We have a flag to signal we are shortening the embeddings of a model.
Only used in Open AI's text-embedding-3-*, but we plan to use it for other services.
* Use AR model for embeddings features
* endpoints
* Embeddings CRUD UI
* Add presets. Hide a couple more settings
* system specs
* Seed embedding definition from old settings
* Generate search bit index on the fly. cleanup orphaned data
* support for seeded models
* Fix run test for new embedding
* fix selected model not set correctly
Adds a comprehensive quota management system for LLM models that allows:
- Setting per-group (applied per user in the group) token and usage limits with configurable durations
- Tracking and enforcing token/usage limits across user groups
- Quota reset periods (hourly, daily, weekly, or custom)
- Admin UI for managing quotas with real-time updates
This system provides granular control over LLM API usage by allowing admins
to define limits on both total tokens and number of requests per group.
Supports multiple concurrent quotas per model and automatically handles
quota resets.
Co-authored-by: Keegan George <kgeorge13@gmail.com>
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.
- Add spam_score_type to AiSpamSerializer for better integration with reviewables.
- Introduce a custom filter for detecting AI spam false negatives in moderation workflows.
- Refactor spam report generation to improve identification of false negatives.
- Add tests to verify the custom filter and its behavior.
- Introduce links for all spam counts in report
In this PR, we added functionality to hide the admin header for edit/new actions - https://github.com/discourse/discourse/pull/30175
To make it work properly, we have to rename `show` to `edit` which is also a more accurate name.
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
---------
Co-authored-by: Keegan George <kgeorge13@gmail.com>
Co-authored-by: Martin Brennan <martin@discourse.org>
* UX: Improve rough edges of AI usage page
* Ensure all text uses I18n
* Change from <button> usage to <DButton>
* Use <AdminConfigAreaCard> in place of custom card styles
* Format numbers nicely using our number format helper,
show full values on hover using title attr
* Ensure 0 is always shown for counters, instead of being blank
* FEATURE: Load usage data after page load
Use ConditionalLoadingSpinner to hide load of usage
data, this prevents us hanging on page load with a white
screen.
* UX: Split users table, and add empty placeholders and page subheader
* DEV: Test fix
* FEATURE: first class support for OpenRouter
This new implementation supports picking quantization and provider pref
Also:
- Improve logging for summary generation
- Improve error message when contacting LLMs fails
* Better support for full screen artifacts on iPad
Support back button to close full screen
Previously, when clicking add footnote on an explain suggestion it would replace the selected word by finding the first occurrence of the word. This results in issues when there are more than one occurrences of a word in a post. This is not trivial to solve, so this PR instead prevents incorrect text replacements by only allowing the replacement if it's unique. We use the same logic here that we use to determine if something can be fast edited.
In this PR we also update tests for post helper explain suggestions. For a while, we haven't had tests here due to streaming/timing issues, we've been skipping our system specs. In this PR, we add acceptance tests to handle this which gives us improved ability to publish message bus updates in the testing environment so that it can be better tested without issues.
This PR fixes an issue where the tag suggester for edit title topic area was suggesting tags that are already assigned on a post. It also updates the amount of suggested tags to 7 so that there is still a decent amount of tags suggested when tags are already assigned.
Add support for versioned artifacts with improved diff handling
* Add versioned artifacts support allowing artifacts to be updated and tracked
- New `ai_artifact_versions` table to store version history
- Support for updating artifacts through a new `UpdateArtifact` tool
- Add version-aware artifact rendering in posts
- Include change descriptions for version tracking
* Enhance artifact rendering and security
- Add support for module-type scripts and external JS dependencies
- Expand CSP to allow trusted CDN sources (unpkg, cdnjs, jsdelivr, googleapis)
- Improve JavaScript handling in artifacts
* Implement robust diff handling system (this is dormant but ready to use once LLMs catch up)
- Add new DiffUtils module for applying changes to artifacts
- Support for unified diff format with multiple hunks
- Intelligent handling of whitespace and line endings
- Comprehensive error handling for diff operations
* Update routes and UI components
- Add versioned artifact routes
- Update markdown processing for versioned artifacts
Also
- Tweaks summary prompt
- Improves upload support in custom tool to also provide urls
In the tag suggester menu we use `DButton` as a wrapper element and use the `discourseTag` helper to render the text inside the element. So visually there is text content inside the button. However, since `DButton` assumes that no `label`/`translatedLabel` inside an element means `.no-text` CSS style should be applied to the button's element, it was resulting in some incorrect styling being applied to this menu. This PR resolves that by programmatically adding the tag as a `translatedLabel` and then visually hiding it with CSS.
