import base64 import io import time import uvicorn from threading import Lock from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image from fastapi import APIRouter, Depends, FastAPI, HTTPException from fastapi.security import HTTPBasic, HTTPBasicCredentials from secrets import compare_digest import modules.shared as shared from modules import sd_samplers, deepbooru from modules.api.models import * from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images from modules.extras import run_extras, run_pnginfo from PIL import PngImagePlugin from modules.sd_models import checkpoints_list from modules.realesrgan_model import get_realesrgan_models from typing import List def upscaler_to_index(name: str): try: return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) except: raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}") def validate_sampler_name(name): config = sd_samplers.all_samplers_map.get(name, None) if config is None: raise HTTPException(status_code=404, detail="Sampler not found") return name def setUpscalers(req: dict): reqDict = vars(req) reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1) reqDict['extras_upscaler_2'] = upscaler_to_index(req.upscaler_2) reqDict.pop('upscaler_1') reqDict.pop('upscaler_2') return reqDict def encode_pil_to_base64(image): with io.BytesIO() as output_bytes: # Copy any text-only metadata use_metadata = False metadata = PngImagePlugin.PngInfo() for key, value in image.info.items(): if isinstance(key, str) and isinstance(value, str): metadata.add_text(key, value) use_metadata = True image.save( output_bytes, "PNG", pnginfo=(metadata if use_metadata else None) ) bytes_data = output_bytes.getvalue() return base64.b64encode(bytes_data) class Api: def __init__(self, app: FastAPI, queue_lock: Lock): if shared.cmd_opts.api_auth: self.credenticals = dict() for auth in shared.cmd_opts.api_auth.split(","): user, password = auth.split(":") self.credenticals[user] = password self.router = APIRouter() self.app = app self.queue_lock = queue_lock self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse) self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse) self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse) self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse) self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse) self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse) self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"]) self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"]) self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"]) self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=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=FlagsModel) self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem]) self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem]) self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem]) self.add_api_route("/sdapi/v1/prompt-styles", self.get_promp_styles, methods=["GET"], response_model=List[PromptStyleItem]) self.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str]) self.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem]) def add_api_route(self, path: str, endpoint, **kwargs): if shared.cmd_opts.api_auth: return self.app.add_api_route(path, endpoint, dependencies=[Depends(self.auth)], **kwargs) return self.app.add_api_route(path, endpoint, **kwargs) def auth(self, credenticals: HTTPBasicCredentials = Depends(HTTPBasic())): if credenticals.username in self.credenticals: if compare_digest(credenticals.password, self.credenticals[credenticals.username]): return True raise HTTPException(status_code=401, detail="Incorrect username or password", headers={"WWW-Authenticate": "Basic"}) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): populate = txt2imgreq.copy(update={ # Override __init__ params "sd_model": shared.sd_model, "sampler_name": validate_sampler_name(txt2imgreq.sampler_index), "do_not_save_samples": True, "do_not_save_grid": True } ) p = StableDiffusionProcessingTxt2Img(**vars(populate)) # Override object param shared.state.begin() with self.queue_lock: processed = process_images(p) shared.state.end() b64images = list(map(encode_pil_to_base64, processed.images)) return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI): init_images = img2imgreq.init_images if init_images is None: raise HTTPException(status_code=404, detail="Init image not found") mask = img2imgreq.mask if mask: mask = decode_base64_to_image(mask) populate = img2imgreq.copy(update={ # Override __init__ params "sd_model": shared.sd_model, "sampler_name": validate_sampler_name(img2imgreq.sampler_index), "do_not_save_samples": True, "do_not_save_grid": True, "mask": mask } ) p = StableDiffusionProcessingImg2Img(**vars(populate)) imgs = [] for img in init_images: img = decode_base64_to_image(img) imgs = [img] * p.batch_size p.init_images = imgs shared.state.begin() with self.queue_lock: processed = process_images(p) shared.state.end() b64images = list(map(encode_pil_to_base64, processed.images)) if (not img2imgreq.include_init_images): img2imgreq.init_images = None img2imgreq.mask = None return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) def extras_single_image_api(self, req: ExtrasSingleImageRequest): reqDict = setUpscalers(req) reqDict['image'] = decode_base64_to_image(reqDict['image']) with self.queue_lock: result = run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", **reqDict) return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): reqDict = setUpscalers(req) def prepareFiles(file): file = decode_base64_to_file(file.data, file_path=file.name) file.orig_name = file.name return file reqDict['image_folder'] = list(map(prepareFiles, reqDict['imageList'])) reqDict.pop('imageList') with self.queue_lock: result = run_extras(extras_mode=1, image="", input_dir="", output_dir="", **reqDict) return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) def pnginfoapi(self, req: PNGInfoRequest): if(not req.image.strip()): return PNGInfoResponse(info="") result = run_pnginfo(decode_base64_to_image(req.image.strip())) return PNGInfoResponse(info=result[1]) def progressapi(self, req: ProgressRequest = Depends()): # copy from check_progress_call of ui.py if shared.state.job_count == 0: return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict()) # avoid dividing zero progress = 0.01 if shared.state.job_count > 0: progress += shared.state.job_no / shared.state.job_count if shared.state.sampling_steps > 0: progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps time_since_start = time.time() - shared.state.time_start eta = (time_since_start/progress) eta_relative = eta-time_since_start progress = min(progress, 1) shared.state.set_current_image() current_image = None if shared.state.current_image and not req.skip_current_image: current_image = encode_pil_to_base64(shared.state.current_image) return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image) def interrogateapi(self, interrogatereq: InterrogateRequest): image_b64 = interrogatereq.image if image_b64 is None: raise HTTPException(status_code=404, detail="Image not found") img = decode_base64_to_image(image_b64) img = img.convert('RGB') # Override object param with self.queue_lock: if interrogatereq.model == "clip": processed = shared.interrogator.interrogate(img) elif interrogatereq.model == "deepdanbooru": processed = deepbooru.model.tag(img) else: raise HTTPException(status_code=404, detail="Model not found") return InterrogateResponse(caption=processed) def interruptapi(self): shared.state.interrupt() return {} def skip(self): shared.state.skip() def get_config(self): options = {} for key in shared.opts.data.keys(): metadata = shared.opts.data_labels.get(key) if(metadata is not None): options.update({key: shared.opts.data.get(key, shared.opts.data_labels.get(key).default)}) else: options.update({key: shared.opts.data.get(key, None)}) return options def set_config(self, req: Dict[str, Any]): for k, v in req.items(): shared.opts.set(k, v) shared.opts.save(shared.config_filename) return def get_cmd_flags(self): return vars(shared.cmd_opts) def get_samplers(self): return [{"name": sampler[0], "aliases":sampler[2], "options":sampler[3]} for sampler in sd_samplers.all_samplers] def get_upscalers(self): upscalers = [] for upscaler in shared.sd_upscalers: u = upscaler.scaler upscalers.append({"name":u.name, "model_name":u.model_name, "model_path":u.model_path, "model_url":u.model_url}) return upscalers def get_sd_models(self): return [{"title":x.title, "model_name":x.model_name, "hash":x.hash, "filename": x.filename, "config": x.config} for x in checkpoints_list.values()] def get_hypernetworks(self): return [{"name": name, "path": shared.hypernetworks[name]} for name in shared.hypernetworks] def get_face_restorers(self): return [{"name":x.name(), "cmd_dir": getattr(x, "cmd_dir", None)} for x in shared.face_restorers] def get_realesrgan_models(self): return [{"name":x.name,"path":x.data_path, "scale":x.scale} for x in get_realesrgan_models(None)] def get_promp_styles(self): styleList = [] for k in shared.prompt_styles.styles: style = shared.prompt_styles.styles[k] styleList.append({"name":style[0], "prompt": style[1], "negative_prompr": style[2]}) return styleList def get_artists_categories(self): return shared.artist_db.cats def get_artists(self): return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists] def launch(self, server_name, port): self.app.include_router(self.router) uvicorn.run(self.app, host=server_name, port=port)