Commit Graph

368 Commits

Author SHA1 Message Date
Many the fish
9e1b458010
Merge branch 'main' into change-proximity-precision-settings 2023-12-18 09:08:47 +01:00
ManyTheFish
6425996e36 Change the naming of attributeScale and wordScale into byAttribute and byWord 2023-12-14 16:31:00 +01:00
Louis Dureuil
806e5b6899
Tests pass 2023-12-14 16:08:41 +01:00
Louis Dureuil
e0cc775dc4
Various changes
- 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
2023-12-14 16:08:41 +01:00
Louis Dureuil
922a640188
WIP multi embedders
fixed template bugs
2023-12-14 16:08:41 +01:00
Louis Dureuil
d4715e0c4d
Fix same vector sort bug 2023-12-14 16:08:41 +01:00
Louis Dureuil
11e2a2c1aa
Fix geosort bug 2023-12-14 16:08:41 +01:00
Louis Dureuil
65e49b7092
Remove stuff, add distribution shift (WIP) 2023-12-14 16:08:38 +01:00
Louis Dureuil
cb4ebe163e
WIP 2023-12-14 16:07:49 +01:00
Louis Dureuil
dde3a04679
WIP arroy integration 2023-12-14 16:07:49 +01:00
Louis Dureuil
13c2c6c16b
Small commit to add hybrid search and autoembedding 2023-12-14 16:07:48 +01:00
Clément Renault
56571f762a
Merge remote-tracking branch 'origin/main' into tmp-release-v1.5.1 2023-12-13 11:57:01 +01:00
ManyTheFish
467b49153d Implement proximityPrecision setting on milli side 2023-12-06 15:49:02 +01:00
ManyTheFish
bddc168d83 List TODOs 2023-12-06 14:59:23 +01:00
ManyTheFish
3b3fa38f27 Put the restrict list in a sub-struct 2023-11-28 18:37:57 +01:00
ManyTheFish
d6c2ee15a9 Filter on attributes before computing the docids when attribute restriction is on 2023-11-28 14:55:29 +01:00
Clément Renault
d32eb11329
Move to the v0.20.0-alpha.9 of heed 2023-11-27 11:52:22 +01:00
Clément Renault
58dac8af42
Remove the panics and unwraps 2023-11-23 15:00:48 +01:00
Clément Renault
0dbf1a16ff
Make clippy happy 2023-11-23 14:11:38 +01:00
Clément Renault
0d4482625a
Make the changes to use heed v0.20-alpha.6 2023-11-23 11:43:58 +01:00
Clément Renault
7cb7e37ba8
Merge branch 'main' into tmp-release-v1.5.0 2023-11-21 16:30:46 +01:00
ManyTheFish
1f36410541 Update tests 2023-11-13 13:36:39 +01:00
Louis Dureuil
8c649d8061
Throw error when the vector search is sent with the wrong size 2023-11-13 09:57:42 +01:00
ManyTheFish
688266c83e Remove word pair proximity prefix cache and compute it at search time 2023-11-08 14:16:01 +01:00
ManyTheFish
94206b0055 Update tests 2023-10-31 13:48:47 +01:00
ManyTheFish
1c5705c164
clean PR warnings 2023-10-30 11:22:05 +01:00
ManyTheFish
df9e5c8651
Generalize usage of CboRoaringBitmap codec to ease the use 2023-10-30 11:15:02 +01:00
ManyTheFish
17b647dfe5
Wip 2023-10-30 11:13:08 +01:00
Tamo
e7244aa485 fix warnings 2023-10-30 11:00:46 +01:00
Louis Dureuil
2bae9550c8
Add explanatory comment 2023-10-23 12:06:28 +02:00
Vivek Kumar
5fe7c4545a
compute all candidates correctly when skipping 2023-10-23 12:02:45 +02:00
meili-bors[bot]
5e0485d8dd
Merge #4131
4131: Reduce proximity range from 7 to 3 r=Kerollmops a=ManyTheFish

## Summary
This PR aims to reduce the impact of the proximity databases on the indexing time and on the database size by reducing the maximum distance between two words to be indexed in the proximity database.

