessagebox(\n 707→ title=\"Error\",\n 708→ message=\"Please enter some text to convert.\",\n 709→ icon=\"cancel\"\n 710→ )\n 711→ return\n 712→ self._direct_text = text_content\n 713→ else:\n 714→ # File input mode\n 715→ input_file = self._input_file.get().strip()\n 716→ if not input_file:\n 717→ CTkMessagebox(\n 718→ title=\"Error\",\n 719→ message=\"Please select an input file.\",\n 720→ icon=\"cancel\"\n 721→ )\n 722→ return\n 723→\n 724→ if not Path(input_file).exists():\n 725→ CTkMessagebox(\n 726→ title=\"Error\",\n 727→ message=f\"Input file not found: {input_file}\",\n 728→ icon=\"cancel\"\n 729→ )\n 730→ return\n 731→ self._direct_text = \"\"\n 732→\n 733→ output_file = self._output_file.get().strip()\n 734→ if not output_file:\n 735→ CTkMessagebox(\n 736→ title=\"Error\",\n 737→ message=\"Please select an output file location.\",\n 738→ icon=\"cancel\"\n 739→ )\n 740→ return\n 741→\n 742→ # Start conversion in background thread\n 743→ self._processing = True\n 744→ self._cancel_requested = False\n 745→ self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n 746→ self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n 747→ self._progress_bar.set(0)\n 748→ self._start_button_animation() # Start ellipsis animation\n 749→\n 750→ thread = threading.Thread(target=self._run_conversion)\n 751→ thread.daemon = True\n 752→ thread.start()\n 753→\n 754→ def _cancel_conversion(self):\n 755→ \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n 756→ if self._processing and not self._cancel_requested:"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"ee405a5b-1eb9-4bf5-97fb-e05c640ead57","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py","oldString":" def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()","newString":" def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs based on mode\n if self._use_text_input.get():\n # Text input mode\n text_content = self._text_input_box.get(\"1.0\", \"end-1c\").strip()\n if not text_content:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please enter some text to convert.\",\n icon=\"cancel\"\n )\n return\n self._direct_text = text_content\n else:\n # File input mode\n input_file = self._input_file.get().strip()\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n self._direct_text = \"\"\n\n output_file = self._output_file.get().strip()\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()","originalFile":"\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(paren | |
| [2025-12-29T13:31:17.309Z] [INFO] t)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n\n def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dialog.\"\"\"\n extensions = self._reader_registry.supported_extensions\n patterns = \" \".join(f\"*{ext}\" for ext in extensions)\n return [\n (\"Supported documents\", patterns),\n (\"PDF files\", \"*.pdf\"),\n (\"Word documents\", \"*.doc *.docx\"),\n (\"Rich Text files\", \"*.rtf\"),\n (\"Text files\", \"*.txt\"),\n (\"Markdown files\", \"*.md\"),\n (\"All files\", \"*.*\")\n ]\n\n def _browse_input(self):\n \"\"\"Open file dialog for input file.\"\"\"\n from tkinter import filedialog\n\n filetypes = self._get_input_filetypes()\n filename = filedialog.askopenfilename(\n title=\"Select Input Document\",\n filetypes=filetypes\n )\n if filename:\n self._input_file.set(filename)\n # Auto-generate output filename\n input_path = Path(filename)\n output_path = input_path.with_suffix(\".wav\")\n self._output_file.set(str(output_path))\n self._status_label.configure(text=f\"Selected: {input_path.name}\")\n\n def _browse_output(self):\n \"\"\"Open file dialog for output file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.asksaveasfilename(\n title=\"Save Audio File\",\n defaultextension=\".wav\",\n filetypes=[(\"WAV files\", \"*.wav\"), (\"All files\", \"*.*\")]\n )\n if filename:\n self._output_file.set(filename)\n\n def _browse_voice_reference(self):\n \"\"\"Open file dialog for voice reference file.\"\"\"\n from tkinter import filedialog\n\n filename = filedialog.askopenfilename(\n title=\"Select Voice Reference Audio\",\n filetypes=[\n (\"Audio files\", \"*.wav *.mp3 *.flac *.ogg\"),\n (\"WAV files\", \"*.wav\"),\n (\"All files\", \"*.*\")\n ]\n )\n if filename:\n self._voice_reference.set(filename)\n\n def _on_text_input_toggle(self):\n \"\"\"Handle toggle between file input and text input mode.\"\"\"\n if self._use_text_input.get():\n # Show text input, hide file input\n self._input_file_frame.pack_forget()\n self._text_input_frame.pack(fill=\"x\", pady=(0, 10), after=self._text_toggle_checkbox.master)\n else:\n # Show file input, hide text input\n self._text_input_frame.pack_forget()\n # Re-pack file input frame in the correct position\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10), before=self._text_toggle_checkbox.master)\n\n def _on_model_change(self):\n \"\"\"Handle model type change.