Bagatur/deeplake docs fixes (#9275)

Co-authored-by: adilkhan <adilkhan.sarsen@nu.edu.kz>

docs/extras/modules/data_connection/retrievers/self_query/activeloop_deeplake_self_query.ipynb

@@ -6,7 +6,7 @@
    "id": "13afcae7",
    "metadata": {},
    "source": [
-    "# DeepLake self-querying \n",
+    "# Deep Lake self-querying \n",
     "\n",
     ">[DeepLake](https://www.activeloop.ai) is a multimodal database for building AI applications.\n",
     "\n",
@@ -19,7 +19,7 @@
    "id": "68e75fb9",
    "metadata": {},
    "source": [
-    "## Creating a DeepLake vectorstore\n",
+    "## Creating a Deep Lake vectorstore\n",
     "First we'll want to create a DeepLake VectorStore and seed it with some data. We've created a small demo set of documents that contain summaries of movies.\n",
     "\n",
     "NOTE: The self-query retriever requires you to have `lark` installed (`pip install lark`). We also need the `deeplake` package."
@@ -27,26 +27,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "id": "63a8af5b",
-   "metadata": {
-    "tags": []
-   },
+   "execution_count": null,
+   "id": "a798fe66",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "#!pip install lark"
+    "# !pip install lark"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "22431060-52c4-48a7-a97b-9f542b8b0928",
-   "metadata": {
-    "tags": []
-   },
+   "id": "43821a8e",
+   "metadata": {},
    "outputs": [],
    "source": [
-    "#!pip install 'deeplake[enterprise]'"
+    "# in case if some queries fail consider installing libdeeplake manually\n",
+    "# !pip install libdeeplake"
    ]
   },
   {
@@ -60,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "dd01b61b-7d32-4a55-85d6-b2d2d4f18840",
    "metadata": {
     "tags": []
@@ -70,12 +67,13 @@
     "import os\n",
     "import getpass\n",
     "\n",
-    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
+    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
+    "os.environ[\"ACTIVELOOP_TOKEN\"] = getpass.getpass(\"Activeloop token:\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "cb4a5787",
    "metadata": {
     "tags": []
@@ -108,7 +106,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "-"
+      "/"
      ]
     },
     {
@@ -166,9 +164,9 @@
     "        },\n",
     "    ),\n",
     "]\n",
-    "username_or_org = \"<USER_NAME_OR_ORG>\"\n",
+    "username_or_org = \"<USERNAME_OR_ORG>\"\n",
     "vectorstore = DeepLake.from_documents(\n",
-    "    docs, embeddings, dataset_path=f\"hub://{username_or_org}/self_queery\"\n",
+    "    docs, embeddings, dataset_path=f\"hub://{username_or_org}/self_queery\", overwrite=True,\n",
     ")"
    ]
   },
@@ -185,10 +183,8 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "86e34dbf",
-   "metadata": {
-    "tags": []
-   },
+   "id": "c90b0b40",
+   "metadata": {},
    "outputs": [],
    "source": [
     "from langchain.llms import OpenAI\n",
@@ -242,7 +238,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/adilkhansarsen/Documents/work/LangChain/langchain/langchain/chains/llm.py:275: UserWarning: The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain.\n",
+      "/home/ubuntu/langchain_activeloop/langchain/libs/langchain/langchain/chains/llm.py:279: UserWarning: The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain.\n",
       "  warnings.warn(\n"
      ]
     },
@@ -299,7 +295,9 @@
    ],
    "source": [
     "# This example only specifies a filter\n",
-    "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")"
+    "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")\n",
+    "\n",
+    "# in case if this example errored out, consider installing libdeeplake manually: `pip install libdeeplake`, and then restart notebook."
    ]
   },
   {
@@ -456,14 +454,6 @@
     "# This example only specifies a relevant query\n",
     "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c93f0847-cbd9-4c25-aed1-91588e856b5c",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -482,7 +472,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,