ssrajadh/sentrysearch

Health v2 · maintenance only

Flags: prerelease_only young

Adoption not part of the score

4433 stars · 425 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SentrySearch is a Python CLI tool that provides semantic search over video footage by embedding video chunks with Gemini Embedding, Alibaba DashScope Qwen, or a local Qwen3-VL model, and storing vectors in a local ChromaDB database. Text or image queries return the best-matching segment automatically trimmed from the original video as a clip.

Use cases

• find a specific event in hours of dashcam footage by typing a description
• search Tesla sentry mode videos for a moment like 'car door opened'
• search video by uploading a reference image instead of text
• extract a trimmed clip of a matched event from an mp4
• index large video archives locally with a local vision-language model
• run the whole pipeline offline without any API key

When to choose

• you need natural-language search across large collections of video files
• you want a local-first index (ChromaDB) with an optional no-API-key local model
• you work with dashcam or Tesla footage and want clip extraction plus companion tools for merging and redaction

When to avoid

• you need real-time or live-stream video search
• you want a polished GUI application rather than a CLI workflow
• your videos lack visual events the embedding models can represent (e.g., mostly audio-driven content)

Facets

cli-tool · maturity active

search-engine vector-database video-processing machine-learning cli machine-learning developer-tools windows python cli semantic-search video-embeddings chromadb gemini-embedding qwen3-vl dashcam tesla clip-trimming multimodal-search video search macos linux

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markdown · JSON · MCP: product_card(name="ssrajadh/sentrysearch")