openclaw/skills/vlmrun/SKILL.md

name	description	homepage	metadata
vlmrun	Use VLM Run's Orion visual AI agent via CLI. Process images, videos, and documents with natural language. Triggers: image understanding/generation, object detection, OCR, video summarization, document extraction, image generation, visual AI chat, 'generate an image/video', 'analyze this image/video', 'extract text from', 'summarize this video', 'process this PDF'.	https://vlm.run	clawdbot emoji requires primaryEnv install 👁️ bins env uv VLMRUN_API_KEY VLMRUN_API_KEY id kind formula bins label uv-brew brew uv uv Install uv (brew)

VLM Run CLI

Chat with VLM Run's Orion visual AI agent via CLI. Process images, videos, and documents with state-of-the-art visual intelligence.

Features

• Image Intelligence: Understanding, captioning, detection, segmentation, generation, editing
• Video Intelligence: Summarization, transcription, keyframe extraction, highlight detection
• Document Intelligence: Layout understanding, OCR, markdown extraction, data extraction from invoices/receipts/forms

Setup

uv venv && source .venv/bin/activate
uv pip install "vlmrun[cli]"

Environment Variables

Variable	Type	Description
VLMRUN_API_KEY	Required	Your VLM Run API key from app.vlm.run
VLMRUN_BASE_URL	Optional	Base URL (default: https://agent.vlm.run/v1)
VLMRUN_CACHE_DIR	Optional	Cache directory (default: ~/.vlmrun/cache/artifacts/)

Command

vlmrun chat "<prompt>" -i input.jpg [options]

Options

Flag	Description
-p, --prompt	Prompt text, file path, or stdin
-i, --input	Input file(s) - images, videos, docs (repeatable)
-o, --output	Artifact directory (default: ~/.vlmrun/cache/artifacts/)
-m, --model	vlmrun-orion-1:fast, vlmrun-orion-1:auto (default), vlmrun-orion-1:pro
-s, --session	Optional session ID to continue a previous session
-j, --json	Raw JSON output
-ns, --no-stream	Disable streaming
-nd, --no-download	Skip artifact download

Examples

Image Understanding

vlmrun chat "Describe what you see in this image in detail" -i photo.jpg
vlmrun chat "Detect and list all objects visible in this scene" -i scene.jpg
vlmrun chat "Extract all text and numbers from this document image" -i document.png
vlmrun chat "Compare these two images and describe the differences" -i before.jpg -i after.jpg

Image Generation

vlmrun chat "Generate a photorealistic image of a cozy cabin in a snowy forest at sunset" -o ./generated
vlmrun chat "Remove the background from this product image and make it transparent" -i product.jpg -o ./output

Video Processing

vlmrun chat "Summarize the key points discussed in this meeting video" -i meeting.mp4
vlmrun chat "Find the top 3 highlight moments and create short clips from them" -i sports.mp4
vlmrun chat "Transcribe this lecture with timestamps for each section" -i lecture.mp4 --json

Video Generation

vlmrun chat "Generate a 5-second video of ocean waves crashing on a rocky beach at golden hour" -o ./videos
vlmrun chat "Create a smooth slow-motion video from this image" -i ocean.jpg -o ./output

Document Extraction

vlmrun chat "Extract the vendor name, line items, and total amount" -i invoice.pdf --json
vlmrun chat "Summarize the key terms and obligations in this contract" -i contract.pdf

Prompt Sources

# Direct prompt
vlmrun chat "What objects and people are visible in this image?" -i photo.jpg

# Prompt from file
vlmrun chat -p long_prompt.txt -i photo.jpg

# Prompt from stdin
echo "Describe this image in detail" | vlmrun chat - -i photo.jpg

Continuing a Session

# Start a new session
vlmrun chat "Create an iconic scene of a ninja in a forest, practicing his skills with a katana" -i photo.jpg

# Continue with previous context (use the session ID from above)
vlmrun chat "Create a new scene with the same character meditating under a tree" -i photo.jpg -s <session_id>

Notes

• Use -o ./<directory> to save generated artifacts (images, videos) relative to your current working directory
• Without -o, artifacts save to ~/.vlmrun/cache/artifacts/<session_id>/
• Multiple input files upload concurrently
• Get your API key from app.vlm.run