3702: Update charabia v0.7.2 r=curquiza a=ManyTheFish
fixes#3701fixes#3689fixes#3285
3710: Updated messages pointing to the docs website r=curquiza a=roy9495
# Pull Request
Fixes partially #3668
## What does this PR do?
- ...Any messages referencing this docs site https://docs.meilisearch.com has been changed to this docs site https://meilisearch.com/docs .
Thanks.
## 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: ManyTheFish <many@meilisearch.com>
Co-authored-by: TATHAGATA ROY <98920199+roy9495@users.noreply.github.com>
3571: Introduce two filters to select documents with `null` and empty fields r=irevoire a=Kerollmops
# Pull Request
## Related issue
This PR implements the `X IS NULL`, `X IS NOT NULL`, `X IS EMPTY`, `X IS NOT EMPTY` filters that [this comment](https://github.com/meilisearch/product/discussions/539#discussioncomment-5115884) is describing in a very detailed manner.
## What does this PR do?
### `IS NULL` and `IS NOT NULL`
This PR will be exposed as a prototype for now. Below is the copy/pasted version of a spec that defines this filter.
- `IS NULL` matches fields that `EXISTS` AND `= IS NULL`
- `IS NOT NULL` matches fields that `NOT EXISTS` OR `!= IS NULL`
1. `{"name": "A", "price": null}`
2. `{"name": "A", "price": 10}`
3. `{"name": "A"}`
`price IS NULL` would match 1
`price IS NOT NULL` or `NOT price IS NULL` would match 2,3
`price EXISTS` would match 1, 2
`price NOT EXISTS` or `NOT price EXISTS` would match 3
common query : `(price EXISTS) AND (price IS NOT NULL)` would match 2
### `IS EMPTY` and `IS NOT EMPTY`
- `IS EMPTY` matches Array `[]`, Object `{}`, or String `""` fields that `EXISTS` and are empty
- `IS NOT EMPTY` matches fields that `NOT EXISTS` OR are not empty.
1. `{"name": "A", "tags": null}`
2. `{"name": "A", "tags": [null]}`
3. `{"name": "A", "tags": []}`
4. `{"name": "A", "tags": ["hello","world"]}`
5. `{"name": "A", "tags": [""]}`
6. `{"name": "A"}`
7. `{"name": "A", "tags": {}}`
8. `{"name": "A", "tags": {"t1":"v1"}}`
9. `{"name": "A", "tags": {"t1":""}}`
10. `{"name": "A", "tags": ""}`
`tags IS EMPTY` would match 3,7,10
`tags IS NOT EMPTY` or `NOT tags IS EMPTY` would match 1,2,4,5,6,8,9
`tags IS NULL` would match 1
`tags IS NOT NULL` or `NOT tags IS NULL` would match 2,3,4,5,6,7,8,9,10
`tags EXISTS` would match 1,2,3,4,5,7,8,9,10
`tags NOT EXISTS` or `NOT tags EXISTS` would match 6
common query : `(tags EXISTS) AND (tags IS NOT NULL) AND (tags IS NOT EMPTY)` would match 2,4,5,8,9
## What should the reviewer do?
- Check that I tested the filters
- Check that I deleted the ids of the documents when deleting documents
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
3688: Following release v1.1.1: bring back changes into `main` r=curquiza a=curquiza
`@meilisearch/engine-team` ensure the changes we bring to `main` are the ones you want
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: bors[bot] <26634292+bors[bot]@users.noreply.github.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: dureuill <dureuill@users.noreply.github.com>
3641: Bring back changes from `release v1.1.0` into `main` after v1.1.0 release r=curquiza a=curquiza
Replace https://github.com/meilisearch/meilisearch/pull/3637 since we don't want to pull commits from `main` into `release-v1.1.0` when fixing git conflicts
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: bors[bot] <26634292+bors[bot]@users.noreply.github.com>
Co-authored-by: Charlotte Vermandel <charlottevermandel@gmail.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
Co-authored-by: curquiza <clementine@meilisearch.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Many the fish <many@meilisearch.com>
3623: Update mini-dashboard to version v0.2.7 r=curquiza a=bidoubiwa
## Changes
* Retrieve the API Key from the url parameters (#416) `@qdequele`
## 🐛 Bug Fixes
* Fix show more button not displaying all fields (#419) `@bidoubiwa`
Thanks again to `@bidoubiwa,` and `@qdequele!` 🎉
Co-authored-by: Charlotte Vermandel <charlottevermandel@gmail.com>
3568: CI: Fix `publish-aarch64` job that still uses ubuntu-18.04 r=Kerollmops a=curquiza
Fixes#3563
Main change
- add the usage of the `ubuntu-18.04` container instead of the native `ubuntu-18.04` of GitHub actions: I had to install docker in the container.
Small additional changes
- remove useless `fail-fast` and unused/irrelevant matrix inputs (`build`, `linker`, `os`, `use-cross`...)
