Instead of a stacked chart showing a separate series for positive and negative, this PR introduces a simplification to the overall sentiment dashboard. It comprises the sentiment into a single series of the difference between `positive - negative` instead. This should allow for the data to be more easy to scan and look for trends.
* 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.
* FEATURE: Backfill posts sentiment.
It adds a scheduled job to backfill posts' sentiment, similar to our existing rake task, but with two settings to control the batch size and posts' max-age.
* Make sure model_name order is consistent.
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
The description of the automatic captions dialog prompt included "Would you like to enable automatic auto captions on image uploads." I removed the second "auto" at the suggestion of translators.
- 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`
* FEATURE: allow mentioning an LLM mid conversation to switch
This is a edgecase feature that allow you to start a conversation
in a PM with LLM1 and then use LLM2 to evaluation or continue
the conversation
* FEATURE: allow auto silencing of spam accounts
New rule can also allow for silencing an account automatically
This can prevent spammers from creating additional posts.
* PERF: Preload only gists when including summaries in topic list
* Add unique index on summaries and dedup existing records
* Make hot topics batch size setting hidden
* FIX: automatically bust cache for share ai assets
CDNs can be configured to strip query params in Discourse
hosting. This is generally safe, but in this case we had
no way of busting the cache using the path.
New design properly caches and properly breaks busts the
cache if asset changes so we don't need to worry about versions
* one day I will set up conditional lint on save :)
* FEATURE: Make emotion /filter ordering match the dashboard table
This change makes the /filter endpoint use the same criteria we use
in the dashboard table for emotion, so it is not confusing for users.
It means that only posts made in the period with the emotion shall be
shown in the /filter, and the order is simply a count of posts that
match the emotion in the period.
It also uses a trick to extract the filter period, and apply it to
the CTE clause that calculates post emotion count on the period, making
it a bit more efficient. Downside is that /filter filters are evaluated
from left to right, so it will only get the speed-up if the emotion
order is last. As we do this on the dashboard table, it should cover
most uses of the ordering, kicking the need for materialized views
down the road.
* Remove zero score in filter
* add table tooltip
* lint
1. Keep source in a "details" block after rendered so it does
not overwhelm users
2. Ensure artifacts are never indexed by robots
3. Cache break our CSS that changed recently
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)
This change introduces a job to summarize topics and cache the results automatically. We provide a setting to control how many topics we'll backfill per hour and what the topic's minimum word count is to qualify.
We'll prioritize topics without summary over outdated ones.
The new `/admin/plugins/discourse-ai/ai-personas/stream-reply.json` was added.
This endpoint streams data direct from a persona and can be used
to access a persona from remote systems leaving a paper trail in
PMs about the conversation that happened
This endpoint is only accessible to admins.
---------
Co-authored-by: Gabriel Grubba <70247653+Grubba27@users.noreply.github.com>
Co-authored-by: Keegan George <kgeorge13@gmail.com>
This changeset contains 4 fixes:
1. We were allowing running tests on unsaved tools,
this is problematic cause uploads are not yet associated or indexed
leading to confusing results. We now only show the test button when
tool is saved.
2. We were not properly scoping rag document fragements, this
meant that personas and ai tools could get results from other
unrelated tools, just to be filtered out later
3. index.search showed options as "optional" but implementation
required the second option
4. When testing tools searching through document fragments was
not working at all cause we did not properly load the tool
* FIX: Llm selector / forced tools / search tool
This fixes a few issues:
1. When search was not finding any semantic results we would break the tool
2. Gemin / Anthropic models did not implement forced tools previously despite it being an API option
3. Mechanics around displaying llm selector were not right. If you disabled LLM selector server side persona PM did not work correctly.
4. Disabling native tools for anthropic model moved out of a site setting. This deliberately does not migrate cause this feature is really rare to need now, people who had it set probably did not need it.
5. Updates anthropic model names to latest release
* linting
* fix a couple of tests I missed
* clean up conditional
A new feature_context json column was added to ai_api_audit_logs
This allows us to store rich json like context on any LLM request
made.
This new field now stores automation id and name.
Additionally allows llm_triage to specify maximum number of tokens
This means that you can limit the cost of llm triage by scanning only
first N tokens of a post.
