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add examples
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‎examples/avatar_live.py‎

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"""
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Avatar Live Example
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This example demonstrates how to use the avatar-live model to animate an avatar image.
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The avatar can be animated with audio input (microphone or audio file).
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Usage:
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# With audio file:
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DECART_API_KEY=your-key python avatar_live.py avatar.png audio.mp3
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# With just avatar image (will wait for audio):
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DECART_API_KEY=your-key python avatar_live.py avatar.png
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Requirements:
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pip install decart[realtime]
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"""
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import asyncio
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import os
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import sys
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from pathlib import Path
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try:
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from aiortc.contrib.media import MediaPlayer, MediaRecorder
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except ImportError:
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print("aiortc is required for this example.")
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print("Install with: pip install decart[realtime]")
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sys.exit(1)
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from decart import DecartClient, models
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async def main():
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api_key = os.getenv("DECART_API_KEY")
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if not api_key:
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print("Error: DECART_API_KEY environment variable not set")
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print("Usage: DECART_API_KEY=your-key python avatar_live.py <avatar_image> [audio_file]")
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return
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if len(sys.argv) < 2:
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print("Usage: python avatar_live.py <avatar_image> [audio_file]")
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print("")
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print("Arguments:")
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print(" avatar_image - Path to avatar image (PNG, JPG)")
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print(" audio_file - Optional: Path to audio file for the avatar to speak")
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print("")
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print("Examples:")
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print(" python avatar_live.py avatar.png")
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print(" python avatar_live.py avatar.png speech.mp3")
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return
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avatar_image = sys.argv[1]
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if not os.path.exists(avatar_image):
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print(f"Error: Avatar image not found: {avatar_image}")
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return
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audio_file = sys.argv[2] if len(sys.argv) > 2 else None
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if audio_file and not os.path.exists(audio_file):
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print(f"Error: Audio file not found: {audio_file}")
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return
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print(f"🖼️ Avatar image: {avatar_image}")
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if audio_file:
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print(f"🔊 Audio file: {audio_file}")
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# Load audio if provided
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audio_track = None
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if audio_file:
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print("Loading audio file...")
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player = MediaPlayer(audio_file)
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if player.audio:
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audio_track = player.audio
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print("✓ Audio loaded")
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else:
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print("⚠️ Warning: No audio stream found in file, continuing without audio")
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try:
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from decart.realtime.client import RealtimeClient
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from decart.realtime.types import RealtimeConnectOptions, AvatarOptions
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except ImportError:
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print("Error: Realtime API not available")
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print("Install with: pip install decart[realtime]")
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return
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print("\nCreating Decart client...")
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async with DecartClient(api_key=api_key) as client:
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model = models.realtime("avatar-live")
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print(f"Using model: {model.name}")
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frame_count = 0
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recorder = None
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output_file = Path(f"output_avatar_live.mp4")
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def on_remote_stream(track):
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nonlocal frame_count, recorder
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frame_count += 1
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if frame_count % 25 == 0:
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print(f"📹 Received {frame_count} frames...")
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if recorder is None:
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print(f"💾 Recording to {output_file}")
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recorder = MediaRecorder(str(output_file))
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recorder.addTrack(track)
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asyncio.create_task(recorder.start())
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def on_connection_change(state):
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print(f"🔄 Connection state: {state}")
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def on_error(error):
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print(f"❌ Error: {error.__class__.__name__} - {error.message}")
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print("\nConnecting to Avatar Live API...")
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print("(Sending avatar image...)")
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try:
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realtime_client = await RealtimeClient.connect(
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base_url=client.base_url,
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api_key=client.api_key,
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local_track=audio_track, # Can be None if no audio
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options=RealtimeConnectOptions(
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model=model,
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on_remote_stream=on_remote_stream,
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avatar=AvatarOptions(avatar_image=Path(avatar_image)),
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),
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)
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realtime_client.on("connection_change", on_connection_change)
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realtime_client.on("error", on_error)
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print("✓ Connected!")
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print(f"Session ID: {realtime_client.session_id}")
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if audio_file:
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print("\nPlaying audio through avatar...")
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print("(The avatar will animate based on the audio)")
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else:
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print("\nNo audio provided - avatar will be static")
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print("You can update the avatar image dynamically using set_image()")
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print("\nPress Ctrl+C to stop and save the recording...")
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# Demo: Update avatar image after 5 seconds (if you want to test set_image)
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# Uncomment the following to test dynamic image updates:
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# await asyncio.sleep(5)
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# print("Updating avatar image...")
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# await realtime_client.set_image(Path("new_avatar.png"))
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# print("✓ Avatar image updated!")
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try:
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while True:
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await asyncio.sleep(1)
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except KeyboardInterrupt:
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print(f"\n\n✓ Received {frame_count} frames total")
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finally:
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if recorder:
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try:
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print(f"💾 Saving video to {output_file}...")
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await asyncio.sleep(0.5)
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await recorder.stop()
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print(f"✓ Video saved to {output_file}")
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except Exception as e:
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print(f"⚠️ Warning: Could not save video cleanly: {e}")
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print(" Video file may be incomplete")
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except Exception as e:
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print(f"\n❌ Connection failed: {e}")
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import traceback
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traceback.print_exc()
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finally:
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if "realtime_client" in locals():
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print("\nDisconnecting...")
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await realtime_client.disconnect()
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print("✓ Disconnected")
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if __name__ == "__main__":
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asyncio.run(main())

