Update app.py

app.py

@@ -22,35 +22,30 @@ try:
         username=SF_USERNAME,
         password=SF_PASSWORD,
         security_token=SF_SECURITY_TOKEN,
-        domain='login'  # Use 'test' for sandbox orgs
+        domain='login'  # Use 'test' for sandbox
     )
 except Exception as e:
     print(f"Salesforce connection failed: {str(e)}")
     raise
 
-# Safe milestone values (must match Salesforce picklist exactly)
-MILESTONE_MAPPING = {
-    "In Progress": "In_Progress",
-    "Started": "In_Progress",
-    "Completed": "Completed",
-    "Planning": "Planning"
-}
+# ✅ Valid milestone values from Salesforce picklist
+VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
 
-# Mock AI model for milestone detection
+# Mock AI model for milestone detection (since we can't train a real model here)
 def mock_ai_model(image):
+    # Preprocessing: Resize, normalize (simulated)
     img = image.convert("RGB")
     max_size = 1024
     img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
 
-    # Simulated AI result
-    predicted_label = "In Progress"  # This label is mapped to valid picklist
-    milestone = MILESTONE_MAPPING.get(predicted_label, "Planning")  # Safe fallback
-    completion_percent = 30
+    # Simulate milestone detection by picking a random valid value
+    milestone = random.choice(VALID_MILESTONES)
+    completion_percent = random.choice([10, 30, 50, 80, 100])  # Just for variety
     confidence_score = round(random.uniform(0.85, 0.95), 2)
 
     return milestone, completion_percent, confidence_score
 
-# Function for Gradio UI
+# Function for Gradio UI to process the image
 def process_image(image):
     try:
         if image is None:
@@ -64,7 +59,9 @@ def process_image(image):
         if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')):
             return "Error: Only JPG/PNG images are supported.", "Failure", "", "", 0
 
+        # Run mock AI model
         milestone, percent_complete, confidence_score = mock_ai_model(img)
+
         unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
 
         record = {
@@ -92,7 +89,7 @@ def process_image(image):
     except Exception as e:
         return f"Error: {str(e)}", "Failure", "", "", 0
 
-# Gradio interface
+# Gradio interface for testing
 with gr.Blocks(css=".gradio-container {background-color: #f0f4f8; font-family: Arial;} .title {color: #2c3e50; font-size: 24px; text-align: center;}") as demo:
     gr.Markdown("<h1 class='title'>Construction Milestone Detector</h1>")
     image_input = gr.Image(type="filepath", label="Upload Construction Site Photo (JPG/PNG, ≤ 20MB)")
@@ -109,5 +106,4 @@ with gr.Blocks(css=".gradio-container {background-color: #f0f4f8; font-family: A
         outputs=[output_text, upload_status, milestone, confidence, progress]
     )
 
-# Launch the Gradio app
 demo.launch(share=False)