Update app.py

app.py

@@ -38,7 +38,7 @@ def encode_image(image):
 def analyze_construction_image(image):
     if image is None:
         logger.warning("No image provided")
-        return "Error: No image uploaded", "", "", []
+        return [(None, "Error: No image uploaded")]
 
     try:
         logger.info("Starting image analysis")
@@ -83,7 +83,7 @@ def analyze_construction_image(image):
             parsed_result = json.loads(result)
         except json.JSONDecodeError:
             logger.error("Failed to parse API response as JSON")
-            return "Error: Invalid response format", "", "", []
+            return [(None, "Error: Invalid response format")]
 
         snag_category = parsed_result.get('snag_category', 'N/A')
         snag_description = parsed_result.get('snag_description', 'N/A')
@@ -93,13 +93,13 @@ def analyze_construction_image(image):
         
         # Initialize chat history with analysis results
         chat_history = [
-            (None, f"Snag Category: {snag_category}\n\nSnag Description: {snag_description}\n\nSteps to Desnag:\n{desnag_steps}")
+            (None, f"Image Analysis Results:\n\nSnag Category: {snag_category}\n\nSnag Description: {snag_description}\n\nSteps to Desnag:\n{desnag_steps}")
         ]
         
-        return snag_category, snag_description, desnag_steps, chat_history
+        return chat_history
     except Exception as e:
         logger.error(f"Error during image analysis: {str(e)}")
-        return f"Error: {str(e)}", "", "", []
+        return [(None, f"Error: {str(e)}")]
 
 def chat_about_image(message, chat_history):
     try:
@@ -120,7 +120,7 @@ def chat_about_image(message, chat_history):
         
         # Make API call
         completion = client.chat.completions.create(
-            model="llama-3.2-90b-vision-preview",  # Using the chat model here
+            model="llama-3.2-90b-vision-preview",
             messages=messages,
             temperature=0.7,
             max_tokens=500,
@@ -145,18 +145,15 @@ with gr.Blocks() as iface:
             image_input = gr.Image(type="pil", label="Upload Construction Image")
             analyze_button = gr.Button("Analyze Image")
         with gr.Column(scale=2):
-            snag_category = gr.Textbox(label="Snag Category")
-            snag_description = gr.Textbox(label="Snag Description")
-            desnag_steps = gr.Textbox(label="Steps to Desnag")
+            chatbot = gr.Chatbot(label="Analysis Results and Chat")
     
-    chatbot = gr.Chatbot(label="Chat about the Image")
     msg = gr.Textbox(label="Ask a question about the image")
-    clear = gr.Button("Clear")
+    clear = gr.Button("Clear Chat")
 
     analyze_button.click(
         analyze_construction_image,
         inputs=[image_input],
-        outputs=[snag_category, snag_description, desnag_steps, chatbot]
+        outputs=[chatbot]
     )
 
     msg.submit(chat_about_image, [msg, chatbot], [msg, chatbot])