Skip to content

Professional services

Need expert help? RAGcon GmbH offers:

  • RAGflow Support
  • RAGflow Hosting
  • Moodle Support
Talk to RAGcon GmbH →

Using it with the Moodle RAGflow Suite

The connector and the Moodle RAGflow Suite are separate products that fit together well: the connector fills a RAGflow knowledge base from Moodle, and the suite's plugins (Tutor, Search, Helpdesk) query that knowledge base from inside Moodle.

You do not need one to use the other — but combined, they give a course a tutor/search grounded in the course's own Moodle material, kept up to date automatically.

Course-scoped answers

Each connector document carries course_id and moodle_url in its metadata (see Content & metadata). That is exactly what the suite's document source → Moodle Connector option filters on:

  • In the Tutor or Search block (or a provider action), choose the Moodle Connector / This Moodle document source. The plugin then restricts retrieval to documents whose course_id matches the current course and whose moodle_url matches the site.
  • The result: a block placed in a course answers only from that course's synced material, without a per-course knowledge base — one connector-filled knowledge base can serve every course.

So the typical pairing is:

  1. Connector → sync the whole Moodle site into one RAGflow knowledge base.
  2. Suite → point the Tutor/Search blocks at that knowledge base with the Moodle Connector source, and each course automatically scopes to its own content.

A note on external sharing

The suite also offers an External sharing document source (documents flagged external_sharing = 1). The connector does not set that flag — it writes course_id / moodle_url but not external_sharing. If you want to use the external-sharing scope, that metadata has to be provided another way; the connector alone enables the course scope, not the external-sharing scope.

Which knowledge base?

Point the connector at the same knowledge base the plugins read from. The plugins select a knowledge base (dataset) by id; the connector fills that dataset. Keep the embedding model consistent — a knowledge base's embedding model is fixed at creation, so decide it before the first sync.

See the suite docs for the plugin side: AI provider · Tutor · Search.


Note: This documentation was created with the help of AI. Spotted an error, an omission, or something unclear? Please report it in the ragcon-docs GitHub repository so we can fix it.