Commit Graph

64 Commits

Author SHA1 Message Date
Roman Rizzi 9505a8976c
FEATURE: Automatically backfill regular summaries. (#892)
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We'll prioritize topics without summary over outdated ones.
2024-11-04 17:48:11 -03:00
Sam be0b78cacd
FEATURE: new endpoint for directly accessing a persona (#876)
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>
2024-10-30 10:28:20 +11:00
Bianca Nenciu 294c364a75
DEV: Fix mismatched column types (#868)
The primary key is usually a bigint column, but the foreign key columns
are usually of integer type. This can lead to issues when joining these
columns due to mismatched types and different value ranges.

This was using a temporary plugin / test API to make tests pass, but it
is safe to alter "ai_document_fragment_embeddings" and
"rag_document_fragments" tables because they usually have less than 1M
rows and migration is going to be fast.

Depending on the size of the community, "classification_results" table
may have more than 1M rows and the migration will lock the table for a
longer time. However, classification runs in background jobs and they
will be automatically retried if they fail due to the lock, which makes
it acceptable.
2024-10-28 15:36:42 +02:00
Sam 059d3b6fd2
FEATURE: better logging for automation reports (#853)
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.
2024-10-23 16:49:56 +11:00
Sam bdf3b6268b
FEATURE: smarter persona tethering (#832)
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
2024-10-16 07:20:31 +11:00
Roman Rizzi c7acb4a6a0
REFACTOR: Support of different summarization targets/prompts. (#835)
* DEV: Add summary types

* Refactor for different summary types

* Use enum for summary types

* Update lib/summarization/strategies/topic_summary.rb

Co-authored-by: Penar Musaraj <pmusaraj@gmail.com>

* Update lib/summarization/strategies/topic_gist.rb

Co-authored-by: Penar Musaraj <pmusaraj@gmail.com>

* Update lib/summarization/strategies/chat_messages.rb

Co-authored-by: Penar Musaraj <pmusaraj@gmail.com>

* Fix chat_messages single prompt

* Small tweak to the chat summarization prompt

---------

Co-authored-by: Penar Musaraj <pmusaraj@gmail.com>
2024-10-15 13:53:26 -03:00
Rafael dos Santos Silva 791fad1e6a
FEATURE: Index embeddings using bit vectors (#824)
On very large sites, the rare cache misses for Related Topics can take around 200ms, which affects our p99 metric on the topic page. In order to mitigate this impact, we now have several tools at our disposal.

First, one is to migrate the index embedding type from halfvec to bit and change the related topic query to leverage the new bit index by changing the search algorithm from inner product to Hamming distance. This will reduce our index sizes by 90%, severely reducing the impact of embeddings on our storage. By making the related query a bit smarter, we can have zero impact on recall by using the index to over-capture N*2 results, then re-ordering those N*2 using the full halfvec vectors and taking the top N. The expected impact is to go from 200ms to <20ms for cache misses and from a 2.5GB index to a 250MB index on a large site.

Another tool is migrating our index type from IVFFLAT to HNSW, which can increase the cache misses performance even further, eventually putting us in the under 5ms territory. 

Co-authored-by: Roman Rizzi <roman@discourse.org>
2024-10-14 13:26:03 -03:00
Sam 6c4c96e83c
FEATURE: allow persona to only force tool calls on limited replies (#827)
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.
2024-10-11 07:23:42 +11:00
Sam 5cbc9190eb
FEATURE: RAG search within tools (#802)
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
2024-09-30 17:27:50 +10:00
Sam 03eccbe392
FEATURE: Make tool support polymorphic (#798)
Polymorphic RAG means that we will be able to access RAG fragments both from AiPersona and AiCustomTool

In turn this gives us support for richer RAG implementations.
2024-09-16 08:17:17 +10:00
Rafael dos Santos Silva 1686a8a683
DEV: Move to single table per embeddings type (#561)
Also move us to halfvecs for speed and disk usage gains
2024-08-08 11:55:20 -03:00
Roman Rizzi 20efc9285e
FIX: Correctly save provider-specific params for new models. (#744)
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.
2024-08-07 16:08:56 -03:00
Natalie Tay 7cd7f71857
DEV: Promote historical post-deploy migrations (#728) 2024-07-30 01:44:57 +08:00
Rafael dos Santos Silva 665637fbad
FIX: Properly fix ai_summaries table sequence (#727)
* FIX: Properly fix ai_summaries table sequence

