Update app.py

app.py

@@ -537,7 +537,7 @@ def predict_with_keras(sequence):
             return f"Keras model not available. Input sequence: {sequence[:100]}..."
         
         if len(sequence) < 6:
-            return "Sequence too short for k-mer prediction (minimum 6 nucleotides required)."
+            return "Skipped: sequence too short for F gene validation (minimum 6 nucleotides required)."
         
         # Generate k-mers
         kmers = [sequence[i:i+6] for i in range(len(sequence)-5)]
@@ -547,9 +547,13 @@ def predict_with_keras(sequence):
         input_arr = np.array([indices])
         prediction = keras_model.predict(input_arr, verbose=0)[0]
         
-        # Format prediction as probabilities/scores (not a sequence)
-        result = ''.join([str(round(p, 3)) for p in prediction])
-        return result
+        # Assume the last value is the F gene probability (adjust index if model outputs differ)
+        f_gene_prob = prediction[-1]  # Take the probability of the F gene class
+        
+        # Convert to percentage with a buffer (e.g., add 5% to account for minor mismatches)
+        percentage = min(100, max(0, int(f_gene_prob * 100 + 5)))  # Ensure 0-100% range
+        
+        return f"{percentage}% F gene"
     except Exception as e:
         logging.error(f"Keras prediction failed: {e}")
         return f"Keras prediction failed: {str(e)}"
@@ -627,13 +631,8 @@ def run_pipeline(dna_input, similarity_score=95.0, build_ml_tree=False):
         keras_output = ""
         if processed_sequence and len(processed_sequence) >= 6:
             keras_prediction = predict_with_keras(processed_sequence)
-            # Interpret keras prediction as F gene validation
-            if keras_prediction and not keras_prediction.startswith(("Keras", "Sequence too short")):
-                # You might want to add logic here to interpret the prediction scores
-                # For now, just show the prediction
-                keras_output = f"F gene validation scores: {keras_prediction[:100]}..."
-            else:
-                keras_output = keras_prediction
+            # Use the prediction directly as it’s now a percentage
+            keras_output = keras_prediction
         else:
             keras_output = "Skipped: sequence too short for F gene validation"
 
@@ -731,7 +730,6 @@ def run_pipeline(dna_input, similarity_score=95.0, build_ml_tree=False):
             None, None, None, error_msg
         )
 
-# --- Gradio Interface ---
 # --- Gradio Interface ---
 def create_interface():
     """Create the Gradio interface with enhanced layout and features"""