Files
Bria-AI-ComfyUI-BRIA-API/nodes/text_2_image_fast_node.py
T
2026-04-14 11:58:02 +00:00

93 lines
4.3 KiB
Python

import requests
from .common import (
bria_json_headers,
image_to_base64,
postprocess_image,
preprocess_image,
)
class Text2ImageFastNode():
@classmethod
def INPUT_TYPES(self):
return {
"required": {
"api_key": ("STRING", ),
},
"optional": {
"prompt": ("STRING",),
"aspect_ratio": (["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"], {"default": "4:3"}),
"seed": ("INT", {"default": -1}),
"steps_num": ("INT", {"default": 8}),
"prompt_enhancement": ("INT", {"default": 0}),
"guidance_method_1": (["controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid"], {"default": "controlnet_canny"}),
"guidance_method_1_scale": ("FLOAT", {"default": 1.0}),
"guidance_method_1_image": ("IMAGE", ),
"guidance_method_2": (["controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid"], {"default": "controlnet_canny"}),
"guidance_method_2_scale": ("FLOAT", {"default": 1.0}),
"guidance_method_2_image": ("IMAGE", ),
"image_prompt_mode": (["regular", "style_only"], {"default": "regular"}),
"image_prompt_image": ("IMAGE", ),
"image_prompt_scale": ("FLOAT", {"default": 1.0}),
"content_moderation": ("INT", {"default": 0}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/fast/2.3" #"http://0.0.0.0:5000/v1/text-to-image/fast/2.3"
def execute(
self, api_key, prompt, aspect_ratio, seed,
steps_num, prompt_enhancement,
guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
content_moderation=0,
):
payload = {
"prompt": prompt,
"num_results": 1,
"aspect_ratio": aspect_ratio,
"sync": True,
"seed": seed,
"steps_num": steps_num,
"prompt_enhancement": prompt_enhancement,
"content_moderation": content_moderation,
}
if guidance_method_1_image is not None:
guidance_method_1_image = preprocess_image(guidance_method_1_image)
guidance_method_1_image = image_to_base64(guidance_method_1_image)
payload["guidance_method_1"] = guidance_method_1
payload["guidance_method_1_scale"] = guidance_method_1_scale
payload["guidance_method_1_image_file"] = guidance_method_1_image
if guidance_method_2_image is not None:
guidance_method_2_image = preprocess_image(guidance_method_2_image)
guidance_method_2_image = image_to_base64(guidance_method_2_image)
payload["guidance_method_2"] = guidance_method_2
payload["guidance_method_2_scale"] = guidance_method_2_scale
payload["guidance_method_2_image_file"] = guidance_method_2_image
if image_prompt_image is not None:
image_prompt_image = preprocess_image(image_prompt_image)
image_prompt_image = image_to_base64(image_prompt_image)
payload["image_prompt_mode"] = image_prompt_mode
payload["image_prompt_file"] = image_prompt_image
payload["image_prompt_scale"] = image_prompt_scale
response = requests.post(
self.api_url,
json=payload,
headers=bria_json_headers(api_key),
)
if response.status_code == 200:
response_dict = response.json()
image_response = requests.get(response_dict['result'][0]["urls"][0])
result_image = postprocess_image(image_response.content)
return (result_image,)
else:
raise Exception(f"Error: API request failed with status code {response.status_code} and text {response.text}")