Conversational.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 374
    },
    "executionInfo": {
     "elapsed": 259,
     "status": "error",
     "timestamp": 1689102456498,
     "user": {
      "displayName": "Jazear Brooks",
      "userId": "03061299682422563415"
     },
     "user_tz": 420
    },
    "id": "ivNjVsPoHm1t",
    "outputId": "72b3b5a7-ec68-46b8-e3aa-de180b5388d6"
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "issubclass() arg 1 must be a class",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Tool\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AgentType\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmemory\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ConversationBufferMemory\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/__init__.py:6\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mimportlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m metadata\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Optional\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m MRKLChain, ReActChain, SelfAskWithSearchChain\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcache\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseCache\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mchains\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      9\u001b[0m     ConversationChain,\n\u001b[1;32m     10\u001b[0m     LLMBashChain,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     18\u001b[0m     VectorDBQAWithSourcesChain,\n\u001b[1;32m     19\u001b[0m )\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/agents/__init__.py:2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"Interface for agents.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magent\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      3\u001b[0m     Agent,\n\u001b[1;32m      4\u001b[0m     AgentExecutor,\n\u001b[1;32m      5\u001b[0m     AgentOutputParser,\n\u001b[1;32m      6\u001b[0m     BaseMultiActionAgent,\n\u001b[1;32m      7\u001b[0m     BaseSingleActionAgent,\n\u001b[1;32m      8\u001b[0m     LLMSingleActionAgent,\n\u001b[1;32m      9\u001b[0m )\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magent_toolkits\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m     11\u001b[0m     create_csv_agent,\n\u001b[1;32m     12\u001b[0m     create_json_agent,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     21\u001b[0m     create_vectorstore_router_agent,\n\u001b[1;32m     22\u001b[0m )\n\u001b[1;32m     23\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magent_types\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AgentType\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/agents/agent.py:16\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpydantic\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseModel, root_validator\n\u001b[1;32m     15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magent_types\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AgentType\n\u001b[0;32m---> 16\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01magents\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m InvalidTool\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcallbacks\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseCallbackManager\n\u001b[1;32m     18\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcallbacks\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmanager\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m     19\u001b[0m     AsyncCallbackManagerForChainRun,\n\u001b[1;32m     20\u001b[0m     AsyncCallbackManagerForToolRun,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     23\u001b[0m     Callbacks,\n\u001b[1;32m     24\u001b[0m )\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/agents/tools.py:8\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Optional\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcallbacks\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmanager\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      5\u001b[0m     AsyncCallbackManagerForToolRun,\n\u001b[1;32m      6\u001b[0m     CallbackManagerForToolRun,\n\u001b[1;32m      7\u001b[0m )\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseTool, Tool, tool\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mInvalidTool\u001b[39;00m(BaseTool):\n\u001b[1;32m     12\u001b[0m     \u001b[38;5;124;03m\"\"\"Tool that is run when invalid tool name is encountered by agent.\"\"\"\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/tools/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"Core toolkit implementations.\"\"\"\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marxiv\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtool\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ArxivQueryRun\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mazure_cognitive_services\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      5\u001b[0m     AzureCogsFormRecognizerTool,\n\u001b[1;32m      6\u001b[0m     AzureCogsImageAnalysisTool,\n\u001b[1;32m      7\u001b[0m     AzureCogsSpeech2TextTool,\n\u001b[1;32m      8\u001b[0m     AzureCogsText2SpeechTool,\n\u001b[1;32m      9\u001b[0m )\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseTool, StructuredTool, Tool, tool\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/tools/arxiv/tool.py:12\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcallbacks\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmanager\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      8\u001b[0m     AsyncCallbackManagerForToolRun,\n\u001b[1;32m      9\u001b[0m     CallbackManagerForToolRun,\n\u001b[1;32m     10\u001b[0m )\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseTool\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutilities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marxiv\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ArxivAPIWrapper\n\u001b[1;32m     15\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mArxivQueryRun\u001b[39;00m(BaseTool):\n\u001b[1;32m     16\u001b[0m     \u001b[38;5;124;03m\"\"\"Tool that adds the capability to search using the Arxiv API.\"\"\"\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/utilities/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;124;03m\"\"\"General utilities.\"\"\"\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mrequests\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m TextRequestsWrapper\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutilities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapify\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ApifyWrapper\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutilities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marxiv\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ArxivAPIWrapper\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutilities\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mawslambda\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m LambdaWrapper\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/utilities/apify.py:5\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Any, Callable, Dict, Optional\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpydantic\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseModel, root_validator\n\u001b[0;32m----> 5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ApifyDatasetLoader\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Document\n\u001b[1;32m      7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_from_dict_or_env\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/document_loaders/__init__.py:44\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mduckdb_loader\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m