update py

app.py

@@ -1,7 +1,44 @@
 import gradio as gr
+import torch
+import tempfile
+from diffusers import StableVideoDiffusionPipeline
+from diffusers.utils import export_to_video
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Use the official SVD-XT img2vid-xt model
+MODEL = "stabilityai/stable-video-diffusion-img2vid-xt"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Load pipeline in half-precision on GPU
+pipe = StableVideoDiffusionPipeline.from_pretrained(
+    MODEL, torch_dtype=torch.float16
+).to("cuda")
+
+def infer(first_image, last_image, prompt, guidance=7.5, frames=25):
+    # Generate the in-between frames
+    video = pipe(
+        image=first_image,
+        last_image=last_image,
+        prompt=prompt,
+        guidance_scale=guidance,
+        num_frames=frames
+    ).frames
+    # Export as MP4 to a temp file
+    mp4_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
+    export_to_video(video, mp4_path, fps=15)
+    return mp4_path  # Gradio will auto-encode this to base64 for the API
+
+# Build a minimal Gradio interface
+demo = gr.Interface(
+    fn=infer,
+    inputs=[
+        gr.Image(type="pil", label="Start frame"),
+        gr.Image(type="pil", label="End frame"),
+        gr.Textbox(placeholder="Prompt (optional)"),
+        gr.Slider(0, 12, 7.5, label="Guidance scale"),
+        gr.Slider(8, 48, 25, step=1, label="Num frames"),
+    ],
+    outputs="video",
+    title="Eggman – 2-Frame SVD API"
+)
+
+# Enable the REST API
+demo.queue(concurrency_count=1).launch(show_api=True)