Update app.py

app.py

@@ -1,65 +1,37 @@
 # interfaceV2.py
 
 import gradio as gr
-import sounddevice as sd
-from scipy.io.wavfile import write
-import tempfile
 import shutil
 import os
 import subprocess
 import sys
 from whisper_audio_transcriber import transcribe_audio, guardar_transcripcion
-from call_openai_api import  moni as rtff   # Asegúrate de que el archivo call_open_api.py esté en el mismo directorio
-
-
-# Paths to files (adjusted as per your specified structure)
-AUDIO_RECORD_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/assets/audio/grabacion_gradio.wav")
-#VIDEO_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/assets/video/data_video_sun_5s.mp4")
-VIDEO_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/assets/video/data_video_sun.mp4")
-#TRANSCRIPTION_TEXT_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/results/transcripcion.txt")
-TRANSCRIPTION_TEXT_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/results/transcripcion.txt")
-RESULT_AUDIO_TEMP_PATH = os.path.abspath( "C:/programacionEjercicios/miwav2lipv6/results/audiov2.wav")
-RESULT_AUDIO_FINAL_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/assets/audio/audio.wav")
-RESULT_VIDEO_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/results/result_voice.mp4")
-TEXT_TO_SPEECH_PATH = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/src/text_to_speech.py")
-
-# Function to record 8-second audio
-def grabar_audio(duration=8, sample_rate=44100):
-    print("Starting recording...")
-    audio_data = sd.rec(int(duration * sample_rate), samplerate=sample_rate, channels=1)
-    print(f"Recording in progress for {duration} seconds...")
-    sd.wait()
-    print("Recording completed.")
-
-    temp_audio = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
-    write(temp_audio.name, sample_rate, audio_data)
-    print("Audio temporarily saved at:", temp_audio.name)
-    temp_audio.close()  # Asegúrate de cerrarlo antes de usarlo
-    os.makedirs(os.path.dirname(AUDIO_RECORD_PATH), exist_ok=True)
-    shutil.copy(temp_audio.name, AUDIO_RECORD_PATH)
-    print(f"Recording copied to: {AUDIO_RECORD_PATH}")
-
-    return AUDIO_RECORD_PATH, "Recording completed."
-
-# Function to transcribe audio with Whisper
+from call_openai_api import moni as rtff
+
+# Rutas
+AUDIO_RECORD_PATH = os.path.abspath("./assets/audio/grabacion_gradio.wav")
+VIDEO_PATH = os.path.abspath("./assets/video/data_video_sun.mp4")
+TRANSCRIPTION_TEXT_PATH = os.path.abspath("./results/transcripcion.txt")
+RESULT_AUDIO_TEMP_PATH = os.path.abspath("./results/audiov2.wav")
+RESULT_AUDIO_FINAL_PATH = os.path.abspath("./assets/audio/audio.wav")
+RESULT_VIDEO_PATH = os.path.abspath("./results/result_voice.mp4")
+TEXT_TO_SPEECH_PATH = os.path.abspath("./src/text_to_speech.py")
+RUN_INFERENCE_PATH = os.path.abspath("./src/run_inference.py")
+
+
 def transcribir_con_progreso(audio_path):
     progreso = gr.Progress()
-    progreso(0, "Starting transcription...")
+    progreso(0, "Iniciando transcripción...")
     model_name = "openai/whisper-large"
-    progreso(25, "Loading Whisper model...")
-
+    progreso(25, "Cargando modelo Whisper...")
     transcripcion = transcribe_audio(audio_path, model_name)
-    progreso(75, "Saving transcription...")
+    progreso(75, "Guardando transcripción...")
     guardar_transcripcion(transcripcion, filename=TRANSCRIPTION_TEXT_PATH)
-    progreso(100, "Transcription completed.")
-    if not os.path.exists(TRANSCRIPTION_TEXT_PATH):
-        raise FileNotFoundError(f"El archivo {TRANSCRIPTION_TEXT_PATH} no se generó.")
-
+    progreso(100, "Transcripción completada.")
     return transcripcion
 
-# Function to convert text to audio using text_to_speech.py
+
 def generar_audio_desde_texto():
-    print("Generating audio from text...")
     result = subprocess.run(
         [sys.executable, TEXT_TO_SPEECH_PATH],
         capture_output=True,
@@ -67,117 +39,70 @@ def generar_audio_desde_texto():
     )
     if result.returncode != 0:
         raise RuntimeError(f"Error ejecutando text_to_speech.py: {result.stderr}")
-    if result.stdout:
-        print("Output:", result.stdout)
-    if result.stderr:
-        print("Errors:", result.stderr)
 
     if os.path.exists(RESULT_AUDIO_TEMP_PATH):
-        print(f"Temporary audio generated at: {RESULT_AUDIO_TEMP_PATH}")
-        
         os.makedirs(os.path.dirname(RESULT_AUDIO_FINAL_PATH), exist_ok=True)
         shutil.copy(RESULT_AUDIO_TEMP_PATH, RESULT_AUDIO_FINAL_PATH)
-        print(f"Final audio copied to: {RESULT_AUDIO_FINAL_PATH}")
-
         return RESULT_AUDIO_FINAL_PATH
     else:
-        print(f"Error: Audio file was not generated in {RESULT_AUDIO_FINAL_PATH} ")
         return None
 
-# Function to process video and audio using run_inference.py with the generated audio file
-def procesar_video_audio():
-    print("Starting video and audio processing...")
-    run_inference_path = os.path.abspath("C:/programacionEjercicios/miwav2lipv6/src/run_inference.py")
 
