[hotfix] Deep Lake fails on newer version due to hardcode (#6383)

Hot Fixes for Deep Lake [would highly appreciate expedited review]

* deeplake version was hardcoded and since deeplake upgraded the
integration fails with confusing error
* an additional integration test fixed due to embedding function
* Additionally fixed docs for code understanding links after docs
upgraded
* notebook removal of public parameter to make sure code understanding
notebook works

#### Who can review?
  @hwchase17  @dev2049

---------

Co-authored-by: Davit Buniatyan <d@activeloop.ai>

docs/extras/use_cases/code/index.mdx

@@ -22,5 +22,5 @@ Query Understanding: GPT-4 processes user queries, grasping the context and extr
 5. Ask questions: Define a list of questions to ask about the codebase, and then use the ConversationalRetrievalChain to generate context-aware answers. The LLM (GPT-4) generates comprehensive, context-aware answers based on retrieved code snippets and conversation history.
 
 The full tutorial is available below.
-- [Twitter the-algorithm codebase analysis with Deep Lake](code/twitter-the-algorithm-analysis-deeplake.html): A notebook walking through how to parse github source code and run queries conversation.
-- [LangChain codebase analysis with Deep Lake](code/code-analysis-deeplake.html): A notebook walking through how to analyze and do question answering over THIS code base.
+- [Twitter the-algorithm codebase analysis with Deep Lake](./twitter-the-algorithm-analysis-deeplake.html): A notebook walking through how to parse github source code and run queries conversation.
+- [LangChain codebase analysis with Deep Lake](./code-analysis-deeplake.html): A notebook walking through how to analyze and do question answering over THIS code base.

docs/extras/use_cases/code/twitter-the-algorithm-analysis-deeplake.ipynb

@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -29,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,6 +62,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -78,6 +80,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -86,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -105,6 +108,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -124,6 +128,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -140,12 +145,12 @@
     "db = DeepLake(\n",
     "    dataset_path=f\"hub://{username}/twitter-algorithm\",\n",
     "    embedding_function=embeddings,\n",
-    "    public=True,\n",
-    ")  # dataset would be publicly available\n",
+    ")\n",
     "db.add_documents(texts)"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -155,9 +160,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Deep Lake Dataset in hub://davitbun/twitter-algorithm already exists, loading from the storage\n"
+     ]
+    }
+   ],
    "source": [
     "db = DeepLake(\n",
     "    dataset_path=\"hub://davitbun/twitter-algorithm\",\n",
@@ -168,7 +181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -180,6 +193,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -188,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -208,7 +222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -391,6 +405,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": []
@@ -412,7 +427,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.0"
+   "version": "3.9.7"
   }
  },
  "nbformat": 4,