项目介绍
Agent 开发框架 · 2026-11-09 更新 · 本站尚未实测
CAMEL 是一个开源的多智能体框架,目标是研究和构建可在规模化条件下运行的多智能体系统。按仓库 README 的描述,它支持多种智能体、任务、提示词、模型和模拟环境,并提供数据生成、任务自动化与世界模拟等方向的示例。
需要注意:CAMEL 是 Python 框架与库,不是单个可以直接下载运行的工作流文件,也不是 MCP 服务器或 Skill。使用者通常需要在代码中调用其模块来搭建自己的智能体应用。
核心能力
点击能力名称查看输入、输出和原文依据。
- 智能体与智能体社会:提供 ChatAgent、角色扮演、Workforce 等组件,用于构建单智能体或协作式多智能体系统。
- 数据生成:README 中列出 CoT 数据生成、Self-Instruct、Source2Synth 等数据生成模块与示例。
- 工具调用:通过 Toolkits 接入搜索、浏览器、文档处理等能力;快速开始示例使用 DuckDuckGo 搜索工具。
- 模型接入:通过 ModelFactory 和 ModelType 指定模型平台与模型;示例使用 OpenAI GPT-4o。
- 记忆、RAG 与存储:模块表包含 Memory、Retrievers、Storage、Data Loaders 等。
- 评估与运行时:包含 Benchmarks、Interpreters、Runtime 和 Human-in-the-Loop 等模块。
实际应用场景
适用场景
- 研究多智能体协作、角色扮演与规模化智能体行为。
- 用多个模型或工具搭建任务自动化原型,例如检索增强问答、文档/视频分析。
- 生成合成数据,用于模型训练或评测流程。
- 作为二次开发基础,构建面向业务的多智能体应用。
对于仅想使用现成 Agent 产品、而不写 Python 代码的用户,CAMEL 的门槛较高;它更适合开发者与研究团队。
安装与接入
README 提供的 PyPI 安装方式为:
pip install camel-ai
若需要网页工具,README 给出:
pip install 'camel-ai[web_tools]'
快速开始示例需要设置 OpenAI API Key:
export OPENAI_API_KEY='your_openai_api_key'
README 还说明可以复制 .env.example 为 .env 并填入密钥。随后在 Python 中创建 ChatAgent 并调用 step。具体代码与更多安装选项请以官方文档为准。
需要注意,README 中的快速开始是示例流程,不代表所有模型、工具或平台都已本地或国内可直接使用;网络、API 可用性与模型支持范围需自行核验。
使用条件与限制
- 是否需要部署
- 需自行准备运行环境,具体要求见正文
- 是否需要注册
- 账号和认证要求见正文;未明确说明的项目仍待核验
- 是否需要 API Key
- 待核验
- 费用与额度
- 费用边界见正文,项目许可不代表模型或托管服务免费
- 所需权限
- 待核验
- 许可证与服务条款
- 待核验
权限费用与限制
- 模型调用通常需要对应平台的 API Key;费用由模型服务商决定,README 未提供价格信息。
- 工具调用可能产生第三方服务请求,例如搜索、网页抓取或文档解析;相关权限、配额与费用须向对应服务商核验。
- 框架本身不承诺免费使用所有模型或托管服务。
- README 未给出 Windows、macOS、Linux 的明确系统支持矩阵,相关信息待核验。
- 本项目为开发框架,不提供开箱即用的托管 Agent 服务。
国内使用情况
网友核验 用户经验分享
与站长实测独立,不代表官方认证或本站已实测。
最近核验:暂无有效核验。参与人数按当前项目有效身份去重;不同核验项分别统计,不合并成用户总结果。仅统计审核通过且未过期的记录。
分项统计、有效期与样本量
| 核验项目 | 有效人数 | 成功 / 部分 / 失败 / 无法判断 | 成功率 | 最近核验 / 有效期 |
|---|---|---|---|---|
| 官方网站访问 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 7 天 |
| GitHub 仓库访问 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 7 天 |
| 安装与运行 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 官方服务国内连接 / MCP 连接 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 国内网络情况 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 7 天 |
| 国内模型兼容性 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 自定义 API | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 海外服务依赖 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 海外账号要求 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 中文界面 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 客户端兼容性 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
| 账号及费用信息 | 0 | 0 / 0 / 0 / 0 | 样本不足 | 暂无 / 30 天 |
