jae
7fe886fea5
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Skills included: - venice-chat: Chat with Venice LLM models, vision, reasoning - venice-chat-benchmark: Benchmark chat models with infographics - venice-image-gen: Generate images via Venice API - venice-list-image-models: List available image models - venice-list-text-models: List available text models - venice-list-video-models: List available video models - venice-tts: Text-to-speech via Venice API - venice-video-generate: Generate videos from text/images - venice-video-queue: Queue video generation jobs - venice-video-quote: Get video generation cost quotes - venice-video-retrieve: Retrieve completed videos All rebranded from Agent Zero paths to Agent JAE (~/.jae/agent/skills/). Requires VENICE_API_KEY environment variable.
295 lines
8.8 KiB
Python
295 lines
8.8 KiB
Python
"""# Venice.ai Video Retrieve Skill
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Retrieve a queued video by polling until complete.
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Usage:
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python retrieve_video.py MODEL QUEUE_ID [options]
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Examples:
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# Basic retrieval
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id
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# Save to specific path
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id --output /path/to/video.mp4
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"""
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import os
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import sys
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import time
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import json
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import base64
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import argparse
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import requests
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from pathlib import Path
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from typing import Optional, Union
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from pydantic import BaseModel
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VENICE_RETRIEVE_URL = "https://api.venice.ai/api/v1/video/retrieve"
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VENICE_API_KEY = os.getenv("VENICE_API_KEY")
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DEFAULT_OUTPUT_DIR = "/root/venice_videos"
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class VideoRetrieveResponse(BaseModel):
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status: str = "unknown"
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video_url: Optional[str] = None
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video_data: Optional[bytes] = None
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error: Optional[str] = None
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progress: Optional[float] = None
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eta: Optional[int] = None
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def retrieve_video(
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model: str,
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queue_id: str,
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delete_media_on_completion: bool = False
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) -> VideoRetrieveResponse:
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"""Single retrieve request - handles JSON or binary video response."""
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headers = {
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"Authorization": f"Bearer {VENICE_API_KEY}",
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"Content-Type": "application/json"
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}
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request_data = {
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"model": model,
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"queue_id": queue_id,
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"delete_media_on_completion": delete_media_on_completion
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}
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response = requests.post(
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VENICE_RETRIEVE_URL,
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headers=headers,
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json=request_data,
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timeout=120
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)
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if not response.ok:
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return VideoRetrieveResponse(
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status="error",
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error=f"HTTP {response.status_code}: {response.text[:200]}"
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)
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content_type = response.headers.get("Content-Type", "")
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# If response is video data (MP4), return as completed
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if "video" in content_type or b'ftyp' in response.content[:20]:
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return VideoRetrieveResponse(
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status="completed",
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video_data=response.content
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)
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# Try to parse as JSON
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if not response.text or response.text.strip() == "":
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return VideoRetrieveResponse(
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status="pending",
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error="Empty response"
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)
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try:
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data = response.json()
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return VideoRetrieveResponse(**data)
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except Exception as e:
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# Might be binary video without proper content-type
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if len(response.content) > 1000: # Probably video data
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return VideoRetrieveResponse(
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status="completed",
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video_data=response.content
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)
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return VideoRetrieveResponse(
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status="error",
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error=f"Parse error: {e}"
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)
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def poll_until_complete(
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model: str,
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queue_id: str,
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poll_interval: int = 5,
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max_wait: int = 600,
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delete_media_on_completion: bool = False,
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verbose: bool = True
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) -> VideoRetrieveResponse:
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"""Poll until video is complete or failed."""
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start_time = time.time()
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error_count = 0
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while True:
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elapsed = time.time() - start_time
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if elapsed > max_wait:
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raise TimeoutError(f"Timed out after {max_wait}s")
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result = retrieve_video(model, queue_id, delete_media_on_completion)
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status = result.status.lower() if result.status else "unknown"
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if verbose:
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progress_str = f"{result.progress:.0f}%" if result.progress else "?"
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eta_str = f"ETA {result.eta}s" if result.eta else ""
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print(f" [{elapsed:.0f}s] Status: {status} | Progress: {progress_str} {eta_str}")
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if status in ["completed", "complete"]:
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if verbose:
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print(f" ✅ Video ready!")
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return result
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if status == "failed":
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raise RuntimeError(f"Generation failed: {result.error}")
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if status == "error":
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error_count += 1
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if error_count > 10:
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raise RuntimeError(f"Too many errors: {result.error}")
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if verbose:
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print(f" ⚠️ Retrying...")