This changeset:
1. Corrects some issues with "force_default_llm" not applying
2. Expands the LLM list page to show LLM usage
3. Clarifies better what "enabling a bot" on an llm means (you get it in the selector)
* Display gists in the hot topics list
* Adjust hot topics gist strategy and add a job to generate gists
* Replace setting with a configurable batch size
* Avoid loading summaries for other topic lists
* Tweak gist prompt to focus on latest posts in the context of the OP
* Remove serializer hack and rely on core change from discourse/discourse#29291
* Update lib/summarization/strategies/hot_topic_gists.rb
Co-authored-by: Rafael dos Santos Silva <xfalcox@gmail.com>
---------
Co-authored-by: Rafael dos Santos Silva <xfalcox@gmail.com>
Splits persona permissions so you can allow a persona on:
- chat dms
- personal messages
- topic mentions
- chat channels
(any combination is allowed)
Previously we did not have this flexibility.
Additionally, adds the ability to "tether" a language model to a persona so it will always be used by the persona. This allows people to use a cheaper language model for one group of people and more expensive one for other people
This introduces another configuration that allows operators to
limit the amount of interactions with forced tool usage.
Forced tools are very handy in initial llm interactions, but as
conversation progresses they can hinder by slowing down stuff
and adding confusion.
This adds chain halting (ability to terminate llm chain in a tool)
and the ability to create uploads in a tool
Together this lets us integrate custom image generators into a
custom tool.
* FEATURE: allows forced LLM tool use
Sometimes we need to force LLMs to use tools, for example in RAG
like use cases we may want to force an unconditional search.
The new framework allows you backend to force tool usage.
Front end commit to follow
* UI for forcing tools now works, but it does not react right
* fix bugs
* fix tests, this is now ready for review
Previous to this change we could flag, but there was no way
to hide content and treat the flag as spam.
We had the option to hide topics, but this is not desirable for
a spam reply.
New option allows triage to hide a post if it is a reply, if the
post happens to be the first post on the topic, the topic will
be hidden.
This allows custom tools access to uploads and sophisticated searches using embedding.
It introduces:
- A shared front end for listing and uploading files (shared with personas)
- Backend implementation of index.search function within a custom tool.
Custom tools now may search through uploaded files
function invoke(params) {
return index.search(params.query)
}
This means that RAG implementers now may preload tools with knowledge and have high fidelity over
the search.
The search function support
specifying max results
specifying a subset of files to search (from uploads)
Also
- Improved documentation for tools (when creating a tool a preamble explains all the functionality)
- uploads were a bit finicky, fixed an edge case where the UI would not show them as updated
Restructures LLM config page so it is far clearer.
Also corrects bugs around adding LLMs and having LLMs not editable post addition
---------
Co-authored-by: Sam Saffron <sam.saffron@gmail.com>
Previously we had some hardcoded markup with scss making a loading indicator wave. This code was being duplicated and used in both semantic search and summarization. We want to add the indicator wave to the AI helper diff modal as well and have the text flashing instead of the loading spinner. To ensure we do not repeat ourselves, in this PR we turn the summary indicator wave into a reusable template only component called: `AiIndicatorWave`. We then apply the usage of that component to semantic search, summarization, and the composer helper modal.
Previously we had moved the AI helper from the options menu to a selection menu that appears when selecting text in the composer. This had the benefit of making the AI helper a more discoverable feature. Now that some time has passed and the AI helper is more recognized, we will be moving it back to the composer toolbar.
This is better because:
- It consistent with other behavior and ways of accessing tools in the composer
- It has an improved mobile experience
- It reduces unnecessary code and keeps things easier to migrate when we have composer V2.
- It allows for easily triggering AI helper for all content by clicking the button instead of having to select everything.
Previously there was too much work proofreading text, new implementation
provides a single shortcut and easy way of proofreading text.
Co-authored-by: Martin Brennan <martin@discourse.org>
* FEATURE: LLM Triage support for systemless models.
This change adds support for OSS models without support for system messages. LlmTriage's system message field is no longer mandatory. We now send the post contents in a separate user message.
* Models using Ollama can also disable system prompts
New `ai_pm_summarization_allowed_groups` can be used to allow
visibility of the summarization feature on PMs.
This can be useful on forums where a lot of communication happens
inside PMs.
Creating a new model, either manually or from presets, doesn't initialize the `provider_params` object, meaning their custom params won't persist.
Additionally, this change adds some validations for Bedrock params, which are mandatory, and a clear message when a completion fails because we cannot build the URL.
