hap.types.agents

HAP type definitions for Haive agents.

This module defines HAP protocol types for exposing Haive agents, which are the primary building blocks of AI systems.

Classes

AgentConfigUpdate	Request to update agent configuration.
AgentExecutionRequest	Request to execute an agent.
AgentExecutionResult	Result from agent execution.
AgentInfo	Information about a Haive agent exposed through HAP.
AgentReasoningStep	A step in agent reasoning (for agents that support it).
AgentStateSnapshot	Snapshot of agent state at a point in time.
AgentStatistics	Statistics about agent usage.
AgentToolCall	Information about a tool call made by an agent.
MultiAgentInfo	Information about multi-agent systems.
RAGAgentInfo	Information specific to RAG agents.
ReactAgentInfo	Information specific to ReactAgent.
SimpleAgentInfo	Information specific to SimpleAgent.

Module Contents

class hap.types.agents.AgentConfigUpdate(/, **data: Any)

Bases: pydantic.BaseModel

Request to update agent configuration.

Parameters:

data (Any)

max_tokens: int | None = None

structured_output_enabled: bool | None = None

system_message: str | None = None

temperature: float | None = None

tool_names: list[str] | None = None

tools_enabled: bool | None = None

class hap.types.agents.AgentExecutionRequest(/, **data: Any)

Bases: pydantic.BaseModel

Request to execute an agent.

This is the primary tool for agent execution through HAP.

Parameters:

data (Any)

checkpoint_id: str | None = None

config: dict[str, Any] | None = None

include_state: bool = None

input_data: str | dict[str, Any] | list[dict[str, Any]] = None

save_checkpoint: bool = None

stream: bool = None

class hap.types.agents.AgentExecutionResult(/, **data: Any)

Bases: pydantic.BaseModel

Result from agent execution.

Parameters:

data (Any)

checkpoint_id: str | None = None

duration_ms: float | None = None

error: str | None = None

metadata: dict[str, Any] = None

result: Any | None = None

state: dict[str, Any] | None = None

status: Literal['success', 'error', 'interrupted'] = None

token_usage: dict[str, int] | None = None

class hap.types.agents.AgentInfo(/, **data: Any)

Bases: haive.hap.types.BaseInfo

Information about a Haive agent exposed through HAP.

Agents are workflow + engine combinations that provide intelligent behavior through LLMs or other AI models.

Parameters:

data (Any)

agent_class: str = None

agent_type: str = None

capabilities: list[str] = None

engine_class: str | None = None

engine_type: str | None = None

graph_info: dict[str, Any] | None = None

has_structured_output: bool = None

has_tools: bool = None

input_schema: str | None = None

metadata: dict[str, Any] = None

output_schema: str | None = None

state_schema: str | None = None

structured_output_model: str | None = None

tool_count: int = None

tool_names: list[str] = None

class hap.types.agents.AgentReasoningStep(/, **data: Any)

Bases: pydantic.BaseModel

A step in agent reasoning (for agents that support it).

Parameters:

data (Any)

action: str | None = None

action_input: Any | None = None

metadata: dict[str, Any] = None

observation: str | None = None

step_number: int = None

thought: str = None

class hap.types.agents.AgentStateSnapshot(/, **data: Any)

Bases: pydantic.BaseModel

Snapshot of agent state at a point in time.

Parameters:

data (Any)

agent_name: str = None

context: dict[str, Any] | None = None

messages: list[dict[str, Any]] | None = None

metadata: dict[str, Any] = None

state: dict[str, Any] = None

timestamp: str = None

class hap.types.agents.AgentStatistics(/, **data: Any)

Bases: pydantic.BaseModel

Statistics about agent usage.

Parameters:

data (Any)

average_duration_ms: float = None

error_types: dict[str, int] = None

failed_executions: int = None

last_execution: str | None = None

successful_executions: int = None

total_duration_ms: float = None

total_executions: int = None

total_tokens: int = None

class hap.types.agents.AgentToolCall(/, **data: Any)

Bases: pydantic.BaseModel

Information about a tool call made by an agent.

Parameters:

data (Any)

arguments: dict[str, Any] = None

duration_ms: float | None = None

error: str | None = None

result: Any | None = None

tool_name: str = None

class hap.types.agents.MultiAgentInfo(/, **data: Any)

Bases: AgentInfo

Information about multi-agent systems.

Parameters:

data (Any)

agent_type: Literal['MultiAgent'] = 'MultiAgent'

coordination_mode: Literal['sequential', 'parallel', 'hierarchical', 'collaborative'] = None

routing_strategy: str | None = None

sub_agents: list[str] = None

class hap.types.agents.RAGAgentInfo(/, **data: Any)

Bases: AgentInfo

Information specific to RAG agents.

Parameters:

data (Any)

agent_type: Literal['RAGAgent'] = 'RAGAgent'

chunk_size: int | None = None

embedding_model: str | None = None

retriever_type: str | None = None

top_k: int | None = None

vector_store: str | None = None

class hap.types.agents.ReactAgentInfo(/, **data: Any)

Bases: AgentInfo

Information specific to ReactAgent.

Parameters:

data (Any)

agent_type: Literal['ReactAgent'] = 'ReactAgent'

max_iterations: int = None

reasoning_style: Literal['react', 'cot', 'tot'] = None

supports_reasoning: bool = None

class hap.types.agents.SimpleAgentInfo(/, **data: Any)

Bases: AgentInfo

Information specific to SimpleAgent.

Parameters:

data (Any)

agent_type: Literal['SimpleAgent'] = 'SimpleAgent'

prompt_template: str | None = None

system_message: str | None = None