Create build_graph

agents/build_graph

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+from langgraph.graph import StateGraph, END
+
+def build_graph(llm_model_name: str = "gpt-4o-mini"):
+
+    # --- Base LLM for agents & synthesizer (swap to your provider as needed) ---
+    openai_api_key="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"
+    llm = ChatOpenAI(api_key=openai_api_key,model=llm_model_name, temperature=0)
+
+    # --- Create specialized agents ---
+    news_agent = make_news_agent(llm)
+    earnings_agent = make_earnings_agent(llm)
+    market_agent = make_market_agent(llm)
+
+    # --- Create synthesizer chain ---
+    synthesizer = make_synthesizer(llm)
+
+    # --- LangGraph: wire nodes ---
+    g = StateGraph(GraphState)
+
+    # Bind node callables with their dependencies via closures
+    g.add_node("news", lambda s: news_node(s, news_agent))
+    g.add_node("earnings", lambda s: earnings_node(s, earnings_agent))
+    g.add_node("market", lambda s: market_node(s, market_agent))
+    g.add_node("synth", lambda s: synth_node(s, synthesizer))
+
+    # Supervisor node
+    g.add_node("supervisor", supervisor_node)
+    # Edges: start -> supervisor -> (news|earnings|market|synth) -> supervisor ... -> synth -> END
+    g.set_entry_point("supervisor")
+    
+    for a in AGENTS:
+        g.add_edge(a, "supervisor")
+    g.add_edge("synth", END)
+
+    # Route decisions come from the router function (returns a string)
+    g.add_conditional_edges(
+        "supervisor",
+        supervisor_router,   # returns: "news" | "earnings" | "market" | "synth"
+        {
+            "news": "news",
+            "earnings": "earnings",
+            "market": "market",
+            "synth": "synth",
+        },
+    )
+
+    return g.compile()