Changed alwayson_script_name and alwayson_script_args api params to 1 alwayson_scripts param dict (2174f58d) · Commits · github_fork / Stable Diffusion Webui

modules/api/api.py

+7 −16

Original line number	Diff line number	Diff line
		@@ -195,22 +195,17 @@ class Api:
		script_args[0] = 0

		# Now check for always on scripts
		if request.alwayson_script_name and (len(request.alwayson_script_name) > 0):
		# always on script with no arg should always run, but if you include their name in the api request, send an empty list for there args
		if not request.alwayson_script_args:
		raise HTTPException(status_code=422, detail=f"Script {request.alwayson_script_name} has no arg list")
		if len(request.alwayson_script_name) != len(request.alwayson_script_args):
		raise HTTPException(status_code=422, detail=f"Number of script names and number of script arg lists doesn't match")

		for alwayson_script_name, alwayson_script_args in zip(request.alwayson_script_name, request.alwayson_script_args):
		if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
		for alwayson_script_name in request.alwayson_scripts.keys():
		alwayson_script = self.get_script(alwayson_script_name, script_runner)
		if alwayson_script == None:
		raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found")
		# Selectable script in always on script param check
		if alwayson_script.alwayson == False:
		raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params")
		if alwayson_script_args != []:
		script_args[alwayson_script.args_from:alwayson_script.args_to] = alwayson_script_args
		# always on script with no arg should always run so you don't really need to add them to the requests
		if "args" in request.alwayson_scripts[alwayson_script_name]:
		script_args[alwayson_script.args_from:alwayson_script.args_to] = request.alwayson_scripts[alwayson_script_name]["args"]
		return script_args

		def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
		@@ -226,15 +221,13 @@ class Api:
		"do_not_save_grid": True
		}
		)

		if populate.sampler_name:
		populate.sampler_index = None # prevent a warning later on

		args = vars(populate)
		args.pop('script_name', None)
		args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
		args.pop('alwayson_script_name', None)
		args.pop('alwayson_script_args', None)
		args.pop('alwayson_scripts', None)

		script_args = self.init_script_args(txt2imgreq, selectable_scripts, selectable_script_idx, script_runner)

		@@ -279,7 +272,6 @@ class Api:
		"mask": mask
		}
		)

		if populate.sampler_name:
		populate.sampler_index = None # prevent a warning later on

		@@ -287,8 +279,7 @@ class Api:
		args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
		args.pop('script_name', None)
		args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
		args.pop('alwayson_script_name', None)
		args.pop('alwayson_script_args', None)
		args.pop('alwayson_scripts', None)

		script_args = self.init_script_args(img2imgreq, selectable_scripts, selectable_script_idx, script_runner)

modules/api/models.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -100,13 +100,13 @@ class PydanticModelGenerator:
		StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
		"StableDiffusionProcessingTxt2Img",
		StableDiffusionProcessingTxt2Img,
		[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_script_name", "type": list, "default": []}, {"key": "alwayson_script_args", "type": list, "default": []}]
		[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_scripts", "type": dict, "default": {}}]
		).generate_model()

		StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
		"StableDiffusionProcessingImg2Img",
		StableDiffusionProcessingImg2Img,
		[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_script_name", "type": list, "default": []}, {"key": "alwayson_script_args", "type": list, "default": []}]
		[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_scripts", "type": dict, "default": {}}]
		).generate_model()

		class TextToImageResponse(BaseModel):

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