Update app.py

app.py

@@ -23,29 +23,40 @@ from dotenv import load_dotenv
 from datetime import datetime
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.model_selection import train_test_split
+from faker import Faker
+from random_word import RandomWords
+from textgenrnn import textgenrnn
 
 load_dotenv()
 
 app = FastAPI()
 
 lemmatizer = WordNetLemmatizer()
-redis_password = os.getenv("REDIS_PASSWORD")
-r = redis.Redis(host=os.getenv("REDIS_HOST"), port=int(os.getenv("REDIS_PORT")), password=redis_password)
+faker = Faker()
+r = redis.Redis(host=os.getenv("REDIS_HOST"), port=int(os.getenv("REDIS_PORT")), password=os.getenv("REDIS_PASSWORD"))
+random_words = RandomWords()
+textgen = textgenrnn()
 
 def create_intents_json():
     intents = {
         "intents": [
             {
                 "tag": "greeting",
-                "patterns": ["Hola", "¿Cómo estás?", "Buenos días"],
+                "patterns": [faker.sentence() for _ in range(5)],
                 "responses": ["¡Hola!", "¿Cómo puedo ayudarte?"],
-                "date": "2021-01-01"
+                "date": datetime.now().strftime("%Y-%m-%d")
             },
             {
                 "tag": "goodbye",
-                "patterns": ["Adiós", "Hasta luego", "Nos vemos"],
+                "patterns": [faker.sentence() for _ in range(5)],
                 "responses": ["¡Hasta luego!", "Cuídate!"],
-                "date": "2021-01-01"
+                "date": datetime.now().strftime("%Y-%m-%d")
+            },
+            {
+                "tag": "random_word",
+                "patterns": [random_words.get_random_word() for _ in range(5)],
+                "responses": [faker.sentence() for _ in range(5)],
+                "date": datetime.now().strftime("%Y-%m-%d")
             }
         ]
     }