mirror of
https://github.com/lllyasviel/stable-diffusion-webui-forge.git
synced 2026-03-04 12:39:48 +00:00
Gradio 4 + WebUI 1.10
This commit is contained in:
layerdiffusion
@@ -1,6 +1,6 @@
|
||||
import inspect
|
||||
|
||||
from pydantic import BaseModel, Field, create_model
|
||||
from pydantic import BaseModel, Field, create_model, ConfigDict
|
||||
from typing import Any, Optional, Literal
|
||||
from inflection import underscore
|
||||
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
|
||||
@@ -92,9 +92,7 @@ class PydanticModelGenerator:
|
||||
fields = {
|
||||
d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias, exclude=d.field_exclude)) for d in self._model_def
|
||||
}
|
||||
DynamicModel = create_model(self._model_name, **fields)
|
||||
DynamicModel.__config__.allow_population_by_field_name = True
|
||||
DynamicModel.__config__.allow_mutation = True
|
||||
DynamicModel = create_model(self._model_name, __config__=ConfigDict(populate_by_name=True, frozen=False), **fields)
|
||||
return DynamicModel
|
||||
|
||||
StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
|
||||
@@ -102,13 +100,13 @@ StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
|
||||
StableDiffusionProcessingTxt2Img,
|
||||
[
|
||||
{"key": "sampler_index", "type": str, "default": "Euler"},
|
||||
{"key": "script_name", "type": str, "default": None},
|
||||
{"key": "script_name", "type": str | None, "default": None},
|
||||
{"key": "script_args", "type": list, "default": []},
|
||||
{"key": "send_images", "type": bool, "default": True},
|
||||
{"key": "save_images", "type": bool, "default": False},
|
||||
{"key": "alwayson_scripts", "type": dict, "default": {}},
|
||||
{"key": "force_task_id", "type": str, "default": None},
|
||||
{"key": "infotext", "type": str, "default": None},
|
||||
{"key": "force_task_id", "type": str | None, "default": None},
|
||||
{"key": "infotext", "type": str | None, "default": None},
|
||||
]
|
||||
).generate_model()
|
||||
|
||||
@@ -117,27 +115,27 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
|
||||
StableDiffusionProcessingImg2Img,
|
||||
[
|
||||
{"key": "sampler_index", "type": str, "default": "Euler"},
|
||||
{"key": "init_images", "type": list, "default": None},
|
||||
{"key": "init_images", "type": list | None, "default": None},
|
||||
{"key": "denoising_strength", "type": float, "default": 0.75},
|
||||
{"key": "mask", "type": str, "default": None},
|
||||
{"key": "mask", "type": str | None, "default": None},
|
||||
{"key": "include_init_images", "type": bool, "default": False, "exclude" : True},
|
||||
{"key": "script_name", "type": str, "default": None},
|
||||
{"key": "script_name", "type": str | None, "default": None},
|
||||
{"key": "script_args", "type": list, "default": []},
|
||||
{"key": "send_images", "type": bool, "default": True},
|
||||
{"key": "save_images", "type": bool, "default": False},
|
||||
{"key": "alwayson_scripts", "type": dict, "default": {}},
|
||||
{"key": "force_task_id", "type": str, "default": None},
|
||||
{"key": "infotext", "type": str, "default": None},
|
||||
{"key": "force_task_id", "type": str | None, "default": None},
|
||||
{"key": "infotext", "type": str | None, "default": None},
|
||||
]
|
||||
).generate_model()
|
||||
|
||||
class TextToImageResponse(BaseModel):
|
||||
images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
images: list[str] | None = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
parameters: dict
|
||||
info: str
|
||||
|
||||
class ImageToImageResponse(BaseModel):
|
||||
images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
images: list[str] | None = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
parameters: dict
|
||||
info: str
|
||||
|
||||
@@ -147,7 +145,7 @@ class ExtrasBaseRequest(BaseModel):
|
||||
gfpgan_visibility: float = Field(default=0, title="GFPGAN Visibility", ge=0, le=1, allow_inf_nan=False, description="Sets the visibility of GFPGAN, values should be between 0 and 1.")
|
||||
codeformer_visibility: float = Field(default=0, title="CodeFormer Visibility", ge=0, le=1, allow_inf_nan=False, description="Sets the visibility of CodeFormer, values should be between 0 and 1.")
|
||||
codeformer_weight: float = Field(default=0, title="CodeFormer Weight", ge=0, le=1, allow_inf_nan=False, description="Sets the weight of CodeFormer, values should be between 0 and 1.")
|
||||
upscaling_resize: float = Field(default=2, title="Upscaling Factor", ge=1, le=8, description="By how much to upscale the image, only used when resize_mode=0.")
|
||||
upscaling_resize: float = Field(default=2, title="Upscaling Factor", gt=0, description="By how much to upscale the image, only used when resize_mode=0.")
|
||||
upscaling_resize_w: int = Field(default=512, title="Target Width", ge=1, description="Target width for the upscaler to hit. Only used when resize_mode=1.")
|
||||
upscaling_resize_h: int = Field(default=512, title="Target Height", ge=1, description="Target height for the upscaler to hit. Only used when resize_mode=1.")
|
||||
upscaling_crop: bool = Field(default=True, title="Crop to fit", description="Should the upscaler crop the image to fit in the chosen size?")
|
||||
@@ -163,7 +161,7 @@ class ExtrasSingleImageRequest(ExtrasBaseRequest):
|
||||
image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
|
||||
|
||||
class ExtrasSingleImageResponse(ExtraBaseResponse):
|
||||
image: str = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
image: str | None = Field(default=None, title="Image", description="The generated image in base64 format.")
