InvokeAI/invokeai/app/services/events.py
psychedelicious 160267c71a feat(nodes): refactor image types
- Remove `ImageType` entirely, it is confusing
- Create `ResourceOrigin`, may be `internal` or `external`
- Revamp `ImageCategory`, may be `general`, `mask`, `control`, `user`, `other`. Expect to add more as time goes on
- Update images `list` route to accept `include_categories` OR `exclude_categories` query parameters to afford finer-grained querying. All services are updated to accomodate this change.

The new setup should account for our types of images, including the combinations we couldn't really handle until now:
- Canvas init and masks
- Canvas when saved-to-gallery or merged
2023-05-28 20:19:56 -04:00

104 lines
3.3 KiB
Python

# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from typing import Any
from invokeai.app.models.image import ProgressImage
from invokeai.app.util.misc import get_timestamp
class EventServiceBase:
session_event: str = "session_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_session_event(self, event_name: str, payload: dict) -> None:
payload["timestamp"] = get_timestamp()
self.dispatch(
event_name=EventServiceBase.session_event,
payload=dict(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,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
progress_image: ProgressImage | None,
step: int,
total_steps: int,
) -> None:
"""Emitted when there is generation progress"""
self.__emit_session_event(
event_name="generator_progress",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
node=node,
source_node_id=source_node_id,
progress_image=progress_image.dict() if progress_image is not None else None,
step=step,
total_steps=total_steps,
),
)
def emit_invocation_complete(
self,
graph_execution_state_id: str,
result: dict,
node: dict,
source_node_id: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_session_event(
event_name="invocation_complete",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
node=node,
source_node_id=source_node_id,
result=result,
),
)
def emit_invocation_error(
self,
graph_execution_state_id: str,
node: dict,
source_node_id: str,
error: str,
) -> None:
"""Emitted when an invocation has completed"""
self.__emit_session_event(
event_name="invocation_error",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
node=node,
source_node_id=source_node_id,
error=error,
),
)
def emit_invocation_started(
self, graph_execution_state_id: str, node: dict, source_node_id: str
) -> None:
"""Emitted when an invocation has started"""
self.__emit_session_event(
event_name="invocation_started",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
node=node,
source_node_id=source_node_id,
),
)
def emit_graph_execution_complete(self, graph_execution_state_id: str) -> None:
"""Emitted when a session has completed all invocations"""
self.__emit_session_event(
event_name="graph_execution_state_complete",
payload=dict(
graph_execution_state_id=graph_execution_state_id,
),
)