What credentials do I need for deployment?

You will need a Vercel or Netlify token, a Supabase database URI, and an OpenAI API key for generating vector embeddings.

Why is the Vercel prebuilt mode mandatory?

In many virtual environments, standard Vercel deployments fail due to Git author permission issues. Local prebuilding allows Claude to bypass these restrictions for a successful deployment.

Can I use this for both development and production?

While it handles environment setup, this skill is specifically optimized for production build and deployment workflows rather than local dev server management.

Does this skill handle database migrations?

Yes, it includes a setup command that automatically creates the pgvector extension, the documents table, and the necessary matching functions in Supabase.

How are environment variables managed?

The skill reads your .env.example to identify required variables and helps sync current environment values to your .env file and your deployment provider's dashboard.

Build and Deploy LangChain Agent

Name: Build and Deploy LangChain Agent
Author: rebyteai-template

byrebyteai-template

デプロイメントとDevOps

Automates the environment configuration, vector store setup, and production deployment of LangChain retrieval applications.

概要

This skill streamlines the deployment lifecycle for LangChain-based retrieval agents, handling complex tasks like Supabase vector store initialization and environment variable synchronization. It specifically addresses deployment constraints in virtual environments by enforcing the Vercel prebuilt workflow, which bypasses Git permission issues commonly encountered in automated CI/CD pipelines. Whether you are launching a RAG application on Vercel or Netlify, this skill ensures your AI agent moves from development to production with all necessary database schemas and infrastructure settings in place.

主な機能

Environment variable synchronization from .env.example templates
Automated Supabase vector store setup including pgvector and document tables
Streamlined dependency management and production build sequences
0 GitHub stars
Mandatory Vercel prebuilt workflow to prevent deployment permission errors
Multi-platform deployment support for both Vercel and Netlify

ユースケース

Initializing Supabase database schemas for vector-based AI search
Automating the migration of local AI agent projects to serverless cloud hosting
Deploying production-ready RAG (Retrieval-Augmented Generation) applications

概要

主な機能

Environment variable synchronization from .env.example templates
Automated Supabase vector store setup including pgvector and document tables
Streamlined dependency management and production build sequences
0 GitHub stars
Mandatory Vercel prebuilt workflow to prevent deployment permission errors
Multi-platform deployment support for both Vercel and Netlify

ユースケース

Initializing Supabase database schemas for vector-based AI search
Automating the migration of local AI agent projects to serverless cloud hosting
Deploying production-ready RAG (Retrieval-Augmented Generation) applications