|
||||
|
||||
class FileData(BaseModel):
|
||||
data: str = Field(title="File data", description="Base64 representation of the file")
|
||||
@@ -190,15 +188,15 @@ class ProgressResponse(BaseModel):
|
||||
progress: float = Field(title="Progress", description="The progress with a range of 0 to 1")
|
||||
eta_relative: float = Field(title="ETA in secs")
|
||||
state: dict = Field(title="State", description="The current state snapshot")
|
||||
current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
|
||||
textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
|
||||
current_image: str | None = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
|
||||
textinfo: str | None = Field(default=None, title="Info text", description="Info text used by WebUI.")
|
||||
|
||||
class InterrogateRequest(BaseModel):
|
||||
image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
|
||||
model: str = Field(default="clip", title="Model", description="The interrogate model used.")
|
||||
|
||||
class InterrogateResponse(BaseModel):
|
||||
caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")
|
||||
caption: str | None = Field(default=None, title="Caption", description="The generated caption for the image.")
|
||||
|
||||
class TrainResponse(BaseModel):
|
||||
info: str = Field(title="Train info", description="Response string from train embedding or hypernetwork task.")
|
||||
@@ -223,7 +221,7 @@ _options = vars(parser)['_option_string_actions']
|
||||
for key in _options:
|
||||
if(_options[key].dest != 'help'):
|
||||
flag = _options[key]
|
||||
_type = str
|
||||
_type = str | None
|
||||
if _options[key].default is not None:
|
||||
_type = type(_options[key].default)
|
||||
flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))})
|
||||
@@ -233,9 +231,19 @@ FlagsModel = create_model("Flags", **flags)
|
||||
class SamplerItem(BaseModel):
|
||||
name: str = Field(title="Name")
|
||||
aliases: list[str] = Field(title="Aliases")
|
||||
options: dict[str, str] = Field(title="Options")
|
||||
options: dict[str, Any] = Field(title="Options")
|
||||
|
||||
class SchedulerItem(BaseModel):
|
||||
name: str = Field(title="Name")
|
||||
label: str = Field(title="Label")
|
||||
aliases: Optional[list[str]] = Field(title="Aliases")
|
||||
default_rho: Optional[float] = Field(title="Default Rho")
|
||||
need_inner_model: Optional[bool] = Field(title="Needs Inner Model")
|
||||
|
||||
class UpscalerItem(BaseModel):
|
||||
class Config:
|
||||
protected_namespaces = ()
|
||||
|
||||
name: str = Field(title="Name")
|
||||
model_name: Optional[str] = Field(title="Model Name")
|
||||
model_path: Optional[str] = Field(title="Path")
|
||||
@@ -246,6 +254,9 @@ class LatentUpscalerModeItem(BaseModel):
|
||||
name: str = Field(title="Name")
|
||||
|
||||
class SDModelItem(BaseModel):
|
||||
class Config:
|
||||
protected_namespaces = ()
|
||||
|
||||
title: str = Field(title="Title")
|
||||
model_name: str = Field(title="Model Name")
|
||||
hash: Optional[str] = Field(title="Short hash")
|
||||
@@ -254,6 +265,9 @@ class SDModelItem(BaseModel):
|
||||
config: Optional[str] = Field(title="Config file")
|
||||
|
||||
class SDVaeItem(BaseModel):
|
||||
class Config:
|
||||
protected_namespaces = ()
|
||||
|
||||
model_name: str = Field(title="Model Name")
|
||||
filename: str = Field(title="Filename")
|
||||
|
||||
@@ -293,12 +307,12 @@ class MemoryResponse(BaseModel):
|
||||
|
||||
|
||||
class ScriptsList(BaseModel):
|
||||
txt2img: list = Field(default=None, title="Txt2img", description="Titles of scripts (txt2img)")
|
||||
img2img: list = Field(default=None, title="Img2img", description="Titles of scripts (img2img)")
|
||||
txt2img: list | None = Field(default=None, title="Txt2img", description="Titles of scripts (txt2img)")
|
||||
img2img: list | None = Field(default=None, title="Img2img", description="Titles of scripts (img2img)")
|
||||
|
||||
|
||||
class ScriptArg(BaseModel):
|
||||
label: str = Field(default=None, title="Label", description="Name of the argument in UI")
|
||||
label: str | None = Field(default=None, title="Label", description="Name of the argument in UI")
|
||||
value: Optional[Any] = Field(default=None, title="Value", description="Default value of the argument")
|
||||
minimum: Optional[Any] = Field(default=None, title="Minimum", description="Minimum allowed value for the argumentin UI")
|
||||
maximum: Optional[Any] = Field(default=None, title="Minimum", description="Maximum allowed value for the argumentin UI")
|
||||
@@ -307,9 +321,9 @@ class ScriptArg(BaseModel):
|
||||
|
||||
|
||||
class ScriptInfo(BaseModel):
|
||||
name: str = Field(default=None, title="Name", description="Script name")
|
||||
is_alwayson: bool = Field(default=None, title="IsAlwayson", description="Flag specifying whether this script is an alwayson script")
|
||||
is_img2img: bool = Field(default=None, title="IsImg2img", description="Flag specifying whether this script is an img2img script")
|
||||
name: str | None = Field(default=None, title="Name", description="Script name")
|
||||
is_alwayson: bool | None = Field(default=None, title="IsAlwayson", description="Flag specifying whether this script is an alwayson script")
|
||||
is_img2img: bool | None = Field(default=None, title="IsImg2img", description="Flag specifying whether this script is an img2img script")
|
||||
args: list[ScriptArg] = Field(title="Arguments", description="List of script's arguments")
|
||||
|
||||
class ExtensionItem(BaseModel):
|
||||
|
||||
Reference in New Issue
Block a user