s

app.py

@@ -1,10 +1,44 @@
 import gradio as gr
 
+def generate_video(text_prompt, token):
+    """Generate video from text using the Wan-AI/Wan2.2-TI2V-5B model"""
+    if not token:
+        return None, "Please sign in to use this feature."
+    
+    try:
+        # Use Gradio's client to call the model
+        client = gr.Interface.load("models/Wan-AI/Wan2.2-TI2V-5B", hf_token=token)
+        result = client(text_prompt)
+        return result, "Video generated successfully!"
+    except Exception as e:
+        return None, f"Error generating video: {str(e)}"
+
 with gr.Blocks(fill_height=True) as demo:
     with gr.Sidebar():
-        gr.Markdown("# Inference Provider")
+        gr.Markdown("# Text-to-Video Generator")
         gr.Markdown("This Space showcases the Wan-AI/Wan2.2-TI2V-5B model, served by the replicate API. Sign in with your Hugging Face account to use this API.")
         button = gr.LoginButton("Sign in")
-    gr.load("models/Wan-AI/Wan2.2-TI2V-5B", accept_token=button, provider="replicate")
     
-demo.launch()
+    with gr.Column():
+        gr.Markdown("## Generate Video from Text")
+        gr.Markdown("Enter a text description and generate a video using AI!")
+        
+        text_input = gr.Textbox(
+            label="Text Prompt",
+            placeholder="Describe the video you want to generate...",
+            lines=3
+        )
+        
+        generate_btn = gr.Button("Generate Video", variant="primary")
+        
+        with gr.Row():
+            video_output = gr.Video(label="Generated Video")
+            status_output = gr.Textbox(label="Status", interactive=False)
+        
+        generate_btn.click(
+            fn=generate_video,
+            inputs=[text_input, button],
+            outputs=[video_output, status_output]
+        )
+
+demo.launch()