AgentCoord: Visually Exploring Coordination Strategy for LLM-based Multi-Agent Collaboration

AgentCoord is an experimental open-source system to help general users design coordination strategies for multiple LLM-based agents (Research paper forthcoming).

System Usage

Installation

Installation

git clone https://github.com/AgentCoord/AgentCoord.git
cd AgentCoord
pip install -r requirements.txt

Configuration

LLM configuration

You can set the configuration (i.e. API base, API key, Model name, Max tokens, Response per minute) for default LLM in config\config.yaml. Currently, we only support OpenAI’s LLMs as the default model. We recommend using gpt-4-0125-preview as the default model (WARNING: the execution process of multiple agents may consume a significant number of tokens).

You can switch to a fast mode that uses the Mistral 8×7B model with hardware acceleration by Groq for the first time in strategy generation to strike a balance of response quality and efficiency. To achieve this, you need to set the FAST_DESIGN_MODE field in the yaml file as True and fill the GROQ_API_KEY field with the api key of Groq.

Agent configuration

Currently, we support config agents by role-prompting. You can customize your agents by changing the role prompts in AgentRepo\agentBoard_v1.json. We plan to support more methods to customize agents (e.g., supporting RAG, or providing a unified wrapper for customized agents).

Launch

Execute the following command to launch the system:

python server.py

More Papers & Projects for LLM-based Multi-Agent Collaboration

If you’re interested in LLM-based multi-agent collaboration and want more papers & projects for reference, you may check out the corpus collected by us: