langchain/docs/extras/integrations/retrievers/google_drive.ipynb

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    "# Google Drive Retriever\n",
    "This notebook covers how to retrieve documents from Google Drive.\n",
    "\n",
    "## Prerequisites\n",
    "\n",
    "1. Create a Google Cloud project or use an existing project\n",
    "1. Enable the [Google Drive API](https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com)\n",
    "1. [Authorize credentials for desktop app](https://developers.google.com/drive/api/quickstart/python#authorize_credentials_for_a_desktop_application)\n",
    "1. `pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib`\n",
    "\n",
    "## Instructions for retrieving your Google Docs data\n",
    "By default, the `GoogleDriveRetriever` expects the `credentials.json` file to be `~/.credentials/credentials.json`, but this is configurable using the `GOOGLE_ACCOUNT_FILE` environment variable. \n",
    "The location of `token.json` use the same directory (or use the parameter `token_path`). Note that `token.json` will be created automatically the first time you use the retriever.\n",
    "\n",
    "`GoogleDriveRetriever` can retrieve a selection of files with some requests. \n",
    "\n",
    "By default, If you use a `folder_id`, all the files inside this folder can be retrieved to `Document`.\n"
   ]
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   "cell_type": "markdown",
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    "You can obtain your folder and document id from the URL:\n",
    "* Folder: https://drive.google.com/drive/u/0/folders/1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5 -> folder id is `\"1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5\"`\n",
    "* Document: https://docs.google.com/document/d/1bfaMQ18_i56204VaQDVeAFpqEijJTgvurupdEDiaUQw/edit -> document id is `\"1bfaMQ18_i56204VaQDVeAFpqEijJTgvurupdEDiaUQw\"`\n",
    "\n",
    "The special value `root` is for your personal home."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c9665c9-a023-4078-9d95-e43021cecb6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "878928a6-a5ae-4f74-b351-64e3b01733fe",
   "metadata": {
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     "start_time": "2023-05-09T10:45:57.955900302Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain.retrievers import GoogleDriveRetriever"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "755907c2-145d-4f0f-9b15-07a628a2d2d2",
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2023-05-09T10:45:59.440941528Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "folder_id=\"root\"\n",
    "#folder_id='1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2216c83f-68e4-4d2f-8ea2-5878fb18bbe7",
   "metadata": {
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    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "retriever = GoogleDriveRetriever(\n",
    "    num_results=2,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa339ca0-f478-440c-ba80-0e5f41a19ce1",
   "metadata": {},
   "source": [
    "By default, all files with these mime-type can be converted to `Document`.\n",
    "- text/text\n",
    "- text/plain\n",
    "- text/html\n",
    "- text/csv\n",
    "- text/markdown\n",
    "- image/png\n",
    "- image/jpeg\n",
    "- application/epub+zip\n",
    "- application/pdf\n",
    "- application/rtf\n",
    "- application/vnd.google-apps.document (GDoc)\n",
    "- application/vnd.google-apps.presentation (GSlide)\n",
    "- application/vnd.google-apps.spreadsheet (GSheet)\n",
    "- application/vnd.google.colaboratory (Notebook colab)\n",
    "- application/vnd.openxmlformats-officedocument.presentationml.presentation (PPTX)\n",
    "- application/vnd.openxmlformats-officedocument.wordprocessingml.document (DOCX)\n",
    "\n",
    "It's possible to update or customize this. See the documentation of `GDriveRetriever`.\n",
    "\n",
    "But, the corresponding packages must be installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9dadec48",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install unstructured"
   ]
  },
  {
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   "execution_count": null,
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    "tags": []
   },
   "outputs": [],
   "source": [
    "retriever.get_relevant_documents(\"machine learning\")"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "You can customize the criteria to select the files. A set of predefined filter are proposed:\n",
    "| template                               | description                                                           |\n",
    "| -------------------------------------- | --------------------------------------------------------------------- |\n",
    "| gdrive-all-in-folder                   | Return all compatible files from a `folder_id`                        |\n",
    "| gdrive-query                           | Search `query` in all drives                                          |\n",
    "| gdrive-by-name                         | Search file with name `query`)                                        |\n",
    "| gdrive-query-in-folder                 | Search `query` in `folder_id` (and sub-folders in `_recursive=true`)  |\n",
    "| gdrive-mime-type                       | Search a specific `mime_type`                                         |\n",
    "| gdrive-mime-type-in-folder             | Search a specific `mime_type` in `folder_id`                          |\n",
    "| gdrive-query-with-mime-type            | Search `query` with a specific `mime_type`                            |\n",
    "| gdrive-query-with-mime-type-and-folder | Search `query` with a specific `mime_type` and in `folder_id`         |"
   ]
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  {
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   "source": [
    "retriever = GoogleDriveRetriever(\n",
    "    template=\"gdrive-query\", # Search everywhere\n",
    "    num_results=2,  # But take only 2 documents\n",
    ")\n",
    "for doc in retriever.get_relevant_documents(\"machine learning\"):\n",
    "    print(\"---\")\n",
    "    print(doc.page_content.strip()[:60]+\"...\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5a0f3ef-26fb-4a5c-85f0-5aba90b682b1",
   "metadata": {},
   "source": [
    "Else, you can customize the prompt with a specialized `PromptTemplate`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0bbebde-0487-4d20-9d77-8070e4f0e0d6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain import PromptTemplate\n",
    "retriever = GoogleDriveRetriever(\n",
    "    template=PromptTemplate(input_variables=['query'],\n",
    "                            # See https://developers.google.com/drive/api/guides/search-files\n",
    "                            template=\"(fullText contains '{query}') \"\n",
    "                              \"and mimeType='application/vnd.google-apps.document' \"\n",
    "                              \"and modifiedTime > '2000-01-01T00:00:00' \"\n",
    "                              \"and trashed=false\"),\n",
    "    num_results=2,\n",
    "    # See https://developers.google.com/drive/api/v3/reference/files/list\n",
    "    includeItemsFromAllDrives=False,\n",
    "    supportsAllDrives=False,\n",
    ")\n",
    "for doc in retriever.get_relevant_documents(\"machine learning\"):\n",
    "    print(f\"{doc.metadata['name']}:\")\n",
    "    print(\"---\")\n",
    "    print(doc.page_content.strip()[:60]+\"...\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b6fed29-1666-452e-b677-401613270388",
   "metadata": {},
   "source": [
    "# Use GDrive 'description' metadata\n",
    "Each Google Drive has a `description` field in metadata (see the *details of a file*).\n",
    "Use the `snippets` mode to return the description of selected files.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "342dbe12-ed83-40f4-8957-0cc8c4609542",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "retriever = GoogleDriveRetriever(\n",
    "    template='gdrive-mime-type-in-folder',\n",
    "    folder_id=folder_id,\n",
    "    mime_type='application/vnd.google-apps.document',  # Only Google Docs\n",
    "    num_results=2,\n",
    "    mode='snippets',\n",
    "    includeItemsFromAllDrives=False,\n",
    "    supportsAllDrives=False,\n",
    ")\n",
    "retriever.get_relevant_documents(\"machine learning\")"
   ]
  }
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