Update app.py

app.py

@@ -1,46 +1,46 @@
+# Realizado por Leonardo Vannoni Lorenzo para el curso de Deep Learning de INTEC, 1105795
+
 import gradio as gr
 from transformers import pipeline
 import torch
 from gtts import gTTS
 from PyPDF2 import PdfReader
 
-# --- Dispositivo ---
+# --- Usar GPU si esta disponible ---
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
  
-# --- Summarizer en español (modelo multilingüe compatible) ---
+# --- Resumidor multilingual ---
 summarizer = pipeline(
     "summarization",
     model="csebuetnlp/mT5_multilingual_XLSum",
     tokenizer="csebuetnlp/mT5_multilingual_XLSum",
     device=0 if torch.cuda.is_available() else -1
 )
-
-# ... (other imports and functions remain the same)
  
 def summarize_and_speak(input_type, text_input, pdf_input):
     """
-    Summarizes the input data (text or PDF) and converts the summary to speech.
+    Resumir el input y devolver mensaje hablado.
     """
     try:
-        if input_type == "text":
+        if input_type == "text":                # Resumir el cuadro de texto
             text = text_input
         elif input_type == "pdf":
-            reader = PdfReader(pdf_input.name)  # Assuming input_data is a file-like object
+            reader = PdfReader(pdf_input.name)  # Resumir el PDF
             text = ""
             for page in reader.pages:
                 text += page.extract_text()
         else:
             raise ValueError("Invalid input type. Choose 'text' or 'pdf'.")
  
-        # --- Usando el nuevo modelo de summarize ---
+        # --- Usando el modelo de summarize ---
         summary = summarizer(
             text,
-            max_length=300,
-            min_length=80,
+            max_length=2500,
+            min_length=500,
             do_sample=False
         )[0]["summary_text"]
  
-        tts = gTTS(text=summary, lang='es')
+        tts = gTTS(text=summary, lang='es')     
         tts.save("summary.mp3")
         return summary, "summary.mp3"
     except Exception as e:
@@ -60,12 +60,9 @@ with gr.Blocks() as demo:
  
     submit_btn = gr.Button("Resumir y Convertir a Voz")
    
-    # Updated to use gr.components for input elements
-    # The 'default' keyword argument is replaced by setting the value directly.
     input_type = gr.components.Radio(choices=["text", "pdf"], label="Tipo de entrada")
-    input_type.value = "text"  # Set the default value here
+    input_type.value = "text"  
  
-    # Pass all inputs to the function, and the function will decide which one to use
     submit_btn.click(fn=summarize_and_speak,
                      inputs=[input_type, text_input, pdf_input],
                      outputs=[text_output, audio_output])