Agent-Skills.md

Agent Skills: LangChain Retrieval

Document Q&A with RAG using Supabase pgvector store.

UncategorizedID: eng0ai/eng0-template-skills/langchain-retrieval

Repository

eng0ai/eng0-template-skills
rebyteai-template
1

Install this agent skill to your local

pnpm dlx add-skill https://github.com/rebyteai-template/rebyte-skills/tree/HEAD/langchain-retrieval

Skill Files

Browse the full folder contents for langchain-retrieval.

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langchain-retrieval/SKILL.md

Skill Metadata

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
LangChain Retrieval Skill | Agent Skills