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Dockerfile.txt

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+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.11
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+
+COPY --chown=user ui.py ui.py
+COPY --chown=user veo_vid.py veo_vid.py
+
+EXPOSE 7860
+
+CMD ["python", "ui.py"]

env.example.txt

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+GOOGLE_API_KEY=

requirements.txt

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+google-genai
+gradio
+python-dotenv

ui.py

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+import gradio as gr
+
+from veo_vid import generate_video
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# Veo Video Generator\nEnter your prompt and generate a video!")
+    prompt = gr.Textbox(
+        label="Prompt",
+        value="A high-end fashion ad showing a confident male model in a new dark blue suit sprinting down a professional runway.",
+    )
+    generate_btn = gr.Button("Generate Video")
+    video_output = gr.Video(label="Generated Video")
+
+    def on_generate(prompt):
+        video_path = generate_video(prompt)
+        if video_path:
+            return gr.update(value=video_path)
+        else:
+            return gr.update(value=None)
+
+    generate_btn.click(on_generate, inputs=prompt, outputs=video_output)
+
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0", server_port=7860, auth=("devmode", "testdeployment8721")
+    )

veo_vid.py

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+import os
+import time
+
+from dotenv import load_dotenv
+from google import genai
+
+load_dotenv()
+
+
+def generate_video(prompt):
+    client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))
+
+    operation = client.models.generate_videos(
+        model="veo-3.0-generate-001",
+        prompt=prompt,
+        config={
+            "aspect_ratio": "16:9",
+            "negative_prompt": "cartoon, drawing, low quality",
+        },
+    )
+
+    # Poll the operation status until the video is ready.
+    while not operation.done:
+        print("Waiting for video generation to complete...")
+        time.sleep(10)
+        operation = client.operations.get(operation)
+
+    # Download the generated video.
+    generated_video = operation.response.generated_videos[0]
+    client.files.download(file=generated_video.video)
+    generated_video.video.save("example.mp4")
+    print("Generated video saved to example.mp4")
+    return "example.mp4"  # Return the path of the generated video
+
+
+if __name__ == "__main__":
+
+    prompt = (
+        "A high-end fashion ad showing a confident male model in a new dark blue suit "
+        "sprinting down a professional runway. The model begins at the ramp's edge, "
+        "straightening his jacket and giving a close-up, focused look. He runs "
+        "forward, energetically engaging with the camera, then transitions to smooth "
+        "side and three-quarter views. The video uses fast, smooth cinematic cuts, "
+        "dynamic tracking, and stylish lateral pans. The model does a slow-motion "
+        "turn, strikes a confident pose with hands in pockets, and the camera "
+        "elegantly pans from shoes to face. Dramatic runway lighting, crisp highlights, "
+        "and an upbeat, trendy soundtrack add excitement. In the final second, the "
+        "model stops, looks directly into the camera with a smile, and the scene "
+        "blurs to a bold, minimalist animated brand title card: 'Best Name.' The "
+        "whole scene is energetic, clean, visually striking, and lasts 8 seconds, "
+        "echoing top luxury fashion campaigns."
+    )
+    generate_video(prompt)