Agentic Chat

/**
 * A simple agentic chat flow using LangGraph instead of CrewAI.
 */

import { ChatOpenAI } from "@langchain/openai";
import { SystemMessage } from "@langchain/core/messages";
import { RunnableConfig } from "@langchain/core/runnables";
import { StateGraph, Command, START, END } from "@langchain/langgraph";

import { ClientStateAnnotation, ClientState } from "@ag-kit/adapter-langgraph";
import { MemorySaver } from "@langchain/langgraph";

async function chatNode(state: ClientState, config?: RunnableConfig) {
  const model = new ChatOpenAI({
    model: process.env.OPENAI_MODEL || "gpt-4o-mini",
    apiKey: process.env.OPENAI_API_KEY,
    configuration: {
      baseURL: process.env.OPENAI_BASE_URL,
    },
  });

  if (!config) {
    config = { recursionLimit: 25 };
  }

  const modelWithTools = model.bindTools([...(state.client?.tools || [])], {
    parallel_tool_calls: false,
  });

  const systemMessage = new SystemMessage({
    content: "You are a helpful assistant.",
  });

  const response = await modelWithTools.invoke(
    [systemMessage, ...state.messages],
    config
  );

  return new Command({
    goto: END,
    update: {
      messages: [response],
    },
  });
}

const workflow = new StateGraph(ClientStateAnnotation)
  .addNode("chat_node", chatNode)
  .addEdge(START, "chat_node")
  .addEdge("chat_node", END);

export const agenticChatGraph = workflow.compile({
  checkpointer: new MemorySaver(),
});