update version

fix invalid token error message
Update pyproject.toml
2025-11-12 12:03:13 +00:00 · 2025-11-12 09:44:45 +00:00 · 2025-11-11 15:50:02 +02:00 · 2025-11-11 15:39:44 +02:00 · 2025-11-09 06:51:29 +00:00 · 2025-10-30 15:41:37 +02:00
35 changed files with 2029 additions and 306 deletions
@@ -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                                                        |
 |------------------------|--------------------------------------------------------------------|
@@ -68,6 +82,15 @@ These nodes create high-quality product images for eCommerce workflows.
 | **ShotByText**         | Modifies an image's background by providing a text prompt. Powered by BRIA's ControlNet Background-Generation. |
 | **ShotByImage**        | Modifies an image's background by providing a reference image. Uses BRIA's ControlNet Background-Generation and Image-Prompt. |

+## Attribution Node
+
+| Node                          | Description |
+|-------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| **Attribution By Image Node** | This node shares generated images via API for Bria to pay attribution to the data owners who contributed to the generation. Once the images are shared with Bria, Bria calculates the attribution, completes the payment on behalf of the user, and erases the images immediately. This node should be included in any workflow using nodes of Bria’s Models (not necessary for Bria’s API nodes). You can also refer to the [**API documentation**]( https://docs.bria.ai/bria-attribution-service/other/postattributionbyimage) |
+
+
+
+
 # Installation
 There are two methods to install the BRIA ComfyUI API nodes:

@@ -1,6 +1,34 @@
-from .nodes import (EraserNode, GenFillNode, ImageExpansionNode, ReplaceBgNode, RmbgNode, RemoveForegroundNode, ShotByTextNode, ShotByImageNode, TailoredGenNode,
-                     TailoredModelInfoNode, Text2ImageBaseNode, Text2ImageFastNode, Text2ImageHDNode, TailoredPortraitNode,
-                     ReimagineNode)
+from .nodes import (
+    EraserNode,
+    GenFillNode,
+    ImageExpansionNode,
+    ReplaceBgNode,
+    RmbgNode,
+    RemoveForegroundNode,
+    ShotByTextOriginalNode,
+    ShotByImageOriginalNode,
+    TailoredGenNode,
+    TailoredModelInfoNode,
+    Text2ImageBaseNode,
+    Text2ImageFastNode,
+    Text2ImageHDNode,
+    TailoredPortraitNode,
+    ReimagineNode,
+    GenerateImageNodeV2,
+    RefineImageNodeV2,
+    ShotByTextAutomaticNode,
+    ShotByImageManualPaddingNode,
+    ShotByImageAutomaticAspectRatioNode,
+    ShotByImageCustomCoordinatesNode,
+    ShotByImageManualPlacementNode,
+    ShotByImageAutomaticNode,
+    ShotByTextAutomaticAspectRatioNode,
+    ShotByTextManualPlacementNode,
+    ShotByTextManualPaddingNode,
+    ShotByTextCustomCoordinatesNode,
+    AttributionByImageNode
+)
+
 # Map the node class to a name used internally by ComfyUI
 NODE_CLASS_MAPPINGS = {
    "BriaEraser": EraserNode,  # Return the class, not an instance
@@ -9,8 +37,18 @@ NODE_CLASS_MAPPINGS = {
    "ReplaceBgNode": ReplaceBgNode,
    "RmbgNode": RmbgNode,
    "RemoveForegroundNode": RemoveForegroundNode,
-    "ShotByTextNode": ShotByTextNode,
-    "ShotByImageNode": ShotByImageNode,
+    "ShotByTextOriginal": ShotByTextOriginalNode,
+    "ShotByImageOriginal": ShotByImageOriginalNode,
+    "ShotByTextAutomatic": ShotByTextAutomaticNode,
+    "ShotByTextManualPlacement": ShotByTextManualPlacementNode,
+    "ShotByTextCustomCoordinates": ShotByTextCustomCoordinatesNode,
+    "ShotByTextManualPadding": ShotByTextManualPaddingNode,
+    "ShotByTextAutomaticAspectRatio": ShotByTextAutomaticAspectRatioNode,
+    "ShotByImageAutomatic": ShotByImageAutomaticNode,
+    "ShotByImageManualPlacement": ShotByImageManualPlacementNode,
+    "ShotByImageCustomCoordinates": ShotByImageCustomCoordinatesNode,
+    "ShotByImageManualPadding": ShotByImageManualPaddingNode,
+    "ShotByImageAutomaticAspectRatio": ShotByImageAutomaticAspectRatioNode,
    "BriaTailoredGen": TailoredGenNode,
    "TailoredModelInfoNode": TailoredModelInfoNode,
    "TailoredPortraitNode": TailoredPortraitNode,
@@ -18,6 +56,9 @@ NODE_CLASS_MAPPINGS = {
    "Text2ImageFastNode": Text2ImageFastNode,
    "Text2ImageHDNode": Text2ImageHDNode,
    "ReimagineNode": ReimagineNode,
+    "AttributionByImageNode": AttributionByImageNode,
+    "GenerateImageNodeV2": GenerateImageNodeV2,
+    "RefineImageNodeV2": RefineImageNodeV2,
 }
 # Map the node display name to the one shown in the ComfyUI node interface
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -27,8 +68,18 @@ NODE_DISPLAY_NAME_MAPPINGS = {
