4536: Limit concurrent search requests r=ManyTheFish a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4489
## What does this PR do?
- Adds a « search queue » that limits the number of search requests we can process at the same time and stores search requests to be processed
- Process only one search request per core/thread (we use available_parallelism)
- When the search queue is full, new search requests replace old ones **randomly**. The reason is that:
- If we serve the oldest one first, like Typesense, we give the worst performances to everyone
- If we serve the latest one, it gets too easy to DoS us (you just need to fill the queue with as many search requests as we can process simultaneously to ensure no other request will ever be processed)
- By picking the search request randomly, we give a chance to recent search requests to be processed while ensuring that we can't be owned unless they fill our queue entirely and we start returning errors 5xx
- Adds an experimental parameter to control the size of the queue
- Adds a bunch of tests to ensure the search queue works correctly
- Ensure the loop consuming the search queue is running in the health route and crashes if it’s not the case
Co-authored-by: Tamo <tamo@meilisearch.com>
4509: Rest embedder r=ManyTheFish a=dureuill
Fixes#4531
See [Usage page](https://meilisearch.notion.site/v1-8-AI-search-API-usage-135552d6e85a4a52bc7109be82aeca42?pvs=25#e6f58c3b742c4effb4ddc625ce12ee16)
### Implementation changes
- Remove tokio, futures, reqwests
- Add a new `milli::vector::rest::Embedder` embedder
- Update OpenAI and Ollama embedders to use the REST embedder internally
- Make Embedder::embed a sync method
- Add the new embedder source as described in the usage
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
4530: fix: set the histogram bucket boundaries to follow the otel spec r=curquiza a=rohankmr414
# Pull Request
## What does this PR do?
- Fixes the http request duration histogram bucket boundaries to follow the opentelemetry spec, currently the bucket boundaries are too granular and only track latencies below 1s.
## PR checklist
Please check if your PR fulfills the following requirements:
- [ ] 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: Rohan Kumar <rohankmr414@gmail.com>
4476: Make the `/facet-search` route use the `sortFacetValuesBy` setting r=irevoire a=Kerollmops
This PR fixes#4423 by ensuring that the `/facet-search` route uses the `sortFacetValuesBy` setting.
Note for the documentation team (to be moved in the tracking issue): Using the new `sortFacetValuesBy` setting can slow down the facet-search requests as Meilisearch iterates over the whole list of facet values and computes the count of documents on every entry. That is hardly or even impossible to optimize correctly.
### TODO
- [x] Create a custom HashMap wrapper for the facet `OrderBy` settings.
This wrapper will return the `OrderBy` setting of the facet, if not defined will use the default `*` one, and if not there either (strange) will fall back on the lexicographic one.
- [x] Create a `ValuesCollection` wrapper that implements the logic for the lexicographic and count order by.
- [x] Use it when there is no search query.
- [x] Use it when there is a search query with and without allowed typos.
- [x] Do not change the original logic, only use a wrapper.
- [x] Add tests
Co-authored-by: Clément Renault <clement@meilisearch.com>
4456: Add Ollama as an embeddings provider r=dureuill a=jakobklemm
# Pull Request
## Related issue
[Related Discord Thread](https://discord.com/channels/1006923006964154428/1211977150316683305)
## What does this PR do?
- Adds Ollama as a provider of Embeddings besides HuggingFace and OpenAI under the name `ollama`
- Adds the environment variable `MEILI_OLLAMA_URL` to set the embeddings URL of an Ollama instance with a default value of `http://localhost:11434/api/embeddings` if no variable is set
- Changes some of the structs and functions in `openai.rs` to be public so that they can be shared.
- Added more error variants for Ollama specific errors
- It uses the model `nomic-embed-text` as default, but any string value is allowed, however it won't automatically check if the model actually exists or is an embedding model
Tested against Ollama version `v0.1.27` and the `nomic-embed-text` model.
## 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?
Co-authored-by: Jakob Klemm <jakob@jeykey.net>
Co-authored-by: Louis Dureuil <louis.dureuil@gmail.com>
Initial prototype of Ollama embeddings actually working, error handlign / retries still missing.
Allow model to be any String and require dimensions parameter
Fixed rustfmt formatting issues
There were some formatting issues in the initial PR and this should not make the changes comply with the Rust style guidelines
Because I accidentally didn't follow the style guide for commits in my commit messages I squashed them into one to comply
4443: Add GPU analytics r=dureuill a=dureuill
# Pull Request
## Related issue
Adds analytics indicating whether Meilisearch was compiled with the `milli/cuda` feature.
Cc `@macraig`
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
