Welcome to CAMEL’s documentation!

Finding the Scaling Law of Agents: The First and the Best Multi-Agent Framework.

CAMEL emerges as the earliest LLM-based multi-agent framework, and is now a generic framework to build and use LLM-based agents for real-world task solving. 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.

Main Documentation

Get Started

• Installation
• API Setup

Key Modules

• Models
• Message
• Memory
• Tools
• Prompt
• Task
• Loaders
• Storages
• Society
• Embeddings
• Retrievers
• Workforce

Cookbooks

• Basic Concepts
  • Creating Your First Agent
  • Creating Your First Agent Society
  • Message Cookbook
  • Prompting Cookbook
  • Model Speed Comparison Cookbook
• Advanced Features
  • Tools Cookbook
  • Using Tools from Composio
  • Agents with Human-in-loop and Tool Approval from HumanLayer
  • Memory Cookbook
  • RAG Cookbook
  • Graph RAG Cookbook
  • Track CAMEL Agents with AgentOps
  • Critic Agents and Tree Search
  • Embodied Agents
• Multi-agent Society
  • Develop Trading Bot with Role Playing
  • Create A Hackathon Judge Committee with Workforce
  • Task Generation Cookbook
• Model Training and Fine-tuning
  • Agenetic SFT Data generation with CAMEL and finetuning Mistral models with Unsloth
  • Data models
  • Agenetic Data generation with CAMEL and finetuning Qwen models with Unsloth
  • Data models
  • Agenetic SFT Data generation with CAMEL and finetuning Meta models with Unsloth
  • Data models
  • Data Gen with Real Function Calls and Hermes Format
  • Self-instruct Data Generation Using Qwen
  • CoT Data Generation and SFT Qwen With Unsloth
  • Config Access Token of Huggingface
  • Start model training
  • Agentic Data Generation, Evaluation & Filtering with Reward Models
  • 🚀 Data Generation
  • 📊 Point to content and generate data!
  • 🔄 Code for Conversion to Reward Model Format
  • ✨Test Reward Model
  • Data Model Generation and Structured Output with Qwen Model
• Applications
  • Role-Playing Scraper for Report & Knowledge Graph Generation
  • Dynamic Travel Planner Role-Playing: Multi-Agent System with Real-Time Insights Powered by Dappier
  • Customer Service Discord Bot with Agentic RAG
  • Customer Service Discord Bot Using SambaNova with Agentic RAG
  • Customer Service Discord Bot Using Local Models with Agentic RAG
• Data Processing and Analysis
  • Video Analysis
  • Create AI Agents that work with your PDFs using Chunkr & Mistral AI
  • ⚡️ Step-by-step Guide of Digesting PDFs with Chunkr
  • 3 ways to ingest data from websites with Firecrawl

API References

• camel

Indices and tables

• Index

• Module Index

• Search Page

Get Involved

We are always happy to work with friends to continuously move forward with our own competitive edges.

For Research Aficionados: New, rigorous and in-depth research takes time and resources. With access to almost unlimited usage of advanced GPU computes and a team of amazing researchers and engineers, we are bold enough to explore the frontier with patience. Whether you would like to join in our on-going project or have new idea to test, feel free to talk to us and see how we may work together.

For Coding Enthusiasts: Whether you want to introduce new features, enhance the infrastructure, improve documentation, asking issues, add more examples, implement state-of-the-art research ideas, or fix bugs, we appreciate each and every commit. Get started by checking out the Contributing Guidelines on GitHub.

For Interested Humans: Connect with us on Discord, WeChat, or Slack.