- 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.
* 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 :)
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.
* 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>
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Co-authored-by: Rafael dos Santos Silva <xfalcox@gmail.com>
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.
* 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.
* Seeding the SRV-backed model should happen inside an initializer.
* Keep the model up to date when the hidden setting changes.
* Use the correct Mixtral model name and fix previous data migration.
* URL validation should trigger only when we attempt to update it.
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>
* 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 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
* Well, it was quite a journey but now tools have "context" which
can be critical for the stuff they generate
This entire change was so Dall E and Artist generate images in the correct context
* FIX: improve error handling around image generation
- also corrects image markdown and clarifies code
* fix spec
This commit uses a new plugin modifier introduced in https://github.com/discourse/discourse/pull/26508
to mark all uploads as _not_ secure in shared PM AI conversations.
This is so images created by the AI bot (or uploaded by the user)
do not end up as broken URLs because of the security requirements
around them.
This relies on the UpdateTopicUploadSecurity job in core as well,
which is fired when an AI conversation is shared or deleted.
* FEATURE: Add metadata support for RAG
You may include non indexed metadata in the RAG document by using
[[metadata ....]]
This information is attached to all the text below and provided to
the retriever.
This allows for RAG to operate within a rich amount of contexts
without getting lost
Also:
- re-implemented chunking algorithm so it streams
- moved indexing to background low priority queue
* Baran gem no longer required.
* tokenizers is on 4.4 ... upgrade it ...
This PR lets you associate uploads to an AI persona, which we'll split and generate embeddings from. When building the system prompt to get a bot reply, we'll do a similarity search followed by a re-ranking (if available). This will let us find the most relevant fragments from the body of knowledge you associated with the persona, resulting in better, more informed responses.
For now, we'll only allow plain-text files, but this will change in the future.
Commits:
* FEATURE: RAG embeddings for the AI Bot
This first commit introduces a UI where admins can upload text files, which we'll store, split into fragments,
and generate embeddings of. In a next commit, we'll use those to give the bot additional information during
conversations.
* Basic asymmetric similarity search to provide guidance in system prompt
* Fix tests and lint
* Apply reranker to fragments
* Uploads filter, css adjustments and file validations
* Add placeholder for rag fragments
* Update annotations
This allows users to share a static page of an AI conversation with
the rest of the world.
By default this feature is disabled, it is enabled by turning on
ai_bot_allow_public_sharing via site settings
Precautions are taken when sharing
1. We make a carbonite copy
2. We minimize work generating page
3. We limit to 100 interactions
4. Many security checks - including disallowing if there is a mix
of users in the PM.
* Bonus commit, large PRs like this PR did not work with github tool
large objects would destroy context
Co-authored-by: Martin Brennan <martin@discourse.org>
* DEV: AI bot migration to the Llm pattern.
We added tool and conversation context support to the Llm service in discourse-ai#366, meaning we met all the conditions to migrate this module.
This PR migrates to the new pattern, meaning adding a new bot now requires minimal effort as long as the service supports it. On top of this, we introduce the concept of a "Playground" to separate the PM-specific bits from the completion, allowing us to use the bot in other contexts like chat in the future. Commands are called tools, and we simplified all the placeholder logic to perform updates in a single place, making the flow more one-wayish.
* Followup fixes based on testing
* Cleanup unused inference code
* FIX: text-based tools could be in the middle of a sentence
* GPT-4-turbo support
* Use new LLM API
Introduce a Discourse Automation based periodical report. Depends on Discourse Automation.
Report works best with very large context language models such as GPT-4-Turbo and Claude 2.
- Introduces final_insts to generic llm format, for claude to work best it is better to guide the last assistant message (we should add this to other spots as well)
- Adds GPT-4 turbo support to generic llm interface
* FEATURE: User sentiment on profile summary page
This introduces a new user stat in a user profile summary page.
It will show either neutral/positive/negative according to the dominant
sentiment in the user last interactions.
The user-stat widget is only rendered for staff.
Co-authored-by: Keegan George <kgeorge13@gmail.com>
Previous to this change we relied on explicit loading for a files in Discourse AI.
This had a few downsides:
- Busywork whenever you add a file (an extra require relative)
- We were not keeping to conventions internally ... some places were OpenAI others are OpenAi
- Autoloader did not work which lead to lots of full application broken reloads when developing.
This moves all of DiscourseAI into a Zeitwerk compatible structure.
It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there)
To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi
Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections
Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
* FIX: no selected persona should pick first prioritized one
Previously we were looking at `.personaId` but there is only an
id attribute so it failed
* FEATURE: new DALL-E-3 persona
This persona generates images using DALL-E-3 API and is enabled
by default
Keep in mind that we are still waiting on seeds/gen_id so we can
not retain style consistently between turns.
This will change as soon as a new Open AI API provides the missing
parameters
Co-authored-by: Martin Brennan <martin@discourse.org>
* DEV: One LLM abstraction to rule them all
* REFACTOR: HyDE search uses new LLM abstraction
* REFACTOR: Summarization uses the LLM abstraction
* Updated documentation and made small fixes. Remove Bedrock claude-2 restriction
People tend to keep to 1 persona when working with the bot,
this adds local browser memory for the last persona you interacted
with so you do not need to select it over and over again.
This is per browser, not per user memory.
Also... clean up tests so they do not need to require stubs which
were breaking the build
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Co-authored-by: Martin Brennan <martin@discourse.org>
Introduces a UI to manage customizable personas (admin only feature)
Part of the change was some extensive internal refactoring:
- AIBot now has a persona set in the constructor, once set it never changes
- Command now takes in bot as a constructor param, so it has the correct persona and is not generating AIBot objects on the fly
- Added a .prettierignore file, due to the way ALE is configured in nvim it is a pre-req for prettier to work
- Adds a bunch of validations on the AIPersona model, system personas (artist/creative etc...) are all seeded. We now ensure
- name uniqueness, and only allow certain properties to be touched for system personas.
- (JS note) the client side design takes advantage of nested routes, the parent route for personas gets all the personas via this.store.findAll("ai-persona") then child routes simply reach into this model to find a particular persona.
- (JS note) data is sideloaded into the ai-persona model the meta property supplied from the controller, resultSetMeta
- This removes ai_bot_enabled_personas and ai_bot_enabled_chat_commands, both should be controlled from the UI on a per persona basis
- Fixes a long standing bug in token accounting ... we were doing to_json.length instead of to_json.to_s.length
- Amended it so {commands} are always inserted at the end unconditionally, no need to add it to the template of the system message as it just confuses things
- Adds a concept of required_commands to stock personas, these are commands that must be configured for this stock persona to show up.
- Refactored tests so we stop requiring inference_stubs, it was very confusing to need it, added to plugin.rb for now which at least is clearer
- Migrates the persona selector to gjs
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Co-authored-by: Joffrey JAFFEUX <j.jaffeux@gmail.com>
Co-authored-by: Martin Brennan <martin@discourse.org>
This PR adds new reports for displaying information about post sentiments grouped by date and emotions group by TL.
Depends on discourse/discourse#24274
The new automation rule can be used to perform llm based classification and categorization of topics.
You specify a system prompt (which has %%POST%% as an input), if it returns a particular piece of text then we will apply rules such as tagging, hiding, replying or categorizing.
This can be used as a spam filter, a "oops you are in the wrong place" filter and so on.
Co-authored-by: Joffrey JAFFEUX <j.jaffeux@gmail.com>
If a module LLM model is set to claude-2 and the ai_bedrock variables are all present we will use AWS Bedrock instead of Antrhopic own APIs.
This is quite hacky, but will allow us to test the waters with AWS Bedrock early access with every module.
This situation of "same module, completely different API" is quite a bit far from what we had in the OpenAI/Azure separation, so it's more food for thought for when we start working on the LLM abstraction layer soon this year.
* FEATURE: HyDE-powered semantic search.
It relies on the new outlet added on discourse/discourse#23390 to display semantic search results in an unobtrusive way.
We'll use a HyDE-backed approach for semantic search, which consists on generating an hypothetical document from a given keywords, which gets transformed into a vector and used in a asymmetric similarity topic search.
This PR also reorganizes the internals to have less moving parts, maintaining one hierarchy of DAOish classes for vector-related operations like transformations and querying.
Completions and vectors created by HyDE will remain cached on Redis for now, but we could later use Postgres instead.
* Missing translation and rate limiting
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Co-authored-by: Roman Rizzi <rizziromanalejandro@gmail.com>
Open AI support function calling, this has a very specific shape
that other LLMs have not quite adopted.
This simulates a command framework using system prompts on LLMs
that are not open AI.
Features include:
- Smart system prompt to steer the LLM
- Parameter validation (we ensure all the params are specified correctly)
This is being tested on Anthropic at the moment and intial results
are promising.
Rafael dos Santos Silva
Sam
Kris
Roman Rizzi
Keegan George
chapoi
Martin Brennan
Jarek Radosz
Martin Brennan