‎examples/video_restyle.py‎

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"""
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Video Restyle Example
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This example demonstrates how to use the lucy-restyle-v2v model to restyle a video
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using either a text prompt OR a reference image.
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Usage:
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# With text prompt:
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DECART_API_KEY=your-key python video_restyle.py input.mp4 --prompt "anime style"
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# With reference image:
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DECART_API_KEY=your-key python video_restyle.py input.mp4 --reference style.png
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Requirements:
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pip install decart
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"""
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import asyncio
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import argparse
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import os
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import sys
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from pathlib import Path
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from decart import DecartClient, models
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async def main():
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parser = argparse.ArgumentParser(
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description="Restyle a video using text prompt or reference image"
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)
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parser.add_argument("video", help="Path to input video file")
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parser.add_argument(
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"--prompt", "-p",
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help="Text prompt describing the style (e.g., 'anime style', 'oil painting')"
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)
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parser.add_argument(
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"--reference", "-r",
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help="Path to reference image for style transfer"
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)
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parser.add_argument(
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"--output", "-o",
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help="Output file path (default: output_restyle.mp4)"
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)
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parser.add_argument(
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"--seed", "-s",
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type=int,
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help="Random seed for reproducibility"
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)
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parser.add_argument(
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"--enhance",
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action="store_true",
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default=True,
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help="Enhance the prompt (only with --prompt, default: True)"
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)
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parser.add_argument(
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"--no-enhance",
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action="store_true",
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help="Disable prompt enhancement"
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)
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args = parser.parse_args()
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# Validate arguments
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if not args.prompt and not args.reference:
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print("Error: Must provide either --prompt or --reference")
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parser.print_help()
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sys.exit(1)
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if args.prompt and args.reference:
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print("Error: Cannot use both --prompt and --reference")
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print(" Please choose one or the other")
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sys.exit(1)
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api_key = os.getenv("DECART_API_KEY")
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if not api_key:
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print("Error: DECART_API_KEY environment variable not set")
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sys.exit(1)
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video_path = Path(args.video)
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if not video_path.exists():
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print(f"Error: Video file not found: {video_path}")
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sys.exit(1)
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if args.reference:
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ref_path = Path(args.reference)
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if not ref_path.exists():
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print(f"Error: Reference image not found: {ref_path}")
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sys.exit(1)
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output_path = args.output or f"output_restyle_{video_path.stem}.mp4"
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print("=" * 50)
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print("Video Restyle")
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print("=" * 50)
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print(f"Input video: {video_path}")
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if args.prompt:
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print(f"Style: Text prompt - '{args.prompt}'")
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print(f"Enhance prompt: {not args.no_enhance}")
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else:
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print(f"Style: Reference image - {args.reference}")
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print(f"Output: {output_path}")
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if args.seed:
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print(f"Seed: {args.seed}")
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print("=" * 50)
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async with DecartClient(api_key=api_key) as client:
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# Build options
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options = {
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"model": models.video("lucy-restyle-v2v"),
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"data": video_path,
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}
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if args.prompt:
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options["prompt"] = args.prompt
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options["enhance_prompt"] = not args.no_enhance
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else:
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options["reference_image"] = Path(args.reference)
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if args.seed:
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options["seed"] = args.seed
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def on_status_change(job):
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status_emoji = {
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"pending": "⏳",
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"processing": "🔄",
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"completed": "✅",
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"failed": "❌",
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}
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emoji = status_emoji.get(job.status, "•")
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print(f"{emoji} Status: {job.status}")
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options["on_status_change"] = on_status_change
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print("\nSubmitting job...")
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result = await client.queue.submit_and_poll(options)
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if result.status == "failed":
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print(f"\n❌ Job failed: {result.error}")
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sys.exit(1)
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print(f"\n✅ Job completed!")
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print(f"💾 Saving to {output_path}...")
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with open(output_path, "wb") as f:
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f.write(result.data)
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print(f"✓ Video saved to {output_path}")
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print(f" Size: {len(result.data) / 1024 / 1024:.2f} MB")
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if __name__ == "__main__":
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asyncio.run(main())

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