Da 1250/fix tutorials titles (#109)

* DA-1250 fix: title-1

* DA-1250 fix: title-2

Author: VirajAgarwal1

capella-model-services/langchain/query_based/RAG_with_Capella_Model_Services_and_LangChain.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Introduction\n",
+    "## Introduction\n",
     "In this guide, we will walk you through building a Retrieval Augmented Generation (RAG) application using Couchbase Capella as the database, [Mistral-7B-Instruct-v0.3](https://build.nvidia.com/mistralai/mistral-7b-instruct-v03/modelcard) model as the large language model provided by Capella Model Services. We will use the [NVIDIA NeMo Retriever Llama3.2](https://build.nvidia.com/nvidia/llama-3_2-nv-embedqa-1b-v2/modelcard) model for generating embeddings via Capella Model Services.\n",
     "\n",
     "This notebook demonstrates how to build a RAG system using:\n",

smolagents/query_based/RAG_with_Couchbase_SmolAgents.ipynb

@@ -703,7 +703,6 @@
         "vector_store.create_index(index_type=IndexType.BHIVE, index_name=\"smolagents_bhive_index\", index_description=\"IVF,SQ8\")"
       ]
     },
-    
     {
       "cell_type": "code",
       "execution_count": null,
@@ -893,7 +892,7 @@
         "\n",
         "- 🛠️ Tool-agnostic: you can use tools from LangChain, Anthropic's MCP, you can even use a Hub Space as a tool.\n",
         "\n",
-        "# Building a RAG Agent using smolagents\n",
+        "## Building a RAG Agent using smolagents\n",
         "\n",
         "smolagents allows users to define their own tools for the agent to use. These tools can be of two types:\n",
         "1. Tools defined as classes: These tools are subclassed from the `Tool` class and must override the `forward` method, which is called when the tool is used.\n",