Update app.py

app.py

@@ -2,7 +2,7 @@ import nltk
 nltk.download('punkt')
 nltk.download('wordnet')
 nltk.download('omw-1.4')
-nltk.download('punkt_tab')
+nltk.download('punkt_tab') # Added punkt_tab download
 from nltk.stem import WordNetLemmatizer
 
 import json
@@ -39,6 +39,10 @@ async def train_and_save_model():
     r = redis.Redis(host=os.getenv("REDIS_HOST"), port=int(os.getenv("REDIS_PORT")), password=redis_password)
 
     while True:
+        words.clear()
+        classes.clear()
+        documents.clear()
+
         for intent in intents['intents']:
             for pattern in intent['patterns']:
                 w = nltk.word_tokenize(pattern)
@@ -48,6 +52,7 @@ async def train_and_save_model():
                     classes.append(intent['tag'])
 
         words = [lemmatizer.lemmatize(w.lower()) for w in words if w not in ignore_words]
+        words = sorted(list(set(words)))
 
         training = []
         output_empty = [0] * len(classes)
@@ -63,7 +68,8 @@ async def train_and_save_model():
 
             training.append([bag, output_row])
 
-        training = np.array(training)
+        training = np.array(training, dtype=object)
+
         train_x = list(training[:, 0])
         train_y = list(training[:, 1])
 
@@ -91,7 +97,7 @@ async def train_and_save_model():
 @app.on_event("startup")
 async def startup_event():
     import asyncio
-    asyncio.create_task(train_and_save_model()) # Start training in the background
+    asyncio.create_task(train_and_save_model())
 
 
 if __name__ == "__main__":