Previous attempt at 3815360 could fail due to a race introduced in 1b0ba91 where summaries are migrated to core in a post_migrate erroneously.
2024-07-26 14:45:01 -03:00
Roman Rizzi 5c196bca89
FEATURE: Track if a model can do vision in the llm_models table (#725)
* FEATURE: Track if a model can do vision in the llm_models table

* Data migration
2024-07-24 16:29:47 -03:00
Sam 38153608f8
FIX: repair id sequence identity on summary table (#701)
1. Repairs the identity on the summary table, we migrated data without resetting it.
2. Adds an index into ai_summary table to match expected retrieval pattern
2024-07-04 12:23:46 +10:00
Keegan George 1b0ba9197c
DEV: Add summarization logic from core (#658) 2024-07-02 08:51:59 -07:00
Sam b863ddc94b
FEATURE: custom user defined tools (#677)
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>
2024-06-27 17:27:40 +10:00
Loïc Guitaut 6f5873b072 DEV: Use Rails 7.0 instead of 7.1 in migrations 2024-06-26 18:32:11 +02:00
Roman Rizzi f622e2644f
FEATURE: Store provider-specific parameters. (#686)
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.
2024-06-25 08:26:30 +10:00
Roman Rizzi 8d5f901a67
DEV: Rewire AI bot internals to use LlmModel (#638)
* 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
2024-06-18 14:32:14 -03:00
Sam 5abf80cb4e
FIX: do not mark column read only so certain deployments work (#663)
In some case we may be deploying migrations, seeding and then
running post migrations, we need this to work so we give up
on this small window of protection
2024-06-11 21:32:49 +10:00
Sam 52a7dd2a4b
FEATURE: optional tool detail blocks (#662)
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>
2024-06-11 18:14:14 +10:00
Loïc Guitaut dd4e305ff7
DEV: Update rubocop-discourse to version 3.8.0 (#641) 2024-05-28 11:15:42 +02:00
Keegan George a1c649965f
FEATURE: Auto image captions (#637) 2024-05-27 10:49:24 -07:00
Sam baf88e7cfc
FEATURE: improve logging by including llm name (#640)
Log the language model name when logging api requests
2024-05-27 16:46:01 +10:00
Roman Rizzi 1d786fbaaf
FEATURE: Set endpoint credentials directly from LlmModel. (#625)
* 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>
2024-05-16 09:50:22 -03:00
Sam 8eee6893d6
FEATURE: GPT4o support and better auditing (#618)
- 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
2024-05-14 13:28:46 +10:00
Roman Rizzi 62fc7d6ed0
FEATURE: Configurable LLMs. (#606)
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
2024-05-13 12:46:42 -03:00
Sam e4b326c711
FEATURE: support Chat with AI Persona via a DM (#488)
Add support for chat with AI personas

- Allow enabling chat for AI personas that have an associated user
- Add new setting `allow_chat` to AI persona to enable/disable chat
- When a message is created in a DM channel with an allowed AI persona user, schedule a reply job
- AI replies to chat messages using the persona's `max_context_posts` setting to determine context
- Store tool calls and custom prompts used to generate a chat reply on the `ChatMessageCustomPrompt` table
- Add tests for AI chat replies with tools and context

At the moment unlike posts we do not carry tool calls in the context.

No @mention support yet for ai personas in channels, this is future work
2024-05-06 09:49:02 +10:00
Sam 32b3004ce9
FEATURE: Add Question Consolidator for robust Upload support in Personas (#596)
This commit introduces a new feature for AI Personas called the "Question Consolidator LLM". The purpose of the Question Consolidator is to consolidate a user's latest question into a self-contained, context-rich question before querying the vector database for relevant fragments. This helps improve the quality and relevance of the retrieved fragments.

Previous to this change we used the last 10 interactions, this is not ideal cause the RAG would "lock on" to an answer. 

EG:

- User: how many cars are there in europe
- Model: detailed answer about cars in europe including the term car and vehicle many times
- User: Nice, what about trains are there in the US

In the above example "trains" and "US" becomes very low signal given there are pages and pages talking about cars and europe. This mean retrieval is sub optimal. 

Instead, we pass the history to the "question consolidator", it would simply consolidate the question to "How many trains are there in the United States", which would make it fare easier for the vector db to find relevant content. 