\"\"\"\n if self._model_type.get() == \"multilingual\":\n self._language_frame.pack(fill=\"x\", pady=(0, 10), after=self._language_frame.master.winfo_children()[1])\n else:\n self._language_frame.pack_forget()\n\n def _on_language_select(self, value):\n \"\"\"Handle language selection.\"\"\"\n # Extract language code from \"en - English\" format\n code = value.split(\" - \")[0]\n self._language.set(code)\n\n def _start_conversion(self):\n \"\"\"Start the conversion process in a background thread.\"\"\"\n if self._processing:\n return\n\n # Validate inputs\n input_file = self._input_file.get().strip()\n output_file = self._output_file.get().strip()\n\n if not input_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an input file.\",\n icon=\"cancel\"\n )\n return\n\n if not output_file:\n CTkMessagebox(\n title=\"Error\",\n message=\"Please select an output file location.\",\n icon=\"cancel\"\n )\n return\n\n if not Path(input_file).exists():\n CTkMessagebox(\n title=\"Error\",\n message=f\"Input file not found: {input_file}\",\n icon=\"cancel\"\n )\n return\n\n # Start conversion in background thread\n self._processing = True\n self._cancel_requested = False\n self._convert_btn.configure(state=\"disabled\", text=\"Converting\")\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0)) # Show cancel button\n self._progress_bar.set(0)\n self._start_button_animation() # Start ellipsis animation\n\n thread = threading.Thread(target=self._run_conversion)\n thread.daemon = True\n thread.start()\n\n def _cancel_conversion(self):\n \"\"\"Request cancellation of the ongoing conversion.\"\"\"\n if self._processing and not self._cancel_requested:\n self._cancel_requested = True\n self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n self._update_progress(0, \"Cancelling... (saving generated audio)\")\n logger.info(\"Cancellation requested by user\")\n\n def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")\n\n # Step 3: Initialize TTS engine\n model_name = self._model_type.get()\n device_name = self._device.get()\n\n # Handle language auto-detection for multilingual model\n language = self._language.get()\n if model_name == \"multilingual\" and language == \"auto\":\n self._update_progress(0.22, \"Detecting language...\")\n from tts_app.utils.language_detection import detect_primary_language, get_language_name\n language = detect_primary_language(processed_text)\n detected_name = get_language_name(language)\n logger.info(f\"Auto-detected language: {language} ({detected_name})\")\n self._update_progress(0.23, f\"Detected language: {detected_name}\")\n\n self._update_progress(0.25, f\"Initializing {model_name} model on {device_name}...\")\n\n # Start indeterminate animation for model download/initialization\n # This provides visual feedback that something is happening during long waits\n self.after(0, self._start_indeterminate_progress)\n self.after(0, lambda: self._progress_label.configure(\n text=f\"Downloading/loading {model_name} model (may take several minutes on first run)...\"\n ))\n\n config = TTSConfig(\n model_type=model_name,\n language=language,\n voice_reference=Path(self._voice_reference.get()) if self._voice_reference.get() else None,\n device=device_name,\n hf_token=self._hf_token.get() if self._hf_token.get() else None\n )\n\n if self._tts_engine is None:\n self._tts_engine = ChatterboxEngine()\n\n self._tts_engine.initialize(config)\n\n # Stop indeterminate animation and switch back to determinate progress\n self.after(0, self._stop_indeterminate_progress)\n self._update_progress(0.35, \"TTS engine ready, starting synthesis...\")\n\n # Step 4: Synthesize speech\n def progress_callback(current, total, status, estimated_remaining):\n progress = 0.35 + (0.60 * current / total)\n # Format estimated time remaining\n time_str = \"\"\n if estimated_remaining is not None and estimated_remaining > 0:\n mins = int(estimated_remaining // 60)\n secs = int(estimated_remaining % 60)\n if mins > 0:\n time_str = f\" (~{mins}m {secs}s remaining)\"\n else:\n time_str = f\" (~{secs}s remaining)\"\n self._update_progress(progress, f\"Synthesizing: {status}{time_str}\")\n\n def cancel_check():\n return self._cancel_requested\n\n result = self._tts_engine.synthesize(\n processed_text,\n output_path,\n progress_callback=progress_callback,\n cancel_check=cancel_check\n )\n\n # Handle result (complete or cancelled with partial)\n duration_str = f\"{int(result.duration_seconds // 60)}:{int(result.duration_seconds % 60):02d}\"\n\n if result.was_cancelled:\n # Partial result from cancellation\n self._update_progress(1.0, f\"Cancelled - partial audio saved ({result.chunks_completed}/{result.chunks_total} chunks)\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Cancelled\",\n message=f\"Partial audio saved to:\\n{output_path}\\n\\n\"\n f\"Duration: {duration_str}\\n\"\n f\"Progress: {result.chunks_completed}/{result.chunks_total} chunks\",\n file_path=output_path\n ))\n else:\n # Complete\n self._update_progress(1.0, \"Complete!