Update pyproject.toml

update automatic nodes to return 7 results
fix Gabi Feedback
2025-10-22 20:38:36 +03:00 · 2025-10-16 08:15:20 +00:00 · 2025-10-15 10:39:44 +00:00 · 2025-09-29 13:44:10 +00:00 · 2025-09-29 13:39:47 +00:00 · 2025-09-29 15:47:10 +03:00
45 changed files with 1624 additions and 1517 deletions
@@ -7,17 +7,19 @@ on:
    paths:
      - "pyproject.toml"

+permissions:
+  issues: write
+
 jobs:
  publish-node:
    name: Publish Custom Node to registry
    runs-on: ubuntu-latest
-    # if this is a forked repository. Skipping the workflow.
-    if: github.event.repository.fork == false 
+    if: ${{ github.repository_owner == 'Bria-AI' }}
    steps:
      - name: Check out code
        uses: actions/checkout@v4
      - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@v1
        with:
          ## Add your own personal access token to your Github Repository secrets and reference it here.
          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
@@ -1 +1,2 @@
-*.pyc
+*.pyc
+.idea
@@ -4,14 +4,22 @@
  <img src="./images/Bria Logo.svg" alt="BRIA Logo" width="200"/>
 </p>

-This repository provides custom nodes for ComfyUI, enabling direct access to **BRIA's API endpoints** for image generation workflows. **API documentation** is available [**here**](https://bria-ai-api-docs.redoc.ly/#operation//generation/bria-v2/text-to-image). 
+This repository provides custom nodes for ComfyUI, enabling direct access to **BRIA's API endpoints** for image generation and editing workflows. **API documentation** is available [**here**](https://docs.bria.ai/). 
+
+BRIA's APIs and models are built for commercial use and trained on 100% licensed data and does not contain copyrighted materials, such as fictional characters, logos, trademarks, public figures, harmful content, or privacy-infringing content.

 An API token is required to use the nodes in your workflows. Get started quickly here
 <a href="https://bria.ai/api/" style="text-decoration:none; vertical-align:middle;">
  <img src="https://img.shields.io/badge/GET%20YOUR%20TOKEN-1000%20Free%20Calls-blue?style=flat-square" alt="Get Your Token" height="20">
 </a>.

+for direct API endpoint use, you can find our APIs through partners like [**fal.ai**](https://fal.ai/models?keywords=bria).  
+For source code and weigths access, go to our [**Hugging Face**](https://huggingface.co/briaai) space.
+
 To load a workflow, import the compatible workflow.json files from this [folder](workflows).  
+<p align="center">
+  <img src="./images/background_workflow.png" width="1200"/>
+</p>


 <!-- Placeholder image of cool workflows. -->
@@ -19,43 +27,55 @@ To load a workflow, import the compatible workflow.json files from this [folder]

 <!-- <img src="./images/bria_api_nodes_workflow_diagram.png" alt="all workflows example" width="400"/> <img src="./images/bria_api_nodes_workflow_diagram_2.png" alt="all workflows example" width="400"/> -->

-# Coming soon
-
- [ ] Video Editing
-
 # 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.

-### **Text2Image Base Node**
-This node generates images from text prompts, serving as the foundation for creating visuals based on descriptive input. [[🤗model card](https://huggingface.co/briaai/BRIA-2.3)]
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **Text2Image Base**    | Generates images from text prompts, serving as the foundation for text-based image creation. |
+| **Text2Image Fast**    | Optimized for speed, this node generates images from text prompts with faster results while maintaining quality. |
+| **Text2Image HD**      | Optimized for high-resolution outputs, this node generates detailed and sharp visuals from text prompts. |
+| **Reimagine**          | Guides image generation using both prompts and an input image. Preserve the original structure and depth while introducing new materials, colors, and textures. |

 ## Tailored Generation Nodes
-These nodes use pre-trained tailored models to generate images that faithfully reproduce specific visual IP elements or guidelines. [[API docs](https://bria-ai-api-docs.redoc.ly/tag/Tailored-Generation)].
+These nodes use pre-trained tailored models to generate images that faithfully reproduce specific visual IP elements or guidelines.

-### **Tailored Gen**
-This node generates images using a trained tailored model, faithfully reproducing specific visual IP elements or guidelines established during model training.
-
-### **Tailored Model Info**
-This node retrieves the **default settings** and **prompt prefix** of a **trained tailored model**. It provides the necessary information to configure and run the model in the **Tailored Gen node**, ensuring consistency with the model's intended behavior.  
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **Tailored Gen**       | Generates images using a trained tailored model, reproducing specific visual IP elements or guidelines. Use the Tailored Model Info node to load the model's default settings. |
+| **Tailored Model Info**| Retrieves the default settings and prompt prefix of a trained tailored model, which can be used to configure the Tailored Gen node. |
+| **Restyle Portrait**   | Transforms the style of a portrait while preserving the person's facial features. |

 ## Image Editing Nodes
-These nodes modify specific parts of images, enabling adjustments, while maintaining the integrity of the rest of the image.[[API docs](https://bria-ai-api-docs.redoc.ly/tag/Image-Editing)]
+These nodes modify specific parts of images, enabling adjustments while maintaining the integrity of the rest of the image.

-### **Eraser**
-This node is used to remove specific objects or areas from an image by providing a mask. Powered by BRIA's ControlNet inpainting [[🤗model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Inpainting)] [[🤗HF demo](https://huggingface.co/spaces/briaai/BRIA-Eraser-API)].
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **RMBG 2.0 (Remove Background)** | Removes the background from an image, isolating the foreground subject. |
+| **Replace Background**  | Replaces an image’s background with a new one, guided by either a reference image or a prompt. |
+| **Expand Image**        | Expands the dimensions of an image, generating new content to fill the extended areas. |
+| **Eraser**             | Removes specific objects or areas from an image by providing a mask. |
+| **GenFill**            | Generates objects by prompt in a specific region of an image. |
+| **Erase Foreground**    | Removes the foreground from an image, isolating the background. |

-### **GenFill**
-This node is used to generate objects by prompt in a specific region of an image. This functionality is powered by BRIA's ControlNet Generative Fill. [[🤗model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Generative-Fill)] [[🤗HF demo](https://huggingface.co/spaces/briaai/BRIA-Generative-Fill-API)]
+## Product Shot Editing Nodes
+These nodes create high-quality product images for eCommerce workflows.
+
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **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) |

-## Product Shot Generation Nodes
-These nodes create high-quality product images for eCommerce workflows. [[API docs](https://bria-ai-api-docs.redoc.ly/tag/Product-Shots-Generation)]

-### **ShotByText**
-This node is used to modify the background in an image by providing a prompt, This functionality is powered by BRIA's ControlNet Background-Generation.[[🤗ContrlNet model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-BG-Gen)] [[🤗HF demo](https://huggingface.co/spaces/briaai/Product-Shot-Generation)].