## Stats

### Impact on database size and indexing time
![Impact on datasets](https://github.com/meilisearch/meilisearch/assets/6482087/28ed3d96-bdde-41c1-bdac-e90c1b1dbb23)

### Impact on search relevancy

<details>

| dataset_name | host_name        | Relevancy rate (Precision) | completion_rate  25.00% | completion_rate 50.00% | completion_rate 75.00% | completion_rate 100.00% |
|--------------|------------------|------------------------------------|-----------------|-----------------|-----------------|-----------------|
| FBIS         | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |           5.56% |
| FBIS         | 1_4_0            | percentile-75 |           0.00% |          12.50% |          35.00% |          45.00% |
| FBIS         | 1_4_0            | percentile-90 |          20.00% |          40.00% |                 |         100.00% |
| FBIS         | 1_4_0            | average       |           5.78% |          11.16% |          21.90% |          26.29% |
| FBIS         | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |           5.56% |
| FBIS         | reduce_proximity | percentile-75 |           0.00% |          15.00% |          35.00% |          40.00% |
| FBIS         | reduce_proximity | percentile-90 |          20.00% |          40.00% |          85.00% |         100.00% |
| FBIS         | reduce_proximity | average       |           5.55% |          11.34% |          21.75% |          26.14% |
| FR94         | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-50 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-75 |           0.00% |           5.00% |          15.00% |          42.11% |
| FR94         | 1_4_0            | percentile-90 |          15.00% |          54.55% |         100.00% |         100.00% |
| FR94         | 1_4_0            | average       |           5.95% |          12.07% |          18.70% |          25.57% |
| FR94         | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-50 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-75 |           0.00% |           5.00% |          15.00% |          42.11% |
| FR94         | reduce_proximity | percentile-90 |          15.00% |          54.55% |         100.00% |         100.00% |
| FR94         | reduce_proximity | average       |           5.79% |          12.00% |          18.70% |          25.53% |
| FT           | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |          10.00% |
| FT           | 1_4_0            | percentile-75 |           0.00% |          15.00% |          30.00% |          40.00% |
| FT           | 1_4_0            | percentile-90 |          20.00% |          50.00% |          65.00% |         100.00% |
| FT           | 1_4_0            | average       |           5.08% |          12.58% |          20.00% |          25.49% |
| FT           | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |          10.00% |
| FT           | reduce_proximity | percentile-75 |           0.00% |          15.00% |          30.00% |          40.00% |
| FT           | reduce_proximity | percentile-90 |          10.00% |          45.00% |          60.00% |         100.00% |
| FT           | reduce_proximity | average       |           5.01% |          12.64% |          20.10% |          25.53% |
| LAT          | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |           5.00% |
| LAT          | 1_4_0            | percentile-75 |           5.00% |          15.00% |          30.00% |          30.00% |
| LAT          | 1_4_0            | percentile-90 |          15.00% |          45.00% |          60.00% |          80.00% |
| LAT          | 1_4_0            | average       |           4.80% |          11.80% |          17.88% |          21.62% |
| LAT          | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |           5.00% |
| LAT          | reduce_proximity | percentile-75 |           0.00% |          11.11% |          25.00% |          35.00% |
| LAT          | reduce_proximity | percentile-90 |          15.00% |          45.00% |          55.00% |          80.00% |
| LAT          | reduce_proximity | average       |           4.43% |          11.23% |          17.32% |          21.45% |

