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Analyze Mattermost attachments with OpenAI vision for AI agents

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Created by: Sergei Byvshev || javdet
Sergei Byvshev

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Last update 2 months ago

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Overview

Subworkflow for analyzing Mattermost attachments.

Per-attachment behavior

  • Image (mime starts with image/, size ≤ MAX_IMAGE_SIZE_BYTES): downloaded and analyzed by OpenAI vision model.
  • Text small (text-like by mime/extension, size ≤ MAX_TEXT_SIZE_BYTES): downloaded as plain text and inlined into the context block (with line count check ≤ MAX_TEXT_LINES).
  • Text too large (text-like, exceeds byte or line limit): replaced with a "too big" marker so the agent asks the user for the relevant excerpt.
  • Other (binaries, oversized images, unknown): replaced with a generic "not analyzed" marker.

Setup checklist

  1. Set MATTERMOST_BASE_URL in the Config node.
  2. Create an HTTP Header Auth credential called "Mattermost PAT" with:
    • Name: Authorization
    • Value: Bearer <your_personal_access_token>
  3. Attach this credential to all three HTTP Request nodes (Get file info, Download file, Download text file).
  4. Attach your OpenAI credential to the "OpenAI: Analyze Image" node.
  5. Tune in Config: VISION_MODEL, MAX_IMAGE_SIZE_BYTES, MAX_TEXT_SIZE_BYTES, MAX_TEXT_LINES.

Notes

  • The IF guard short-circuits when file_ids is empty so the parent workflow can call this subworkflow unconditionally.
  • Classification by mime + extension catches .log files served as application/octet-stream.
  • Final output is always a single item with the same shape — safe to consume in the parent.