\")\n self.after(0, lambda: SuccessDialog(\n self,\n title=\"Conversion Complete\",\n message=f\"Audio saved to:\\n{output_path}\\n\\nDuration: {duration_str}\",\n file_path=output_path\n ))\n\n except Exception as e:\n logger.exception(\"Conversion failed\")\n error_msg = str(e)\n tb = traceback.format_exc()\n # Stop indeterminate progress if it was running\n self.after(0, self._stop_indeterminate_progress)\n self.after(0, lambda: ErrorDialog(\n self,\n title=\"Conversion Error\",\n message=f\"Conversion failed:\\n{error_msg}\",\n full_traceback=tb\n ))\n\n finally:\n self._processing = False\n self.after(0, self._reset_ui)\n\n def _update_progress(self, value: float, status: str):\n \"\"\"Update progress bar and status from any thread.\"\"\"\n self.after(0, lambda: self._progress_bar.set(value))\n self.after(0, lambda: self._progress_label.configure(text=status))\n self.after(0, lambda: self._status_label.configure(text=status))\n\n def _start_indeterminate_progress(self):\n \"\"\"Start indeterminate progress bar animation (for long operations without known progress).\"\"\"\n self._progress_bar.configure(mode=\"indeterminate\")\n self._progress_bar.start()\n\n def _stop_indeterminate_progress(self):\n \"\"\"Stop indeterminate progress bar animation and switch back to determinate mode.\"\"\"\n self._progress_bar.stop()\n self._progress_bar.configure(mode=\"determinate\")\n\n def _start_button_animation(self):\n \"\"\"Start ellipsis animation on buttons to show activity.\"\"\"\n self._ellipsis_state = 0\n self._animate_button_ellipsis()\n\n def _stop_button_animation(self):\n \"\"\"Stop ellipsis animation on buttons.\"\"\"\n if self._button_animation_id:\n self.after_cancel(self._button_animation_id)\n self._button_animation_id = None\n\n def _animate_button_ellipsis(self):\n \"\"\"Animate ellipsis on Converting.../Cancelling... buttons.\"\"\"\n if not self._processing:\n return\n\n ellipsis = \".\" * (self._ellipsis_state % 4)\n padded_ellipsis = ellipsis.ljust(3) # Pad to 3 chars to prevent button resizing\n\n if self._cancel_requested:\n self._cancel_btn.configure(text=f\"Cancelling{padded_ellipsis}\")\n else:\n self._convert_btn.configure(text=f\"Converting{padded_ellipsis}\")\n\n self._ellipsis_state += 1\n self._button_animation_id = self.after(400, self._animate_button_ellipsis)\n\n def _reset_ui(self):\n \"\"\"Reset UI after conversion.\"\"\"\n self._stop_button_animation() # Stop ellipsis animation\n self._convert_btn.configure(state=\"normal\", text=\"Convert to Speech\")\n self._cancel_btn.pack_forget() # Hide cancel button\n self._cancel_btn.configure(state=\"normal\", text=\"Cancel\") # Reset cancel button\n self._cancel_requested = False\n self._progress_label.configure(text=\"Ready\")\n\n\ndef run_app():\n \"\"\"Create and run the application.\"\"\"\n app = TTSApplication()\n app.mainloop()\n","structuredPatch":[{"oldStart":698,"oldLines":18,"newStart":698,"newLines":39,"lines":[" if self._processing:"," return"," ","- # Validate inputs","- input_file = self._input_file.get().strip()","- output_file = self._output_file.get().strip()","+ # Validate inputs based on mode","+ if self._use_text_input.get():","+ # Text input mode","+ text_content = self._text_input_box.get(\"1.0\", \"end-1c\").strip()","+ if not text_content:","+ CTkMessagebox(","+ title=\"Error\",","+ message=\"Please enter some text to convert.\",","+ icon=\"cancel\"","+ )","+ return","+ self._direct_text = text_content","+ else:","+ # File input mode","+ input_file = self._input_file.get().strip()","+ if not input_file:","+ CTkMessagebox(","+ title=\"Error\",","+ message=\"Please select an input file.\",","+ icon=\"cancel\"","+ )","+ return"," ","- if not input_file:","- CTkMessagebox(","- title=\"Error\",","- message=\"Please select an input file.\",","- icon=\"cancel\"","- )","- return","+ if not Path(input_file).exists():","+ CTkMessagebox(","+ title=\"Error\",","+ message=f\"Input file not found: {input_file}\",","+ icon=\"cancel\"","+ )","+ return","+ self._direct_text = \"\""," ","+ output_file = self._output_file.get().strip()"," if not output_file:"," CTkMessagebox("," title=\"Error\","]},{"oldStart":718,"oldLines":14,"newStart":739,"newLines":6,"lines":[" )"," return"," ","- if not Path(input_file).exists():","- CTkMessagebox(","- title=\"Error\",","- message=f\"Input file not found: {input_file}\",","- icon=\"cancel\"","- )","- return","-"," # Start conversion in background thread"," self._processing = True"," self._cancel_requested = False"]}],"userModified":false,"replaceAll":false}} | |
