simbiot-harness/venv/lib/python3.12/site-packages/strands/hooks/events.py
Simbiot Harness b60439152b Simbiot Harness v0.1: тактовая лестница на Strands + CQRS/ES-спина
- harness/es.py: append-only event store + проекции (образец — кооп-портал)
- harness/levels.py: уровни 1с/1м/1ч/1д, контекст ∝ масштабу
- harness/scheduler.py: уровневые потоки, идемпотентные тики, absorbed-стабы
- harness/isolated_runner.py + _llm_worker.py: LLM-тик в сабпроцессе
  (глобальный asyncio-рантайм Strands не переживает 2+ create_harness)
- cli.py: init/task/tasks/status/events + requeue (написан самим минутным агентом)
- 9router: отдельный ключ sk-simbiot, модель auto (glm-5.3 первым)
2026-09-29 15:28:50 +00:00

507 lines
19 KiB
Python

"""Hook events emitted as part of invoking Agents.
This module defines the events that are emitted as Agents run through the lifecycle of a request.
"""
import uuid
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any
from typing_extensions import override
if TYPE_CHECKING:
from ..agent.agent_result import AgentResult
from ..types.agent import AgentInput
from ..types.content import ContentBlock, Message, Messages
from ..types.interrupt import _Interruptible
from ..types.streaming import StopReason
from ..types.tools import AgentTool, ToolResult, ToolUse
from .registry import BaseHookEvent, HookEvent, _LocalAgentT
if TYPE_CHECKING:
from ..multiagent.base import MultiAgentBase
@dataclass
class AgentInitializedEvent(HookEvent[_LocalAgentT]):
"""Event triggered when an agent has finished initialization.
This event is fired after the agent has been fully constructed and all
built-in components have been initialized. Hook providers can use this
event to perform setup tasks that require a fully initialized agent.
"""
pass
@dataclass
class BeforeInvocationEvent(HookEvent):
"""Event triggered at the beginning of a new agent request.
This event is fired before the agent begins processing a new user request,
before any model inference or tool execution occurs. Hook providers can
use this event to perform request-level setup, logging, or validation.
This event is triggered at the beginning of the following api calls:
- Agent.__call__
- Agent.stream_async
- Agent.structured_output
Attributes:
invocation_state: State and configuration passed through the agent invocation.
This can include shared context for multi-agent coordination, request tracking,
and dynamic configuration.
messages: The input messages for this invocation. Can be modified by hooks
to redact or transform content before processing.
cancel: When set, cancels the invocation. If a string, used as the cancellation message.
If True, a default message is used.
"""
invocation_state: dict[str, Any] = field(default_factory=dict)
messages: Messages | None = None
cancel: bool | str = False
def _can_write(self, name: str) -> bool:
return name in ["messages", "cancel"]
@dataclass
class AfterInvocationEvent(HookEvent):
"""Event triggered at the end of an agent request.
This event is fired after the agent has completed processing a request,
regardless of whether it completed successfully or encountered an error.
Hook providers can use this event for cleanup, logging, or state persistence.
Note: This event uses reverse callback ordering, meaning callbacks registered
later will be invoked first during cleanup.
This event is triggered at the end of the following api calls:
- Agent.__call__
- Agent.stream_async
- Agent.structured_output
Resume:
When ``resume`` is set to a non-None value by a hook callback, the agent will
automatically re-invoke itself with the provided input. This enables hooks to
implement autonomous looping patterns where the agent continues processing
based on its previous result. The resume triggers a full new invocation cycle
including ``BeforeInvocationEvent``.
Attributes:
invocation_state: State and configuration passed through the agent invocation.
This can include shared context for multi-agent coordination, request tracking,
and dynamic configuration.
result: The result of the agent invocation, if available.
This will be None when invoked from structured_output methods, as those return typed output directly rather
than AgentResult.
resume: When set to a non-None agent input by a hook callback, the agent will
re-invoke itself with this input. The value can be any valid AgentInput
(str, content blocks, messages, etc.). Defaults to None (no resume).
"""
invocation_state: dict[str, Any] = field(default_factory=dict)
result: "AgentResult | None" = None
resume: AgentInput = None
def _can_write(self, name: str) -> bool:
return name == "resume"
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True
@dataclass
class MessageAddedEvent(HookEvent[_LocalAgentT]):
"""Event triggered when a message is added to the agent's conversation.
This event is fired whenever the agent adds a new message to its internal
message history, including user messages, assistant responses, and tool
results. Hook providers can use this event for logging, monitoring, or
implementing custom message processing logic.
Note: This event is only triggered for messages added by the framework
itself, not for messages manually added by tools or external code.
Attributes:
message: The message that was added to the conversation history.
"""
message: Message
@dataclass
class MessageUpdatedEvent(HookEvent[_LocalAgentT]):
"""Event triggered after the framework replaces a message.
Attributes:
tracking_id: Stable identifier of the replaced message.
message: Replacement message.
"""
tracking_id: str
message: Message
@dataclass
class BeforeToolsEvent(HookEvent, _Interruptible):
"""Event triggered before executing tools.
This event is fired when the model returns tool use blocks that need to be executed.
Hook callbacks can set ``cancel`` to prevent all tools from executing. Fires once per
cycle, so may fire more than once per assistant message when a per-tool interrupt
splits the batch.
Attributes:
message: The assistant message containing tool use requests.
invocation_state: State and configuration passed through the agent invocation.
cancel: When set, cancels all tool calls. If a string, used as the tool result
error message. If True, a default message is used.
"""
message: Message
invocation_state: dict[str, Any]
cancel: bool | str = False
def _can_write(self, name: str) -> bool:
return name == "cancel"
@override
def _interrupt_id(self, name: str) -> str:
"""Unique id for the interrupt.
Args:
name: User defined name for the interrupt.
Returns:
Interrupt id.
"""
return f"v1:before_tools:{uuid.uuid5(uuid.NAMESPACE_OID, name)}"
@dataclass
class AfterToolsEvent(HookEvent):
"""Event triggered after all tools complete execution.
This event is fired after tool results are collected and ready to be added to conversation.
Paired with a preceding ``BeforeToolsEvent`` when the batch proceeds past the
pre-execution phase (cancel, interrupt, and error paths included). Fires once per
cycle, so may fire more than once per assistant message when a per-tool interrupt
splits the batch.
Note: This event uses reverse callback ordering, meaning callbacks registered
later will be invoked first during cleanup.
Attributes:
message: The user-role message containing the tool results.
invocation_state: State and configuration passed through the agent invocation.
end_turn: When set, the agent loop halts after this tool batch without calling the
model again. A string becomes the final assistant text. A list of content blocks
becomes the final assistant message content. If True, a default message
is used. In any case, the stop_reason is "end_turn".
"""
message: Message
invocation_state: dict[str, Any]
end_turn: bool | str | list[ContentBlock] = False
def _can_write(self, name: str) -> bool:
return name == "end_turn"
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True
@dataclass
class BeforeToolCallEvent(HookEvent[_LocalAgentT], _Interruptible):
"""Event triggered before a tool is invoked.
This event is fired just before the agent executes a tool, allowing hook
providers to inspect, modify, or replace the tool that will be executed.
The selected_tool can be modified by hook callbacks to change which tool
gets executed.
Attributes:
selected_tool: The tool that will be invoked. Can be modified by hooks
to change which tool gets executed. This may be None if tool lookup failed.
tool_use: The tool parameters that will be passed to selected_tool.
invocation_state: Keyword arguments that will be passed to the tool.
cancel_tool: A user defined message that when set, will cancel the tool call.
The message will be placed into a tool result with an error status. If set to `True`, Strands will cancel
the tool call and use a default cancel message.
"""
selected_tool: AgentTool | None
tool_use: ToolUse
invocation_state: dict[str, Any]
cancel_tool: bool | str = False
def _can_write(self, name: str) -> bool:
return name in ["cancel_tool", "selected_tool", "tool_use"]
@override
def _interrupt_id(self, name: str) -> str:
"""Unique id for the interrupt.
Args:
name: User defined name for the interrupt.
Returns:
Interrupt id.
"""
return f"v1:before_tool_call:{self.tool_use['toolUseId']}:{uuid.uuid5(uuid.NAMESPACE_OID, name)}"
@dataclass
class AfterToolCallEvent(HookEvent[_LocalAgentT]):
"""Event triggered after a tool invocation completes.
This event is fired after the agent has finished executing a tool,
regardless of whether the execution was successful or resulted in an error.
Hook providers can use this event for cleanup, logging, or post-processing.
Note: This event uses reverse callback ordering, meaning callbacks registered
later will be invoked first during cleanup.
Tool Retrying:
When ``retry`` is set to True by a hook callback, the tool executor will
discard the current tool result and invoke the tool again. This has important
implications for streaming consumers:
- ToolStreamEvents (intermediate streaming events) from the discarded tool execution
will have already been emitted to callers before the retry occurs. Agent invokers
consuming streamed events should be prepared to handle this scenario, potentially
by tracking retry state or implementing idempotent event processing
- ToolResultEvent is NOT emitted for discarded attempts - only the final attempt's
result is emitted and added to the conversation history
Attributes:
selected_tool: The tool that was invoked. It may be None if tool lookup failed.
tool_use: The tool parameters that were passed to the tool invoked.
invocation_state: Keyword arguments that were passed to the tool
result: The result of the tool invocation. Either a ToolResult on success
or an Exception if the tool execution failed.
cancel_message: The cancellation message if the user cancelled the tool call.
duration: Elapsed time in seconds spent executing the tool. Starts after
BeforeToolCallEvent returns and stops before AfterToolCallEvent is constructed.
None when the tool call was cancelled by a BeforeToolCallEvent hook
before execution.
retry: Whether to retry the tool invocation. Can be set by hook callbacks
to trigger a retry. When True, the current result is discarded and the
tool is called again. Defaults to False.
"""
selected_tool: AgentTool | None
tool_use: ToolUse
invocation_state: dict[str, Any]
result: ToolResult
exception: Exception | None = None
cancel_message: str | None = None
duration: float | None = None
retry: bool = False
def _can_write(self, name: str) -> bool:
return name in ["result", "retry"]
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True
@dataclass
class BeforeModelCallEvent(HookEvent):
"""Event triggered before the model is invoked.
This event is fired just before the agent calls the model for inference,
allowing hook providers to inspect or modify the messages and configuration
that will be sent to the model.
Note: This event is not fired for invocations to structured_output.
Attributes:
invocation_state: State and configuration passed through the agent invocation.
This can include shared context for multi-agent coordination, request tracking,
and dynamic configuration.
projected_input_tokens: Projected input token count for the upcoming model call.
Computed by the agent loop from message metadata and token estimation.
Available for hooks and plugins (e.g. conversation managers) to make
proactive decisions about context management. None if estimation failed.
cancel: When set, cancels the model call. If a string, used as the cancellation message.
If True, a default message is used.
"""
invocation_state: dict[str, Any] = field(default_factory=dict)
projected_input_tokens: int | None = None
cancel: bool | str = False
def _can_write(self, name: str) -> bool:
return name == "cancel"
@dataclass
class AfterModelCallEvent(HookEvent):
"""Event triggered after the model invocation completes.
This event is fired after the agent has finished calling the model,
regardless of whether the invocation was successful or resulted in an error.
Hook providers can use this event for cleanup, logging, or post-processing.
Note: This event uses reverse callback ordering, meaning callbacks registered
later will be invoked first during cleanup.
Note: This event is not fired for invocations to structured_output.
Model Retrying:
When ``retry`` is set to True by a hook callback, the agent will discard
the current model response and invoke the model again. This has important
implications for streaming consumers:
- Streaming events from the discarded response will have already been emitted
to callers before the retry occurs. Agent invokers consuming streamed events
should be prepared to handle this scenario, potentially by tracking retry state
or implementing idempotent event processing
- The original model message is thrown away internally and not added to the
conversation history
Attributes:
invocation_state: State and configuration passed through the agent invocation.
This can include shared context for multi-agent coordination, request tracking,
and dynamic configuration.
stop_response: The model response data if invocation was successful, None if failed.
exception: Exception if the model invocation failed, None if successful.
retry: Whether to retry the model invocation. Can be set by hook callbacks
to trigger a retry. When True, the current response is discarded and the
model is called again. Defaults to False.
"""
@dataclass
class ModelStopResponse:
"""Model response data from successful invocation.
Attributes:
stop_reason: The reason the model stopped generating.
message: The generated message from the model.
"""
message: Message
stop_reason: StopReason
invocation_state: dict[str, Any] = field(default_factory=dict)
stop_response: ModelStopResponse | None = None
exception: Exception | None = None
retry: bool = False
def _can_write(self, name: str) -> bool:
return name == "retry"
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True
# Multiagent hook events start here
@dataclass
class MultiAgentInitializedEvent(BaseHookEvent):
"""Event triggered when multi-agent orchestrator initialized.
Attributes:
source: The multi-agent orchestrator instance
invocation_state: Configuration that user passes in
"""
source: "MultiAgentBase"
invocation_state: dict[str, Any] | None = None
@dataclass
class BeforeNodeCallEvent(BaseHookEvent, _Interruptible):
"""Event triggered before individual node execution starts.
Attributes:
source: The multi-agent orchestrator instance
node_id: ID of the node about to execute
invocation_state: Configuration that user passes in
cancel_node: A user defined message that when set, will cancel the node execution with status FAILED.
The message will be emitted under a MultiAgentNodeCancel event. If set to `True`, Strands will cancel the
node using a default cancel message.
"""
source: "MultiAgentBase"
node_id: str
invocation_state: dict[str, Any] | None = None
cancel_node: bool | str = False
def _can_write(self, name: str) -> bool:
return name in ["cancel_node"]
@override
def _interrupt_id(self, name: str) -> str:
"""Unique id for the interrupt.
Args:
name: User defined name for the interrupt.
Returns:
Interrupt id.
"""
node_id = uuid.uuid5(uuid.NAMESPACE_OID, self.node_id)
call_id = uuid.uuid5(uuid.NAMESPACE_OID, name)
return f"v1:before_node_call:{node_id}:{call_id}"
@dataclass
class AfterNodeCallEvent(BaseHookEvent):
"""Event triggered after individual node execution completes.
Attributes:
source: The multi-agent orchestrator instance
node_id: ID of the node that just completed execution
invocation_state: Configuration that user passes in
"""
source: "MultiAgentBase"
node_id: str
invocation_state: dict[str, Any] | None = None
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True
@dataclass
class BeforeMultiAgentInvocationEvent(BaseHookEvent):
"""Event triggered before orchestrator execution starts.
Attributes:
source: The multi-agent orchestrator instance
invocation_state: Configuration that user passes in
"""
source: "MultiAgentBase"
invocation_state: dict[str, Any] | None = None
@dataclass
class AfterMultiAgentInvocationEvent(BaseHookEvent):
"""Event triggered after orchestrator execution completes.
Attributes:
source: The multi-agent orchestrator instance
invocation_state: Configuration that user passes in
"""
source: "MultiAgentBase"
invocation_state: dict[str, Any] | None = None
@property
def should_reverse_callbacks(self) -> bool:
"""True to invoke callbacks in reverse order."""
return True