mirror of
https://github.com/meilisearch/meilisearch.git
synced 2025-07-20 05:20:36 +00:00
Compare commits
1 Commits
check-wind
...
tmp-spawn-
| Author | SHA1 | Date | |
|---|---|---|---|
| b3952e8b3d |
9
.github/workflows/bench-pr.yml
vendored
9
.github/workflows/bench-pr.yml
vendored
@ -43,11 +43,4 @@ jobs:
|
||||
|
||||
- name: Run benchmarks on PR ${{ github.event.issue.id }}
|
||||
run: |
|
||||
cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" \
|
||||
--dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" \
|
||||
--reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" \
|
||||
-- ${{ steps.command.outputs.command-arguments }} > benchlinks.txt
|
||||
|
||||
- name: Send comment in PR
|
||||
run: |
|
||||
gh pr comment ${{github.event.issue.number}} --body-file benchlinks.txt
|
||||
cargo xtask bench --api-key "${{ secrets.BENCHMARK_API_KEY }}" --dashboard-url "${{ vars.BENCHMARK_DASHBOARD_URL }}" --reason "[Comment](${{ github.event.comment.html_url }}) on [#${{ github.event.issue.number }}](${{ github.event.issue.html_url }})" -- ${{ steps.command.outputs.command-arguments }}
|
||||
18
.github/workflows/test-suite.yml
vendored
18
.github/workflows/test-suite.yml
vendored
@ -56,12 +56,6 @@ jobs:
|
||||
matrix:
|
||||
os: [macos-12, windows-2022]
|
||||
steps:
|
||||
- name: Check free disk space on C
|
||||
run: |
|
||||
fsutil volume diskfree c:
|
||||
- name: Check free disk space on D
|
||||
run: |
|
||||
fsutil volume diskfree d:
|
||||
- uses: actions/checkout@v3
|
||||
- name: Cache dependencies
|
||||
uses: Swatinem/rust-cache@v2.7.1
|
||||
@ -69,23 +63,11 @@ jobs:
|
||||
with:
|
||||
toolchain: stable
|
||||
override: true
|
||||
- name: Check free disk space on C
|
||||
run: |
|
||||
fsutil volume diskfree c:
|
||||
- name: Check free disk space on D
|
||||
run: |
|
||||
fsutil volume diskfree d:
|
||||
- name: Run cargo check without any default features
|
||||
uses: actions-rs/cargo@v1
|
||||
with:
|
||||
command: build
|
||||
args: --locked --release --no-default-features --all
|
||||
- name: Check free disk space on C
|
||||
run: |
|
||||
fsutil volume diskfree c:
|
||||
- name: Check free disk space on D
|
||||
run: |
|
||||
fsutil volume diskfree d:
|
||||
- name: Run cargo test
|
||||
uses: actions-rs/cargo@v1
|
||||
with:
|
||||
|
||||
@ -187,8 +187,8 @@ They are JSON files with the following structure (comments are not actually supp
|
||||
},
|
||||
// Core of the workload.
|
||||
// A list of commands to run sequentially.
|
||||
// Optional: A precommand is a request to the Meilisearch instance that is executed before the profiling runs.
|
||||
"precommands": [
|
||||
// A command is a request to the Meilisearch instance that is executed while the profiling runs.
|
||||
"commands": [
|
||||
{
|
||||
// Meilisearch route to call. `http://localhost:7700/` will be prepended.
|
||||
"route": "indexes/movies/settings",
|
||||
@ -224,11 +224,8 @@ They are JSON files with the following structure (comments are not actually supp
|
||||
// - DontWait: run the next command without waiting the response to this one.
|
||||
// - WaitForResponse: run the next command as soon as the response from the server is received.
|
||||
// - WaitForTask: run the next command once **all** the Meilisearch tasks created up to now have finished processing.
|
||||
"synchronous": "WaitForTask"
|
||||
}
|
||||
],
|
||||
// A command is a request to the Meilisearch instance that is executed while the profiling runs.
