langgraph nb changes (#8070)

GitOrigin-RevId: 1971dd957b60a6d6f6bcf70717a92e423ccb9e68

cookbooks/self-rag-agents/pathway_deploy_langgraph_agents.ipynb

@@ -1,5 +1,16 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d58d3552-9168-4f0f-8a79-4dbaa4a01bbf",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "> The following cookbook is an adaption of the original [LangGraph cookbook](https://github.com/langchain-ai/langgraph/blob/e3ca7bb3e9d34b09633852f4d08d55f6dcd4364b/examples/rag/langgraph_self_rag.ipynb)\n",
+    "\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b3e94de1-ca3d-4956-b212-4a558b68062a",
@@ -26,6 +37,20 @@
     "OpenAI is used for embeddings during the indexing stage and to power the LangGraph agent."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9e055de9-723f-44e3-ad39-70cc5f8932bf",
+   "metadata": {},
+   "source": [
+    "Magic library is used for detecting file types in the `ParseUnstructured` module.\n",
+    "\n",
+    "If you are running this notebook on **MacOS**, you can install it with:\n",
+    "> `brew install libmagic`\n",
+    "\n",
+    "If you are running the notebook on **colab** or any **linux** environment, you can install it with:\n",
+    "> `apt-get install libmagic1`"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -351,7 +376,9 @@
    },
    "cell_type": "markdown",
    "id": "5894115c-0323-4098-83be-da49d949a53c",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "### Self-RAG\n",
     "\n",
@@ -385,7 +412,7 @@
     "\n",
     "We will implement some of these ideas from scratch using [LangGraph](https://langchain-ai.github.io/langgraph/).\n",
     "![image.png](attachment:76895b7a-fcc5-4758-9fbb-510b17fdeda4.png)\n",
-    "> Figure taken from the LangGraph cookbook"
+    "> Figure and the explanation taken from the [LangGraph cookbook](https://github.com/langchain-ai/langgraph/blob/e3ca7bb3e9d34b09633852f4d08d55f6dcd4364b/examples/rag/langgraph_self_rag.ipynb)"
    ]
   },
   {
@@ -1001,14 +1028,6 @@
     "\n",
     "Thus, whenever you POST a `\"user_query\"` to the `/agent` endpoint, the agent pipeline runs, and returns the final answer."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "512f527d-400e-44af-add3-30a1b5a3c844",
-   "metadata": {},
-   "source": [
-    "> This notebook was inspired by this [LangGraph cookbook](https://github.com/langchain-ai/langgraph/blob/e3ca7bb3e9d34b09633852f4d08d55f6dcd4364b/examples/rag/langgraph_self_rag.ipynb)"
-   ]
   }
  ],
  "metadata": {