{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0c3f1df8",
   "metadata": {},
   "source": [
    "# Self Ask With Search\n",
    "\n",
    "This notebook showcases the Self Ask With Search chain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7e3b513e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3m Yes.\n",
      "Follow up: Who is the reigning men's U.S. Open champion?\u001b[0m\n",
      "Intermediate answer: \u001b[36;1m\u001b[1;3mCarlos Alcaraz won the 2022 Men's single title while Poland's Iga Swiatek won the Women's single title defeating Tunisian's Ons Jabeur.\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mFollow up: Where is Carlos Alcaraz from?\u001b[0m\n",
      "Intermediate answer: \u001b[36;1m\u001b[1;3mEl Palmar, Spain\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mSo the final answer is: El Palmar, Spain\u001b[0m\n",
      "\u001b[1m> Finished AgentExecutor chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'El Palmar, Spain'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain import OpenAI, SerpAPIWrapper\n",
    "from langchain.agents import initialize_agent, Tool\n",
    "\n",
    "llm = OpenAI(temperature=0)\n",
    "search = SerpAPIWrapper()\n",
    "tools = [\n",
    "    Tool(\n",
    "        name=\"Intermediate Answer\",\n",
    "        func=search.run,\n",
    "        description=\"useful for when you need to ask with search\"\n",
    "    )\n",
    "]\n",
    "\n",
    "self_ask_with_search = initialize_agent(tools, llm, agent=\"self-ask-with-search\", verbose=True)\n",
    "self_ask_with_search.run(\"What is the hometown of the reigning men's U.S. Open champion?\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.9"
  },
  "vscode": {
   "interpreter": {
    "hash": "b1677b440931f40d89ef8be7bf03acb108ce003de0ac9b18e8d43753ea2e7103"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}