Unverified Commit 92464233 authored by AUTOMATIC1111's avatar AUTOMATIC1111 Committed by GitHub
Browse files

Merge pull request #12846 from a666/deprecated-types 

Fix some deprecated types
parents c9c457ed b6c1a1bb

modules/api/api.py

+13 −13
Original line number Diff line number Diff line
@@ -29,7 +29,7 @@ from modules.sd_models import unload_model_weights, reload_model_weights, checkp 
from modules.sd_models_config import find_checkpoint_config_near_filename

from modules.realesrgan_model import get_realesrgan_models

from modules import devices

from typing import Dict, List, Any

from typing import Any

import piexif

import piexif.helper

from contextlib import closing
@@ -221,15 +221,15 @@ class Api: 
        self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)

        self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])

        self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)

        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])

        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])

        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=List[models.LatentUpscalerModeItem])

        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])

        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=List[models.SDVaeItem])

        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])

        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])

        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])

        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])

        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=list[models.SamplerItem])

        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=list[models.UpscalerItem])

        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=list[models.LatentUpscalerModeItem])

        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=list[models.SDModelItem])

        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=list[models.SDVaeItem])

        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=list[models.HypernetworkItem])

        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=list[models.FaceRestorerItem])

        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=list[models.RealesrganItem])

        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=list[models.PromptStyleItem])

        self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)

        self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])

        self.add_api_route("/sdapi/v1/refresh-vae", self.refresh_vae, methods=["POST"])
@@ -242,8 +242,8 @@ class Api: 
        self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])

        self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])

        self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)

        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo])

        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=List[models.ExtensionItem])

        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=list[models.ScriptInfo])

        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])



        if shared.cmd_opts.api_server_stop:

            self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -563,7 +563,7 @@ class Api: 


        return options



    def set_config(self, req: Dict[str, Any]):

    def set_config(self, req: dict[str, Any]):

        checkpoint_name = req.get("sd_model_checkpoint", None)

        if checkpoint_name is not None and checkpoint_name not in checkpoint_aliases:

            raise RuntimeError(f"model {checkpoint_name!r} not found")

modules/api/models.py

+11 −13
Original line number Diff line number Diff line 
import inspect



from pydantic import BaseModel, Field, create_model

from typing import Any, Optional

from typing_extensions import Literal

from typing import Any, Optional, Literal

from inflection import underscore

from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img

from modules.shared import sd_upscalers, opts, parser

from typing import Dict, List



API_NOT_ALLOWED = [

    "self",
@@ -130,12 +128,12 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( 
).generate_model()



class TextToImageResponse(BaseModel):

    images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")

    images: list[str] = 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] = Field(default=None, title="Image", description="The generated image in base64 format.")

    parameters: dict

    info: str
@@ -168,10 +166,10 @@ class FileData(BaseModel): 
    name: str = Field(title="File name")



class ExtrasBatchImagesRequest(ExtrasBaseRequest):

    imageList: List[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings")

    imageList: list[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings")



class ExtrasBatchImagesResponse(ExtraBaseResponse):

    images: List[str] = Field(title="Images", description="The generated images in base64 format.")

    images: list[str] = Field(title="Images", description="The generated images in base64 format.")



class PNGInfoRequest(BaseModel):

    image: str = Field(title="Image", description="The base64 encoded PNG image")
@@ -233,8 +231,8 @@ 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")

    aliases: list[str] = Field(title="Aliases")

    options: dict[str, str] = Field(title="Options")



class UpscalerItem(BaseModel):

    name: str = Field(title="Name")
@@ -285,8 +283,8 @@ class EmbeddingItem(BaseModel): 
    vectors: int = Field(title="Vectors", description="The number of vectors in the embedding")



class EmbeddingsResponse(BaseModel):

    loaded: Dict[str, EmbeddingItem] = Field(title="Loaded", description="Embeddings loaded for the current model")

