Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Use the VLM Run CLI (`vlmrun`) to interact with Orion visual AI agent. 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'.
Use the VLM Run CLI (`vlmrun`) to interact with Orion visual AI agent. 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'.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Chat with VLM Run's Orion visual AI agent via CLI.
uv venv && source .venv/bin/activate uv pip install "vlmrun[cli]"
You must load the following variables in your environment so that the CLI can use them. You may load the ./env file to your environment. VariableTypeDescriptionVLMRUN_API_KEYRequiredYour VLM Run API key (required)VLMRUN_BASE_URLOptionalBase URL (default: https://agent.vlm.run/v1)VLMRUN_CACHE_DIROptionalCache directory (default: ~/.vlmrun/cache/artifacts/)
vlmrun chat "<prompt>" -i input.jpg [options]
FlagDescription-p, --promptPrompt text, file path, or stdin-i, --inputInput file(s) - images, videos, docs (repeatable)-o, --outputArtifact directory (default: ~/.vlmrun/cache/artifacts/)-m, --modelvlmrun-orion-1:fast, vlmrun-orion-1:auto (default), vlmrun-orion-1:pro-s, --sessionOptional session ID to continue a previous session-j, --jsonRaw JSON output-ns, --no-streamDisable streaming-nd, --no-downloadSkip artifact download
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
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
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
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
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
# 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
If you want to keep the past conversation and generated artifacts in context, you can use the -s flag to continue a previous session using the session ID generated when you started the session. # Start a new session of an image generation task where a new character is generated vlmrun chat "Create an iconic scene of a ninja in a forest, practicing his skills with a katana?" -i photo.jpg # Use the previous chat session in context to retain the same character and scene context (where the session ID is <session_id>) vlmrun chat "Create a new scene with the same character meditating under a tree" -i photo.jpg -s <session_id>
If you want to skip the artifact download, you can use the -nd flag. vlmrun chat "What objects and people are visible in this image?" -i photo.jpg -nd
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
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