InvokeAI/invokeai/app/api/routers/app_info.py

185 lines
6.2 KiB
Python

import typing
from enum import Enum
from importlib.metadata import PackageNotFoundError, version
from pathlib import Path
from platform import python_version
from typing import Optional
import torch
from fastapi import Body
from fastapi.routing import APIRouter
from pydantic import BaseModel, Field
from invokeai.app.api.dependencies import ApiDependencies
from invokeai.app.invocations.upscale import ESRGAN_MODELS
from invokeai.app.services.invocation_cache.invocation_cache_common import InvocationCacheStatus
from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch
from invokeai.backend.util.logging import logging
from invokeai.version import __version__
class LogLevel(int, Enum):
NotSet = logging.NOTSET
Debug = logging.DEBUG
Info = logging.INFO
Warning = logging.WARNING
Error = logging.ERROR
Critical = logging.CRITICAL
class Upscaler(BaseModel):
upscaling_method: str = Field(description="Name of upscaling method")
upscaling_models: list[str] = Field(description="List of upscaling models for this method")
app_router = APIRouter(prefix="/v1/app", tags=["app"])
class AppVersion(BaseModel):
"""App Version Response"""
version: str = Field(description="App version")
class AppDependencyVersions(BaseModel):
"""App depencency Versions Response"""
accelerate: str = Field(description="accelerate version")
compel: str = Field(description="compel version")
cuda: Optional[str] = Field(description="CUDA version")
diffusers: str = Field(description="diffusers version")
numpy: str = Field(description="Numpy version")
opencv: str = Field(description="OpenCV version")
onnx: str = Field(description="ONNX version")
pillow: str = Field(description="Pillow (PIL) version")
python: str = Field(description="Python version")
torch: str = Field(description="PyTorch version")
torchvision: str = Field(description="PyTorch Vision version")
transformers: str = Field(description="transformers version")
xformers: Optional[str] = Field(description="xformers version")
class AppConfig(BaseModel):
"""App Config Response"""
infill_methods: list[str] = Field(description="List of available infill methods")
upscaling_methods: list[Upscaler] = Field(description="List of upscaling methods")
nsfw_methods: list[str] = Field(description="List of NSFW checking methods")
watermarking_methods: list[str] = Field(description="List of invisible watermark methods")
@app_router.get("/version", operation_id="app_version", status_code=200, response_model=AppVersion)
async def get_version() -> AppVersion:
return AppVersion(version=__version__)
@app_router.get("/app_deps", operation_id="get_app_deps", status_code=200, response_model=AppDependencyVersions)
async def get_app_deps() -> AppDependencyVersions:
try:
xformers = version("xformers")
except PackageNotFoundError:
xformers = None
return AppDependencyVersions(
accelerate=version("accelerate"),
compel=version("compel"),
cuda=torch.version.cuda,
diffusers=version("diffusers"),
numpy=version("numpy"),
opencv=version("opencv-python"),
onnx=version("onnx"),
pillow=version("pillow"),
python=python_version(),
torch=torch.version.__version__,
torchvision=version("torchvision"),
transformers=version("transformers"),
xformers=xformers,
)
@app_router.get("/config", operation_id="get_config", status_code=200, response_model=AppConfig)
async def get_config() -> AppConfig:
infill_methods = ["tile", "lama", "cv2", "color"] # TODO: add mosaic back
if PatchMatch.patchmatch_available():
infill_methods.append("patchmatch")
upscaling_models = []
for model in typing.get_args(ESRGAN_MODELS):
upscaling_models.append(str(Path(model).stem))
upscaler = Upscaler(upscaling_method="esrgan", upscaling_models=upscaling_models)
nsfw_methods = ["nsfw_checker"]
watermarking_methods = ["invisible_watermark"]
return AppConfig(
infill_methods=infill_methods,
upscaling_methods=[upscaler],
nsfw_methods=nsfw_methods,
watermarking_methods=watermarking_methods,
)
@app_router.get(
"/logging",
operation_id="get_log_level",
responses={200: {"description": "The operation was successful"}},
response_model=LogLevel,
)
async def get_log_level() -> LogLevel:
"""Returns the log level"""
return LogLevel(ApiDependencies.invoker.services.logger.level)
@app_router.post(
"/logging",
operation_id="set_log_level",
responses={200: {"description": "The operation was successful"}},
response_model=LogLevel,
)
async def set_log_level(
level: LogLevel = Body(description="New log verbosity level"),
) -> LogLevel:
"""Sets the log verbosity level"""
ApiDependencies.invoker.services.logger.setLevel(level)
return LogLevel(ApiDependencies.invoker.services.logger.level)
@app_router.delete(
"/invocation_cache",
operation_id="clear_invocation_cache",
responses={200: {"description": "The operation was successful"}},
)
async def clear_invocation_cache() -> None:
"""Clears the invocation cache"""
ApiDependencies.invoker.services.invocation_cache.clear()
@app_router.put(
"/invocation_cache/enable",
operation_id="enable_invocation_cache",
responses={200: {"description": "The operation was successful"}},
)
async def enable_invocation_cache() -> None:
"""Clears the invocation cache"""
ApiDependencies.invoker.services.invocation_cache.enable()
@app_router.put(
"/invocation_cache/disable",
operation_id="disable_invocation_cache",
responses={200: {"description": "The operation was successful"}},
)
async def disable_invocation_cache() -> None:
"""Clears the invocation cache"""
ApiDependencies.invoker.services.invocation_cache.disable()
@app_router.get(
"/invocation_cache/status",
operation_id="get_invocation_cache_status",
responses={200: {"model": InvocationCacheStatus}},
)
async def get_invocation_cache_status() -> InvocationCacheStatus:
"""Clears the invocation cache"""
return ApiDependencies.invoker.services.invocation_cache.get_status()