</details>

### Impact on Search time

| dataset_name | host_name        |      25.00% |      50.00% |      75.00% |     100.00% | Average     |
|--------------|------------------|------------:|------------:|------------:|------------:|-------------|
| FBIS         | 1_4_0            |        3.45 | 7.446666667 | 9.773489933 | 9.620300752 | 7.572614338 |
| FBIS         | reduce_proximity | 2.983333333 | 5.316666667 | 6.911073826 | 7.637218045 | 5.712072968 |
| FR94         | 1_4_0            | 2.236666667 |        4.45 | 5.523489933 | 4.560150376 | 4.192576744 |
| FR94         | reduce_proximity |        2.09 | 3.991666667 | 4.981543624 | 4.266917293 | 3.832531896 |
| FT           | 1_4_0            | 5.956666667 | 9.656666667 | 13.86912752 | 10.83270677 |  10.0787919 |
| FT           | reduce_proximity |        4.51 | 5.981666667 | 7.701342282 | 6.766917293 |  6.23998156 |
| LAT          | 1_4_0            | 5.856666667 | 9.233333333 | 12.98322148 | 10.78759398 | 9.715203865 |
| LAT          | reduce_proximity |        6.91 | 6.706666667 | 8.463087248 | 8.265037594 | 7.586197877 |

## Technical approach

- Ensure the MAX_DISTANCE constant is used everywhere needed
- Reduce the MAX_DISTANCE from 8 to 4

## Related

TBD

Co-authored-by: ManyTheFish <many@meilisearch.com>
2023-10-18 14:56:08 +00:00
ManyTheFish
27eec21415 Fix tests 2023-10-18 16:03:22 +02:00
Vivek Kumar
d4da06ff47
fix bug where distinct search with no ranking returns offset+limit hits 2023-10-11 19:02:16 +05:30
ManyTheFish
43989fe2e4 Reduce porximity range from 7 to 3 2023-10-03 12:16:48 +02:00
Vivek Kumar
abfa7ded25
use a new temp index in the test 2023-09-08 12:32:47 +05:30
Vivek Kumar
f2837aaec2
add another test case 2023-09-08 11:39:54 +05:30
Vivek Kumar
11df155598
fix highlighting bug when searching for a phrase with cropping 2023-09-08 11:39:52 +05:30
meili-bors[bot]
ccf3ba3f32
Merge #4019
4019: Bringing back changes from `v1.3.2` onto `main` r=irevoire a=Kerollmops



Co-authored-by: Kerollmops <clement@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: irevoire <irevoire@users.noreply.github.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
2023-08-28 12:14:11 +00:00
Clément Renault
8c0ebd1331
Update milli/src/search/new/bucket_sort.rs
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2023-08-23 16:40:39 +02:00
Kerollmops
5130e06b41
Temporarily disable an assert in the ranking rules 2023-08-23 16:11:54 +02:00
meili-bors[bot]
914b125c5f
Merge #3945
3945: Do not leak field information on error r=Kerollmops a=vivek-26

# Pull Request

## Related issue
Fixes #3865

## What does this PR do?
This PR ensures that `InvalidSortableAttribute`and `InvalidFacetSearchFacetName` errors do not leak field information i.e. fields which are not part of `displayedAttributes` in the settings are hidden from the error message.

## 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: Vivek Kumar <vivek.26@outlook.com>
2023-08-22 18:55:27 +00:00
ManyTheFish
4a21fecf67 Merge branch 'main' into settings-customizing-tokenization 2023-08-08 16:08:16 +02:00
Vivek Kumar
dd57873f8e
hide fields not in the displayedAttributes list from errors 2023-08-05 16:03:10 +05:30
ManyTheFish
b0c1a9504a ensure the synonyms are updated when the tokenizer settings are changed 2023-07-26 09:33:42 +02:00
Kerollmops
29ab54b259
Replace the hnsw crate by the instant-distance one 2023-07-25 12:37:35 +02:00
ManyTheFish
9c485f8563 Make the search and the indexing work 2023-07-24 18:35:20 +02:00
Kerollmops
d383afc82b
Fix the geo sort when lat and lng are strings 2023-07-17 18:28:04 +02:00
Louis Dureuil
4310928803
Fixes #3912 2023-07-12 10:08:56 +02:00
Louis Dureuil
74315b4ea8
Fixes #3911 2023-07-12 10:08:29 +02:00
Louis Dureuil
55cd7738b9
Update snapshots 2023-07-04 16:31:01 +02:00
Louis Dureuil
48409c9183
Add missing exactness.matchingWords, exactness.maxMatchingWords 2023-07-04 16:31:01 +02:00
Louis Dureuil
324d448236
Format let-else ❤️ 🎉 2023-07-03 10:20:28 +02:00
ManyTheFish
6ec7541026 Update inta snapshots 2023-06-29 17:18:39 +02:00
ManyTheFish
84845de9ef Update Charabia 2023-06-29 15:56:32 +02:00
meili-bors[bot]
d4f10800f2
Merge #3834
3834: Define searchable fields at runtime r=Kerollmops a=ManyTheFish

