langchain-retrieval
Document Q&A with RAG using Supabase pgvector store.
When & Why to Use This Skill
This Claude skill implements a robust Document Q&A system using Retrieval-Augmented Generation (RAG). By integrating LangChain.js with Supabase pgvector, it enables the creation of a high-performance vector store for semantic search. It allows users to upload documents and receive precise, context-aware answers, making it an essential tool for building intelligent knowledge management systems.
Use Cases
- Enterprise Internal Wiki: Convert static company documentation and SOPs into an interactive AI assistant that helps employees find information instantly.
- Technical Support Automation: Power customer service bots with product manuals and troubleshooting guides to provide accurate, automated technical assistance.
- Research Data Synthesis: Efficiently query and summarize insights from large collections of academic papers, legal contracts, or financial reports.
- Personal Knowledge Management: Build a private 'second brain' to store and retrieve information from personal notes, books, and saved articles using natural language.
| name | langchain-retrieval |
|---|---|
| description | Document Q&A with RAG using Supabase pgvector store. |
LangChain Retrieval
Document Q&A with RAG (Retrieval Augmented Generation) using Supabase vector store.
Tech Stack
- Framework: Next.js
- AI: LangChain.js, AI SDK
- Vector Store: Supabase pgvector
- Package Manager: pnpm
Prerequisites
- Supabase project with pgvector extension
- OpenAI API key
Setup
1. Clone the Template
git clone --depth 1 https://github.com/Eng0AI/langchain-retrieval.git .
If the directory is not empty:
git clone --depth 1 https://github.com/Eng0AI/langchain-retrieval.git _temp_template
mv _temp_template/* _temp_template/.* . 2>/dev/null || true
rm -rf _temp_template
2. Remove Git History (Optional)
rm -rf .git
git init
3. Install Dependencies
pnpm install
4. Setup Environment Variables
Create .env with required variables:
SUPABASE_URL- Supabase project URLSUPABASE_PRIVATE_KEY- Supabase service role keyOPENAI_API_KEY- For embeddings and LLMSUPABASE_DB_URL- Direct PostgreSQL connection URL
5. Setup Vector Store
Initialize pgvector extension and create documents table in Supabase.
Build
pnpm build
Development
pnpm dev