Create app.py

app.py

@@ -0,0 +1,60 @@
+import gradio as gr
+import torch
+from diffusers import LTXPipeline
+from diffusers.utils import export_to_video
+import tempfile
+import random
+
+# Load the LTX Video model
+pipe = LTXPipeline.from_pretrained("Lightricks/LTX-Video", torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+def generate_video(prompt, negative_prompt, height, width, num_frames, num_inference_steps, seed):
+    if seed == -1:
+        seed = random.randint(0, 2**32 - 1)
+    
+    generator = torch.Generator(device="cuda").manual_seed(seed)
+
+    video = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        height=height,
+        width=width,
+        num_frames=num_frames,
+        num_inference_steps=num_inference_steps,
+        generator=generator
+    ).frames[0]
+
+    # Export video to temporary file
+    with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
+        export_to_video(video, tmpfile.name, fps=24)
+        return tmpfile.name
+
+# Gradio Interface
+title = "LTX-Video Generator"
+description = "Generate high-quality videos from text using the Lightricks LTX-Video model."
+
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(f"## {title}\n{description}")
+    
+    with gr.Row():
+        prompt = gr.Textbox(label="Prompt", value="A woman with long brown hair and light skin smiles at another woman...", lines=5)
+        negative_prompt = gr.Textbox(label="Negative Prompt", value="worst quality, inconsistent motion, blurry, jittery, distorted", lines=5)
+
+    with gr.Row():
+        height = gr.Slider(minimum=64, maximum=720, step=32, value=480, label="Height")
+        width = gr.Slider(minimum=64, maximum=1280, step=32, value=704, label="Width")
+        num_frames = gr.Slider(minimum=9, maximum=257, step=8, value=161, label="Number of Frames")
+        num_inference_steps = gr.Slider(minimum=10, maximum=100, step=1, value=50, label="Inference Steps")
+        seed = gr.Number(value=-1, label="Seed (set -1 for random)")
+
+    generate_btn = gr.Button("Generate Video")
+    output_video = gr.Video(label="Generated Video")
+
+    generate_btn.click(
+        fn=generate_video,
+        inputs=[prompt, negative_prompt, height, width, num_frames, num_inference_steps, seed],
+        outputs=output_video
+    )
+
+demo.launch()