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from langgraph.graph import StateGraph
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from typing import TypedDict
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class State(TypedDict):
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    query: str
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    findings: list
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    report: str
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def research(state: State) -> dict:
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    results = search_web(state["query"])
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    return {"findings": results}
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def summarize(state: State) -> dict:
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    report = llm.invoke(f"Summarize: {state['findings']}")
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    return {"report": report}
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graph = StateGraph(State)
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graph.add_node("research", research)
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graph.add_node("summarize", summarize)
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graph.add_edge("research", "summarize")
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graph.set_entry("research")

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from crewai import Agent, Task, Crew
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researcher = Agent(role="Researcher", goal="Find competitor info")
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writer = Agent(role="Writer", goal="Create report")
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research_task = Task(description="Research competitors", agent=researcher)
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write_task = Task(description="Write report", agent=writer, output_file="report.md")
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crew = Crew(agents=[researcher, writer], tasks=[research_task, write_task])
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crew.kickoff()

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from autogen import ConversableAgent
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researcher = ConversableAgent("researcher", llm_config={...})
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writer = ConversableAgent("writer", llm_config={...})
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result = researcher.initiate_chat(
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    writer,
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    message="Research competitors and write a report",
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    max_turns=5
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)

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from claude_agent import Agent
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agent = Agent(
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    model="claude-sonnet-4",
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    mcp_servers=[web_search_mcp, file_system_mcp],
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    system_prompt="Research competitors and save a markdown report."
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)
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result = await agent.run("Research top 3 competitors, summarize, save as report.md")

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from agents import Agent, Runner
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researcher = Agent(name="researcher", tools=[web_search])
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writer = Agent(name="writer", instructions="Create markdown reports", handoffs=[reviewer])
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result = Runner.run_sync(researcher, "Research competitors")
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# Handoff to writer happens automatically based on instructions