Update app.py

app.py

@@ -79,16 +79,20 @@ def analyze_construction_image(images=None, video=None):
 
         if images:
             for i, image_file in enumerate(images):
-                image = Image.open(image_file.name)  # For image uploads, we use image_file.name
-                resized_image = resize_image(image)  # Resize image before processing
+                image = Image.open(image_file.name)
+                resized_image = resize_image(image)
                 image_data_url = f"data:image/png;base64,{encode_image(resized_image)}"
                 messages = [
+                    {
+                        "role": "system",
+                        "content": "You are an AI assistant specialized in analyzing images for safety issues. Your task is to first determine if the image shows a construction site. If it does, identify any safety issues or hazards, categorize them, provide a detailed description, and suggest steps to resolve them. If it's not a construction site, simply state that and briefly describe what you see in the image."
+                    },
                     {
                         "role": "user",
                         "content": [
                             {
                                 "type": "text",
-                                "text": f"Analyze this construction site image (Image {i+1}/{len(images)}). Explain the image in detail. Identify any safety issues or hazards, categorize them, provide a detailed description, and suggest steps to resolve them."
+                                "text": f"Analyze this image (Image {i+1}/{len(images)}). First, determine if it's a construction site. If it is, explain the image in detail, focusing on safety aspects. If it's not, briefly describe what you see."
                             },
                             {
                                 "type": "image_url",
@@ -112,16 +116,20 @@ def analyze_construction_image(images=None, video=None):
                 results.append((f"Image {i+1} analysis", result))
 
         if video:
-            frames = extract_frames_from_video(video)  # Use video directly, as it's a file path
+            frames = extract_frames_from_video(video)
             for i, frame in enumerate(frames):
                 image_data_url = f"data:image/png;base64,{encode_image(frame)}"
                 messages = [
+                    {
+                        "role": "system",
+                        "content": "You are an AI assistant specialized in analyzing video frames for safety issues. Your task is to first determine if the frame shows a construction site. If it does, identify any safety issues or hazards, categorize them, provide a detailed description, and suggest steps to resolve them. If it's not a construction site, simply state that and briefly describe what you see in the frame."
+                    },
                     {
                         "role": "user",
                         "content": [
                             {
                                 "type": "text",
-                                "text": f"Analyze this frame from a construction site video (Frame {i+1}/5). Explain what you observed in the video. Identify any safety issues or hazards, categorize them, provide a detailed description, and suggest steps to resolve them."
+                                "text": f"Analyze this frame from a video (Frame {i+1}/{len(frames)}). First, determine if it's a construction site. If it is, explain what you observe, focusing on safety aspects. If it's not, briefly describe what you see."
                             },
                             {
                                 "type": "image_url",
@@ -148,7 +156,7 @@ def analyze_construction_image(images=None, video=None):
         return results
     except Exception as e:
         logger.error(f"Error during analysis: {str(e)}")
-        logger.error(traceback.format_exc())  # Log the full traceback for debugging
+        logger.error(traceback.format_exc())
         return [("Analysis error", f"Error during analysis: {str(e)}")]
         
 def chat_about_image(message, chat_history):