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Author: davidhou17

README.md

@@ -1,7 +1,7 @@
 # MongoDB Documentation Notebooks
 
 This repository contains Jupyter Notebooks that follow
-tutorials and code examples in MongoDB's official [MongoDB Vector Search documentation](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/). You can run, download, and modify these notebooks as you learn how to use MongoDB Vector Search for your use case.
+tutorials and code examples in the official [MongoDB Vector Search documentation](https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/). You can run, download, and modify these notebooks as you learn how to use MongoDB Vector Search for your use case.
 
 ## Overview
 

ai-integrations/langchain-natural-language.ipynb

@@ -13,7 +13,7 @@
    "id": "e696dea0",
    "metadata": {},
    "source": [
-    "This notebook is a companion to the [Query MongoDB with Natural Language Using LangChain and LangGraph](https://www.mongodb.com/docs//ai-integrations/langchain/natural-language-to-mql/) tutorial. Refer to the page for set-up instructions and detailed explanations.\n",
+    "This notebook is a companion to the [Query MongoDB with Natural Language Using LangChain and LangGraph](https://www.mongodb.com/docs/atlas/ai-integrations/langchain/natural-language-to-mql/) tutorial. Refer to the page for set-up instructions and detailed explanations.\n",
     "\n",
     "This notebook demonstrates how to query a MongoDB cluster with a natural language prompt using an AI agent built with the [LangChain MongoDB Toolkit](https://langchain-mongodb.readthedocs.io/en/latest/langchain_mongodb/agent_toolkit/langchain_mongodb.agent_toolkit.toolkit.MongoDBDatabaseToolkit.html#langchain_mongodb.agent_toolkit.toolkit.MongoDBDatabaseToolkit) and the [LangGraph ReAct Agent Framework](https://langchain-ai.github.io/langgraph/agents/agents/).\n",
     "\n",

use-cases/ai-agent.ipynb

@@ -13,7 +13,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This notebook is a companion to the [Build AI Agents with MongoDB](https://www.mongodb.com/docs/atlas/atlas-vector-search/build-agents) page. For a more traditional Python development example and detailed explanations of the code, refer to the tutorial on the page.\n",
+    "This notebook is a companion to the [Build AI Agents with MongoDB](https://www.mongodb.com/docs/atlas/atlas-vector-search/ai-agents) page. For a more traditional Python development example and detailed explanations of the code, refer to the tutorial on the page.\n",
     "\n",
     "This notebook demonstrates an AI agent that uses MongoDB as the database for both agentic RAG and agent memory.\n",
     "\n",

use-cases/local-rag.ipynb

@@ -67,7 +67,7 @@
     "from pymongo import MongoClient\n",
     "from sentence_transformers import SentenceTransformer\n",
     "\n",
-    "# Connect to your local Atlas deployment or MongoDB Cluster\n",
+    "# Connect to your local Atlas deployment or MongoDB cluster\n",
     "client = MongoClient(MONGODB_URI)\n",
     "\n",
     "# Select the sample_airbnb.listingsAndReviews collection\n",