| [2025-12-29T13:31:22.426Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01HuLeEFiPAagPwbyW9LgXGN", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now I need to update the `_run_conversion` method to handle both modes:" | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1776, | |
| "cache_read_input_tokens": 75376, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1776, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 5, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "c9983407-7ce1-4e4e-95a6-72cb029f5e70" | |
| } | |
| [2025-12-29T13:31:30.943Z] [INFO] { | |
| "type": "assistant", | |
| "message": { | |
| "model": "claude-opus-4-5-20251101", | |
| "id": "msg_01HuLeEFiPAagPwbyW9LgXGN", | |
| "type": "message", | |
| "role": "assistant", | |
| "content": [ | |
| { | |
| "type": "tool_use", | |
| "id": "toolu_01AATvBuNJRXgQAhCZJ5ebZE", | |
| "name": "Edit", | |
| "input": { | |
| "file_path": "/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py", | |
| "old_string": " def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")", | |
| "new_string": " def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n output_path = Path(self._output_file.get())\n\n # Step 1: Get text content (from file or direct input)\n if self._direct_text:\n # Direct text input mode\n self._update_progress(0.1, \"Processing text input...\")\n raw_text = self._direct_text\n footnotes = []\n page_count = None\n logger.info(f\"Using direct text input: {len(raw_text)} chars\")\n else:\n # File input mode\n input_path = Path(self._input_file.get())\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n raw_text = content.text\n footnotes = content.footnotes\n page_count = content.page_count\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=page_count\n )\n processed_text = self._pipeline.process(raw_text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found\")" | |
| } | |
| } | |
| ], | |
| "stop_reason": null, | |
| "stop_sequence": null, | |
| "usage": { | |
| "input_tokens": 0, | |
| "cache_creation_input_tokens": 1776, | |
| "cache_read_input_tokens": 75376, | |
| "cache_creation": { | |
| "ephemeral_5m_input_tokens": 1776, | |
| "ephemeral_1h_input_tokens": 0 | |
| }, | |
| "output_tokens": 784, | |
| "service_tier": "standard" | |
| }, | |
| "context_management": null | |
| }, | |
| "parent_tool_use_id": null, | |
| "session_id": "ad096264-e8c8-4480-a14c-7222d9a5eceb", | |
| "uuid": "a0c30de2-24f4-44e7-9d6c-05c1048118fc" | |
| } | |
| [2025-12-29T13:31:30.983Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AATvBuNJRXgQAhCZJ5ebZE","type":"tool_result","content":"The file /tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n 758→ self._cancel_btn.configure(state=\"disabled\", text=\"Cancelling\")\n 759→ self._update_progress(0, \"Cancelling... (saving generated audio)\")\n 760→ logger.info(\"Cancellation requested by user\")\n 761→\n 762→ def _run_conversion(self):\n 763→ \"\"\"Run the conversion process (in background thread).\"\"\"\n 764→ try:\n 765→ output_path = Path(self._output_file.get())\n 766→\n 767→ # Step 1: Get text content (from file or direct input)\n 768→ if self._direct_text:\n 769→ # Direct text input mode\n 770→ self._update_progress(0.1, \"Processing text input...\")\n 771→ raw_text = self._direct_text\n 772→ footnotes = []\n 773→ page_count = None\n 774→ logger.info(f\"Using direct text input: {len(raw_text)} chars\")\n 775→ else:\n 776→ # File input mode\n 777→ input_path = Path(self._input_file.get())\n 778→ self._update_progress(0.1, \"Reading document...\")\n 779→ content = self._reader_registry.read(input_path)\n 780→ raw_text = content.text\n 781→ footnotes = content.footnotes\n 782→ page_count = content.page_count\n 783→ logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n 784→\n 785→ # Step 2: Preprocess text\n 786→ self._update_progress(0.2, \"Preprocessing text...