BaseAgent¶

The BaseAgent class is the foundation for all agents in the framework. It handles configuration loading, session management, LLM setup, tool creation, and observability initialization.

Usage¶

from src.all_agents.base_agent import BaseAgent
from src.service.models.base_models import TextInput, TextOutput

class MyAgent(BaseAgent):
    def __init__(self):
        super().__init__(
            config_path=resolve_config_path(relative_to=__file__),
            input_schema=TextInput,
            output_schema=TextOutput
        )

Responsibilities¶

BaseAgent handles:

Configuration Loading: Loads AgentConfig from YAML files
Session Management: Wires up session services and manages conversation history
LLM Setup: Configures the Google ADK Runner with your LLM provider
Tool Creation: Builds tools from YAML configuration
Observability: Initializes Opik tracing and metrics

Subclass Requirements¶

Subclasses typically only need to:

Provide input_schema and output_schema via super().__init__
Optionally override _create_input_from_request for custom input mapping

Methods¶

`chat(request: AgentChatRequest) -> AgentChatResponse`¶

Processes a chat request and returns a response. Handles session management, input parsing, LLM execution, and response parsing automatically.

`_create_input_from_request(request: AgentChatRequest) -> BaseModel`¶

Converts an AgentChatRequest to your agent’s input schema. Override this for custom input mapping.

`_get_agent_name() -> str`¶

Returns the agent’s name from configuration.

See the API Reference for complete method documentation.