vss-deploy-video-embedding

name	vss-deploy-video-embedding
description	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.
license	Apache-2.0
metadata	{"version":"3.2.0","github-url":"https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization","tags":"nvidia blueprint operational deployment"}

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: 3.2.0 (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 endpoint: GET /v1/ready.
• Healthcheck startup grace: 1200s (20 minutes) on first boot.

Prerequisites

Before bringing the service up:

1. NVIDIA driver + NVIDIA Container Toolkit installed; default runtime set to nvidia.
2. Docker Engine and Docker Compose plugin recent enough to support ${VAR:+value} conditional volume substitution.
3. docker login nvcr.io completed with $oauthtoken and a valid NGC API key.
4. Host environment provides at minimum: RTVI_EMBED_PORT, VSS_DATA_DIR, NGC_API_KEY, and optionally HF_TOKEN to avoid Hugging Face 429 rate-limit errors during the Cosmos-Embed1 weights download.
5. Free disk space for persistent caches: rtvi-hf-cache, rtvi-ngc-model-cache, rtvi-triton-model-repo (multi-GB).

See references/deploy-vss-deploy-video-embedding.md for the full prerequisite list and references/environment.md for the variable matrix.

Deploy

For standalone RT-Embed, work from the service directory:

cd "{{repo_root}}/deploy/docker/services/rtvi/rtvi-embed"

Do not use /vss-deploy-profile or scripts/dev-profile.sh for this standalone deployment.

For agent-driven validation, never let sudo prompt interactively. Before any privileged ownership or Docker operation, use the non-interactive guard in references/deploy-vss-deploy-video-embedding.md and references/troubleshooting.md: prefer plain docker; otherwise use sudo -n docker; if sudo -n fails, stop with the exact manual command for the host owner instead of retrying with interactive sudo or weakening permissions.

Set a minimal standalone environment before docker compose up. If sudo -n chown fails, stop before docker compose up and ask the host owner to run the printed command.

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.
CLIP_STORAGE_DIR="${VSS_DATA_DIR}/data_log/vst/clip_storage"
mkdir -p "$CLIP_STORAGE_DIR"
if ! sudo -n chown -R 1001:1001 "$CLIP_STORAGE_DIR"; then
  echo "ERROR: passwordless sudo is unavailable for host-path ownership." >&2
  echo "Ask the host owner to run: sudo chown -R 1001:1001 \"$CLIP_STORAGE_DIR\"" >&2
  echo "Do not work around this with chmod 777 or world-writable permissions." >&2
  return 1 2>/dev/null || exit 1
fi

This avoids mounting /data_log/vst/clip_storage from filesystem root when VSS_DATA_DIR is unset, and prevents startup stalls from missing Kafka/Redis peers in standalone mode.

# Bring up the service under the required Compose profile.
docker compose -f rtvi-embed-docker-compose.yml \
  --profile bp_developer_search_2d up -d rtvi-embed

If Docker requires elevated privileges, use sudo -n docker compose ... and fail fast if sudo -n reports that a password is required.

# Watch logs while the model downloads and Triton repo builds.
docker compose -f rtvi-embed-docker-compose.yml logs -f rtvi-embed

First-boot startup may take 20 minutes for the Cosmos-Embed1 download and Triton model repository build. Do not shorten the start_period: 1200s healthcheck during the first boot or the container will be marked unhealthy while still warming up.

Verify

BASE_URL="http://localhost:${RTVI_EMBED_PORT}"

curl -fsS "$BASE_URL/v1/ready"               # 200 when warm.
curl -fsS "$BASE_URL/v1/ready?detailed=true" # Component-level status.
curl -fsS "$BASE_URL/v1/version"
MODELS_JSON=$(curl -fsS "$BASE_URL/v1/models")
echo "$MODELS_JSON"                          # Confirms cosmos-embed1-448p is loaded.

MODEL_ID="$(echo "$MODELS_JSON" | jq -r '.data[0].id // empty')"
test -n "$MODEL_ID" || { echo "ERROR: /v1/models has no model id — wait until /v1/ready is 200" >&2; exit 1; }

The sections below that call the API reuse $BASE_URL and $MODEL_ID from this block.

