The custom field "discourse_ai_bypass_ai_reply" was added so
we can signal the post created hook to bypass replying even
if it thinks it should.
Otherwise there are cases where we double answer user questions
leading to much confusion.
This also slightly refactors code making the controller smaller
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.
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Co-authored-by: Gabriel Grubba <70247653+Grubba27@users.noreply.github.com>
Co-authored-by: Keegan George <kgeorge13@gmail.com>
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.
* FEATURE: Fast-track gist regeneration when a hot topic gets a new post
* DEV: Introduce an upsert-like summarize
* FIX: Only enqueue fast-track gist for hot hot hot topics
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Co-authored-by: Rafael Silva <xfalcox@gmail.com>
* FIX/REFACTOR: FoldContent revamp
We hit a snag with our hot topic gist strategy: the regex we used to split the content didn't work, so we cannot send the original post separately. This was important for letting the model focus on what's new in the topic.
The algorithm doesn’t give us full control over how prompts are written, and figuring out how to format the content isn't straightforward. This means we're having to use more complicated workarounds, like regex.
To tackle this, I'm suggesting we simplify the approach a bit. Let's focus on summarizing as much as we can upfront, then gradually add new content until there's nothing left to summarize.
Also, the "extend" part is mostly for models with small context windows, which shouldn't pose a problem 99% of the time with the content volume we're dealing with.
* Fix fold docs
* Use #shift instead of #pop to get the first elem, not the last
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
AI bot won't be turned on for seeded LLMs so it makes no sense to expose it here. This will cleanup the template and avoid the double `{{#unless}}` check.
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.
In preparation for applying the streaming animation elsewhere, we want to better improve the organization of folder structure and methods used in the `ai-streamer`
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)
Previously, when we added smooth streaming animation to summarization (https://github.com/discourse/discourse-ai/pull/778) we used the same logic and lib we did for AI Bot. However, since `AiSummaryBox` is an Ember component, the direct DOM manipulation done in the streamer (`SummaryUpdater`) would often result in issues with summarization where sometimes summarization updates would hang, especially on the last result. This is likely due to the DOM manipulation being done in the streamer being incongruent with Ember's way of rendering.
In this PR, we remove the direct DOM manipulation done in the lib `SummaryUpdater` in favour of directly updating the properties in `AiSummaryBox` using the `componentContext`. Instead of messing with Ember's rendered DOM, passing the updates and allowing the component to render the updates directly should likely prevent further issues with summarization.
The bug itself is quite difficult to repro and also difficult to test, so no tests have been added to this PR. But I will be manually testing and assessing for any potential issues.
* 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>
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
Kris
Roman Rizzi
Sam
Discourse Translator Bot
dependabot[bot]
Rafael dos Santos Silva
David Taylor
Bianca Nenciu
jbrw
Keegan George
Loïc Guitaut
Martin Brennan