Fix active session override bug and feature array inflation

executable_code/app.py

@@ -163,12 +163,12 @@ def chatbot_route():
     return jsonify({'reply': random.choice(fallback_responses)})
 
 def recommend_crop(user_message):
-    recommend_synonyms = ['recommend', 'suggest', 'advise', 'what crops can i grow', 'what should i plant', 'crop recommendation', 'yes', 'ya']
+    recommend_synonyms = ['recommend', 'suggest', 'advise', 'what crops can i grow', 'what should i plant', 'crop recommendation']
     positive_feedback = ['thanks', 'great', 'good', 'helpful', 'useful', 'love', 'like', 'happy', 'nic']
     negative_feedback = ['bad', 'not good', 'useless', 'hate', 'dislike', 'terrible', 'worst']
 
-    # Start recommendation
-    if any(word in user_message.lower() for word in recommend_synonyms) and session.get('intent') != 'recommend_crop':
+    # Check if user explicitly wants to restart / start a new recommendation
+    if any(word in user_message.lower() for word in recommend_synonyms):
         session['intent'] = 'recommend_crop'
         session['step'] = 0
         session['data'] = []
@@ -222,7 +222,10 @@ def recommend_crop(user_message):
     if session.get('intent') == 'recommend_crop':
         try:
             val = float(user_message)
-            session['data'].append(val)
+            if len(session['data']) >= len(questions):
+                session['data'][-1] = val  # replace last value if already full
+            else:
+                session['data'].append(val)
         except ValueError:
             return jsonify({'reply': "Please enter a valid numeric value for the soil reading."})
 
@@ -232,21 +235,14 @@ def recommend_crop(user_message):
             return jsonify({'reply': questions[session['step'] - 2]})
         else:
             try:
-                # Ensure data length is exactly 4 (in case of double submissions)
-                if len(session['data']) > 4:
-                    session['data'] = session['data'][:4]
-
-                # Model expects: N, P, K, temperature, humidity, ph, rainfall
-                n, p, k, ph = session['data']
-                temp = session['weather']['temperature']
-                hum = session['weather']['humidity']
-                rain = session['weather']['rainfall']
-
-                # Use DataFrame to avoid scikit-learn un-named feature warnings
-                features_df = pd.DataFrame([[n, p, k, temp, hum, ph, rain]], 
-                                        columns=['N', 'P', 'K', 'temperature', 'humidity', 'ph', 'rainfall'])
-                
-                predicted_crops = crop_model.predict(features_df)
+                # Prepare features for crop model
+                features = session['data'] + [
+                    session['weather']['temperature'],
+                    session['weather']['humidity'],
+                    session['weather']['rainfall']
+                ]
+                features_arr = np.array(features, dtype=float).reshape(1, -1)
+                predicted_crops = crop_model.predict(features_arr)
                 session['recommendations'] = predicted_crops
 
                 if len(predicted_crops) == 0:
@@ -295,9 +291,7 @@ def recommend_crop(user_message):
 
             except Exception as e:
                 print(f"Prediction error: {e}")
-                session.pop('intent', None)
-                session.pop('step', None)
-                return jsonify({'reply': f'An error occurred during prediction ({str(e)}). Please type "recommend" to try again.'})
+                return jsonify({'reply': 'An error occurred during prediction. Please try again or check model configuration.'})
 
 def handle_soil_conditions(user_message):
     try: