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Merged
shyam-cb merged 1 commit into from
Nov 4, 2025
Merged

haystack and llamaindex title change #68

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6 changes: 3 additions & 3 deletions haystack/fts/frontmatter.md
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Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
---
# frontmatter
path: "/tutorial-openai-haystack-rag-with-fts"
title: "Retrieval-Augmented Generation (RAG) with OpenAI and Haystack"
short_title: "RAG with Openai and Haystack"
title: "Retrieval-Augmented Generation (RAG) with OpenAI, Haystack and Couchbase Search Vector Index"
short_title: "RAG with OpenAI, Haystack and Couchbase Search Vector Index"
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@gemini-code-assist gemini-code-assist Bot Nov 4, 2025

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medium

The short_title is quite long, nearly the same length as the full title. For better display in UI elements where a shorter title is preferred, consider abbreviating it. Using "FTS" as seen in the path would make it more concise.

Suggested change
short_title: "RAG with OpenAI, Haystack and Couchbase Search Vector Index"
short_title: "RAG with OpenAI, Haystack and Couchbase FTS"

description:
- Learn how to build a semantic search engine using Couchbase's Search vector index.
- Learn how to build a semantic search engine using Couchbase's Search Vector Index.
- This tutorial demonstrates how to integrate Couchbase's vector search capabilities with the embeddings generated by OpenAI Services.
- You will understand how to perform Retrieval-Augmented Generation (RAG) using Haystack, Couchbase and OpenAI services.
content_type: tutorial
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6 changes: 3 additions & 3 deletions haystack/gsi/frontmatter.md
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Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
---
# frontmatter
path: "/tutorial-openai-haystack-rag-with-gsi"
title: "Retrieval-Augmented Generation (RAG) with OpenAI and Haystack"
short_title: "RAG with Openai and Haystack"
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"
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@gemini-code-assist gemini-code-assist Bot Nov 4, 2025

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medium

The short_title could be improved for clarity and conciseness.

  • It's quite long. Using "GSI" as seen in the path would make it more concise.
  • There appears to be a missing comma between "OpenAI" and "Haystack", which affects readability.
Suggested change
short_title: "RAG with OpenAI Haystack and Couchbase Hyperscale and Composite Vector Indexes"
short_title: "RAG with OpenAI, Haystack and Couchbase GSI"

description:
- Learn how to build a semantic search engine using Couchbase's GSI vector index.
- 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.
- You will understand how to perform Retrieval-Augmented Generation (RAG) using Haystack, Couchbase and OpenAI services.
content_type: tutorial
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6 changes: 3 additions & 3 deletions lamaindex/fts/frontmatter.md
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Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
---
# frontmatter
path: "/tutorial-openai-llamaindex-rag-with-fts"
title: "Retrieval-Augmented Generation (RAG) with OpenAI and LlamaIndex"
short_title: "RAG with Openai and LlamaIndex"
title: "Retrieval-Augmented Generation (RAG) with OpenAI, LlamaIndex and Couchbase Search Vector Index"
short_title: "RAG with Openai, LlamaIndex and Couchbase Search Vector Index"
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@gemini-code-assist gemini-code-assist Bot Nov 4, 2025

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medium

The short_title could be improved for consistency and conciseness.

  • It's quite long. Using "FTS" as seen in the path would make it more concise.
  • "Openai" should be capitalized to "OpenAI" to be consistent with the main title and other files.
Suggested change
short_title: "RAG with Openai, LlamaIndex and Couchbase Search Vector Index"
short_title: "RAG with OpenAI, LlamaIndex and Couchbase FTS"

description:
- Learn how to build a semantic search engine using Couchbase's Search vector index.
- 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.
- You will understand how to perform Retrieval-Augmented Generation (RAG) using Llamaindex, Couchbase and OpenAI services.
content_type: tutorial
Expand Down
6 changes: 3 additions & 3 deletions lamaindex/gsi/frontmatter.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
---
# frontmatter
path: "/tutorial-openai-llamaindex-rag-with-gsi"
title: "Retrieval-Augmented Generation (RAG) with OpenAI and LlamaIndex"
short_title: "RAG with Openai and LlamaIndex"
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"
Copy link
Copy Markdown
Contributor

@gemini-code-assist gemini-code-assist Bot Nov 4, 2025

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medium

The short_title could be improved for consistency and conciseness.

  • It's quite long. Using "GSI" as seen in the path would make it more concise.
  • "Openai" should be capitalized to "OpenAI" to be consistent with the main title and other files.
Suggested change
short_title: "RAG with Openai, LlamaIndex and Couchbase Hyperscale and Composite Vector Indexes"
short_title: "RAG with OpenAI, LlamaIndex and Couchbase GSI"

description:
- Learn how to build a semantic search engine using Couchbase's GSI vector search.
- 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.
- You will understand how to perform Retrieval-Augmented Generation (RAG) using LlamaIndex and GSI vector indexes.
content_type: tutorial
Expand Down
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