Solution published: add main.py

main.py

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+"""LangGraph research brief agent.
+
+This script implements a LangGraph agent that, given a topic, produces a short research brief.
+The brief consists of:
+1. An outline of 4–5 research points.
+2. For each point, a single web search via Tavily and a short note.
+3. A final synthesis of all notes into a coherent brief.
+
+The agent uses LangGraph's StateGraph and LangChain's Tavily and OpenAI LLM.
+"""
+
+import os
+from typing import TypedDict, List
+
+from langgraph.graph import StateGraph, END
+from langchain_openai import ChatOpenAI
+from langchain_tavily import TavilySearchResults
+from langchain_core.messages import HumanMessage
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# --- State definition -----------------------------------------------------
+class BriefState(TypedDict):
+    topic: str
+    outline: List[str] | None
+    step_index: int
+    notes: List[str]
+    final_brief: str | None
+
+# --- LLM and Tavily -------------------------------------------------------
+llm = ChatOpenAI(temperature=0.2)
+search = TavilySearchResults(max_results=1)
+
+# --- Node functions -------------------------------------------------------
+async def outline_node(state: BriefState) -> BriefState:
+    """Generate an outline of 4–5 research points for the topic."""
+    prompt = (
+        f"Generate a concise outline of 4–5 research points for the following topic. "
+        f"Return the points as a numbered list, one per line. Topic: {state['topic']}"
+    )
+    response = await llm.agenerate([HumanMessage(content=prompt)])
+    outline_text = response.generations[0][0].text.strip()
+    outline = [line.strip() for line in outline_text.splitlines() if line.strip()]
+    return {"outline": outline, "step_index": 0, "notes": []}
+
+async def research_step_node(state: BriefState) -> BriefState:
+    """Perform a single web search for the current outline point and store a short note."""
+    idx = state["step_index"]
+    point = state["outline"][idx]
+    # Search via Tavily
+    search_results = await search.ainvoke(point)
+    snippet = search_results[0].snippet if search_results else "No snippet found."
+    # Summarize snippet with LLM
+    prompt = (
+        f"You are a concise researcher. Based on the following snippet, write a 5–8 sentence note summarizing the key information. "
+        f"Snippet: {snippet}"
+    )
+    note_resp = await llm.agenerate([HumanMessage(content=prompt)])
+    note = note_resp.generations[0][0].text.strip()
+    notes = state["notes"] + [note]
+    return {"notes": notes, "step_index": idx + 1}
+
+async def synthesize_node(state: BriefState) -> BriefState:
+    """Combine all notes into a coherent brief with headings."""
+    outline = state["outline"]
+    notes = state["notes"]
+    sections = [f"**{point}**\n{note}" for point, note in zip(outline, notes)]
+    brief = "\n\n".join(sections)
+    return {"final_brief": brief}
+
+# --- Graph construction ---------------------------------------------------
+workflow = StateGraph(BriefState)
+workflow.add_node("outline", outline_node)
+workflow.add_node("research_step", research_step_node)
+workflow.add_node("synthesize", synthesize_node)
+
+workflow.set_entry_point("outline")
+workflow.add_conditional_edges(
+    "outline",
+    lambda state: "research_step" if state["outline"] else END,
+)
+workflow.add_conditional_edges(
+    "research_step",
+    lambda state: "research_step" if state["step_index"] < len(state["outline"]) else "synthesize",
+)
+workflow.add_edge("synthesize", END)
+
+graph = workflow.compile()
+
+# --- Runner ----------------------------------------------------------------
+async def run_brief(topic: str) -> str:
+    state: BriefState = {"topic": topic, "outline": None, "step_index": 0, "notes": [], "final_brief": None}
+    result = await graph.ainvoke(state)
+    return result["final_brief"]
+
+if __name__ == "__main__":
+    import asyncio
+    topic = os.getenv("TOPIC", "Как студенту безопасно подключать MCP к LangChain")
+    brief = asyncio.run(run_brief(topic))
+    print("\n=== Brief ===")
+    print(brief)