\")\n 787→ context = ProcessingContext(\n 788→ footnotes=footnotes,\n 789→ ignore_footnotes=self._ignore_footnotes.get(),\n 790→ page_count=page_count\n 791→ )\n 792→ processed_text = self._pipeline.process(raw_text, context)\n 793→ logger.info(f\"Processed text: {len(processed_text)} chars\")\n 794→\n 795→ if not processed_text.strip():\n 796→ raise ValueError(\"No text content found\")\n 797→\n 798→ # Step 3: Initialize TTS engine\n 799→ model_name = self._model_type.get()\n 800→ device_name = self._device.get()"}]},"parent_tool_use_id":null,"session_id":"ad096264-e8c8-4480-a14c-7222d9a5eceb","uuid":"270eeb1e-883d-4d86-b3df-ab27489bbc5d","tool_use_result":{"filePath":"/tmp/gh-issue-solver-1767014767488/src/tts_app/gui/app.py","oldString":" def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n input_path = Path(self._input_file.get())\n output_path = Path(self._output_file.get())\n\n # Step 1: Read document\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=content.footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=content.page_count\n )\n processed_text = self._pipeline.process(content.text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found in document\")","newString":" def _run_conversion(self):\n \"\"\"Run the conversion process (in background thread).\"\"\"\n try:\n output_path = Path(self._output_file.get())\n\n # Step 1: Get text content (from file or direct input)\n if self._direct_text:\n # Direct text input mode\n self._update_progress(0.1, \"Processing text input...\")\n raw_text = self._direct_text\n footnotes = []\n page_count = None\n logger.info(f\"Using direct text input: {len(raw_text)} chars\")\n else:\n # File input mode\n input_path = Path(self._input_file.get())\n self._update_progress(0.1, \"Reading document...\")\n content = self._reader_registry.read(input_path)\n raw_text = content.text\n footnotes = content.footnotes\n page_count = content.page_count\n logger.info(f\"Read document: {content.page_count} pages, {len(content.text)} chars\")\n\n # Step 2: Preprocess text\n self._update_progress(0.2, \"Preprocessing text...\")\n context = ProcessingContext(\n footnotes=footnotes,\n ignore_footnotes=self._ignore_footnotes.get(),\n page_count=page_count\n )\n processed_text = self._pipeline.process(raw_text, context)\n logger.info(f\"Processed text: {len(processed_text)} chars\")\n\n if not processed_text.strip():\n raise ValueError(\"No text content found\")","originalFile":"\"\"\"Main GUI application using CustomTkinter.\"\"\"\n\nimport logging\nimport threading\nimport traceback\nfrom pathlib import Path\nfrom typing import Optional\n\nimport customtkinter as ctk\nfrom CTkMessagebox import CTkMessagebox\n\nfrom tts_app.readers import ReaderRegistry\nfrom tts_app.readers.registry import create_default_registry\nfrom tts_app.preprocessors import PreprocessorPipeline, ProcessingContext\nfrom tts_app.preprocessors.pipeline import create_default_pipeline\nfrom tts_app.tts import ChatterboxEngine, TTSConfig\n\nlogger = logging.getLogger(__name__)\n\n\nclass SuccessDialog(ctk.CTkToplevel):\n \"\"\"Custom success dialog with Open File Location button.\n\n This dialog displays a success message and provides buttons to open\n the file location in the file explorer.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, file_path: Path):\n \"\"\"Initialize the success dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Success message.\n file_path: Path to the generated file.\n \"\"\"\n super().__init__(parent)\n\n self._file_path = file_path\n\n self.title(title)\n self.geometry(\"450x200\")\n self.minsize(400, 180)\n self.transient(parent)\n self.grab_set()\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Success icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n success_label = ctk.CTkLabel(\n title_frame,\n text=\"Success\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#55AA55\"\n )\n success_label.pack(side=\"left\")\n\n # Message\n message_label = ctk.CTkLabel(\n main_frame,\n text=message,\n font=ctk.CTkFont(size=12),\n justify=\"left\"\n )\n message_label.pack(fill=\"x\", pady=(0, 15))\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Open File Location button\n open_location_btn = ctk.CTkButton(\n button_frame,\n text=\"Open File Location\",\n command=self._open_file_location,\n width=140\n )\n open_location_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _open_file_location(self):\n \"\"\"Open the file's directory in the system file explorer.\"\"\"\n import platform\n import subprocess\n\n folder_path = self._file_path.parent\n\n try:\n system = platform.system()\n if system == \"Windows\":\n # On Windows, use explorer with /select to highlight the file\n subprocess.run([\"explorer\", \"/select,\", str(self._file_path)])\n elif system == \"Darwin\":\n # On macOS, use open command with -R to reveal the file\n subprocess.run([\"open\", \"-R\", str(self._file_path)])\n else:\n # On Linux, use xdg-open to open the folder\n subprocess.run([\"xdg-open\", str(folder_path)])\n except Exception as e:\n logger.warning(f\"Failed to open file location: {e}\")\n # Fall back to showing a message\n CTkMessagebox(\n master=self,\n title=\"Info\",\n message=f\"File is located at:\\n{folder_path}\",\n icon=\"info\",\n width=400\n )\n\n\nclass ErrorDialog(ctk.CTkToplevel):\n \"\"\"Custom error dialog with copy button for error message.