{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/soumyadip/Library/Python/3.9/lib/python/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from llama_index.core.agent import ReActAgent\n",
    "from llama_index.llms.groq import Groq\n",
    "from llama_index.core.llms import ChatMessage\n",
    "from llama_index.core.tools import BaseTool, FunctionTool\n",
    "from llama_index.tools.tavily_research.base import TavilyToolSpec\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "search = TavilyToolSpec(api_key=os.getenv('TAVILY_API_KEY'))\n",
    "def search_tool(prompt:str)->list:\n",
    "    \"return only search result from the web\"\n",
    "    results = search.search(prompt)\n",
    "    return [result.text for result in results]\n",
    "search_toolkit = FunctionTool.from_defaults(fn=search_tool)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "llm = Groq(model = \"gemma2-9b-it\")\n",
    "agent = ReActAgent.from_tools([search_toolkit],llm=llm,verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "> Running step 72522799-577e-4630-afd1-3f7637988a23. Step input: what is the addition of 25 and 26?\n",
      "\u001b[1;3;38;5;200mThought: I can answer without using any more tools. I'll use the user's language to answer\n",
      "Answer: 51\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "response = agent.chat(\"what is the instagram link of Soumyadip Changder?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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  "language_info": {
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