nodes/Bria-AI-ComfyUI-BRIA-API
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WAI-4383

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Ubuntu
2026-01-13 19:38:15 +00:00
parent 2c97deb804
commit a970f19bf2
4 changed files with 260 additions and 3 deletions
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__init__.py
+9 -3
View File
@@ -39,7 +39,9 @@ from .nodes import (
VideoIncreaseResolutionNode,
VideoEraseElementsNode,
LoadVideoFramesNode,
PreviewVideoURLNode
PreviewVideoURLNode,
FIBOEditNode,
FIBOEditStructuredInstructionNode
)
# Map the node class to a name used internally by ComfyUI
@@ -84,7 +86,9 @@ NODE_CLASS_MAPPINGS = {
"VideoIncreaseResolutionNode":VideoIncreaseResolutionNode,
"VideoEraseElementsNode":VideoEraseElementsNode,
"LoadVideoFramesNode":LoadVideoFramesNode,
"PreviewVideoURLNode":PreviewVideoURLNode
"PreviewVideoURLNode":PreviewVideoURLNode,
"FIBOEditNode": FIBOEditNode,
"FIBOEditStructuredInstructionNode": FIBOEditStructuredInstructionNode
}
# Map the node display name to the one shown in the ComfyUI node interface
NODE_DISPLAY_NAME_MAPPINGS = {
@@ -128,7 +132,9 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"VideoIncreaseResolutionNode":"Bria Video Increase Resolution",
"VideoEraseElementsNode":"Bria Video Erase Elements",
"LoadVideoFramesNode":"Bria Load Video",
"PreviewVideoURLNode":"Bria Preview Video"
"PreviewVideoURLNode":"Bria Preview Video",
"FIBOEditNode": "FIBO - Edit",
"FIBOEditStructuredInstructionNode": "FIBO - Edit - Structured Instruction"
}
nodes/__init__.py
+3
View File
@@ -41,4 +41,7 @@ from .video_nodes.video_mask_by_prompt_node import VideoMaskByPromptNode
from .video_nodes.video_mask_by_key_points_node import VideoMaskByKeyPointsNode
from .video_nodes.load_video import LoadVideoFramesNode
from .video_nodes.preview_video_node_from_url import PreviewVideoURLNode
from .fibo_edit_node import FIBOEditNode
from .fibo_edit_structured_instruction_node import FIBOEditStructuredInstructionNode
nodes/fibo_edit_node.py
+163
View File
@@ -0,0 +1,163 @@
import requests
import torch
from .common import (
deserialize_and_get_comfy_key,
postprocess_image,
preprocess_image,
image_to_base64,
poll_status_until_completed,
preprocess_mask,
)
class FIBOEditNode:
"""FIBO Edit Node - Edit images with instructions"""
api_url = "https://engine.prod.bria-api.com/v2/image/edit"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
"instruction": ("STRING",),
"images": ("IMAGE",),
},
"optional": {
"mask": ("MASK",),
"structured_instruction": ("STRING",),
"negative_prompt": ("STRING",),
"steps_num": (
"INT",
{
"default": 50,
"min": 1,
"max": 100,
},
),
"guidance_scale": (
"INT",
{
"default": 5,
"min": 1,
"max": 20,
},
),
"seed": ("INT", {"default": 123456}),
},
}
RETURN_TYPES = ("IMAGE", "STRING", "INT")
RETURN_NAMES = ("IMAGE", "structured_prompt", "seed")
CATEGORY = "API Nodes"
FUNCTION = "execute"
def _validate_token(self, api_token: str):
if api_token.strip() == "" or api_token.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API token.")
def _build_payload(
self,
instruction,
images,
mask=None,
structured_instruction=None,
negative_prompt=None,
steps_num=50,
guidance_scale=5,
seed=123456,
):
# Process images
if isinstance(images, torch.Tensor):
processed_images = preprocess_image(images)
else:
processed_images = images
payload = {
"instruction": instruction,
"images": [image_to_base64(processed_images)],
"steps_num": steps_num,
"guidance_scale": guidance_scale,
"seed": seed,
}
# Add optional mask
if mask is not None:
if isinstance(mask, torch.Tensor):
processed_mask = preprocess_mask(mask)
else:
processed_mask = mask
payload["mask"] = image_to_base64(processed_mask)
# Add optional structured_instruction
if structured_instruction:
payload["structured_instruction"] = structured_instruction
# Add optional negative_prompt
if negative_prompt:
payload["negative_prompt"] = negative_prompt
return payload
def execute(
self,
api_token,
instruction,
images,
mask=None,
structured_instruction=None,
negative_prompt=None,
steps_num=50,
guidance_scale=5,
seed=123456,
):
self._validate_token(api_token)
payload = self._build_payload(
instruction,
images,
mask,
structured_instruction,
negative_prompt,
steps_num,
guidance_scale,
seed,
)
api_token = deserialize_and_get_comfy_key(api_token)
headers = {"Content-Type": "application/json", "api_token": api_token}
try:
response = requests.post(self.api_url, json=payload, headers=headers)
if response.status_code in (200, 202):
print(
f"Initial request successful to {self.api_url}, polling for completion..."
)
response_dict = response.json()
status_url = response_dict.get("status_url")
request_id = response_dict.get("request_id")
if not status_url:
raise Exception("No status_url returned from API")
print(f"Request ID: {request_id}, Status URL: {status_url}")
final_response = poll_status_until_completed(status_url, api_token)
result = final_response.get("result", {})
result_image_url = result.get("image_url")
structured_prompt = result.get("structured_prompt", "")
used_seed = result.get("seed")
image_response = requests.get(result_image_url)
result_image = postprocess_image(image_response.content)
return (result_image, structured_prompt, used_seed)
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
except Exception as e:
raise Exception(f"{e}")
nodes/fibo_edit_structured_instruction_node.py
+85
View File
@@ -0,0 +1,85 @@
import requests
import torch
from .common import (
deserialize_and_get_comfy_key,
image_to_base64,
poll_status_until_completed,
preprocess_image,
)
class FIBOEditStructuredInstructionNode:
"""FIBO Edit Structured Instruction Node - Generate structured instructions for image editing"""
api_url = "https://engine.prod.bria-api.com/v2/structured_instruction/generate"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
"image": ("IMAGE",),
"instruction": ("STRING",),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("structured_instruction",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def _validate_token(self, api_token: str):
if api_token.strip() == "" or api_token.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API token.")
def _build_payload(self, image, instruction):
# Process image
if isinstance(image, torch.Tensor):
processed_image = preprocess_image(image)
else:
processed_image = image
payload = {
"instruction": instruction,
"images": [image_to_base64(processed_image)],
}
return payload
def execute(self, api_token, image, instruction):
self._validate_token(api_token)
payload = self._build_payload(image, instruction)
api_token = deserialize_and_get_comfy_key(api_token)
headers = {"Content-Type": "application/json", "api_token": api_token}
try:
response = requests.post(self.api_url, json=payload, headers=headers)
if response.status_code in (200, 202):
print(
f"Initial request successful to {self.api_url}, polling for completion..."
)
response_dict = response.json()
status_url = response_dict.get("status_url")
request_id = response_dict.get("request_id")
if not status_url:
raise Exception("No status_url returned from API")
print(f"Request ID: {request_id}, Status URL: {status_url}")
final_response = poll_status_until_completed(status_url, api_token)
result = final_response.get("result", {})
structured_instruction = result.get("structured_instruction", "")
return (structured_instruction,)
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
except Exception as e:
raise Exception(f"{e}")