{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0",
   "metadata": {},
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If not already in your PYTHONPATH, add the project root so we can import agent-2\n",
    "import sys, os, pathlib, importlib\n",
    "\n",
    "project_root = pathlib.Path.cwd()  # adjust if the notebook sits elsewhere\n",
    "sys.path.append(str(project_root))\n",
    "\n",
    "# Optional: load .env for API keys\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()                     # expects OPENAI_API_KEY and NEBIUS_API_KEY\n",
    "\n",
    "\n",
    "import os\n",
    "os.environ[\"LANGSMITH_TRACING\"] = \"true\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2",
   "metadata": {},
   "source": [
    "# Import Agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import agent\n",
    "agent_module = importlib.import_module(\"agent\")   # agent.py ➜ agent\n",
    "Agent = agent_module.Agent                          # grab the class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initiate\n",
    "agent = Agent()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# visualise\n",
    "from IPython.display import Image, display\n",
    "\n",
    "try:\n",
    "    display(Image(agent.graph.get_graph().draw_mermaid_png()))\n",
    "except Exception:\n",
    "    # This requires some extra dependencies and is optional\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6",
   "metadata": {},
   "source": [
    "# Question"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Question\n",
    "question_text = \"How many at bats did the Yankee with the most walks in the 1977 regular season have that same season?\"\n",
    "\n",
    "\n",
    "answer = agent(question=question_text)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(answer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "print(\"Answer:\", answer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Show the messages\n",
    "for m in answer['Answer']:\n",
    "    m.pretty_print()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.8"
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