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Apache Camel is a project that helps you integrate various systems with data formats, components, and patterns. Learn what Camel is, why use it, and how to get started with its subprojects and resources.
- Overview
- Community
- Try it yourself
- Installation
- Example
- Use Open-Source Models as Backends
- Implemented Research Ideas from Other Works
- News
- Acknowledgement
The 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 coopera...
🐫 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, Discord or WeChat) in pushing the boundaries of building AI Societiy.
We provide a demo 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.
From PyPI
To install the base camel library, simply run pip install camel-ai Some features require extra dependencies. To use hugging-face agent, run pip install camel-ai[huggingface-agent] To enable RAG or use agent memory, run pip install camel-ai[tools] To install with all dependencies, run pip install camel-ai[all]
From Source
Install CAMEL from source with poetry (Recommended): Install CAMEL from source with conda and pip:
You can find a list of tasks for different set of assistant and user role pairs here
Run the role_playing.py script
First, 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):
For Windows Command Prompt:
For Windows PowerShell:
The 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 chose FastChat to 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 that it supports OpenAI-compatible APIs, especially the method openai.ChatCompletion.create.
Here are some instructions for enabling open-source backends, where we use the FastChat and a LLaMA2-based model (meta-llama/Llama-2-7b-chat-hf) in the example. Please install FastChat in advance following their installation guidance.
1.Before running CAMEL, we should firstly launch FastChat server following the guidance on https://github.com/lm-sys/FastChat/blob/main/docs/openai_api.md. The instructions summarized below should be kept running in separate processes:
1.After observing the controller successfully receiving the heart beat signal from the worker, the server should be ready for use at http://localhost:8000/v1.
2.Then we can try on running role_playing_with_open_source_model.py, where each agent in this example is initialized with specifying the model_path and server_url, similar to the example code below:
We 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, TaskPrioritizationAgent and BabyAGI from Nakajima et al.: Task-Driven Autonomous Agent. [Example]
•Released AI Society and Code dataset (April 2, 2023)
•Initial release of CAMEL python library (March 21, 2023)
Special thanks to Nomic AI for giving us extended access to their data set exploration tool (Atlas).
We would also like to thank Haya Hammoud for designing the initial logo of our project.
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