成功率 = 成功 ÷(成功 + 部分成功 + 失败);无法判断不计入分母。至少 5 份可判断结果才显示成功率。账号、费用、海外依赖与语言等事实项,成功表示核查结论与资料吻合,具体观察另行统计;不表示免费或没有海外依赖。不同网络、客户端和版本的结果不能直接等同。
最近有效核验
暂无审核通过且未过期的网友核验。欢迎提交真实使用记录。
查看全部有效核验 →国内实测状态:国内可用性待核验。协议兼容和官方资料说明不等于国内网络可用。
- 官方网站访问
- 尚未实测 待核验
- GitHub 仓库访问
- 尚未实测 待核验
- 官方服务国内连接
- 尚未实测 待核验
- 国内网络情况
- 尚未实测 待核验
- 国内模型兼容性
- 尚未实测 待核验
- 自定义 API
- 尚未实测 待核验
- 海外服务依赖
- 尚未实测 待核验
- 海外账号要求
- 尚未实测 待核验
- 中文界面
- 尚未实测 待核验
- 国内最后核验时间
- 尚未实测
许可与国内使用
仓库包含 Apache License 2.0 许可证文件,版权声明为 2023 CAMEL-AI.org。该许可适用于仓库中的代码,但不自动覆盖第三方模型、API、数据集或托管服务;这些服务有各自的条款与费用。
国内使用方面,README 未对国内网络环境、国内模型平台兼容性或服务部署地域作出明确说明,相关信息待核验。公开仓库不等于所有依赖服务均可在中国大陆直接访问或免费使用。若计划用于生产,应先核查模型服务商条款、数据跨境与合规要求。
项目资料与来源
字段依据与待核验事项
access:来源确认 · pip install camel-ai
project_type:来源确认 · we implement and support various types of agents, tasks, prompts, models, and simulated environments.
原始 README(折叠技术参考)
<div align="center">
<a href="https://www.camel-ai.org/">
<img src="docs/images/banner.png" alt="Banner">
</a>
</div>
</br>
<div align="center">
[![Documentation][docs-image]][docs-url]
[![Discord][discord-image]][discord-url]
[![X][x-image]][x-url]
[![Reddit][reddit-image]][reddit-url]
[![Wechat][wechat-image]][wechat-url]
[![Hugging Face][huggingface-image]][huggingface-url]
[![Star][star-image]][star-url]
[![Package License][package-license-image]][package-license-url]
[![PyPI Download][package-download-image]][package-download-url]
[![][join-us-image]][join-us]
<a href="https://trendshift.io/repositories/649" target="_blank"><img src="https://trendshift.io/api/badge/repositories/649" alt="camel-ai/camel | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
[English](README.md) |
[简体中文](README.zh.md) |
[日本語](README.ja.md)
</div>
<hr>
<div align="center">
<h4 align="center">
[Community](https://github.com/camel-ai/camel#community) |
[Installation](https://github.com/camel-ai/camel#installation) |
[Examples](https://github.com/camel-ai/camel/tree/HEAD/examples) |
[Paper](https://arxiv.org/abs/2303.17760) |
[Citation](https://github.com/camel-ai/camel#citation) |
[Contributing](https://github.com/camel-ai/camel#contributing-to-camel-) |
[CAMEL-AI](https://www.camel-ai.org/)
</h4>
<p style="line-height: 1.5; text-align: center;"> 🐫 CAMEL is an open-source community dedicated to finding the scaling laws of 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.</p>
<br>
Join us ([*Discord*](https://discord.camel-ai.org/) or [*WeChat*](https://ghli.org/camel/wechat.png)) in pushing the boundaries of finding the scaling laws of agents.
🌟 Star CAMEL on GitHub and be instantly notified of new releases.
