Update app.py

app.py

@@ -1,59 +1,49 @@
 import gradio as gr
-import subprocess
-import os
 import random
 
-# You can also import your real generate_video() from your comfy pipeline here
-# For demo, this will simulate calling your WAN pipeline
-
-WAN_SCRIPT = "generate_wan_video.py"  # You can rename this to your actual comfy runner
-
-def generate_video(prompt, negative_prompt, image, frames, fps):
-    # Save uploaded image
-    image_path = "/tmp/uploaded_image.png"
-    image.save(image_path)
-
-    output_path = f"/tmp/generated_{random.randint(1000,9999)}.mp4"
-
-    # Example: calling your WAN I2V pipeline (replace with actual command)
-    command = [
-        "python3", WAN_SCRIPT,
-        "--prompt", prompt,
-        "--negative_prompt", negative_prompt,
-        "--image", image_path,
-        "--frames", str(frames),
-        "--fps", str(fps),
-        "--output", output_path
-    ]
-
-    print("Running command:", " ".join(command))
-    subprocess.run(command)
-
-    print("Generated:", output_path)
-    return output_path
-
-# Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## 🎬 WAN 2.1 I2V Video Generator\nUpload an image, enter a prompt — generate animated video!")
+with gr.Blocks(fill_height=True) as demo:
+    with gr.Sidebar():
+        gr.Markdown("# Inference Provider")
+        gr.Markdown("This Space showcases the Wan-AI/Wan2.1-T2V-1.3B model, served by the fal-ai API. Sign in with your Hugging Face account to use this API.")
+        button = gr.LoginButton("Sign in")
 
+    gr.Markdown("## 🎬 Generate Video from Text")
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(label="Positive Prompt", value="A beautiful anime girl turning around")
-            negative_prompt = gr.Textbox(label="Negative Prompt", value="ugly, low quality")
-            image = gr.Image(label="Input Image", type="pil")
-            frames = gr.Slider(label="Frames", minimum=8, maximum=64, step=1, value=32)
-            fps = gr.Slider(label="FPS", minimum=8, maximum=30, step=1, value=16)
-            generate_btn = gr.Button("Generate Video")
-        
+            text_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt to generate video...")
+            fps_slider = gr.Slider(1, 24, value=8, label="FPS")
+            frames_slider = gr.Slider(8, 48, value=24, label="Number of Frames")
+            aspect_ratio = gr.Dropdown(choices=["square", "landscape", "portrait"], value="square", label="Aspect Ratio")
+            guidance_scale = gr.Slider(1, 20, value=15, label="Guidance Scale")
+            seed_input = gr.Number(value=random.randint(1, 99999), label="Seed")
+            generate_button = gr.Button("Generate Video")
         with gr.Column():
-            output_video = gr.Video(label="Generated Video")
+            video_output = gr.Video(label="Generated Video")
+
+    # Load model
+    model = gr.load(
+        "models/Wan-AI/Wan2.1-T2V-1.3B",
+        inputs=["prompt", "num_frames", "fps", "aspect_ratio", "guidance_scale", "negative_prompt", "seed"],
+        outputs=video_output,
+        accept_token=button,
+        provider="fal-ai"
+    )
 
-    generate_btn.click(
-        fn=generate_video,
-        inputs=[prompt, negative_prompt, image, frames, fps],
-        outputs=[output_video]
+    def generate_video_fn(prompt, fps, num_frames, aspect_ratio, guidance_scale, seed):
+        return model(
+            prompt=prompt,
+            num_frames=num_frames,
+            fps=fps,
+            aspect_ratio=aspect_ratio,
+            guidance_scale=guidance_scale,
+            negative_prompt="",
+            seed=int(seed)
+        )
+
+    generate_button.click(
+        fn=generate_video_fn,
+        inputs=[text_input, fps_slider, frames_slider, aspect_ratio, guidance_scale, seed_input],
+        outputs=video_output
     )
 
-# Run Gradio app
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()