Claude-skill-registry langchain-retrieval

Document Q&A with RAG using Supabase pgvector store.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/langchain-retrieval" ~/.claude/skills/majiayu000-claude-skill-registry-langchain-retrieval && rm -rf "$T"

manifest: skills/data/langchain-retrieval/SKILL.md

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