Hands-on LLMs Project

This repository contains implementations and examples of working with different Large Language Model (LLM) services and platforms. The project is structured into three main components, each focusing on a different LLM integration.

Project Structure

1. Azure OpenAI Integration

A comprehensive implementation for integrating with Azure OpenAI services, providing interfaces for chat completions and text generation tasks.

Key Features:

• Azure OpenAI service integration with configuration management
• Chat completion examples with various parameters
• Lyric completion demo using conversation history
• Environment variable management for secure configuration

View Azure OpenAI Documentation

2. Hugging Face Integration

Integration with Hugging Face's transformers library and model hub, providing access to a wide range of open-source language models.

View Hugging Face Documentation

3. MCP (Model Control Panel)

A control panel implementation for managing and interacting with various language models.

View MCP Documentation

Getting Started

Each project has its own setup instructions and dependencies. Please refer to the individual README files in each directory for specific setup and usage instructions.

Common Requirements

• Python 3.8+
• Virtual environment management
• API keys for respective services (where applicable)

Repository Structure

.
├── OpenAI/          # Azure OpenAI integration
├── HuggingFace/     # Hugging Face models integration
└── MCP/             # Model Control Panel implementation

Contributing

Feel free to contribute to any of the sub-projects by creating pull requests or reporting issues.