### Run MoA Docker Container

Source: https://github.com/ai-mickyj/mixture-of-agents/blob/main/README.md

This command runs the previously built Docker image in an interactive session. It mounts the current directory into the container and passes the API keys from the '.env' file, allowing the MoA model to start and process prompts.

```bash
docker run -it --env-file .env -v "$(pwd)":/app moa_project
```

--------------------------------

### Configure API Keys in .env File

Source: https://github.com/ai-mickyj/mixture-of-agents/blob/main/README.md

This snippet shows how to create a '.env' file in the project's root directory and populate it with your API keys for OpenAI, Anthropic, and Google. These keys are essential for the MoA model to authenticate and interact with the respective Large Language Models.

```markdown
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
GOOGLE_API_KEY=your_google_api_key
```

--------------------------------

### Clone MoA Repository

Source: https://github.com/ai-mickyj/mixture-of-agents/blob/main/README.md

This command clones the Mixture of Agents implementation repository from GitHub to your local machine. It's the initial step required to set up the project environment.

```python
git clone https://github.com/yourusername/moa-implementation.git
cd moa-implementation
```

--------------------------------

### Build MoA Docker Image

Source: https://github.com/ai-mickyj/mixture-of-agents/blob/main/README.md

This command builds the Docker image for the Mixture of Agents project. It packages all the application's dependencies and code into a portable container, preparing it for execution.

```bash
docker build -t moa_project
```

--------------------------------

### Mixture of Agents Architecture Diagram

Source: https://github.com/ai-mickyj/mixture-of-agents/blob/main/README.md

This Mermaid diagram illustrates the multi-layer architecture of the MoA model. It shows the flow from user input through multiple layers of LLM agents (GPT-4, Claude, Gemini), aggregation, peer review, and synthesis steps, culminating in a final response.

```mermaid
graph TD
    A[User Input] --> B[Layer 1]
    B --> C[GPT-4 Agent]
    B --> D[Claude Agent]
    B --> E[Gemini Agent]
    C --> F[Aggregation & Peer Review]
    D --> F
    E --> F
    F --> G[Gemini Synthesis]
    G --> H[Layer 2]
    H --> I[GPT-4 Agent]
    H --> J[Claude Agent]
    H --> K[Gemini Agent]
    I --> L[Aggregation & Peer Review]
    J --> L
    K --> L
    L --> M[Gemini Synthesis]
    M --> N[Claude Final Output]
    N --> O[Final Response]
```

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