The llm used for question consolidator can often be less powerful than the model you are talking to, we recommend using lighter weight and fast models cause the task is very simple. This is configurable from the persona ui.

This PR also removes support for {uploads} placeholder, this is too complicated to get right and we want freedom to shift RAG implementation. 

Key changes:

1. Added a new `question_consolidator_llm` column to the `ai_personas` table to store the LLM model used for question consolidation.

2. Implemented the `QuestionConsolidator` module which handles the logic for consolidating the user's latest question. It extracts the relevant user and model messages from the conversation history, truncates them if needed to fit within the token limit, and generates a consolidated question prompt.

3. Updated the `Persona` class to use the Question Consolidator LLM (if configured) when crafting the RAG fragments prompt. It passes the conversation context to the consolidator to generate a self-contained question.

4. Added UI elements in the AI Persona editor to allow selecting the Question Consolidator LLM. Also made some UI tweaks to conditionally show/hide certain options based on persona configuration.

5. Wrote unit tests for the QuestionConsolidator module and updated existing persona tests to cover the new functionality.

This feature enables AI Personas to better understand the context and intent behind a user's question by consolidating the conversation history into a single, focused question. This can lead to more relevant and accurate responses from the AI assistant.
2024-04-30 13:49:21 +10:00
Sam f6ac5cd0a8
FEATURE: allow tuning of RAG generation (#565)
* FEATURE: allow tuning of RAG generation

- change chunking to be token based vs char based (which is more accurate)
- allow control over overlap / tokens per chunk and conversation snippets inserted
- UI to control new settings

* improve ui a bit

* fix various reindex issues

* reduce concurrency

* try ultra low queue ... concurrency 1 is too slow.
2024-04-12 10:32:46 -03:00
Rafael dos Santos Silva eb93b21769
FEATURE: Add BGE-M3 embeddings support (#569)
BAAI/bge-m3 is an interesting model, that is multilingual and with a
context size of 8192. Even with a 16x larger context, it's only 4x slower
to compute it's embeddings on the worst case scenario.

Also includes a minor refactor of the rake task, including setting model
and concurrency levels when running the backfill task.
2024-04-10 17:24:01 -03:00
Sam 830cc26075
FEATURE: Add metadata support for RAG (#553)
* 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 ...
2024-04-04 11:02:16 -03:00
Roman Rizzi 1f1c94e5c6
FEATURE: AI Bot RAG support. (#537)
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
2024-04-01 13:43:34 -03:00
Sam 61e4c56e1a
FEATURE: Add vision support to AI personas (Claude 3) (#546)
This commit adds the ability to enable vision for AI personas, allowing them to understand images that are posted in the conversation.

For personas with vision enabled, any images the user has posted will be resized to be within the configured max_pixels limit, base64 encoded and included in the prompt sent to the AI provider.

The persona editor allows enabling/disabling vision and has a dropdown to select the max supported image size (low, medium, high). Vision is disabled by default.

This initial vision support has been tested and implemented with Anthropic's claude-3 models which accept images in a special format as part of the prompt.

Other integrations will need to be updated to support images.

Several specs were added to test the new functionality at the persona, prompt building and API layers.

 - Gemini is omitted, pending API support for Gemini 1.5. Current Gemini bot is not performing well, adding images is unlikely to make it perform any better.

 - Open AI is omitted, vision support on GPT-4 it limited in that the API has no tool support when images are enabled so we would need to full back to a different prompting technique, something that would add lots of complexity


---------

Co-authored-by: Martin Brennan <martin@discourse.org>
2024-03-27 14:30:11 +11:00
Sam a03bc6ddec
FEATURE: Share conversations with AI via a URL (#521)
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>
2024-03-12 16:51:41 +11:00
Sam 3a8d95f6b2
FEATURE: mentionable personas and random picker tool, context limits (#466)
1. Personas are now optionally mentionable, meaning that you can mention them either from public topics or PMs
       - Mentioning from PMs helps "switch" persona mid conversation, meaning if you want to look up sites setting you can invoke the site setting bot, or if you want to generate an image you can invoke dall e
        - Mentioning outside of PMs allows you to inject a bot reply in a topic trivially
     - We also add the support for max_context_posts this allow you to limit the amount of context you feed in, which can help control costs

2. Add support for a "random picker" tool that can be used to pick random numbers 

3. Clean up routing ai_personas -> ai-personas

4. Add Max Context Posts so users can control how much history a persona can consume (this is important for mentionable personas) 

Co-authored-by: Martin Brennan <martin@discourse.org>
2024-02-15 16:37:59 +11:00
Sam a3c827efcc
FEATURE: allow personas to supply top_p and temperature params (#459)
* FEATURE: allow personas to supply top_p and temperature params

Code assistance generally are more focused at a lower temperature
This amends it so SQL Helper runs at 0.2 temperature vs the more
common default across LLMs of 1.0.

