Update app.py

app.py

@@ -56,6 +56,7 @@ except Exception as e:
     tokenizer = model = None
 
 def generate_with_logprobs(prompt, max_new_tokens=100):
+    """Generate text and return (generated_text, avg_log_prob)."""
     if tokenizer is None or model is None:
         return "[Model not loaded]", -10.0
     inputs = tokenizer(prompt, return_tensors="pt")
@@ -138,11 +139,13 @@ iot_sim = IoTSimulator()
 iot_history = []  # store recent readings for prediction
 
 # ----------------------------------------------------------------------
-# Helper: update risk with feedback
+# Helper: update risk with feedback (global state – shared across users)
+# For per‑session risk, use gr.State instead of globals.
 # ----------------------------------------------------------------------
 last_task_category = None
 
 def feedback(thumbs_up: bool):
+    """Handle user feedback to update Beta priors."""
     global last_task_category
     if last_task_category is None:
         return "No previous analysis to rate."
@@ -153,6 +156,7 @@ def feedback(thumbs_up: bool):
 # Async handlers for each tab
 # ----------------------------------------------------------------------
 async def handle_text(task_type, prompt):
+    """Handle text generation and analysis."""
     global last_task_category
     last_task_category = task_type
     try:
@@ -196,6 +200,7 @@ async def handle_text(task_type, prompt):
         return {"error": str(e)}
 
 async def handle_image(prompt):
+    """Handle image generation and quality analysis."""
     global last_task_category
     last_task_category = "image"
     if image_pipe is None:
@@ -239,6 +244,7 @@ async def handle_image(prompt):
         return {"error": str(e)}, None
 
 async def handle_audio(audio_file):
+    """Handle audio transcription and quality analysis."""
     global last_task_category
     last_task_category = "audio"
     if audio_pipe is None:
@@ -287,6 +293,7 @@ async def handle_audio(audio_file):
         return {"error": str(e)}
 
 async def read_iot_sensors(fault_type):
+    """Read simulated IoT sensors, run diagnostics, and predict failure."""
     global last_task_category, iot_history
     last_task_category = "iot"
     iot_sim.set_fault(fault_type if fault_type != "none" else None)
@@ -313,7 +320,7 @@ async def read_iot_sensors(fault_type):
     # Run diagnostician
     diag_result = await robotics_diagnostician.analyze(event)
 
-    # Simple failure prediction
+    # Simple failure prediction (linear extrapolation)
     prediction = None
     if len(iot_history) >= 5:
         temps = [h['temperature'] for h in iot_history[-5:]]
@@ -369,7 +376,7 @@ with gr.Blocks(title="ARF v4 – AI Reliability Lab", theme="soft") as demo:
             diag_display = gr.JSON(label="Diagnosis")
             pred_display = gr.JSON(label="Failure Prediction")
 
-    # Feedback row
+    # Feedback row (shared across all users – for demo purposes)
     with gr.Row():
         feedback_up = gr.Button("👍 Correct")
         feedback_down = gr.Button("👎 Incorrect")