kausmeows

# paper2saas_agent.py
import argparse
import os
import json
from typing import Dict, Any, List

from pydantic import BaseModel, Field

# Agno SDK Imports
from agno.workflow import Workflow, Step, Parallel

kausmeows

from typing import List

from agno.agent.agent import Agent
from agno.models.openai import OpenAIChat
from agno.workflow.router import Router
from agno.workflow.step import Step
from agno.workflow.types import StepInput, StepOutput
from agno.workflow.workflow import Workflow

# Define your agents/steps

kausmeows

from typing import List

from agno.agent.agent import Agent
from agno.models.openai import OpenAIChat
from agno.workflow.router import Router
from agno.workflow.step import Step
from agno.workflow.types import StepInput
from agno.workflow.workflow import Workflow

# Define your agents/steps

kausmeows

import asyncio

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from pydantic import BaseModel, Field
from rich.pretty import pprint


class PersonInfo(BaseModel):
    name: str = Field(..., description="Person's full name")

kausmeows

[
  {
    "input": "ai trends in 2025",

kausmeows

import asyncio
from dataclasses import dataclass
from datetime import datetime
from os import getenv
from typing import (
    Any,
    AsyncIterator,
    Awaitable,
    Callable,
    Dict,

kausmeows

[
  {
    "input": "Tell me a story about a husky named Max.",
    "content": "**Prelogue:**  \nIn a serene winter landscape, where the forest is blanketed by soft, white snow, we meet Max, a lively husky with a shimmering coat and an adventurous spirit. The setting introduces the mood of a sparkling winter day, hinting at the adventures that await Max.\n\n**Body:**  \nMax explores the snow-covered forest, leaving behind paw prints that echo his playful nature. His curiosity leads him to a frozen pond, which captures his attention with its glass-like surface. Driven by the thrill of adventure, he ventures onto the ice, but his excitement leads to a slip, and he tumbles into the cold water. The chilling shock is soon met with laughter from a girl who witnesses his playful misfortune. This moment of shared joy sparks a connection between them, resulting in a budding friendship amidst the enchanting snowfall.\n\n**Epilogue:**  \nAs winter continues to blanket the forest, Max and the girl nurture their newfound b

kausmeows

[
  {
    "input": "Tell me a story about a husky named Max.",
    "content": "**Prelogue:**\nIn the picturesque landscape of Pine Ridge, where the snowflakes danced like little fairies, lived a spirited husky named Max. Known for his playful antics and love for adventure, Max's days were filled with excitement, exploring the snowy trails and seeking out new experiences. \n\n**Body:**\nOne crisp, sun-kissed morning, while bounding through the glistening snow, Max's keen eyes caught sight of a vibrant scarf fluttering enticingly from a high branch of a tree. His innate curiosity sparked, and with a joyful bark, he sprinted towards the eye-catching object. On his way, he stumbled upon a group of cheerful children, happily engaged in constructing a snowman. \n\nWithout a second thought, Max decided to enhance their fun by snatching up the scarf. With his tail wagging in delight, he dashed back towards the children, proudly flaunting his find. The children erupted into laughter, their spirits lifted by Max’s play

kausmeows

from agno.agent import Agent
from agno.db.in_memory import InMemoryDb
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.team import Team
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.googlesearch import GoogleSearchTools
from agno.tools.hackernews import HackerNewsTools
from agno.workflow.step import Step, StepInput, StepOutput

kausmeows

[
  {
    "input": "write about machine learning",
    "content": "To create a comprehensive content schedule over 4 weeks on the topic of Machine Learning (ML), with 3 posts per week, we can focus on different aspects of ML to provide a broad overview while diving into specifics as the weeks progress. Here is a suggested schedule:\n\n### Week 1: Introduction to Machine Learning\n\n**Post 1:**\n- **Title:** What is Machine Learning?\n- **Content:** Define machine learning, its history, and how it differs from traditional programming. Briefly introduce the key concepts: supervised, unsupervised, and reinforcement learning.\n\n**Post 2:**\n- **Title:** Getting Started with Supervised Learning\n- **Content:** Dive into supervised learning, explaining concepts of labeled data, and discuss common algorithms like linear regression, decision trees, and support vector machines. Include use cases and examples.\n\n**Post 3:**\n- **Title:** Exploring Unsupervised Learning\n- **Content:** Explain what unsupervised learni