Full Control RAG System Template: Self-Hosted AI Support (Python/FastAPI/Docker)

Tired of the limitations and potential costs of visual automation tools like n8n for complex AI tasks? Want full control over your AI Customer Support system?

This template provides a robust, self-hosted foundation for creating powerful Retrieval-Augmented Generation (RAG) systems. Gain deep customization, enhanced data privacy, and transparent control that visual builders can't offer. Save weeks of development while retaining full ownership of your application.

Built with Python and FastAPI, this system is designed for flexibility, performance, and easy deployment via Docker.

Why Choose This Self-Hosted Template?

• Unmatched Customization: Access 100% of the Python code. Modify core logic, fine-tune prompts, integrate unique components, or rebuild the UI – impossible with closed platforms.
• Own Your Data: Keep sensitive knowledge bases and customer interactions securely within your own infrastructure. Essential for privacy compliance (GDPR, CCPA) and handling confidential information.
• Transparent & Debuggable: No black boxes. Easily trace execution, debug issues directly in the code, and understand every step of the RAG pipeline.
• Cost-Effective Scaling: Avoid per-transaction fees common on automation platforms. Optimize your infrastructure and leverage high-performance, low-cost LLMs via providers like Groq.
• No Platform Lock-in: You own the code. Deploy it anywhere, modify it freely, and integrate it seamlessly without being tied to a specific vendor's ecosystem.

Key Features:

• Flexible LLM Integration: Supports:
  • OpenAI: gpt-4o, gpt-4-turbo, etc.
  • Anthropic: claude-3-5-sonnet, claude-3-opus, etc.
  • Groq (for extreme speed): Access models like Meta's Llama 4 Scout, DeepSeek-R1, Qwen2.5, and more. Easily switch providers via environment variables.
• Multiple Vector DB Options: Use local ChromaDB or production-grade Pinecone.
• Comprehensive Document Processing: Ingest knowledge from PDF, DOCX, TXT, HTML.
• Robust FastAPI Backend: Endpoints for querying, streaming, document management, cost tracking, evaluation, and health checks.
• User-Friendly Web Interface: Simple UI for document upload and querying.
• Dockerized for Easy Deployment: Includes Dockerfile! Develop locally and deploy anywhere Docker is supported.

Who is this for?

• Developers needing full control over their AI stack.
• Teams prioritizing data privacy and security for their knowledge bases.
• AI Agencies wanting a customizable, white-label RAG foundation for clients.
• Businesses seeking a transparent, potentially more cost-effective RAG solution than managed services or automation platforms.

What you get:

• Complete Python source code.
• Dockerfile for easy containerization.
• requirements.txt and detailed README.md.
• Sample documents and utility scripts.

Take control of your AI. Build, customize, and deploy your RAG system with confidence!

Link to Live Demo

Vieo Demo