MOYA is a reference implementation of our research paper titled "Engineering LLM Powered Multi-agent Framework for Autonomous CloudOps". The framework provides a flexible and extensible architecture for creating, managing, and orchestrating multiple AI agents to handle various tasks autonomously.
Preprint of the paper can be accessed at arXiv.
- Agent Management: Create, register, and manage multiple AI agents.
- Orchestration: Orchestrate conversations and tasks across multiple agents.
- Memory Tools: Integrate memory tools to maintain conversation context and history.
- Streaming Responses: Support for streaming responses from agents.
- Extensibility: Easily extend the framework with new agents, tools, and orchestrators.
- Python 3.10+
- Install required dependencies:
pip install .
Interactive chat example using OpenAI agent with conversation memory.
# filepath: ~/github/moya/examples/quick_start_openai.py
python -m examples.quick_start_openai
Interactive chat example using BedrockAgent with conversation memory.
# filepath: ~/github/moya/examples/quick_start_bedrock.py
AWS_PROFILE=my_profile_name python -m examples.quick_start_bedrock
Example demonstrating multi-agent orchestration with language and task classification.
# filepath: ~/github/moya/examples/quick_start_multiagent.py
python -m examples.quick_start_multiagent
Example demonstrating dynamic agent creation and registration during runtime.
# filepath: ~/github/moya/examples/dynamic_agents.py
python -m examples.dynamic_agents
moya/
├── agents/ # Agent implementations (OpenAI, Bedrock, Ollama, Remote)
├── classifiers/ # Classifier implementations for agent selection
├── memory/ # Memory repository implementations
├── orchestrators/ # Orchestrator implementations for managing agent interactions
├── registry/ # Agent registry and repository implementations
├── tools/ # Tool implementations (e.g., MemoryTool)
├── examples/ # Example scripts demonstrating various use cases
└── README.md # This README file
We welcome contributions to the MOYA framework. Please follow these steps to contribute:
- Fork the repository.
- Create a new branch for your feature or bugfix.
- Make your changes and commit them with descriptive messages.
- Push your changes to your fork.
- Create a pull request to the main repository.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or inquiries, please contact the authors of the research paper or open an issue on the GitHub repository.