Comprehensive update: Image captioning improvements, audio inference, and node color standardization

- Fix image captioning widget targeting to prevent prompt field overwriting
- Add support for multiple images, custom prompts, and model selection in image captioning
- Add missing audio inference nodes to unified color scheme
- Add missing provider settings nodes to unified color scheme
- Fix tensor boolean evaluation error in image captioning
- Update image captioning to match SDK logic for inputImages/inputImage handling
- Separate prompt input from generated caption output fields

clientlibs/utils.js

@@ -44,11 +44,15 @@ function captionNodeHandler(msgEvent) {
     const captionData = msgEvent.detail;
     const captionText = captionData.captionText;
     const captionNodeID = parseInt(captionData.nodeID);
+    
     if(captionData.success) {
         const captionNode = app.graph.getNodeById(captionNodeID);
-        if(captionNode !== null || captionNode !== undefined) {
-            const captionInput = captionNode.widgets[1].inputEl;
-            captionInput.value = captionText;
+        if(captionNode !== null && captionNode !== undefined) {
+            // Find the imageCaption widget specifically
+            const imageCaptionWidget = captionNode.widgets.find(widget => widget.name === "imageCaption");
+            if(imageCaptionWidget && imageCaptionWidget.inputEl) {
+                imageCaptionWidget.inputEl.value = captionText;
+            }
         }
     }
     return false;

modules/imageCaptioning.py

@@ -11,20 +11,40 @@ class imageCaptioning:
                     "label_on": "Enabled",
                     "label_off": "Disabled",
                 }),
-                "Image": ("IMAGE", {
-                    "tooltip": "Specify The Image to be Captioned."
+                "prompt": ("STRING", {
+                    "multiline": True,
+                    "default": "Describe this image in detail",
+                    "placeholder": "Enter the prompt for image captioning. You can provide multiple prompts separated by newlines.",
+                    "tooltip": "The prompt(s) to guide the image captioning. Multiple prompts can be provided, each on a new line."
                 }),
             },
             "optional": {
-                "Image Description": ("STRING", {
+                "inputImages": ("IMAGE", {
+                    "tooltip": "Connect multiple Load Image nodes here to caption multiple images at once."
+                }),
+                "inputImage": ("IMAGE", {
+                    "tooltip": "Connect a single Load Image node here for convenience. If inputImages is provided, this will be ignored."
+                }),
+                "model": ("STRING", {
+                    "default": "",
+                    "placeholder": "Leave empty for default model (runware:150@1)",
+                    "tooltip": "Optional: Specify the AIR model ID (e.g., runware:150@1, runware:150@2). Leave empty to use the default model."
+                }),
+                "template": ("STRING", {
+                    "default": "",
+                    "placeholder": "Optional template for structured output",
+                    "tooltip": "Optional template to structure the caption output."
+                }),
+                "imageCaption": ("STRING", {
                     "multiline": True,
-                    "placeholder": "You Don't Have to write Anything here.\nThe Image Description Will Be Generated Automatically.",
+                    "placeholder": "Generated image caption will appear here automatically.",
+                    "tooltip": "This field will be automatically populated with the generated image caption."
                 }),
             },
             "hidden": { "node_id": "UNIQUE_ID" }
         }
 
-    DESCRIPTION = "Image to text, also known as image captioning, allows you to obtain descriptive text prompts based on uploaded or previously generated images. This process is instrumental in generating textual descriptions that can be used to create additional images or provide detailed insights into visual content."
+    DESCRIPTION = "Advanced image captioning with support for multiple images, custom prompts, and model selection. Generate descriptive text from single or multiple images using customizable prompts and optional AIR models. Perfect for batch processing and structured output generation."
 
     FUNCTION = "imageCaptioning"
     RETURN_TYPES = ("STRING",)
@@ -40,16 +60,75 @@ class imageCaptioning:
         return True
 
     def imageCaptioning(self, **kwargs):
-        image = kwargs.get("Image")
-        genConfig = [
-            {
-                "taskType": "imageCaption",
-                "taskUUID": rwUtils.genRandUUID(),
-                "inputImage": rwUtils.convertTensor2IMG(image)
-            }
-        ]
+        inputImages = kwargs.get("inputImages", None)
+        inputImage = kwargs.get("inputImage", None)
+        prompt = kwargs.get("prompt", "Describe this image in detail")
+        model = kwargs.get("model", "")
+        template = kwargs.get("template", "")
+        
+        # Handle multiple prompts - split by newlines
+        prompt_list = [p.strip() for p in prompt.split('\n') if p.strip()]
+        if not prompt_list:
+            prompt_list = ["Describe this image in detail"]
+        
+        # Determine which images to use (following SDK logic)
+        if inputImages is not None:
+            images_to_process = inputImages
+        elif inputImage is not None:
+            # Single image provided via inputImage - convert to array
+            images_to_process = [inputImage]
+        else:
+            raise Exception("Either inputImages or inputImage must be provided")
+        
+        # Set inputImage to inputImages[0] if not already provided
+        actual_input_image = inputImage
+        if actual_input_image is None and len(images_to_process) > 0:
+            actual_input_image = images_to_process[0]
+        
+        # Convert images to base64 format
+        converted_images = []
+        for img in images_to_process:
+            converted_images.append(rwUtils.convertTensor2IMG(img))
+        
+        # Create a dictionary with mandatory parameters
+        task_params = {
+            "taskType": "imageCaption",
+            "taskUUID": rwUtils.genRandUUID(),
+        }
+        
+        # Add either inputImage or inputImages, but not both (API requirement)
+        if len(converted_images) == 1:
+            # Single image - use inputImage parameter
+            task_params["inputImage"] = converted_images[0]
+        else:
+            # Multiple images - use inputImages parameter
+            task_params["inputImages"] = converted_images
 
+        # Add model parameter only if specified - backend handles default
+        if model and model.strip():
+            task_params["model"] = model.strip()
+
+        # Add template parameter if specified
+        if template and template.strip():
+            task_params["template"] = template.strip()
+            # When using template, do NOT include prompt parameter
+        else:
+            # Use the provided prompt when no template
+            task_params["prompt"] = prompt_list
+
+        # Send the task with all applicable parameters
+        genConfig = [task_params]
         genResult = rwUtils.inferenecRequest(genConfig)
-        genText = genResult["data"][0]["text"]
+        print(genResult)
+        
+        # Handle multiple results if multiple images were processed
+        if len(genResult["data"]) > 1:
+            # Multiple images - combine results
+            combined_text = "\n\n".join([item["text"] for item in genResult["data"]])
+            genText = combined_text
+        else:
+            # Single image
+            genText = genResult["data"][0]["text"]
+        
         rwUtils.sendImageCaption(genText, kwargs.get("node_id"))
         return (genText, )

modules/utils/runwareUtils.py

@@ -240,6 +240,7 @@ def sendImageCaption(captionText, nodeID):
             "success": True,
             "captionText": captionText,
             "nodeID": nodeID,
+            "widgetName": "imageCaption",  # Target the new imageCaption widget
         },
     )