allow api requests to specify do not send images in response
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@ -190,6 +190,9 @@ class Api:
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args = vars(populate)
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args.pop('script_name', None)
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send_images = True if not 'do_not_send_images' in args else not args['do_not_send_images']
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args.pop('do_not_send_images', None)
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with self.queue_lock:
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p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
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@ -203,7 +206,7 @@ class Api:
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processed = process_images(p)
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shared.state.end()
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b64images = list(map(encode_pil_to_base64, processed.images))
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b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
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return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
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@ -232,6 +235,9 @@ class Api:
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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.
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args.pop('script_name', None)
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send_images = True if not 'do_not_send_images' in args else not args['do_not_send_images']
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args.pop('do_not_send_images', None)
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with self.queue_lock:
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p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
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p.init_images = [decode_base64_to_image(x) for x in init_images]
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@ -246,7 +252,7 @@ class Api:
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processed = process_images(p)
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shared.state.end()
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b64images = list(map(encode_pil_to_base64, processed.images))
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b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
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if not img2imgreq.include_init_images:
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img2imgreq.init_images = None
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@ -100,13 +100,27 @@ class PydanticModelGenerator:
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StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
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"StableDiffusionProcessingTxt2Img",
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StableDiffusionProcessingTxt2Img,
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[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}]
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[
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{"key": "sampler_index", "type": str, "default": "Euler"},
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{"key": "script_name", "type": str, "default": None},
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{"key": "script_args", "type": list, "default": []},
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{"key": "do_not_send_images", "type": bool, "default": False}
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]
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).generate_model()
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StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
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"StableDiffusionProcessingImg2Img",
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StableDiffusionProcessingImg2Img,
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[{"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": []}]
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[
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{"key": "sampler_index", "type": str, "default": "Euler"},
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{"key": "init_images", "type": list, "default": None},
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{"key": "denoising_strength", "type": float, "default": 0.75},
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{"key": "mask", "type": str, "default": None},
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{"key": "include_init_images", "type": bool, "default": False, "exclude" : True},
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{"key": "script_name", "type": str, "default": None},
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{"key": "script_args", "type": list, "default": []},
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{"key": "do_not_send_images", "type": bool, "default": False}
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]
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).generate_model()
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class TextToImageResponse(BaseModel):
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