Enables AI agents to download, transcribe, and inspect video or audio URLs from YouTube, TikTok, X, and 1000+ other sites using server-side yt-dlp, residential proxies, and speech-to-text.
Enables coding agents to watch and analyze videos by extracting scene-aware frames, transcribing speech, and generating shot timelines, all constrained by a token budget to fit LLM context limits.
Lets any LLM agent actually watch videos: a watch_video tool takes a URL or local file and returns scene-aware keyframes fused with a timestamped transcript, processed 100% locally with per-source caching.
Enables AI agents to analyze videos and images using Qwen3-VL deployed on Modal, supporting hours-long videos with timestamp grounding, text extraction, video summarization, and Q\&A with 256K context window.
Enables AI assistants to watch YouTube videos by extracting frames at scene changes and visual references, pairing each frame with the exact words spoken at that timestamp. Provides dense frame-transcript interleaving for any model.