Update app.py

app.py

@@ -140,13 +140,24 @@ def predict(prompt, video_data, temperature, model, tokenizer):
     
     return response
 
+def get_analysis_prompt(step_number):
+    """Constructs the prompt for analyzing manufacturing delays based on the selected step."""
+    return f"""You are an AI expert system specializing in manufacturing processes. 
+Your task is to analyze video footage from Step {step_number} of a tire manufacturing process and identify any issues based on the observed footage.
+- Focus on identifying signs of delay or disruption.
+- If no person is visible, it may indicate a staffing issue.
+- If a person is seen modifying the tire, they may be repairing defects or handling material issues.
+- Carefully examine for mechanical failures, material problems, or human involvement.
+
+Provide an analysis of the video by determining the most likely cause of delay in this step, and explain why this conclusion was reached based on the visual evidence."""
+
 def inference(video, step_number):
     """Analyzes video to predict possible issues based on the manufacturing step."""
     try:
         if not video:
             return "Please upload a video first."
         
-        prompt = f"You are analyzing video footage from Step {step_number} of a manufacturing process. Provide an analysis based on the observed video."
+        prompt = get_analysis_prompt(step_number)
         temperature = 0.8
         response = predict(prompt, video, temperature, model, tokenizer)
         
@@ -178,10 +189,7 @@ def create_interface():
         gr.Examples(
             examples=[
                 ["7838_step2_2_eval.mp4", "Step 2"],
-                ["7838_step6_2_eval.mp4", "Step 6"],
-                ["7838_step8_1_eval.mp4", "Step 8"],
-                ["7993_step6_3_eval.mp4", "Step 6"],
-                ["7993_step8_3_eval.mp4", "Step 8"]
+                ["7838_step6_2_eval.mp4", "Step 6"]
             ],
             inputs=[video, step_number],
             cache_examples=False