update version

WAI-4030

Readme.md

@@ -30,7 +30,21 @@ To load a workflow, import the compatible workflow.json files from this [folder]
 # Available Nodes
 
 ## Image Generation Nodes
-These nodes create high-quality images from text or image prompts, generating photorealistic or artistic results with support for various aspect ratios.
+
+These nodes allow you to leverage Bria's image generation capabilities within ComfyUI. We offer our latest **V2 nodes** designed for precise control via structured prompts (currently powered by the **FIBO** model), alongside our **V1 nodes** for various established pipelines.
+
+### V2 Generation Nodes
+
+These nodes generate images based on detailed **structured prompts** for enhanced control and consistency. They are currently powered by the state-of-the-art **FIBO** text-to-image model.
+
+| **Node** | **Description** |
+| --- | --- |
+| **Generate Image** | Creates new images from text or image inputs. Internally translates the input into a structured prompt using a selected VLM bridge before generating with the image model. |
+| **Refine and Regenerate Image** | Refines a generated image using a provided `structured_prompt` (from a previous generation) and a refinement text prompt. |
+
+### V1 Generation Nodes
+
+These nodes create high-quality images using Bria's V1 pipelines, supporting various aspect ratios and styles.
 
 | Node                   | Description                                                        |
 |------------------------|--------------------------------------------------------------------|

__init__.py

@@ -14,6 +14,8 @@ from .nodes import (
     Text2ImageHDNode,
     TailoredPortraitNode,
     ReimagineNode,
+    GenerateImageNodeV2,
+    RefineImageNodeV2,
     ShotByTextAutomaticNode,
     ShotByImageManualPaddingNode,
     ShotByImageAutomaticAspectRatioNode,
@@ -54,7 +56,9 @@ NODE_CLASS_MAPPINGS = {
     "Text2ImageFastNode": Text2ImageFastNode,
     "Text2ImageHDNode": Text2ImageHDNode,
     "ReimagineNode": ReimagineNode,
-    "AttributionByImageNode":AttributionByImageNode
+    "AttributionByImageNode": AttributionByImageNode,
+    "GenerateImageNodeV2": GenerateImageNodeV2,
+    "RefineImageNodeV2": RefineImageNodeV2,
 }
 # Map the node display name to the one shown in the ComfyUI node interface
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -83,5 +87,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "Text2ImageFastNode": "Bria Text2Image Fast",
     "Text2ImageHDNode": "Bria Text2Image HD",
     "ReimagineNode": "Bria Reimagine",
-    "AttributionByImageNode":"Attribution By Image Node"
+    "AttributionByImageNode": "Attribution By Image Node",
+    "GenerateImageNodeV2": "Generate Image",
+    "RefineImageNodeV2": "Refine and Regenerate Image",
 }

nodes/__init__.py

@@ -11,6 +11,8 @@ from .text_2_image_base_node import Text2ImageBaseNode
 from .text_2_image_fast_node import Text2ImageFastNode
 from .text_2_image_hd_node import Text2ImageHDNode
 from .reimagine_node import ReimagineNode
+from .generate_image_node_v2 import GenerateImageNodeV2
+from .refine_image_node_v2 import RefineImageNodeV2
 from .shot_by_text_node import ShotByTextOriginalNode
 from .shot_by_text_automatic_aspect_ratio_node import ShotByTextAutomaticAspectRatioNode
 from .shot_by_text_automatic_node import ShotByTextAutomaticNode

nodes/attribution_by_image_node.py

@@ -1,7 +1,7 @@
 import requests
 import torch
 
-from .common import preprocess_image, image_to_base64, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, preprocess_image, image_to_base64, poll_status_until_completed
 
 class AttributionByImageNode():
     @classmethod
@@ -26,6 +26,7 @@ class AttributionByImageNode():
     def execute(self, image, model_version, api_key):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
 
         # Check if image is tensor, if so, convert to NumPy array
         if isinstance(image, torch.Tensor):

nodes/common.py

@@ -6,6 +6,15 @@ import base64
 from torchvision.transforms import ToPILImage
 import requests
 import time
+import json
+
+
+COMFY_KEY_ERROR = (
+    "Invalid Token Type\n\n"
+    "The API token you’ve entered is not a ComfyUI token.\n"
+    "Please use the valid token from your BRIA Account API Keys page:\n"
+    "https://platform.bria.ai/console/account/api-keys"
+)
 
 def postprocess_image(image):
     result_image = Image.open(io.BytesIO(image))
@@ -48,6 +57,7 @@ def preprocess_mask(mask):
 def process_request(api_url, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation):
     if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
         raise Exception("Please insert a valid API key.")
+    api_key = deserialize_and_get_comfy_key(api_key)
 
