Create app.py

app.py

@@ -0,0 +1,61 @@
+import torch
+from diffusers import DiffusionPipeline
+import gradio as gr
+import os
+
+# 1. Load the Model
+# Use 'cuda' if you have an NVIDIA GPU and CUDA installed, otherwise 'cpu'
+# Hugging Face Spaces will handle the GPU for you if you selected it
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+try:
+    pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16 if device == "cuda" else torch.float32)
+    pipe.to(device)
+    print(f"Model loaded successfully on {device}!")
+except Exception as e:
+    print(f"Error loading model: {e}")
+    print("Ensure all dependencies are in requirements.txt and GPU is available if using 'cuda'.")
+    pipe = None # Set pipe to None if loading fails
+
+# 2. Define the Generation Function
+def generate_video(prompt: str, num_frames: int = 24, guidance_scale: float = 9.0):
+    if pipe is None:
+        return "Error: AI model not loaded. Please check server logs in the 'Logs' tab."
+
+    if not prompt:
+        return "Please enter a text prompt."
+
+    print(f"Generating video for prompt: '{prompt}'")
+    try:
+        # Generate video frames
+        video_frames = pipe(
+            prompt=prompt,
+            num_frames=num_frames,
+            guidance_scale=guidance_scale
+        ).frames
+
+        # The output file path for the video
+        output_filename = "generated_video.mp4"
+        # pipe.to_video creates the video file from frames
+        video_path = pipe.to_video(video_frames, output_filename)
+        return video_path
+    except Exception as e:
+        print(f"Video generation failed: {e}")
+        return f"Video generation failed: {e}"
+
+# 3. Create Gradio Interface
+iface = gr.Interface(
+    fn=generate_video,
+    inputs=[
+        gr.Textbox(label="Text Prompt", placeholder="e.g., 'A robot dancing in the rain'"),
+        gr.Slider(minimum=16, maximum=64, step=4, value=24, label="Number of Frames (Video Length)"),
+        gr.Slider(minimum=1.0, maximum=15.0, step=0.5, value=9.0, label="Guidance Scale (Creativity vs. Prompt Adherence)")
+    ],
+    outputs=gr.Video(label="Generated Video"),
+    title="Simple Text-to-Video Generator (Zeroscope v2)",
+    description="Enter a text prompt to generate a short video using Zeroscope v2."
+)
+
+# 4. Launch the App
+if __name__ == "__main__":
+    iface.launch() # Hugging Face Spaces handles sharing automatically