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langchain-retrieval

@Eng0AI/eng0-template-skills
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Document Q&A with RAG using Supabase pgvector store.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

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 URL
  • SUPABASE_PRIVATE_KEY - Supabase service role key
  • OPENAI_API_KEY - For embeddings and LLM
  • SUPABASE_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