Generated markdown tutorials from Jupyter Notebooks

Generated from: couchbase-examples/vector-search-cookbook

Author: actions-user

tutorial/markdown/generated/vector-search-cookbook/lamaindex-fts-RAG_with_Couchbase_Capella_and_OpenAI.md

@@ -2,7 +2,7 @@
 # frontmatter
 path: "/tutorial-openai-llamaindex-rag-with-fts"
 title: "Retrieval-Augmented Generation (RAG) with OpenAI, LlamaIndex and Couchbase Search Vector Index"
-short_title: "RAG with Openai, LlamaIndex and Couchbase Search Vector Index"
+short_title: "RAG with OpenAI, LlamaIndex and Couchbase Search Vector Index"
 description:
   - Learn how to build a semantic search engine using Couchbase's Search Vector Index.
   - This tutorial demonstrates how to integrate Couchbase's search vector search capabilities with the embeddings generated by OpenAI Services.

tutorial/markdown/generated/vector-search-cookbook/lamaindex-gsi-RAG_with_Couchbase_Capella_and_OpenAI.md

@@ -2,7 +2,7 @@
 # frontmatter
 path: "/tutorial-openai-llamaindex-rag-with-gsi"
 title: "Retrieval-Augmented Generation (RAG) with OpenAI, LlamaIndex and Couchbase Hyperscale and Composite Vector Indexes"
-short_title: "RAG with Openai, LlamaIndex and Couchbase Hyperscale and Composite Vector Indexes"
+short_title: "RAG with OpenAI, LlamaIndex and Couchbase Hyperscale and Composite Vector Indexes"
 description:
   - Learn how to build a semantic search engine using Couchbase's Hyperscale and Composite Vector Indexes.
   - This tutorial demonstrates how to integrate Couchbase's GSI vector search capabilities with OpenAI embeddings.