Reduced temperature leads to more focused, concise and predictable
answers for the SQL Helper

* fix tests

* This is not perfect, but far better than what we do today

Instead of fishing for

1. Draft sequence
2. Draft body

We skip (2), this means the composer "only" needs 1 http request to
open, we also want to eliminate (1) but it is a bit of a trickier
core change, may figure out how to pull it off (defer it to first draft save)

Value of bot drafts < value of opening bot conversations really fast
2024-02-03 07:09:34 +11:00
Sam b2b01185f2
FEATURE: add support for new OpenAI embedding models (#445)
* FEATURE: add support for new OpenAI embedding models

This adds support for just released text_embedding_3_small and large

Note, we have not yet implemented truncation support which is a
new API feature. (triggered using dimensions)

* Tiny side fix, recalc bots when ai is enabled or disabled

* FIX: downsample to 2000 items per vector which is a pgvector limitation
2024-01-29 13:24:30 -03:00
Jarek Radosz 5802cd1a0c
DEV: Fix various typos (#434) 2024-01-19 12:51:26 +01:00
Sam 03fc94684b
FIX: AI helper not working correctly with mixtral (#399)
* FIX: AI helper not working correctly with mixtral

This PR introduces a new function on the generic llm called #generate

This will replace the implementation of completion!

#generate introduces a new way to pass temperature, max_tokens and stop_sequences

Then LLM implementers need to implement #normalize_model_params to
ensure the generic names match the LLM specific endpoint

This also adds temperature and stop_sequences to completion_prompts
this allows for much more robust completion prompts

* port everything over to #generate

* Fix translation

- On anthropic this no longer throws random "This is your translation:"
- On mixtral this actually works

* fix markdown table generation as well
2024-01-04 09:53:47 -03:00
Rafael dos Santos Silva 140359c2ef
FEATURE: Per post embeddings (#387) 2023-12-29 12:28:45 -03:00
Rafael dos Santos Silva 1287ef4428
FEATURE: Support for Gemini Embeddings (#382) 2023-12-28 10:28:01 -03:00
Sam 6380ebd829
FEATURE: allow personas to provide command options (#331)
Personas now support providing options for commands.

This PR introduces a single option "base_query" for the SearchCommand. When supplied all searches the persona will perform will also include the pre-supplied filter.

This can allow personas to search a subset of the forum (such as documentation)

This system is extensible we can add options to any command trivially.
2023-12-08 08:42:56 +11:00
Sam 5b5edb22c6
FEATURE: UI to update ai personas on admin page (#290)
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

---------

Co-authored-by: Joffrey JAFFEUX <j.jaffeux@gmail.com>
Co-authored-by: Martin Brennan <martin@discourse.org>
2023-11-21 16:56:43 +11:00
Sam a4f419f54f
FEATURE: basic infrastructure for custom personas (#288)
- New AiPersona model which can store custom personas
- Persona are restricted via group security
- They can contain custom system messages
- They can support a list of commands optionally

To avoid expensive DB calls in the serializer a Multisite friendly Hash was introduced (which can be expired on transaction commit)
2023-11-10 11:39:49 +11:00
Sam fc65404896
FEATURE: support topic_id and post_id logging in ai audit log (#274)
This makes it easier to track who is responsible for a completion
in logs

Note: ai helper and summarization are not yet implemented
2023-11-01 08:41:31 +11:00
Rafael dos Santos Silva b9d6179bfc
DEV: Migrations shouldn't rely on the app (#253) 2023-10-16 18:50:37 -03:00
Rafael dos Santos Silva 84cc369552
FEATURE: Bge-large-en embeddings via Cloudflare Workers AI API (#241)
* FEATURE: Bge-large-en embeddings via Cloudflare Workers AI API

* forgot a file

* lint
2023-10-04 13:47:51 -03:00