fixes

Author: markjbrown

articles/cosmos-db/.openpublishing.redirection.cosmos-db.json

@@ -6172,7 +6172,7 @@
     },
     {
       "source_path_from_root": "/articles/cosmos-db/rag-data-openai.md",
-      "redirect_url": "/azure/cosmos-db/cosmos-db/vector-search",
+      "redirect_url": "/azure/cosmos-db/vector-search",
       "redirect_document_id": true
     }
   ]

articles/cosmos-db/introduction.md

@@ -20,7 +20,7 @@ Today's applications are required to be highly responsive and always online. To
 
 Azure Cosmos DB is a fully managed NoSQL and relational database for modern app development. Azure Cosmos DB offers single-digit millisecond response times, automatic and instant scalability, along with guaranteed speed at any scale. Business continuity is assured with [SLA-backed](https://azure.microsoft.com/support/legal/sla/cosmos-db) availability and enterprise-grade security.
 
-Use Retrieval Augmented Generation (RAG) to bring the most semantically relevant data to enrich your AI-powered applications built with Azure OpenAI models like GPT-3.5 and GPT-4. For more information, see [Retrieval Augmented Generation (RAG) with Azure Cosmos DB](vector-search.md#Retrieval-Augmented-Generation-(RAG)).
+Use Retrieval Augmented Generation (RAG) to bring the most semantically relevant data to enrich your AI-powered applications built with Azure OpenAI models like GPT-3.5 and GPT-4. For more information, see [Retrieval Augmented Generation (RAG) with Azure Cosmos DB](vector-search.md#retrieval-augmented-generation).
 
 App development is faster and more productive thanks to:
 

articles/cosmos-db/mongodb/TOC.yml

@@ -390,7 +390,7 @@
             - name: Integrate with Azure services
               href: integrations-overview.md              
             - name: RAG with Azure OpenAI
-              href: ../vector-search#Retrieval-Augmented-Generation-(RAG).md
+              href: ../vector-search.md#retrieval-augmented-generation
             - name: Vercel
               href: ../vercel-integration.md
         - name: Migrate data to Azure Cosmos DB

articles/cosmos-db/nosql/TOC.yml

@@ -896,7 +896,7 @@
     - name: Integrate with other Azure services
       items:
         - name: RAG with Azure OpenAI
-          href: ../vector-search.md#Retrieval-Augmented-Generation-(RAG)
+          href: ../vector-search.md#retrieval-augmented-generation
         - name: Change feed Ecommerce solution
           href: changefeed-ecommerce-solution.md
         - name: Azure App Service

articles/cosmos-db/vector-search.md

@@ -29,7 +29,7 @@ To jump right into tutorials and sample code for RAG patterns with Azure Cosmos
 
 This section includes key concepts that are critical to implementing RAG with Azure Cosmos DB and Azure OpenAI.
 
-### Retrieval Augmented Generation (RAG)
+### Retrieval Augmented Generation (RAG) <a id="retrieval-augmented-generation"></a>
 
 RAG involves the process of retrieving supplementary data to provide the LLM with the ability to use this data when it generates responses. When presented with a user's question or prompt, RAG aims to select the most pertinent and current domain-specific knowledge from external sources, such as articles or documents. This retrieved information serves as a valuable reference for the model when generating its response. For example, a simple RAG pattern using Azure Cosmos DB for NoSQL could be: