InvokeAI/invokeai/app/services/events/events_base.py
Lincoln Stein fbede84405
[feature] Download Queue (#5225)
* add base definition of download manager

* basic functionality working

* add unit tests for download queue

* add documentation and FastAPI route

* fix docs

* add missing test dependency; fix import ordering

* fix file path length checking on windows

* fix ruff check error

* move release() into the __del__ method

* disable testing of stderr messages due to issues with pytest capsys fixture

* fix unsorted imports

* harmonized implementation of start() and stop() calls in download and & install modules

* Update invokeai/app/services/download/download_base.py

Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>

* replace test datadir fixture with tmp_path

* replace DownloadJobBase->DownloadJob in download manager documentation

* make source and dest arguments to download_queue.download() an AnyHttpURL and Path respectively

* fix pydantic typecheck errors in the download unit test

* ruff formatting

* add "job cancelled" as an event rather than an exception

* fix ruff errors

* Update invokeai/app/services/download/download_default.py

Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>

* use threading.Event to stop service worker threads; handle unfinished job edge cases

* remove dangling STOP job definition

* fix ruff complaint

* fix ruff check again

* avoid race condition when start() and stop() are called simultaneously from different threads

* avoid race condition in stop() when a job becomes active while shutting down

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
2023-12-22 12:35:57 -05:00

476 lines
16 KiB
Python

# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from typing import Any, Optional
from invokeai.app.services.invocation_processor.invocation_processor_common import ProgressImage
from invokeai.app.services.session_queue.session_queue_common import (
BatchStatus,
EnqueueBatchResult,
SessionQueueItem,
SessionQueueStatus,
)
from invokeai.app.util.misc import get_timestamp
from invokeai.backend.model_management.model_manager import ModelInfo
from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
class EventServiceBase:
queue_event: str = "queue_event"
download_event: str = "download_event"
model_event: str = "model_event"
"""Basic event bus, to have an empty stand-in when not needed"""
def dispatch(self, event_name: str, payload: Any) -> None:
pass
def __emit_queue_event(self, event_name: str, payload: dict) -> None:
"""Queue events are emitted to a room with queue_id as the room name"""
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.queue_event,
payload={"event": event_name, "data": payload},
)
def __emit_download_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.download_event,
payload={"event": event_name, "data": payload},
)
def __emit_model_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.model_event,
payload={"event": event_name, "data": payload},
)
# Define events here for every event in the system.
# This will make them easier to integrate until we find a schema generator.
def emit_generator_progress(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
progress_image: Optional[ProgressImage],
step: int,
order: int,
total_steps: int,
) -> None:
"""Emitted when there is generation progress"""
self.__emit_queue_event(
event_name="generator_progress",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"node_id": node.get("id"),
"source_node_id": source_node_id,
"progress_image": progress_image.model_dump() if progress_image is not None else None,
"step": step,
"order": order,
"total_steps": total_steps,
},
)
def emit_invocation_complete(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
result: dict,
node: dict,
source_node_id: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_queue_event(
event_name="invocation_complete",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"node": node,
"source_node_id": source_node_id,
"result": result,
},
)
def emit_invocation_error(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
error_type: str,
error: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_queue_event(
event_name="invocation_error",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"node": node,
"source_node_id": source_node_id,
"error_type": error_type,
"error": error,
},
)
def emit_invocation_started(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
) -> None:
"""Emitted when an invocation has started"""
self.__emit_queue_event(
event_name="invocation_started",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"node": node,
"source_node_id": source_node_id,
},
)
def emit_graph_execution_complete(
self, queue_id: str, queue_item_id: int, queue_batch_id: str, graph_execution_state_id: str
) -> None:
"""Emitted when a session has completed all invocations"""
self.__emit_queue_event(
event_name="graph_execution_state_complete",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
},
)
def emit_model_load_started(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
model_name: str,
base_model: BaseModelType,
model_type: ModelType,
submodel: SubModelType,
) -> None:
"""Emitted when a model is requested"""
self.__emit_queue_event(
event_name="model_load_started",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"model_name": model_name,
"base_model": base_model,
"model_type": model_type,
"submodel": submodel,
},
)
def emit_model_load_completed(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
model_name: str,
base_model: BaseModelType,
model_type: ModelType,
submodel: SubModelType,
model_info: ModelInfo,
) -> None:
"""Emitted when a model is correctly loaded (returns model info)"""
self.__emit_queue_event(
event_name="model_load_completed",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"model_name": model_name,
"base_model": base_model,
"model_type": model_type,
"submodel": submodel,
"hash": model_info.hash,
"location": str(model_info.location),
"precision": str(model_info.precision),
},
)
def emit_session_retrieval_error(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
error_type: str,
error: str,
) -> None:
"""Emitted when session retrieval fails"""
self.__emit_queue_event(
event_name="session_retrieval_error",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"error_type": error_type,
"error": error,
},
)
def emit_invocation_retrieval_error(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
node_id: str,
error_type: str,
error: str,
) -> None:
"""Emitted when invocation retrieval fails"""
self.__emit_queue_event(
event_name="invocation_retrieval_error",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
"node_id": node_id,
"error_type": error_type,
"error": error,
},
)
def emit_session_canceled(
self,
queue_id: str,
queue_item_id: int,
queue_batch_id: str,
graph_execution_state_id: str,
) -> None:
"""Emitted when a session is canceled"""
self.__emit_queue_event(
event_name="session_canceled",
payload={
"queue_id": queue_id,
"queue_item_id": queue_item_id,
"queue_batch_id": queue_batch_id,
"graph_execution_state_id": graph_execution_state_id,
},
)
def emit_queue_item_status_changed(
self,
session_queue_item: SessionQueueItem,
batch_status: BatchStatus,
queue_status: SessionQueueStatus,
) -> None:
"""Emitted when a queue item's status changes"""
self.__emit_queue_event(
event_name="queue_item_status_changed",
payload={
"queue_id": queue_status.queue_id,
"queue_item": {
"queue_id": session_queue_item.queue_id,
"item_id": session_queue_item.item_id,
"status": session_queue_item.status,
"batch_id": session_queue_item.batch_id,
"session_id": session_queue_item.session_id,
"error": session_queue_item.error,
"created_at": str(session_queue_item.created_at) if session_queue_item.created_at else None,
"updated_at": str(session_queue_item.updated_at) if session_queue_item.updated_at else None,
"started_at": str(session_queue_item.started_at) if session_queue_item.started_at else None,
"completed_at": str(session_queue_item.completed_at) if session_queue_item.completed_at else None,
},
"batch_status": batch_status.model_dump(),
"queue_status": queue_status.model_dump(),
},
)
def emit_batch_enqueued(self, enqueue_result: EnqueueBatchResult) -> None:
"""Emitted when a batch is enqueued"""
self.__emit_queue_event(
event_name="batch_enqueued",
payload={
"queue_id": enqueue_result.queue_id,
"batch_id": enqueue_result.batch.batch_id,
"enqueued": enqueue_result.enqueued,
},
)
def emit_queue_cleared(self, queue_id: str) -> None:
"""Emitted when the queue is cleared"""
self.__emit_queue_event(
event_name="queue_cleared",
payload={"queue_id": queue_id},
)
def emit_download_started(self, source: str, download_path: str) -> None:
"""
Emit when a download job is started.
:param url: The downloaded url
"""
self.__emit_download_event(
event_name="download_started",
payload={"source": source, "download_path": download_path},
)
def emit_download_progress(self, source: str, download_path: str, current_bytes: int, total_bytes: int) -> None:
"""
Emit "download_progress" events at regular intervals during a download job.
:param source: The downloaded source
:param download_path: The local downloaded file
:param current_bytes: Number of bytes downloaded so far
:param total_bytes: The size of the file being downloaded (if known)
"""
self.__emit_download_event(
event_name="download_progress",
payload={
"source": source,
"download_path": download_path,
"current_bytes": current_bytes,
"total_bytes": total_bytes,
},
)
def emit_download_complete(self, source: str, download_path: str, total_bytes: int) -> None:
"""
Emit a "download_complete" event at the end of a successful download.
:param source: Source URL
:param download_path: Path to the locally downloaded file
:param total_bytes: The size of the downloaded file
"""
self.__emit_download_event(
event_name="download_complete",
payload={
"source": source,
"download_path": download_path,
"total_bytes": total_bytes,
},
)
def emit_download_cancelled(self, source: str) -> None:
"""Emit a "download_cancelled" event in the event that the download was cancelled by user."""
self.__emit_download_event(
event_name="download_cancelled",
payload={
"source": source,
},
)
def emit_download_error(self, source: str, error_type: str, error: str) -> None:
"""
Emit a "download_error" event when an download job encounters an exception.
:param source: Source URL
:param error_type: The name of the exception that raised the error
:param error: The traceback from this error
"""
self.__emit_download_event(
event_name="download_error",
payload={
"source": source,
"error_type": error_type,
"error": error,
},
)
def emit_model_install_started(self, source: str) -> None:
"""
Emitted when an install job is started.
:param source: Source of the model; local path, repo_id or url
"""
self.__emit_model_event(
event_name="model_install_started",
payload={"source": source},
)
def emit_model_install_completed(self, source: str, key: str) -> None:
"""
Emitted when an install job is completed successfully.
:param source: Source of the model; local path, repo_id or url
:param key: Model config record key
"""
self.__emit_model_event(
event_name="model_install_completed",
payload={
"source": source,
"key": key,
},
)
def emit_model_install_progress(
self,
source: str,
current_bytes: int,
total_bytes: int,
) -> None:
"""
Emitted while the install job is in progress.
(Downloaded models only)
:param source: Source of the model
:param current_bytes: Number of bytes downloaded so far
:param total_bytes: Total bytes to download
"""
self.__emit_model_event(
event_name="model_install_progress",
payload={
"source": source,
"current_bytes": int,
"total_bytes": int,
},
)
def emit_model_install_error(
self,
source: str,
error_type: str,
error: str,
) -> None:
"""
Emitted when an install job encounters an exception.
:param source: Source of the model
:param exception: The exception that raised the error
"""
self.__emit_model_event(
event_name="model_install_error",
payload={
"source": source,
"error_type": error_type,
"error": error,
},
)