</div>
<div align="center">
<img src="docs/images/stars.gif" alt="Star">
</a>
</div>
<br>
[![][image-join-us]][join-us]
<details>
<summary><kbd>Table of contents</kbd></summary>
<br/>
- [CAMEL Framework Design Principles](#camel-framework-design-principles)
- [Why Use CAMEL for Your Research?](#why-use-camel-for-your-research)
- [What Can You Build With CAMEL?](#what-can-you-build-with-camel)
- [Data Generation](#1-data-generation)
- [Task Automation](#2-task-automation)
- [World Simulation](#3-world-simulation)
- [Quick Start](#quick-start)
- [Starting with ChatAgent](#starting-with-chatagent)
- [Seeking Help](#seeking-help)
- [Tech Stack](#tech-stack)
- [Research](#research)
- [Synthetic Datasets](#synthetic-datasets)
- [Cookbooks (Usecases)](#cookbooks-usecases)
- [Basic Concepts](#1-basic-concepts)
- [Advanced Features](#2-advanced-features)
- [Model Training & Data Generation](#3-model-training--data-generation)
- [Multi-Agent Systems & Applications](#4-multi-agent-systems--applications)
- [Data Processing](#5-data-processing)
- [Real-World Usecases](#real-world-usecases)
- [🧱 Built with CAMEL (Real-world Producs & Research)](#-built-with-camel-real-world-producs--research)
- [Research Projects](#research-projects)
- [Product Projects](#product-projects)
- [🗓️ Events](#️-events)
- [Contributing to CAMEL](#contributing-to-camel)
- [Community & Contact](#community--contact)
- [Citation](#citation)
- [Acknowledgment](#acknowledgment)
- [License](#license)
####
<br/>
</details>
## CAMEL Framework Design Principles
<h3>🧬 Evolvability</h3 >
The framework enables multi-agent systems to continuously evolve by generating data and interacting with environments. This evolution can be driven by reinforcement learning with verifiable rewards or supervised learning.
<h3>📈 Scalability</h3>
The framework is designed to support systems with millions of agents, ensuring efficient coordination, communication, and resource management at scale.
<h3>💾 Statefulness</h3>
Agents maintain stateful memory, enabling them to perform multi-step interactions with environments and efficiently tackle sophisticated tasks.
<h3>📖 Code-as-Prompt</h3>
Every line of code and comment serves as a prompt for agents. Code should be written clearly and readably, ensuring both humans and agents can interpret it effectively.
<br>
## Why Use CAMEL for Your Research?
We are a community-driven research collective comprising over 100 researchers dedicated to advancing frontier research in Multi-Agent Systems. Researchers worldwide choose CAMEL for their studies based on the following reasons.
<table style="width: 100%;">
<tr>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Large-Scale Agent System</td>
<td align="left">Simulate up to 1M agents to study emergent behaviors and scaling laws in complex, multi-agent environments.</td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Dynamic Communication</td>
<td align="left">Enable real-time interactions among agents, fostering seamless collaboration for tackling intricate tasks.</td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Stateful Memory</td>
<td align="left">Equip agents with the ability to retain and leverage historical context, improving decision-making over extended interactions.</td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Support for Multiple Benchmarks</td>
<td align="left">Utilize standardized benchmarks to rigorously evaluate agent performance, ensuring reproducibility and reliable comparisons.</td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Support for Different Agent Types</td>
<td align="left">Work with a variety of agent roles, tasks, models, and environments, supporting interdisciplinary experiments and diverse research applications.</td>
</tr>
<tr>
<td align="left">✅</td>
<td align="left" style="font-weight: bold;">Data Generation and Tool Integration</td>
<td align="left">Automate the creation of large-scale, structured datasets while seamlessly integrating with multiple tools, streamlining synthetic data generation and research workflows.</td>
</tr>
</table>
<br>
## What Can You Build With CAMEL?
### 1. Data Generation
<div align="center">
<a href="https://github.com/camel-ai/camel/blob/master/camel/datagen/cot_datagen.py">
<img src="docs/images/cot.png" alt="CoT Data Generation">
</a>
</div>
<div align="center">
<a href="https://github.com/camel-ai/camel/tree/master/camel/datagen/self_instruct">
<img src="docs/images/self_instruct.png" alt="Self-Instruct Data Generation">
</a>
</div>
<div align="center">
<a href="https://github.com/camel-ai/camel/tree/master/camel/datagen/source2synth">
<img src="docs/images/source2synth.png" alt="Source2Synth Data Generation">
</a>
</div>
<div align="center">
<a href="https://github.com/camel-ai/camel/blob/master/camel/datagen/self_improving_cot.py">
<img src="docs/images/self_improving.png" alt="Self-Improving Data Generation">
</a>
</div>
### 2. Task Automation
<div align="center">
<a href="https://github.com/camel-ai/camel/blob/master/camel/societies/role_playing.py">
<img src="docs/images/role_playing.png" alt="Role Playing">
</a>
</div>
<div align="center">
<a href="https://github.com/camel-ai/camel/tree/master/camel/societies/workforce">
<img src="docs/images/workforce.png" alt="Workforce">
</a>
</div>
<div align="center">
<a href="https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_rag">
<img src="docs/images/rag_pipeline.png" alt="RAG Pipeline">
</a>
</div>
### 3. World Simulation
<div align="center">
<a href="https://github.com/camel-ai/oasis">
<img src="docs/images/oasis_case.png" alt="Oasis Case">
</a>
</div>
<br>
## Quick Start
Installing CAMEL is a breeze thanks to its availability on PyPI. Simply open your terminal and run:
```bash
pip install camel-ai
```
### Starting with ChatAgent
This example demonstrates how to create a `ChatAgent` using the CAMEL framework and perform a search query using DuckDuckGo.
