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Sift Video

Sift Video is a self-hosted semantic video search system that indexes speech and sampled frames, stores their embeddings in Qdrant, and returns timestamped audio and visual matches to natural-language queries.

Independent OpenViST project profile, based on linked sources.

Sift Video — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you need timestamp-level discovery across a video collection and can run the indexing and search stack yourself.

Who it is for

  • People who want to search a self-managed library of video by describing a moment in natural language.
  • Developers or operators comfortable running a multi-service Docker application.

Documented uses

  • Build a searchable index of local videos or videos fetched from yt-dlp-compatible URLs.
  • Find relevant moments using speech and visual content, then jump to them in the built-in player.
  • Filter searches to one indexed video or to audio versus visual matches.
Before you choose

Requirements & limits

The documented setup runs locally with Docker Compose and serves the web interface at http://localhost:8080. The project is licensed under GPL-3.0.

  • The system indexes audio and visual content, and labels returned matches by modality.
  • The documented stack uses Docker Compose, Qdrant, Whisper, FFmpeg, ONNX Runtime, and MobileCLIP2-S3-OpenCLIP.
  • CPU setup is documented; the separate GPU configuration requires NVIDIA Container Toolkit.
  • The repository describes local video uploads and yt-dlp-compatible URL ingestion.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up Sift Video and index a local file

Start the self-hosted service and add a local video to its searchable library.

Before you start

  • Git
  • Docker and Docker Compose
  • A local video file

Steps

  1. Clone the repository with its submodules and create the videos and output directories.

  2. Start the CPU services with Docker Compose.

  3. Open the local web interface at http://localhost:8080 and add a video through the upload panel, or copy a file into the videos directory.

  4. Use the search panel to submit a natural-language query after the video has been indexed.

Expected outcome

Search results show relevant timestamps and audio, visual, or combined match types; selecting a result jumps the built-in player to that moment.

Guide limitations

  • The documented NVIDIA GPU configuration requires NVIDIA Container Toolkit on the host.
  • Files added to the videos directory are detected by a polling process described as running every 30 seconds.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
sourav4243/sift-video · Official homepage title · retained in its source language