agentUniverse is an LLM multi-agent framework designed for developers and enterprises to build sophisticated, domain-expert-level intelligent agents. It simplifies the creation of collaborative agent applications by providing a rich set of pre-built, industry-tested multi-agent collaboration patterns and enabling easy integration of domain expertise.

How It Works

The framework's core is its "collaborative pattern factory," offering components like the PEER pattern (Plan, Execute, Express, Review) for complex problem decomposition and iterative improvement, and the DOE pattern (Data-fining, Opinion-inject, Express) for data-intensive tasks requiring expert input. This modular approach allows agents to specialize and collaborate effectively, enhancing reasoning and analytical capabilities. Integration with various LLM vendors (Qwen, Deepseek, OpenAI, Claude, Gemini, Llama, etc.) is achieved through simple configuration.

Quick Start & Requirements

• Install: pip install agentUniverse
• Prerequisites: ruamel.yaml for the visual platform. API keys for desired LLM vendors.
• Resources: Detailed tutorials are available for building single agents, multi-agent applications, and using the visual agentic workflow platform.
• Links: User Guide, Quick Start for Product Platform, Discord.

Highlighted Details

• PEER pattern demonstrated superior performance over BabyAGI in completeness, relevance, and logicality, achieving 83% accuracy with GPT-3.5 Turbo and 81% with GPT-4.
• Supports a wide array of LLM vendors and models through simple configuration.
• Includes a visual agentic workflow platform for creating agentic workflows.
• Validated in real-world financial business practices at AntGroup.

Maintenance & Community

The project originates from AntGroup and is actively maintained. Support is available via GitHub Issues (response within 2 business days) and a Discord channel. Contact emails for administrators are provided.

Licensing & Compatibility

The project acknowledges dependencies on other open-source projects like Langchain and Pydantic. The specific license for agentUniverse itself is not explicitly stated in the README, which may require further investigation for commercial use or closed-source linking.

Limitations & Caveats

The README does not explicitly state the project's license, which could be a concern for commercial adoption. While many LLM vendors are supported, specific model compatibility or performance tuning might require user effort.