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else:
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error_count = 0
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time.sleep(poll_interval)
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def save_video(
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video_url: Optional[str] = None,
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video_data: Optional[bytes] = None,
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output_path: Optional[str] = None,
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filename: Optional[str] = None
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) -> str:
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"""Save video from URL, base64, or raw bytes to disk."""
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if output_path:
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path = Path(output_path)
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elif filename:
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path = Path(DEFAULT_OUTPUT_DIR) / filename
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else:
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path = Path(DEFAULT_OUTPUT_DIR) / f"video_{int(time.time())}.mp4"
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path.parent.mkdir(parents=True, exist_ok=True)
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if video_data:
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# Direct binary data
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with open(path, "wb") as f:
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f.write(video_data)
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elif video_url:
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if video_url.startswith("data:"):
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# Base64 data URI
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header, encoded = video_url.split(",", 1)
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data = base64.b64decode(encoded)
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with open(path, "wb") as f:
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f.write(data)
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else:
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# URL download
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response = requests.get(video_url, timeout=120)
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response.raise_for_status()
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with open(path, "wb") as f:
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f.write(response.content)
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else:
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raise ValueError("No video_url or video_data provided")
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return str(path)
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def retrieve_and_save(
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model: str,
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queue_id: str,
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output_path: Optional[str] = None,
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filename: Optional[str] = None,
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poll_interval: int = 5,
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max_wait: int = 600,
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verbose: bool = True
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) -> str:
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"""Poll until complete, then save to disk."""
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result = poll_until_complete(
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model=model,
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queue_id=queue_id,
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poll_interval=poll_interval,
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max_wait=max_wait,
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verbose=verbose
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)
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saved_path = save_video(
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video_url=result.video_url,
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video_data=result.video_data,
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output_path=output_path,
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filename=filename
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)
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if verbose:
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print(f" 💾 Saved to: {saved_path}")
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return saved_path
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def main():
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"""CLI entry point."""
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parser = argparse.ArgumentParser(
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description="Retrieve a queued video from Venice.ai",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""Examples:
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# Basic retrieval (saves to default location)
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id
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# Save to specific path
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id -o /path/to/video.mp4
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# Custom polling settings
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id --interval 10 --max-wait 900
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# Quiet mode (no progress output)
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python retrieve_video.py wan-2.5-preview-text-to-video abc123-queue-id --quiet
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"""
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)
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parser.add_argument("model", help="Model that was used for generation")
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parser.add_argument("queue_id", help="Queue ID returned from queue_video")
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parser.add_argument("--output", "-o", default=None,
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help="Output path for the video file (default: /root/venice_videos/video_<timestamp>.mp4)")
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parser.add_argument("--interval", "-i", type=int, default=5,
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help="Polling interval in seconds (default: 5)")
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parser.add_argument("--max-wait", "-w", type=int, default=600,
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help="Maximum wait time in seconds (default: 600)")
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parser.add_argument("--delete-after", action="store_true",
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help="Delete video from Venice servers after download")
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parser.add_argument("--quiet", "-q", action="store_true",
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help="Suppress progress output")
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parser.add_argument("--json", action="store_true",
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help="Output result as JSON")
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args = parser.parse_args()
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# Check API key
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if not VENICE_API_KEY:
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print("Error: VENICE_API_KEY environment variable not set", file=sys.stderr)
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sys.exit(1)
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verbose = not args.quiet
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try:
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if verbose:
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print(f"🎬 Retrieving video...")
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print(f" Model: {args.model}")
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print(f" Queue ID: {args.queue_id}")
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print(f"")
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saved_path = retrieve_and_save(
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model=args.model,
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queue_id=args.queue_id,
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output_path=args.output,
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poll_interval=args.interval,
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max_wait=args.max_wait,
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verbose=verbose
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)
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if args.json:
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print(json.dumps({"status": "completed", "path": saved_path}))
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elif verbose:
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print(f"")
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print(f"✅ Video saved to: {saved_path}")
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except TimeoutError as e:
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print(f"Error: {e}", file=sys.stderr)
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sys.exit(2)
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except RuntimeError as e:
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print(f"Error: {e}", file=sys.stderr)
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sys.exit(1)
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except Exception as e:
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print(f"Error: {e}", file=sys.stderr)
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sys.exit(1)
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if __name__ == "__main__":
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main()
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