1. **Install the tools package:**
```bash
pip install 'camel-ai[web_tools]'
```
2. **Set up your OpenAI API key:**
```bash
export OPENAI_API_KEY='your_openai_api_key'
```
Alternatively, use a `.env` file:
```bash
cp .env.example .env
# then edit .env and add your keys
```
3. **Run the following Python code:**
```python
from camel.models import ModelFactory
from camel.types import ModelPlatformType, ModelType
from camel.agents import ChatAgent
from camel.toolkits import SearchToolkit
model = ModelFactory.create(
model_platform=ModelPlatformType.OPENAI,
model_type=ModelType.GPT_4O,
model_config_dict={"temperature": 0.0},
)
search_tool = SearchToolkit().search_duckduckgo
agent = ChatAgent(model=model, tools=[search_tool])
response_1 = agent.step("What is CAMEL-AI?")
print(response_1.msgs[0].content)
# CAMEL-AI is the first LLM (Large Language Model) multi-agent framework
# and an open-source community focused on finding the scaling laws of agents.
# ...
response_2 = agent.step("What is the Github link to CAMEL framework?")
print(response_2.msgs[0].content)
# The GitHub link to the CAMEL framework is
# [https://github.com/camel-ai/camel](https://github.com/camel-ai/camel).
```
4. **(Optional) Enable model request/response logs:**
```bash
export CAMEL_MODEL_LOG_ENABLED=true
export CAMEL_MODEL_LOG_MODEL_CONFIG_ENABLED=true
export CAMEL_LOG_DIR=camel_logs
```
- `CAMEL_MODEL_LOG_ENABLED`: Enables request/response JSON logs.
- `CAMEL_MODEL_LOG_MODEL_CONFIG_ENABLED`: Controls whether
`model_config_dict` is logged under `request.model_config_dict`.
When unset, it defaults to the same value as
`CAMEL_MODEL_LOG_ENABLED`.
- `CAMEL_LOG_DIR`: Directory for generated log files
(default: `camel_logs`).
- Logs are written as UTF-8 JSON with multilingual text preserved
(for example Chinese, Japanese, Arabic) without Unicode escape noise.
For more detailed instructions and additional configuration options, check out the [installation section](https://github.com/camel-ai/camel/blob/master/docs/get_started/installation.md).
After running, you can explore our CAMEL Tech Stack and Cookbooks at [docs.camel-ai.org](https://docs.camel-ai.org) to build powerful multi-agent systems.
We provide a [](https://colab.research.google.com/drive/1AzP33O8rnMW__7ocWJhVBXjKziJXPtim?usp=sharing) 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.
Explore different types of agents, their roles, and their applications.
- **[Creating Your First Agent](https://docs.camel-ai.org/cookbooks/basic_concepts/create_your_first_agent)**
- **[Creating Your First Agent Society](https://docs.camel-ai.org/cookbooks/basic_concepts/create_your_first_agents_society)**
- **[Critic Agents](https://docs.camel-ai.org/cookbooks/advanced_features/critic_agents_and_tree_search)**
### Seeking Help
Please reach out to us on [CAMEL discord](https://discord.camel-ai.org/) if you encounter any issue set up CAMEL.
<br>
## Tech Stack
<div align="center">
<a href="https://docs.camel-ai.org">
<img src="https://camel-ai.github.io/camel_asset/graphics/techstack.png" alt="TechStack">
</a>
</div>
### Key Modules
Core components and utilities to build, operate, and enhance CAMEL-AI agents and societies.
