| name | vss-search-archive |
| description | Search video archives using natural language — find events, objects, actions, and people across recorded video using Cosmos Embed1 semantic search. Use when asked to search for something in video, find events, locate objects, or query video archives. Requires the search profile to be deployed. |
| owner | NVIDIA |
| service | vss-sop |
| version | 1.0.0 |
| license | CC-BY-4.0 AND Apache-2.0 |
| reviewed | "2026-06-23T00:00:00.000Z" |
| metadata | {"openclaw":{"os":["linux"]},"author":"nvidia <info@nvidia.com>","tags":["vss","search","cosmos-embed","archive"]} |
Video Search Workflows
Search video archives by natural language using Cosmos Embed1 embeddings. Requires the search profile — deploy with the deploy skill (-p search).
Alpha Feature — not recommended for production use.
Overview
Use this skill when a user asks to search historical footage or locate visual entities inside the recorded video database via natural language.
Key use cases:
- "Find all instances of forklifts"
- "When did someone enter the restricted area?"
- "Show me people near the loading dock"
- "Search for vehicles between 8am and noon"
Prerequisites
- Search Profile Deployed: Ensure that the search profile has been started (
vss-sop-deploy with -p search).
- Embedding Ingestion Active: Video uploads/streams must be active so the
rtvi-embed service can write vectors to Elasticsearch.
Instructions
1. Ingestion & Indexing
Videos uploaded or streamed via VIOS are processed by the rtvi-embed service. Cosmos Embed1 is used to generate 1024-dimension embeddings, which are automatically indexed into Elasticsearch via Kafka. No manual indexing steps are required.
2. Formulating Natural Language Queries
Users query using visual concepts (objects, colors, actions). The queries are mapped to similarity vectors to search the Elasticsearch index.
3. Execution via VSS Agent
Execute the natural-language search query by passing it to the VSS Agent's /generate endpoint.
Examples
Search via VSS Agent API
curl -s -X POST http://localhost:8000/generate \
-H "Content-Type: application/json" \
-d '{"input_message": "find all instances of forklifts"}' | jq .
Visual Description Search
curl -s -X POST http://localhost:8000/generate \
-H "Content-Type: application/json" \
-d '{"input_message": "find someone wearing a red jacket near entrance"}' | jq .
Action-Based Search
curl -s -X POST http://localhost:8000/generate \
-H "Content-Type: application/json" \
-d '{"input_message": "show me people running in the parking lot"}' | jq .
Error Handling
Agent API Connection Refused (port 8000)
If requests fail with connection refused:
- Check the VSS Agent container status:
docker ps -a --filter name=vss-agent
- Restart the agent container if needed:
docker compose -f deployments/compose.yml --profile bp_sop_2d restart vss-agent
Search Results Empty / No Matches
If semantic search queries return empty lists:
- Verify the
search profile is deployed and rtvi-embed is running:
docker ps --format '{{.Names}}' | grep rtvi-embed
- Verify Elasticsearch indices exist and are populated:
curl -s http://localhost:9200/_cat/indices?v
License
Use of this skill is governed by the Creative Commons Attribution 4.0 International License (CC BY 4.0) and the Apache License, Version 2.0.
