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FastAPI Project Setup

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Bootstrap FastAPI backends with RAG.

Software Engineering#fastapi#rag#supabase#docker#setup#vector-search#project-bootstrap
AuthorShenSeanChen
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps developers bootstrap a production-ready FastAPI backend tailored for Retrieval-Augmented Generation (RAG), reducing setup time and ensuring best practices are followed.

Core Features & Use Cases

  • Guided choice between launch-rag and launch-agentic-rag to suit basic vs. advanced needs.
  • End-to-end project bootstrap: clone repository, create virtual environment, install dependencies, and configure environment variables.
  • Built-in guidance for database integration (Supabase/pgvector), model providers (OpenAI/Anthropic), and optional tool integrations.
  • Docker-ready and API/docs scaffolding to accelerate deployment and testing.

Quick Start

Clone the chosen repository, create a Python 3.11+ virtual environment, install dependencies, copy .env.example to .env, populate credentials, initialize the database, and run the server with uvicorn.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: FastAPI Project Setup
Download link: https://github.com/ShenSeanChen/launch-agent-skills/archive/main.zip#fastapi-project-setup

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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