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Added alwayson_script_name and alwayson_script_args to api

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Added 2 additional possible entries in the api request: alwayson_script_name, a string list, and, alwayson_script_args, a list of list containing the args of each script. This allows us to send args to always on script and keep backwards compatibility with old script_name and script_arg api params
This commit is contained in:
Vespinian 2023-02-26 19:17:58 -05:00
parent 0cc0ee1bcb
commit 3b6de96467
2 changed files with 100 additions and 15 deletions
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111
modules/api/api.py
View file

@ -163,20 +163,26 @@ class Api:
raise HTTPException(status_code=401, detail="Incorrect username or password", headers={"WWW-Authenticate": "Basic"})
def get_script(self, script_name, script_runner):
if script_name is None:
def get_selectable_script(self, script_name, script_runner):
if script_name is None or script_name == "":
return None, None
if not script_runner.scripts:
script_runner.initialize_scripts(False)
ui.create_ui()
script_idx = script_name_to_index(script_name, script_runner.selectable_scripts)
script = script_runner.selectable_scripts[script_idx]
return script, script_idx
def get_script(self, script_name, script_runner):
for script in script_runner.scripts:
if script_name.lower() == script.title().lower():
return script
return None
def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
script, script_idx = self.get_script(txt2imgreq.script_name, scripts.scripts_txt2img)
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
ui.create_ui()
api_selectable_scripts, api_selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner)
populate = txt2imgreq.copy(update={ # Override __init__ params
"sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index),
@ -184,22 +190,59 @@ 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 later with script_args
args.pop('alwayson_script_name', None)
args.pop('alwayson_script_args', None)
#find max idx from the scripts in runner and generate a none array to init script_args
last_arg_index = 1
for script in script_runner.scripts:
if last_arg_index < script.args_to:
last_arg_index = script.args_to
# None everywhere exepct position 0 to initialize script args
script_args = [None]*last_arg_index
# position 0 in script_arg is the idx+1 of the selectable script that is going to be run
if api_selectable_scripts:
script_args[api_selectable_scripts.args_from:api_selectable_scripts.args_to] = txt2imgreq.script_args
script_args[0] = api_selectable_script_idx + 1
else:
# if 0 then none
script_args[0] = 0
# Now check for always on scripts
if len(txt2imgreq.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 len(txt2imgreq.alwayson_script_name) != len(txt2imgreq.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(txt2imgreq.alwayson_script_name, txt2imgreq.alwayson_script_args):
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
with self.queue_lock:
p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
p.scripts = script_runner
shared.state.begin()
if script is not None:
if api_selectable_scripts != None:
p.script_args = script_args
p.outpath_grids = opts.outdir_txt2img_grids
p.outpath_samples = opts.outdir_txt2img_samples
p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args
processed = scripts.scripts_txt2img.run(p, *p.script_args)
else:
p.script_args = tuple(script_args)
processed = process_images(p)
shared.state.end()
@ -212,12 +255,16 @@ class Api:
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
script, script_idx = self.get_script(img2imgreq.script_name, scripts.scripts_img2img)
mask = img2imgreq.mask
if mask:
mask = decode_base64_to_image(mask)
script_runner = scripts.scripts_img2img
if not script_runner.scripts:
script_runner.initialize_scripts(True)
ui.create_ui()
api_selectable_scripts, api_selectable_script_idx = self.get_selectable_script(img2imgreq.script_name, script_runner)
populate = img2imgreq.copy(update={ # Override __init__ params
"sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
"do_not_save_samples": True,
@ -225,24 +272,62 @@ class Api:
"mask": mask
}
)
if populate.sampler_name:
populate.sampler_index = None # prevent a warning later on
args = vars(populate)
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 later with script_args
args.pop('alwayson_script_name', None)
args.pop('alwayson_script_args', None)
#find max idx from the scripts in runner and generate a none array to init script_args
last_arg_index = 1
for script in script_runner.scripts:
if last_arg_index < script.args_to:
last_arg_index = script.args_to
# None everywhere exepct position 0 to initialize script args
script_args = [None]*last_arg_index
# position 0 in script_arg is the idx+1 of the selectable script that is going to be run
if api_selectable_scripts:
script_args[api_selectable_scripts.args_from:api_selectable_scripts.args_to] = img2imgreq.script_args
script_args[0] = api_selectable_script_idx + 1
else:
# if 0 then none
script_args[0] = 0
# Now check for always on scripts
if len(img2imgreq.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 len(img2imgreq.alwayson_script_name) != len(img2imgreq.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(img2imgreq.alwayson_script_name, img2imgreq.alwayson_script_args):
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
with self.queue_lock:
p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
p.init_images = [decode_base64_to_image(x) for x in init_images]
p.scripts = script_runner
shared.state.begin()
if script is not None:
if api_selectable_scripts != None:
p.script_args = script_args
p.outpath_grids = opts.outdir_img2img_grids
p.outpath_samples = opts.outdir_img2img_samples
p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args
processed = scripts.scripts_img2img.run(p, *p.script_args)
else:
p.script_args = tuple(script_args)
processed = process_images(p)
shared.state.end()

4
modules/api/models.py
View file

@ -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": "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": []}]
).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": "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": []}]
).generate_model()
class TextToImageResponse(BaseModel):