Remove .idea files and update .gitignore

- Removed .idea/ directory from git tracking
- Added .idea/ to .gitignore to prevent future IDE files
- Clean up IDE-specific files that shouldn't be in version control

.gitignore

@@ -157,4 +157,4 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+.idea/

brain_api_client.py

@@ -0,0 +1,372 @@
+"""
+Brain API Client for ComfyUI Nodes
+
+This client provides methods to interact with the Brain API storage endpoints,
+replacing the need for pre-signed URLs in the ComfyUI workflow.
+"""
+
+import requests
+import os
+import logging
+from typing import Optional, Dict, Any
+from dotenv import load_dotenv
+
+# Load environment variables
+current_dir = os.path.dirname(os.path.abspath(__file__))
+dotenv_path = os.path.join(current_dir, ".env")
+load_dotenv(dotenv_path=dotenv_path)
+
+# Setup logging
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
+
+
+class BrainApiClient:
+    """
+    Client for interacting with Brain API storage endpoints.
+    
+    This client handles authentication and provides methods for uploading,
+    downloading, and deleting files through the Brain API storage endpoints.
+    """
+    
+    def __init__(self):
+        """Initialize the Brain API client with configuration from environment variables."""
+        self.base_url = os.getenv("BRANDO_BRAIN_API_BASE_URL", "http://localhost:2024/api")
+        self.api_key = os.getenv("BRANDO_API_KEY")
+        
+        if not self.api_key:
+            raise ValueError(
+                "BRANDO_API_KEY environment variable is required for Brain API authentication"
+            )
+        
+        self.headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "User-Agent": "ComfyUI-NilorNodes/1.0"
+        }
+        
+        logging.info(f"Brain API Client initialized with base URL: {self.base_url}")
+    
+    def upload_file_to_storage(self, file_path: str, filename: str) -> Dict[str, Any]:
+        """
+        Upload a file to Brain API storage and return storage metadata.
+        
+        Args:
+            file_path: Local path to the file to upload
+            filename: Name to use for the uploaded file
+            
+        Returns:
+            Dict containing storage_id and filename
+            
+        Raises:
+            requests.RequestException: If upload fails
+            FileNotFoundError: If file_path doesn't exist
+        """
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File not found: {file_path}")
+        
+        url = f"{self.base_url}/storage/upload"
+        
+        try:
+            with open(file_path, 'rb') as file:
+                files = {'file': (filename, file, 'application/octet-stream')}
+                
+                logging.info(f"Uploading file '{filename}' to Brain API storage...")
+                response = requests.post(
+                    url, 
+                    files=files, 
+                    headers=self.headers, 
+                    timeout=300
+                )
+                response.raise_for_status()
+                
+                result = response.json()
+                logging.info(f"Upload successful. Storage ID: {result.get('storage_id')}")
+                return result
+                
+        except requests.RequestException as e:
+            logging.error(f"Failed to upload file '{filename}': {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error uploading file '{filename}': {e}")
+            raise
+    
+    def upload_fileobj_to_storage(self, file_obj, filename: str, content_type: str = 'application/octet-stream') -> Dict[str, Any]:
+        """
+        Upload a file-like object to Brain API storage and return storage metadata.
+        
+        Args:
+            file_obj: File-like object to upload
+            filename: Name to use for the uploaded file
+            content_type: MIME type of the file
+            
+        Returns:
+            Dict containing storage_id and filename
+            
+        Raises:
+            requests.RequestException: If upload fails
+        """
+        url = f"{self.base_url}/storage/upload"
+        
+        try:
+            files = {'file': (filename, file_obj, content_type)}
+            
+            logging.info(f"Uploading file object '{filename}' to Brain API storage...")
+            response = requests.post(
+                url, 
+                files=files, 
+                headers=self.headers, 
+                timeout=300
+            )
+            response.raise_for_status()
