A Python package for managing AI chat conversation history with support for multiple LLM providers (OpenAI, Anthropic, Google, X.AI) and convenient conversation management features.
- Support for multiple AI providers:
- OpenAI (GPT-3.5, GPT-4)
- Anthropic (Claude)
- Google (Gemini)
- X.AI (Grok)
- Intelligent message role management (system, user, assistant)
- Conversation history tracking and validation
- Load balancing across multiple API keys
- Error handling and retry mechanisms
- Conversation saving and loading
- Memory management options
- Conversation search and indexing
- Rich conversation display options
pip install llm-dialog-manager
Create a .env
file in your project root:
# OpenAI
OPENAI_API_KEY_1=your-key-1
OPENAI_API_BASE_1=https://api.openai.com/v1
# Anthropic
ANTHROPIC_API_KEY_1=your-anthropic-key
ANTHROPIC_API_BASE_1=https://api.anthropic.com
# Google
GEMINI_API_KEY=your-gemini-key
# X.AI
XAI_API_KEY=your-x-key
from llm_dialog_manager import Agent
# Initialize an agent with a specific model
agent = Agent("claude-2.1", memory_enabled=True)
# Add messages and generate responses
agent.add_message("system", "You are a helpful assistant")
agent.add_message("user", "What is the capital of France?")
response = agent.generate_response()
# Save conversation
agent.save_conversation()
python app.py
# open localhost:8000
Screen-2024-11-24-201206.mp4
pytest tests/
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
For support, please open an issue in the GitHub repository or contact the maintainers.