\n\n This dialog displays an error message and provides a button to copy\n the full error text to the clipboard.\n \"\"\"\n\n def __init__(self, parent, title: str, message: str, full_traceback: str = \"\"):\n \"\"\"Initialize the error dialog.\n\n Args:\n parent: Parent window.\n title: Dialog title.\n message: Short error message.\n full_traceback: Full traceback for copying (optional).\n \"\"\"\n super().__init__(parent)\n\n self.title(title)\n self.geometry(\"500x300\")\n self.minsize(400, 200)\n self.transient(parent)\n self.grab_set()\n\n # Store the full error text for copying\n self._error_text = f\"{message}\\n\\n{full_traceback}\" if full_traceback else message\n\n # Main frame with padding\n main_frame = ctk.CTkFrame(self)\n main_frame.pack(fill=\"both\", expand=True, padx=20, pady=20)\n\n # Error icon and title\n title_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n title_frame.pack(fill=\"x\", pady=(0, 10))\n\n error_label = ctk.CTkLabel(\n title_frame,\n text=\"❌ Error\",\n font=ctk.CTkFont(size=18, weight=\"bold\"),\n text_color=\"#FF5555\"\n )\n error_label.pack(side=\"left\")\n\n # Error message in scrollable text\n text_frame = ctk.CTkFrame(main_frame)\n text_frame.pack(fill=\"both\", expand=True, pady=(0, 15))\n\n self._error_textbox = ctk.CTkTextbox(\n text_frame,\n wrap=\"word\",\n font=ctk.CTkFont(size=12)\n )\n self._error_textbox.pack(fill=\"both\", expand=True, padx=5, pady=5)\n self._error_textbox.insert(\"1.0\", self._error_text)\n self._error_textbox.configure(state=\"disabled\")\n\n # Button frame\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\")\n\n # Copy button\n copy_btn = ctk.CTkButton(\n button_frame,\n text=\"📋 Copy Error\",\n command=self._copy_to_clipboard,\n width=120\n )\n copy_btn.pack(side=\"left\", padx=(0, 10))\n\n # OK button\n ok_btn = ctk.CTkButton(\n button_frame,\n text=\"OK\",\n command=self.destroy,\n width=80\n )\n ok_btn.pack(side=\"right\")\n\n # Center the dialog on parent\n self.update_idletasks()\n self._center_on_parent(parent)\n\n def _center_on_parent(self, parent):\n \"\"\"Center this dialog on the parent window.\"\"\"\n parent_x = parent.winfo_x()\n parent_y = parent.winfo_y()\n parent_w = parent.winfo_width()\n parent_h = parent.winfo_height()\n\n dialog_w = self.winfo_width()\n dialog_h = self.winfo_height()\n\n x = parent_x + (parent_w - dialog_w) // 2\n y = parent_y + (parent_h - dialog_h) // 2\n\n self.geometry(f\"+{x}+{y}\")\n\n def _copy_to_clipboard(self):\n \"\"\"Copy the error text to clipboard.\"\"\"\n self.clipboard_clear()\n self.clipboard_append(self._error_text)\n\n # Show feedback\n CTkMessagebox(\n master=self,\n title=\"Copied\",\n message=\"Error text copied to clipboard!\",\n icon=\"check\",\n width=300\n )\n\n\nclass TTSApplication(ctk.CTk):\n \"\"\"Main application window for Text-to-Speech conversion.\n\n This provides a user-friendly interface for:\n - Selecting input documents (PDF, DOCX, TXT, MD)\n - Configuring TTS options (model, language, voice reference)\n - Setting preprocessing options (ignore footnotes)\n - Converting documents to speech\n \"\"\"\n\n def __init__(self):\n \"\"\"Initialize the application.\"\"\"\n super().__init__()\n\n # Configure window\n self.title(\"Text to Speech with Chatterbox\")\n self.geometry(\"700x700\")\n self.minsize(600, 500)\n\n # Set appearance\n ctk.set_appearance_mode(\"system\")\n ctk.set_default_color_theme(\"blue\")\n\n # Initialize components\n self._reader_registry: ReaderRegistry = create_default_registry()\n self._pipeline: Prepr**********eline = create_default_pipeline()\n self._tts_engine: Optional[ChatterboxEngine] = None\n self._processing = False\n self._cancel_requested = False # Flag to signal cancellation\n self._progress_animation_id = None # Track progress bar animation\n self._button_animation_id = None # Track button ellipsis animation\n self._ellipsis_state = 0 # Current ellipsis state (0-3)\n\n # Variables\n self._input_file = ctk.StringVar()\n self._output_file = ctk.StringVar()\n self._voice_reference = ctk.StringVar()\n self._model_type = ctk.StringVar(value=\"turbo\")\n self._language = ctk.StringVar(value=\"en\")\n self._ignore_footnotes = ctk.BooleanVar(value=True)\n self._device = ctk.StringVar(value=\"auto\")\n self._hf_token = ctk.StringVar()\n self._use_text_input = ctk.BooleanVar(value=False) # Toggle for text input mode\n self._direct_text = \"\" # Store direct text input\n\n # Build UI\n self._create_widgets()\n\n def _create_widgets(self):\n \"\"\"Create all UI widgets.