| name | vss-summarize-video |
| description | Use when summarizing a recorded video through HITL-gated LVS, with an explicitly approved VLM fallback. Not for reports, archive search, or live RTSP captioning. |
| license | Apache-2.0 |
| metadata | {"version":"3.2.2","author":"NVIDIA Video Search and Summarization team","github-url":"https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization","tags":"nvidia blueprint operational"} |
VSS Summarize Video
Instructions
- Execute the five workflow stages below in order.
- Run API commands yourself; do not tell the user to run them.
- Use the required references at their named decision points.
Examples
Runnable scenarios live under evals/. The command implementations are in
references/end-to-end-example.md.
When to Use
Use when summarizing a recorded video through HITL-gated LVS, to produce one
polished narrative summary with timestamped events when LVS is available.
Do not use this skill for:
- Live RTSP captioning: use
vss-deploy-dense-captioning.
- Incident or alert-window reports: use
vss-generate-video-report Mode B.
- Archive search: use
vss-search-archive.
Required References
Load these files only as directed:
references/end-to-end-example.md: load
before executing the recorded-video workflow. It contains the exact
readiness, VIOS preparation, single-run summarize, and VLM fallback commands.
references/cli_usage.md: load before Stage 4.
vss summarize run issues the summarize request and applies the operator's
configured memory policy; this reference has its flags, exit codes, output
shape, and read verbs.
references/video-summarization-api.md:
load before constructing a live LVS operation by hand — a direct API
question, or the approved VLM fallback. Follow its Runtime OpenAPI
Discovery procedure on Docker. On Kubernetes, follow the K8s note there —
stock LVS Ingress does not publish LVS /openapi.json. The ordered
workflow does not build a summarize payload; the CLI owns that.
references/hitl-prompts.md: load when
collecting LVS scenario, events, and optional objects of interest.
references/video-summarization-debugging.md:
load only when diagnosing a failed or empty response.
references/video-summarization-deployment.md:
load only for deployment, configuration, logs, or service operations.
references/video-summarization-environment-variables.md
and assets/video-summarization.env.example: use when configuring the
service environment.
../vss-build-vision-ai/references/deployment_resolution.md:
Kubernetes VSS_PUBLIC_URL contract and the /lvs mount.
references/deploy-lvs-service.md: load
when asked about LVS's own container image, GPU/CPU/storage sizing, or
deployment contract as a peer service (heavier than
video-summarization-deployment.md, which covers operating an already
running deployment).
references/integrate-lvs-service.md:
load when another agent or skill needs to integrate with LVS as a peer
service — required peers, integration interfaces, API schema, and network
requirements.
Core Invariants
- Route by LVS readiness, never by video duration.
- HTTP 200 from
/v1/ready selects LVS. Empty response bodies do not mean
unavailable.
- Once LVS is selected, do not call a VLM
/v1/chat/completions endpoint.
- Issue exactly one
vss summarize run per user summarize request. One run is
one POST /v1/summarize. Never retry, hedge, broaden events, or run a second
backend automatically.
- Endpoints come from the deployment
vss configure recorded. Never pass an
endpoint, index, or model flag the caller did not name, and never replace a
failed run with hand-rolled curl against /v1/summarize.
- Save the complete command and its stdout. Diagnose failures from those files,
the run's own exit code, service logs, and non-mutating GET requests.
- Render
video_summary and every returned event verbatim. Do not paraphrase,
truncate descriptions, add fields, or fabricate id.
- Direct VLM fallback requires explicit user approval unless the original
request pre-authorized it.
Prerequisites
- VSS
lvs profile reachable either on Docker ($HOST_IP:38111) or through
the public Ingress at ${VSS_PUBLIC_URL}/lvs.
curl and jq on the agent host.
- Network reachability from the LVS service to the final VIOS clip URL (Docker:
from
vss-lvs; Kubernetes: deploy must mint a URL the LVS pod can fetch).
- A checkout containing
services/agent and host uv, for vss summarize run.