- Validate fields to reduce the chance of breaking features by a misconfigured model.
- Fixed a bug where the URL might get deleted during an update.
- Display a warning when a model is currently in use.
* DEV: Remove old code now that features rely on LlmModels.
* Hide old settings and migrate persona llm overrides
* Remove shadowing special URL + seeding code. Use srv:// prefix instead.
This allows summary to use the new LLM models and migrates of API key based model selection
Claude 3.5 etc... all work now.
---------
Co-authored-by: Roman Rizzi <rizziromanalejandro@gmail.com>
Follow up to b863ddc94b
Ruby:
* Validate `summary` (the column is `not null`)
* Fix `name` validation (the column has `max_length` 100)
* Fix table annotations
* Accept missing `parameter` attributes (`required, `enum`, `enum_values`)
JS:
* Use native classes
* Don't use ember's array extensions
* Add explicit service injections
* Correct class names
* Use `||=` operator
* Use `store` service to create records
* Remove unused service injections
* Extract consts
* Group actions together
* Use `async`/`await`
* Use `withEventValue`
* Sort html attributes
* Use DButtons `@label` arg
* Use `input` elements instead of Ember's `Input` component (same w/ textarea)
* Remove `btn-default` class (automatically applied by DButton)
* Don't mix `I18n.t` and `i18n` in the same template
* Don't track props that aren't used in a template
* Correct invalid `target.value` code
* Remove unused/invalid `this.parameter`/`onChange` code
* Whitespace
* Use the new service import `inject as service` -> `service`
* Use `Object.entries()`
* Add missing i18n strings
* Fix an error in `addEnumValue` (calling `pushObject` on `undefined`)
* Use `TrackedArray`/`TrackedObject`
* Transform tool `parameters` keys (`enumValues` -> `enum_values`)
Introduces custom AI tools functionality.
1. Why it was added:
The PR adds the ability to create, manage, and use custom AI tools within the Discourse AI system. This feature allows for more flexibility and extensibility in the AI capabilities of the platform.
2. What it does:
- Introduces a new `AiTool` model for storing custom AI tools
- Adds CRUD (Create, Read, Update, Delete) operations for AI tools
- Implements a tool runner system for executing custom tool scripts
- Integrates custom tools with existing AI personas
- Provides a user interface for managing custom tools in the admin panel
3. Possible use cases:
- Creating custom tools for specific tasks or integrations (stock quotes, currency conversion etc...)
- Allowing administrators to add new functionalities to AI assistants without modifying core code
- Implementing domain-specific tools for particular communities or industries
4. Code structure:
The PR introduces several new files and modifies existing ones:
a. Models:
- `app/models/ai_tool.rb`: Defines the AiTool model
- `app/serializers/ai_custom_tool_serializer.rb`: Serializer for AI tools
b. Controllers:
- `app/controllers/discourse_ai/admin/ai_tools_controller.rb`: Handles CRUD operations for AI tools
c. Views and Components:
- New Ember.js components for tool management in the admin interface
- Updates to existing AI persona management components to support custom tools
d. Core functionality:
- `lib/ai_bot/tool_runner.rb`: Implements the custom tool execution system
- `lib/ai_bot/tools/custom.rb`: Defines the custom tool class
e. Routes and configurations:
- Updates to route configurations to include new AI tool management pages
f. Migrations:
- `db/migrate/20240618080148_create_ai_tools.rb`: Creates the ai_tools table
g. Tests:
- New test files for AI tool functionality and integration
The PR integrates the custom tools system with the existing AI persona framework, allowing personas to use both built-in and custom tools. It also includes safety measures such as timeouts and HTTP request limits to prevent misuse of custom tools.
Overall, this PR significantly enhances the flexibility and extensibility of the Discourse AI system by allowing administrators to create and manage custom AI tools tailored to their specific needs.
Co-authored-by: Martin Brennan <martin@discourse.org>
Previously, we stored request parameters like the OpenAI organization and Bedrock's access key and region as site settings. This change stores them in the `llm_models` table instead, letting us drop more settings while also becoming more flexible.
* FEATURE: LLM presets for model creation
Previous to this users needed to look up complicated settings
when setting up models.
This introduces and extensible preset system with Google/OpenAI/Anthropic
presets.
This will cover all the most common LLMs, we can always add more as
we go.