## Summary
This feature allows the end-user to search in one or multiple attributes using the search parameter `attributesToSearchOn`:

```json
{
  "q": "Captain Marvel",
  "attributesToSearchOn": ["title"]
}
```

This feature act like a filter, forcing Meilisearch to only return the documents containing the requested words in the attributes-to-search-on. Note that, with the matching strategy `last`, Meilisearch will only ensure that the first word is in the attributes-to-search-on, but, the retrieved documents will be ordered taking into account the word contained in the attributes-to-search-on. 

## Trying the prototype

A dedicated docker image has been released for this feature:

#### last prototype version:

```bash
docker pull getmeili/meilisearch:prototype-define-searchable-fields-at-search-time-1
```

#### others prototype versions:

```bash
docker pull getmeili/meilisearch:prototype-define-searchable-fields-at-search-time-0
```

## Technical Detail

The attributes-to-search-on list is given to the search context, then, the search context uses the `fid_word_docids`database using only the allowed field ids instead of the global `word_docids` database. This is the same for the prefix databases.
The database cache is updated with the merged values, meaning that the union of the field-id-database values is only made if the requested key is missing from the cache.

### Relevancy limits

Almost all ranking rules behave as expected when ordering the documents.
Only `proximity` could miss-order documents if all the searched words are in the restricted attribute but a better proximity is found in an ignored attribute in a document that should be ranked lower. I put below a failing test showing it:
```rust
#[actix_rt::test]
async fn proximity_ranking_rule_order() {
    let server = Server::new().await;
    let index = index_with_documents(
        &server,
        &json!([
        {
            "title": "Captain super mega cool. A Marvel story",
            // Perfect distance between words in an ignored attribute
            "desc": "Captain Marvel",
            "id": "1",
        },
        {
            "title": "Captain America from Marvel",
            "desc": "a Shazam ersatz",
            "id": "2",
        }]),
    )
    .await;

    // Document 2 should appear before document 1.
    index
        .search(json!({"q": "Captain Marvel", "attributesToSearchOn": ["title"], "attributesToRetrieve": ["id"]}), |response, code| {
            assert_eq!(code, 200, "{}", response);
            assert_eq!(
                response["hits"],
                json!([
                    {"id": "2"},
                    {"id": "1"},
                ])
            );
        })
        .await;
}
```

Fixing this would force us to create a `fid_word_pair_proximity_docids` and a `fid_word_prefix_pair_proximity_docids` databases which may multiply the keys of `word_pair_proximity_docids` and `word_prefix_pair_proximity_docids` by the number of attributes in the searchable_attributes list. If we think we should fix this test, I'll suggest doing it in another PR.

