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Usage dashboard

Component: local_ragflowdashboard · Release: 0.5.3 · Requires: Moodle 5.0–5.2 · Depends on: aiprovider_ragflow

An admin-only report that visualises how the suite is used: request volume, success/failure rates, latency and error breakdowns — plus an optional per-feature debug capture for diagnosis. It observes the provider's usage events, so it is entirely optional and harmless if not installed. It also ships rfdsource_* sub-plugins that give each feature its own dashboard section.

Features

  • Dashboard page at Site administration → Reports → RAGflow Dashboard, with a view selector ("All features" + one per installed source) and a period selector (7 / 14 / 30 / 90 days, default 30). Controls reload the view over AJAX.
  • KPI cards: Requests, Success rate (%), Failures, Average latency (ms).
  • Charts: requests per day (successful vs failed), requests by feature (global view), and failures by error type (labelled, e.g. RAGflow server error (5xx), Query too long for embedding model, Rate limited).
  • Recent-errors table: most recent failures (50 global / 20 per feature) — time, feature, action, error type, latency.
  • Usage log — metrics only: every usage event is stored without message content (safe for the standard log store).
  • Per-feature debug capture — content: when an admin enables debug for a feature, the bounded request/response (question + answer/error, including the technical cause) is stored in a dashboard-owned, admin-only table and shown as a "Debug captures" table. Enable it only while diagnosing.
  • XML export of the usage log (metrics only) for a date range, scoped to the current view.
  • Retention/purge task (daily) removes log and debug rows older than the retention period.
  • Anonymisation option stores rows without a user link (aggregate stats still work).

Configuration

Admin settings — Site administration → Plugins → Local plugins → RAGflow Dashboard settings

Setting Type Default Meaning
Log retention (days) (retentiondays) integer 90 Delete log entries older than this many days. 0 = keep indefinitely.
Anonymise log data (anonymize) checkbox off Store no user link (user id 0). Aggregate stats still work; per-user analysis / privacy export do not.
Debug content limit (characters) (detailmaxlen) integer 2000 Max characters stored per captured question and response.
Per-feature debug mode (heading) When enabled for a feature, the (bounded) request/response content is stored for troubleshooting — this captures user messages and answers, so enable only temporarily and mind data protection.
Debug: {feature} (debug_<component>) checkbox off One toggle per feature owned by an installed source (Tutor / Helpdesk / Search, and any future rfdsource_*). When on, that feature's request/response content is captured.

Capabilities

Capability Default roles Purpose
local/ragflowdashboard:view Manager (admin report) View the dashboard, logs, debug captures and export. Intentionally not granted to teaching roles, since the data reveals usage patterns.

Data model

  • local_ragflowdashboard_log — one row per usage event, metrics only: time, component, action, user id, course id, context id, success, error type, latency (ms), item count. Never stores content.
  • local_ragflowdashboard_debug — request/response content (question + response), written only while a feature's debug toggle is on, truncated to the debug content limit. Written directly (never via events), so content never reaches the standard log store.

Sub-plugins (rfdsource_*)

Each RAGflow feature contributes a dashboard section as a sub-plugin, shipped inside the dashboard package: RAGflow Tutor (rfdsource_tutor), RAGflow Helpdesk (rfdsource_helpdesk), RAGflow Search (rfdsource_search). Installing another rfdsource_* adds its section and debug toggle automatically.

Privacy

The dashboard stores usage metrics and (only while debug is enabled) bounded request/response content, with full privacy export/deletion support. With anonymise on, rows carry no user link. Retention purges old rows automatically.


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.