Update app.py

app.py

@@ -23,40 +23,38 @@ 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 transformers import pipeline
 from faker import Faker
 from random_word import RandomWords
 from textgenrnn import textgenrnn
+import logging
+
+# Configuración de logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 load_dotenv()
 
 app = FastAPI()
 
 lemmatizer = WordNetLemmatizer()
-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()
+redis_password = os.getenv("REDIS_PASSWORD")
+r = redis.Redis(host=os.getenv("REDIS_HOST"), port=int(os.getenv("REDIS_PORT")), password=redis_password)
 
 def create_intents_json():
     intents = {
         "intents": [
             {
                 "tag": "greeting",
-                "patterns": [faker.sentence() for _ in range(5)],
+                "patterns": ["Hola", "¿Cómo estás?", "Buenos días"],
                 "responses": ["¡Hola!", "¿Cómo puedo ayudarte?"],
-                "date": datetime.now().strftime("%Y-%m-%d")
+                "date": "2021-01-01"
             },
             {
                 "tag": "goodbye",
-                "patterns": [faker.sentence() for _ in range(5)],
+                "patterns": ["Adiós", "Hasta luego", "Nos vemos"],
                 "responses": ["¡Hasta luego!", "Cuídate!"],
-                "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")
+                "date": "2021-01-01"
             }
         ]
     }
@@ -102,13 +100,16 @@ async def train_and_save_model():
                 if intent['tag'] not in classes:
                     classes.append(intent['tag'])
 
-        for intent in intents['intents']:
-            for pattern in intent['patterns']:
-                synonyms = generate_synonyms(pattern)
-                for synonym in synonyms:
-                    processed_words = nltk.word_tokenize(synonym)
-                    documents.append((processed_words, intent['tag']))
-                    words.extend(processed_words)
+        # Generar contenido adicional para intents.json
+        fake = Faker()
+        random_words = RandomWords()
+        for _ in range(10):  # Generar 10 nuevas entradas
+            random_pattern = f"{fake.sentence()}"
+            random_tag = random_words.get_random_word()
+            documents.append((nltk.word_tokenize(random_pattern), random_tag))
+            words.extend(nltk.word_tokenize(random_pattern))
+            if random_tag not in classes:
+                classes.append(random_tag)
 
         words = sorted(set(words))
         classes = sorted(set(classes))
@@ -312,7 +313,7 @@ async def root():
     return html_code
 
 if __name__ == "__main__":
-    print("Iniciando la aplicación...")
+    logger.info(f"Application Startup at {datetime.now()}")
     create_intents_json()
     asyncio.run(train_and_save_model())
     uvicorn.run(app, host="0.0.0.0", port=7860)