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authorGitLab Bot <gitlab-bot@gitlab.com>2023-10-26 21:11:56 +0300
committerGitLab Bot <gitlab-bot@gitlab.com>2023-10-26 21:11:56 +0300
commitea413f31cf00268c71bfab1351b92f75e72c9a80 (patch)
tree40d55fd066fd6ef9d901d66f006bde24ee2836bb /doc/development
parent5ef8690cb95a549153572811313b1401e77cef2d (diff)
Add latest changes from gitlab-org/gitlab@master
Diffstat (limited to 'doc/development')
-rw-r--r--doc/development/ai_features/index.md29
-rw-r--r--doc/development/utilities.md2
2 files changed, 2 insertions, 29 deletions
diff --git a/doc/development/ai_features/index.md b/doc/development/ai_features/index.md
index 4401a7e3fb1..2c6bec530cd 100644
--- a/doc/development/ai_features/index.md
+++ b/doc/development/ai_features/index.md
@@ -131,36 +131,9 @@ Gitlab::CurrentSettings.update!(anthropic_api_key: <insert API key>)
### Populating embeddings and using embeddings fixture
-Currently we have embeddings generate both with OpenAI and VertexAI. Bellow sections explain how to populate
+Embeddings are generated through VertexAI text embeddings endpoint. The sections below explain how to populate
embeddings in the DB or extract embeddings to be used in specs.
-FLAG:
-We are moving towards having VertexAI embeddings only, so eventually the OpenAI embeddings support will be drop
-as well as the section bellow will be removed.
-
-#### OpenAI embeddings
-
-To seed your development database with the embeddings for GitLab Documentation,
-you may use the pre-generated embeddings and a Rake task.
-
-```shell
-RAILS_ENV=development bundle exec rake gitlab:llm:embeddings:seed_pre_generated
-```
-
-The DBCleaner gem we use clear the database tables before each test runs.
-Instead of fully populating the table `tanuki_bot_mvc` where we store OpenAI embeddings for the documentations,
-we can add a few selected embeddings to the table from a pre-generated fixture.
-
-For instance, to test that the question "How can I reset my password" is correctly
-retrieving the relevant embeddings and answered, we can extract the top N closet embeddings
-to the question into a fixture and only restore a small number of embeddings quickly.
-To facilitate an extraction process, a Rake task been written.
-You can add or remove the questions needed to be tested in the Rake task and run the task to generate a new fixture.
-
-```shell
-RAILS_ENV=development bundle exec rake gitlab:llm:embeddings:extract_embeddings
-```
-
#### VertexAI embeddings
To seed your development database with the embeddings for GitLab Documentation,
diff --git a/doc/development/utilities.md b/doc/development/utilities.md
index 343d03b9d68..83b87d6d289 100644
--- a/doc/development/utilities.md
+++ b/doc/development/utilities.md
@@ -206,7 +206,7 @@ Refer to [`strong_memoize.rb`](https://gitlab.com/gitlab-org/gitlab/-/blob/maste
# good
def expensive_method(arg)
- strong_memoize_with(:expensive_method, arg)
+ strong_memoize_with(:expensive_method, arg) do
# ...
end
end