langgraph basic use in tool inject

examples/qwen_langgraph_custom_model.py

@@ -0,0 +1,46 @@
+"""
+Use the custom BaseChatModel-like class ChatQwenOpenAICompat with LangGraph.
+
+Prereqs:
+  pip install -U langgraph langchain httpx
+
+Env:
+  export QWEN_API_KEY=sk-...
+  export QWEN_BASE_URL=https://dashscope-intl.aliyuncs.com/compatible-mode/v1
+  export QWEN_MODEL=qwen3-coder-flash
+"""
+
+from langgraph.prebuilt import create_react_agent
+from langchain_core.messages import HumanMessage
+
+try:
+    from langchain.tools import tool
+except Exception:
+    from langchain_core.tools import tool  # type: ignore
+
+from langgraph_qwen import ChatQwenOpenAICompat
+
+
+@tool
+def multiply(x_and_y: str) -> str:
+    """Multiply two integers given as 'x y'."""
+    try:
+        a, b = [int(s) for s in x_and_y.strip().split()]
+    except Exception:
+        return "Please provide two integers: 'x y'"
+    return str(a * b)
+
+
+def main():
+    base = ChatQwenOpenAICompat(temperature=0)
+    model = base.bind_tools([multiply]).bind(tool_choice="auto")
+
+    agent = create_react_agent(model, [multiply])
+    res = agent.invoke({"messages": [HumanMessage(content="计算 6 和 7 的乘积，然后解释你的步骤。")]} )
+    print("\n=== Final ===\n")
+    print(res["messages"][-1].content)
+
+
+if __name__ == "__main__":
+    main()
+