## Related

Fixes #3772

Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
2023-06-28 08:19:23 +00:00
Clément Renault
29d8268c94
Fix the vector query part by using the correct universe 2023-06-27 12:32:43 +02:00
Kerollmops
ab9f2269aa
Normalize the vectors during indexation and search 2023-06-27 12:32:41 +02:00
Kerollmops
3b560ef7d0
Make clippy happy 2023-06-27 12:32:40 +02:00
Kerollmops
3c31e1cdd1
Support more pages but in an ugly way 2023-06-27 12:32:39 +02:00
Kerollmops
c79e82c62a
Move back to the hnsw crate
This reverts commit 7a4b6c065482f988b01298642f4c18775503f92f.
2023-06-27 12:32:39 +02:00
Kerollmops
268a9ef416
Move to the hgg crate 2023-06-27 12:32:38 +02:00
Clément Renault
642b0f3a1b
Expose a new vector field on the search route 2023-06-27 12:32:38 +02:00
ManyTheFish
63ca25290b Take into account small Review requests 2023-06-26 14:56:19 +02:00
ManyTheFish
59f64a5256 Return an error when an attribute is not searchable 2023-06-26 14:56:19 +02:00
ManyTheFish
42709ea9a5 Fix clippy warnings 2023-06-26 14:55:57 +02:00
ManyTheFish
fb8fa07169 Restrict field ids in search context 2023-06-26 14:55:57 +02:00
ManyTheFish
0ccf1e2e40 Allow the search cache to store owned values 2023-06-26 14:55:57 +02:00
ManyTheFish
461b5118bd Add API search setting 2023-06-26 14:55:14 +02:00
Louis Dureuil
d26e9a96ec
Add score details to new search tests 2023-06-22 12:39:14 +02:00
Louis Dureuil
49c8bc4de6
Fix tests 2023-06-22 12:39:14 +02:00
Louis Dureuil
da833eb095
Expose the scores and detailed scores in the API 2023-06-22 12:39:14 +02:00
Louis Dureuil
701d44bd91
Store the scores for each bucket
Remove optimization where ranking rules are not executed on buckets of a single document
when the score needs to be computed
2023-06-22 12:39:14 +02:00
Louis Dureuil
c621a250a7
Score for graph based ranking rules
Count phrases in matchingWords and maxMatchingWords
2023-06-22 12:39:14 +02:00
Louis Dureuil
8939e85f60
Add rank_to_score for graph based ranking rules 2023-06-22 12:39:14 +02:00
Louis Dureuil
fa41d2489e
Score for sort 2023-06-22 12:39:14 +02:00
Louis Dureuil
59c5b992c2
Score for geosort 2023-06-22 12:39:14 +02:00
Louis Dureuil
2ea8194c18
Score for exact_attributes 2023-06-22 12:39:14 +02:00
Louis Dureuil
421df64602
RankingRuleOutput now contains a Score 2023-06-22 12:39:14 +02:00
Louis Dureuil
f050634b1e
add virtual conditions to fid and position to always have the max cost 2023-06-20 10:07:18 +02:00
Louis Dureuil
becf1f066a
Change how the cost of removing words is computed 2023-06-20 09:45:43 +02:00
Louis Dureuil
701d299369
Remove out-of-date comment 2023-06-20 09:45:42 +02:00
Louis Dureuil
a20e4d447c
Position now takes into account the distance to the position of the word in the query
it used to be based on the distance to the position 0
2023-06-20 09:45:42 +02:00
Louis Dureuil
af57c3c577
Proximity costs 0 for documents that are perfectly matching 2023-06-20 09:45:42 +02:00
Louis Dureuil
0c40ef6911
Fix sort id 2023-06-20 09:45:42 +02:00
Loïc Lecrenier
2da86b31a6 Remove comments and add documentation 2023-06-14 12:39:42 +02:00
Louis Dureuil
a2a3b8c973
Fix offset difference between query and indexing for hard separators 2023-06-08 12:07:12 +02:00
Louis Dureuil
1dfc4038ab
Add test that fails before PR and passes now 2023-05-29 11:58:26 +02:00
Louis Dureuil
73198179f1
Consistently use wrapping add to avoid overflow in debug when query starts with a separator 2023-05-29 11:54:12 +02:00
meili-bors[bot]
2e49d6aec1
Merge #3768
3768: Fix bugs in graph-based ranking rules + make `words` a graph-based ranking rule r=dureuill a=loiclec

This PR contains three changes:

## 1. Don't call the `words` ranking rule if the term matching strategy is `All`

This is because the purpose of `words` is only to remove nodes from the query graph. It would never do any useful work when the matching strategy was `All`. Remember that the universe was already computed before by computing all the docids corresponding to the "maximally reduced" query graph, which, in the case of `All`, is equal to the original graph.

