Package: camel-ai
CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model SocietyCommunity|Installation|Documentation|Examples|Paper|Citation|Contributing|CAMEL-AIOverviewThe rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework namedrole-playing. Our approach involves usinginception promptingto guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. Our contributions include introducing a novel communicative agent framework, offering a scalable approach for studying the cooperative behaviors and capabilities of multi-agent systems, and open-sourcing our library to support research on communicative agents and beyond. The GitHub repository of this project is made publicly available on:https://github.com/camel-ai/camel.Community🐫 CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.Join us (Slack,DiscordorWeChat) in pushing the boundaries of building AI Societiy.Try it yourselfWe provide ademo showcasing a conversation between two ChatGPT agents playing roles as a python programmer and a stock trader collaborating on developing a trading bot for stock market.DocumentationCAMEL package documentation pagesInstallationInstallCAMELfrom source with poetry (Recommended):# Clone github repo# For the latest code:gitclonehttps://github.com/camel-ai/camel.git# Or for the stable code:gitclone-bv0.1.0https://github.com/camel-ai/camel.git# Change directory into project directorycdcamel# Activate camel virtual environmentpoetryshell# Install camel from source# It takes about 90 seconds to resolve dependenciespoetryinstall# Or if you want to use "huggingface agent"poetryinstall-Ehuggingface-agent# (Optional)# do something with camel# Exit the virtual environmentexitInstallCAMELfrom source with conda and pip:# Create a conda virtual environmentcondacreate--namecamelpython=3.10# Activate camel conda environmentcondaactivatecamel# Clone github repogitclone-bv0.1.0https://github.com/camel-ai/camel.git# Change directory into project directorycdcamel# Install camel from sourcepipinstall-e.# Or if you want to use "huggingface agent"pipinstall-e.[huggingface-agent]# (Optional)ExampleYou can find a list of tasks for different set of assistant and user role pairshereRun therole_playing.pyscriptFirst, you need to add your OpenAI API key to system environment variables. The method to do this depends on your operating system and the shell you're using.For Bash shell (Linux, macOS, Git Bash on Windows):# Export your OpenAI API keyexportOPENAI_API_KEY=<insertyourOpenAIAPIkey>OPENAI_API_BASE_URL=<inertyourOpenAIAPIBASEURL>#(Should you utilize an OpenAI proxy service, kindly specify this)For Windows Command Prompt:REM export your OpenAI API key
set OPENAI_API_KEY=<insert your OpenAI API key>
set OPENAI_API_BASE_URL=<inert your OpenAI API BASE URL>  #(Should you utilize an OpenAI proxy service, kindly specify this)For Windows PowerShell:# Export your OpenAI API key$env:OPENAI_API_KEY="<insert your OpenAI API key>"$env:OPENAI_API_BASE_URL="<inert your OpenAI API BASE URL>"#(Should you utilize an OpenAI proxy service, kindly specify this)Replace<insert your OpenAI API key>with your actual OpenAI API key in each case. Make sure there are no spaces around the=sign.After setting the OpenAI API key, you can run the script:# You can change the role pair and initial prompt in role_playing.pypythonexamples/ai_society/role_playing.pyPlease note that the environment variable is session-specific. If you open a new terminal window or tab, you will need to set the API key again in that new session.Use Open-Source Models as BackendsThe basic workflow of using an open-sourced model as the backend is based on an external server running LLM inference service, e.g. during the development we choseFastChatto run the service.We do not fix the choice of server to decouple the implementation of any specific LLM inference server with CAMEL (indicating the server needs to be deployed by the user himself). But the server to be deployed must satisfy thatit supports OpenAI-compatible APIs, especially the methodopenai.ChatCompletion.create.Here are some instructions for enabling open-source backends, where we use theFastChatand a LLaMA2-based model (meta-llama/Llama-2-7b-chat-hf) in the example. Please install FastChat in advance following their installation guidance.Before running CAMEL, we should firstly launch FastChat server following the guidance onhttps://github.com/lm-sys/FastChat/blob/main/docs/openai_api.md. The instructions summarized below should be kept runningin separate processes:# Launch the controllerpython-mfastchat.serve.controller# Launch the model worker(s)python3-mfastchat.serve.model_worker--model-pathmeta-llama/Llama-2-7b-chat-hf# Launch the RESTful API serverpython3-mfastchat.serve.openai_api_server--hostlocalhost--port8000After observing the controller successfully receiving the heart beat signal from the worker, the server should be ready for use athttp://localhost:8000/v1.Then we can try on runningrole_playing_with_open_source_model.py, where each agent in this example is initialized with specifying themodel_pathandserver_url, similar to the example code below:system_message=# ...agent_kwargs=dict(model=model_type,model_config=OpenSourceConfig(model_path="meta-llama/Llama-2-7b-chat-hf",server_url="http://localhost:8000/v1",),)agent=ChatAgent(system_message,**agent_kwargs,)Supported ModelsLLaMA2-based modelsexample:meta-llama/Llama-2-7b-chat-hfVicuna-based modelsexample:lmsys/vicuna-7b-v1.5Data (Hosted on Hugging Face)DatasetChat formatInstruction formatChat format (translated)AI SocietyChat formatInstruction formatChat format (translated)CodeChat formatInstruction formatxMathChat formatxxPhysicsChat formatxxChemistryChat formatxxBiologyChat formatxxVisualizations of Instructions and TasksDatasetInstructionsTasksAI SocietyInstructionsTasksCodeInstructionsTasksMisalignmentInstructionsTasksImplemented Research Ideas from Other WorksWe implemented amazing research ideas from other works for you to build, compare and customize your agents. If you use any of these modules, please kindly cite the original works:TaskCreationAgent,TaskPrioritizationAgentandBabyAGIfromNakajima et al.:Task-Driven Autonomous Agent. [Example]NewsReleased AI Society and Code dataset (April 2, 2023)Initial release ofCAMELpython library (March 21, 2023)Citation@inproceedings{li2023camel,
  title={CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society},
  author={Li, Guohao and Hammoud, Hasan Abed Al Kader and Itani, Hani and Khizbullin, Dmitrii and Ghanem, Bernard},
  booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
  year={2023}
}AcknowledgementSpecial thanks toNomic AIfor giving us extended access to their data set exploration tool (Atlas).We would also like to thank Haya Hammoud for designing the logo of our project.LicenseThe intended purpose and licensing of CAMEL is solely for research use.The source code is licensed under Apache 2.0.The datasets are licensed under CC BY NC 4.0, which permits only non-commercial usage. It is advised that any models trained using the dataset should not be utilized for anything other than research purposes.Contributing to CAMEL 🐫We appreciate your interest in contributing to our open-source initiative. We provide a document ofcontributing guidelineswhich outlines the steps for contributing to CAMEL. Please refer to this guide to ensure smooth collaboration and successful contributions. 🤝🚀ContactFor more information please contactcamel.ai.team@gmail.com.