- One recorded deployment origin. Configure it once, before Stage 4:
VSS_REPO_ROOT="${VSS_REPO_ROOT:-$HOME/video-search-and-summarization}"
test -f "${VSS_REPO_ROOT}/services/agent/pyproject.toml" || {
echo "VSS checkout not found at ${VSS_REPO_ROOT}; set VSS_REPO_ROOT explicitly" >&2
exit 1
}
VSS=(uv run --project "${VSS_REPO_ROOT}/services/agent" --no-dev --extra cli vss)
cd "${VSS_REPO_ROOT}" && "${VSS[@]}" summarize run --help >/dev/null || exit 1
VSS_ORIGIN="${VSS_PUBLIC_URL:-http://${HOST_IP:-localhost}:7777}"
"${VSS[@]}" configure --base-url "${VSS_ORIGIN%/}" || exit 1
--extra cli is mandatory: the base distribution holds the core libraries,
while nvidia-vss-cli declares the vss executable. Configure against the
ingress origin, never :38111 — that LVS container port exposes no
Elasticsearch, so a deployment recorded from it cannot persist.
The vss-deploy-profile skill can deploy the profile. A remote fallback VLM
must be able to fetch the clip URL; it generally cannot fetch localhost or
private addresses.
Limitations
- Direct VLM fallback cannot target LVS scenarios or events and is lower
quality.
- Private VIOS URLs may be unreachable from remote VLM endpoints.
- Each user request permits one
vss summarize run, with no automatic retry.
- Persistence needs a routed Elasticsearch. A deployment without one summarizes
and reports the result unpersisted rather than failing the job.
- Both edges are configured to wait an hour, matching the CLI's own default, so
a long summarization is not cut short by a 504 that would be recorded as a
failed job. An Ingress the deployment overrides shorter still caps the wait.
- Stock LVS Helm Ingress does not publish LVS
/models, LVS /openapi.json,
/recommended_config, or /metrics — those remain Docker :38111 only.
Endpoint resolution (Kubernetes vs Docker)
Resolve endpoints once before probing. Follow
../vss-build-vision-ai/references/deployment_resolution.md.
if [ -z "${VSS_PUBLIC_URL:-}" ] && [ -n "${VSS_ENDPOINT:-}" ]; then
VSS_PUBLIC_URL="${VSS_ENDPOINT}"
fi
if [ -n "${VSS_PUBLIC_URL:-}" ]; then
DEPLOYMENT_KIND="kubernetes"
VSS_PUBLIC_URL="${VSS_PUBLIC_URL%/}"
LVS_BACKEND_URL="${VSS_PUBLIC_URL}/lvs"
VIDEO_SUMMARIZATION_URL="${LVS_BACKEND_URL}"
VSS_VIOS_URL="${VSS_PUBLIC_URL}/vst"
VST_API_BASE="${VSS_VIOS_URL}/api/v1"
VLM="${VSS_PUBLIC_URL}/rtvi-vlm"
else
DEPLOYMENT_KIND="docker"
LVS_BACKEND_URL="${LVS_BACKEND_URL:-http://${HOST_IP:-localhost}:38111}"
VIDEO_SUMMARIZATION_URL="${LVS_BACKEND_URL}"
VSS_VIOS_URL="http://${HOST_IP:-localhost}:30888/vst"
VST_API_BASE="${VSS_VIOS_URL}/api/v1"
VLM="${VLM_BASE_URL:-${RTVI_VLM_BASE_URL:-http://${HOST_IP:-localhost}:8018}}"
VLM="${VLM%/v1}"
fi
On Kubernetes, do not use kubectl port-forward, Service DNS, NodePorts,
docker exec, or docker inspect. Do not append /v1 to LVS_BACKEND_URL.
Ignore Docker-derived LVS_BACKEND_URL / VLM_BASE_URL / RTVI_VLM_BASE_URL
when VSS_PUBLIC_URL is set. Do not treat public /openapi.json as the LVS
schema (that path is Agent on stock Ingress).
Routing
| Service | Base URL |
|---|
| LVS | ${VIDEO_SUMMARIZATION_URL} (K8s: ${VSS_PUBLIC_URL}; Docker: http://${HOST_IP}:38111) |
| VLM / RT-VLM | ${VLM} then append /v1/... (K8s: the /rtvi-vlm mount; Docker: :8018) |
| VIOS | ${VST_API_BASE} |
Strip a trailing /v1 from the VLM base because this skill appends it. Do not
scan ports or inspect configuration files to guess endpoints.
Probe LVS /v1/ready using the loop in the end-to-end reference. Readiness is
the HTTP status only: retry 503 warmup responses for about 30 seconds, and do
not inspect the body.
| LVS result | Action |
|---|
| HTTP 200 | Use LVS for every video duration. |
| Anything else | Ask to deploy LVS or ask before using VLM fallback. |
If LVS is unavailable, ask:
The VSS lvs profile isn't reachable
(${VSS_PUBLIC_URL:-$HOST_IP:38111}). Shall I deploy it now using
/vss-deploy-profile -p lvs? Reply no to stop here; I can use the
lower-quality VLM-only fallback only if you explicitly ask for it.
- Deployment approved or pre-authorized: invoke
vss-deploy-profile, re-probe,
and continue only after LVS returns 200.
- Deployment declined: ask separately whether to use VLM fallback. Stop unless
the user approves it.
- Fallback pre-authorized: use the fallback without another prompt.
- Non-interactive run: the original task is the only approval source. If it
pre-authorizes neither deployment nor fallback, report blocked and stop.
Recorded Video Workflow
Stage 1: Select the Backend
Load the end-to-end and CLI references. Run the LVS readiness probe before
preparing the clip. Also probe VLM /v1/models so an approved fallback can be
validated, but do not infer against it while LVS is ready.
The summarization model needs no discovery: vss configure recorded the id LVS
reports serving, and vss summarize run defaults to it on both Docker and
Kubernetes. Pass --model only when the caller named one, and read the recorded
value from vss configure show when it has to be reported.
Discover a model id by hand only for an approved VLM fallback, which does not
run through the CLI:
- Docker: honor
${VLM_NAME} only if it matches an id from LVS GET /models;
otherwise use the sole advertised LVS id.
- Kubernetes: prefer
${VLM_NAME} when set; otherwise take the sole id from
GET ${LVS_BACKEND_URL}/models (LVS) or GET ${VLM}/v1/models (RT-VLM). If
multiple ids exist and no valid preference selects one, report them and stop.
A non-200 LVS readiness result after warmup is the only unavailability signal.
An empty summary, empty events, missing optional fields, or empty readiness
stdout must not trigger fallback.
Stage 2: Prepare the Video Through VIOS
Execute VIOS API operations directly as part of this workflow; do not invoke a
separate skill. Follow Prepare the video through VIOS in the end-to-end
reference (uses ${VST_API_BASE}).
- List sensors and reuse the exact requested recording when present.
- If absent and the exact local file is available, upload it through the VIOS
file API. For uploaded or sample media without a requested timestamp, use
2025-01-01T00:00:00.000Z so timeline resolution is deterministic.
- Poll the returned stream's timelines and obtain the complete minimum start
and maximum end time.
- Generate a fresh temporary MP4 URL for that full interval with audio
disabled. Pass that minted URL to
--url as returned (after stripping a
doubled http:// scheme if present). Do not rewrite it for browser Ingress
paths before the summarize run.
- If LVS was selected, verify one-byte reachability:
- Docker:
docker exec vss-lvs Python range probe in the reference.
- Kubernetes: bounded Range GET of the minted URL from the agent host
(no
docker exec / kubectl exec). Deploy must mint a URL the LVS pod
can fetch.
Require the exact recording, full timeline, and fresh clip URL before
continuing. When the source file is available, compare VIOS timeline duration
with source duration. An upload response or byte probe proves reachability, not
complete media readiness.