     # Check if image and mask are tensors, if so, convert to NumPy arrays
     if isinstance(image, torch.Tensor):
@@ -145,3 +155,21 @@ def poll_status_until_completed(status_url, api_key, timeout=360, check_interval
             raise Exception(f"Error checking status: {e}")
     
     raise Exception(f"Timeout reached after {timeout} seconds")
+
+def deserialize_and_get_comfy_key(encoded: str) -> str:
+    """
+    Decodes a base64-encoded JSON token and returns the ComfyUI API key.
+    """
+    try:
+        decoded = base64.b64decode(encoded).decode("utf-8")
+        payload = json.loads(decoded)
+
+        if payload.get("type") != "comfy":
+            raise Exception(COMFY_KEY_ERROR)
+
+        return payload.get("apiKey")
+
+    except Exception as e:
+        raise Exception(COMFY_KEY_ERROR)
+
+   

nodes/generate_image_node_v2.py

@@ -0,0 +1,143 @@
+import requests
+import torch
+
+from .common import (
+    deserialize_and_get_comfy_key,
+    postprocess_image,
+    preprocess_image,
+    image_to_base64,
+    poll_status_until_completed,
+)
+
+
+class _BaseGenerateImageNodeV2:
+    """Base class for image generation nodes (standard & pro)."""
+
+    api_url = None  # Each subclass must define its API endpoint
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
+                "prompt": ("STRING",),
+            },
+            "optional": {
+                "model_version": (["FIBO"], {"default": "FIBO"}),
+                "negative_prompt": ("STRING", {"default": ""}),
+                "images": ("IMAGE",),
+                "aspect_ratio": (
+                    ["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": 50, "min": 20, "max": 50}),
+                "guidance_scale": ("INT", {"default": 5, "min": 3, "max": 5}),
+                "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,
+        prompt,
+        model_version,
+        negative_prompt,
+        aspect_ratio,
+        steps_num,
+        guidance_scale,
+        seed,
+        images=None,
+    ):
+        payload = {
+            "prompt": prompt,
+            "model_version": model_version,
+            "negative_prompt": negative_prompt,
+            "aspect_ratio": aspect_ratio,
+            "steps_num": steps_num,
+            "guidance_scale": guidance_scale,
+            "seed": seed,
+        }
+
+        if images is not None:
+            if isinstance(images, torch.Tensor):
+                preprocess_images = preprocess_image(images)
+            payload["images"] = [image_to_base64(preprocess_images)]
+
+
+        return payload
+
+    def execute(
+        self,
+        api_token,
+        prompt,
+        model_version,
+        negative_prompt,
+        aspect_ratio,
+        steps_num,
+        guidance_scale,
+        seed,
+        images=None,
+    ):
+        self._validate_token(api_token)
+        payload = self._build_payload(
+            prompt,
+            model_version,
+            negative_prompt,
+            aspect_ratio,
+            steps_num,
+            guidance_scale,
+            seed,
+            images,
+        )
+        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}")
+
+
+class GenerateImageNodeV2(_BaseGenerateImageNodeV2):
+    """Standard Image Generation Node"""
+    def __init__(self):
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/generate"

nodes/generative_fill_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import preprocess_image, preprocess_mask, image_to_base64, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, preprocess_image, preprocess_mask, image_to_base64, poll_status_until_completed
 
 
 class GenFillNode():
@@ -39,6 +39,7 @@ class GenFillNode():
     def execute(self, image, mask, prompt, api_key, seed, prompt_content_moderation, visual_input_content_moderation, visual_output_content_moderation):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
 
