Function chat_node

agent/sample_agent/agent.py:53–87

This is a simplified agent that uses the ReAct agent as a subgraph. It handles both chat responses and tool execution in one node.

(state: AgentState, config: RunnableConfig)

}

async def chat_node(state: AgentState, config: RunnableConfig) -> Command[Literal["__end__"]]:
    """
    This is a simplified agent that uses the ReAct agent as a subgraph.
    It handles both chat responses and tool execution in one node.
    """
    # Get MCP configuration from state, or use the default config if not provided
    mcp_config = state.get("mcp_config", DEFAULT_MCP_CONFIG)

    print(f"mcp_config: {mcp_config}, default: {DEFAULT_MCP_CONFIG}")
    
    # Set up the MCP client and tools using the configuration from state
    async with MultiServerMCPClient(mcp_config) as mcp_client:
        # Get the tools
        mcp_tools = mcp_client.get_tools()
        
        # Create the react agent
        model = ChatOpenAI(model="gpt-4o")
        react_agent = create_react_agent(model, mcp_tools)
        
        # Prepare messages for the react agent
        agent_input = {
            "messages": state["messages"]
        }
        
        # Run the react agent subgraph with our input
        agent_response = await react_agent.ainvoke(agent_input)
        
        # Update the state with the new messages
        updated_messages = state["messages"] + agent_response.get("messages", []) 
        await copilotkit_exit(config)
        # End the graph with the updated messages
        return Command(
            goto=END,
            update={"messages": updated_messages},
        )

# Define the workflow graph with only a chat node
workflow = StateGraph(AgentState)