- Added a new admin interface to track AI usage metrics, including tokens, features, and models.
- Introduced a new route `/admin/plugins/discourse-ai/ai-usage` and supporting API endpoint in `AiUsageController`.
- Implemented `AiUsageSerializer` for structuring AI usage data.
- Integrated CSS stylings for charts and tables under `stylesheets/modules/llms/common/usage.scss`.
- Enhanced backend with `AiApiAuditLog` model changes: added `cached_tokens` column (implemented with OpenAI for now) with relevant DB migration and indexing.
- Created `Report` module for efficient aggregation and filtering of AI usage metrics.
- Updated AI Bot title generation logic to log correctly to user vs bot
- Extended test coverage for the new tracking features, ensuring data consistency and access controls.
This commit applies further admin UI guidelines, now that they have been more
fleshed out in core, to the AI admin UI:
* Tools
* LLMs
* Personas
The changes include but are not limited to:
* Applying the table CSS classes, for desktop and mobile
* Adding a description and learn more link for each tab
* Adding an empty list placeholder with CTA using `AdminConfigAreaEmptyList`
* Replacing custom headings with `AdminPageSubheader`
* FIX: Misc fixes for sentiment in the admin dashboard
- Fixes missing filters for the main graph
- Fixes previous 30 days trend in emotion table
Also moves links to individual cells in emotion table, so admins can
drill down to the specific time period on their reports.
* lints
This is a significant PR that introduces AI Artifacts functionality to the discourse-ai plugin along with several other improvements. Here are the key changes:
1. AI Artifacts System:
- Adds a new `AiArtifact` model and database migration
- Allows creation of web artifacts with HTML, CSS, and JavaScript content
- Introduces security settings (`strict`, `lax`, `disabled`) for controlling artifact execution
- Implements artifact rendering in iframes with sandbox protection
- New `CreateArtifact` tool for AI to generate interactive content
2. Tool System Improvements:
- Adds support for partial tool calls, allowing incremental updates during generation
- Better handling of tool call states and progress tracking
- Improved XML tool processing with CDATA support
- Fixes for tool parameter handling and duplicate invocations
3. LLM Provider Updates:
- Updates for Anthropic Claude models with correct token limits
- Adds support for native/XML tool modes in Gemini integration
- Adds new model configurations including Llama 3.1 models
- Improvements to streaming response handling
4. UI Enhancements:
- New artifact viewer component with expand/collapse functionality
- Security controls for artifact execution (click-to-run in strict mode)
- Improved dialog and response handling
- Better error management for tool execution
5. Security Improvements:
- Sandbox controls for artifact execution
- Public/private artifact sharing controls
- Security settings to control artifact behavior
- CSP and frame-options handling for artifacts
6. Technical Improvements:
- Better post streaming implementation
- Improved error handling in completions
- Better memory management for partial tool calls
- Enhanced testing coverage
7. Configuration:
- New site settings for artifact security
- Extended LLM model configurations
- Additional tool configuration options
This PR significantly enhances the plugin's capabilities for generating and displaying interactive content while maintaining security and providing flexible configuration options for administrators.
This re-implements tool support in DiscourseAi::Completions::Llm #generate
Previously tool support was always returned via XML and it would be the responsibility of the caller to parse XML
New implementation has the endpoints return ToolCall objects.
Additionally this simplifies the Llm endpoint interface and gives it more clarity. Llms must implement
decode, decode_chunk (for streaming)
It is the implementers responsibility to figure out how to decode chunks, base no longer implements. To make this easy we ship a flexible json decoder which is easy to wire up.
Also (new)
Better debugging for PMs, we now have a next / previous button to see all the Llm messages associated with a PM
Token accounting is fixed for vllm (we were not correctly counting tokens)
