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Integratie / Document & File Management

VLM Run integratie

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

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Over 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.

Alle integraties
Categorie
Document & File Management, AI & Machine Learning
Verbinding
API-sleutel
Type
Tool
Acties
11
Tags
library

Voorbeeldprompts

Wat je Growf kunt vragen te doen met VLM Run

  • “Extract invoice fields from uploaded PDFs”
  • “Classify product images by defect type”
  • “Evaluate extraction quality against gold labels”

Beschikbare acties

11 acties die je agents kunnen uitvoeren 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.

Zet VLM Run aan het werk in Growf.

Koppel het één keer en elke workspace, agent en workflow kan het gebruiken — veilig, met je team in de loop.

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