Common Operations

Generate video embeddings from an uploaded file

FILE_ID=$(curl -fsS -X POST "$BASE_URL/v1/files" \
  -F purpose=vision \
  -F media_type=video \
  -F file=@/path/to/clip.mp4 | jq -r .id)

curl -fsS -X POST "$BASE_URL/v1/generate_video_embeddings" \
  -H "Content-Type: application/json" \
  -d "{
    \"id\": \"$FILE_ID\",
    \"model\": \"$MODEL_ID\",
    \"chunk_duration\": 60,
    \"chunk_overlap_duration\": 10
  }"

Generate text embeddings (for text-to-video search)

curl -fsS -X POST "$BASE_URL/v1/generate_text_embeddings" \
  -H "Content-Type: application/json" \
  -d "{\"text_input\":\"a forklift moving pallets\",\"model\":\"${MODEL_ID}\"}"

Embed a live RTSP stream

Live streams require stream: true and chunk_duration > 0. A synchronous call returns 400 BadParameters: "Only streaming output is supported for live-streams", and the chunk_duration: 0 returned by streams/add is a placeholder — it must be overridden on the embed request or you get 400 BadParameter: "chunk_duration must be greater than 0".

POST /v1/streams/add does not deduplicate by liveStreamUrl — submitting the same URL twice mints two distinct stream_ids. Before adding, call GET /v1/streams/get-stream-info and reuse any existing registration for that URL to avoid orphaned entries.

STREAM_ID=$(curl -fsS -X POST "$BASE_URL/v1/streams/add" \
  -H "Content-Type: application/json" \
  -d '{"streams":[{"liveStreamUrl":"rtsp://host:port/live/video","description":"camera-001"}]}' \
  | jq -r '.results[0].id')

curl -N -X POST "$BASE_URL/v1/generate_video_embeddings" \
  -H "Content-Type: application/json" \
  -H "Accept: text/event-stream" \
  -d "{
    \"id\": \"$STREAM_ID\",
    \"model\": \"$MODEL_ID\",
    \"stream\": true,
    \"chunk_duration\": 10,
    \"chunk_overlap_duration\": 2
  }"

# List registered live streams (use this to recover stream_ids across sessions).
curl -fsS "$BASE_URL/v1/streams/get-stream-info"

# Stop embedding for the stream when done (terminates SSE with data: [DONE]).
curl -fsS -X DELETE "$BASE_URL/v1/generate_video_embeddings/$STREAM_ID"

See references/rest-api.md for the full endpoint catalog, SSE streaming, and single-stream control-plane patterns.

Logs, Metrics, And Status

docker compose -f rtvi-embed-docker-compose.yml ps
docker compose -f rtvi-embed-docker-compose.yml logs -f rtvi-embed
docker stats vss-rtvi-embed

curl -fsS "$BASE_URL/v1/metrics"          # Prometheus.
curl -fsS "$BASE_URL/v1/assets/stats"     # Asset storage counts and TTL.

If RTVI_EMBED_LOG_DIR is bound to a host directory, log files are also available at /opt/nvidia/rtvi/log/rtvi/ on the host.

Integration Surface

• Inputs: REST API on :${RTVI_EMBED_PORT} (POST /v1/files, POST /v1/generate_text_embeddings, POST /v1/generate_video_embeddings, live-stream control endpoints).
• Outputs: Synchronous REST responses, optional SSE for chunked video embeddings, optional Kafka messages on the topics named by RTVI_EMBED_KAFKA_TOPIC (container KAFKA_TOPIC) and RTVI_EMBED_ERROR_MESSAGE_TOPIC (container ERROR_MESSAGE_TOPIC) when Kafka is enabled (host: RTVI_EMBED_KAFKA_ENABLED=true, which Compose maps to container KAFKA_ENABLED).
• Optional peers: Redis (ENABLE_REDIS_ERROR_MESSAGES=true), Kafka (host: RTVI_EMBED_KAFKA_ENABLED=true → container KAFKA_ENABLED), OpenTelemetry collector (host: RTVI_EMBED_ENABLE_OTEL_MONITORING=true → container ENABLE_OTEL_MONITORING).

references/integrate-vss-deploy-video-embedding.md documents the full integration contract.

