mcp server
rag-project
Retrieval-Augmented Generation project
Set up
Runs on your computer. Pick your agent and operating system.
This project does not publish an install method we can turn into a config. Follow the README instead.
README
synced Oct 23, 2026Retrieval Augmented Generation Project
🗒 TODO
- Migrate services from Flask to FastAPI
- Switch the LangChain driver from Yandex to OpenAI
- Implement unit tests
- Split the augmented‑generation component into two separate services
- Add an API gateway
📋 Overview
🏗️ Components
- Flask - Lightweight WSGI web framework for Python, designed for rapid development and easy deployment of web applications.
- LangChain - Framework for developing applications powered by language models, providing tools for data retrieval, processing, and orchestration of LLM workflows.
- Qdrant - High-performance vector database optimized for similarity search and machine learning applications, supporting efficient storage and retrieval of vector embeddings.
- Yandex GPT - Comprehensive artificial intelligence platform offering a range of machine learning tools and services, including natural language processing, speech recognition, and computer vision capabilities.
📊 Diagrams
🛠️ Installation
Getting Started
docker compose up -d
Configuration
cp .env.example .env
💻 System Endpoints Overview
- Qdrant - http://localhost:6333
- data-vector-manager - http://localhost:8001
- augmentes-generation - http://localhost:8001
- llm-audit - http://localhost:8003
- mcp-server - http://localhost:3000
- mcp-client - http://localhost:8004
Swagger UI - /api/docs
License
This project is licensed under the MIT License - see the LICENSE file for details.