## 2. The `words` ranking rule is replaced by a graph-based ranking rule. 

This is for three reasons:

1. **performance**: graph-based ranking rules benefit from a lot of optimisations by default, which ensures that they are never too slow. The previous implementation of `words` could call `compute_query_graph_docids` many times if some words had to be removed from the query, which would be quite expensive. I was especially worried about its performance in cases where it is placed right after the `sort` ranking rule. Furthermore, `compute_query_graph_docids` would clone a lot of bitmaps many times unnecessarily.

2. **consistency**: every other ranking rule (except `sort`) is graph-based. It makes sense to implement `words` like that as well. It will automatically benefit from all the features, optimisations, and bug fixes that all the other ranking rules get.

3. **surfacing bugs**: as the first ranking rule to be called (most of the time), I'd like `words` to behave the same as the other ranking rules so that we can quickly detect bugs in our graph algorithms. This actually already happened, which is why this PR also contains a bug fix.

## 3. Fix the `update_all_costs_before_nodes` function

It is a bit difficult to explain what was wrong, but I'll try. The bug happened when we had graphs like:
<img width="730" alt="Screenshot 2023-05-16 at 10 58 57" src="https://github.com/meilisearch/meilisearch/assets/6040237/40db1a68-d852-4e89-99d5-0d65757242a7">
and we gave the node `is` as argument.

Then, we'd walk backwards from the node breadth-first. We'd update the costs of:
1. `sun`
2. `thesun`
3. `start`
4. `the`

which is an incorrect order. The correct order is:

1. `sun`
2. `thesun`
3. `the`
4. `start`

That is, we can only update the cost of a node when all of its successors have either already been visited or were not affected by the update to the node passed as argument. To solve this bug, I factored out the graph-traversal logic into a `traverse_breadth_first_backward` function.


Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2023-05-23 13:28:08 +00:00
Louis Dureuil
51043f78f0
Remove trailing whitespace 2023-05-23 15:27:25 +02:00
Louis Dureuil
a490a11325
Add explanatory comment on the way we're recomputing costs 2023-05-23 15:24:24 +02:00
Loïc Lecrenier
ec8f685d84 Fix bug in cheapest path algorithm 2023-05-16 17:01:30 +02:00
Loïc Lecrenier
5758268866 Don't compute split_words for phrases 2023-05-16 17:01:18 +02:00
Loïc Lecrenier
3e19702de6 Update snapshot tests 2023-05-16 12:22:46 +02:00
Loïc Lecrenier
f6524a6858 Adjust costs of edges in position ranking rule
To ensure good performance
2023-05-16 11:28:56 +02:00
meili-bors[bot]
65ad8cce36
Merge #3741
3741: Add ngram support to the highlighter r=ManyTheFish a=loiclec

This PR fixes a bug introduced by the search refactor, where ngrams were not highlighted. 

The solution was to add the ngrams to the vector of `LocatedQueryTerm` that is given to the `MatchingWords` structure.

Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
2023-05-16 09:03:31 +00:00
Loïc Lecrenier
a37da36766 Implement words as a graph-based ranking rule and fix some bugs 2023-05-16 10:42:11 +02:00
Loïc Lecrenier
85d96d35a8 Highlight ngram matches as well 2023-05-16 10:39:36 +02:00
Loïc Lecrenier
4d352a21ac Compute split words derivations of terms that don't accept typos 2023-05-10 13:31:19 +02:00