-### **ShotByImage**
-This node is used to modify the background in an image by providing a reference image. This functionality is powered by BRIA's ControlNet Background-Generation and BRIA's Image-Prompt. [[🤗ContrlNet model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Inpainting)] [[🤗IP-Adapter model card](https://huggingface.co/briaai/Image-Prompt)] [[🤗HF demo](https://huggingface.co/spaces/briaai/Product-Shot-Generation)].

 # Installation
 There are two methods to install the BRIA ComfyUI API nodes:
@@ -1,6 +1,32 @@
-from .nodes import (EraserNode, GenFillNode, ImageExpansionNode, ReplaceBgNode, RmbgNode, RemoveForegroundNode, ShotByTextNode, ShotByImageNode, TailoredGenNode,
-                     TailoredModelInfoNode, Text2ImageBaseNode, Text2ImageFastNode, Text2ImageHDNode,
-                     ReimagineNode)
+from .nodes import (
+    EraserNode,
+    GenFillNode,
+    ImageExpansionNode,
+    ReplaceBgNode,
+    RmbgNode,
+    RemoveForegroundNode,
+    ShotByTextOriginalNode,
+    ShotByImageOriginalNode,
+    TailoredGenNode,
+    TailoredModelInfoNode,
+    Text2ImageBaseNode,
+    Text2ImageFastNode,
+    Text2ImageHDNode,
+    TailoredPortraitNode,
+    ReimagineNode,
+    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
@@ -9,14 +35,26 @@ 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,
    "Text2ImageBaseNode": Text2ImageBaseNode,
    "Text2ImageFastNode": Text2ImageFastNode,
    "Text2ImageHDNode": Text2ImageHDNode,
    "ReimagineNode": ReimagineNode,
+    "AttributionByImageNode":AttributionByImageNode
 }
 # Map the node display name to the one shown in the ComfyUI node interface
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -26,12 +64,24 @@ 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",
    "Text2ImageBaseNode": "Bria Text2Image Base",
    "Text2ImageFastNode": "Bria Text2Image Fast",
    "Text2ImageHDNode": "Bria Text2Image HD",
    "ReimagineNode": "Bria Reimagine",
+    "AttributionByImageNode":"Attribution By Image Node"
 }
@@ -4,11 +4,25 @@ 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 .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 +1,66 @@
+import requests
+import torch
+
+from .common import 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.")
+
+        # 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}")
@@ -5,6 +5,7 @@ import torch
 import base64
 from torchvision.transforms import ToPILImage
 import requests
+import time

 def postprocess_image(image):
    result_image = Image.open(io.BytesIO(image))
@@ -44,7 +45,7 @@ def preprocess_mask(mask):
    return mask


-def process_request(api_url, image, mask, api_key):
+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.")

@@ -58,10 +59,12 @@ def process_request(api_url, image, mask, api_key):
    image_base64 = image_to_base64(image)
    mask_base64 = image_to_base64(mask)

-    # Prepare the API request payload
+    # Prepare the API request payload for v2 API
    payload = {
-        "file": f"{image_base64}",
-        "mask_file": f"{mask_base64}"
+        "image": image_base64,
+        "mask": mask_base64,
+        "visual_input_content_moderation":visual_input_content_moderation,
+        "visual_output_content_moderation":visual_output_content_moderation
    }

    headers = {
@@ -70,13 +73,23 @@ def process_request(api_url, image, mask, api_key):
    }

    try:
-        response = requests.post(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 = requests.post(api_url, json=payload, headers=headers) 
+        if response.status_code == 200 or response.status_code == 202:
+            print('Initial request successful, polling for completion...')
            response_dict = response.json()
-            image_response = requests.get(response_dict['result_url'])
+            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)
+            result_image_url = final_response['result']['image_url']
+            
+            # Download and process the result image
+            image_response = requests.get(result_image_url)
            result_image = Image.open(io.BytesIO(image_response.content))
            result_image = result_image.convert("RGBA")
            result_image = np.array(result_image).astype(np.float32) / 255.0
@@ -84,9 +97,51 @@ def process_request(api_url, image, mask, api_key):
            # image_tensor = image_tensor = ToTensor()(output_image)
            # image_tensor = image_tensor.permute(1, 2, 0) / 255.0  # Shape now becomes [1, 2200, 1548, 3]
            # print(f"output tensor shape is: {image_tensor.shape}")
-            return (result_image,)
+            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}")
+
+
+def poll_status_until_completed(status_url, api_key, timeout=360, check_interval=2):
+    """
+    Poll a status URL until the status is COMPLETED or timeout is reached.
+    
+    Args:
+        status_url (str): The status URL to poll
+        api_key (str): API token for authentication
+        timeout (int): Maximum time to wait in seconds (default: 360)
+        check_interval (int): Time between checks in seconds (default: 2)
+    
+    Returns:
+        dict: The final response containing the result
+    
+    Raises:
+        Exception: If timeout is reached or API request fails
+    """
+    start_time = time.time()
+    headers = {"api_token": api_key}
+    
+    while time.time() - start_time < timeout:
+        try:
+            response = requests.get(status_url, headers=headers)            
+            if response.status_code == 200 or response.status_code == 202:
+                response_dict = response.json()
+                status = response_dict.get("status", "").upper()
+                
+                if status == "COMPLETED":
+                    return response_dict
+                elif status == "ERROR":
+                    raise Exception(f"Request failed: {response_dict}")
+                else:
+                    print(f"Status: {status}, waiting...")
+                    time.sleep(check_interval)
+            else:
+                raise Exception(f"Status check failed with status code {response.status_code}")
+                
+        except requests.exceptions.RequestException as e:
+            raise Exception(f"Error checking status: {e}")
+    
+    raise Exception(f"Timeout reached after {timeout} seconds")
@@ -8,6 +8,10 @@ class EraserNode():
                "image": ("IMAGE",),  # Input image from another node
                "mask": ("MASK",),  # Binary mask input
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"})  # API Key input with a default value
+            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
            }
        }

@@ -17,9 +21,9 @@ class EraserNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/eraser"  # Eraser API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/erase"  # Eraser API URL

    # Define the execute method as expected by ComfyUI
-    def execute(self, image, mask, api_key):
-        return process_request(self.api_url, image, mask, api_key)
+    def execute(self, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation):
+        return process_request(self.api_url, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation)
    
@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch

-from .common import image_to_base64, preprocess_image, preprocess_mask
+from .common import preprocess_image, preprocess_mask, image_to_base64, poll_status_until_completed


 class GenFillNode():
@@ -17,6 +17,14 @@ class GenFillNode():
                "prompt": ("STRING",),
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
            },
+            "optional": {
+                "seed": ("INT", {"default": 123456}),
+                "prompt_content_moderation": ("BOOLEAN", {"default": True}), 
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+
+
+            }
        }

    RETURN_TYPES = ("IMAGE",)
@@ -25,10 +33,10 @@ class GenFillNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/gen_fill"  # Eraser API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/gen_fill"

    # Define the execute method as expected by ComfyUI
-    def execute(self, image, mask, prompt, api_key):
+    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.")

@@ -44,11 +52,14 @@ class GenFillNode():

        # Prepare the API request payload
        payload = {
-            "file": f"{image_base64}",
-            "mask_file": f"{mask_base64}",
+            "image": image_base64,
+            "mask": mask_base64,
            "prompt": prompt,
            "negative_prompt": "blurry",
-            "sync": True
+            "seed": seed,
+            "prompt_content_moderation":prompt_content_moderation,
+            "visual_input_content_moderation":visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation
        }

        headers = {
@@ -57,20 +68,30 @@ class GenFillNode():
        }

        try:
+            # Send initial request to get status URL
            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
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial genfill request successful, polling for completion...')
                response_dict = response.json()
-                image_response = requests.get(response_dict['urls'][0])
+                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)                
+                result_image_url = final_response['result']['image_url']
+                image_response = requests.get(result_image_url)
                result_image = Image.open(io.BytesIO(image_response.content))
                result_image = result_image.convert("RGB")
                result_image = np.array(result_image).astype(np.float32) / 255.0
                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}")
@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch

-from .common import image_to_base64, preprocess_image
+from .common import image_to_base64, preprocess_image, poll_status_until_completed


 class ImageExpansionNode():
@@ -13,16 +13,21 @@ class ImageExpansionNode():
        return {
            "required": {
                "image": ("IMAGE",),  # Input image from another node
-                "original_image_size": ("STRING",),
-                "original_image_location": ("STRING",),
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
            },
            
            "optional": {
+                "original_image_size": ("STRING",),
+                "original_image_location": ("STRING",),
                "canvas_size": ("STRING", {"default": "1000, 1000"}),
+                "aspect_ratio": (["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9","None"], {"default": "None"}),
                "prompt": ("STRING", {"default": ""}),
                "seed": ("INT", {"default": 681794}),
                "negative_prompt": ("STRING", {"default": "Ugly, mutated"}),
+                "prompt_content_moderation": ("BOOLEAN", {"default": False}),
+                "preserve_alpha": ("BOOLEAN", {"default": True}),
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}),
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}),
            } 
        }

@@ -32,26 +37,28 @@ class ImageExpansionNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/image_expansion"  # Image Expansion API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/expand"  # Image Expansion API URL

    # Define the execute method as expected by ComfyUI
    def execute(self, image, 
                original_image_size,
                original_image_location,
                canvas_size,
+                aspect_ratio,
                prompt,
                seed,
                negative_prompt,
+                prompt_content_moderation,
+                preserve_alpha,
+                visual_input_content_moderation,
+                visual_output_content_moderation,
                api_key):
        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
            raise Exception("Please insert a valid 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 ()
        
-        original_image_size = [int(x.strip()) for x in original_image_size.split(",")]
-        original_image_location = [int(x.strip()) for x in original_image_location.split(",")]
-        canvas_size = [int(x.strip()) for x in canvas_size.split(",")]
-        
-        if prompt == "":
-            prompt = None
        if negative_prompt == "":
            negative_prompt = " " # hack to avoid error in triton which expects non-empty string

@@ -61,18 +68,32 @@ class ImageExpansionNode():

        # Convert the image directly to Base64 string
        image_base64 = image_to_base64(image)
-
-        # Prepare the API request payload
-        payload = {
-            "file": f"{image_base64}",
-            "original_image_size": original_image_size,
-            "original_image_location": original_image_location,
-            "canvas_size": canvas_size,
+        if aspect_ratio and aspect_ratio != "None":
+            payload = {
+            "image": image_base64,
+            "aspect_ratio": aspect_ratio,
            "prompt": prompt,
            "negative_prompt": negative_prompt,
-            "seed": seed
-            # "sync": True
+            "seed": seed,
+            "prompt_content_moderation": prompt_content_moderation,
+            "preserve_alpha": preserve_alpha,
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation": visual_output_content_moderation
        }
+        else:
+            payload = {
+                "image": image_base64,
+                "original_image_size": original_image_size,
+                "original_image_location": original_image_location,
+                "canvas_size": canvas_size,
+                "prompt": prompt,
+                "negative_prompt": negative_prompt,
+                "seed": seed,
+                "prompt_content_moderation": prompt_content_moderation,
+                "preserve_alpha": preserve_alpha,
+                "visual_input_content_moderation": visual_input_content_moderation,
+                "visual_output_content_moderation": visual_output_content_moderation
+            }

        headers = {
            "Content-Type": "application/json",
@@ -81,19 +102,34 @@ class ImageExpansionNode():

        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
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial image expansion request successful, polling for completion...')
                response_dict = response.json()
-                image_response = requests.get(response_dict['result_url'])
+                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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
                result_image = Image.open(io.BytesIO(image_response.content))
                result_image = result_image.convert("RGB")
                result_image = np.array(result_image).astype(np.float32) / 255.0
                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}")
@@ -20,6 +20,7 @@ class ReimagineNode():
                "tailored_model_id": ("STRING", ),
                "tailored_model_influence": ("FLOAT", {"default": 0.5}),
                "tailored_generation_prefix": ("STRING",), # if used with tailored, possibly get this from the tailored model info node
+                "content_moderation": ("INT", {"default": 0}),
            }
        }

@@ -35,8 +36,8 @@ class ReimagineNode():
            self, api_key, prompt, seed, 
            steps_num, fast, structure_ref_influence, structure_image=None,
            tailored_model_id=None, tailored_model_influence=None, tailored_generation_prefix=None,
-        ):
-        fast = bool(fast)
+            content_moderation=0,
+        ):        
        payload = {
            "prompt": tailored_generation_prefix + prompt,
            "num_results": 1,
@@ -44,6 +45,7 @@ class ReimagineNode():
            "seed": seed,
            "steps_num": steps_num,
            "include_generation_prefix": False,
+            "content_moderation": content_moderation,
        }
        if structure_image is not None:
            structure_image = preprocess_image(structure_image)
@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch

-from .common import preprocess_image, image_to_base64
+from .common import preprocess_image, image_to_base64, poll_status_until_completed


 class RemoveForegroundNode():
@@ -15,6 +15,11 @@ class RemoveForegroundNode():
                "image": ("IMAGE",),  # Input image from another node
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "preserve_alpha": ("BOOLEAN", {"default": True}), 
+            }
        }

    RETURN_TYPES = ("IMAGE",)
@@ -23,10 +28,10 @@ class RemoveForegroundNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.internal.prod.bria-api.com/v1/erase_foreground"  # remove foreground API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/erase_foreground"  # remove foreground API URL

    # Define the execute method as expected by ComfyUI
-    def execute(self, image, api_key):
+    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.")

@@ -41,7 +46,12 @@ class RemoveForegroundNode():
        
 #         files=[('file',('temp_img.jpeg', open(temp_img_path, 'rb'),'image/jpeg'))
 #   ]
-        payload = {"file": image_to_base64(image)}
+        payload = {
+            "image": image_to_base64(image),
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "preserve_alpha": preserve_alpha
+        }

        headers = {
            "Content-Type": "application/json",
@@ -50,18 +60,31 @@ class RemoveForegroundNode():

        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
+
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial request successful, polling for completion...')
                response_dict = response.json()
-                image_response = requests.get(response_dict['result_url'])
+                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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                image_response = requests.get(result_image_url)
                result_image = Image.open(io.BytesIO(image_response.content))
                result_image = np.array(result_image).astype(np.float32) / 255.0
                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}")
@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch

-from .common import image_to_base64, preprocess_image, preprocess_mask
+from .common import image_to_base64, preprocess_image, preprocess_mask, poll_status_until_completed


 class ReplaceBgNode():
@@ -16,15 +16,17 @@ class ReplaceBgNode():
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
            },
            "optional": {
-                "fast": ("BOOLEAN", {"default": True}), 
-                "bg_prompt": ("STRING",),
-                "ref_image": ("IMAGE",), # Input ref image from another node
+                "mode": (["base", "fast", "high_control"], {"default": "base"}),
+                "prompt": ("STRING",),
+                "ref_images": ("IMAGE",),
                "refine_prompt": ("BOOLEAN", {"default": True}), 
-                "enhance_ref_image": ("BOOLEAN", {"default": True}), 
+                "enhance_ref_images": ("BOOLEAN", {"default": True}), 
                "original_quality": ("BOOLEAN", {"default": False}), 
-                "force_rmbg": ("BOOLEAN", {"default": False}), 
                "negative_prompt": ("STRING", {"default": None}), 
-                "seed": ("INT", {"default": 681794})
+                "seed": ("INT", {"default": 681794}),
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "prompt_content_moderation": ("BOOLEAN", {"default": False}),
+                "force_background_detection": ("BOOLEAN", {"default": False}),
            }
        }

@@ -34,19 +36,21 @@ class ReplaceBgNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/background/replace"  # Replace BG API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/replace_background"  # Replace BG API URL

    # Define the execute method as expected by ComfyUI
-    def execute(self, image, fast,
+    def execute(self, image, mode,
                refine_prompt,
-                enhance_ref_image,
                original_quality,
-                force_rmbg,
                negative_prompt,
                seed,
                api_key,
-                bg_prompt=None,
-                ref_image=None,):
+                visual_output_content_moderation,
+                prompt_content_moderation,
+                enhance_ref_images,
+                force_background_detection,
+                prompt=None,
+                ref_images=None,):
        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
            raise Exception("Please insert a valid API key.")

@@ -54,27 +58,29 @@ class ReplaceBgNode():
        if isinstance(image, torch.Tensor):
            image = preprocess_image(image)

-        # Convert the image and mask directly to Base64 strings
+        # Convert the image to Base64 string
        image_base64 = image_to_base64(image)
-        ref_image_file = None # initialization, will be updated if it is supplied
-        if ref_image is not None:
-            ref_image = preprocess_image(ref_image)
-            ref_image_file = image_to_base64(ref_image)
+        
+        if ref_images is not None:
+            ref_images = preprocess_image(ref_images)
+            ref_images = [image_to_base64(ref_images)]
+        else:
+            ref_images=[]

-        # Prepare the API request payload
+        # Prepare the API request payload for v2 API
        payload = {
-            "file": f"{image_base64}",
-            "fast": fast,
-            "bg_prompt": bg_prompt,
-            "ref_image_file": ref_image_file,
+            "image": image_base64,
+            "mode": mode,
+            "prompt": prompt,
+            "ref_images":ref_images,
            "refine_prompt": refine_prompt,
-            "enhance_ref_image": enhance_ref_image,
            "original_quality": original_quality,
-            "force_rmbg": force_rmbg,
            "negative_prompt": negative_prompt,
            "seed": seed,
-            "sync": True,
-            "num_results": 1
+            "prompt_content_moderation": prompt_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "enhance_ref_images":enhance_ref_images,
+            "force_background_detection": force_background_detection        
        }   

        headers = {
@@ -84,19 +90,34 @@ class ReplaceBgNode():

        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
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial replace background request successful, polling for completion...')
                response_dict = response.json()
-                image_response = requests.get(response_dict['result'][0][0]) # first indexing for batched, second for url
+                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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
                result_image = Image.open(io.BytesIO(image_response.content))
                result_image = result_image.convert("RGB")
                result_image = np.array(result_image).astype(np.float32) / 255.0
                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}")
@@ -4,8 +4,7 @@ from PIL import Image
 import io
 import torch

-from .common import preprocess_image
-
+from .common import preprocess_image, image_to_base64, poll_status_until_completed

 class RmbgNode():
    @classmethod
@@ -15,6 +14,12 @@ class RmbgNode():
                "image": ("IMAGE",),  # Input image from another node
                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "preserve_alpha": ("BOOLEAN", {"default": True}), 
+            
+            }               
        }

    RETURN_TYPES = ("IMAGE",)
@@ -23,10 +28,10 @@ class RmbgNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/background/remove"  # RMBG API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/remove_background"  # RMBG API URL

    # Define the execute method as expected by ComfyUI
-    def execute(self, image, api_key):
+    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.")

