This update adds a safety checker which scans the streamed updates. It ensures that incomplete segments of text are not sent yet over message bus as this will cause breakage with the diff streamer. It also updates the diff streamer to handle a thinking state for when we are waiting for message bus updates.
This change fixes two bugs and adds a safeguard.
The first issue is that the schema Gemini expected differed from the one sent, resulting in 400 errors when performing completions.
The second issue was that creating a new persona won't define a method
for `response_format`. This has to be explicitly defined when we wrap it inside the Persona class. Also, There was a mismatch between the default value and what we stored in the DB. Some parts of the code expected symbols as keys and others as strings.
Finally, we add a safeguard when, even if asked to, the model refuses to reply with a valid JSON. In this case, we are making a best-effort to recover and stream the raw response.
* FEATURE: allow researcher to also research specific topics
Also improve UI around research with more accurate info
* this ensures that under no conditions PMs will be included
* DEV: use a proper object for tool definition
This moves away from using a loose hash to define tools, which
is error prone.
Instead given a proper object we will also be able to coerce the
return values to match tool definition correctly
* fix xml tools
* fix anthropic tools
* fix specs... a few more to go
* specs are passing
* FIX: coerce values for XML tool calls
* Update spec/lib/completions/tool_definition_spec.rb
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit introduces a new Forum Researcher persona specialized in deep forum content analysis along with comprehensive improvements to our AI infrastructure.
Key additions:
New Forum Researcher persona with advanced filtering and analysis capabilities
Robust filtering system supporting tags, categories, dates, users, and keywords
LLM formatter to efficiently process and chunk research results
Infrastructure improvements:
Implemented CancelManager class to centrally manage AI completion cancellations
Replaced callback-based cancellation with a more robust pattern
Added systematic cancellation monitoring with callbacks
Other improvements:
Added configurable default_enabled flag to control which personas are enabled by default
Updated translation strings for the new researcher functionality
Added comprehensive specs for the new components
Renames Researcher -> Web Researcher
This change makes our AI platform more stable while adding powerful research capabilities that can analyze forum trends and surface relevant content.
Examples simulate previous interactions with an LLM and come
right after the system prompt. This helps grounding the model and
producing better responses.
We were logging persona triage as "bot" in logs, causing some
confusions around real world usage
This amends it so we log usage to "automation - AUTOMATION NAME"
* 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
This ensures webp / gif are converted to png prior to sending
to LLMs given webp and gif are not evenly supported.
png/jpg is universally supported and are the only supported format.
longer term we need to add support for audio/video/pdf which is supported by some models.
* more specs
System personas leaned on reused classes, this was a problem
in a multisite environement cause state, such as "enabled"
ended up being reused between sites.
New implementation ensures state is pristine between sites in
a multisite
* more handling for new superclass story
* small oversight, display name should be used for display
AI bots come in 2 flavors
1. An LLM and LLM user, in this case we should decorate posts with persona name
2. A Persona user, in this case, in PMs we decorate with LLM name
(2) is a significant improvement, cause previously when creating a conversation
you could not tell which LLM you were talking to by simply looking at the post, you would
have to scroll to the top of the page.
* lint
* translation missing
This commit enhances the AI image generation functionality by adding support for:
1. OpenAI's GPT-based image generation model (gpt-image-1)
2. Image editing capabilities through the OpenAI API
3. A new "Designer" persona specialized in image generation and editing
4. Two new AI tools: CreateImage and EditImage
Technical changes include:
- Renaming `ai_openai_dall_e_3_url` to `ai_openai_image_generation_url` with a migration
- Adding `ai_openai_image_edit_url` setting for the image edit API endpoint
- Refactoring image generation code to handle both DALL-E and the newer GPT models
- Supporting multipart/form-data for image editing requests
* wild guess but maybe quantization is breaking the test sometimes
this increases distance
* Update lib/personas/designer.rb
Co-authored-by: Alan Guo Xiang Tan <gxtan1990@gmail.com>
* simplify and de-flake code
* fix, in chat we need enough context so we know exactly what uploads a user uploaded.
* Update lib/personas/tools/edit_image.rb
Co-authored-by: Alan Guo Xiang Tan <gxtan1990@gmail.com>
* cleanup downloaded files right away
* fix implementation
---------
Co-authored-by: Alan Guo Xiang Tan <gxtan1990@gmail.com>
* FEATURE: display more places where AI is used
- Usage was not showing automation or image caption in llm list.
- Also: FIX - reasoning models would time out incorrectly after 60 seconds (raised to 10 minutes)
* correct enum not to enumerate non configured models
* FEATURE: implement chat streamer
This implements a basic chat streamer, it provides 2 things:
1. Gives feedback to the user when LLM is generating
2. Streams stuff much more efficiently to client (given it may take 100ms or so per call to update chat)
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.
* FEATURE: Update model names and specs
- not a bug, but made it explicit that tools and thinking are not a chat thing
- updated all models to latest in presets (Gemini and OpenAI)
* allow larger context windows
1. Add age of post to topic context (1 month ago, 1 year ago, etc)
2. Refactor code for simplicity
3. Fix handling of post context in DMs which was not using new handling of uploads
Previous to this fix we assumed the name field contained usernames
when in fact it was stored in the id field.
This fixes the context contruction and also adds some basic user
information to the context to assist responders in understanding
the cast of chars
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.
Add API methods to AI tools for reading and updating personas, enabling
more flexible AI workflows. This allows custom tools to:
- Fetch persona information through discourse.getPersona()
- Update personas with modified settings via discourse.updatePersona()
- Also update using persona.update()
These APIs enable new use cases like "trainable" moderation bots, where
users with appropriate permissions can set and refine moderation rules
through direct chat interactions, without needing admin panel access.
Also adds a special API scope which allows people to lean on API
for similar actions
Additionally adds a rather powerful hidden feature can allow custom tools
to inject content into the context unconditionally it can be used for memory and similar features
Previously, allowing "everyone" to access gists meant anons would see them too.
With the move to Personas, we used "[]" to reflect that.
With discourse/discourse#32199 adding the "everyone" option to the personas-allowed
groups, we are switching back to the original behavior.
Leaving allowed groups empty should always mean nobody can use the feature.
* 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 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.
This PR adds support for disabling further tool calls by setting tool_choice to :none across all supported LLM providers:
- OpenAI: Uses "none" tool_choice parameter
- Anthropic: Uses {type: "none"} and adds a prefill message to prevent confusion
- Gemini: Sets function_calling_config mode to "NONE"
- AWS Bedrock: Doesn't natively support tool disabling, so adds a prefill message
We previously used to disable tool calls by simply removing tool definitions, but this would cause errors with some providers. This implementation uses the supported method appropriate for each provider while providing a fallback for Bedrock.
Co-authored-by: Natalie Tay <natalie.tay@gmail.com>
* remove stray puts
* cleaner chain breaker for last tool call (works in thinking)
remove unused code
* improve test
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Co-authored-by: Natalie Tay <natalie.tay@gmail.com>
Keegan George
Roman Rizzi
Sam
Rafael dos Santos Silva
Mark VanLandingham
Natalie Tay
Régis Hanol
Alan Guo Xiang Tan