rt-vlm

Generates vision-language captions and incident alerts from videos or RTSP streams via RTVI VLM API in VSS 3.1.

Updated May 23, 2026
One-click install
npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill rt-vlm-yo-steven
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rt-vlm
Source: https://github.com/yo-steven/skills-exploration-20260522/tree/main/skills/video-search-and-summarization/rt-vlm
Command: npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill rt-vlm-yo-steven

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

RTVI VLM helps you turn video files or live RTSP streams into dense, timestamped vision-language captions while also producing anomaly-style incident alerts via the VSS 3.1 rtvi-vlm microservice.

Core Features & Use Cases

  • Dense captioning for stored videos and live streams: generate captions and chunked outputs through /v1/generate_captions_alerts.
  • Media and stream lifecycle management: upload files via /v1/files and register/delete RTSP sources via /v1/streams/add and /v1/streams/delete/{stream_id}.
  • OpenAI-compatible inference and operational debugging: use /v1/chat/completions for NIM/OpenAI-style requests and consult health/models/metrics endpoints.
  • Kafka incident + error publishing: consume caption, incident, and error topics for downstream monitoring and validation.

Quick Start

Upload a video to get a file id, then request chunked dense captions and alert generation by calling POST /v1/generate_captions_alerts with stream enabled.

Frequently Asked Questions about rt-vlm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate dense video captions from RTSP live streams?▼

Generate dense video captions from RTSP live streams by registering the source via /v1/streams/add, then calling /v1/generate_captions_alerts with streaming enabled to receive timestamped outputs and anomaly incident alerts.

How does Kafka integration work for video captioning and incident alerts?▼

Kafka integration for video captioning works by publishing caption, incident, and error events to dedicated topics during stream processing, allowing downstream consumers to monitor and validate outputs from the /v1/generate_captions_alerts endpoint.

Can I use OpenAI-compatible chat completions with VLM video captioning APIs?▼

You can use OpenAI-compatible chat completions with VLM video captioning via the /v1/chat/completions endpoint, which supports NIM-compatible requests alongside the core /v1/generate_captions_alerts and /v1/files endpoints.

What is the process for uploading stored video files to get timestamped captions?▼

Uploading stored video files for timestamped captions requires using the /v1/files endpoint to upload media and obtain a file ID, then passing that ID to /v1/generate_captions_alerts to retrieve dense chunked caption outputs.

Does the VSS 3.1 VLM API support Server-Sent Events for streaming caption outputs?▼

The VSS 3.1 VLM API supports Server-Sent Events for streaming caption outputs by enabling the stream parameter when calling /v1/generate_captions_alerts, returning chunked dense captions and alerts incrementally as they are processed.

How do I manage and delete active RTSP stream sources for video captioning?▼

Manage and delete active RTSP stream sources for video captioning by registering new feeds through /v1/streams/add and removing existing sources using the /v1/streams/delete/{stream_id} endpoint within the VSS 3.1 microservice.