Additionally:
- Proper support for Anthropic Claude Sonnet 3.5
- Stop blurring api keys when navigating away - this made it very complex to reuse keys
Previously read tool only had access to public topics, this allows
access to all topics user has access to, if admin opts for the option
Also
- Fixes VLLM migration
- Display which llms have bot enabled
* DRAFT: Create AI Bot users dynamically and support custom LlmModels
* Get user associated to llm_model
* Track enabled bots with attribute
* Don't store bot username. Minor touches to migrate default values in settings
* Handle scenario where vLLM uses a SRV record
* Made 3.5-turbo-16k the default version so we can remove hack
This is a rather huge refactor with 1 new feature (tool details can
be suppressed)
Previously we use the name "Command" to describe "Tools", this unifies
all the internal language and simplifies the code.
We also amended the persona UI to use less DToggles which aligns
with our design guidelines.
Co-authored-by: Martin Brennan <martin@discourse.org>
Native tools do not work well on Opus.
Chain of Thought prompting means it consumes enormous amounts of
tokens and has poor latency.
This commit introduce and XML stripper to remove various chain of
thought XML islands from anthropic prompts when tools are involved.
This mean Opus native tools is now functions (albeit slowly)
From local testing XML just works better now.
Also fixes enum support in Anthropic native tools
1. New tool to easily find files (and default branch) in a Github repo
2. Improved read tool with clearer params and larger context
* limit can totally mess up the richness semantic search adds, so include the results unconditionally.
Initial implementation allowed internet wide sharing of
AI conversations, on sites that require login.
This feature can be an anti feature for private sites cause they
can not share conversations internally.
For now we are removing support for public sharing on login required
sites, if the community need the feature we can consider adding a
setting.
Previoulsy on GPT-4-vision was supported, change introduces support
for Google/Anthropic and new OpenAI models
Additionally this makes vision work properly in dev environments
cause we sent the encoded payload via prompt vs sending urls
This change allows us to delete custom models. It checks if there is no module using them.
It also fixes a bug where the after-create transition wasn't working. While this prevents a model from being saved multiple times, endpoint validations are still needed (will be added in a separate PR).:
This is similar to code interpreter by ChatGPT, except that it uses
JavaScript as the execution engine.
Safeguards were added to ensure memory is constrained and evaluation
times out.
* FEATURE: Set endpoint credentials directly from LlmModel.
Drop Llama2Tokenizer since we no longer use it.
* Allow http for custom LLMs
---------
Co-authored-by: Rafael Silva <xfalcox@gmail.com>
- a post can be triaged a maximum of twice a minute
- system can run a total of 60 triages a minute
Low defaults were picked to safeguard against any possible loops
This can be amended if required via hidden site settings.
- Introduce new support for GPT4o (automation / bot / summary / helper)
- Properly account for token counts on OpenAI models
- Track feature that was used when generating AI completions
- Remove custom llm support for summarization as we need better interfaces to control registration and de-registration
There are still some limitations to which models we can support with the `LlmModel` class. This will enable support for Llama3 while we sort those out.
This PR introduces the concept of "LlmModel" as a new way to quickly add new LLM models without making any code changes. We are releasing this first version and will add incremental improvements, so expect changes.
The AI Bot can't fully take advantage of this feature as users are hard-coded. We'll fix this in a separate PR.s
This optional feature allows search to be performed in the context
of the user that executed it.
By default we do not allow this behavior cause it means llm gets
access to potentially secure data.
Both endpoints provide OpenAI-compatible servers. The only difference is that Vllm doesn't support passing tools as a separate parameter. Even if the tool param is supported, it ultimately relies on the model's ability to handle native functions, which is not the case with the models we have today.
As a part of this change, we are dropping support for StableBeluga/Llama2 models. They don't have a chat_template, meaning the new API can translate them.
These changes let us remove some of our existing dialects and are a first step in our plan to support any LLM by defining them as data-driven concepts.
I rewrote the "translate" method to use a template method and extracted the tool support strategies into its classes to simplify the code.
Finally, these changes bring support for Ollama when running in dev mode. It only works with Mistral for now, but it will change soon..
Discourse Translator Bot
Keegan George
Sam
Roman Rizzi
Tobias Eigen
Rafael dos Santos Silva
Martin Brennan
Kris
Hoa Nguyen
chapoi
Jarek Radosz
Ted Johansson