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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "from agent import Agent\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "try:\n",
    "    # 1. Initialize your agent\n",
    "    print(\"Initializing agent...\")\n",
    "    agent = Agent()\n",
    "    print(\"Agent initialized successfully.\")\n",
    "\n",
    "    # 2. Define a sample question to test with\n",
    "    # You can use a question from questions.json or a custom one.\n",
    "    sample_question = \"What is the capital of France and what is its square root of 25?\"\n",
    "\n",
    "    # 3. Run the agent\n",
    "    print(f\"Running agent with question: '{sample_question}'\")\n",
    "    answer = agent(sample_question)\n",
    "\n",
    "    # 4. Print the final answer\n",
    "    print(\"\\n--- Agent's Final Answer ---\")\n",
    "    print(answer)\n",
    "    print(\"--------------------------\")\n",
    "\n",
    "except Exception as e:\n",
    "    print(f\"An error occurred: {e}\")\n"
   ]
  }
 ],
 "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}