Commit 3b6de964 authored by Vespinian's avatar Vespinian
Browse files

Added alwayson_script_name and alwayson_script_args to api 

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
parent 0cc0ee1b

modules/api/api.py

+98 −13
Original line number Diff line number Diff line
@@ -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()

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": "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):

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