langchain/docs/modules/indexes/retrievers/examples/chatgpt-plugin-retriever.ipynb

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  {
   "cell_type": "markdown",
   "id": "1edb9e6b",
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   "source": [
    "# ChatGPT Plugin Retriever\n",
    "\n",
    "This notebook shows how to use the ChatGPT Retriever Plugin within LangChain."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "074b0004",
   "metadata": {},
   "source": [
    "## Create\n",
    "\n",
    "First, let's go over how to create the ChatGPT Retriever Plugin.\n",
    "\n",
    "To set up the ChatGPT Retriever Plugin, please follow instructions [here](https://github.com/openai/chatgpt-retrieval-plugin).\n",
    "\n",
    "You can also create the ChatGPT Retriever Plugin from LangChain document loaders. The below code walks through how to do that."
   ]
  },
  {
   "cell_type": "code",
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   "id": "bbe89ca0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# STEP 1: Load\n",
    "\n",
    "# Load documents using LangChain's DocumentLoaders\n",
    "# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html\n",
    "\n",
    "from langchain.document_loaders.csv_loader import CSVLoader\n",
    "loader = CSVLoader(file_path='../../document_loaders/examples/example_data/mlb_teams_2012.csv')\n",
    "data = loader.load()\n",
    "\n",
    "\n",
    "# STEP 2: Convert\n",
    "\n",
    "# Convert Document to format expected by https://github.com/openai/chatgpt-retrieval-plugin\n",
    "from typing import List\n",
    "from langchain.docstore.document import Document\n",
    "import json\n",
    "\n",
    "def write_json(path: str, documents: List[Document])-> None:\n",
    "    results = [{\"text\": doc.page_content} for doc in documents]\n",
    "    with open(path, \"w\") as f:\n",
    "        json.dump(results, f, indent=2)\n",
    "\n",
    "write_json(\"foo.json\", data)\n",
    "\n",
    "# STEP 3: Use\n",
    "\n",
    "# Ingest this as you would any other json file in https://github.com/openai/chatgpt-retrieval-plugin/tree/main/scripts/process_json\n"
   ]
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  {
   "cell_type": "markdown",
   "id": "0474661d",
   "metadata": {},
   "source": [
    "## Using the ChatGPT Retriever Plugin\n",
    "\n",
    "Okay, so we've created the ChatGPT Retriever Plugin, but how do we actually use it?\n",
    "\n",
    "The below code walks through how to do that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "39d6074e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.retrievers import ChatGPTPluginRetriever"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33fd23d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "retriever = ChatGPTPluginRetriever(url=\"http://0.0.0.0:8000\", bearer_token=\"foo\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "16250bdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Document(page_content=\"This is Alice's phone number: 123-456-7890\", lookup_str='', metadata={'id': '456_0', 'metadata': {'source': 'email', 'source_id': '567', 'url': None, 'created_at': '1609592400.0', 'author': 'Alice', 'document_id': '456'}, 'embedding': None, 'score': 0.925571561}, lookup_index=0),\n",
       " Document(page_content='This is a document about something', lookup_str='', metadata={'id': '123_0', 'metadata': {'source': 'file', 'source_id': 'https://example.com/doc1', 'url': 'https://example.com/doc1', 'created_at': '1609502400.0', 'author': 'Alice', 'document_id': '123'}, 'embedding': None, 'score': 0.6987589}, lookup_index=0),\n",
       " Document(page_content='Team: Angels \"Payroll (millions)\": 154.49 \"Wins\": 89', lookup_str='', metadata={'id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631_0', 'metadata': {'source': None, 'source_id': None, 'url': None, 'created_at': None, 'author': None, 'document_id': '59c2c0c1-ae3f-4272-a1da-f44a723ea631'}, 'embedding': None, 'score': 0.697888613}, lookup_index=0)]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retriever.get_relevant_documents(\"alice's phone number\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8b5794b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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