+            
+            result = response.json()
+            logging.info(f"Upload successful. Storage ID: {result.get('storage_id')}")
+            return result
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to upload file object '{filename}': {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error uploading file object '{filename}': {e}")
+            raise
+    
+    def download_file_from_storage(self, storage_id: str, filename: str, dest_path: str) -> str:
+        """
+        Download a file from Brain API storage to a local path.
+        
+        Args:
+            storage_id: Storage ID of the file to download
+            filename: Name of the file to download
+            dest_path: Local path where the file should be saved
+            
+        Returns:
+            Path to the downloaded file
+            
+        Raises:
+            requests.RequestException: If download fails
+        """
+        url = f"{self.base_url}/storage/{storage_id}"
+        params = {'filename': filename}
+        
+        try:
+            logging.info(f"Downloading file '{filename}' (storage_id: {storage_id}) from Brain API storage...")
+            response = requests.get(
+                url, 
+                params=params, 
+                headers=self.headers, 
+                timeout=300,
+                stream=True
+            )
+            response.raise_for_status()
+            
+            # Ensure destination directory exists
+            os.makedirs(os.path.dirname(dest_path), exist_ok=True)
+            
+            with open(dest_path, 'wb') as f:
+                for chunk in response.iter_content(chunk_size=8192):
+                    f.write(chunk)
+            
+            logging.info(f"Download successful. File saved to: {dest_path}")
+            return dest_path
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to download file '{filename}' (storage_id: {storage_id}): {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error downloading file '{filename}': {e}")
+            raise
+    
+    def get_file_from_storage(self, storage_id: str, filename: str) -> bytes:
+        """
+        Get file content from Brain API storage as bytes.
+        
+        Args:
+            storage_id: Storage ID of the file to download
+            filename: Name of the file to download
+            
+        Returns:
+            File content as bytes
+            
+        Raises:
+            requests.RequestException: If download fails
+        """
+        url = f"{self.base_url}/storage/{storage_id}"
+        params = {'filename': filename}
+        
+        try:
+            logging.info(f"Getting file '{filename}' (storage_id: {storage_id}) from Brain API storage...")
+            response = requests.get(
+                url, 
+                params=params, 
+                headers=self.headers, 
+                timeout=300
+            )
+            response.raise_for_status()
+            
+            logging.info(f"File retrieval successful. Size: {len(response.content)} bytes")
+            return response.content
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to get file '{filename}' (storage_id: {storage_id}): {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error getting file '{filename}': {e}")
+            raise
+    
+    def delete_file_from_storage(self, storage_id: str, filename: str) -> None:
+        """
+        Delete a file from Brain API storage.
+        
+        Args:
+            storage_id: Storage ID of the file to delete
+            filename: Name of the file to delete
+            
+        Raises:
+            requests.RequestException: If deletion fails
+        """
+        url = f"{self.base_url}/storage/{storage_id}"
+        params = {'filename': filename}
+        
+        try:
+            logging.info(f"Deleting file '{filename}' (storage_id: {storage_id}) from Brain API storage...")
+            response = requests.delete(
+                url, 
+                params=params, 
+                headers=self.headers, 
+                timeout=60
+            )
+            response.raise_for_status()
+            
+            logging.info(f"File deletion successful")
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to delete file '{filename}' (storage_id: {storage_id}): {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error deleting file '{filename}': {e}")
+            raise
+    
+    def get_presigned_upload_url(self, filename: str, content_type: str, minio_endpoint: str) -> Dict[str, Any]:
+        """
+        Get a presigned upload URL from Brain API for direct MinIO upload.
+        
+        Args:
+            filename: Name of the file to upload
+            content_type: MIME type of the file
+            minio_endpoint: MinIO endpoint that ComfyUI can access
+            
+        Returns:
+            Dict containing storage_id, upload_url, and object_key
+            
+        Raises:
+            requests.RequestException: If request fails
+        """
+        url = f"{self.base_url}/storage/generate-upload-url"
+        payload = {
+            "filename": filename,
+            "content_type": content_type,
+            "minio_endpoint": minio_endpoint
+        }
+        
+        try:
+            logging.info(f"Requesting presigned upload URL for '{filename}' from Brain API...")
+            response = requests.post(
+                url,
+                json=payload,
+                headers=self.headers,
+                timeout=30
+            )
+            response.raise_for_status()
+            
+            result = response.json()
+            logging.info(f"Presigned upload URL generated. Storage ID: {result.get('storage_id')}")
+            return result
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to get presigned upload URL for '{filename}': {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error getting presigned upload URL for '{filename}': {e}")
+            raise
+    
+    def get_presigned_download_url(self, storage_id: str, filename: str, minio_endpoint: str) -> Dict[str, Any]:
+        """
+        Get a presigned download URL from Brain API for direct MinIO download.
+        
+        Args:
+            storage_id: Storage ID of the file to download
+            filename: Name of the file to download
+            minio_endpoint: MinIO endpoint that ComfyUI can access
+            
+        Returns:
+            Dict containing download_url
+            
+        Raises:
+            requests.RequestException: If request fails
+        """
+        url = f"{self.base_url}/storage/generate-download-url"
+        payload = {
+            "storage_id": storage_id,
+            "filename": filename,
+            "minio_endpoint": minio_endpoint
+        }
+        
+        try:
+            logging.info(f"Requesting presigned download URL for '{filename}' (storage_id: {storage_id}) from Brain API...")
+            response = requests.post(
+                url,
+                json=payload,
+                headers=self.headers,
+                timeout=30
+            )
+            response.raise_for_status()
+            
+            result = response.json()
+            logging.info(f"Presigned download URL generated for '{filename}'")
+            return result
+            
+        except requests.RequestException as e:
+            logging.error(f"Failed to get presigned download URL for '{filename}' (storage_id: {storage_id}): {e}")
+            raise
+        except Exception as e:
+            logging.error(f"Unexpected error getting presigned download URL for '{filename}': {e}")
+            raise
+
+    def health_check(self) -> bool:
+        """
+        Check if the Brain API is accessible and authentication is working.
+        
+        Returns:
+            True if API is accessible, False otherwise
+        """
+        try:
+            # Try to access a simple endpoint to verify connectivity
+            url = f"{self.base_url}/health"  # Assuming there's a health endpoint
+            response = requests.get(url, headers=self.headers, timeout=10)
+            return response.status_code == 200
+        except:
+            # If health endpoint doesn't exist, try the storage upload endpoint
+            # with a HEAD request to check authentication
+            try:
+                url = f"{self.base_url}/storage/upload"
+                response = requests.head(url, headers=self.headers, timeout=10)
+                return response.status_code in [200, 405]  # 405 Method Not Allowed is OK for HEAD
+            except:
+                return False
+
+
+# Global client instance
+_brain_api_client = None
+
+def get_brain_api_client() -> BrainApiClient:
+    """
+    Get or create the global Brain API client instance.
+    
+    Returns:
+        BrainApiClient instance
+    """
+    global _brain_api_client
+    if _brain_api_client is None:
+        _brain_api_client = BrainApiClient()
+    return _brain_api_client

media_stream.py

@@ -10,6 +10,7 @@ import boto3
 import os
 import json
 from dotenv import load_dotenv
+from .brain_api_client import get_brain_api_client
 
 # --- Load Environment Variables ---
 # Get the directory of the current script
@@ -49,9 +50,13 @@ class MediaStreamInput:
                     {"default": "default_input", "multiline": False},
                 ),
                 "format": (["image", "image_batch", "video"],),
-                "presigned_download_url": (
+                "storage_id": (
                     "STRING",
-                    {"multiline": True, "default": "<auto-filled by system>"},
+                    {"default": "<auto-filled by system>", "multiline": False},
+                ),
+                "filename": (
+                    "STRING",
+                    {"default": "<auto-filled by system>", "multiline": False},
                 ),
             },
             "hidden": {},
@@ -64,19 +69,31 @@ class MediaStreamInput:
 
     def download(
         self,
-        presigned_download_url: str,
+        storage_id: str,
+        filename: str,
         format: str,
         input_name: str = "default_input",
     ):
         logging.info(
-            f"ℹ️\u2009 Nilor-Nodes: MediaStreamInput: Downloading from {presigned_download_url} for input '{input_name}' with format '{format}'"
+            f"ℹ️\u2009 Nilor-Nodes: MediaStreamInput: Downloading file '{filename}' (storage_id: {storage_id}) for input '{input_name}' with format '{format}'"
         )
         try:
+            # Get Brain API client and MinIO endpoint
+            brain_client = get_brain_api_client()
+            minio_endpoint = os.getenv("MINIO_ENDPOINT")
+            if not minio_endpoint:
+                raise ValueError("MINIO_ENDPOINT environment variable is required but not set")
+            
             # Two-phase download for batches: manifest first, then assets
             if format == "image_batch":
-                manifest_response = requests.get(presigned_download_url, timeout=60)
+                # Get presigned download URL for manifest
+                manifest_url_response = brain_client.get_presigned_download_url(storage_id, filename, minio_endpoint)
+                manifest_url = manifest_url_response["download_url"]
+                
+                # Download manifest file directly from MinIO
+                manifest_response = requests.get(manifest_url, timeout=300)
                 manifest_response.raise_for_status()
-                manifest = manifest_response.json()
+                manifest = json.loads(manifest_response.content.decode('utf-8'))
 
                 logging.info(
                     f"ℹ️\u2009 Nilor-Nodes: Processing manifest for '{manifest.get('input_name')}' with {len(manifest.get('files', []))} assets."
@@ -87,14 +104,24 @@ class MediaStreamInput:
                     manifest.get("files", []), key=lambda x: x.get("sequence", 0)
                 )
 
-                # Download all assets in parallel
+                # Download all assets using presigned URLs
                 asset_responses = []
                 for file_info in sorted_files:
                     try:
-                        resp = requests.get(file_info["presigned_url"], timeout=180)
-                        resp.raise_for_status()
-                        asset_responses.append(resp.content)
-                    except requests.RequestException as e:
+                        file_storage_id = file_info.get("storage_id")
+                        file_filename = file_info.get("filename")
+                        if not file_storage_id or not file_filename:
+                            raise ValueError(f"Missing storage_id or filename in manifest file info: {file_info}")
+                        
+                        # Get presigned download URL for this asset
+                        asset_url_response = brain_client.get_presigned_download_url(file_storage_id, file_filename, minio_endpoint)
+                        asset_url = asset_url_response["download_url"]
+                        
+                        # Download asset directly from MinIO
+                        asset_response = requests.get(asset_url, timeout=300)
+                        asset_response.raise_for_status()
+                        asset_responses.append(asset_response.content)
+                    except Exception as e:
                         logging.error(
                             f"🛑\u2009 Nilor-Nodes: Failed to download asset {file_info.get('filename')}: {e}"
                         )
@@ -103,9 +130,14 @@ class MediaStreamInput:
                 return self._process_image_batch(asset_responses)
 
             # --- Single-file download ---
-            response = requests.get(presigned_download_url, timeout=180)
-            response.raise_for_status()
-            media_bytes = response.content
+            # Get presigned download URL
+            download_url_response = brain_client.get_presigned_download_url(storage_id, filename, minio_endpoint)
+            download_url = download_url_response["download_url"]
+            
+            # Download file directly from MinIO
+            media_response = requests.get(download_url, timeout=300)
+            media_response.raise_for_status()
+            media_bytes = media_response.content
 
             if format == "video":
                 return self._process_video(media_bytes)
@@ -117,14 +149,9 @@ class MediaStreamInput:
                     f"[🛑] Nilor-Nodes (MediaStreamInput): Unsupported format '{format}' for single media download."
                 )
 
-        except requests.RequestException as e:
-            logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamInput): Failed to download file: {e}"
-            )
-            return (None,)
         except Exception as e:
             logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamInput): Failed to process media: {e}"
+                f"🛑\u2009 Nilor-Nodes (MediaStreamInput): Failed to download or process media: {e}"
             )
             return (None,)
 
@@ -219,18 +246,10 @@ class MediaStreamOutput:
                     "STRING",
                     {"default": "<auto-filled by system>", "multiline": False},
                 ),
-                "presigned_upload_url": (
-                    "STRING",
-                    {"multiline": True, "default": "<auto-filled by system>"},
-                ),
                 "job_completions_queue_url": (
                     "STRING",
                     {"multiline": True, "default": "<auto-filled by system>"},
                 ),
-                "output_object_keys": (
-                    "STRING",
-                    {"multiline": False, "default": "<auto-filled by system>"},
-                ),
             },
             "hidden": {
                 "prompt": "PROMPT",
@@ -238,8 +257,7 @@ class MediaStreamOutput:
             },
         }
 
-    RETURN_TYPES = ("STRING",)
-    RETURN_NAMES = ("uploaded_url",)
+    RETURN_TYPES = ()
     FUNCTION = "upload_and_notify"
     OUTPUT_NODE = True
     CATEGORY = category + subcategories["streaming"]
@@ -252,9 +270,7 @@ class MediaStreamOutput:
         venue,
         canvas,
         scene,
-        presigned_upload_url,
         job_completions_queue_url,
-        output_object_keys,
         framerate,
         output_name: str = "default_output",
         prompt=None,
@@ -265,35 +281,28 @@ class MediaStreamOutput:
                 "[🛑] Nilor-Nodes (MediaStreamOutput): content_id is a required input for MediaStreamOutput."
             )
 
-        # The `output_object_keys` is received as a string representation of a dictionary.
-        # We must parse it back into a dictionary.
-        final_outputs_dict = {}
-        try:
-            # The string may use single quotes, so we replace them for valid JSON.
-            final_outputs_dict = json.loads(output_object_keys.replace("'", '"'))
-        except Exception as e:
-            logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamOutput): FATAL -- Could not parse output_object_keys from string: {output_object_keys}. Error: {e}"
-            )
-            final_outputs_dict = {}  # Send empty dict on failure.
+        # No longer need to parse output_object_keys since we use storage_ids directly
 
-        # The presigned_upload_url provided to this node is specific to its output_name.
-        # We don't need to re-select it. We just need to perform the upload.
+        # Upload the media using Brain API client
+        brain_client = get_brain_api_client()
+        storage_result = None
+        
         if format == "png":
-            self._upload_image(images[0], presigned_upload_url)
+            storage_result = self._upload_image(images[0], brain_client, output_name)
         elif format == "mp4":
-            self._upload_video(images, presigned_upload_url, framerate)
+            storage_result = self._upload_video(images, brain_client, framerate, output_name)
 
-        # This node is responsible for a single output. We find its corresponding object key.
-        output_key_for_this_node = final_outputs_dict.get(output_name)
-        if not output_key_for_this_node:
+        # Use the storage_id from the upload result for the SQS message
+        if not storage_result:
             logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamOutput): FATAL -- Could not find object key for output name '{output_name}' in output_object_keys."
+                f"🛑\u2009 Nilor-Nodes (MediaStreamOutput): FATAL -- Upload failed or no storage_id returned."
             )
             # Send an empty dictionary to signal failure.
             final_outputs_for_sqs = {}
         else:
-            final_outputs_for_sqs = {output_name: output_key_for_this_node}
+            # Use storage_id directly (it's now a string, not a dict)
+            storage_id = storage_result
+            final_outputs_for_sqs = {output_name: storage_id}
 
         # After upload, send the filtered dictionary of outputs to the SQS queue.
         completion_message = {
@@ -330,9 +339,9 @@ class MediaStreamOutput:
             )
             raise  # Re-raise to fail the ComfyUI job
 
-        return {"ui": {"images": []}, "result": (presigned_upload_url,)}
+        return {"ui": {"images": []}}
 
-    def _upload_image(self, image_tensor, url):
+    def _upload_image(self, image_tensor, brain_client, output_name):
         logging.info(
             "ℹ️\u2009 Nilor-Nodes (MediaStreamOutput): Uploading as PNG image..."
         )
@@ -343,9 +352,30 @@ class MediaStreamOutput:
         img_pil.save(buffer, format="PNG", compress_level=4)
         buffer.seek(0)
 
-        self._perform_upload(buffer, url, "image/png")
+        filename = f"{output_name}.png"
+        minio_endpoint = os.getenv("MINIO_ENDPOINT")
+        if not minio_endpoint:
+            raise ValueError("MINIO_ENDPOINT environment variable is required but not set")
+        
+        # Get presigned upload URL
+        upload_url_response = brain_client.get_presigned_upload_url(filename, "image/png", minio_endpoint)
+        upload_url = upload_url_response["upload_url"]
+        storage_id = upload_url_response["storage_id"]
+        
+        # Upload directly to MinIO
+        buffer.seek(0)
+        upload_response = requests.put(
+            upload_url,
+            data=buffer.getvalue(),
+            headers={"Content-Type": "image/png"},
+            timeout=300
+        )
+        upload_response.raise_for_status()
+        
+        logging.info(f"✅ Nilor-Nodes (MediaStreamOutput): PNG image uploaded successfully. Storage ID: {storage_id}")
+        return storage_id
 
-    def _upload_video(self, image_batch_tensor, url, framerate):
+    def _upload_video(self, image_batch_tensor, brain_client, framerate, output_name):
         logging.info(
             f"ℹ️\u2009 Nilor-Nodes (MediaStreamOutput): Uploading as MP4 video. Frame count: {len(image_batch_tensor)}"
         )
@@ -359,29 +389,29 @@ class MediaStreamOutput:
         imageio.mimwrite(buffer, frames, format="mp4", fps=framerate, quality=8)
         buffer.seek(0)
 
-        self._perform_upload(buffer, url, "video/mp4")
+        filename = f"{output_name}.mp4"
+        minio_endpoint = os.getenv("MINIO_ENDPOINT")
+        if not minio_endpoint:
+            raise ValueError("MINIO_ENDPOINT environment variable is required but not set")
+        
+        # Get presigned upload URL
+        upload_url_response = brain_client.get_presigned_upload_url(filename, "video/mp4", minio_endpoint)
+        upload_url = upload_url_response["upload_url"]
+        storage_id = upload_url_response["storage_id"]
+        
+        # Upload directly to MinIO
+        buffer.seek(0)
+        upload_response = requests.put(
+            upload_url,
+            data=buffer.getvalue(),
+            headers={"Content-Type": "video/mp4"},
+            timeout=300
+        )
+        upload_response.raise_for_status()
+        
+        logging.info(f"✅ Nilor-Nodes (MediaStreamOutput): MP4 video uploaded successfully. Storage ID: {storage_id}")
+        return storage_id
 
-    def _perform_upload(self, buffer, url, content_type):
-        try:
-            logging.info(
-                f"ℹ️\u2009 Nilor-Nodes (MediaStreamOutput): Uploading to {url} with Content-Type: {content_type}"
-            )
-            headers = {"Content-Type": content_type}
-            response = requests.put(
-                url, data=buffer.read(), headers=headers, timeout=300
-            )
-            response.raise_for_status()
-            logging.info("✅ Nilor-Nodes (MediaStreamOutput): Upload successful.")
-        except requests.RequestException as e:
-            logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamOutput): Failed to upload media: {e}"
-            )
-            raise
-        except Exception as e:
-            logging.error(
-                f"🛑\u2009 Nilor-Nodes (MediaStreamOutput): Failed to process and upload media: {e}"
-            )
-            raise
 
 
 # --- Node Mappings ---
@@ -391,6 +421,6 @@ NODE_CLASS_MAPPINGS = {
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "MediaStreamInput": "👺 Media Stream Input (URL)",
-    "MediaStreamOutput": "👺 Media Stream Output (URL)",
+    "MediaStreamInput": "👺 Media Stream Input (Storage)",
+    "MediaStreamOutput": "👺 Media Stream Output (Storage)",
 }

user_input.py

@@ -59,7 +59,7 @@ class NilorUserInput_Float:
                     "STRING",
                     {"default": "my_float_input", "multiline": False},
                 ),
-                "value": ("FLOAT", {"default": 0.0, "step": 0.001}),
+                "value": ("FLOAT", {"default": 0.0}),
             }
         }
 

web/js/media_stream.js

@@ -19,95 +19,45 @@ function hideWidgets(node, widgetNames) {
     });
 }
 
-function setupMediaStreamOutput(node) {
-    // Hide system inputs by default
-    hideWidgets(node, [
-        "content_id",
-        "venue",
-        "canvas",
-        "scene",
-        "presigned_upload_url",
-        "job_completions_queue_url",
-        "output_object_keys",
-    ]);
-
-    const formatWidget = node.widgets.find((w) => w.name === "format");
-    if (!formatWidget) return;
-
-    // Apply current value
-    toggleFramerateWidget(node, formatWidget.value === "mp4");
-    try {
-        const size = node.computeSize();
-        node.onResize?.(size);
-        app.graph?.setDirtyCanvas(true, true);
-    } catch (_) {}
-
-    // Chain the widget callback once
-    if (!formatWidget.__nilorPatched) {
-        const originalCallback = formatWidget.callback;
-        formatWidget.callback = function (value) {
-            toggleFramerateWidget(node, value === "mp4");
-            try {
-                const size = node.computeSize();
-                node.onResize?.(size);
-                app.graph?.setDirtyCanvas(true, true);
-            } catch (_) {}
-            if (originalCallback) return originalCallback.apply(this, arguments);
-        };
-        formatWidget.__nilorPatched = true;
-    }
-}
-
-function setupMediaStreamInput(node) {
-    hideWidgets(node, ["presigned_download_url"]);
-}
-
 app.registerExtension({
     name: "comfy.nilor-nodes.mediaStream",
-
-    async beforeRegisterNodeDef(nodeType, nodeData, appInstance) {
-        if (nodeData?.name === "MediaStreamOutput") {
-            const origAdded = nodeType.prototype.onAdded;
-            nodeType.prototype.onAdded = function () {
-                if (typeof origAdded === "function") origAdded.apply(this, arguments);
-                try { setTimeout(() => setupMediaStreamOutput(this), 0); } catch (_) {}
-            };
-
-            const origConfigure = nodeType.prototype.onConfigure;
-            nodeType.prototype.onConfigure = function () {
-                if (typeof origConfigure === "function") origConfigure.apply(this, arguments);
-                try { setTimeout(() => setupMediaStreamOutput(this), 0); } catch (_) {}
-            };
-        }
-
-        if (nodeData?.name === "MediaStreamInput") {
-            const origAddedIn = nodeType.prototype.onAdded;
-            nodeType.prototype.onAdded = function () {
-                if (typeof origAddedIn === "function") origAddedIn.apply(this, arguments);
-                try { setTimeout(() => setupMediaStreamInput(this), 0); } catch (_) {}
-            };
-
-            const origConfigureIn = nodeType.prototype.onConfigure;
-            nodeType.prototype.onConfigure = function () {
-                if (typeof origConfigureIn === "function") origConfigureIn.apply(this, arguments);
-                try { setTimeout(() => setupMediaStreamInput(this), 0); } catch (_) {}
-            };
-        }
-    },
-
-    afterConfigureGraph(graph) {
-        try {
-            (graph?._nodes || graph?.nodes || []).forEach((n) => {
-                if (n?.comfyClass === "MediaStreamOutput") setupMediaStreamOutput(n);
-                if (n?.comfyClass === "MediaStreamInput") setupMediaStreamInput(n);
-            });
-        } catch (e) {
-            console.warn("nilor-media-stream afterConfigureGraph error", e);
-        }
-    },
-
     nodeCreated(node) {
-        if (node.comfyClass === "MediaStreamOutput") setupMediaStreamOutput(node);
-        if (node.comfyClass === "MediaStreamInput") setupMediaStreamInput(node);
+        if (node.comfyClass === "MediaStreamOutput") {
+            // Hide system inputs by default
+            hideWidgets(node, [
+                "content_id",
+                "venue",
+                "canvas",
+                "scene",
+                "presigned_upload_url",
+                "job_completions_queue_url",
+                "output_object_keys"
+            ]);
+
+            const formatWidget = node.widgets.find((w) => w.name === "format");
+
+            // Initial toggle for framerate based on the default format value
+            toggleFramerateWidget(node, formatWidget.value === "mp4");
+
+            // Store original callback to chain it
+            const originalCallback = formatWidget.callback;
+
+            formatWidget.callback = function (value) {
+                toggleFramerateWidget(node, value === "mp4");
+
+                // Recalculate node size after toggling widgets
+                const size = node.computeSize();
+                node.onResize?.(size);
+                
+                if (originalCallback) {
+                    return originalCallback.apply(this, arguments);
+                }
+            };
+        }
+
+        if (node.comfyClass === "MediaStreamInput") {
+            // Hide system inputs by default
+            hideWidgets(node, ["presigned_download_url"]);
+        }
     },
 });