This project demonstrates automated multi-agent collaboration using the AutoGen framework, where AI agents work together to solve complex tasks through structured communication. The system consists of multiple agents, including a User Proxy (Admin), Coder, and Product Manager, all coordinated by a Group Chat Manager to enhance efficiency in problem-solving.
- Multi-Agent Collaboration – AI agents interact dynamically to achieve a common goal.
- Automated Task Execution – Intelligent delegation and execution of tasks based on agent roles.
- Scalable Architecture – Easily modify the number and functionality of agents.
- Configurable Execution – Customize system messages, execution settings, and agent behaviors.
Oversees the conversation, provides input, and ensures smooth execution.
Responsible for writing, reviewing, and debugging code.
Generates software product ideas and strategic recommendations.
Facilitates structured multi-agent communication.
The Group Chat enables the agents to interact seamlessly, exchanging information and refining solutions in a collaborative manner.
- Software Development Assistance – Automate coding tasks through AI-driven collaboration.
- AI-Powered Brainstorming – Generate and refine product ideas with structured AI discussions.
- Automated Research & Analysis – Leverage LLMs to extract insights and provide recommendations.
Add or remove agents based on your requirements.
Define custom behaviors for different AI personas.
Adjust parameters like conversation length and task complexity.
- ✅ Support for additional AI roles (e.g., Tester, Data Analyst).
- ✅ Integration with external APIs for real-world applications.
- ✅ Improved task prioritization and workflow automation.
This project is open-source and available under the MIT License.