Create app.py

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import os
+import subprocess
+from gtts import gTTS
+from pydub import AudioSegment
+from transformers import GPT2LMHeadModel, GPT2Tokenizer, pipeline
+
+os.environ["TOKENIZERS_PARALLELISM"] = "true"
+generator = pipeline('text-generation', model="salomonsky/deepSP")
+
+def generate_output(text):
+    prompt = ""
+    input_text = prompt + ""
+    gpt2_output = generator(input_text, max_length=20, do_sample=True, temperature=0.9)
+    generated_text = gpt2_output[0]['generated_text']
+    generated_text = generated_text.replace(input_text, "").strip()
+
+    tts = gTTS(generated_text, lang='es')
+    temp_audio_path = "temp_audio.mp3"
+    tts.save(temp_audio_path)
+    audio_path = "audio.wav"
+    audio = AudioSegment.from_mp3(temp_audio_path)
+    audio.export(audio_path, format="wav")
+
+    command = f"python3 inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face face.jpg --audio audio.wav --outfile video.mp4 --nosmooth"
+    process = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    if process.returncode != 0:
+        return None
+
+    output_video_path = "video.mp4"
+    os.remove(temp_audio_path)
+
+    if os.path.isfile(output_video_path):
+        return output_video_path
+
+    return None
+
+iface = gr.Interface(
+    fn=generate_output,
+    inputs=gr.inputs.Textbox(lines=1, placeholder='Escribe tu nombre para presentarte con Andrea...'),
+    outputs=[
+        gr.outputs.Video(label="Respuesta de Andrea (un minuto aproximadamente)")
+    ],
+    title="Andrea - Humanoid Chatbot IA 2023(c)",
+)
+
+iface.launch()