app.py

app.py

@@ -0,0 +1,49 @@
+import os
+from diffusers import StableDiffusionPipeline
+import ffmpeg
+import gradio as gr
+
+# Retrieve the token from Hugging Face secrets
+token = os.getenv("HUGGINGFACE_TOKEN")
+
+print(f"Using Hugging Face Token: {os.getenv('HUGGINGFACE_TOKEN')}")
+
+model = StableDiffusionPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5"
+)
+model.to("cpu")  # Use CPU since GPU is not available
+
+def generate_video(prompt):
+    # Generate frames
+    frames = []
+    for i in range(5):  # Adjust the number of frames for your video
+        image = model(prompt).images[0]
+        frame_path = f"frame_{i}.png"
+        image.save(frame_path)
+        frames.append(frame_path)
+
+    # Combine frames into a video
+    output_video = "output.mp4"
+    (
+        ffmpeg
+        .input("frame_%d.png", framerate=1)  # Adjust framerate
+        .output(output_video)
+        .run(overwrite_output=True)
+    )
+
+    # Clean up frames
+    for frame in frames:
+        os.remove(frame)
+
+    return output_video  # Path to the generated video
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Video Generator")
+    prompt_input = gr.Textbox(label="Enter your video prompt", placeholder="Type something creative...")
+    video_output = gr.File(label="Download Your Video")
+    generate_button = gr.Button("Generate Video")
+
+    generate_button.click(fn=generate_video, inputs=prompt_input, outputs=video_output)
+
+demo.launch()