+def procesar_video_audio():
     result = subprocess.run(
-        [sys.executable, run_inference_path, "--audio", RESULT_AUDIO_FINAL_PATH, "--video", VIDEO_PATH],
+        [sys.executable, RUN_INFERENCE_PATH, "--audio", RESULT_AUDIO_FINAL_PATH, "--video", VIDEO_PATH],
         capture_output=True,
         text=True
     )
-
-    if result.stdout:
-        print("Output:", result.stdout)
-    if result.stderr:
-        print("Errors:", result.stderr)
-
     if os.path.exists(RESULT_VIDEO_PATH):
-        print(f"Processed video saved at: {RESULT_VIDEO_PATH}")
         return RESULT_VIDEO_PATH
     else:
-        print("Error: Video file was not generated at 'results/result_voice.mp4'")
         return None
 
-# Gradio Interface Configuration
+
+def flujo_completo(audio_file_path):
+    try:
+        shutil.copy(audio_file_path, AUDIO_RECORD_PATH)
+        transcripcion = transcribir_con_progreso(AUDIO_RECORD_PATH)
+        respuesta_openai = rtff(TRANSCRIPTION_TEXT_PATH)
+        audio_generado = generar_audio_desde_texto()
+        video_path = procesar_video_audio()
+
+        return "Grabación recibida", AUDIO_RECORD_PATH, transcripcion, audio_generado, video_path
+
+    except Exception as e:
+        return (
+            f"Error durante el flujo completo: {str(e)}",
+            None,
+            f"Error: {str(e)}",
+            None,
+            None
+        )
+
+
 def interfaz():
     with gr.Blocks() as demo:
         with gr.Row():
             with gr.Column():
                 gr.Video(VIDEO_PATH, loop=True, autoplay=True, height=300, width=500)
-                grabar_button = gr.Button("Comenzando la grabacion de audio")
-                estado_grabacion = gr.Textbox(label="Recording Status", interactive=False)
+                audio_input = gr.Audio(source="microphone", type="filepath", label="Graba tu voz")
+                estado_grabacion = gr.Textbox(label="Estado", interactive=False)
 
             with gr.Column():
-                output_audio = gr.Audio(AUDIO_RECORD_PATH, label="Audio Grabado", interactive=False)
-                output_audio_speech = gr.Audio(RESULT_AUDIO_FINAL_PATH, label="Audio TTS", interactive=False)
-                video_resultado = gr.Video(RESULT_VIDEO_PATH,label="Video procesado", interactive=False)
+                output_audio = gr.Audio(label="Audio grabado", interactive=False)
+                output_audio_speech = gr.Audio(label="Audio TTS", interactive=False)
+                video_resultado = gr.Video(label="Video procesado", interactive=False)
                 texto_transcripcion = gr.Textbox(label="Texto transcrito")
-                progreso_transcripcion = gr.Textbox(label="Transcription Status", interactive=False)
-
-            # Full flow: recording, transcription, text-to-speech, and video processing
-            """
-            def flujo_completo():
-                _, mensaje_grabacion = grabar_audio()
-                transcripcion = transcribir_con_progreso(AUDIO_RECORD_PATH)
-                audio_generado = generar_audio_desde_texto()
-                video_path = procesar_video_audio()
-
-                # Ensure function always returns 5 outputs for Gradio, even in error cases
-                if video_path and audio_generado:
-                    return mensaje_grabacion, AUDIO_RECORD_PATH, transcripcion, audio_generado, video_path
-                else:
-                    return mensaje_grabacion, AUDIO_RECORD_PATH, transcripcion, audio_generado or "Audio generation failed", video_path or "Video generation failed"
-            """
-            def flujo_completo():
-                try:
-                    print("Inicio del flujo completo...")
-                    # Grabar audio
-                    audio_path, mensaje_grabacion = grabar_audio()
-                    print("Audio grabado en:", audio_path)
-                    # Transcribir audio
-                    transcripcion = transcribir_con_progreso(audio_path)
-                    print("Transcripción completada:", transcripcion)
-                    
-                    #respuesta_openai = rtff(transcripcion)
-                    respuesta_openai = rtff(TRANSCRIPTION_TEXT_PATH)
-                    print("Respuesta generada  por OpenAI")
-                    
-                    # Generar audio desde texto
-                    audio_generado = generar_audio_desde_texto()
-                    print("Audio generado:", audio_generado)
-                    # Procesar video y audio
-                    video_path = procesar_video_audio()
-                    print("Video procesado en:", video_path)
-                    # Devolver resultados si todo fue exitoso
-                    return mensaje_grabacion, audio_path, transcripcion, audio_generado, video_path
-                
-                except Exception as e:
-                    # Imprime el error en la terminal y regresa mensajes de error a la interfaz
-                    print("Error detectado en flujo completo:", str(e))
-                    return (
-                        "Error durante el flujo completo",
-                        None,  # Audio grabado
-                        f"Error: {str(e)}",  # Transcripción
-                        None,  # Audio generado
-                        None   # Video procesado
-                            )
-
-            grabar_button.click(
-                flujo_completo,
-                outputs=[estado_grabacion, output_audio, texto_transcripcion, output_audio_speech, video_resultado]
-            )
+
+        audio_input.change(
+            flujo_completo,
+            inputs=audio_input,
+            outputs=[estado_grabacion, output_audio, texto_transcripcion, output_audio_speech, video_resultado]
+        )
 
     return demo
 
+
 if __name__ == "__main__":
     demo = interfaz()
-    demo.launch(allowed_paths=["C:/programacionEjercicios/miwav2lipv6/assets", "C:/programacionEjercicios/miwav2lipv6/results"])
+    demo.launch()