\"\"\"\n # Scrollable main container\n self._scrollable_frame = ctk.CTkScrollableFrame(self)\n self._scrollable_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Main frame inside scrollable area\n main_frame = ctk.CTkFrame(self._scrollable_frame)\n main_frame.pack(fill=\"both\", expand=True, padx=10, pady=10)\n\n # Title\n title_label = ctk.CTkLabel(\n main_frame,\n text=\"Document to Speech Converter\",\n font=ctk.CTkFont(size=24, weight=\"bold\")\n )\n title_label.pack(pady=(0, 20))\n\n # Input file section\n self._input_file_frame = ctk.CTkFrame(main_frame)\n self._input_file_frame.pack(fill=\"x\", pady=(0, 10))\n self._create_file_section_in_frame(\n self._input_file_frame,\n \"Input Document:\",\n self._input_file,\n self._browse_input,\n self._get_input_filetypes()\n )\n\n # Text input toggle\n text_toggle_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n text_toggle_frame.pack(fill=\"x\", pady=(0, 5))\n\n self._text_toggle_checkbox = ctk.CTkCheckBox(\n text_toggle_frame,\n text=\"Use text input instead of file\",\n variable=self._use_text_input,\n command=self._on_text_input_toggle\n )\n self._text_toggle_checkbox.pack(anchor=\"w\")\n\n # Collapsible text input section (hidden by default)\n self._text_input_frame = ctk.CTkFrame(main_frame)\n # Don't pack yet - will be shown when checkbox is toggled\n\n text_input_label = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Enter text to convert to speech:\"\n )\n text_input_label.pack(anchor=\"w\", pady=(0, 5))\n\n self._text_input_box = ctk.CTkTextbox(\n self._text_input_frame,\n height=150,\n wrap=\"word\"\n )\n self._text_input_box.pack(fill=\"x\", pady=(0, 5))\n\n text_input_help = ctk.CTkLabel(\n self._text_input_frame,\n text=\"Paste or type your text here. Supports multiple paragraphs.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n text_input_help.pack(anchor=\"w\")\n\n # Output file section\n self._create_file_section(\n main_frame,\n \"Output Audio File:\",\n self._output_file,\n self._browse_output,\n [(\"WAV files\", \"*.wav\")],\n save=True\n )\n\n # Voice reference section (optional)\n voice_frame = ctk.CTkFrame(main_frame)\n voice_frame.pack(fill=\"x\", pady=(10, 0))\n\n voice_label = ctk.CTkLabel(voice_frame, text=\"Voice Reference (optional):\")\n voice_label.pack(anchor=\"w\")\n\n voice_input_frame = ctk.CTkFrame(voice_frame)\n voice_input_frame.pack(fill=\"x\", pady=(5, 0))\n\n voice_entry = ctk.CTkEntry(\n voice_input_frame,\n textvariable=self._voice_reference,\n placeholder_text=\"Select a ~10 second audio file for voice cloning\"\n )\n voice_entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n voice_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Browse\",\n command=self._browse_voice_reference,\n width=100\n )\n voice_btn.pack(side=\"right\")\n\n clear_btn = ctk.CTkButton(\n voice_input_frame,\n text=\"Clear\",\n command=lambda: self._voice_reference.set(\"\"),\n width=60,\n fg_color=\"gray\"\n )\n clear_btn.pack(side=\"right\", padx=(0, 5))\n\n # Options frame\n options_frame = ctk.CTkFrame(main_frame)\n options_frame.pack(fill=\"x\", pady=(20, 0))\n\n options_label = ctk.CTkLabel(\n options_frame,\n text=\"Options\",\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n options_label.pack(anchor=\"w\", pady=(0, 10))\n\n # Model selection\n model_frame = ctk.CTkFrame(options_frame)\n model_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(model_frame, text=\"Model:\").pack(side=\"left\")\n\n for model, label in [(\"turbo\", \"Turbo (Fast)\"), (\"standard\", \"Standard\"), (\"multilingual\", \"Multilingual\")]:\n rb = ctk.CTkRadioButton(\n model_frame,\n text=label,\n variable=self._model_type,\n value=model,\n command=self._on_model_change\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Language selection (for multilingual model)\n self._language_frame = ctk.CTkFrame(options_frame)\n self._language_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(self._language_frame, text=\"Language:\").pack(side=\"left\")\n\n languages = [\n (\"auto\", \"Auto-detect\"),\n (\"en\", \"English\"), (\"fr\", \"French\"), (\"de\", \"German\"),\n (\"es\", \"Spanish\"), (\"it\", \"Italian\"), (\"pt\", \"Portuguese\"),\n (\"ru\", \"Russian\"), (\"zh\", \"Chinese\"), (\"ja\", \"Japanese\"),\n (\"ko\", \"Korean\"), (\"ar\", \"Arabic\"), (\"hi\", \"Hindi\")\n ]\n\n self._language_menu = ctk.CTkOptionMenu(\n self._language_frame,\n variable=self._language,\n values=[f\"{code} - {name}\" for code, name in languages],\n command=self._on_language_select\n )\n self._language_menu.pack(side=\"left\", padx=(20, 0))\n self._language_frame.pack_forget() # Hidden by default\n\n # Language auto-detect help text\n self._language_help = ctk.CTkLabel(\n self._language_frame,\n text=\"Auto-detect works best for single-language texts\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n self._language_help.pack(side=\"left\", padx=(10, 0))\n\n # Device selection\n device_frame = ctk.CTkFrame(options_frame)\n device_frame.pack(fill=\"x\", pady=(0, 10))\n\n ctk.CTkLabel(device_frame, text=\"Device:\").pack(side=\"left\")\n\n # Auto-detect includes: NVIDIA CUDA, AMD ROCm, Apple MPS\n for device, label in [(\"auto\", \"Auto (GPU/CPU)\"), (\"cuda\", \"GPU\"), (\"cpu\", \"CPU\")]:\n rb = ctk.CTkRadioButton(\n device_frame,\n text=label,\n variable=self._device,\n value=device\n )\n rb.pack(side=\"left\", padx=(20, 0))\n\n # Device help text (more detailed with AMD information)\n device_help = ctk.CTkLabel(\n options_frame,\n text=\"Auto detects: NVIDIA (CUDA), AMD (ROCm on Linux), Apple (MPS). Note: AMD GPUs on Windows use CPU.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n device_help.pack(anchor=\"w\", padx=(80, 0))\n\n # CPU performance note\n cpu_note = ctk.CTkLabel(\n options_frame,\n text=\"CPU mode is slower (5-15 min/chunk). For faster CPU: use Turbo model, reduce text length.\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n cpu_note.pack(anchor=\"w\", padx=(80, 0))\n\n # HuggingFace Token section\n hf_token_frame = ctk.CTkFrame(options_frame)\n hf_token_frame.pack(fill=\"x\", pady=(10, 0))\n\n ctk.CTkLabel(hf_token_frame, text=\"HF Token (optional):\").pack(side=\"left\")\n\n self._hf_token_entry = ctk.CTkEntry(\n hf_token_frame,\n textvariable=self._hf_token,\n placeholder_text=\"Enter HuggingFace token for Turbo model\",\n show=\"*\",\n width=300\n )\n self._hf_token_entry.pack(side=\"left\", padx=(10, 0), fill=\"x\", expand=True)\n\n # HF Token help text\n hf_token_help = ctk.CTkLabel(\n options_frame,\n text=\"Required for Turbo model. Get token at: huggingface.co/settings/tokens\",\n text_color=\"gray\",\n font=ctk.CTkFont(size=11)\n )\n hf_token_help.pack(anchor=\"w\", padx=(80, 0), pady=(2, 10))\n\n # Footnotes option\n footnote_frame = ctk.CTkFrame(options_frame)\n footnote_frame.pack(fill=\"x\", pady=(0, 10))\n\n self._footnote_checkbox = ctk.CTkCheckBox(\n footnote_frame,\n text=\"Ignore footnotes (don't read them aloud)\",\n variable=self._ignore_footnotes\n )\n self._footnote_checkbox.pack(anchor=\"w\")\n\n # Progress bar\n self._progress_frame = ctk.CTkFrame(main_frame)\n self._progress_frame.pack(fill=\"x\", pady=(20, 0))\n\n self._progress_label = ctk.CTkLabel(self._progress_frame, text=\"Ready\")\n self._progress_label.pack(anchor=\"w\")\n\n self._progress_bar = ctk.CTkProgressBar(self._progress_frame)\n self._progress_bar.pack(fill=\"x\", pady=(5, 0))\n self._progress_bar.set(0)\n\n # Button frame for convert and cancel buttons\n button_frame = ctk.CTkFrame(main_frame, fg_color=\"transparent\")\n button_frame.pack(fill=\"x\", pady=(20, 0))\n\n # Convert button\n self._convert_btn = ctk.CTkButton(\n button_frame,\n text=\"Convert to Speech\",\n command=self._start_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\")\n )\n self._convert_btn.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 5))\n\n # Cancel button (hidden by default)\n self._cancel_btn = ctk.CTkButton(\n button_frame,\n text=\"Cancel\",\n command=self._cancel_conversion,\n height=50,\n font=ctk.CTkFont(size=16, weight=\"bold\"),\n fg_color=\"#CC4444\",\n hover_color=\"#AA3333\"\n )\n self._cancel_btn.pack(side=\"right\", fill=\"x\", expand=True, padx=(5, 0))\n self._cancel_btn.pack_forget() # Hidden by default\n\n # Status bar\n self._status_label = ctk.CTkLabel(\n main_frame,\n text=\"Select an input file to begin\",\n text_color=\"gray\"\n )\n self._status_label.pack(pady=(10, 0))\n\n def _create_file_section(self, parent, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create a file selection section.\"\"\"\n frame = ctk.CTkFrame(parent)\n frame.pack(fill=\"x\", pady=(0, 10))\n\n self._create_file_section_in_frame(frame, label_text, variable, browse_command, filetypes, save)\n\n def _create_file_section_in_frame(self, frame, label_text, variable, browse_command, filetypes, save=False):\n \"\"\"Create file selection widgets inside an existing frame.\"\"\"\n label = ctk.CTkLabel(frame, text=label_text)\n label.pack(anchor=\"w\")\n\n input_frame = ctk.CTkFrame(frame)\n input_frame.pack(fill=\"x\", pady=(5, 0))\n\n entry = ctk.CTkEntry(input_frame, textvariable=variable)\n entry.pack(side=\"left\", fill=\"x\", expand=True, padx=(0, 10))\n\n btn = ctk.CTkButton(\n input_frame,\n text=\"Browse\",\n command=browse_command,\n width=100\n )\n btn.pack(side=\"right\")\n\n def _get_input_filetypes(self):\n \"\"\"Get file types for input file dial |
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