nodes/Bria-AI-ComfyUI-BRIA-API
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add fibo pro nodes

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This commit is contained in:
Ubuntu
2025-10-27 20:19:53 +00:00
parent 43893286cc
commit 270128d32a
4 changed files with 142 additions and 76 deletions
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__init__.py
+12 -6
View File
@@ -15,8 +15,10 @@ from .nodes import (
TailoredPortraitNode,
ReimagineNode,
AttributionByImageNode,
FiboGenerateNode,
FiboRefineAndRegenerateNode,
GenerateImageNodeV2,
GenerateImageProNodeV2,
RefineImageNodeV2,
RefineImageProNodeV2,
)
# Map the node class to a name used internally by ComfyUI
@@ -37,8 +39,10 @@ NODE_CLASS_MAPPINGS = {
"Text2ImageHDNode": Text2ImageHDNode,
"ReimagineNode": ReimagineNode,
"AttributionByImageNode": AttributionByImageNode,
"Text2ImageFiboGenerateNode": FiboGenerateNode,
"Text2ImageFiboRefineAndRegenerateNode": FiboRefineAndRegenerateNode,
"GenerateImageNodeV2": GenerateImageNodeV2,
"RefineImageNodeV2": RefineImageNodeV2,
"GenerateImageProNodeV2":GenerateImageProNodeV2,
"RefineImageProNodeV2":RefineImageProNodeV2
}
# Map the node display name to the one shown in the ComfyUI node interface
NODE_DISPLAY_NAME_MAPPINGS = {
@@ -58,6 +62,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"Text2ImageHDNode": "Bria Text2Image HD",
"ReimagineNode": "Bria Reimagine",
"AttributionByImageNode": "Attribution By Image Node",
"Text2ImageFiboGenerateNode": "Bria FIBO - Generate",
"Text2ImageFiboRefineAndRegenerateNode": "Bria FIBO - Refine and Regenerate",
"GenerateImageNodeV2": "Generate Image",
"RefineImageNodeV2": "Refine and Regenerate Image",
"GenerateImageProNodeV2":"Generate Image - Pro",
"RefineImageProNodeV2":"Refine and Regenerate Image - Pro"
}
nodes/__init__.py
+2 -2
View File
@@ -14,5 +14,5 @@ from .text_2_image_fast_node import Text2ImageFastNode
from .text_2_image_hd_node import Text2ImageHDNode
from .reimagine_node import ReimagineNode
from .attribution_by_image_node import AttributionByImageNode
from .fibo_generate_node import FiboGenerateNode
from .fibo_refine_node import FiboRefineAndRegenerateNode
from .generate_image_node_v2 import GenerateImageNodeV2, GenerateImageProNodeV2
from .refine_image_node_v2 import RefineImageNodeV2, RefineImageProNodeV2
nodes/fibo_generate_node.py → nodes/generate_image_node_v2.py
+67 -36
View File
@@ -9,9 +9,13 @@ from .common import (
)
class FiboGenerateNode:
class _BaseGenerateImageNodeV2:
"""Base class for image generation nodes (standard & pro)."""
api_url = None # Each subclass must define its API endpoint
@classmethod
def INPUT_TYPES(self):
def INPUT_TYPES(cls):
return {
"required": {
"api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
@@ -25,7 +29,7 @@ class FiboGenerateNode:
["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
{"default": "1:1"},
),
"steps_num": ("INT", {"default": 30, "min": 20, "max": 50}),
"steps_num": ("INT", {"default": 50, "min": 20, "max": 50}),
"guidance_scale": ("INT", {"default": 5, "min": 3, "max": 5}),
"seed": ("INT", {"default": 123456}),
},
@@ -36,8 +40,37 @@ class FiboGenerateNode:
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/image/generate"
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,
prompt,
mode,
negative_prompt,
aspect_ratio,
steps_num,
guidance_scale,
seed,
image=None,
):
payload = {
"prompt": prompt,
"mode": mode,
"negative_prompt": negative_prompt,
"aspect_ratio": aspect_ratio,
"steps_num": steps_num,
"guidance_scale": guidance_scale,
"seed": seed,
}
if image is not None:
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
payload["images"] = [image_to_base64(image)]
return payload
def execute(
self,
@@ -51,36 +84,26 @@ class FiboGenerateNode:
seed,
image=None,
):
if api_token.strip() == "" or api_token.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API token.")
payload = {
"prompt": prompt,
"mode": mode,
"negative_prompt": negative_prompt,
"aspect_ratio": aspect_ratio,
"steps_num": steps_num,
"guidance_scale": guidance_scale,
"seed": seed,
}
# Add image if provided
if image is not None:
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
image_base64 = image_to_base64(image)
payload["image"] = image_base64
self._validate_token(api_token)
payload = self._build_payload(
prompt,
mode,
negative_prompt,
aspect_ratio,
steps_num,
guidance_scale,
seed,
image,
)
headers = {"Content-Type": "application/json", "api_token": api_token}
try:
# Send initial request to get status URL
response = requests.post(self.api_url, json=payload, headers=headers)
if response.status_code == 200 or response.status_code == 202:
if response.status_code in (200, 202):
print(
"Initial FIBO generate request successful, polling for completion..."
f"Initial request successful to {self.api_url}, polling for completion..."
