4269: Remove dependency that requires libstdc++ r=dureuill a=dureuill
Removes the dependency that caused the additional runtime dependency on libstdc++ by disabling the default features of the hf tokenizer.
## Discussion
- This removes a feature that is using a C++ dependency and is supposed to accelerate the tokenizer. As the tokenizer is likely to be a significant bottleneck for embedding texts using a HF model, this is an issue.
- We should at least rerun the movies vector indexing and check that it still works correctly and that it has a runtime in the ballpark of what it used to be.
Co-authored-by: Louis Dureuil <louis.dureuil@xinra.net>
4268: Add libstdc++ in Dockerfile r=curquiza a=sanders41
# Pull Request
## Related issue
Fixes#4267
## What does this PR do?
- Add libstdc++ in the Dockerfile
## 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: Paul Sanders <psanders1@gmail.com>
4262: Update version for the next release (v1.6.0) in Cargo.toml r=curquiza a=meili-bot
⚠️ This PR is automatically generated. Check the new version is the expected one and Cargo.lock has been updated before merging.
Co-authored-by: curquiza <curquiza@users.noreply.github.com>
4257: Change proximity precision settings r=dureuill a=ManyTheFish
- [x] Add proximity_precision value into the analytics
- [x] Change the naming of `attributeScale` and `wordScale` into `byAttribute` and `byWord`
- [x] Remove proximityPrecision from the experimental feature
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Many the fish <many@meilisearch.com>
4226: Hybrid search r=dureuill a=dureuill
Allows to perform hybrid search requests that combine the results of semantic and keyword search and automatically generate embeddings.
## How to use
See [feature description](https://meilisearch.notion.site/v1-6-Hybrid-Search-Embedders-ea42c82f90cc4bc0be1eeb917c1118c8)
## Changes
- work is based on #4213
- milli::new search now takes an input universe directly, rather than computing it from a filter. This adds flexibility to require results on a subset of documents
- vector search is now a regular ranking rule (akin to sort and geosort) and reports its score as a ScoreDetail
- separate keyword search and vector search functions, vector search now respects (geo)sort ranking rules
- add automatic embedding
- add hybrid search
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
- DistributionShift in Search object (to be set from model in embed?)
- Fix issue where embedder index wasn't computed at search time
- Accept as default embedder either the "default" one, or the only embedder when there is only one
