Update app.py

app.py

@@ -44,7 +44,6 @@ def detect_milestone_from_image(image_path):
     """
     Placeholder for content-based milestone detection.
     In a real implementation, use a trained ML model to analyze image features.
-    Here, we use a simplified approach based on image properties.
     """
     try:
         img = Image.open(image_path).convert("RGB")
@@ -112,21 +111,21 @@ def process_image(images, project_name, confirmed_milestone=None):
             img = Image.open(image)
             image_size_mb = os.path.getsize(image) / (1024 * 1024)
             if image_size_mb > 20:
-                return "Error: Image {image} exceeds 20MB.", "Failure", "", "", 0, []
-            if not str(image).lower().lower().endswith(('.jpg', '.jpeg', '.png')):
+                return f"Error: Image {image} exceeds 20MB.", "Failure", "", "", 0, []
+            if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')):
                 return "Error: Only JPG or PNG images are supported.", "Failure", "", "", 0, []
 
             # Save image to local directory
             upload_dir = "public_uploads"
             os.makedirs(upload_dir, exist_ok=True)
-            unique_id = datetime.now().strftime("%Y%m%d%H%M%S")")
-            image_filename = f"{unique_id}_{{os.path.basename(image)}}"
+            unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
+            image_filename = f"{unique_id}_{os.path.basename(image)}"
             saved_path = os.path.join(upload_dir, image_filename)
-            shutil.copy2(image, saved_path))
+            shutil.copy2(image, saved_path)
 
             # Upload image to Salesforce
             with open(saved_path, 'rb') as image_file:
-                image_data = base64.b64encode(image_file.read()).decode('utf-8')
+                image_data = base64.b64encode(image_file.read()).decode('8')
 
             try:
                 content_version = {
@@ -140,14 +139,14 @@ def process_image(images, project_name, confirmed_milestone=None):
                 file_urls.append(file_url)
             except Exception as e:
                 logger.error(f"Failed to upload image to Salesforce: {str(e)}")
-                return f"Error: Failed to upload image - {str(e)}", "Failure", "", "", 0, []
+                return f"Error: Failed to upload image - {str(e)}", "Failure", "", "", 0
 
             milestone = detect_milestone_from_image(saved_path)
             milestones.append(milestone)
 
         # Determine final milestone
         final_milestone = confirmed_milestone or max(set(milestones), key=milestones.count)
-        if not final_milestone in VALID_MILESTONES:
+        if final_milestone not in VALID_MILESTONES:
             return "Error: Invalid milestone detected.", "Failure", "", "", 0, []
 
         # Calculate completion percentage