    "ReplaceBgNode": "Bria Replace Background",
    "RmbgNode": "Bria RMBG",
    "RemoveForegroundNode": "Bria Remove Foreground",
-    "ShotByTextNode": "Bria Shot By Text",
-    "ShotByImageNode": "Bria Shot By Image",
+    "ShotByTextOriginal": "Shot by Text - Original",
+    "ShotByImageOriginal": "Shot by Image - Original",
+    "ShotByTextAutomatic": "Shot by Text - Automatic",
+    "ShotByTextManualPlacement": "Shot by Text - Manual Placement",
+    "ShotByTextCustomCoordinates": "Shot by Text - Custom Coordinates",
+    "ShotByTextManualPadding": "Shot by Text - Manual Padding",
+    "ShotByTextAutomaticAspectRatio": "Shot by Text - Automatic Aspect Ratio",
+    "ShotByImageAutomatic": "Shot by Image - Automatic",
+    "ShotByImageManualPlacement": "Shot by Image - Manual Placement",
+    "ShotByImageCustomCoordinates": "Shot by Image - Custom Coordinates",
+    "ShotByImageManualPadding": "Shot by Image - Manual Padding",
+    "ShotByImageAutomaticAspectRatio": "Shot by Image - Automatic Aspect Ratio",
    "BriaTailoredGen": "Bria Tailored Gen",
    "TailoredModelInfoNode": "Bria Tailored Model Info",
    "TailoredPortraitNode": "Bria Restyle Portrait",
@@ -36,4 +87,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
    "Text2ImageFastNode": "Bria Text2Image Fast",
    "Text2ImageHDNode": "Bria Text2Image HD",
    "ReimagineNode": "Bria Reimagine",
+    "AttributionByImageNode": "Attribution By Image Node",
+    "GenerateImageNodeV2": "Generate Image",
+    "RefineImageNodeV2": "Refine and Regenerate Image",
 }
@@ -4,12 +4,27 @@ from .image_expansion_node import ImageExpansionNode
 from .replace_bg_node import ReplaceBgNode
 from .rmbg_node import RmbgNode
 from .remove_foreground_node import RemoveForegroundNode
-from .shot_by_text_node import ShotByTextNode
-from .shot_by_image_node import ShotByImageNode
 from .tailored_gen_node import TailoredGenNode
 from .tailored_model_info_node import TailoredModelInfoNode
 from .tailored_portrait_node import TailoredPortraitNode
 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 .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
+from .shot_by_text_custom_coordinates_node import ShotByTextCustomCoordinatesNode
+from .shot_by_text_manual_placement_node import ShotByTextManualPlacementNode
+from .shot_by_text_manual_padding_node import ShotByTextManualPaddingNode
+from .shot_by_image_automatic_aspect_ratio_node import (
+    ShotByImageAutomaticAspectRatioNode,
+)
+from .shot_by_image_automatic_node import ShotByImageAutomaticNode
+from .shot_by_image_custom_coordinates_node import ShotByImageCustomCoordinatesNode
+from .shot_by_image_node import ShotByImageOriginalNode
+from .shot_by_image_manual_placement_node import ShotByImageManualPlacementNode
+from .shot_by_image_manual_padding_node import ShotByImageManualPaddingNode
+from .attribution_by_image_node import AttributionByImageNode
@@ -0,0 +1,67 @@
+import requests
+import torch
+
+from .common import deserialize_and_get_comfy_key, preprocess_image, image_to_base64, poll_status_until_completed
+
+class AttributionByImageNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "model_version": (["2.3", "3.0","3.2"], {"default": "2.3"}),
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}),
+            },              
+        }
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("api_response",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"  # This is the method that will be executed
+
+    def __init__(self):
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/attribution/by_image"
+
+    # Define the execute method as expected by ComfyUI
+    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):
+            image = preprocess_image(image)
+
+        # Convert image to base64 for the new API format
+        image_base64 = image_to_base64(image)
+        payload = {
+            "image": image_base64,
+            "model_version": model_version,
+        }
+
+        headers = {
+            "Content-Type": "application/json",
+            "api_token": f"{api_key}"
+        }
+
+        try:
+            response = requests.post(self.api_url, json=payload, headers=headers)
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial Attribution via Images API request successful, 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_key)
+                return (str(final_response.get("result",{}).get("content")),)
+            else:
+                raise Exception(f"Error: API request failed with status code {response.status_code} {response.text}")
