71 lines
3.1 KiB
Python
71 lines
3.1 KiB
Python
import requests
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from .common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
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class ReimagineNode():
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@classmethod
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def INPUT_TYPES(self):
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return {
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"required": {
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"api_key": ("STRING", ),
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"prompt": ("STRING",),
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},
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"optional": {
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"seed": ("INT", {"default": -1}),
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"steps_num": ("INT", {"default": 12}), # if used with tailored, possibly get this from the tailored model info node
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"structure_ref_influence": ("FLOAT", {"default": 0.75}),
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"fast": ("INT", {"default": 0}), # if used with tailored, possibly get this from the tailored model info node
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"structure_image": ("IMAGE", ),
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"tailored_model_id": ("STRING", ),
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"tailored_model_influence": ("FLOAT", {"default": 0.5}),
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"tailored_generation_prefix": ("STRING",), # if used with tailored, possibly get this from the tailored model info node
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"content_moderation": ("INT", {"default": 0}),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("output_image",)
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CATEGORY = "API Nodes"
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FUNCTION = "execute" # This is the method that will be executed
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def __init__(self):
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self.api_url = "https://engine.prod.bria-api.com/v1/reimagine" #"http://0.0.0.0:5000/v1/reimagine"
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def execute(
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self, api_key, prompt, seed,
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steps_num, fast, structure_ref_influence, structure_image=None,
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tailored_model_id=None, tailored_model_influence=None, tailored_generation_prefix=None,
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content_moderation=0,
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):
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api_key = deserialize_and_get_comfy_key(api_key)
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payload = {
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"prompt": tailored_generation_prefix + prompt,
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"num_results": 1,
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"sync": True,
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"seed": seed,
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"steps_num": steps_num,
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"include_generation_prefix": False,
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"content_moderation": content_moderation,
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}
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if structure_image is not None:
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structure_image = preprocess_image(structure_image)
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structure_image = image_to_base64(structure_image)
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payload["structure_image_file"] = structure_image
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payload["structure_ref_influence"] = structure_ref_influence
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if tailored_model_id is not None and tailored_model_id != "":
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payload["tailored_model_id"] = tailored_model_id
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payload["tailored_model_influence"] = tailored_model_influence
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response = requests.post(
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self.api_url,
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json=payload,
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headers={"api_token": api_key}
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)
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if response.status_code == 200:
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response_dict = response.json()
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image_response = requests.get(response_dict['result'][0]["urls"][0])
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result_image = postprocess_image(image_response.content)
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return (result_image,)
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else:
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raise Exception(f"Error: API request failed with status code {response.status_code} and text {response.text}")
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