         # Check if image and mask are tensors, if so, convert to NumPy arrays
         if isinstance(image, torch.Tensor):

nodes/image_expansion_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import image_to_base64, preprocess_image, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, image_to_base64, preprocess_image, poll_status_until_completed
 
 
 class ImageExpansionNode():
@@ -55,6 +55,7 @@ class ImageExpansionNode():
                 api_key):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
         original_image_size = [int(x.strip()) for x in original_image_size.split(",")] if original_image_size else ()
         original_image_location = [int(x.strip()) for x in original_image_location.split(",")] if original_image_location else ()
         canvas_size = [int(x.strip()) for x in canvas_size.split(",")] if canvas_size else ()

nodes/refine_image_node_v2.py

@@ -0,0 +1,161 @@
+import requests
+from .common import deserialize_and_get_comfy_key, poll_status_until_completed, postprocess_image
+
+
+class _BaseRefineImageNodeV2:
+    """Base class for refine image nodes (standard & pro)."""
+
+    api_url = None  # Must be overridden by subclasses
+    generate_api_url = None
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "api_token": ("STRING", {"default": "BRIA_API_TOKEN"}),
+                "prompt": ("STRING",),
+                "structured_prompt": ("STRING",),
+            },
+            "optional": {
+                "model_version": (["FIBO"], {"default": "FIBO"}),
+                "negative_prompt": ("STRING", {"default": ""}),
+                "aspect_ratio": (
+                    ["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": 50, "min": 20, "max": 50}),
+                "guidance_scale": ("INT", {"default": 5, "min": 3, "max": 5}),
+                "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,
+        prompt,
+        structured_prompt,
+        model_version,
+        negative_prompt,
+        aspect_ratio,
+        steps_num,
+        guidance_scale,
+        seed,
+    ):
+        return {
+            "prompt": prompt,
+            "model_version": model_version,
+            "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,
+        api_token,
+        prompt,
+        structured_prompt,
+        model_version,
+        negative_prompt,
+        aspect_ratio,
+        steps_num,
+        guidance_scale,
+        seed,
+    ):
+        self._validate_token(api_token)
+        payload = self._build_payload(
+            prompt,
+            structured_prompt,
+            model_version,
+            negative_prompt,
+            aspect_ratio,
+            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 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")
+
+                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_prompt = result.get("structured_prompt", "")
+                used_seed = result.get("seed", seed)
+
+                # Step 2 to call genearte image
+                payloadForImageGenetrate = {
+                    "prompt": prompt,
+                    "structured_prompt":structured_prompt,
+                    "model_version": model_version,
+                    "negative_prompt": negative_prompt,
+                    "aspect_ratio": aspect_ratio,
+                    "steps_num": steps_num,
+                    "guidance_scale": guidance_scale,
+                    "seed": used_seed,
+                }
+                headers = {"Content-Type": "application/json", "api_token": api_token}
+
+                response = requests.post(self.generate_api_url, json=payloadForImageGenetrate, headers=headers)
+
+                if response.status_code in (200, 202):
+                    print(
+                        f"Initial request successful to {self.generate_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}")
+
+
+class RefineImageNodeV2(_BaseRefineImageNodeV2):
+    """Standard Refine Image Node"""
+    def __init__(self):
+        self.api_url = "https://engine.prod.bria-api.com/v2/structured_prompt/generate"
+        self.generate_api_url = "https://engine.prod.bria-api.com/v2/image/generate"

nodes/reimagine_node.py

@@ -1,6 +1,6 @@
 import requests
 
-from .common import postprocess_image, preprocess_image, image_to_base64
+from .common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
 
 
 class ReimagineNode():
@@ -37,7 +37,8 @@ class ReimagineNode():
             steps_num, fast, structure_ref_influence, structure_image=None,
             tailored_model_id=None, tailored_model_influence=None, tailored_generation_prefix=None,
             content_moderation=0,
-        ):        
+        ):    
+        api_key = deserialize_and_get_comfy_key(api_key)    
         payload = {
             "prompt": tailored_generation_prefix + prompt,
             "num_results": 1,

nodes/remove_foreground_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import preprocess_image, image_to_base64, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, preprocess_image, image_to_base64, poll_status_until_completed
 
 
 class RemoveForegroundNode():
@@ -34,6 +34,7 @@ class RemoveForegroundNode():
     def execute(self, image, visual_input_content_moderation, visual_output_content_moderation, preserve_alpha, api_key):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
 
         # Check if image is tensor, if so, convert to NumPy array
         if isinstance(image, torch.Tensor):

nodes/replace_bg_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import image_to_base64, preprocess_image, preprocess_mask, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, image_to_base64, preprocess_image, preprocess_mask, poll_status_until_completed
 
 
 class ReplaceBgNode():
@@ -53,6 +53,7 @@ class ReplaceBgNode():
                 ref_images=None,):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
 
         # Check if image and mask are tensors, if so, convert to NumPy arrays
         if isinstance(image, torch.Tensor):

nodes/rmbg_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import preprocess_image, image_to_base64, poll_status_until_completed
+from .common import deserialize_and_get_comfy_key, preprocess_image, image_to_base64, poll_status_until_completed
 
 class RmbgNode():
     @classmethod
@@ -34,7 +34,7 @@ class RmbgNode():
     def execute(self, image, visual_input_content_moderation, visual_output_content_moderation, preserve_alpha, api_key):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
-
+        api_key = deserialize_and_get_comfy_key(api_key)
         # Check if image is tensor, if so, convert to NumPy array
         if isinstance(image, torch.Tensor):
             image = preprocess_image(image)

nodes/tailored_gen_node.py

@@ -1,6 +1,6 @@
 import requests
 
-from .common import postprocess_image, preprocess_image, image_to_base64
+from .common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
 
 
 class TailoredGenNode():
@@ -45,6 +45,7 @@ class TailoredGenNode():
             guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
             content_moderation=0,
         ):
+        api_key = deserialize_and_get_comfy_key(api_key)
         payload = {
             "prompt": generation_prefix + prompt,
             "num_results": 1,

nodes/tailored_model_info_node.py

@@ -1,5 +1,5 @@
 import requests
-
+from .common import deserialize_and_get_comfy_key
 
 class TailoredModelInfoNode():
     @classmethod
@@ -21,6 +21,7 @@ class TailoredModelInfoNode():
 
     # Define the execute method as expected by ComfyUI
     def execute(self, model_id, api_key):
+        api_key = deserialize_and_get_comfy_key(api_key)
         response = requests.get(
             self.api_url + model_id,
             headers={"api_token": api_key}

nodes/tailored_portrait_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import image_to_base64, preprocess_image
+from .common import deserialize_and_get_comfy_key, image_to_base64, preprocess_image
 
 class TailoredPortraitNode():
     @classmethod
@@ -12,7 +12,7 @@ class TailoredPortraitNode():
         return {
             "required": {
                 "image": ("IMAGE",),  # Input image from another node
-                "tailored_model_id": ("INT",),
+                "tailored_model_id": ("STRING",), # API Key input with a default value
                 "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
             },
             "optional": {
@@ -34,6 +34,7 @@ class TailoredPortraitNode():
     def execute(self, image, tailored_model_id, api_key, seed, tailored_model_influence, id_strength):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
+        api_key = deserialize_and_get_comfy_key(api_key)
 
         # Convert the image and mask directly to  if isinstance(image, torch.Tensor):
         if isinstance(image, torch.Tensor):
@@ -44,7 +45,7 @@ class TailoredPortraitNode():
         # Prepare the API request payload
         payload = {
             "id_image_file": f"{image_base64}",
-            "tailored_model_id": tailored_model_id,
+            "tailored_model_id": int(tailored_model_id),
             "tailored_model_influence": tailored_model_influence,
             "id_strength": id_strength,
             "seed": seed
@@ -69,7 +70,7 @@ class TailoredPortraitNode():
                 result_image = torch.from_numpy(result_image)[None,]
                 return (result_image,)
             else:
-                raise Exception(f"Error: API request failed with status code {response.status_code}")
+                raise Exception(f"Error: API request failed with status code {response.status_code} {response.text}")
 
         except Exception as e:
             raise Exception(f"{e}")

nodes/text_2_image_base_node.py

@@ -1,6 +1,6 @@
 import requests
 
-from .common import postprocess_image, preprocess_image, image_to_base64
+from .common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
 
 
 class Text2ImageBaseNode():
@@ -48,6 +48,7 @@ class Text2ImageBaseNode():
             image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
             content_moderation=0,
         ):
+        api_key = deserialize_and_get_comfy_key(api_key)
         payload = {
             "prompt": prompt,
             "num_results": 1,

nodes/text_2_image_fast_node.py

@@ -1,6 +1,6 @@
 import requests
 
-from .common import postprocess_image, preprocess_image, image_to_base64
+from .common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
 
 
 class Text2ImageFastNode():
@@ -45,6 +45,7 @@ class Text2ImageFastNode():
             image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
             content_moderation=0,
         ):
+        api_key = deserialize_and_get_comfy_key(api_key)
         payload = {
             "prompt": prompt,
             "num_results": 1,

nodes/text_2_image_hd_node.py

@@ -1,6 +1,6 @@
 import requests
 
-from .common import postprocess_image
+from .common import deserialize_and_get_comfy_key, postprocess_image
 
 
 class Text2ImageHDNode():
@@ -29,12 +29,13 @@ class Text2ImageHDNode():
     FUNCTION = "execute"
 
