from threading import Lock from fastapi.responses import JSONResponse from modules import errors, shared, scripts, ui from modules.api import models, script, helpers from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images errors.install() class APIGenerate(): def __init__(self, queue_lock: Lock): self.queue_lock = queue_lock self.default_script_arg_txt2img = [] self.default_script_arg_img2img = [] def sanitize_args(self, args: dict): args = vars(args) args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model args.pop('script_name', None) args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them args.pop('alwayson_scripts', None) args.pop('face', None) args.pop('face_id', None) args.pop('ip_adapter', None) args.pop('save_images', None) return args def sanitize_b64(self, request): def sanitize_str(args: list): for idx in range(0, len(args)): if isinstance(args[idx], str) and len(args[idx]) >= 1000: args[idx] = f"" if hasattr(request, "alwayson_scripts") and request.alwayson_scripts: for script_name in request.alwayson_scripts.keys(): script_obj = request.alwayson_scripts[script_name] if script_obj and "args" in script_obj and script_obj["args"]: sanitize_str(script_obj["args"]) if hasattr(request, "script_args") and request.script_args: sanitize_str(request.script_args) def prepare_face_module(self, request): if hasattr(request, "face") and request.face and not request.script_name and (not request.alwayson_scripts or "face" not in request.alwayson_scripts.keys()): request.script_name = "face" request.script_args = [ request.face.mode, request.face.source_images, request.face.ip_model, request.face.ip_override_sampler, request.face.ip_cache_model, request.face.ip_strength, request.face.ip_structure, request.face.id_strength, request.face.id_conditioning, request.face.id_cache, request.face.pm_trigger, request.face.pm_strength, request.face.pm_start, request.face.fs_cache ] del request.face def post_text2img(self, txt2imgreq: models.ReqTxt2Img): self.prepare_face_module(txt2imgreq) script_runner = scripts.scripts_txt2img if not script_runner.scripts: script_runner.initialize_scripts(False) ui.create_ui(None) if not self.default_script_arg_txt2img: self.default_script_arg_txt2img = script.init_default_script_args(script_runner) selectable_scripts, selectable_script_idx = script.get_selectable_script(txt2imgreq.script_name, script_runner) populate = txt2imgreq.copy(update={ # Override __init__ params "sampler_name": helpers.validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index), "do_not_save_samples": not txt2imgreq.save_images, "do_not_save_grid": not txt2imgreq.save_images, }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on args = self.sanitize_args(populate) send_images = args.pop('send_images', True) with self.queue_lock: p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args) p.scripts = script_runner p.outpath_grids = shared.opts.outdir_grids or shared.opts.outdir_txt2img_grids p.outpath_samples = shared.opts.outdir_samples or shared.opts.outdir_txt2img_samples shared.state.begin('api-txt2img', api=True) script_args = script.init_script_args(p, txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner) if selectable_scripts is not None: processed = scripts.scripts_txt2img.run(p, *script_args) # Need to pass args as list here else: p.script_args = tuple(script_args) # Need to pass args as tuple here processed = process_images(p) shared.state.end(api=False) b64images = list(map(helpers.encode_pil_to_base64, processed.images)) if send_images else [] self.sanitize_b64(txt2imgreq) return models.ResTxt2Img(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) def post_img2img(self, img2imgreq: models.ReqImg2Img): self.prepare_face_module(img2imgreq) init_images = img2imgreq.init_images if init_images is None: return JSONResponse(status_code=400, content={"error": "Init image is none"}) mask = img2imgreq.mask if mask: mask = helpers.decode_base64_to_image(mask) script_runner = scripts.scripts_img2img if not script_runner.scripts: script_runner.initialize_scripts(True) ui.create_ui(None) if not self.default_script_arg_img2img: self.default_script_arg_img2img = script.init_default_script_args(script_runner) selectable_scripts, selectable_script_idx = script.get_selectable_script(img2imgreq.script_name, script_runner) populate = img2imgreq.copy(update={ # Override __init__ params "sampler_name": helpers.validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index), "do_not_save_samples": not img2imgreq.save_images, "do_not_save_grid": not img2imgreq.save_images, "mask": mask, }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on args = self.sanitize_args(populate) send_images = args.pop('send_images', True) with self.queue_lock: p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args) p.init_images = [helpers.decode_base64_to_image(x) for x in init_images] p.scripts = script_runner p.outpath_grids = shared.opts.outdir_img2img_grids p.outpath_samples = shared.opts.outdir_img2img_samples shared.state.begin('api-img2img', api=True) script_args = script.init_script_args(p, img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner) if selectable_scripts is not None: processed = scripts.scripts_img2img.run(p, *script_args) # Need to pass args as list here else: p.script_args = tuple(script_args) # Need to pass args as tuple here processed = process_images(p) shared.state.end(api=False) b64images = list(map(helpers.encode_pil_to_base64, processed.images)) if send_images else [] if not img2imgreq.include_init_images: img2imgreq.init_images = None img2imgreq.mask = None self.sanitize_b64(img2imgreq) return models.ResImg2Img(images=b64images, parameters=vars(img2imgreq), info=processed.js())