+        except Exception as e:
+            raise Exception(f"{e}")
@@ -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)
+
+   
@@ -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"
@@ -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):
@@ -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 ()
@@ -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"
@@ -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,
@@ -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):
@@ -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):
@@ -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)
@@ -0,0 +1,46 @@
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageAutomaticAspectRatioNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        input_types["required"]["aspect_ratio"] = (
+            ["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
+            {"default": "1:1"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+
+    def execute(
+        self,
+        image,
+        ref_image,
+        aspect_ratio,
+        api_key,
+        sync=False,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.AUTOMATIC_ASPECT_RATIO.value,
+            aspect_ratio=aspect_ratio,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,51 @@
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageAutomaticNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        return input_types
+
+    RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE")
+    RETURN_NAMES = (
+        "output_image_1",
+        "output_image_2",
+        "output_image_3",
+        "output_image_4",
+        "output_image_5",
+        "output_image_6",
+        "output_image_7",
+    )
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+
+    def execute(
+        self,
+        image,
+        ref_image,
+        shot_size,
+        api_key,
+        sync=False,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.AUTOMATIC.value,
+            shot_size=shot_size,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key, Placement_type =  PlacementType.AUTOMATIC.value)
@@ -0,0 +1,55 @@
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageCustomCoordinatesNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        input_types["required"]["foreground_image_size"] = (
+            "STRING",
+            {"default": "500,500"},
+        )
+        input_types["required"]["foreground_image_location"] = (
+            "STRING",
+            {"default": "0, 0"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+
+    def execute(
+        self,
+        image,
+        ref_image,
+        shot_size,
+        foreground_image_size,
+        foreground_image_location,
+        api_key,
+        sync=False,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.CUSTOM_COORDINATES.value,
+            shot_size=shot_size,
+            foreground_image_size=foreground_image_size,
+            foreground_image_location=foreground_image_location,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,44 @@
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageManualPaddingNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        input_types["required"]["padding_values"] = ("STRING", {"default": "0,0,0,0"})
+
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+
+    def execute(
+        self,
+        image,
+        ref_image,
+        padding_values,
+        api_key,
+        sync=False,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.MANUAL_PADDING.value,
+            padding_values=padding_values,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,59 @@
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageManualPlacementNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        input_types["required"]["manual_placement_selection"] = (
+            [
+                "upper_left",
+                "upper_right",
+                "bottom_left",
+                "bottom_right",
+                "right_center",
+                "left_center",
+                "upper_center",
+                "bottom_center",
+                "center_vertical",
+                "center_horizontal",
+            ],
+            {"default": "upper_left"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+    def execute(
+        self,
+        image,
+        ref_image,
+        shot_size,
+        manual_placement_selection,
+        api_key,
+        sync=False,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.MANUAL_PLACEMENT.value,
