From 3a32223a6f9ad5e66f2ea09962c93ab6324b77c5 Mon Sep 17 00:00:00 2001 From: Viraj Agarwal Date: Thu, 6 Nov 2025 10:35:43 +0530 Subject: [PATCH 1/3] update: shortened rag --- haystack/gsi/frontmatter.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/haystack/gsi/frontmatter.md b/haystack/gsi/frontmatter.md index 23fab296..8a27e9cc 100644 --- a/haystack/gsi/frontmatter.md +++ b/haystack/gsi/frontmatter.md @@ -1,8 +1,8 @@ --- # frontmatter path: "/tutorial-openai-haystack-rag-with-gsi" -title: "Retrieval-Augmented Generation (RAG) with OpenAI, Haystack and Couchbase Hyperscale and Composite Vector Indexes" -short_title: "RAG with OpenAI Haystack and Couchbase Hyperscale and Composite Vector Indexes" +title: "RAG with OpenAI, Haystack and Couchbase Hyperscale and Composite Vector Indexes" +short_title: "RAG with OpenAI, Haystack 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. From 78b772e12b89c4e743757c78559c1e56f7dd097c Mon Sep 17 00:00:00 2001 From: Viraj Agarwal Date: Thu, 6 Nov 2025 10:41:10 +0530 Subject: [PATCH 2/3] update: short title --- haystack/gsi/frontmatter.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/haystack/gsi/frontmatter.md b/haystack/gsi/frontmatter.md index 8a27e9cc..1da0623e 100644 --- a/haystack/gsi/frontmatter.md +++ b/haystack/gsi/frontmatter.md @@ -2,7 +2,7 @@ # frontmatter path: "/tutorial-openai-haystack-rag-with-gsi" title: "RAG with OpenAI, Haystack and Couchbase Hyperscale and Composite Vector Indexes" -short_title: "RAG with OpenAI, Haystack and Couchbase Hyperscale and Composite Vector Indexes" +short_title: "RAG with OpenAI, Haystack and Couchbase CVI and HVI" 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. From 897d1da75c71b1a9bff73900e4d5cdb788afab22 Mon Sep 17 00:00:00 2001 From: Viraj Agarwal Date: Thu, 6 Nov 2025 10:43:43 +0530 Subject: [PATCH 3/3] update: shortened llamaindex titles --- lamaindex/gsi/frontmatter.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lamaindex/gsi/frontmatter.md b/lamaindex/gsi/frontmatter.md index 0449ace0..17e0aadf 100644 --- a/lamaindex/gsi/frontmatter.md +++ b/lamaindex/gsi/frontmatter.md @@ -1,8 +1,8 @@ --- # 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" +title: "RAG with OpenAI, LlamaIndex and Couchbase Hyperscale and Composite Vector Indexes" +short_title: "RAG with OpenAI, LlamaIndex and Couchbase CVI and HVI" 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.