vss-deploy-video-embedding
Use this skill when deploying, operating, or integrating the VSS 3.2 GA RT-Embed Video Embedding microservice. Covers Docker Compose bring-up, GPU and storage prerequisites, the `/v1` REST API (file uploads, text and video embeddings, live RTSP streams, health and metrics), Redis/Kafka/OTel integration, common failure modes, and teardown.
npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# VSS Video Embedding (RT-Embed) Use this skill when you need to: - Deploy the VSS Video Embedding microservice from a Docker Compose file. - Generate text or video embeddings against the Cosmos-Embed1-448p model. - Embed an uploaded file, an HTTP/S3/file/data URL, or a live RTSP stream. - Wire the service into a VSS deployment alongside Redis, Kafka, and OpenTelemetry. - Triage readiness, model-download, GPU, or stream-reconnection failures. **Trigger phrases:** `vss-deploy-video-embedding`, `RT-Embed`, `rtvi-embed`, `video embedding service`, `Cosmos-Embed1`, `embed live stream`, `embed video file`, `generate video embeddings`, `text embedding for video search`. ## Service Snapshot - **VSS 3.2 GA skill:** `vss-deploy-video-embedding`. - **Legacy 3.1 name:** RT-Embed. - **Compose service:** `rtvi-embed`. - **Container name:** `vss-rtvi-embed`. - **Image:** `nvcr.io/nvidia/vss-core/vss-rt-embed` (override with `RTVI_EMBED_IMAGE`). - **Default tag:** `3.2.1` (override with `RTVI_EMBED_TAG`). - **Profile:** `bp_developer_search_2d`. - **Container port:** `8000` (host-side `${RTVI_EMBED_PORT}`). - **Default model:** `cosmos-embed1-448p` from `nvidia/Cosmos-Embed1-448p`. - **Health end
- Service Snapshot
- Prerequisites
- Deploy
- Verify
- Common Operations
- Generate video embeddings from an uploaded file
- Generate text embeddings (for text-to-video search)
- Embed a live RTSP stream
- Logs, Metrics, And Status
- Integration Surface
- Error Handling
- Troubleshooting
- Upgrade And Rollback
- Tear Down
cd "{{repo_root}}/deploy/docker/services/rtvi/rtvi-embed"
export RTVI_EMBED_PORT=8017
export VSS_DATA_DIR="${VSS_DATA_DIR:-$(pwd)/.standalone-data}"
export NGC_API_KEY="<your-ngc-api-key>"
export HOST_IP="$(hostname -I | awk '{print $1}')"
export HF_TOKEN="${HF_TOKEN:-}" # optional, but recommended to avoid HF 429s
export RTVI_EMBED_KAFKA_ENABLED=false
export ENABLE_REDIS_ERROR_MESSAGES=false
Prepare VST clip-storage host dir; use `sudo -n` for ownership fixes.
mkdir -p "$CLIP_STORAGE_DIR"What does the vss-deploy-video-embedding skill do?
Use this skill when deploying, operating, or integrating the VSS 3.2 GA RT-Embed Video Embedding microservice. Covers Docker Compose bring-up, GPU and storage prerequisites, the `/v1` REST API (file uploads, text and video embeddings, live RTSP streams, health and metrics), Redis/Kafka/OTel integration, common failure modes, and teardown.
How do I install it?
Run `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA-AI-Blueprints/video-search-and-summarization, a repository with 1,773 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.