| Module | Description |
|:---|:---|
| **[Agents](https://docs.camel-ai.org/key_modules/agents)** | Core agent architectures and behaviors for autonomous operation. |
| **[Agent Societies](https://docs.camel-ai.org/key_modules/society)** | Components for building and managing multi-agent systems and collaboration. |
| **[Data Generation](https://docs.camel-ai.org/key_modules/datagen)** | Tools and methods for synthetic data creation and augmentation. |
| **[Models](https://docs.camel-ai.org/key_modules/models)** | Model architectures and customization options for agent intelligence. |
| **[Tools](https://docs.camel-ai.org/key_modules/tools)** | Tools integration for specialized agent tasks. |
| **[Memory](https://docs.camel-ai.org/key_modules/memory)** | Memory storage and retrieval mechanisms for agent state management. |
| **[Storage](https://docs.camel-ai.org/key_modules/storages)** | Persistent storage solutions for agent data and states. |
| **[Benchmarks](https://github.com/camel-ai/camel/tree/master/camel/benchmarks)** | Performance evaluation and testing frameworks. |
| **[Interpreters](https://docs.camel-ai.org/key_modules/interpreters)** | Code and command interpretation capabilities. |
| **[Data Loaders](https://docs.camel-ai.org/key_modules/loaders)** | Data ingestion and preprocessing tools. |
| **[Retrievers](https://docs.camel-ai.org/key_modules/retrievers)** | Knowledge retrieval and RAG components. |
| **[Runtime](https://github.com/camel-ai/camel/tree/master/camel/runtime)** | Execution environment and process management. |
| **[Human-in-the-Loop](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_human_in_loop_and_tool_approval)** | Interactive components for human oversight and intervention. |
---
## Research
We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks.
**Explore our research projects:**
<div align="center">
<a href="https://github.com/camel-ai/owl">
<img src="docs/images/owl.png" alt="OWL">
</a>
</div>
<div align="center">
<a href="https://oasis.camel-ai.org/">
<img src="docs/images/oasis.png" alt="OASIS">
</a>
</div>
<div align="center">
<a href="https://crab.camel-ai.org/">
<img src="docs/images/crab.png" alt="CRAB">
</a>
</div>
<div align="center">
<a href="https://github.com/camel-ai/loong">
<img src="docs/images/loong.png" alt="Loong">
</a>
</div>
<div align="center">
<a href="https://agent-trust.camel-ai.org/">
<img src="docs/images/agent_trust.png" alt="Agent Trust">
</a>
</div>
<div align="center">
<a href="https://emos-project.github.io/">
<img src="docs/images/emos.png" alt="Emos">
</a>
</div>
>### Research with US
>
>We warmly invite you to use CAMEL for your impactful research.
>
> Rigorous research takes time and resources. We are a community-driven research collective with 100+ researchers exploring the frontier research of Multi-agent Systems. Join our ongoing projects or test new ideas with us, [reach out via email](mailto:camel-ai@eigent.ai) for more information.
>
><div align="center">
> <img src="docs/images/partners.png" alt="Partners">
></div>
<br>
## Synthetic Datasets
### 1. Utilize Various LLMs as Backends
For more details, please see our [`Models Documentation`](https://docs.camel-ai.org/key_modules/models#).
> **Data (Hosted on Hugging Face)**
| Dataset | Chat format | Instruction format | Chat format (translated) |
|----------------|-----------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------|
| **AI Society** | [Chat format](https://huggingface.co/datasets/camel-ai/ai_society/blob/main/ai_society_chat.tar.gz) | [Instruction format](https://huggingface.co/datasets/camel-ai/ai_society/blob/main/ai_society_instructions.json) | [Chat format (translated)](https://huggingface.co/datasets/camel-ai/ai_society_translated) |
| **Code** | [Chat format](https://huggingface.co/datasets/camel-ai/code/blob/main/code_chat.tar.gz) | [Instruction format](https://huggingface.co/datasets/camel-ai/code/blob/main/code_instructions.json) | x |
| **Math** | [Chat format](https://huggingface.co/datasets/camel-ai/math) | x | x |
| **Physics** | [Chat format](https://huggingface.co/datasets/camel-ai/physics) | x | x |
| **Chemistry** | [Chat format](https://huggingface.co/datasets/camel-ai/chemistry) | x | x |
| **Biology** | [Chat format](https://huggingface.co/datasets/camel-ai/biology) | x | x |
### 2. Visualizations of Instructions and Tasks
| Dataset | Instructions | Tasks |
|------------------|----------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|
| **AI Society** | [Instructions](https://atlas.nomic.ai/map/3a559a06-87d0-4476-a879-962656242452/db961915-b254-48e8-8e5c-917f827b74c6) | [Tasks](https://atlas.nomic.ai/map/cb96f41b-a6fd-4fe4-ac40-08e101714483/ae06156c-a572-46e9-8345-ebe18586d02b) |
| **Code** | [Instructions](https://atlas.nomic.ai/map/902d6ccb-0bbb-4294-83a8-1c7d2dae03c8/ace2e146-e49f-41db-a1f4-25a2c4be2457) | [Tasks](https://atlas.nomic.ai/map/efc38617-9180-490a-8630-43a05b35d22d/2576addf-a133-45d5-89a9-6b067b6652dd) |
| **Misalignment** | [Instructions](https://atlas.nomic.ai/map/5c491035-a26e-4a05-9593-82ffb2c3ab40/2bd98896-894e-4807-9ed8-a203ccb14d5e) | [Tasks](https://atlas.nomic.ai/map/abc357dd-9c04-4913-9541-63e259d7ac1f/825139a4-af66-427c-9d0e-f36b5492ab3f) |
<br>
## Cookbooks (Usecases)
Practical guides and tutorials for implementing specific functionalities in CAMEL-AI agents and societies.
