Update app.py

app.py

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+import gradio as gr
+import torch
+import spaces
+from diffusers import LTXConditionPipeline
+from diffusers.utils import export_to_video
+from gtts import gTTS
+from pydub import AudioSegment
+import whisper
+import ffmpeg
+import os
+
+# Load pipeline
+pipe = LTXConditionPipeline.from_pretrained(
+    "Lightricks/LTX-Video-0.9.7-distilled", torch_dtype=torch.float16
+)
+pipe.to("cuda")
+
+@spaces.GPU(duration=120)
+def generate_video(prompt):
+    generator = torch.Generator("cuda").manual_seed(42)
+
+    # Generate latent video
+    latents = pipe(
+        prompt=prompt,
+        width=512,
+        height=512,
+        num_frames=24,
+        output_type="latent",
+        generator=generator,
+        num_inference_steps=7
+    ).frames
+
+    # Decode frames
+    frames = pipe(
+        prompt=prompt,
+        latents=latents,
+        num_frames=24,
+        output_type="pil",
+        generator=generator,
+        num_inference_steps=7
+    ).frames[0]
+
+    # Save as video
+    video_path = "output.mp4"
+    export_to_video(frames, video_path, fps=12)
+
+    # TTS
+    tts = gTTS(text=prompt, lang='en')
+    tts.save("voice.mp3")
+    AudioSegment.from_mp3("voice.mp3").export("voice.wav", format="wav")
+
+    # Subtitles
+    model = whisper.load_model("base")
+    result = model.transcribe("voice.wav", language="en")
+    with open("subtitles.srt", "w") as f:
+        f.write(result["srt"])
+
+    # Merge audio + subtitles into video
+    ffmpeg.input(video_path).output(
+        "final.mp4",
+        vf="subtitles=subtitles.srt",
+        i="voice.mp3",
+        c="copy",
+        shortest=None,
+        loglevel="error"
+    ).run()
+
+    return "final.mp4"
+
+# Gradio UI
+demo = gr.Interface(fn=generate_video, inputs="text", outputs=gr.Video())
+demo.launch()