Update app.py

app.py

@@ -32,20 +32,18 @@ except Exception as e:
 # Valid milestones
 VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
 
-# Updated deterministic AI prediction with accurate completion percentages
+# Deterministic AI prediction with fixed confidence and percent
 def mock_ai_model(image):
     img = image.convert("RGB")
     max_size = 1024
     img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
 
-    # Hash image bytes for deterministic output
     img_bytes = img.tobytes()
     img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
 
     milestone_index = img_hash % len(VALID_MILESTONES)
     milestone = VALID_MILESTONES[milestone_index]
 
-    # Map milestones to fixed completion percentages
     milestone_completion_map = {
         "Planning": 10,
         "Foundation": 30,
@@ -54,13 +52,12 @@ def mock_ai_model(image):
     }
     completion_percent = milestone_completion_map.get(milestone, 0)
 
-    # Deterministic confidence score between 0.85 and 0.95
     confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
     confidence_score = round(confidence_raw, 2)
 
     return milestone, completion_percent, confidence_score
 
-# Gradio function
+# Image processing and Salesforce upload
 def process_image(image, project_name):
     try:
         if image is None:
@@ -73,7 +70,7 @@ def process_image(image, project_name):
         if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')):
             return "Error: Only JPG/PNG images are supported.", "Failure", "", "", 0
 
-        # Save image to public folder for URL generation
+        # Save image to public folder
         upload_dir = "public_uploads"
         os.makedirs(upload_dir, exist_ok=True)
         unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
@@ -81,14 +78,16 @@ def process_image(image, project_name):
         saved_image_path = os.path.join(upload_dir, image_filename)
         shutil.copy(image, saved_image_path)
 
-        # Create public URL assuming you're serving /public_uploads/ via static web server (e.g., on localhost or external host)
-        public_url_base = os.getenv("PUBLIC_URL_BASE", "http://localhost:7860/public_uploads")
-        image_url = f"{public_url_base}/{image_filename}"
+        # Corrected public URL logic
+        if os.getenv("GRADIO_SERVER_NAME"):
+            public_url_base = f"https://{os.getenv('GRADIO_SERVER_NAME')}/file"
+        else:
+            public_url_base = "http://localhost:7860/file"
+
+        image_url = f"{public_url_base}/{upload_dir}/{image_filename}"
 
-        # Predict
         milestone, percent_complete, confidence_score = mock_ai_model(img)
 
-        # Construct Salesforce record
         record = {
             "Name__c": project_name,
             "Current_Milestone__c": milestone,