langchain-retrieval

Original：🇺🇸 English

Translated

Document Q&A with RAG using Supabase pgvector store.

1installs

Sourceeng0ai/eng0-template-skills

Added on2026-02-09

NPX Install

npx skill4agent add eng0ai/eng0-template-skills langchain-retrieval

SKILL.md Content

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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

bash

git clone --depth 1 https://github.com/Eng0AI/langchain-retrieval.git .

If the directory is not empty:

bash

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)

bash

rm -rf .git
git init

3. Install Dependencies

bash

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

bash

pnpm build

Development

bash

pnpm dev

langchain-retrieval

NPX Install

Tags

SKILL.md Content

LangChain Retrieval

Tech Stack

Prerequisites

Setup

1. Clone the Template

2. Remove Git History (Optional)

3. Install Dependencies

4. Setup Environment Variables

5. Setup Vector Store

Build

Development