     def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/hd/2.3" #"http://0.0.0.0:5000/v1/text-to-image/hd/2.3"
+        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/hd/2.2" #"http://0.0.0.0:5000/v1/text-to-image/hd/2.3"
 
     def execute(
             self, api_key, prompt, aspect_ratio, seed, negative_prompt, 
             steps_num, prompt_enhancement, text_guidance_scale, medium, content_moderation=0,
         ):
+        api_key = deserialize_and_get_comfy_key(api_key)
         payload = {
             "prompt": prompt,
             "num_results": 1,

nodes/utils/shot_utils.py

@@ -1,6 +1,6 @@
 import requests
 import torch
-from ..common import postprocess_image, preprocess_image, image_to_base64
+from ..common import deserialize_and_get_comfy_key, postprocess_image, preprocess_image, image_to_base64
 
 shot_by_text_api_url = (
     "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_text"
@@ -68,6 +68,7 @@ def create_text_payload(
 
     validate_api_key(api_key)
 
+
     # Process image
     if isinstance(image, torch.Tensor):
         image = preprocess_image(image)
@@ -126,9 +127,11 @@ def create_image_payload(image, ref_image, api_key, placement_type, **kwargs):
 
 def make_api_request(api_url, payload, api_key, Placement_type = None):
     """Make API request and return processed image"""
-    headers = {"Content-Type": "application/json", "api_token": f"{api_key}"}
+
 
     try:
+        api_key = deserialize_and_get_comfy_key(api_key)
+        headers = {"Content-Type": "application/json", "api_token": f"{api_key}"}
         response = requests.post(api_url, json=payload, headers=headers)
 
         if response.status_code == 200:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-bria-api"
 description = "Custom nodes for ComfyUI using BRIA's API."
-version = "2.1.3"
+version = "2.1.7"
 license = {file = "LICENSE"}
 
 [project.urls]

