Install the core CAMEL library:

    ```shell
    pip install camel-ai
    ```

  - **Full Installation (Recommended):**

    Install CAMEL with all features and dependencies:

    ```shell
    pip install 'camel-ai[all]'
    ```

    <Note>
      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.
    </Note>

  - **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:
    ```shell
    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:
    ```shell
    pip show camel-ai
    ```

  <Check>Installation successful! You're ready to create your first multi-agent system! 🎉</Check>
</Step>

- Set up your environment variables by loading the `.env` file:
  ```python
  from dotenv import load_dotenv
  load_dotenv()
  ```

- Run your first multi-agent example:
  ```bash
  python examples/role_playing.py
  ```

# 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]"

By default, CAMEL uses:
```bash
ModelPlatformType.DEFAULT = "openai"
ModelType.DEFAULT = "gpt-4o-mini"
```

**For Windows Command Prompt:**
```cmd
set OPENAI_API_KEY=<insert your OpenAI API key>
set OPENAI_API_BASE_URL=<insert your OpenAI API BASE URL>
```

**For Windows PowerShell:**
```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):**
```bash
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:
```python
from dotenv import load_dotenv
load_dotenv()  # Use load_dotenv(override=True) to overwrite existing variables
```

# 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

# 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/