If preparation fails, stop and report the missing prerequisite. Do not choose
an arbitrary /tmp video, alternate recording, local HTTP server, NvStreamer,
or RTSP source unless the user explicitly requested that source.
Do not use the vss-lvs container's lightweight curl shim for reachability;
it can write the entire video into tool output. Use the one-byte Python probe
on Docker.
Stage 3: Collect LVS Settings
When LVS is selected, load the HITL reference and collect scenario, events,
and optional objects_of_interest before the summarize run.
When the caller explicitly says to run autonomously without prompting and asks
for defaults or supplies no settings, use these values verbatim:
scenario="activity monitoring"
events=["notable activity"]
This is the only HITL bypass. Do not infer defaults from filenames or sensor
names. Mention defaults in the final response and offer a separate rerun with
specific settings.
Stage 4: Submit Once Through the CLI
Load the CLI reference. vss summarize run issues the summarize request on both
Docker and Kubernetes, and persists only when static memory policy enables it.
Do not build a /v1/summarize payload by hand, and do not fetch
/openapi.json to construct one — the CLI owns the request shape,
vss configure owns the endpoint, and vss configure memory owns persistence.
Use the invocation in the end-to-end reference. It passes the fresh VIOS URL
from Stage 2, the exact HITL values from Stage 3, --chunk-duration 10, and
--seed 1; repeat --event per event and add --object-of-interest only when
the caller provided objects. Pass no endpoint flag.
Do not pass --persist or --memory-index; those per-request controls do not
exist. The standard workflow also does not pass --no-persist, so the
operator's configured persistence default applies. When persistence is enabled,
the record needs two values:
--video-id, required alongside --url. Use the recording's VIOS sensor
id — from sensor/list, or from the sensorId an upload returns — never the
stream id. It becomes the record's sensor, which is what list --sensor-id
and time-windowed recall key on. Without --video-id the run exits 2 before
summarizing rather than after.
--creation-time, the media's absolute start. LVS reports event times as
offsets into the clip unless this anchors them, and unified memory stores
instants — so without it the events cannot be written and the run degrades to
exit 6. For uploaded sample media use the same 2025-01-01T00:00:00.000Z
Stage 2 uploaded with.
Do not pass --num-frames-per-chunk in the standard workflow. RT-VLM owns frame
sampling; unset fields are absent from the request, so the deployment's own
default applies.
The final line of stdout is one JSON object naming the job. Read that line and
the exit code; the prose on stderr is a diagnostic, not the result. A call
refused before a job exists prints no marker at all and stderr is the whole
result — check stdout is non-empty before parsing it. Emptiness, not the exit
code, is what says whether a job was created.
| exit | meaning | action |
|---|
| 0 | summarized; persistence followed configured policy | present the result and report persisted truthfully |
| 2 | a flag the CLI refused, before anything was submitted | fix the call, then run once |
| 2 | LVS rejected the request it was sent; the marker names a job closed as failed | report the failure with that job_id |
| 3 | LVS unreachable or returned 5xx | report it with the marker's job_id |
| 4 | deployment configuration is missing, or an explicit Markdown note lacks static sink configuration | no job, no marker — run the remediation command from stderr |
| 6 | summary produced; Elasticsearch or Markdown cache write failed | present the summary; report ES and Markdown outcomes separately |
| 7 | timed out | reconcile with vss summarize get --job-id; do not re-run |
Exits 6 and 7 both mean the summarization already happened. Never repeat the run
to obtain a different view of it, and never repeat it for diagnosis — a second
run requires a separate user request. The exit 2 that carries a marker is the
same story earlier: the request reached LVS and came back refused, so the one
submission this request had is spent and a corrected call belongs to a new
request. Once a job exists, every outcome names its job_id; use it rather than
re-running. A call refused before a job exists names
nothing, which is why empty stdout is the test.
The completion marker's persisted boolean is the authoritative Elasticsearch
outcome. The result body includes persist only when persistence was attempted
and reports its index and event count; optional Markdown status is separate