+            shot_size=shot_size,
+            manual_placement_selection=manual_placement_selection,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -1,72 +1,41 @@
-import requests
-import torch
-
-from .common import postprocess_image, preprocess_image, image_to_base64
-
-class ShotByImageNode():
-    @classmethod
-    def INPUT_TYPES(self):
-        return {
-            "required": {
-                "image": ("IMAGE",),  # Input image from another node
-                "ref_image": ("IMAGE",),  # ref image from another node
-                "enhance_ref_image": ("INT", {"default": 1}),
-                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"})  # API Key input with a default value
-            },
-            "optional": {
-                "content_moderation": ("BOOLEAN", {"default": False}), 
-            }        
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("output_image",)
-    CATEGORY = "API Nodes"
-    FUNCTION = "execute"  # This is the method that will be executed
-
-    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_image"  # Eraser API URL
-
-    # Define the execute method as expected by ComfyUI
-    def execute(self, image, ref_image, api_key, enhance_ref_image, content_moderation):
-        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
-            raise Exception("Please insert a valid API key.")
-
-        # Check if image and mask are tensors, if so, convert to NumPy arrays
-        if isinstance(image, torch.Tensor):
-            image = preprocess_image(image)
-        if isinstance(ref_image, torch.Tensor):
-            ref_image = preprocess_image(ref_image)
-
-        # Convert the image and mask directly to Base64 strings                    
-        image_base64 = image_to_base64(image)
-        ref_image_base64 = image_to_base64(ref_image)
-        enhance_ref_image = bool(enhance_ref_image)
-
-        payload = {
-            "file": image_base64,
-            "ref_image_file": ref_image_base64,
-            "enhance_ref_image": enhance_ref_image,
-            "placement_type": "original",
-            "original_quality": True, 
-            "sync": True,
-            "content_moderation": content_moderation
-        }
-        headers = {
-            "Content-Type": "application/json",
-            "api_token": f"{api_key}"
-        }        
-        try:
-            response = requests.post(self.api_url, json=payload, headers=headers)
-            # Check for successful response
-            if response.status_code == 200:
-                print('response is 200')
-                # Process the output image from API response
-                response_dict = response.json()
-                image_response = requests.get(response_dict['result'][0][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}")
-
-        except Exception as e:
-            raise Exception(f"{e}")        
+from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
+
+
+class ShotByImageOriginalNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_image_input_types()
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_image_api_url
+
+    def execute(
+        self,
+        image,
+        ref_image,
+        api_key,
+        sync=True,
+        enhance_ref_image=True,
+        ref_image_influence=1.0,
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_image_payload(
+            image,
+            ref_image,
+            api_key,
+            PlacementType.ORIGINAL.value,
+            original_quality=True,
+            sync=sync,
+            enhance_ref_image=enhance_ref_image,
+            ref_image_influence=ref_image_influence,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,48 @@
+from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextAutomaticAspectRatioNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        input_types["required"]["aspect_ratio"] = (
+            ["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
+            {"default": "1:1"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        aspect_ratio,
+        api_key,
+        sync=False,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.AUTOMATIC_ASPECT_RATIO.value,
+            aspect_ratio=aspect_ratio,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,53 @@
+from  .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextAutomaticNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        return input_types
+
+    RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE")
+    RETURN_NAMES = (
+        "output_image_1",
