Added tutorial for Langchain Couchbase Vector Search #75

azaddhirajkumar · 2025-11-11T07:28:35Z

No description provided.

gemini-code-assist · 2025-11-11T07:28:47Z

Summary of Changes

Hello @azaddhirajkumar, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request delivers a new tutorial designed to walk developers through the creation of an AI-driven PDF chat application. The tutorial highlights how to effectively combine Couchbase Vector Search for document retrieval, LangChain for managing large language model interactions and data processing, and Streamlit for a user-friendly interface. It provides practical guidance on implementing Retrieval-Augmented Generation (RAG) to enhance LLM responses with document context and demonstrates performance improvements through LLM response caching.

Highlights

New Tutorial: Introduces a comprehensive guide for building a PDF Chat Application using Couchbase Vector Search.
Technology Stack: Demonstrates integration of Couchbase Vector Search (Query Service), LangChain, OpenAI LLMs, and Streamlit for an AI-powered chat experience.
Core Concepts: Explains and implements Retrieval-Augmented Generation (RAG) for contextual Q&A and LLM response caching with Couchbase.
Vector Indexing: Details the use of Hyperscale and Composite Vector Indexes in Couchbase and programmatic index creation.
LangChain Integration: Showcases LangChain's capabilities for PDF processing, embedding generation, vector store integration, and building complex chains with LCEL.

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Code Review

This pull request adds a new tutorial for building a PDF chat application using Couchbase Vector Search with the Query Service, LangChain, and Python. The tutorial is well-structured and comprehensive. I've provided several review comments to enhance clarity, fix minor errors in code snippets and text, and improve formatting. Addressing these points will make the tutorial easier for users to follow and help them avoid potential issues.