{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import utils\n",
    "\n",
    "utils.load_env()\n",
    "os.environ['LANGCHAIN_TRACING_V2'] = \"true\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Annotated, Literal, TypedDict\n",
    "\n",
    "from langchain_core.messages import HumanMessage\n",
    "\n",
    "# for llm model\n",
    "from langchain_anthropic import ChatAnthropic\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "from langchain_core.tools import tool\n",
    "from langgraph.checkpoint.memory import MemorySaver\n",
    "from langgraph.graph import END, StateGraph, MessagesState\n",
    "from langgraph.prebuilt import ToolNode\n",
    "import tools\n",
    "\n",
    "\n",
    "tool_node = tools.tool_node\n",
    "tools.tools\n",
    "\n",
    "# model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\", temperature=0).bind_tools(tools)\n",
    "model = ChatOpenAI(model=\"gpt-4o-mini\")\n",
    "\n",
    "# Define the function that determines whether to continue or not\n",
    "def should_continue(state: MessagesState) -> Literal[\"tools\", END]:\n",
    "    messages = state['messages']\n",
    "    last_message = messages[-1]\n",
    "    # If the LLM makes a tool call, then we route to the \"tools\" node\n",
    "    if last_message.tool_calls:\n",
    "        return \"tools\"\n",
    "    # Otherwise, we stop (reply to the user)\n",
    "    return END\n",
    "\n",
    "\n",
    "# Define the function that calls the model\n",
    "def call_model(state: MessagesState):\n",
    "    messages = state['messages']\n",
    "    response = model.invoke(messages)\n",
    "    # We return a list, because this will get added to the existing list\n",
    "    return {\"messages\": [response]}\n",
    "\n",
    "\n",
    "# Define a new graph\n",
    "workflow = StateGraph(MessagesState)\n",
    "\n",
    "# Define the two nodes we will cycle between\n",
    "workflow.add_node(\"agent\", call_model)\n",
    "workflow.add_node(\"tools\", tool_node)\n",
    "\n",
    "# Set the entrypoint as `agent`\n",
    "# This means that this node is the first one called\n",
    "workflow.set_entry_point(\"agent\")\n",
    "\n",
    "# We now add a conditional edge\n",
    "workflow.add_conditional_edges(\n",
    "    # First, we define the start node. We use `agent`.\n",
    "    # This means these are the edges taken after the `agent` node is called.\n",
    "    \"agent\",\n",
    "    # Next, we pass in the function that will determine which node is called next.\n",
    "    should_continue,\n",
    ")\n",
    "\n",
    "# We now add a normal edge from `tools` to `agent`.\n",
    "# This means that after `tools` is called, `agent` node is called next.\n",
    "workflow.add_edge(\"tools\", 'agent')\n",
    "\n",
    "# Initialize memory to persist state between graph runs\n",
    "checkpointer = MemorySaver()\n",
    "\n",
    "# Finally, we compile it!\n",
    "# This compiles it into a LangChain Runnable,\n",
    "# meaning you can use it as you would any other runnable.\n",
    "# Note that we're (optionally) passing the memory when compiling the graph\n",
    "app = workflow.compile(checkpointer=checkpointer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def submitUserMessage(message:str):\n",
    "    final_state = app.invoke(\n",
    "        {\"messages\": [HumanMessage(content=message)]},\n",
    "        config={\"configurable\": {\"thread_id\": 42}}\n",
    "    )\n",
    "    return final_state[\"messages\"][-1].content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n",
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n",
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n",
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n",
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n",
      "Unable to load requested LangChainTracer. To disable this warning, unset the LANGCHAIN_TRACING_V2 environment variables.\n",
      "LangSmithUserError('API key must be provided when using hosted LangSmith API')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'บริเวณมาบุญครองในกรุงเทพฯ มีร้านกาแฟหลายแห่งที่น่าสนใจ คุณสามารถลองไปที่ร้านเหล่านี้ได้:\\n\\n1. **ร้านกาแฟโฟลว์ (Flow Coffee)** - ร้านกาแฟเล็กๆ ที่มีบรรยากาศสบาย เหมาะสำหรับนั่งทำงานหรือนั่งชิลล์\\n2. **ร้านกาแฟ On the Way** - ร้านกาแฟที่มีเมนูหลากหลายและบรรยากาศดี\\n3. **ร้านกาแฟชิค (Chic)** - ร้านกาแฟที่มีการตกแต่งน่ารักและเครื่องดื่มหลากหลาย\\n4. **ร้านกาแฟ Starbucks** - มีสาขาหลายแห่งในกรุงเทพฯ รวมถึงใกล้บริเวณมาบุญครอง\\n5. **ร้านกาแฟดอยช้าง** - ที่มีชื่อเสียงในเรื่องของกาแฟจากดอยช้าง\\n\\nคุณสามารถค้นหาร้านกาแฟเพิ่มเติมได้จาก Google Maps หรือแอปพลิเคชันค้นหาร้านอาหารต่างๆ เพื่อดูรีวิวและข้อมูลเพิ่มเติมเกี่ยวกับร้านกาแฟใกล้มาบุญครองได้ค่ะ'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submitUserMessage(\"ค้นหาร้านกาแฟใกล้มาบุญครอง\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}