@@ -34,27 +39,49 @@ class RmbgNode():
        if isinstance(image, torch.Tensor):
            image = preprocess_image(image)

-        # Prepare the API request payload
-        # temporary save the image to /tmp
-        temp_img_path = "/tmp/temp_img.jpeg"
-        image.save(temp_img_path, format="JPEG")
-        files=[('file',('temp_img.jpeg', open(temp_img_path, 'rb'),'image/jpeg'))
-  ]
+        # Convert image to base64 for the new API format
+        image_base64 = image_to_base64(image)
+        payload = {
+            "image": image_base64,
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "preserve_alpha":preserve_alpha
+        }
+
+        headers = {
+            "Content-Type": "application/json",
+            "api_token": f"{api_key}"
+        }

        try:
-            response = requests.post(self.api_url, data={}, headers={"api_token": api_key}, files=files)
-            # Check for successful response
-            if response.status_code == 200:
-                print('response is 200')
-                # Process the output image from API response
+            response = requests.post(self.api_url, json=payload, headers=headers)
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial RMBG request successful, polling for completion...')
                response_dict = response.json()
-                image_response = requests.get(response_dict['result_url'])
+
+                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)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
                result_image = Image.open(io.BytesIO(image_response.content))
                result_image = np.array(result_image).astype(np.float32) / 255.0
                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}")
@@ -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)
@@ -1,68 +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
-            }
-        }
-
-    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, ):
-        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
-        }
-        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)
@@ -1,64 +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",),
-                "optimize_description": ("INT", {"default": 1}),
-                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"})  # API Key input with a default value
-            }
-        }
-
-    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, optimize_description, ):
-        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)
-
-        optimize_description = bool(optimize_description)
-        image_base64 = image_to_base64(image)
-        payload = {
-            "file": image_base64,
-            "scene_description": scene_description,
-            "optimize_description": optimize_description,
-            "placement_type": "original",
-            "original_quality": True,
-            "sync": True
-        }
-        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)
@@ -26,6 +26,7 @@ class TailoredGenNode():
                "guidance_method_2": (["controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid"], {"default": "controlnet_canny"}),
                "guidance_method_2_scale": ("FLOAT", {"default": 1.0}),
                "guidance_method_2_image": ("IMAGE", ),
+                "content_moderation": ("INT", {"default": 0}),
            }
        }

@@ -42,8 +43,8 @@ class TailoredGenNode():
            seed, model_influence, negative_prompt, fast, steps_num,
            guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
            guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
+            content_moderation=0,
        ):
-        fast = bool(fast)
        payload = {
            "prompt": generation_prefix + prompt,
            "num_results": 1,
@@ -55,6 +56,7 @@ class TailoredGenNode():
            "fast": fast,
            "steps_num": steps_num,
            "include_generation_prefix": False,
+            "content_moderation": content_moderation,
        }
        if guidance_method_1_image is not None:
            guidance_method_1_image = preprocess_image(guidance_method_1_image)
@@ -0,0 +1,75 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import image_to_base64, preprocess_image
+
+class TailoredPortraitNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "tailored_model_id": ("INT",),
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            "optional": {
+                "seed": ("INT", {"default": 123456}),
+                "tailored_model_influence": ("FLOAT", {"default": 0.9}),
+                "id_strength": ("FLOAT", {"default": 0.7}),
+            }
+        }
+
+    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/tailored-gen/restyle_portrait"  # Eraser API URL
+
+    # Define the execute method as expected by ComfyUI
+    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.")
+
+        # Convert the image and mask directly to  if isinstance(image, torch.Tensor):
+        if isinstance(image, torch.Tensor):
+            image = preprocess_image(image)
+            
+        image_base64 = image_to_base64(image)
+
+        # Prepare the API request payload
+        payload = {
+            "id_image_file": f"{image_base64}",
+            "tailored_model_id": tailored_model_id,
+            "tailored_model_influence": tailored_model_influence,
+            "id_strength": id_strength,
+            "seed": seed
+        }
+
+        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['image_res'])
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = result_image.convert("RGB")
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                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}")
+
+        except Exception as e:
+            raise Exception(f"{e}")
@@ -28,6 +28,7 @@ class Text2ImageBaseNode():
                "image_prompt_mode": (["regular", "style_only"], {"default": "regular"}),
                "image_prompt_image": ("IMAGE", ),
                "image_prompt_scale": ("FLOAT", {"default": 1.0}),
+                "content_moderation": ("INT", {"default": 0}),
            }
        }

@@ -37,7 +38,7 @@ class Text2ImageBaseNode():
    FUNCTION = "execute"  # This is the method that will be executed

    def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/base/2.3" #"http://0.0.0.0:5000/v1/text-to-image/base/2.3"
+        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/base/3.2" 

    def execute(
            self, api_key, prompt, aspect_ratio, seed, negative_prompt, 
@@ -45,8 +46,8 @@ class Text2ImageBaseNode():
            guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
            guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
            image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
+            content_moderation=0,
        ):
-        prompt_enhancement = bool(prompt_enhancement)
        payload = {
            "prompt": prompt,
            "num_results": 1,
@@ -57,6 +58,7 @@ class Text2ImageBaseNode():
            "steps_num": steps_num,
            "text_guidance_scale": text_guidance_scale,
            "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
        }
        if medium != "none":
            payload["medium"] = medium
@@ -25,6 +25,7 @@ class Text2ImageFastNode():
                "image_prompt_mode": (["regular", "style_only"], {"default": "regular"}),
                "image_prompt_image": ("IMAGE", ),
                "image_prompt_scale": ("FLOAT", {"default": 1.0}),
+                "content_moderation": ("INT", {"default": 0}),
            }
        }

@@ -42,8 +43,8 @@ class Text2ImageFastNode():
            guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
            guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
            image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
+            content_moderation=0,
        ):
-        prompt_enhancement = bool(prompt_enhancement)
        payload = {
            "prompt": prompt,
            "num_results": 1,
@@ -52,6 +53,7 @@ class Text2ImageFastNode():
            "seed": seed,
            "steps_num": steps_num,
            "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
        }
        if guidance_method_1_image is not None:
            guidance_method_1_image = preprocess_image(guidance_method_1_image)
@@ -19,6 +19,7 @@ class Text2ImageHDNode():
                "prompt_enhancement": ("INT", {"default": 0}),
                "text_guidance_scale": ("INT", {"default": 5}),
                "medium": (["photography", "art", "none"], {"default": "none"}),
+                "content_moderation": ("INT", {"default": 0}),
            }
        }

@@ -32,9 +33,8 @@ class Text2ImageHDNode():

    def execute(
            self, api_key, prompt, aspect_ratio, seed, negative_prompt, 
-            steps_num, prompt_enhancement, text_guidance_scale, medium,
+            steps_num, prompt_enhancement, text_guidance_scale, medium, content_moderation=0,
        ):
-        prompt_enhancement = bool(prompt_enhancement)
        payload = {
            "prompt": prompt,
            "num_results": 1,
@@ -45,6 +45,7 @@ class Text2ImageHDNode():
            "steps_num": steps_num,
            "text_guidance_scale": text_guidance_scale,
            "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
        }
        if medium != "none":
            payload["medium"] = medium
@@ -0,0 +1,204 @@
+import requests
+import torch
+from ..common import 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"""
+    headers = {"Content-Type": "application/json", "api_token": f"{api_key}"}
+
+    try:
+        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 = "2.0.1"
+version = "2.1.3"
 license = {file = "LICENSE"}

 [project.urls]
@@ -0,0 +1 @@
+{"last_node_id":39,"last_link_id":65,"nodes":[{"id":34,"type":"LoadImage","pos":[19.94045066833496,1075.806640625],"size":[315,314],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[61],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":null,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["quirky-red-brick-brick-wallpaper.jpg","image"]},{"id":36,"type":"PreviewImage","pos":[468.7108154296875,1210.288818359375],"size":[210,246],"flags":{},"order":5,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":63,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":33,"type":"PreviewImage","pos":[1317.4083251953125,1118.4864501953125],"size":[210,246],"flags":{},"order":8,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":59,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":31,"type":"PreviewImage","pos":[1668.734619140625,796.7755737304688],"size":[210,246],"flags":{},"order":10,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":57,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":29,"type":"PreviewImage","pos":[872.8858032226562,679.9429321289062],"size":[210,246],"flags":{},"order":6,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":55,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":28,"type":"LoadImage","pos":[29.629886627197266,676.8370361328125],"size":[315,314],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[54],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":null,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["pexels-photo-1808399.jpeg","image"]},{"id":35,"type":"RemoveForegroundNode","pos":[414.2638854980469,1079.1705322265625],"size":[315,58],"flags":{},"order":3,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":61,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[62,63],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"RemoveForegroundNode"},"widgets_values":["BRIA_API_TOKEN"]},{"id":32,"type":"ReplaceBgNode","pos":[834.6115112304688,1063.0406494140625],"size":[315,294],"flags":{},"order":7,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":65,"localized_name":"image"},{"name":"ref_image","type":"IMAGE","link":62,"shape":7,"localized_name":"ref_image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[59,64],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"ReplaceBgNode"},"widgets_values":["BRIA_API_TOKEN",false,"",true,true,true,false,"",1978,"randomize"]},{"id":30,"type":"ImageExpansionNode","pos":[1265.001220703125,798.8323974609375],"size":[315,226],"flags":{},"order":9,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":64,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[57],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"ImageExpansionNode"},"widgets_values":["600,760","200, 0","BRIA_API_TOKEN","1200, 800","",1729,"randomize","Ugly, mutated"]},{"id":38,"type":"Note","pos":[436.7110900878906,566.2047119140625],"size":[306.28387451171875,58],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["You can get your BRIA API token at:\nhttps://bria.ai/api/"],"color":"#432","bgcolor":"#653"},{"id":27,"type":"RmbgNode","pos":[430.8815002441406,678.7727661132812],"size":[315,58],"flags":{},"order":4,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":54,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[55,65],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"RmbgNode"},"widgets_values":["BRIA_API_TOKEN"]}],"links":[[51,5,0,15,2,"STRING"],[54,28,0,27,0,"IMAGE"],[55,27,0,29,0,"IMAGE"],[57,30,0,31,0,"IMAGE"],[59,32,0,33,0,"IMAGE"],[61,34,0,35,0,"IMAGE"],[62,35,0,32,1,"IMAGE"],[63,35,0,36,0,"IMAGE"],[64,32,0,30,0,"IMAGE"],[65,27,0,32,0,"IMAGE"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8140274938684037,"offset":[101.53311990208498,-477.0342684311694]},"node_versions":{"comfyui-bria-api":"c72754d15b53a13ee0c0419d70401232c56b7fdb","comfy-core":"v0.3.8-1-gc441048","ComfyUI-Jjk-Nodes":"b3c99bb78a99551776b5eab1a820e1cd58f84f31"}},"version":0.4}
@@ -0,0 +1 @@
+{"last_node_id":41,"last_link_id":62,"nodes":[{"id":14,"type":"Note","pos":[478,444],"size":[396.80859375,61.8046875],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Right click, and choose \"Open in Mask Editor\" to draw a mask of areas you want to erase."],"color":"#432","bgcolor":"#653"},{"id":15,"type":"Note","pos":[1080.3062744140625,445.9654541015625],"size":[306.28387451171875,58],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["You can get your BRIA API token at:\nhttps://bria.ai/api/"],"color":"#432","bgcolor":"#653"},{"id":30,"type":"LoadImage","pos":[479,572],"size":[395.7845153808594,352.8512268066406],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[56],"slot_index":0,"shape":3,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":[57],"slot_index":1,"shape":3,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["clipspace/clipspace-mask-4068974.800000012.png [input]","image"]},{"id":37,"type":"PreviewImage","pos":[1504.4755859375,568.9967651367188],"size":[438.50262451171875,376.8338317871094],"flags":{},"order":6,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":58,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":33,"type":"PreviewImage","pos":[1502.785888671875,1078.3564453125],"size":[433.29193115234375,357.1255187988281],"flags":{},"order":7,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":54,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":40,"type":"LoadImage","pos":[541.1226806640625,1079.39697265625],"size":[315,314],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[61],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":[62],"slot_index":1,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["clipspace/clipspace-mask-4411367.100000024.png [input]","image"]},{"id":34,"type":"BriaGenFill","pos":[1032.416748046875,1073.984619140625],"size":[315,102],"flags":{},"order":5,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":61,"localized_name":"image"},{"name":"mask","type":"MASK","link":62,"localized_name":"mask"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[54],"slot_index":0,"shape":3,"localized_name":"output_image"}],"properties":{"Node name for S&R":"BriaGenFill"},"widgets_values":["a blue coffee mug","BRIA_API_TOKEN"]},{"id":36,"type":"BriaEraser","pos":[1068.6063232421875,574.6080322265625],"size":[315,78],"flags":{},"order":4,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":56,"localized_name":"image"},{"name":"mask","type":"MASK","link":57,"localized_name":"mask"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[58],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"BriaEraser"},"widgets_values":["BRIA_API_TOKEN"]}],"links":[[54,34,0,33,0,"IMAGE"],[56,30,0,36,0,"IMAGE"],[57,30,1,36,1,"MASK"],[58,36,0,37,0,"IMAGE"],[61,40,0,34,0,"IMAGE"],[62,40,1,34,1,"MASK"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.6727499949325677,"offset":[131.53042816003972,-419.53430403204317]}},"version":0.4}
@@ -1,203 +0,0 @@
-{
-  "last_node_id": 28,
-  "last_link_id": 42,
-  "nodes": [
-    {
-      "id": 15,
-      "type": "Note",
-      "pos": {
-        "0": 1021,
-        "1": 280
-      },
-      "size": {
-        "0": 311.8914794921875,
-        "1": 153.69827270507812
-      },
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
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 {
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+  "id": "1cdd7d4c-58b5-4047-947b-1977ad36d364",
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      },
      "widgets_values": [
-        "A_bottle_of_perfume.png",
+        "CAR.png",
        "image"
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@@ -61,9 +89,8 @@
          "name": "IMAGE",
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@@ -75,21 +102,21 @@
        "Node name for S&R": "LoadImage"
      },
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-        "A_red_studio_with_a_shelf__close_up.png",
+        "seed_713360865.png",
        "image"
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@@ -103,40 +130,14 @@
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@@ -146,25 +147,26 @@
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@@ -172,7 +174,7 @@
        {
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          "name": "output_image",
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@@ -212,12 +217,12 @@
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@@ -225,58 +230,60 @@
          "name": "output_image",
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-      "ComfyUI-BRIA-API": ""
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-  "version": 0.4
-}
@@ -1,203 +0,0 @@
-{
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-        "image"
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-      "flags": {},
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-      "inputs": [],
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-      "properties": {},
-      "widgets_values": [
-        "Right click, and choose \"Open in Mask Editor\" to draw a mask of areas you want to erase."
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-      "color": "#432",
-      "bgcolor": "#653"
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-      "mode": 0,
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-      "properties": {},
-      "widgets_values": [
-        "You can get your BRIA API token at:\nhttps://bria.ai/api/"
-      ],
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@@ -1,119 +1,103 @@
 {
-  "last_node_id": 36,
-  "last_link_id": 58,
+  "last_node_id": 13,
+  "last_link_id": 11,
  "nodes": [
    {
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+      "type": "LoadImage",
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+        669.7035522460938,
+        136.97129821777344
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-      "properties": {},
-      "widgets_values": [
-        "You can get your BRIA API token at:\nhttps://bria.ai/api/"
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        {
          "name": "IMAGE",
          "type": "IMAGE",
          "links": [
-            57
+            10
          ],
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+          "slot_index": 0
        },
        {
          "name": "MASK",
          "type": "MASK",
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-          ],
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        }
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        "Node name for S&R": "LoadImage"
      },
      "widgets_values": [
-        "9f80551c-dd4f-11ef-a692-e2f8583797ff (1).png",
+        "pexels-photo-3246665.png",
        "image"
      ]
    },
    {
-      "id": 36,
-      "type": "RmbgNode",
+      "id": 11,
+      "type": "PreviewImage",
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+        1587.27001953125,
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      "mode": 0,
      "inputs": [
        {
-          "name": "image",
+          "name": "images",
          "type": "IMAGE",
-          "link": 57
+          "link": 11
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
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+      "type": "Text2ImageFastNode",
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+        96.64427185058594
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+        394.27716064453125
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+          "type": "IMAGE",
+          "link": null,
+          "shape": 7
+        },
+        {
+          "name": "guidance_method_2_image",
+          "type": "IMAGE",
+          "link": null,
+          "shape": 7
+        },
+        {
+          "name": "image_prompt_image",
+          "type": "IMAGE",
+          "link": 10,
+          "shape": 7
        }
      ],
      "outputs": [
@@ -121,41 +105,45 @@
          "name": "output_image",
          "type": "IMAGE",
          "links": [
-            58
+            11
          ],
          "slot_index": 0
        }
      ],
      "properties": {
-        "Node name for S&R": "RmbgNode"
+        "Node name for S&R": "Text2ImageFastNode"
      },
      "widgets_values": [
-        "BRIA_API_TOKEN"
+        "BRIA_API_TOKEN",
+        "A drawing of a lion on a table.\t",
+        "4:3",
+        990,
+        "randomize",
+        8,
+        0,
+        "controlnet_canny",
+        1,
+        "controlnet_canny",
+        1,
+        "regular",
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      ]
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    [
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    [
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@@ -164,16 +152,18 @@
  "config": {},
  "extra": {
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+        11.112206386364164,
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-    }
+      "comfy-core": "v0.3.10-42-gff83865",
+      "comfyui-bria-api": "499ec5d104cc5110407eafce468ce1d47ac168b3"
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+    "VHS_latentpreviewrate": 0
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 }
Author	SHA1	Message	Date
Yazan Numoor	ddbf7d0695	Update pyproject.toml	2025-10-22 20:38:36 +03:00
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	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
Ubuntu	9b3f15b7bd	WAI-3976-feedback-fixes	2025-09-18 12:03:07 +00:00
Yazan Numoor	f7c9ed12b0	Merge pull request #23 from Bria-AI/WAI-3976 WAI-3976	2025-09-17 17:55:23 +03:00
Yazan Numoor	bdd053a81b	update version	2025-09-17 17:55:05 +03:00
Ubuntu	2913a9eb6b	update polling status url	2025-09-17 12:54:10 +00:00
Ubuntu	080c17f4a4	WAI-3976	2025-09-16 17:11:06 +00:00
Yazan Numoor	711080ffb0	Update pyproject.toml	2025-09-10 15:06:35 +03:00
Yazan Numoor	69f111bfe9	Merge pull request #22 from Bria-AI/WAI-3922 WAI-3922	2025-09-10 15:04:09 +03:00
Ubuntu	011f728b0d	WAI-3922	2025-09-10 09:23:52 +00:00
gabiburtman	ac9678cd23	Update pyproject.toml fixed issue in shot_by_text_node	2025-09-09 20:10:44 +03:00
gabiburtman	daede982ac	Delete nodes/shot_by_text_auto_placement_node.py	2025-09-09 20:10:11 +03:00
gabiburtman	e716e585df	Create shot_by_text_auto_placement_node.py	2025-09-09 20:07:26 +03:00
gabiburtman	1296b6a27c	Update shot_by_text_node.py	2025-09-09 20:04:48 +03:00
gabiburtman	19f15f4ba4	Update shot_by_text_node.py	2025-09-09 19:54:21 +03:00
gabiburtman	30d0154caf	Update pyproject.toml	2025-09-09 13:00:51 +03:00
gabiburtman	283665f654	Update shot_by_text_node.py	2025-09-09 13:00:30 +03:00
gabiburtman	03e3bec952	Update pyproject.toml	2025-09-09 12:39:08 +03:00
gabiburtman	f1793ba9ad	Merge pull request #21 from ComfyNodePRs/update-publish-yaml Update Github Action for Publishing to Comfy Registry	2025-09-09 12:22:17 +03:00
gabiburtman	eda093ea66	Update shot_by_text_node.py	2025-09-09 11:13:41 +03:00
gabiburtman	165a103f0c	Update replace_bg_node.py	2025-09-09 11:11:35 +03:00
gabiburtman	ad2f4a5853	Update text_2_image_base_node.py	2025-06-16 16:24:17 +03:00
gabiburtman	43f858dca4	Update text_2_image_base_node.py	2025-06-12 16:06:17 +03:00
gabiburtman	538cd53ac8	Update text_2_image_base_node.py	2025-06-12 15:31:08 +03:00
BriaOr	bae0ed3842	Added restyle portrait to readme	2025-03-17 14:43:25 +02:00
BriaOr	a164f8ec45	Update Readme.md	2025-03-13 14:03:38 +02:00
BriaOr	ebe9e2e6b1	Update Readme.md	2025-03-13 14:03:18 +02:00
BriaOr	429c51ac6d	Update pyproject.toml	2025-03-11 14:50:01 +02:00
BriaOr	aed4832984	Update __init__.py	2025-03-11 14:29:10 +02:00
BriaOr	a78aff0fb2	Update pyproject.toml	2025-03-11 14:02:49 +02:00
xenia-kra	6edfc55109	Comfy tailored portrait (#20 )	2025-03-10 17:32:37 +04:00
MishaFein	00dccbb17a	Update Readme.md	2025-02-10 18:11:40 +02:00
MishaFein	1cb9ce4394	Update Readme.md	2025-02-10 18:10:57 +02:00
MishaFein	b2f8b8d0e3	Update Readme.md	2025-02-10 18:05:56 +02:00
MishaFein	129bc599d0	Update Readme.md	2025-02-10 18:04:28 +02:00
MishaFein	28c2631581	Update Readme.md	2025-02-10 17:57:11 +02:00
ori-liberman	baadbc02bc	Add content moderation option to background removal and image generation nodes	2025-02-10 12:49:02 +00:00
or	a73045f8e6	Added workflow sample to readme	2025-02-09 14:21:38 +02:00
tairBria	dd74d03fd0	Merge pull request #17 from Bria-AI/t2i-tailored-content-moderation content moderation t2i reimagime tailored	2025-02-09 13:12:30 +02:00
or	bfc83da41f	added text-to-image workflow and updated version	2025-02-04 17:40:08 +02:00
BriaOr	499ec5d104	Update Readme.md	2025-02-04 13:44:48 +02:00
BriaOr	fef2e49902	Update Readme.md with new API URL	2025-02-04 13:39:36 +02:00
BriaOr	2eae6dae46	Merge pull request #16 from Bria-AI/feature/content-moderation-expansion-removefg image expansion & remove fg- content moderation	2025-02-03 16:10:11 +02:00
israelweiss90	28c0cdf8d5	image expansion & remove fg- content moderation	2025-02-02 16:14:02 +00:00
Tair	54f380f1f0	content moderation t2i reimagime tailored	2025-02-02 14:52:18 +00:00
BriaOr	4f7691ff93	Merge pull request #14 from Bria-AI/bugfi/rmbg-temp-file temp file to buffer to avoid OS dependency	2025-02-02 14:08:39 +02:00
israelweiss90	1781beff09	temp file to buffer to avoid OS dependency	2025-02-02 10:56:04 +00:00
BriaOr	502206f518	Merge pull request #13 from Bria-AI/DvirYBria-gen-fill-seed Added seed go gen fill	2025-02-02 11:45:15 +02:00
DvirYBria	da8adda281	Added seed go gen fill	2025-02-02 11:35:57 +02:00
BriaOr	1c02dea96b	Update Readme.md	2025-01-30 17:08:42 +02:00
or	5b77fd90a8	updated genfill workflow	2025-01-30 16:52:21 +02:00
BriaOr	246e05ac3e	Update Readme.md	2025-01-30 15:29:41 +02:00
or	b6f2f8b297	Updated background workflow	2025-01-30 15:24:53 +02:00
BriaOr	5052a7bf94	Update Readme.md	2025-01-30 15:13:40 +02:00
BriaOr	afc9599c63	Update Readme.md	2025-01-30 15:03:42 +02:00
BriaOr	13a3dfb2bb	Update Readme.md	2025-01-30 15:02:07 +02:00
BriaOr	6573f2e43d	Rename Product shot generation_workflow.json to product shot generation_workflow.json	2025-01-30 14:52:06 +02:00
or	ac7e97c348	Updated workflows	2025-01-30 14:51:39 +02:00
BriaOr	c6fe701115	Merge pull request #10 from Bria-AI/feature/new-comfyui-nodes 4 new nodes- rmbg, replace bg, expand, remove fg	2025-01-30 14:21:15 +02:00
BriaOr	3b5cca2dc8	Update Readme.md	2025-01-29 16:07:42 +02:00
BriaOr	aaf0729f78	Update Readme.md	2025-01-28 17:57:17 +02:00
BriaOr	1a37414fe4	Update Readme.md	2025-01-28 17:51:10 +02:00
BriaOr	2fbbce0d1b	Update Readme.md	2025-01-28 17:47:33 +02:00
BriaOr	23f9e46eff	Update Readme.md	2025-01-28 17:39:26 +02:00
snomiao	a4855c1a1a	chore(publish): update workflow for node publishing - Added permissions for issue writing in the workflow. - Modified condition to check repository owner instead of fork status. - Updated action version from `main` to `v1` for `publish-node-action`.	2025-01-25 07:47:26 +00:00
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