)
response_dict = response.json()
status_url = response_dict.get("status_url")
@@ -91,25 +114,33 @@ class FiboGenerateNode:
print(f"Request ID: {request_id}, Status URL: {status_url}")
# Poll for completion
final_response = poll_status_until_completed(status_url, api_token)
# Extract results
result = final_response.get("result", {})
print(result)
result_image_url = result.get("image_url")
structured_prompt = result.get("structured_prompt", "")
used_seed = result.get("seed")
# Download and process the result image
image_response = requests.get(result_image_url)
result_image = postprocess_image(image_response.content)
return (result_image, structured_prompt, used_seed)
else:
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
except Exception as e:
raise Exception(f"{e}")
class GenerateImageNodeV2(_BaseGenerateImageNodeV2):
"""Standard Image Generation Node"""
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/image/generate"
class GenerateImageProNodeV2(_BaseGenerateImageNodeV2):
"""Pro Image Generation Node"""
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/image/generate/pro"
nodes/fibo_refine_node.py → nodes/refine_image_node_v2.py
+61 -32
View File
@@ -1,11 +1,14 @@
import requests
from .common import poll_status_until_completed
class FiboRefineAndRegenerateNode:
class _BaseRefineImageNodeV2:
"""Base class for refine image nodes (standard & pro)."""
api_url = None # Must be overridden by subclasses
@classmethod
def INPUT_TYPES(self):
def INPUT_TYPES(cls):
return {
"required": {
"api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
@@ -19,7 +22,7 @@ class FiboRefineAndRegenerateNode:
["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
{"default": "1:1"},
),
"steps_num": ("INT", {"default": 30, "min": 20, "max": 50}),
"steps_num": ("INT", {"default": 50, "min": 20, "max": 50}),
"guidance_scale": ("INT", {"default": 5, "min": 3, "max": 5}),
"seed": ("INT", {"default": 123456}),
},
@@ -30,8 +33,31 @@ class FiboRefineAndRegenerateNode:
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/structured_prompt/generate"
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,
prompt,
structured_prompt,
mode,
negative_prompt,
aspect_ratio,
steps_num,
guidance_scale,
seed,
):
return {
"prompt": prompt,
"mode": mode,
"negative_prompt": negative_prompt,
"aspect_ratio": aspect_ratio,
"steps_num": steps_num,
"guidance_scale": guidance_scale,
"seed": seed,
"structured_prompt": structured_prompt,
}
def execute(
self,
@@ -45,31 +71,25 @@ class FiboRefineAndRegenerateNode:
guidance_scale,
seed,
):
if api_token.strip() == "" or api_token.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API token.")
payload = {
"prompt": prompt,
"mode": mode,
"negative_prompt": negative_prompt,
"aspect_ratio": aspect_ratio,
"steps_num": steps_num,
"guidance_scale": guidance_scale,
"seed": seed,
"structured_prompt":structured_prompt
}
self._validate_token(api_token)
payload = self._build_payload(
prompt,
structured_prompt,
mode,
negative_prompt,
aspect_ratio,
steps_num,
guidance_scale,
seed,
)
headers = {"Content-Type": "application/json", "api_token": api_token}
try:
# Send initial request to get status URL
response = requests.post(self.api_url, json=payload, headers=headers)
if response.status_code == 200 or response.status_code == 202:
print(
"Initial FIBO Refine and Regenerate request successful, polling for completion..."
)
if response.status_code in (200, 202):
print(f"Initial refine 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")
@@ -79,20 +99,29 @@ class FiboRefineAndRegenerateNode:
print(f"Request ID: {request_id}, Status URL: {status_url}")
# Poll for completion
final_response = poll_status_until_completed(status_url, api_token)
# Extract results
result = final_response.get("result", {})
print(result)
structured_prompt = result.get("structured_prompt", "")
used_seed = result.get("seed", seed)
return (structured_prompt, used_seed)
else:
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
raise Exception(
f"Error: API request failed with status code {response.status_code} {response.text}"
)
except Exception as e:
raise Exception(f"{e}")
class RefineImageNodeV2(_BaseRefineImageNodeV2):
"""Standard Refine Image Node"""
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/structured_prompt/generate"
class RefineImageProNodeV2(_BaseRefineImageNodeV2):
"""Pro Refine Image Node"""
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/structured_prompt/generate/pro"