Pattern 6 — Bounded Web Research (Answer model + flow)

snippet15_bounded_research.py

from typing import List, Optional
from pydantic import BaseModel, Field

class Answer(BaseModel):
    summary: str = Field(description="Brief summary of findings")
    bullets: List[str] = Field(description="Key points as bullet list")
    citations: List[str] = Field(description="Source URLs")
    uncertainty: Optional[str] = Field(default=None, description="Any uncertainty notes")

def run_research_demo(query: str) -> Answer:
    # Placeholder demo: replace with real tavily_search / tavily_extract calls
    bullets = [
        "Anthropic: context engineering involves thoughtfully curating tokens; use compaction and structured notes.",
        "LangChain: write/select/compress/isolate context to keep windows tight.",
        "Mezmo: prompt design, context management, RAG, memory, efficiency, safety.",
    ]
    citations = [
        "https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents",
        "https://blog.langchain.com/context-engineering-for-agents/",
        "https://www.mezmo.com/learn-observability/context-engineering-for-observability",
    ]
    return Answer(summary=f"Synthesis of recent context engineering best practices for: {query}",
                  bullets=bullets, citations=citations)

if __name__ == "__main__":
    print(run_research_demo("Context engineering best practices").model_dump_json(indent=2))