InvokeAI/invokeai/app/api_app.py
psychedelicious 2f9ebdec69 fix(app): openapi schema generation
Some tech debt related to dynamic pydantic schemas for invocations became problematic. Including the invocations and results in the event schemas was breaking pydantic's handling of ref schemas. I don't really understand why - I think it's a pydantic bug in a remote edge case that we are hitting.

After many failed attempts I landed on this implementation, which is actually much tidier than what was in there before.

- Create pydantic-enabled types for `AnyInvocation` and `AnyInvocationOutput` and use these in place of the janky dynamic unions. Actually, they are kinda the same, but better encapsulated. Use these in `Graph`, `GraphExecutionState`, `InvocationEventBase` and `InvocationCompleteEvent`.
- Revise the custom openapi function to work with the new models.
- Split out the custom openapi function to a separate file. Add a `post_transform` callback so consumers can customize the output schema.
- Update makefile scripts.
2024-05-30 12:03:03 +10:00

212 lines
7.1 KiB
Python

import asyncio
import logging
import mimetypes
import socket
from contextlib import asynccontextmanager
from pathlib import Path
import torch
import uvicorn
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
from fastapi.openapi.docs import get_redoc_html, get_swagger_ui_html
from fastapi.responses import HTMLResponse
from fastapi_events.handlers.local import local_handler
from fastapi_events.middleware import EventHandlerASGIMiddleware
from torch.backends.mps import is_available as is_mps_available
# for PyCharm:
# noinspection PyUnresolvedReferences
import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
import invokeai.frontend.web as web_dir
from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
from invokeai.app.services.config.config_default import get_config
from invokeai.app.util.custom_openapi import get_openapi_func
from invokeai.backend.util.devices import TorchDevice
from ..backend.util.logging import InvokeAILogger
from .api.dependencies import ApiDependencies
from .api.routers import (
app_info,
board_images,
boards,
download_queue,
images,
model_manager,
session_queue,
utilities,
workflows,
)
from .api.sockets import SocketIO
app_config = get_config()
if is_mps_available():
import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
logger = InvokeAILogger.get_logger(config=app_config)
# fix for windows mimetypes registry entries being borked
# see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
mimetypes.add_type("application/javascript", ".js")
mimetypes.add_type("text/css", ".css")
torch_device_name = TorchDevice.get_torch_device_name()
logger.info(f"Using torch device: {torch_device_name}")
@asynccontextmanager
async def lifespan(app: FastAPI):
# Add startup event to load dependencies
ApiDependencies.initialize(config=app_config, event_handler_id=event_handler_id, logger=logger)
yield
# Shut down threads
ApiDependencies.shutdown()
# Create the app
# TODO: create this all in a method so configuration/etc. can be passed in?
app = FastAPI(
title="Invoke - Community Edition",
docs_url=None,
redoc_url=None,
separate_input_output_schemas=False,
lifespan=lifespan,
)
# Add event handler
event_handler_id: int = id(app)
app.add_middleware(
EventHandlerASGIMiddleware,
handlers=[local_handler], # TODO: consider doing this in services to support different configurations
middleware_id=event_handler_id,
)
socket_io = SocketIO(app)
app.add_middleware(
CORSMiddleware,
allow_origins=app_config.allow_origins,
allow_credentials=app_config.allow_credentials,
allow_methods=app_config.allow_methods,
allow_headers=app_config.allow_headers,
)
app.add_middleware(GZipMiddleware, minimum_size=1000)
# Include all routers
app.include_router(utilities.utilities_router, prefix="/api")
app.include_router(model_manager.model_manager_router, prefix="/api")
app.include_router(download_queue.download_queue_router, prefix="/api")
app.include_router(images.images_router, prefix="/api")
app.include_router(boards.boards_router, prefix="/api")
app.include_router(board_images.board_images_router, prefix="/api")
app.include_router(app_info.app_router, prefix="/api")
app.include_router(session_queue.session_queue_router, prefix="/api")
app.include_router(workflows.workflows_router, prefix="/api")
app.openapi = get_openapi_func(app)
@app.get("/docs", include_in_schema=False)
def overridden_swagger() -> HTMLResponse:
return get_swagger_ui_html(
openapi_url=app.openapi_url, # type: ignore [arg-type] # this is always a string
title=f"{app.title} - Swagger UI",
swagger_favicon_url="static/docs/invoke-favicon-docs.svg",
)
@app.get("/redoc", include_in_schema=False)
def overridden_redoc() -> HTMLResponse:
return get_redoc_html(
openapi_url=app.openapi_url, # type: ignore [arg-type] # this is always a string
title=f"{app.title} - Redoc",
redoc_favicon_url="static/docs/invoke-favicon-docs.svg",
)
web_root_path = Path(list(web_dir.__path__)[0])
try:
app.mount("/", NoCacheStaticFiles(directory=Path(web_root_path, "dist"), html=True), name="ui")
except RuntimeError:
logger.warn(f"No UI found at {web_root_path}/dist, skipping UI mount")
app.mount(
"/static", NoCacheStaticFiles(directory=Path(web_root_path, "static/")), name="static"
) # docs favicon is in here
def check_cudnn(logger: logging.Logger) -> None:
"""Check for cuDNN issues that could be causing degraded performance."""
if torch.backends.cudnn.is_available():
try:
# Note: At the time of writing (torch 2.2.1), torch.backends.cudnn.version() only raises an error the first
# time it is called. Subsequent calls will return the version number without complaining about a mismatch.
cudnn_version = torch.backends.cudnn.version()
logger.info(f"cuDNN version: {cudnn_version}")
except RuntimeError as e:
logger.warning(
"Encountered a cuDNN version issue. This may result in degraded performance. This issue is usually "
"caused by an incompatible cuDNN version installed in your python environment, or on the host "
f"system. Full error message:\n{e}"
)
def invoke_api() -> None:
def find_port(port: int) -> int:
"""Find a port not in use starting at given port"""
# Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
# https://github.com/WaylonWalker
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
if s.connect_ex(("localhost", port)) == 0:
return find_port(port=port + 1)
else:
return port
if app_config.dev_reload:
try:
import jurigged
except ImportError as e:
logger.error(
'Can\'t start `--dev_reload` because jurigged is not found; `pip install -e ".[dev]"` to include development dependencies.',
exc_info=e,
)
else:
jurigged.watch(logger=InvokeAILogger.get_logger(name="jurigged").info)
port = find_port(app_config.port)
if port != app_config.port:
logger.warn(f"Port {app_config.port} in use, using port {port}")
check_cudnn(logger)
# Start our own event loop for eventing usage
loop = asyncio.new_event_loop()
config = uvicorn.Config(
app=app,
host=app_config.host,
port=port,
loop="asyncio",
log_level=app_config.log_level,
ssl_certfile=app_config.ssl_certfile,
ssl_keyfile=app_config.ssl_keyfile,
)
server = uvicorn.Server(config)
# replace uvicorn's loggers with InvokeAI's for consistent appearance
for logname in ["uvicorn.access", "uvicorn"]:
log = InvokeAILogger.get_logger(logname)
log.handlers.clear()
for ch in logger.handlers:
log.addHandler(ch)
loop.run_until_complete(server.serve())
if __name__ == "__main__":
invoke_api()