# Vss Deploy Video Embedding

Use this skill when deploying, operating, integrating, or customizing the VSS RT-Embed...

- Repository: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization (1959 stars)
- Category: AI and agents
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding -g -a claude-code -y`
Codex: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding -g -a codex -y`
Cursor: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-video-embedding -g -a gemini-cli -y`

## Description

Use this skill when deploying, operating, integrating, or customizing the VSS RT-Embed Video Embedding microservice. Covers standalone Docker Compose deployment, the `/v1` REST API for text/video embeddings and live streams, Redis/Kafka/OTel integration, troubleshooting, and bring-your-own-model (BYOM) custom embedding backends, with VideoPrism as an example. Do not use for RT-CV, RT-VLM, VSS Agent, or general VSS deployment work that does not include RT-Embed.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# VSS Video Embedding (RT-Embed)

Use this skill for the RT-Embed video embedding microservice, including the
standard Cosmos-Embed1 deployment path and custom/BYOM embedding model work.

**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`,
`RT-Embed BYOM`, `VideoPrism embed`, `custom embed model`,
`MODEL_IMPLEMENTATION_PATH`, `MODEL_REPOSITORY_SCRIPT_PATH`, `bring your own
embedding model`.

**Do not use this skill** for RT-CV, RT-VLM, VSS Agent, or general VSS
deployment work unless the request deploys, operates, integrates, or customizes
RT-Embed.

## When to Use

- Deploy, size, upgrade, roll back, or tear down standalone RT-Embed (Cosmos-Embed1 or a custom/BYOM model)
- Call RT-Embed's `/v1` API for text/video embeddings, live streams, model listing, health, metrics
- Wire RT-Embed into another service with Redis, Kafka, OpenTelemetry, auth, or storage
- Add or validate a custom/BYOM embedding backend
- Debug RT-Embed readiness, model/cache startup, or Redis/Kafka reachability

## Service Snapshot

- **Skill:** `vss-deploy-video-embedding`.
- **Legacy 3.1 name:** RT-Embed.
- **Compose service:** `rtvi-embed`.
- **Container name:** `vss-rtvi-embed`.
- **Image:** `ghcr.io/nvidia-ai-blueprints/vss/vss-rt-embed` (override with `VSS_RT_EMBED_IMAGE`).
- **Default tag:** `develop-latest` (override with `VSS_RT_EMBED_TAG`; use `develop-latest-sbsa` for an SBSA/DGX Spark host).
- **Profile:** `rtvi-embed`.
- **Container port:** `8000` (host-side `${RTVI_EMBED_PORT}`).
- **Default model:** `cosmos-embed1-448p` from `nvidia/Cosmos-Embed1-448p`.
- **BYOM loader variables:** `MODEL_PATH`, `MODEL_IMPLEMENTATION_PATH`, `MODEL_REPOSITORY_SCRIPT_PATH`.
- **Health endpoint:** `GET /v1/ready`.
- **Healthcheck startup grace:** `1200s` (20 minutes) on first boot.

## Route First

The rest: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization/blob/HEAD/skills/deployment/vss-deploy-video-embedding/SKILL.md