def _func()

in llm_demo/orchestrator/langgraph/tool_node.py [0:0]

• 30 lines of code
• 6 McCabe index (conditional complexity)

    def _func(self, input: dict[str, Any], config: RunnableConfig) -> Any:
        if messages := input.get("messages", []):
            output_type = "dict"
            message = messages[-1]
        else:
            raise ValueError("No message found in input")

        if not isinstance(message, AIMessage):
            raise ValueError("Last message is not an AIMessage")

        user_id_token = input.get("user_id_token")

        def run_one(call: ToolCall, user_id_token: Optional[str]):
            args = copy.copy(call["args"]) or {}
            args["user_id_token"] = user_id_token
            response = self.tools_by_name[call["name"]].invoke(args, config)
            output = response.get("results")
            sql = response.get("sql")
            tool_call_id = call.get("id") or str(uuid.uuid4())
            return ToolMessage(
                content=str_output(output),
                name=call["name"],
                tool_call_id=tool_call_id,
                additional_kwargs={"sql": sql},
            )

        with get_executor_for_config(config) as executor:
            outputs = [
                *executor.map(run_one, message.tool_calls, repeat(user_id_token))
            ]
            if output_type == "list":
                return outputs
            else:
                return {"messages": outputs}