Update app.py

app.py

@@ -2,60 +2,50 @@ import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 from langdetect import detect
 
-# --- Configuración de modelos ---
-MODEL_NAME = "distilgpt2"  # Modelo ligero y estable en CPU
-TRANSLATE_TO_ES_MODEL = "Helsinki-NLP/opus-mt-mul-es"
-TRANSLATE_FROM_ES_MODEL = "Helsinki-NLP/opus-mt-es-mul"
+# --- Modelos ---
+MODEL_NAME = "distilgpt2"  # Chatbot ligero y libre
+EN_ES_MODEL = "Helsinki-NLP/opus-mt-en-es"
+ES_EN_MODEL = "Helsinki-NLP/opus-mt-es-en"
 
 # --- Cargar modelos ---
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
 generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=-1)
 
-translator_to_es = pipeline("translation", model=TRANSLATE_TO_ES_MODEL, device=-1)
-translator_from_es = pipeline("translation", model=TRANSLATE_FROM_ES_MODEL, device=-1)
+translator_en_es = pipeline("translation", model=EN_ES_MODEL, device=-1)
+translator_es_en = pipeline("translation", model=ES_EN_MODEL, device=-1)
 
-# --- Funciones de traducción ---
-def translate_to_es(text):
+# --- Funciones ---
+def translate_message(text):
     try:
         lang = detect(text)
     except:
         lang = "es"
-    if lang != "es":
-        try:
-            translated = translator_to_es(text, max_length=200)[0]["translation_text"]
-        except:
-            translated = text
-        return translated, lang
-    return text, "es"
+    if lang.startswith("en"):
+        text_es = translator_en_es(text, max_length=100)[0]["translation_text"]
+        return text_es, lang
+    return text, lang
 
-def translate_from_es(text, lang):
-    if lang != "es":
-        try:
-            translated = translator_from_es(text, max_length=200)[0]["translation_text"]
-        except:
-            translated = text
-        return translated
+def translate_response(text, lang):
+    if lang.startswith("en"):
+        text_en = translator_es_en(text, max_length=100)[0]["translation_text"]
+        return text_en
     return text
 
-# --- Función principal del chatbot ---
 def answer(history, message):
     if not message.strip():
         return history, ""
 
-    # Detectar idioma y traducir a español si es necesario
-    msg_es, lang = translate_to_es(message)
+    msg_es, lang = translate_message(message)
 
-    # Construir contexto
     context = ""
     for user, bot in history[-6:]:
         context += f"Usuario: {user}\nIA: {bot}\n"
     context += f"Usuario: {msg_es}\nIA:"
 
-    # Generar respuesta en español
     output = generator(
         context,
-        max_new_tokens=100,  # límite de tokens para reducir uso de memoria
+        max_new_tokens=100,
         do_sample=True,
         top_k=40,
         top_p=0.9,
@@ -67,16 +57,13 @@ def answer(history, message):
     else:
         response_es = output
 
-    # Traducir de vuelta al idioma original
-    response_final = translate_from_es(response_es, lang)
-
-    # Añadir al historial
+    response_final = translate_response(response_es, lang)
     history.append((message, response_final))
     return history, ""
 
 # --- Interfaz Gradio ---
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 Chatbot Multilenguaje (Optimizado CPU)")
+    gr.Markdown("# 🤖 Chatbot Español/Inglés (Solo gratuito)")
     chat = gr.Chatbot()
     msg = gr.Textbox(placeholder="Escribe tu mensaje…")
     clear_btn = gr.Button("Limpiar")