Agents

Warden employs an agent-based architecture that allows developers to create, manage, and extend intelligent agents for various tasks. Agents are the core building blocks in Warden, enabling modularity and extensibility while interacting with multiple large language models (LLMs).

Key Features of Agents

1. Pluggable Agents:

   • Create agents with specialized AI capabilities for different tasks.
   • Integrate agents with LLMs such as OpenAI GPT-4, Claude, DeepSeek, and more.

2. Multi-Agent Collaboration:

   • Enable multiple agents to collaborate on tasks using shared memory.
   • Facilitate complex workflows by combining the expertise of different agents.

3. Serialization and Sharing:

   • Export agents as .agent files to share or deploy them across environments.
   • Import pre-configured agents for faster development and deployment.

4. Stateful Interactions:

   • Retain conversation context across multiple interactions.
   • Provide human-like, contextual responses based on memory.

Managing Agents

Creating a New Agent

To create a new agent, implement the BaseAgent interface and define the desired functionality. For example:

type MyAgent struct {
    Name    string
    Memory  *Memory
}

func (a *MyAgent) Respond(input string) string {
    // Add custom logic for response generation
    return "This is my custom agent's response."
}
Here’s the `agents.md` content ready for you to copy and paste:

---

```markdown
# Agents

Warden employs an **agent-based architecture** that allows developers to create, manage, and extend intelligent agents for various tasks. Agents are the core building blocks in Warden, enabling modularity and extensibility while interacting with multiple large language models (LLMs).

## Key Features of Agents

1. **Pluggable Agents**:
   - Create agents with specialized AI capabilities for different tasks.
   - Integrate agents with LLMs such as OpenAI GPT-4, Claude, DeepSeek, and more.

2. **Multi-Agent Collaboration**:
   - Enable multiple agents to collaborate on tasks using shared memory.
   - Facilitate complex workflows by combining the expertise of different agents.

3. **Serialization and Sharing**:
   - Export agents as `.agent` files to share or deploy them across environments.
   - Import pre-configured agents for faster development and deployment.

4. **Stateful Interactions**:
   - Retain conversation context across multiple interactions.
   - Provide human-like, contextual responses based on memory.

## Managing Agents

### Creating a New Agent
To create a new agent, implement the `BaseAgent` interface and define the desired functionality. For example:

```go
type MyAgent struct {
    Name    string
    Memory  *Memory
}

func (a *MyAgent) Respond(input string) string {
    // Add custom logic for response generation
    return "This is my custom agent's response."
}

Exporting an Agent

Save an agent's configuration and memory state to a file:

agent.ExportToFile("my_agent.agent")

Importing an Agent

Load an agent from a .agent file for reuse:

loadedAgent := agent.ImportFromFile("my_agent.agent")

Conclusion

The agent-based design makes Warden a powerful tool for building modular and reusable AI-powered systems. You can extend agents, add tools, and collaborate across multiple platforms seamlessly.