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Tutorial

Python Version RequirementsCAMEL-AI requires Python >=3.10 and <=3.14. Here’s how to check your version:
python3 --version
If you need to update Python, visit python.org/downloads
CAMEL-AI supports multiple installation methods to suit different development workflows. Choose the method that best fits your needs.
1

Install CAMEL-AI 🐪

  • Basic Installation: Install the core CAMEL library: 
    pip install camel-ai
  • Full Installation (Recommended): Install CAMEL with all features and dependencies: 
    pip install 'camel-ai[all]'
    Some features may not work without their required dependencies. Install camel-ai[all] to ensure all dependencies are available, or install specific extras based on the features you need.
  • Custom Installation: Available extras for specific use cases:
    • all: Includes all features below
    • model_platforms: OpenAI, Google, Mistral, Anthropic Claude, Cohere etc.
    • huggingface: Transformers, Diffusers, Accelerate, Datasets, PyTorch etc.
    • rag: Sentence Transformers, Qdrant, Milvus, TiDB, BM25, OceanBase, Weaviate, chroma etc.
    • storage: Neo4j, Redis, Azure Blob, Google Cloud Storage, AWS S3 etc, Pgvector.
    • web_tools: DuckDuckGo, Wikipedia, WolframAlpha, Google Maps, Weather API etc.
    • document_tools: PDF, Word, OpenAPI, BeautifulSoup, Unstructured etc.
    • media_tools: Image Processing, Audio Processing, YouTube Download, FFmpeg etc.
    • communication_tools: Slack, Discord, Telegram, GitHub, Reddit, Notion etc.
    • data_tools: Pandas, TextBlob, DataCommons, OpenBB, Stripe etc.
    • research_tools: arXiv, Google Scholar etc.
    • dev_tools: Docker, Jupyter, Tree-sitter, Code Interpreter etc.
    Multiple extras can be combined: 
    pip install 'camel-ai[rag,web_tools,document_tools]'  # Example: RAG system with web search and document processing
  • To verify that camel-ai is installed, run: 
    pip show camel-ai
Installation successful! You’re ready to create your first multi-agent system! 🎉

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Creating a CAMEL-AI Project

We recommend starting with a simple role-playing scenario to understand CAMEL’s multi-agent capabilities. Here’s how to get started:
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Set Up Your Project Structure

  • Create a new project directory: 
    mkdir my_camel_project
cd my_camel_project
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Configure Your Environment

  • Create a .env file with your API keys: 
    OPENAI_API_KEY=<your_openai_api_key>
OPENAI_API_BASE_URL=<your_openai_base_url>  # Optional: for proxy services
ANTHROPIC_API_KEY=<your_anthropic_api_key>
GOOGLE_API_KEY=<your_google_api_key>
  • Create a requirements.txt file: 
    camel-ai[all]
python-dotenv
3

Install Dependencies and Run

  • Install project dependencies: 
    pip install -r requirements.txt
  • Set up your environment variables by loading the .env file: 
    from dotenv import load_dotenv
load_dotenv()
  • Run your first multi-agent example: 
    python examples/role_playing.py
Want to see multi-agent collaboration at scale? Try running the workforce example:python examples/workforce/multiple_single_agents.py

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Alternative Installation Methods

CAMEL-AI offers multiple installation approaches for different development needs:

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From Docker

  • Containerized deployment with pre-configured environment
  • Detailed guidance available at CAMEL Docker Guide

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From Source with UV

  • Development installation with full source access
  • Supports Python 3.10, 3.11, 3.12, 3.13, 3.14
  • Includes development tools and testing capabilities
Python 3.13+ Compatibility Notes:
  • unstructured and pyobvector packages are not available on Python 3.13+
  • These packages require NumPy < 2.0, which is incompatible with Python 3.13+
  • If you need these features, use Python 3.10-3.12
  • All other features work normally on Python 3.13+
# Clone the repository
git clone https://github.com/camel-ai/camel.git
cd camel

# Install UV package manager
pip install uv

# Create virtual environment
uv venv .venv --python=3.10

# Activate environment (macOS/Linux)
source .venv/bin/activate
# For Windows: .venv\Scripts\activate

# Install CAMEL with all dependencies
uv pip install -e ".[all, dev, docs]"

Explore Development Setup

Learn about contributing to CAMEL-AI and development best practices

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Configuration Options

1

Set Default Model Configuration

Configure default model platform and type using environment variables:
export DEFAULT_MODEL_PLATFORM_TYPE=openai  # e.g., openai, anthropic, etc.
export DEFAULT_MODEL_TYPE=gpt-4o-mini      # e.g., gpt-3.5-turbo, gpt-4o-mini, etc.
By default, CAMEL uses:
ModelPlatformType.DEFAULT = "openai"
ModelType.DEFAULT = "gpt-4o-mini"
2

Set Up API Keys

For Bash shell (Linux, macOS, Git Bash on Windows):
export OPENAI_API_KEY=<insert your OpenAI API key>
export OPENAI_API_BASE_URL=<insert your OpenAI API BASE URL>  # Optional
For Windows Command Prompt:
set OPENAI_API_KEY=<insert your OpenAI API key>
set OPENAI_API_BASE_URL=<insert your OpenAI API BASE URL>
For Windows PowerShell:
$env:OPENAI_API_KEY="<insert your OpenAI API key>"
$env:OPENAI_API_BASE_URL="<insert your OpenAI API BASE URL>"
Using .env File (Recommended):
OPENAI_API_KEY=<fill your API KEY here>
ANTHROPIC_API_KEY=<fill your Anthropic API KEY here>
GOOGLE_API_KEY=<fill your Google API KEY here>
Load in Python:
from dotenv import load_dotenv
load_dotenv()  # Use load_dotenv(override=True) to overwrite existing variables

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Running Examples

After setting up your API keys, explore CAMEL’s capabilities: 
# Two agents role-playing and collaborating
python examples/ai_society/role_playing.py

# Agent utilizing code execution tools
python examples/toolkits/code_execution_toolkit.py

# Generating knowledge graphs with agents
python examples/knowledge_graph/knowledge_graph_agent_example.py

# Multiple agents collaborating on complex tasks
python examples/workforce/multiple_single_agents.py

# Creative image generation with agents
python examples/vision/image_crafting.py

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Testing Your Installation

Run the test suite to ensure everything is working: 
# Activate virtual environment first
source .venv/bin/activate  # macOS/Linux
# .venv\Scripts\activate   # Windows

# Run all tests
pytest --fast-test-mode test/

# Run specific test categories
pytest -v apps/
pytest -v examples/

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Next Steps

Build Your First Agent

Follow our quickstart guide to create role-playing agents and see CAMEL in action.

Explore Advanced Features & Cookbooks

Discover RAG systems, tool integration, and complex multi-agent cookbooks.

Join the Community

Connect with other developers, contribute, and share your CAMEL experiences.

API Documentation

Dive deep into CAMEL’s API and advanced configuration options.
For additional feature examples and use cases, explore the examples directory in the CAMEL repository.