### 1. Basic Concepts
| Cookbook | Description |
|:---|:---|
| **[Creating Your First Agent](https://docs.camel-ai.org/cookbooks/basic_concepts/create_your_first_agent)** | A step-by-step guide to building your first agent. |
| **[Creating Your First Agent Society](https://docs.camel-ai.org/cookbooks/basic_concepts/create_your_first_agents_society)** | Learn to build a collaborative society of agents. |
| **[Message Cookbook](https://docs.camel-ai.org/cookbooks/basic_concepts/agents_message)** | Best practices for message handling in agents. |
### 2. Advanced Features
| Cookbook | Description |
|:---|:---|
| **[Tools Cookbook](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_tools)** | Integrating tools for enhanced functionality. |
| **[Memory Cookbook](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_memory)** | Implementing memory systems in agents. |
| **[RAG Cookbook](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_rag)** | Recipes for Retrieval-Augmented Generation. |
| **[Graph RAG Cookbook](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_graph_rag)** | Leveraging knowledge graphs with RAG. |
| **[Track CAMEL Agents with AgentOps](https://docs.camel-ai.org/cookbooks/advanced_features/agents_tracking)** | Tools for tracking and managing agents in operations. |
### 3. Model Training & Data Generation
| Cookbook | Description |
|:---|:---|
| **[Data Generation with CAMEL and Finetuning with Unsloth](https://docs.camel-ai.org/cookbooks/data_generation/sft_data_generation_and_unsloth_finetuning_Qwen2_5_7B)** | Learn how to generate data with CAMEL and fine-tune models effectively with Unsloth. |
| **[Data Gen with Real Function Calls and Hermes Format](https://docs.camel-ai.org/cookbooks/data_generation/data_gen_with_real_function_calls_and_hermes_format)** | Explore how to generate data with real function calls and the Hermes format. |
| **[CoT Data Generation and Upload Data to Huggingface](https://docs.camel-ai.org/cookbooks/data_generation/distill_math_reasoning_data_from_deepseek_r1)** | Uncover how to generate CoT data with CAMEL and seamlessly upload it to Huggingface. |
| **[CoT Data Generation and SFT Qwen with Unsolth](https://docs.camel-ai.org/cookbooks/data_generation/cot_data_gen_sft_qwen_unsolth_upload_huggingface)** | Discover how to generate CoT data using CAMEL and SFT Qwen with Unsolth, and seamlessly upload your data and model to Huggingface. |
### 4. Multi-Agent Systems & Applications
| Cookbook | Description |
|:---|:---|
| **[Role-Playing Scraper for Report & Knowledge Graph Generation](https://docs.camel-ai.org/cookbooks/applications/roleplaying_scraper)** | Create role-playing agents for data scraping and reporting. |
| **[Create A Hackathon Judge Committee with Workforce](https://docs.camel-ai.org/cookbooks/multi_agent_society/workforce_judge_committee)** | Building a team of agents for collaborative judging. |
| **[Dynamic Knowledge Graph Role-Playing: Multi-Agent System with dynamic, temporally-aware knowledge graphs](https://docs.camel-ai.org/cookbooks/advanced_features/agents_with_dkg)** | Builds dynamic, temporally-aware knowledge graphs for financial applications using a multi-agent system. It processes financial reports, news articles, and research papers to help traders analyze data, identify relationships, and uncover market insights. The system also utilizes diverse and optional element node deduplication techniques to ensure data integrity and optimize graph structure for financial decision-making. |
| **[Customer Service Discord Bot with Agentic RAG](https://docs.camel-ai.org/cookbooks/applications/customer_service_Discord_bot_using_SambaNova_with_agentic_RAG)** | Learn how to build a robust customer service bot for Discord using Agentic RAG. |
| **[Customer Service Discord Bot with Local Model](https://docs.camel-ai.org/cookbooks/applications/customer_service_Discord_bot_using_local_model_with_agentic_RAG)** | Learn how to build a robust customer service bot for Discord using Agentic RAG which supports local deployment. |
### 5. Data Processing
| Cookbook | Description |
|:---|:---|