+        "output_image_2",
+        "output_image_3",
+        "output_image_4",
+        "output_image_5",
+        "output_image_6",
+        "output_image_7",
+    )
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        shot_size,
+        api_key,
+        sync=False,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.AUTOMATIC.value,
+            shot_size=shot_size,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key, Placement_type= PlacementType.AUTOMATIC.value)
@@ -0,0 +1,57 @@
+from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextCustomCoordinatesNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        input_types["required"]["foreground_image_size"] = (
+            "STRING",
+            {"default": "500,500"},
+        )
+        input_types["required"]["foreground_image_location"] = (
+            "STRING",
+            {"default": "0, 0"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        shot_size,
+        foreground_image_size,
+        foreground_image_location,
+        api_key,
+        sync=False,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.CUSTOM_COORDINATES.value,
+            shot_size=shot_size,
+            foreground_image_size=foreground_image_size,
+            foreground_image_location=foreground_image_location,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,45 @@
+from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextManualPaddingNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        input_types["required"]["padding_values"] = ("STRING", {"default": "0,0,0,0"})
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        padding_values,
+        api_key,
+        sync=False,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.MANUAL_PADDING.value,
+            padding_values=padding_values,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,62 @@
+from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextManualPlacementNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
+        input_types["required"]["manual_placement_selection"] = (
+            [
+                "upper_left",
+                "upper_right",
+                "bottom_left",
+                "bottom_right",
+                "right_center",
+                "left_center",
+                "upper_center",
+                "bottom_center",
+                "center_vertical",
+                "center_horizontal",
+            ],
+            {"default": "upper_left"},
+        )
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        shot_size,
+        manual_placement_selection,
+        api_key,
+        sync=False,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.MANUAL_PLACEMENT.value,
+            shot_size=shot_size,
+            manual_placement_selection=manual_placement_selection,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -1,68 +1,42 @@
-import requests
-import torch
-
-from .common import postprocess_image, preprocess_image, image_to_base64
-
-class ShotByTextNode():
-    @classmethod
-    def INPUT_TYPES(self):
-        return {
-            "required": {
-                "image": ("IMAGE",),  # Input image from another node
-                "scene_description": ("STRING",),
-                "mode": (["base", "fast", "high_control"], {"default": "high_control"}),
-                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"})  # API Key input with a default value
-            },
-            "optional": {
-                "content_moderation": ("BOOLEAN", {"default": False}), 
-            }   
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("output_image",)
-    CATEGORY = "API Nodes"
-    FUNCTION = "execute"  # This is the method that will be executed
-
-    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_text"  # Eraser API URL
-        
-    # Define the execute method as expected by ComfyUI
-    def execute(self, image, api_key, scene_description, mode, content_moderation):
-        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
-            raise Exception("Please insert a valid API key.")
-
-        # Check if image and mask are tensors, if so, convert to NumPy arrays
-        if isinstance(image, torch.Tensor):
-            image = preprocess_image(image)
-
-        image_base64 = image_to_base64(image)
-        payload = {
-            "file": image_base64,
-            "scene_description": scene_description,
-            "mode": mode,
-            "placement_type": "original",
-            "original_quality": True,
-            "sync": True,