DuckDBLoader\n\u001b[1;32m     40\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01memail\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m     41\u001b[0m     OutlookMessageLoader,\n\u001b[1;32m     42\u001b[0m     UnstructuredEmailLoader,\n\u001b[1;32m     43\u001b[0m )\n\u001b[0;32m---> 44\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01membaas\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m EmbaasBlobLoader, EmbaasLoader\n\u001b[1;32m     45\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mepub\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m UnstructuredEPubLoader\n\u001b[1;32m     46\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdocument_loaders\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mevernote\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m EverNoteLoader\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/langchain/document_loaders/embaas.py:54\u001b[0m\n\u001b[1;32m     50\u001b[0m     \u001b[38;5;28mbytes\u001b[39m: \u001b[38;5;28mstr\u001b[39m\n\u001b[1;32m     51\u001b[0m     \u001b[38;5;124;03m\"\"\"The base64 encoded bytes of the document to extract text from.\"\"\"\u001b[39;00m\n\u001b[0;32m---> 54\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mBaseEmbaasLoader\u001b[39;00m(BaseModel):\n\u001b[1;32m     55\u001b[0m     \u001b[38;5;124;03m\"\"\"Base class for embedding a model into an Embaas document extraction API.\"\"\"\u001b[39;00m\n\u001b[1;32m     57\u001b[0m     embaas_api_key: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/main.py:204\u001b[0m, in \u001b[0;36mpydantic.main.ModelMetaclass.__new__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:488\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.infer\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:419\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.__init__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:539\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.prepare\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:801\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.populate_validators\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/validators.py:696\u001b[0m, in \u001b[0;36mfind_validators\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/validators.py:585\u001b[0m, in \u001b[0;36mpydantic.validators.make_typeddict_validator\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/annotated_types.py:35\u001b[0m, in \u001b[0;36mpydantic.annotated_types.create_model_from_typeddict\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/main.py:972\u001b[0m, in \u001b[0;36mpydantic.main.create_model\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/main.py:204\u001b[0m, in \u001b[0;36mpydantic.main.ModelMetaclass.__new__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:488\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.infer\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:419\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.__init__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:534\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField.prepare\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/fields.py:638\u001b[0m, in \u001b[0;36mpydantic.fields.ModelField._type_analysis\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.10/typing.py:1158\u001b[0m, in \u001b[0;36m_SpecialGenericAlias.__subclasscheck__\u001b[0;34m(self, cls)\u001b[0m\n\u001b[1;32m   1156\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28missubclass\u001b[39m(\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m__origin__, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__origin__)\n\u001b[1;32m   1157\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mcls\u001b[39m, _GenericAlias):\n\u001b[0;32m-> 1158\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43missubclass\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__origin__\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1159\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__subclasscheck__\u001b[39m(\u001b[38;5;28mcls\u001b[39m)\n",
      "\u001b[0;31mTypeError\u001b[0m: issubclass() arg 1 must be a class"
     ]
    }
   ],
   "source": [
    "from langchain.agents import Tool\n",
    "from langchain.agents import AgentType\n",
    "from langchain.memory import ConversationBufferMemory\n",
    "from langchain import OpenAI\n",
    "from langchain.utilities import SerpAPIWrapper\n",
    "from langchain.agents import initialize_agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "HF7JhHMmHnYu"
   },
   "outputs": [],
   "source": [
    "search = SerpAPIWrapper()\n",
    "tools = [\n",
    "    Tool(\n",
    "        name = \"Current Search\",\n",
    "        func=search.run,\n",
    "        description=\"useful for when you need to answer questions about current events or the current state of the world\"\n",
    "    ),\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "MbTvzGWJHo_d"
   },
   "outputs": [],
   "source": [
    "memory = ConversationBufferMemory(memory_key=\"chat_history\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "dghSyxzZNTjB"
   },
   "outputs": [],
   "source": [
    "llm=OpenAI(temperature=0)\n",
    "agent_chain = initialize_agent(tools, llm, agent=AgentType.CONVERSATIONAL_REACT_DESCRIPTION, verbose=True, memory=memory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "wjhbxIf2Nkc3"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"hi, i am bob\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "p-BFk7QCNtCn"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"what's my name?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "_8G5XDgcNzDP"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(\"what are some good dinners to make this week, if i like thai food?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "BzlGe_iiN5kX"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"tell me the last letter in my name, and also tell me who won the world cup in 1978?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "nssCADO9OCL5"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"whats the current temperature in pomfret?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "8alDo01dPjnE"
   },
   "outputs": [],
   "source": [
    "from langchain.memory import ConversationBufferMemory\n",
    "from langchain.chat_models import ChatOpenAI\n",
    "\n",
    "memory = ConversationBufferMemory(memory_key=\"chat_history\", return_messages=True)\n",
    "llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, temperature=0)\n",
    "agent_chain = initialize_agent(tools, llm, agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, verbose=True, memory=memory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "VIysZ6nSQiKn"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"hi, i am bob\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "S5H_JAJ9RCsD"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"what's my name?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "bGzvetf9RHr1"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(\"what are some good dinners to make this week, if i like thai food?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "lofTlNWhRKQW"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"tell me the last letter in my name, and also tell me who won the world cup in 1978?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "VhQw5Z1VRQjy"
   },
   "outputs": [],
   "source": [
    "agent_chain.run(input=\"whats the weather like in pomfret?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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