Analyze Mattermost attachments with OpenAI vision for AI agents

Description

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