👟Runtime

AgentRuntime Class Documentation

Description:

The AgentRuntime class provides the runtime environment for executing agent workflows. It manages the lifecycle of agent execution, including input processing, payment validation, response generation, and output delivery.

Class Definition:

​Parameters:

• inputs (List[AgentInput]):

  • Description: A list of AgentInput objects. These define the sources from which the agent receives messages.

  • Requirement: Each AgentInput object must implement the start method, which pushes messages to a queue for processing.

• outputs (List[AgentOutput]):

  • Description: A list of AgentOutput objects. These define the destinations to which the agent sends responses.

  • Requirement: Each AgentOutput object must implement the send method, which delivers a response message to its destination.

• agent (Agent):

  • Description: An Agent object that represents the core intelligence of the system.

  • Requirement: This object must implement the execute method, which processes a single request and generates a response.

• pricing (Optional[Pricing], defaults to None):

  • Description: An optional Pricing object that defines the cost of using the agent and the wallet address to which payments should be sent.

  • Default: If None, no payment validation is performed.

• debug (bool, defaults to False):

  • Description: A boolean indicating whether debug mode is enabled. In debug mode, additional logging information is printed.

• enable_logs (bool, defaults to False):

  • Description: A boolean indicating whether logging is enabled. When enabled, logs are exported to the Lunet platform.

Variables:

• inputs (List[AgentInput]): Stores the input sources for the agent.

• outputs (List[AgentOutput]): Stores the output destinations for responses.

• agent (Agent): Stores the agent implementation being used.

• pricing (Optional[Pricing]): Stores the payment configuration, if required.

• spent_payments (Set[str]): A set to keep track of already processed transaction signatures to prevent duplicate processing.

• debug (bool): Flag to enable debug mode for more verbose logging.

• enable_logs (bool): Flag to enable log exporting.

Methods:

​__init__(self, inputs: List[AgentInput], outputs: List[AgentOutput], agent: Agent, pricing: Optional[Pricing] = None, debug: bool = False, enable_logs: bool = False)

Initializes the AgentRuntime with input sources, output destinations, an agent implementation, pricing configuration, debug mode flag, and enable logs flag.

​run(self)

Starts the agent runtime loop, continuously processing incoming requests.

​_run_request(self, request: Message)

Processes a single request through the agent pipeline, handling payment validation, agent execution, and response delivery.

​_get_memory(self) -> List[Dict[str, str]]

Retrieves the current state of the agent’s memory.

​_generate_proof(self, request: Message, response: Message) -> str

Generates a cryptographic proof of the request and response.

​_publish_proof(self, request: Message, response: Message, proof: str)

Publishes the cryptographic proof.

Data Types:

• List[AgentInput]: A list of objects conforming to the AgentInput interface.

• List[AgentOutput]: A list of objects conforming to the AgentOutput interface.

• Agent: An object conforming to the Agent interface.

• Optional[Pricing]: An optional Pricing object with the following attributes:

  • cost (float): The cost of the task in SOL.

  • wallet_address (str): The Solana wallet address where payment should be sent.

• bool: A boolean value (True or False).

• Message: An object with the following attributes:

  • content (str): The content of the message.

  • conversation_id (Optional[str], defaults to None): An optional conversation ID.

  • type (Optional[str], defaults to None): An optional message type.

  • additional_kwargs (Optional[Dict], defaults to None): An optional dictionary of additional keyword arguments.