---
title: "VLM Run integration | Growf"
description: "VLM Run provides multimodal agents, structured extraction, predictions, files, skills, feedback, and evaluation APIs. Connect VLM Run to Growf."
url: "https://www.growf.io/integrations/vlm_run/"
language: "en"
---

Integration / Document & File Management

![VLM Run logo](https://logos.composio.dev/api/vlm_run)

# VLM Run integration

VLM Run provides multimodal agents, structured extraction, predictions, files, skills, feedback, and evaluation APIs.

[Get a demo](https://www.growf.io/demo/)

About VLM Run

## VLM Run is a multimodal AI platform for structured extraction, predictions, files, skills, feedback, and evaluations. It helps teams build reliable vision-language workflows without stitching together model, file, and eval infrastructure by hand.

[All integrations](https://www.growf.io/integrations/)

Category

Document & File Management, AI & Machine Learning

Connection

API key

Type

Tool

Actions

1489

Tags

library

Example prompts

## What you can ask Growf to do with VLM Run

- “Extract invoice fields from uploaded PDFs”

- “Classify product images by defect type”

- “Evaluate extraction quality against gold labels”

Available actions

## 1489 actions your agents can run in VLM Run

- Create Skill  
Create a reusable skill from exactly one uploaded zip, prompt, or chat session.
- Discover Extraction Schemas  
List supported structured-extraction domains, or return the full JSON schema for one domain when domain is provided.
- Execute Agent  
Start a VLM Run agent execution from an existing agent name or inline configuration over multimodal inputs. Execution may consume credits and is asynchronous by default; poll the returned ID with VLM\_RUN\_GET\_RUN.
- Extract Structured JSON  
Start structured JSON extraction from images, a document, a video, or audio using a domain, custom schema, or skill. Extraction may consume credits; document, video, and audio runs are asynchronous by default, so poll the returned prediction ID with VLM\_RUN\_GET\_RUN.
- Find Files  
List uploaded files or find one by file ID or MD5 hash. In list mode, use offset and limit until has\_more is false.
- Find Skills  
List VLM Run skills or find one exact skill by ID, name, and optional version. In list mode, continue from next\_offset while has\_more is true.
- Get Run  
Get the current status and result of one structured-extraction prediction or agent execution; call repeatedly to poll asynchronous work.
- List Agents  
Return agents available to the connected account for selection before execution.
- List Artifacts  
List artifact metadata belonging to exactly one chat session or agent execution. Use offset and limit to traverse pages until has\_more is false.
- List Runs  
List structured-extraction predictions or agent executions for the connected account. Use offset and limit to traverse pages until has\_more is false.
- Upload File  
Upload a local file to VLM Run for extraction, agent input, or skill creation. Retain the returned file ID for tools that consume uploaded files.

## Put VLM Run to work inside Growf.

Connect it once and every workspace, agent and workflow can use it — securely, with your team in the loop.

[Get a demo](https://www.growf.io/demo/)