    skipped: Dict[str, EmbeddingItem] = Field(title="Skipped", description="Embeddings skipped for the current model (likely due to architecture incompatibility)")

    loaded: dict[str, EmbeddingItem] = Field(title="Loaded", description="Embeddings loaded for the current model")

    skipped: dict[str, EmbeddingItem] = Field(title="Skipped", description="Embeddings skipped for the current model (likely due to architecture incompatibility)")



class MemoryResponse(BaseModel):

    ram: dict = Field(title="RAM", description="System memory stats")
@@ -304,14 +302,14 @@ class ScriptArg(BaseModel): 
    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")

    step: Optional[Any] = Field(default=None, title="Minimum", description="Step for changing value of the argumentin UI")

    choices: Optional[List[str]] = Field(default=None, title="Choices", description="Possible values for the argument")

    choices: Optional[list[str]] = Field(default=None, title="Choices", description="Possible values for the argument")





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")

    args: List[ScriptArg] = Field(title="Arguments", description="List of script's arguments")

    args: list[ScriptArg] = Field(title="Arguments", description="List of script's arguments")



class ExtensionItem(BaseModel):

    name: str = Field(title="Name", description="Extension name")

modules/gitpython_hack.py

+1 −1
Original line number Diff line number Diff line
@@ -23,7 +23,7 @@ class Git(git.Git): 
        )

        return self._parse_object_header(ret)



    def stream_object_data(self, ref: str) -> tuple[str, str, int, "Git.CatFileContentStream"]:

    def stream_object_data(self, ref: str) -> tuple[str, str, int, Git.CatFileContentStream]:

        # Not really streaming, per se; this buffers the entire object in memory.

        # Shouldn't be a problem for our use case, since we're only using this for

        # object headers (commit objects).

modules/prompt_parser.py

+3 −4
Original line number Diff line number Diff line
@@ -2,7 +2,6 @@ from __future__ import annotations 


import re

from collections import namedtuple

from typing import List

import lark



# a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
@@ -240,14 +239,14 @@ def get_multicond_prompt_list(prompts: SdConditioning | list[str]): 


class ComposableScheduledPromptConditioning:

    def __init__(self, schedules, weight=1.0):

        self.schedules: List[ScheduledPromptConditioning] = schedules

        self.schedules: list[ScheduledPromptConditioning] = schedules

        self.weight: float = weight





class MulticondLearnedConditioning:

    def __init__(self, shape, batch):

        self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS

        self.batch: List[List[ComposableScheduledPromptConditioning]] = batch

        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch





def get_multicond_learned_conditioning(model, prompts, steps, hires_steps=None, use_old_scheduling=False) -> MulticondLearnedConditioning:
@@ -278,7 +277,7 @@ class DictWithShape(dict): 
        return self["crossattn"].shape





def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_step):

def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):

    param = c[0][0].cond

    is_dict = isinstance(param, dict)

modules/script_callbacks.py

+3 −3
Original line number Diff line number Diff line 
import inspect

import os

from collections import namedtuple

from typing import Optional, Dict, Any

from typing import Optional, Any



from fastapi import FastAPI

from gradio import Blocks
@@ -258,7 +258,7 @@ def image_grid_callback(params: ImageGridLoopParams): 
            report_exception(c, 'image_grid')





def infotext_pasted_callback(infotext: str, params: Dict[str, Any]):

def infotext_pasted_callback(infotext: str, params: dict[str, Any]):

    for c in callback_map['callbacks_infotext_pasted']:

        try:

            c.callback(infotext, params)
@@ -449,7 +449,7 @@ def on_infotext_pasted(callback): 
    """register a function to be called before applying an infotext.

    The callback is called with two arguments:

       - infotext: str - raw infotext.

       - result: Dict[str, any] - parsed infotext parameters.

       - result: dict[str, any] - parsed infotext parameters.

    """

    add_callback(callback_map['callbacks_infotext_pasted'], callback)

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