5 Commits

Author SHA1 Message Date
Keegan George
9be1049de6
DEV: Log AI related configuration to staff action log (#1416)
is update adds logging for changes made in the AI admin panel. When making configuration changes to Embeddings, LLMs, Personas, Tools, or Spam that aren't site setting related, changes will now be logged in Admin > Logs & Screening. This will help admins debug issues related to AI. In this update a helper lib is created called `AiStaffActionLogger` which can be easily used in the future to add logging support for any other admin config we need logged for AI.
2025-06-12 12:39:58 -07:00
Keegan George
d99c335dab
DEV: Ensure enabling/disabling spam is set and logged (#1378)
Since we enable/disable `ai_spam_detection_enabled` setting in a custom Spam tab UI in AI, we want to ensure we retain the setting and logging features. To preserve that, we want to update the controller to use `SiteSetting.set_and_log` instead of setting the value directly.
2025-05-28 10:12:21 -07:00
Keegan George
b24669c810
DEV: Add structure for errors in spam (#1054)
This update adds some structure for handling errors in the spam config while also handling a specific error related to the spam scanning user not being an admin account.
2025-01-09 09:17:06 -08:00
Keegan George
24b69bf840
FIX: Update spam controller action should consider seeded LLM properly (#1053)
The seeded LLM setting: `SiteSetting.ai_spam_detection_model_allowed_seeded_models` returns a _string_ with IDs separated by pipes. running `_map` on it will return an array with strings. We were previously checking for the id with custom prefix identifier, but instead we should be checking the stringified ID.
2025-01-08 13:41:25 -08:00
Sam
47f5da7e42
FEATURE: Add AI-powered spam detection for new user posts (#1004)
This introduces a comprehensive spam detection system that uses LLM models
to automatically identify and flag potential spam posts. The system is
designed to be both powerful and configurable while preventing false positives.

Key Features:
* Automatically scans first 3 posts from new users (TL0/TL1)
* Creates dedicated AI flagging user to distinguish from system flags
* Tracks false positives/negatives for quality monitoring
* Supports custom instructions to fine-tune detection
* Includes test interface for trying detection on any post

Technical Implementation:
* New database tables:
  - ai_spam_logs: Stores scan history and results
  - ai_moderation_settings: Stores LLM config and custom instructions
* Rate limiting and safeguards:
  - Minimum 10-minute delay between rescans
  - Only scans significant edits (>10 char difference)
  - Maximum 3 scans per post
  - 24-hour maximum age for scannable posts
* Admin UI features:
  - Real-time testing capabilities
  - 7-day statistics dashboard
  - Configurable LLM model selection
  - Custom instruction support

Security and Performance:
* Respects trust levels - only scans TL0/TL1 users
* Skips private messages entirely
* Stops scanning users after 3 successful public posts
* Includes comprehensive test coverage
* Maintains audit log of all scan attempts


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Co-authored-by: Keegan George <kgeorge13@gmail.com>
Co-authored-by: Martin Brennan <martin@discourse.org>
2024-12-12 09:17:25 +11:00