fastapi-rag 0.1.1

CLI tool for generating production-ready FastAPI RAG backend templates

FastAPI RAG: Enterprise AI Backend Generator

FastAPI RAG is a sophisticated CLI tool designed to scaffold production-grade AI backends. Instead of assembly-required boilerplates, it generates a complete, modular ecosystem for RAG (Retrieval-Augmented Generation) applications, specialized AI agents, and high-performance SaaS platforms.

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🌟 Why FastAPI RAG?

In the era of AI, the backend is more than just an API—it's an orchestrator. This tool generates a foundation that handles the complex "plumbing" of AI systems so you can focus on your domain logic.

• Intelligent Orchestration: Advanced LLM-based routing and agent selection logic.
• Stateful AI Interactions: Built-in persistence for multi-turn chat and conversation history.
• Production-Ready RAG: Async document ingestion, status tracking, and background processing.
• Infrastructure Agnostic: Pre-configured with swappable providers for LLMs, Vector DBs, and Caches.

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🚀 Quick Start

Generate your enterprise-grade backend in seconds:

1. Installation

pip install fastapi-rag

2. Generate Project

fastapi-rag new my-ai-platform

The CLI will guide you through selecting your preferred stack (OpenAI vs. Ollama, Qdrant vs. PgVector, etc.).

3. Launch Development Stack

cd my-ai-platform
docker compose up --build

Your backend is now live at http://localhost:8000 with full RAG and Agent capabilities.

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📦 What's Included in the Box?

The generated project is a fully-functional ecosystem:

• Security: JWT-based authentication with secure password hashing.
• AI Pipelines:
  • Async Ingestion: PDF/Text upload with background parsing and vector indexing.
  • Agentic Framework: Modular registry for specialized AI agents (SQL, RAG, Web Search).
• Persistence: Async SQLAlchemy 2.0 with the Repository pattern.
• Observability: Integrated Prometheus metrics and JSON logging.
• Infrastructure: Celery + Redis for background workflows and Qdrant for vector search.

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🗺️ Roadmap & Supported Providers

Category	Supported / Modeled Providers
LLMs	OpenAI, Ollama, Anthropic (Planned), Echo (Local Testing)
Vector DBs	Qdrant, Chroma, PgVector, Pinecone
Databases	PostgreSQL, MySQL
Caching	Redis, Dragonfly
Queues	Celery

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🛠️ Repository Development

Local Setup

git clone https://github.com/example/fastapi-rag.git
cd fastapi-rag
pip install -e .[dev]

Testing

pytest

Build Distribution

python -m build

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📚 Documentation

• Architecture Overview - Deep dive into the generator and scaffold design.
• User Guide - How to use the CLI and customize templates.
• First Feature Tutorial - Step-by-step guide to adding your first business rule.
• Publishing Guide - How to build and distribute the package.
• Contributing - Our standards for pull requests and code style.

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📄 License

This project is released under the MIT License.