4731: Fix the missing geo distance when one or both of the lat / lng are string r=irevoire a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4193
## What does this PR do?
- Properly extract the lat / lng when one or both of them are string
- Add a test
Co-authored-by: Tamo <tamo@meilisearch.com>
4724: Improve tenant token error messages r=ManyTheFish a=irevoire
# Pull Request
## Related issue
Fixes #4727
## What does this PR do?
- Introduce a bunch of new error messages around tenant tokens
- Ignore the error messages in most tests that were doing for loop over multiple kinds of errors
- Introduce new tests that specifically test these error messages
Co-authored-by: Tamo <tamo@meilisearch.com>
4716: Fix bad http status and error message on wrong payload r=irevoire a=Karribalu
# Pull Request
## Related issue
Fixes#4698
## What does this PR do?
- Fixes bad http status when bad payload with gzip Content-Encoding
## PR checklist
Please check if your PR fulfills the following requirements:
- [x] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [x] Have you read the contributing guidelines?
- [x] Have you made sure that the title is accurate and descriptive of the changes?
Thank you so much for contributing to Meilisearch!
Co-authored-by: karribalu <karri.balu123456@gmail.com>
4730: fix a possibly flaky test r=irevoire a=irevoire
On slow CI, it was possible for a document addition to _not_ to be processed and then get autobatched with an index deletion, which changed their task summary details in the end.
Now, I wait for the task to finish, and the result will always be the same
Co-authored-by: Tamo <tamo@meilisearch.com>
4725: Store primary key as String when Number exceeds i64 range r=irevoire a=JWSong
# Pull Request
## Related issue
Fixes#4696
## What does this PR do?
- When a Number value exceeding the range of i64 is received as a primary key, it will be stored as a String.
## PR checklist
Please check if your PR fulfills the following requirements:
- [x] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [x] Have you read the contributing guidelines?
- [x] Have you made sure that the title is accurate and descriptive of the changes?
Thank you so much for contributing to Meilisearch!
Co-authored-by: JWSong <thdwjddn123@gmail.com>
4693: Introduce distinct attributes at search time r=irevoire a=Kerollmops
This PR fixes#4611.
### To Do
- [x] Remove the `distinguishableAttributes` settings (not even a commit about that).
- [x] Use the `filterableAttributes` to be able to use the `distinct` parameter at search.
- [x] Work on the errors and make tests.
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
4649: Don't store the vectors in the documents database r=dureuill a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4607
## What does this PR do?
- Ensure that anything falling under `_vectors` is NOT searchable, filterable or sortable
- [x] per embedder, add a roaring bitmap of documents that provide "userProvided" embeddings
- [x] in the indexing process in extract_vector_points, set the bit corresponding to the document depending on the "userProvided" subfield in the _vectors field.
- [x] in the document DB in typed chunks, when writing the _vectors field, remove all keys corresponding to an embedder
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
- when the feature is disabled, documents are never modified
- when the feature is enabled and `retrieveVectors` is disabled, `_vectors` is removed from documents
- when the feature is enabled and `retrieveVectors` is enabled, vectors from the vectors DB are merged with `_vectors` in documents
Additionally `_vectors` is never displayed when the `displayedAttributes` list does not contain either `*` or `_vectors`
- fixed an issue where `_vectors` was not injected when all vectors in the dataset where always generated
4685: Fix ci tests r=dureuill a=ManyTheFish
# Pull Request
Make the all following CI succeed:
https://github.com/meilisearch/meilisearch/actions/runs/9477183091
## Related issue
Fixes#4629
## What does this PR do?
- Change the test behavior for `swedish-recomposition` feature flag
- Remove the `-v` parameter from grep
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Many the fish <many@meilisearch.com>
4646: Reduce `Transform`'s disk usage r=Kerollmops a=Kerollmops
This PR implements what is described in #4485. It reduces the number of disk writes and disk usage.
Co-authored-by: Clément Renault <clement@meilisearch.com>
4633: Allow to mark vectors as "userProvided" r=Kerollmops a=dureuill
# Pull Request
## Related issue
Fixes#4606
## What does this PR do?
[See usage in PRD](https://meilisearch.notion.site/v1-9-AI-search-changes-e90d6803eca8417aa70a1ac5d0225697#deb96fb0595947bda7d4a371100326eb)
- Extends the shape of the special `_vectors` field in documents.
- previously, the `_vectors` field had to be an object, with each field the name of a configured embedder, and each value either `null`, an embedding (array of numbers), or an array of embeddings.
- In this PR, the value of an embedder in the `_vectors` field can additionally be an object. The object has two fields:
1. `embeddings`: `null`, an embedding (array of numbers), or an array of embeddings.
2. `userProvided`: a boolean indicating if the vector was provided by the user.
- The previous form `embedder_or_array_of_embedders` is semantically equivalent to:
```json
{
"embeddings": embedder_or_array_of_embedders,
"userProvided": true
}
```
- During the indexing step, the subfields and values of the `_vectors` field that have `userProvided` set to **false** are added in the vector DB, but not in the documents DB: that means that future modifications of the documents will trigger a regeneration of that particular vector using the document template.
- This allows **importing** embeddings as a one-shot process, while still retaining the ability to regenerate embeddings on document change.
- The dump process now uses this ability: it enriches the `_vectors` fields of documents with the embeddings that were autogenerated, marking them as not `userProvided`. This allows importing the vectors from a dump without regenerating them.
### Tests
This PR adds the following tests
- Long-needed hybrid search tests of a simple hf embedder
- Dump test that imports vectors. Due to the difficulty of actually importing a dump in tests, we just read the dump and check it contains the expected content.
- Tests in the index-scheduler: this tests that documents containing the same kind of instructions as in the dump indexes as expected
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
