Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline
+import imageio
+import tempfile
+
+# Load model (first run will download weights)
+pipe = DiffusionPipeline.from_pretrained(
+    "Wan-AI/Wan2.2-T2V-A14B",
+    torch_dtype=torch.float16
+).to("cuda")
+
+def generate_video(prompt, steps=25):
+    video = pipe(prompt, num_inference_steps=steps).videos[0]
+    tmpfile = tempfile.NamedTemporaryFile(suffix=".gif", delete=False)
+    imageio.mimsave(tmpfile.name, video, fps=8)
+    return tmpfile.name
+
+demo = gr.Interface(
+    fn=generate_video,
+    inputs=[gr.Textbox(label="Prompt"), gr.Slider(1, 50, value=25, label="Steps")],
+    outputs=gr.Video(label="Generated Video")
+)
+
+demo.launch()