-            "content_moderation": content_moderation
-
-        }
-        headers = {
-            "Content-Type": "application/json",
-            "api_token": f"{api_key}"
-        }        
-        try:
-            response = requests.post(self.api_url, json=payload, headers=headers)
-            # Check for successful response
-            if response.status_code == 200:
-                print('response is 200')
-                # Process the output image from API response
-                response_dict = response.json()
-                image_response = requests.get(response_dict['result'][0][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}")
-
-        except Exception as e:
-            raise Exception(f"{e}")                
-
+from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
+
+
+class ShotByTextOriginalNode:
+    @classmethod
+    def INPUT_TYPES(self):
+        input_types = get_text_input_types()
+        return input_types
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("output_image",)
+    CATEGORY = "API Nodes"
+    FUNCTION = "execute"
+
+    def __init__(self):
+        self.api_url = shot_by_text_api_url
+    def execute(
+        self,
+        image,
+        scene_description,
+        mode,
+        api_key,
+        sync=True,
+        optimize_description=True,
+        exclude_elements="",
+        force_rmbg=False,
+        content_moderation=False,
+    ):
+        payload = create_text_payload(
+            image,
+            api_key,
+            scene_description,
+            mode,
+            PlacementType.ORIGINAL.value,
+            original_quality=True,
+            sync=sync,
+            optimize_description=optimize_description,
+            exclude_elements=exclude_elements,
+            force_rmbg=force_rmbg,
+            content_moderation=content_moderation,
+        )
+        return make_api_request(self.api_url, payload, api_key)
@@ -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,
@@ -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}
@@ -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}")
@@ -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,
@@ -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,
@@ -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,
@@ -0,0 +1,207 @@
+import requests
+import torch
+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"
+)
+shot_by_image_api_url = (
+    "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_image"
+)
+
+from enum import Enum
+
+class PlacementType(str, Enum):
+    ORIGINAL = "original"
+    AUTOMATIC = "automatic"
+    MANUAL_PLACEMENT = "manual_placement"
+    MANUAL_PADDING = "manual_padding"
+    CUSTOM_COORDINATES = "custom_coordinates"
+    AUTOMATIC_ASPECT_RATIO = "automatic_aspect_ratio"
+
+
+
+def validate_api_key(api_key):
+    """Validate API key input"""
+    if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
+        raise Exception("Please insert a valid API key.")
+
+
+def update_payload_for_placement(placement_type, payload, **kwargs):
+    if placement_type == PlacementType.AUTOMATIC.value:
+        payload["shot_size"] = [
+            int(x.strip()) for x in kwargs.get("shot_size").split(",")
+        ]
+    elif placement_type == PlacementType.MANUAL_PLACEMENT.value:
+        payload["shot_size"] = [
+            int(x.strip()) for x in kwargs.get("shot_size").split(",")
+        ]
+        payload["manual_placement_selection"] = [
+            kwargs.get("manual_placement_selection", "upper_left")
+        ]
+    elif placement_type == PlacementType.CUSTOM_COORDINATES.value:
+        payload["shot_size"] = [
+            int(x.strip()) for x in kwargs.get("shot_size").split(",")
+        ]
+        payload["foreground_image_size"] = [
+            int(x.strip()) for x in kwargs.get("foreground_image_size").split(",")
+        ]
+        payload["foreground_image_location"] = [
+            int(x.strip()) for x in kwargs.get("foreground_image_location").split(",")
+        ]
+    elif placement_type == PlacementType.MANUAL_PADDING.value:
+        payload["padding_values"] = [
+            int(x.strip()) for x in kwargs.get("padding_values").split(",")
+        ]
+
+    elif placement_type == PlacementType.AUTOMATIC_ASPECT_RATIO.value:
+        payload["aspect_ratio"] = kwargs.get("aspect_ratio", "1:1")
+    elif placement_type == PlacementType.ORIGINAL.value:
+        payload["original_quality"] = kwargs.get("original_quality", True)
+
+    return payload
+
+
+def create_text_payload(