- Remove useless step in job
Proof of work with this CI triggered on this current branch: https://github.com/meilisearch/meilisearch/actions/runs/4366233882
3569: Enhance Japanese language detection r=dureuill a=ManyTheFish
# Pull Request
This PR is a prototype and can be tested by downloading [the dedicated docker image](https://hub.docker.com/layers/getmeili/meilisearch/prototype-better-language-detection-0/images/sha256-a12847de00e21a71ab797879fd09777dadcb0881f65b5f810e7d1ed434d116ef?context=explore):
```bash
$ docker pull getmeili/meilisearch:prototype-better-language-detection-0
```
## Context
Some Languages are harder to detect than others, this miss-detection leads to bad tokenization making some words or even documents completely unsearchable. Japanese is the main Language affected and can be detected as Chinese which has a completely different way of tokenization.
A [first iteration has been implemented for v1.1.0](https://github.com/meilisearch/meilisearch/pull/3347) but is an insufficient enhancement to make Japanese work. This first implementation was detecting the Language during the indexing to avoid bad detections during the search.
Unfortunately, some documents (shorter ones) can be wrongly detected as Chinese running bad tokenization for these documents and making possible the detection of Chinese during the search because it has been detected during the indexing.
For instance, a Japanese document `{"id": 1, "name": "東京スカパラダイスオーケストラ"}` is detected as Japanese during indexing, during the search the query `東京` will be detected as Japanese because only Japanese documents have been detected during indexing despite the fact that v1.0.2 would detect it as Chinese.
However if in the dataset there is at least one document containing a field with only Kanjis like:
_A document with only 1 field containing only Kanjis:_
```json
{
"id":4,
"name": "東京特許許可局"
}
```
_A document with 1 field containing only Kanjis and 1 field containing several Japanese characters:_
```json
{
"id":105,
"name": "東京特許許可局",
"desc": "日経平均株価は26日 に約8カ月ぶりに2万4000円の心理的な節目を上回った。株高を支える材料のひとつは、自民党総裁選で3選を決めた安倍晋三首相の経済政策への期待だ。恩恵が見込まれるとされる人材サービスや建設株の一角が買われている。ただ思惑が先行して資金が集まっている面 は否めない。実際に政策効果を取り込む企業はどこか、なお未知数だ。"
}
```
Then, in both cases, the field `name` will be detected as Chinese during indexing allowing the search to detect Chinese in queries. Therefore, the query `東京` will be detected as Chinese and only the two last documents will be retrieved by Meilisearch.
## Technical Approach
The current PR partially fixes these issues by:
1) Adding a check over potential miss-detections and rerunning the extraction of the document forcing the tokenization over the main Languages detected in it.
> 1) run a first extraction allowing the tokenizer to detect any Language in any Script
> 2) generate a distribution of tokens by Script and Languages (`script_language`)
> 3) if for a Script we have a token distribution of one of the Language that is under the threshold, then we rerun the extraction forbidding the tokenizer to detect the marginal Languages
> 4) the tokenizer will fall back on the other available Languages to tokenize the text. For example, if the Chinese were marginally detected compared to the Japanese on the CJ script, then the second extraction will force Japanese tokenization for CJ text in the document. however, the text on another script like Latin will not be impacted by this restriction.
2) Adding a filtering threshold during the search over Languages that have been marginally detected in documents
## Limits
This PR introduces 2 arbitrary thresholds:
1) during the indexing, a Language is considered miss-detected if the number of detected tokens of this Language is under 10% of the tokens detected in the same Script (Japanese and Chinese are 2 different Languages sharing the "same" script "CJK").
2) during the search, a Language is considered marginal if less than 5% of documents are detected as this Language.
This PR only partially fixes these issues:
- ✅ the query `東京` now find Japanese documents if less than 5% of documents are detected as Chinese.
- ✅ the document with the id `105` containing the Japanese field `desc` but the miss-detected field `name` is now completely detected and tokenized as Japanese and is found with the query `東京`.
- ❌ the document with the id `4` no longer breaks the search Language detection but continues to be detected as a Chinese document and can't be found during the search.
## Related issue
Fixes#3565
## Possible future enhancements
- Change or contribute to the Library used to detect the Language
- the related issue on Whatlang: https://github.com/greyblake/whatlang-rs/issues/122
Co-authored-by: curquiza <clementine@meilisearch.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Many the fish <many@meilisearch.com>
3577: Avoid fetching an LMDB value with an empty string r=ManyTheFish a=Kerollmops
# Pull Request
## Related issue
Fixes#3574
## What does this PR do?
This PR fixes a bug where an empty key fetches an entry in the database. LMDB throws an error if an empty or too-long key is used to fetch an entry. This empty string seems to have been generated by the Charabia tokenizer.
Co-authored-by: Clément Renault <clement@meilisearch.com>
