This update fixes an issue where the AI user preferences tab was not appearing unless `SiteSetting.ai_helper_enabled` was `true`. This is because we previously checked for it's presence when user preferences only had a single setting related to Helper. However, since then, we've also added search discoveries setting there too. As such, we don't want it to depend on Helper. We also sneak in this update a modernization of converting the preferences template from `.hbs` to `.gjs`.
The current menu was rendering inside the post text toolbar (on desktop). This is not ideal as the post text toolbar rendering is conditioned on the presence of text selection, when you click a button on the toolbar, by design of the web browsers you will lose your text selection, making all of this super tricky.
This commit makes desktop and mobile behave in the same way by rendering their own menu and capturing the quote state when we render the post text selection toolbar, this allows us to reason a much simpler way about the AI helper.
This commit also removes what appears to be an unused file and corrects which was seemingly copy/paste mistakes.
⚠️ Technical note, this commit is correcting the message bus subscription which amongst other things allows to write specs which are not flaky. However due to the current implementation we have a channel per post, which means we need to serialize on last message bus id per post.
We have two possible solutions here:
- subscribe at the topic level
- refactor the code to be able to use `MessageBus.last_ids` to be able to grab multiple posts at once instead of having to call `MessageBus.last_id` and done one Redis call per post
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Co-authored-by: Keegan George <[email protected]>
## 🔍 Overview
When you have a post with audio being played and you open and close the AI post helper menu, it re-renders the entire post DOM, causing the audio to be interrupted and stop playing.
The reason for this is because we highlight the selected text when opening the AI post helper menu and we replace the entire post back with the original post HTML when closing the menu. This fix ensures that we do not re-render the entire post DOM and instead only remove the highlighted section that was added.
## 🔗 Context
https://meta.discourse.org/t/ai-helper-interrupting-uploaded-mp3-audio-stream/366817?u=keegan
We were getting an error in this logic causing Ember to fail to render the non-bot-topic that we navigate to.
I believe this is because the getter of participants is re-calculating (due to this.header.topicInfo being updated) before the args to this connector changes. Adding some safe navigation here fixes the issue.
This feature update allows for continuing the conversation with Discobot Discoveries in an AI bot chat. After discoveries gives you a response to your search you can continue with the existing context.
**This update makes a few improvements to search discoveries:**
- [x] in search menu panel: search discoveries should still be triggered when no regular results are present
- [x] in full page search: search discoveries should still be triggered when no regular results are present
- [x] flakiness in search discoveries sometimes not working properly.
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Co-authored-by: awesomerobot <[email protected]>
When editing a topic (instead of creating one) and using the
tag/category suggestion buttons. We want to use existing topic
embeddings instead of creating new ones.
This update adds the ability to disable search discoveries. This can be done through a tooltip when search discoveries are shown. It can also be done in the AI user preferences, which has also been updated to accommodate more than just the one image caption setting.
adds support for "thinking tokens" - a feature that exposes the model's reasoning process before providing the final response. Key improvements include:
- Add a new Thinking class to handle thinking content from LLMs
- Modify endpoints (Claude, AWS Bedrock) to handle thinking output
- Update AI bot to display thinking in collapsible details section
- Fix SEARCH/REPLACE blocks to support empty replacement strings and general improvements to artifact editing
- Allow configurable temperature in triage and report automations
- Various bug fixes and improvements to diff parsing
## 🔍 Overview
This update ensures that the streaming for discoveries is smoother, especially on first update.
## ➕ More details
To help with smoother streaming, the discovery preview (which was being tracked as a separate property in the JS logic) will be removed and the entire discovery content will be shown/hidden via the existing CSS. The preview was already receiving the full update even though it was visually hidden, so removing the separate property shouldn't have any negative performance hit. Visually hiding it with CSS only will help simplify the component and also allow for smoother streaming. We will instead remove the buffered streaming approach and instead use typing timers similar to what we did for streaming summarization.
No related tests as streaming animations are difficult to test.
* FEATURE: Experimental search results from an AI Persona.
When a user searches discourse, we'll send the query to an AI Persona to provide additional context and enrich the results. The feature depends on the user being a member of a group to which the persona has access.
* Update assets/stylesheets/common/ai-blinking-animation.scss
Co-authored-by: Keegan George <[email protected]>
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Co-authored-by: Keegan George <[email protected]>
* DEV: raise timeout for reasoning LLMs
* FIX: use id to identify llms, not model_name
model_name is not unique, in the case of reasoning models
you may configure the same llm multiple times using different
reasoning levels.
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 <[email protected]>
Keegan George
Joffrey JAFFEUXandKeegan George
Roman Rizzi
Alan Guo Xiang Tan
David Taylor
Mark VanLandingham
Kris
Jarek Radosz
Sam
Roman Rizzi
Rafael dos Santos Silva