+    image, api_key, scene_description, mode, placement_type, **kwargs
+):
+
+    validate_api_key(api_key)
+
+
+    # Process image
+    if isinstance(image, torch.Tensor):
+        image = preprocess_image(image)
+
+    image_base64 = image_to_base64(image)
+
+    payload = {
+        "file": image_base64,
+        "placement_type": placement_type,
+        "sync": True,
+        "num_results": 1,
+        "force_rmbg": kwargs.get("force_rmbg", False),
+        "content_moderation": kwargs.get("content_moderation", False),
+        "scene_description": scene_description,
+        "mode": mode,
+        "optimize_description": kwargs.get("optimize_description", True),
+    }
+
+    if kwargs.get("exclude_elements", "").strip():
+        payload["exclude_elements"] = kwargs["exclude_elements"]
+
+    payload = update_payload_for_placement(placement_type, payload, **kwargs)
+
+    return payload
+
+
+def create_image_payload(image, ref_image, api_key, placement_type, **kwargs):
+    """Create payload for image-based shot nodes"""
+    validate_api_key(api_key)
+
+    if isinstance(image, torch.Tensor):
+        image = preprocess_image(image)
+        if isinstance(ref_image, torch.Tensor):
+            ref_image = preprocess_image(ref_image)
+
+        image_base64 = image_to_base64(image)
+        ref_image_base64 = image_to_base64(ref_image)
+
+    # Base payload
+    payload = {
+        "file": image_base64,
+        "ref_image_file": ref_image_base64,
+        "enhance_ref_image": kwargs.get("enhance_ref_image", True),
+        "ref_image_influence": kwargs.get("ref_image_influence", 1.0),
+        "placement_type": placement_type,
+        "sync": True,
+        "num_results": 1,
+        "force_rmbg": kwargs.get("force_rmbg", False),
+        "content_moderation": kwargs.get("content_moderation", False),
+    }
+
+    payload = update_payload_for_placement(placement_type, payload, **kwargs)
+
+    return payload
+
+
+def make_api_request(api_url, payload, api_key, Placement_type = None):
+    """Make API request and return processed image"""
+
+
+    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:
+            print("response is 200")
+            response_dict = response.json()
+            if Placement_type == PlacementType.AUTOMATIC.value:
+                result_images = []
+                for i, result in enumerate(response_dict.get("result", [])[:7]):
+                    image_url = result[0]
+                    image_response = requests.get(image_url)
+                    processed = postprocess_image(image_response.content)
+                    result_images.append(processed)
+
+                # If less than 7 images, pad with None to match ComfyUI return structure
+                while len(result_images) < 7:
+                    result_images.append(None)
+                print(result_images)
+
+                return tuple(result_images)
+
+            image_response = requests.get(response_dict["result"][0][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}{response.text}"
+            )
+
+    except Exception as e:
+        raise Exception(f"{e}")
+
+
+def get_common_input_types():
+    """Get common input types for all nodes"""
+    return {
+        "required": {"api_key": ("STRING", {"default": "BRIA_API_TOKEN"})},
+        "optional": {
+            "force_rmbg": ("BOOLEAN", {"default": False}),
+            "content_moderation": ("BOOLEAN", {"default": False}),
+        },
+    }
+
+
+def get_text_input_types():
+    """Get text-specific input types"""
+    common = get_common_input_types()
+    common["required"].update(
+        {
+            "image": ("IMAGE",),
+            "scene_description": ("STRING",),
+            "mode": (["base", "fast", "high_control"], {"default": "fast"}),
+        }
+    )
+    common["optional"].update(
+        {
+            "optimize_description": ("BOOLEAN", {"default": True}),
+            "exclude_elements": ("STRING", {"default": ""}),
+        }
+    )
+    return common
+
+
+def get_image_input_types():
+    """Get image-specific input types"""
+    common = get_common_input_types()
+    common["required"].update({"image": ("IMAGE",), "ref_image": ("IMAGE",)})
+    common["optional"].update(
+        {
+            "enhance_ref_image": ("BOOLEAN", {"default": True}),
+            "ref_image_influence": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}),
+        }
+    )
+    return common
@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-bria-api"
 description = "Custom nodes for ComfyUI using BRIA's API."