workflows/FIBO_Workflow.json

@@ -0,0 +1,543 @@
+{
+  "id": "3875cd62-7a0e-4c8c-8951-22ec8a63dd8d",
+  "revision": 0,
+  "last_node_id": 14,
+  "last_link_id": 8,
+  "nodes": [
+    {
+      "id": 3,
+      "type": "PreviewImage",
+      "pos": [
+        632.3427124023438,
+        32.13115310668945
+      ],
+      "size": [
+        140,
+        26
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 1
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.62",
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 2,
+      "type": "RefineImageNodeV2",
+      "pos": [
+        704.8090209960938,
+        218.65850830078125
+      ],
+      "size": [
+        287.4712829589844,
+        314
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "widget": {
+            "name": "structured_prompt"
+          },
+          "link": 3
+        },
+        {
+          "name": "seed",
+          "shape": 7,
+          "type": "INT",
+          "widget": {
+            "name": "seed"
+          },
+          "link": 2
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            4
+          ]
+        },
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "links": null
+        },
+        {
+          "name": "seed",
+          "type": "INT",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-bria-api",
+        "ver": "2.1.4",
+        "Node name for S&R": "RefineImageNodeV2",
+        "ue_properties": {
+          "widget_ue_connectable": {
+            "api_token": true,
+            "prompt": true,
+            "structured_prompt": true,
+            "model_version": true,
+            "negative_prompt": true,
+            "aspect_ratio": true,
+            "steps_num": true,
+            "guidance_scale": true,
+            "seed": true
+          },
+          "version": "7.1",
+          "input_ue_unconnectable": {}
+        }
+      },
+      "widgets_values": [
+        "BRIA_API_TOKEN",
+        "",
+        "",
+        "FIBO",
+        "",
+        "1:1",
+        50,
+        5,
+        123456,
+        "randomize"
+      ]
+    },
+    {
+      "id": 4,
+      "type": "PreviewImage",
+      "pos": [
+        1153.29345703125,
+        270.2264404296875
+      ],
+      "size": [
+        140,
+        26
+      ],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 4
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.62",
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 1,
+      "type": "GenerateImageNodeV2",
+      "pos": [
+        272.6366882324219,
+        227.9468231201172
+      ],
+      "size": [
+        270,
+        290
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            1
+          ]
+        },
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "links": [
+            3
+          ]
+        },
+        {
+          "name": "seed",
+          "type": "INT",
+          "links": [
+            2
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-bria-api",
+        "ver": "2.1.4",
+        "Node name for S&R": "GenerateImageNodeV2",
+        "ue_properties": {
+          "widget_ue_connectable": {
+            "api_token": true,
+            "prompt": true,
+            "model_version": true,
+            "negative_prompt": true,
+            "aspect_ratio": true,
+            "steps_num": true,
+            "guidance_scale": true,
+            "seed": true
+          },
+          "version": "7.1",
+          "input_ue_unconnectable": {}
+        }
+      },
+      "widgets_values": [
+        "BRIA_API_TOKEN",
+        "",
+        "FIBO",
+        "",
+        "1:1",
+        50,
+        5,
+        123456,
+        "randomize"
+      ]
+    },
+    {
+      "id": 5,
+      "type": "Note",
+      "pos": [
+        -43.613197326660156,
+        324.2381896972656
+      ],
+      "size": [
+        210,
+        88
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "If you would like to start with prompt"
+      ],
+      "color": "#c09430",
+      "bgcolor": "rgba(24,24,27,.9)"
+    },
+    {
+      "id": 10,
+      "type": "PreviewImage",
+      "pos": [
+        1182.5216064453125,
+        1006.7373657226562
+      ],
+      "size": [
+        140,
+        26
+      ],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 7
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.62",
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 9,
+      "type": "RefineImageNodeV2",
+      "pos": [
+        703.2684326171875,
+        1034.9910888671875
+      ],
+      "size": [
+        287.4712829589844,
+        314
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "widget": {
+            "name": "structured_prompt"
+          },
+          "link": 5
+        },
+        {
+          "name": "seed",
+          "shape": 7,
+          "type": "INT",
+          "widget": {
+            "name": "seed"
+          },
+          "link": 6
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            7
+          ]
+        },
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "links": null
+        },
+        {
+          "name": "seed",
+          "type": "INT",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-bria-api",
+        "ver": "2.1.5",
+        "Node name for S&R": "RefineImageNodeV2"
+      },
+      "widgets_values": [
+        "BRIA_API_TOKEN",
+        "",
+        "",
+        "FIBO",
+        "",
+        "1:1",
+        50,
+        5,
+        123456,
+        "randomize"
+      ]
+    },
+    {
+      "id": 6,
+      "type": "Note",
+      "pos": [
+        -47.50065612792969,
+        1042.9178466796875
+      ],
+      "size": [
+        210,
+        95.76702880859375
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "If you would like to start with reference image + prompt"
+      ],
+      "color": "#c09430",
+      "bgcolor": "rgba(24,24,27,.9)"
+    },
+    {
+      "id": 14,
+      "type": "PreviewImage",
+      "pos": [
+        593.5224609375,
+        844.5531616210938
+      ],
+      "size": [
+        140,
+        26
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 8
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.62",
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 7,
+      "type": "GenerateImageNodeV2",
+      "pos": [
+        262.3690490722656,
+        1041.67431640625
+      ],
+      "size": [
+        270,
+        290
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+      "flags": {},
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+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            8
+          ]
+        },
+        {
+          "name": "structured_prompt",
+          "type": "STRING",
+          "links": [
+            5
+          ]
+        },
+        {
+          "name": "seed",
+          "type": "INT",
+          "links": [
+            6
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-bria-api",
+        "ver": "2.1.5",
+        "Node name for S&R": "GenerateImageNodeV2"
+      },
+      "widgets_values": [
+        "BRIA_API_TOKEN",
+        "",
+        "FIBO",
+        "",
+        "1:1",
+        50,
+        5,
+        123456,
+        "randomize"
+      ]
+    }
+  ],
+  "links": [
+    [
+      1,
+      1,
+      0,
+      3,
+      0,
+      "IMAGE"
+    ],
+    [
+      2,
+      1,
+      2,
+      2,
+      1,
+      "INT"
+    ],
+    [
+      3,
+      1,
+      1,
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+      0,
+      "STRING"
+    ],
+    [
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+      2,
+      0,
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+      0,
+      "IMAGE"
+    ],
+    [
+      5,
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+      1,
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+      0,
+      "STRING"
+    ],
+    [
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+      1,
+      "INT"
+    ],
+    [
+      7,
+      9,
+      0,
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+      0,
+      "IMAGE"
+    ],
+    [
+      8,
+      7,
+      0,
+      14,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ue_links": [],
+    "ds": {
+      "scale": 0.3897342147473183,
+      "offset": [
+        658.5745748406673,
+        99.37411299539059
+      ]
+    },
+    "frontendVersion": "1.28.4",
+    "VHS_latentpreview": false,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}