`agents.components.cortex`¶

Module Contents¶

Classes¶

Cortex

The Cortex component is an LLM-powered task planner and executor that also serves as the system monitor.

API¶

class agents.components.cortex.Cortex(*, actions: Optional[List[agents.ros.Action]] = None, output: Optional[agents.ros.Topic] = None, model_client: Optional[agents.clients.model_base.ModelClient] = None, db_client: Optional[agents.clients.db_base.DBClient] = None, config: Optional[agents.config.CortexConfig] = None, component_name: str, **kwargs)¶

Bases: agents.components.model_component.ModelComponent, agents.ros.Monitor

The Cortex component is an LLM-powered task planner and executor that also serves as the system monitor.

Named after the cerebral cortex, the brain region responsible for higher-order planning, reasoning, and action sequencing, this component takes a high-level task, uses an LLM to decompose it into sub-tasks, and executes them by dispatching Actions registered on other components.

Task execution follows a two-phase approach:

Planning – A single LLM call with all available actions as tools produces a step-by-step plan (returned as multiple tool_calls). Optional RAG context from a vector DB is injected during this phase.
Execution – Each planned step is executed sequentially. Before each step, a brief LLM confirmation call decides: EXECUTE, SKIP, or ABORT, based on the original plan and results so far.

The component runs as a ROS2 action server, receiving task goals and providing feedback during execution.

Parameters:

actions (list[Action]) – The action palette – a list of Action objects with descriptions, representing the actions available to the planner.
output (Topic) – Output topic for publishing results for tasks where an action is not required or a plan is not generated.
model_client (Optional[ModelClient]) – The model client for LLM inference. Optional if enable_local_model is set to True in the config.
db_client (Optional[DBClient]) – Optional database client for RAG context during planning.
config (Optional[CortexConfig]) – Configuration for the Cortex component.
component_name (str) – The name of this component.

Example usage:

from agents.components import Cortex
from agents.config import CortexConfig
from agents.ros import Action, Topic, Launcher

cortex = Cortex(
    actions=[
        Action(method=nav.go_to, description="Navigate to a location"),
        Action(method=arm.grasp, description="Grasp an object"),
    ],
    model_client=my_client,
    config=CortexConfig(max_planning_steps=10, max_execution_steps=15),
    component_name="cortex",
)

custom_on_configure()¶: Create model client if provided and initialize model.

custom_on_activate()¶: Custom configuration for creating triggers.

custom_on_deactivate()¶: Destroy model client if it exists

add_documents(ids: List[str], metadatas: List[Dict], documents: List[str]) → None¶: Add documents to vector DB for RAG context during planning.

main_action_callback(goal_handle)¶

Action server callback. Iterative plan-execute loop.

Plans a batch of steps, executes them, then feeds the results back into the planning conversation so the LLM can continue with additional steps if needed. The loop ends when the planner returns no more tool calls or an abort/failure occurs.

Parameters:: goal_handle – Incoming action goal
Returns:: Action result

property additional_model_clients: Optional[Dict[str, agents.clients.model_base.ModelClient]]¶

Get the dictionary of additional model clients registered to this component.

Returns:: A dictionary mapping client names (str) to ModelClient instances, or None if not set.
Return type:: Optional[Dict[str, ModelClient]]

fallback_to_local() → str¶

Switch from remote model_client to the built-in local model at runtime.

The local model is deployed on first call (lazy initialization) to avoid consuming GPU memory until actually needed. If enable_local_model is not already set in config, it is enabled automatically.

This is commonly used as a target for Actions in the Event system.

Returns:: A confirmation message describing the switch.
Return type:: str
Raises:: RuntimeError – If the local model could not be deployed.
Example:

    from agents.ros import Action

    # Define an action to switch to the 'local model' available in each component
    switch_to_local = Action(
        method=brain.fallback_to_local,
    )

    # Trigger this action if the component fails (e.g. internet outage)
    brain.on_component_fail(action=switch_to_local, max_retries=3)

change_model_client(model_client_name: str) → str¶

Hot-swap the active model client at runtime.

This method replaces the component’s current model_client with one from the registered additional_model_clients. It handles the safe de-initialization of the old client and initialization of the new one.

This is commonly used as a target for Actions in the Event system.

Parameters:: model_client_name (str) – The key corresponding to the desired client in additional_model_clients.
Returns:: A confirmation message describing the swap.
Return type:: str
Raises:: RuntimeError – If no additional clients are registered, the requested client name is not found, or initialization fails.
Example:

    from agents.ros import Action

    # Define an action to switch to the 'remote_backup' client defined previously
    switch_to_backup = Action(
        method=brain.change_model_client,
        args=("remote_backup",)
    )

    # Trigger this action if the component fails (e.g. server down)
    brain.on_component_fail(action=switch_to_backup, max_retries=3)

inspect_component() → str¶: Return component info including additional model clients.

property warmup: bool¶: Enable warmup of the model.

create_all_subscribers()¶: Override to handle trigger topics and fixed inputs. Called by parent BaseComponent

activate_all_triggers() → None¶: Activates component triggers by attaching execution step to callbacks

destroy_all_subscribers() → None¶: Destroys all node subscribers

agents.components.cortex¶

Module Contents¶

Classes¶

API¶

`agents.components.cortex`¶