-version = "2.1.0"
+version = "2.1.7"
 license = {file = "LICENSE"}

 [project.urls]
@@ -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,
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@@ -212,12 +217,12 @@
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          "name": "output_image",
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@@ -285,12 +292,13 @@
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+}
Author	SHA1	Message	Date
Ubuntu	b5d4d41bb8	update version	2025-11-12 12:03:13 +00:00
Ubuntu	0f2b1115c5	fix invalid token error message	2025-11-12 09:44:45 +00:00
Yazan Numoor	b408c8781a	Update pyproject.toml	2025-11-11 15:50:02 +02:00
Yazan Numoor	f6e134cfd3	Merge pull request #30 from Bria-AI/WAI-4030 WAI-4030	2025-11-11 15:39:44 +02:00
Ubuntu	7855c4dba2	WAI-4030	2025-11-09 06:51:29 +00:00
galbria	c1f67dd4fb	remove FIBO Workflow.json file	2025-10-30 15:41:37 +02:00
ליזה ירושבסקי	c1a77106b4	adding fibo workflow	2025-10-30 15:39:49 +02:00
Yazan Numoor	0f170bfc6b	Merge pull request #29 from Bria-AI/fix_comfy_refine_to_support_generate fix_comfy_refine_to_support_generate	2025-10-29 18:27:06 +02:00
Ubuntu	6b4b9e2dee	update version	2025-10-29 16:26:29 +00:00
Ubuntu	4385a8c429	fix_comfy_refine_to_support_generate	2025-10-29 16:18:44 +00:00
Yazan Numoor	dd8d70000f	Merge pull request #27 from Bria-AI/WAI-4116 WAI-4116	2025-10-29 17:08:48 +02:00
Ubuntu	582e16600e	Merge branch 'WAI-4116' of https://github.com/Bria-AI/ComfyUI-BRIA-API into WAI-4116	2025-10-29 12:12:53 +00:00
Ubuntu	33f657ccbd	update version	2025-10-29 12:12:29 +00:00
mabualrob1997	f8a6650b4b	Update Readme.md	2025-10-29 14:10:43 +02:00
Ubuntu	493d23bdcb	remove pro nodes	2025-10-29 11:24:22 +00:00
Ubuntu	ecf52dd764	fix images paramter	2025-10-28 15:08:16 +00:00
Ubuntu	a9f894102d	remmove duplicate import	2025-10-28 07:06:24 +00:00
Ubuntu	e50dd5dd63	remmove duplicate import	2025-10-28 07:04:34 +00:00
Ubuntu	00ce39dae5	Merge branch 'main' of https://github.com/Bria-AI/ComfyUI-BRIA-API into WAI-4116	2025-10-28 07:01:47 +00:00
Ubuntu	270128d32a	add fibo pro nodes	2025-10-27 20:19:53 +00:00
Yazan Numoor	513fec79b5	Merge pull request #26 from Bria-AI/WAI-4049 WAI-4049	2025-10-23 09:48:24 +03:00
Yazan Numoor	ddbf7d0695	Update pyproject.toml	2025-10-22 20:38:36 +03:00
Ubuntu	43893286cc	update Gaia model name to Fibo	2025-10-16 09:27:30 +00:00
Ubuntu	3befc0a2ac	update automatic nodes to return 7 results	2025-10-16 08:15:20 +00:00
Ubuntu	af6ef2a829	fix Gabi Feedback	2025-10-15 10:39:44 +00:00
Ubuntu	96d2924dfc	WAI-4116	2025-10-14 12:30:13 +00:00
Ubuntu	327ace887b	WAI-4116	2025-10-14 08:57:45 +00:00
Ubuntu	bc5dacb9ef	Merge branch 'main' of https://github.com/Bria-AI/ComfyUI-BRIA-API into WAI-4049	2025-09-29 13:44:10 +00:00
Ubuntu	fc8aa8b6a7	WAI-4049	2025-09-29 13:39:47 +00:00
Yazan Numoor	9960a93044	Merge pull request #25 from Bria-AI/WAI-4011 WAI-4011	2025-09-29 15:47:10 +03:00
Ubuntu	8d3eef85ca	update version	2025-09-29 12:44:46 +00:00
Ubuntu	bb4108b6c4	WAI-4049	2025-09-29 11:48:24 +00:00
mabualrob1997	18a5ffbcca	Update Readme.md	2025-09-29 12:45:46 +03:00
Ubuntu	4f3b7fb77a	WAI-4011	2025-09-23 06:49:12 +00:00
Yazan Numoor	c3b5fea335	Update pyproject.toml	2025-09-18 19:31:00 +03:00
Yazan Numoor	b8e40e90bc	Merge pull request #24 from Bria-AI/WAI-3976-feedback-fixes WAI-3976-feedback-fixes	2025-09-18 19:30:33 +03:00