Update README.md
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README.md
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README.md
@ -9,7 +9,35 @@ AgentCoord is an experimental open-source system to help general users design co
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alt="System Usage Video" width="800" border="5" /></a>
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alt="System Usage Video" width="800" border="5" /></a>
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## Installation
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## Installation
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### Installation
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### Install with Docker (Recommended)
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If you have installed [docker](https://www.docker.com/) and [docker-compose](https://docs.docker.com/compose/) on your machine, we recommend running AgentCoord in docker:
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Step 1: Clone our project and start the servers:
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```bash
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git clone https://github.com/AgentCoord/AgentCoord.git
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cd AgentCoord
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docker-compose up
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```
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Step 2: Open http://localhost:8080/ to use the system.
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### Install on your machine
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If you want to install and run AgentCoord on your machine without using docker:
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Step 1: Clone the project
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```bash
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git clone https://github.com/AgentCoord/AgentCoord.git
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cd AgentCoord
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```
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Step 2: Install required packages for the backend and frontend servers (check readme.md in ./frontend and ./backend folders)
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Step 3: Run the backend and frontend servers separately (check readme.md in ./frontend and ./backend folders).
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Step 4: Open http://localhost:8080/ to use the system.
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## Configuration
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```bash
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```bash
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git clone https://github.com/AgentCoord/AgentCoord.git
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git clone https://github.com/AgentCoord/AgentCoord.git
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cd AgentCoord
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cd AgentCoord
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@ -25,11 +53,6 @@ You can switch to a fast mode that uses the Mistral 8×7B model with hardware ac
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Currently, we support config agents by [role-prompting](https://arxiv.org/abs/2305.14688). 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).
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Currently, we support config agents by [role-prompting](https://arxiv.org/abs/2305.14688). 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).
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### Launch
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Execute the following command to launch the system:
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```bash
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python server.py
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```
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## More Papers & Projects for LLM-based Multi-Agent Collaboration
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## More Papers & Projects for LLM-based Multi-Agent Collaboration
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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:
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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:
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