Update app.py

app.py

@@ -70,7 +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
+        # Save image to public folder temporarily before uploading to Salesforce
         upload_dir = "public_uploads"
         os.makedirs(upload_dir, exist_ok=True)
         unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
@@ -78,16 +78,31 @@ def process_image(image, project_name):
         saved_image_path = os.path.join(upload_dir, image_filename)
         shutil.copy(image, saved_image_path)
 
-        # 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"
+        # Read the file into binary format to upload to Salesforce
+        with open(saved_image_path, 'rb') as image_file:
+            image_data = image_file.read()
 
-        image_url = f"{public_url_base}/{upload_dir}/{image_filename}"
+        # Create the ContentVersion record in Salesforce
+        content_version = {
+            'Title': image_filename,
+            'PathOnClient': saved_image_path,
+            'VersionData': image_data
+        }
+
+        # Upload the file to Salesforce
+        try:
+            content_version_result = sf.ContentVersion.create(content_version)
+            content_version_id = content_version_result['id']
+
+            # Generate the public URL for the uploaded file in Salesforce
+            file_url = f"https://sathkruthatechsolutionspri8-dev-ed.develop.lightning.force.com/{content_version_id}"
+        except Exception as e:
+            return f"Error: Failed to upload image to Salesforce - {str(e)}", "Failure", "", "", 0
 
+        # AI-based milestone and completion prediction
         milestone, percent_complete, confidence_score = mock_ai_model(img)
 
+        # Create the Salesforce record with the image URL and AI prediction
         record = {
             "Name__c": project_name,
             "Current_Milestone__c": milestone,
@@ -95,9 +110,10 @@ def process_image(image, project_name):
             "Last_Updated_On__c": datetime.now().isoformat(),
             "Upload_Status__c": "Success",
             "Comments__c": f"AI Prediction: {milestone} with {confidence_score*100}% confidence",
-            "Last_Updated_Image__c": image_url
+            "Last_Updated_Image__c": file_url
         }
 
+        # Upload the record to Salesforce
         try:
             sf.Construction__c.create(record)
         except Exception as e:
@@ -134,4 +150,4 @@ with gr.Blocks(css=".gradio-container {background-color: #f0f4f8; font-family: A
         outputs=[output_text, upload_status, milestone, confidence, progress]
     )
 
-demo.launch(share=True)
+demo.launch(share=True)