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>
4621: Bring back changes from v1.8.0 into main r=curquiza a=curquiza
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
4580: Update the search logs r=Kerollmops a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4579
## What does this PR do?
- Update the debug implementation of the search query and search results so it’s way smaller and doesn’t display useless information
Co-authored-by: Tamo <tamo@meilisearch.com>
4535: Support Negative Keywords r=ManyTheFish a=Kerollmops
This PR fixes#4422 by supporting `-` before any word in the query.
The minus symbol `-`, from the ASCII table, is not the only character that can be considered the negative operator. You can see the two other matching characters under the `Based on "-" (U+002D)` section on [this unicode reference website](https://www.compart.com/en/unicode/U+002D).
It's important to notice the strange behavior when a query includes and excludes the same word; only the derivative ( synonyms and split) will be kept:
- If you input `progamer -progamer`, the engine will still search for `pro gamer`.
- If you have the synonym `like = love` and you input `like -like`, it will still search for `love`.
## TODO
- [x] Add analytics
- [x] Add support to the `-` operator
- [x] Make sure to support spaces around `-` well
- [x] Support phrase negation
- [x] Add tests
Co-authored-by: Clément Renault <clement@meilisearch.com>
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>
