Agents

Agents are the core actors in the LLLM framework. They encapsulate the logic for interacting with LLMs, managing state (Dialog), and executing tools.

The Agent Class

The Agent class represents a single LLM entity with a specific role, system prompt, and model configuration.

Key Attributes

• name: The name or role of the agent (e.g., "assistant", "coder").
• system_prompt: The Prompt object defining the agent's persona and capabilities.
• model: The LLM model to use (e.g., "gpt-4o").
• llm_provider: The provider instance (e.g., OpenAIProvider).

The AgentBase Class

AgentBase is the base class for building complex agentic systems. It allows you to compose multiple Agent instances and define custom orchestration logic.

Creating a Custom Agent

To create a custom agent, subclass AgentBase and implement the call method:

from lllm import AgentBase

class MyAgent(AgentBase):
    agent_type = "my_agent"
    agent_group = ["worker", "reviewer"] # Define sub-agents

    def call(self, task: str, **kwargs):
        # Implement your logic here
        pass