Utilizes environment variables through .env files for configuration settings like API keys and connection parameters.
Provides compatibility with Linux systems, supporting installation of dependencies like Tesseract for OCR functionality.
Supports Node.js for frontend functionality, enabling web-based interface to interact with the multi-model platform.
Uses npm for frontend package management and running the web interface components.
Integrates with OpenAI's API for LLM capabilities, using API keys to access models for text generation and processing.
Offers optional support for Poetry dependency management for Python packages, simplifying installation and environment management.
Built on Python with support for creating virtual environments and managing dependencies for the backend system.
MCP Server (Multi-Model + RAG + LLM Platform)
Kurulum Rehberi
Gereksinimler
- Python 3.9+
- Node.js 16+ (frontend için)
- Tesseract (OCR desteği için)
- (Linux/Mac:
sudo apt install tesseract-ocr
veyabrew install tesseract
) - pip veya poetry (isteğe bağlı)
1. Backend Kurulumu
a) Sanal Ortam Oluştur
b) Bağımlılıkları Yükle
c) Ortam Değişkenleri
.env
dosyasını oluştur:
Gerekirse OPENAI_API_KEY
ve diğer alanları doldur.
d) Veritabanını Başlat
e) Sunucuyu Çalıştır
- Uygulama arayüzü: http://localhost:8000/docs
2. Frontend (Web) Kurulumu
- Arayüz: http://localhost:3000
3. Notlar
- PDF/OCR için Tesseract kurulmalı.
- LLM entegrasyonu için
OPENAI_API_KEY
veya HuggingFace modeli indirecek internet bağlantısı gereklidir. - Vektör veritabanı ve LLM eklemek için ilgili Python dosyalarından kolayca genişletebilirsiniz.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A multi-model platform that integrates RAG (Retrieval-Augmented Generation) with LLMs, supporting OCR via Tesseract and offering both backend API and frontend web interface.
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