AI Agent Build & Deploy

About

This skill automates the complex workflow required to move a LangChain.js retrieval agent from local development to a production-ready cloud environment. It specializes in configuring Supabase vector databases with pgvector, synchronizing environment variables from templates, and executing specific deployment strategies—such as the mandatory Vercel prebuilt mode—to bypass common permission issues in virtual environments. It is ideal for developers building RAG (Retrieval-Augmented Generation) applications who need a reliable, repeatable path to production.

Key Features

• Integrated dependency management and production build optimization
• Environment variable synchronization and cloud secret injection
• Automated Supabase vector store and pgvector initialization
• Support for both Vercel and Netlify production workflows
• 0 GitHub stars
• Mandatory Vercel prebuilt deployment to resolve VM permission issues

Use Cases

• Initial setup of a Supabase vector database for document retrieval
• Deploying a RAG-based AI agent to Vercel production
• Migrating local environment configurations to cloud hosting providers