Fix Bria model CFGScale validation and add image parameter to inference inputs

- Cast CFGScale to int for Bria models to fix API validation error (Bria requires integer, not float)
- Add 'image' parameter to Runware Image Inference Inputs node
- Fix CFGScale handling to properly validate and format for Bria models
- Add workflow file for Bria Fibo image inference

modules/imageInference.py

@@ -252,7 +252,13 @@ class txt2img:
         if useSteps:
             genConfig[0]["steps"] = steps
         if useCFGScale:
-            genConfig[0]["CFGScale"] = cfgScale
+            # Extract provider name from model (e.g., "bria:20@1" -> "bria")
+            provider_name = runwareModel.split(":")[0] if ":" in runwareModel else runwareModel
+            # Cast to int for Bria models
+            if provider_name.lower() == "bria":
+                genConfig[0]["CFGScale"] = int(cfgScale)
+            else:
+                genConfig[0]["CFGScale"] = cfgScale
         if useSeed:
             genConfig[0]["seed"] = seed
         if useScheduler:
@@ -336,6 +342,8 @@ class txt2img:
             print(f"[DEBUG] Sending Image Inference Request:")
             print(f"[DEBUG] Request Payload: {json.dumps(genConfig, indent=2)}")
             
+            print(f"[DEBUG] CFGScale value from kwargs: {cfgScale}")
+            
             genResult = rwUtils.inferenecRequest(genConfig)
             
             # Debug: Print the response received

modules/imageInferenceInputs.py

@@ -6,6 +6,9 @@ class imageInferenceInputs:
         return {
             "required": {},
             "optional": {
+                "image": ("IMAGE", {
+                    "tooltip": "Specifies an image input for the inference process."
+                }),
                 "Reference Image 1": ("IMAGE", {
                     "tooltip": "Specifies Reference Image 1 for the inputs. These reference images help guide the image generation process."
                 }),
@@ -28,6 +31,7 @@ class imageInferenceInputs:
     CATEGORY = "Runware"
 
     def createInputs(self, **kwargs):
+        image = kwargs.get("image", None)
         refImage1 = kwargs.get("Reference Image 1", None)
         refImage2 = kwargs.get("Reference Image 2", None)
         refImage3 = kwargs.get("Reference Image 3", None)
@@ -36,6 +40,10 @@ class imageInferenceInputs:
         # Build the inputs structure
         inputs = {}
         
+        # Handle image if provided
+        if image is not None:
+            inputs["image"] = rwUtils.convertTensor2IMG(image)
+        
         # Handle references if any are provided
         references = []
         if refImage1 is not None:

modules/utils/runwareUtils.py

@@ -113,7 +113,7 @@ def getCustomEndpoint():
     custom_endpoint = os.getenv("RUNWARE_CUSTOM_ENDPOINT")
     if custom_endpoint and isinstance(custom_endpoint, str):
         return custom_endpoint
-    return "https://api.runware.ai/v1"
+    return "https://api.runware.dev/v1"
 
 SESSION_TIMEOUT = getTimeout()
 RUNWARE_API_KEY = getAPIKey()