Update app.py

app.py

@@ -97,7 +97,47 @@ def generate_video(input_image, prompt, height, width,
                    guidance_scale = 1, steps = 4,
                    seed = 42, randomize_seed = False, 
                    progress=gr.Progress(track_tqdm=True)):
+    """
+    Generate a video from an input image using the Wan 2.1 I2V model with CausVid LoRA.
     
+    This function takes an input image and generates a video animation based on the provided
+    prompt and parameters. It uses the Wan 2.1 14B Image-to-Video model with CausVid LoRA
+    for fast generation in 4-8 steps.
+    
+    Args:
+        input_image (PIL.Image): The input image to animate. Will be resized to target dimensions.
+        prompt (str): Text prompt describing the desired animation or motion.
+        height (int): Target height for the output video. Will be adjusted to multiple of MOD_VALUE (32).
+        width (int): Target width for the output video. Will be adjusted to multiple of MOD_VALUE (32).
+        negative_prompt (str, optional): Negative prompt to avoid unwanted elements. 
+            Defaults to default_negative_prompt (contains unwanted visual artifacts).
+        duration_seconds (float, optional): Duration of the generated video in seconds.
+            Defaults to 2. Clamped between MIN_FRAMES_MODEL/FIXED_FPS and MAX_FRAMES_MODEL/FIXED_FPS.
+        guidance_scale (float, optional): Controls adherence to the prompt. Higher values = more adherence.
+            Defaults to 1.0. Range: 0.0-20.0.
+        steps (int, optional): Number of inference steps. More steps = higher quality but slower.
+            Defaults to 4. Range: 1-30.
+        seed (int, optional): Random seed for reproducible results. Defaults to 42.
+            Range: 0 to MAX_SEED (2147483647).
+        randomize_seed (bool, optional): Whether to use a random seed instead of the provided seed.
+            Defaults to False.
+        progress (gr.Progress, optional): Gradio progress tracker. Defaults to gr.Progress(track_tqdm=True).
+    
+    Returns:
+        tuple: A tuple containing:
+            - video_path (str): Path to the generated video file (.mp4)
+            - current_seed (int): The seed used for generation (useful when randomize_seed=True)
+    
+    Raises:
+        gr.Error: If input_image is None (no image uploaded).
+    
+    Note:
+        - The function automatically resizes the input image to the target dimensions
+        - Frame count is calculated as duration_seconds * FIXED_FPS (24)
+        - Output dimensions are adjusted to be multiples of MOD_VALUE (32)
+        - The function uses GPU acceleration via the @spaces.GPU decorator
+        - Generation time varies based on steps and duration (see get_duration function)
+    """
     if input_image is None:
         raise gr.Error("Please upload an input image.")
 
@@ -174,4 +214,4 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.queue().launch(mcp_server=True)