| **[Video Analysis](https://docs.camel-ai.org/cookbooks/data_processing/video_analysis)** | Techniques for agents in video data analysis. |
| **[3 Ways to Ingest Data from Websites with Firecrawl](https://docs.camel-ai.org/cookbooks/data_processing/ingest_data_from_websites_with_Firecrawl)** | Explore three methods for extracting and processing data from websites using Firecrawl. |
| **[Create AI Agents that work with your PDFs](https://docs.camel-ai.org/cookbooks/data_processing/agent_with_chunkr_for_pdf_parsing)** | Learn how to create AI agents that work with your PDFs using Chunkr and Mistral AI. |
<br>
## Real-World Usecases
Real-world usecases demonstrating how CAMEL’s multi-agent framework enables real business value across infrastructure automation, productivity workflows, retrieval-augmented conversations, intelligent document/video analysis, and collaborative research.
### 1 Infrastructure Automation
| Usecase | Description |
| :----------------------------------------------------------- | :----------------------------------------------------------- |
| **[ACI MCP](https://github.com/camel-ai/camel/tree/master/examples/usecases/aci_mcp)** | Real-world usecases demonstrating how CAMEL’s multi-agent framework enables real business value across infrastructure automation, productivity workflows, retrieval-augmented conversations, intelligent document/video analysis, and collaborative research. |
| **[Cloudflare MCP CAMEL](https://github.com/camel-ai/camel/tree/master/examples/usecases/cloudfare_mcp_camel)** | Intelligent agents manage Cloudflare resources dynamically, enabling scalable and efficient cloud security and performance tuning. |
### 2 Productivity & Business Workflows
| Usecase | Description |
| :----------------------------------------------------------- | :----------------------------------------------------------- |
| **[Airbnb MCP](https://github.com/camel-ai/camel/tree/master/examples/usecases/airbnb_mcp)** | Coordinate agents to optimize and manage Airbnb listings and host operations. |
| **[PPTX Toolkit Usecase](https://github.com/camel-ai/camel/tree/master/examples/usecases/pptx_toolkit_usecase)** | Analyze PowerPoint documents and extract structured insights through multi-agent collaboration. |
### 3 Retrieval-Augmented Multi-Agent Chat
| Usecase | Description |
| :----------------------------------------------------------- | :----------------------------------------------------------- |
| **[Chat with GitHub](https://github.com/camel-ai/camel/tree/master/examples/usecases/chat_with_github)** | Query and understand GitHub codebases through CAMEL agents leveraging RAG-style workflows, accelerating developer onboarding and codebase navigation. |
| **[Chat with YouTube](https://github.com/camel-ai/camel/tree/master/examples/usecases/chat_with_youtube)** | Conversational agents extract and summarize video transcripts, enabling faster content understanding and repurposing. |
### 4 Video & Document Intelligence
| Usecase | Description |
| :----------------------------------------------------------- | :----------------------------------------------------------- |
| **[YouTube OCR](https://github.com/camel-ai/camel/tree/master/examples/usecases/youtube_ocr)** | Agents perform OCR on video screenshots to summarize visual content, supporting media monitoring and compliance. |
| **[Mistral OCR](https://github.com/camel-ai/camel/tree/master/examples/usecases/mistral_OCR)** | CAMEL agents use OCR with Mistral to analyze documents, reducing manual effort in document understanding workflows. |
### 5 Research & Collaboration
| Usecase | Description |
| :----------------------------------------------------------- | :----------------------------------------------------------- |
| **[Multi-Agent Research Assistant](https://github.com/camel-ai/camel/tree/master/examples/usecases/multi_agent_research_assistant)** | Simulates a team of research agents collaborating on literature review, improving efficiency in exploratory analysis and reporting. |
<br>
## 🧱 Built with CAMEL (Real-world Producs & Research)
<div align="left">
<a href="https://www.camel-ai.org/">
<img src="docs/images/built_with_CAMEL.png" alt="Built with CAMEL" height="40px">
</a>
</div>
### Research Projects
| Name | Description |
|:---|:---|
| **[ChatDev](https://github.com/OpenBMB/ChatDev/tree/main/camel)** | Communicative Agents for software Development |
| **[Paper2Poster](https://github.com/Paper2Poster/Paper2Poster)** | Multimodal poster automation from scientific papers |
| **[Paper2Video](https://github.com/showlab/Paper2Video)** | Automatic video generation from scientific papers |
### Product Projects
| Name | Description |
|:---|:---|
| **[Eigent](https://www.eigent.ai/)** | The World First Multi-agent Workforce |
## 🗓️ Events
We are actively involved in community events including:
- 🎙️ **Community Meetings** — Weekly virtual syncs with the CAMEL team
- 🏆 **Competitions** — Hackathons, Bounty Tasks and coding challenges hosted by CAMEL
- 🤝 **Volunteer Activities** — Contributions, documentation drives, and mentorship
- 🌍 **Ambassador Programs** — Represent CAMEL in your university or local tech groups
> Want to host or participate in a CAMEL event? Join our [Discord](https://discord.com/invite/CNcNpquyDc) or want to be part of [Ambassador Program](https://www.camel-ai.org/ambassador).
## Contributing to CAMEL
> For those who'd like to contribute code, we appreciate your interest in contributing to our open-source initiative. Please take a moment to review our [contributing guidelines](https://github.com/camel-ai/camel/blob/master/CONTRIBUTING.md) to get started on a smooth collaboration journey.🚀
>
> We also welcome you to help CAMEL grow by sharing it on social media, at events, or during conferences. Your support makes a big difference!
## Contributors
<a href="https://github.com/camel-ai/camel/graphs/contributors">
<img src="https://contrib.rocks/image?repo=camel-ai/camel" />
</a>
Made with [contrib.rocks](https://contrib.rocks).
<br>
## Acknowledgment
Special thanks to [Nomic AI](https://home.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.
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` and `TaskPrioritizationAgent` from *Nakajima et al.*: [Task-Driven Autonomous Agent](https://yoheinakajima.com/task-driven-autonomous-agent-utilizing-gpt-4-pinecone-and-langchain-for-diverse-applications/).
- `PersonaHub` from *Tao Ge et al.*: [Scaling Synthetic Data Creation with 1,000,000,000 Personas](https://arxiv.org/pdf/2406.20094). [[Example](https://github.com/camel-ai/camel/blob/master/examples/personas/personas_generation.py)]
- `Self-Instruct` from *Yizhong Wang et al.*: [SELF-INSTRUCT: Aligning Language Models with Self-Generated Instructions](https://arxiv.org/pdf/2212.10560). [[Example](https://github.com/camel-ai/camel/blob/master/examples/datagen/self_instruct/self_instruct.py)]
## License
The source code is licensed under Apache 2.0.
## 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}
}
```
Here is an example of how to cite our work:
```
We use the CAMEL framework \cite{li2023camel} to develop the agents used in our experiments.
```
## Community & Contact
For more information please contact camel-ai@eigent.ai
- **GitHub Issues:** Report bugs, request features, and track development. [Submit an issue](https://github.com/camel-ai/camel/issues)
- **Discord:** Get real-time support, chat with the community, and stay updated. [Join us](https://discord.camel-ai.org/)
- **X (Twitter):** Follow for updates, AI insights, and key announcements. [Follow us](https://x.com/CamelAIOrg)
- **Ambassador Project:** Advocate for CAMEL-AI, host events, and contribute content. [Learn more](https://www.camel-ai.org/community)
- **WeChat Community:** Scan the QR code below to join our WeChat community.
<div align="center">
<img src="misc/wechat.jpeg" alt="WeChat QR Code" width="200">
</div>
<br>
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历史前置条件说明(补充参考)
Python 环境与 pip;调用模型需相应模型平台的 API Key(README 示例为 OPENAI_API_KEY);工具调用依赖第三方服务;费用由模型与服务商决定;Windows/macOS/Linux 支持矩阵待核验;国内网络与模型兼容性待核验。
项目来源与清单版权许可
https://github.com/camel-ai/camel
整理来源:https://github.com/slavakurilyak/awesome-ai-agents
清单版权与许可:
MIT License
Copyright (c) 2024 Slava Kurilyak
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.