stable-diffusion-webui/modules/api/processing.py

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from inflection import underscore
from typing import Any, Dict, Optional
from pydantic import BaseModel, Field, create_model
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from modules.processing import StableDiffusionProcessingTxt2Img
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import inspect
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API_NOT_ALLOWED = [
"self",
"kwargs",
"sd_model",
"outpath_samples",
"outpath_grids",
"sampler_index",
"do_not_save_samples",
"do_not_save_grid",
"extra_generation_params",
"overlay_images",
"do_not_reload_embeddings",
"seed_enable_extras",
"prompt_for_display",
"sampler_noise_scheduler_override",
"ddim_discretize"
]
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class ModelDef(BaseModel):
"""Assistance Class for Pydantic Dynamic Model Generation"""
field: str
field_alias: str
field_type: Any
field_value: Any
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class PydanticModelGenerator:
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"""
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Takes in created classes and stubs them out in a way FastAPI/Pydantic is happy about:
source_data is a snapshot of the default values produced by the class
params are the names of the actual keys required by __init__
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"""
def __init__(
self,
model_name: str = None,
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class_instance = None,
additional_fields = None,
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):
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def field_type_generator(k, v):
# field_type = str if not overrides.get(k) else overrides[k]["type"]
# print(k, v.annotation, v.default)
field_type = v.annotation
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return Optional[field_type]
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def merge_class_params(class_):
all_classes = list(filter(lambda x: x is not object, inspect.getmro(class_)))
parameters = {}
for classes in all_classes:
parameters = {**parameters, **inspect.signature(classes.__init__).parameters}
return parameters
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self._model_name = model_name
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self._class_data = merge_class_params(class_instance)
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self._model_def = [
ModelDef(
field=underscore(k),
field_alias=k,
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field_type=field_type_generator(k, v),
field_value=v.default
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)
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for (k,v) in self._class_data.items() if k not in API_NOT_ALLOWED
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]
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for fields in additional_fields:
self._model_def.append(ModelDef(
field=underscore(fields["key"]),
field_alias=fields["key"],
field_type=fields["type"],
field_value=fields["default"]))
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def generate_model(self):
"""
Creates a pydantic BaseModel
from the json and overrides provided at initialization
"""
fields = {
d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias)) for d in self._model_def
}
DynamicModel = create_model(self._model_name, **fields)
DynamicModel.__config__.allow_population_by_field_name = True
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DynamicModel.__config__.allow_mutation = True
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return DynamicModel
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StableDiffusionProcessingAPI = PydanticModelGenerator(
"StableDiffusionProcessingTxt2Img",
StableDiffusionProcessingTxt2Img,
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[{"key": "sampler_index", "type": str, "default": "Euler"}]
).generate_model()