Error Handling

API failures return JSON with code and message fields:

{
  "code": "BadParameter",
  "message": "chunk_duration must be greater than 0"
}

Pydantic / OpenAPI validation failures use HTTP 422 with code: "InvalidParameters" and a field-level message.

Code	Meaning	Common Cause
400	Bad Request	Missing text_input; unknown file_id / stream_id / model; live stream called without stream: true; chunk_duration: 0 on a live-stream embed request; chunk_overlap_duration >= chunk_duration
401	Unauthorized	Missing or invalid Authorization: Bearer <token> when the deployment enforces auth
403	Forbidden	file:// URLs disabled (FILE_URL_ALLOWED_DIRS unset) or resolved path outside the allow-list (code: "Forbidden")
409	Conflict	DELETE /v1/files/{file_id} while the file is in use (ResourceInUse); another client already connected to the same live stream (Conflict)
413	Payload Too Large	Uploaded file or decoded data: URI exceeds server size limits
422	Unprocessable Entity	Schema validation failure — malformed UUID, wrong multipart field types, invalid enum values; invalid URL format for supported schemes
429	Rate Limited	Request rate exceeded — retry with exponential backoff
500	Internal Server Error	Unexpected inference or I/O failure — inspect docker compose -f rtvi-embed-docker-compose.yml logs -f rtvi-embed
503	Service Unavailable	/v1/ready still warming up (model download / Triton repo build); embedding endpoint busy with another file or text query; max live streams reached; CUDA OOM during inference

503 on /v1/ready during first boot is expected until Cosmos-Embed1 finishes downloading and the Triton model repo is built (up to ~20 minutes). Do not treat it as an application error until after the healthcheck start_period: 1200s elapses.

503 on embedding endpoints with message "Server is busy processing another file or text" or "Server is busy processing another file / live-stream." means the service handles one synchronous embed job at a time — retry with backoff or shard work across instances.

For endpoint-specific constraints (live-stream SSE requirements, URL schemes, response schemas), see references/rest-api.md. For Compose startup, cache, and permission failures, see references/troubleshooting.md.

Troubleshooting

For common failure patterns and resolutions, see references/troubleshooting.md. Frequent issues:

• /v1/ready stuck at 503 → check for missing NGC_API_KEY, Hugging Face 429 rate-limit failures during the first-boot model download (set HF_TOKEN to avoid), or unreachable Redis/Kafka peers when those flags are enabled.
• Healthcheck flipping unhealthy in the first 20 minutes → restore start_period: 1200s.
• Permission errors on bind-mounted cache directories → sudo -n chown -R 1001:1001 on the host paths; if passwordless sudo is unavailable, ask the host owner to run the printed command (do not use chmod 777).
• sudo prompts for a password during deploy → use sudo -n and fail fast; see references/troubleshooting.md; never retry with interactive sudo in an agent session.

Upgrade And Rollback

Pin RTVI_EMBED_IMAGE / RTVI_EMBED_TAG, pull, recreate with --profile bp_developer_search_2d, and wait for /v1/ready before cutover. Named volumes persist across image swaps.

Full steps: Upgrade & Rollback.

Tear Down

Stop the standalone stack with docker compose -f rtvi-embed-docker-compose.yml down. Use down -v only when you intend to destroy named model caches.

Full steps and cache warnings: Tear Down.

References

File	When to read
references/README.md	Table of contents for all reference files.
references/deploy-vss-deploy-video-embedding.md	Build Vision Agent deployment reference: image, GPU, storage, startup, prerequisites, known issues.
references/integrate-vss-deploy-video-embedding.md	Build Vision Agent integration reference: peers, inputs/outputs, env vars, network, example Compose snippet.
references/rest-api.md	Full REST endpoint catalog with worked curl examples for file uploads, video/text embeddings, live streams, and health/metrics.
references/environment.md	Complete environment-variable matrix, including host-to-container renames and secret-sensitive variables.
references/troubleshooting.md	Operational diagnostics for startup, model/cache, runtime, and observability issues.