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.
In hybrid mode ai artifacts can optionally automatically run.
This is useful for cases where you may want to embed a survey and so on.
Additionally, artifacts now allow for better fidelity around display:
<div class="ai-artifact" data-ai-artifact-id="501" data-ai-artifact-height="300px" data-ai-artifact-autorun data-ai-artifact-seamless></div>
User can supply height and seamless mode to be seamlessly rendered with no box shadow and show full screen button.
Previously we had a logic error and were showing admins keys
that are not theirs when querying for all keys
This makes the API cleaner, to get all results you need to be explicit always
Introduces a persistent, user-scoped key-value storage system for
AI Artifacts, enabling them to be stateful and interactive. This
transforms artifacts from static content into mini-applications that can
save user input, preferences, and other data.
The core components of this feature are:
1. **Model and API**:
- A new `AiArtifactKeyValue` model and corresponding database table to
store data associated with a user and an artifact.
- A new `ArtifactKeyValuesController` provides a RESTful API for
CRUD operations (`index`, `set`, `destroy`) on the key-value data.
- Permissions are enforced: users can only modify their own data but
can view public data from other users.
2. **Secure JavaScript Bridge**:
- A `postMessage` communication bridge is established between the
sandboxed artifact `iframe` and the parent Discourse window.
- A JavaScript API is exposed to the artifact as `window.discourseArtifact`
with async methods: `get(key)`, `set(key, value, options)`,
`delete(key)`, and `index(filter)`.
- The parent window handles these requests, makes authenticated calls to the
new controller, and returns the results to the iframe. This ensures
security by keeping untrusted JS isolated.
3. **AI Tool Integration**:
- The `create_artifact` tool is updated with a `requires_storage`
boolean parameter.
- If an artifact requires storage, its metadata is flagged, and the
system prompt for the code-generating AI is augmented with detailed
documentation for the new storage API.
4. **Configuration**:
- Adds hidden site settings `ai_artifact_kv_value_max_length` and
`ai_artifact_max_keys_per_user_per_artifact` for throttling.
This also includes a minor fix to use `jsonb_set` when updating
artifact metadata, ensuring other metadata fields are preserved.
Additional changes:
Adds a "#features" method in AiPersona to find which features are using that persona.
Serializes a basic version of a LlmModel in the persona's "#default_llm" serializer attribute.
* FEATURE: Display features that rely on multiple personas.
This change makes the previously hidden feature page visible while displaying features, like the AI helper, which relies on multiple personas.
* Fix system specs
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.
* FIX: Improve MessageBus efficiency and correctly stop streaming
This commit enhances the message bus implementation for AI helper streaming by:
- Adding client_id targeting for message bus publications to ensure only the requesting client receives streaming updates
- Limiting MessageBus backlog size (2) and age (60 seconds) to prevent Redis bloat
- Replacing clearTimeout with Ember's cancel method for proper runloop management, we were leaking a stop
- Adding tests for client-specific message delivery
These changes improve memory usage and make streaming more reliable by ensuring messages are properly directed to the requesting client.
* composer suggestion needed a fix as well.
* backlog size of 2 is risky here cause same channel name is reused between clients
Also allow artifact access to current username
Usage inside artifact is:
1. await window.discourseArtifactReady;
2. access data via window.discourseArtifactData;
AI share page assets are loaded via the app CDN, which means the requests have no authentication and will never appear to the app as "logged in". Therefore we should skip the `redirect_to_login_if_required` before_action.
Examples simulate previous interactions with an LLM and come
right after the system prompt. This helps grounding the model and
producing better responses.
* DEV: Use structured responses for summaries
* Fix system specs
* Make response_format a first class citizen and update endpoints to support it
* Response format can be specified in the persona
* lint
* switch to jsonb and make column nullable
* Reify structured output chunks. Move JSON parsing to the depths of Completion
* Switch to JsonStreamingTracker for partial JSON parsing
Invalid access error should be populated to user when trying to search for something they do not have permissions for (i.e. anons searching `in:messages`
# Preview
https://github.com/user-attachments/assets/3fe3ac8f-c938-4df4-9afe-11980046944d
# Details
- Group pms by `last_posted_at`. In this first iteration we are group by `7 days`, `30 days`, then by month beyond that.
- I inject a sidebar section link with the relative (last_posted_at) date and then update a tracked value to ensure we don't do it again. Then for each month beyond the first 30days, I add a value to the `loadedMonthLabels` set and we reference that (plus the year) to see if we need to load a new month label.
- I took the creative liberty to remove the `Conversations` section label - this had no purpose
- I hid the _collapse all sidebar sections_ carrot. This had no purpose.
- Swap `BasicTopicSerializer` to `ListableTopicSerializer` to get access to `last_posted_at`
In the last commit, I introduced a topic_custom_field to determine if a PM is indeed a bot PM.
This commit adds a migration to backfill any PM that is between 1 real user, and 1 bot. The correct topic_custom_field is added for these, so they will appear on the bot conversation sidebar properly.
We can also drop the joining to topic_users in the controller for sidebar conversations, and the isPostFromAiBot logic from the sidebar.
Overview
This PR introduces a Bot Homepage that was first introduced at https://ask.discourse.org/.
Key Features:
Add a bot homepage: /discourse-ai/ai-bot/conversations
Display a sidebar with previous bot conversations
Infinite scroll for large counts
Sidebar still visible when navigation mode is header_dropdown
Sidebar visible on homepage and bot PM show view
Add New Question button to the bottom of sidebar on bot PM show view
Add persona picker to homepage
This update adds metrics for estimated spending in AI usage. To make use of it, admins must add cost details to the LLM config page (input, output, and cached input costs per 1M tokens). After doing so, the metrics will appear in the AI usage dashboard as the AI plugin is used.
### 🔍 Overview
This update performs some enhancements to the LLM configuration screen. In particular, it renames the UI for the number of tokens for the prompt to "Context window" since the naming can be confusing to the user. Additionally, it adds a new optional field called "Max output tokens".
In this feature update, we add the UI for the ability to easily configure persona backed AI-features. The feature will still be hidden until structured responses are complete.
* REFACTOR: Move personas into it's own module.
* WIP: Use personas for summarization
* Prioritize persona default LLM or fallback to newest one
* Simplify summarization strategy
* Keep ai_sumarization_model as a fallback
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 change moves all the personas code into its own module. We want to treat them as a building block features can built on top of, same as `Completions::Llm`.
The code to title a message was moved from `Bot` to `Playground`.
* DEV: refactor bot internals
This introduces a proper object for bot context, this makes
it simpler to improve context management as we go cause we
have a nice object to work with
Starts refactoring allowing for a single message to have
multiple uploads throughout
* transplant method to message builder
* chipping away at inline uploads
* image support is improved but not fully fixed yet
partially working in anthropic, still got quite a few dialects to go
* open ai and claude are now working
* Gemini is now working as well
* fix nova
* more dialects...
* fix ollama
* fix specs
* update artifact fixed
* more tests
* spam scanner
* pass more specs
* bunch of specs improved
* more bug fixes.
* all the rest of the tests are working
* improve tests coverage and ensure custom tools are aware of new context object
* tests are working, but we need more tests
* resolve merge conflict
* new preamble and expanded specs on ai tool
* remove concept of "standalone tools"
This is no longer needed, we can set custom raw, tool details are injected into tool calls
This PR ensures that the category badges are present in the sentiment analysis report. Since the core change in https://github.com/discourse/discourse/pull/31795, there was a regression in the post list drill-down where category badges were not being shown. This PR fixes that and also ensures icons/emojis are shown when categories make use of them. This PR also adds the category badge in the table list.
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.
Keegan George
Kris
Sam
Roman Rizzi
Roman Rizzi
David Taylor
Isaac Janzen
Mark VanLandingham