|
||||
"commands": [
|
||||
"synchronous": "DontWait"
|
||||
},
|
||||
{
|
||||
"route": "indexes/movies/documents",
|
||||
"method": "POST",
|
||||
|
||||
240
Cargo.lock
generated
240
Cargo.lock
generated
@ -80,7 +80,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "e01ed3140b2f8d422c68afa1ed2e85d996ea619c988ac834d255db32138655cb"
|
||||
dependencies = [
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -378,9 +378,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "arroy"
|
||||
version = "0.3.1"
|
||||
version = "0.2.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "73897699bf04bac935c0b120990d2a511e91e563e0f9769f9c8bb983d98dfbc9"
|
||||
checksum = "efddeb1e7c32a551cc07ef4c3e181e3cd5478fdaf4f0bd799983171c1f6efe57"
|
||||
dependencies = [
|
||||
"bytemuck",
|
||||
"byteorder",
|
||||
@ -424,7 +424,7 @@ checksum = "16e62a023e7c117e27523144c5d2459f4397fcc3cab0085af8e2224f643a0193"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -435,7 +435,7 @@ checksum = "c980ee35e870bd1a4d2c8294d4c04d0499e67bca1e4b5cefcc693c2fa00caea9"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -486,12 +486,6 @@ version = "0.21.7"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "9d297deb1925b89f2ccc13d7635fa0714f12c87adce1c75356b39ca9b7178567"
|
||||
|
||||
[[package]]
|
||||
name = "base64"
|
||||
version = "0.22.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "72b3254f16251a8381aa12e40e3c4d2f0199f8c6508fbecb9d91f575e0fbb8c6"
|
||||
|
||||
[[package]]
|
||||
name = "base64ct"
|
||||
version = "1.6.0"
|
||||
@ -558,7 +552,7 @@ dependencies = [
|
||||
"regex",
|
||||
"rustc-hash",
|
||||
"shlex",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -691,7 +685,7 @@ checksum = "4da9a32f3fed317401fa3c862968128267c3106685286e15d5aaa3d7389c2f60"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -851,9 +845,9 @@ checksum = "37b2a672a2cb129a2e41c10b1224bb368f9f37a2b16b612598138befd7b37eb5"
|
||||
|
||||
[[package]]
|
||||
name = "cc"
|
||||
version = "1.0.94"
|
||||
version = "1.0.90"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "17f6e324229dc011159fcc089755d1e2e216a90d43a7dea6853ca740b84f35e7"
|
||||
checksum = "8cd6604a82acf3039f1144f54b8eb34e91ffba622051189e71b781822d5ee1f5"
|
||||
dependencies = [
|
||||
"jobserver",
|
||||
"libc",
|
||||
@ -998,7 +992,7 @@ dependencies = [
|
||||
"heck",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1310,7 +1304,7 @@ dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"strsim",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1332,7 +1326,7 @@ checksum = "836a9bbc7ad63342d6d6e7b815ccab164bc77a2d95d84bc3117a8c0d5c98e2d5"
|
||||
dependencies = [
|
||||
"darling_core 0.20.3",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1362,7 +1356,7 @@ checksum = "67e77553c4162a157adbf834ebae5b415acbecbeafc7a74b0e886657506a7611"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1466,7 +1460,7 @@ dependencies = [
|
||||
"convert_case 0.6.0",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1536,9 +1530,9 @@ checksum = "fea41bba32d969b513997752735605054bc0dfa92b4c56bf1189f2e174be7a10"
|
||||
|
||||
[[package]]
|
||||
name = "doxygen-rs"
|
||||
version = "0.4.2"
|
||||
version = "0.2.2"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "415b6ec780d34dcf624666747194393603d0373b7141eef01d12ee58881507d9"
|
||||
checksum = "bff670ea0c9bbb8414e7efa6e23ebde2b8f520a7eef78273a3918cf1903e7505"
|
||||
dependencies = [
|
||||
"phf",
|
||||
]
|
||||
@ -1684,7 +1678,7 @@ dependencies = [
|
||||
"heck",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1704,7 +1698,7 @@ checksum = "03cdc46ec28bd728e67540c528013c6a10eb69a02eb31078a1bda695438cbfb8"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -1787,7 +1781,7 @@ dependencies = [
|
||||
"darling 0.20.3",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
"uuid",
|
||||
]
|
||||
|
||||
@ -1919,7 +1913,7 @@ checksum = "87750cf4b7a4c0625b1529e4c543c2182106e4dedc60a2a6455e00d212c489ac"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -2123,9 +2117,9 @@ checksum = "36d244a08113319b5ebcabad2b8b7925732d15eec46d7e7ac3c11734f3b7a6ad"
|
||||
|
||||
[[package]]
|
||||
name = "getrandom"
|
||||
version = "0.2.14"
|
||||
version = "0.2.12"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "94b22e06ecb0110981051723910cbf0b5f5e09a2062dd7663334ee79a9d1286c"
|
||||
checksum = "190092ea657667030ac6a35e305e62fc4dd69fd98ac98631e5d3a2b1575a12b5"
|
||||
dependencies = [
|
||||
"cfg-if",
|
||||
"js-sys",
|
||||
@ -2262,11 +2256,12 @@ checksum = "95505c38b4572b2d910cecb0281560f54b440a19336cbbcb27bf6ce6adc6f5a8"
|
||||
|
||||
[[package]]
|
||||
name = "heed"
|
||||
version = "0.20.1"
|
||||
version = "0.20.0-alpha.9"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "6f7acb9683d7c7068aa46d47557bfa4e35a277964b350d9504a87b03610163fd"
|
||||
checksum = "9648a50991c86df7d00c56c268c27754fcf4c80be2ba57fc4a00dc928c6fe934"
|
||||
dependencies = [
|
||||
"bitflags 2.5.0",
|
||||
"bytemuck",
|
||||
"byteorder",
|
||||
"heed-traits",
|
||||
"heed-types",
|
||||
@ -2280,15 +2275,15 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "heed-traits"
|
||||
version = "0.20.0"
|
||||
version = "0.20.0-alpha.9"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "eb3130048d404c57ce5a1ac61a903696e8fcde7e8c2991e9fcfc1f27c3ef74ff"
|
||||
checksum = "5ab0b7d9cde969ad36dde692e487dc89d97f7168bf6a7bd3b894ad4bf7278298"
|
||||
|
||||
[[package]]
|
||||
name = "heed-types"
|
||||
version = "0.20.0"
|
||||
version = "0.20.0-alpha.9"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "3cb0d6ba3700c9a57e83c013693e3eddb68a6d9b6781cacafc62a0d992e8ddb3"
|
||||
checksum = "f0cb3567a7363f28b597bf6e9897b9466397951dd0e52df2c8196dd8a71af44a"
|
||||
dependencies = [
|
||||
"bincode",
|
||||
"byteorder",
|
||||
@ -2418,7 +2413,7 @@ dependencies = [
|
||||
"futures-util",
|
||||
"http 0.2.11",
|
||||
"hyper",
|
||||
"rustls 0.21.12",
|
||||
"rustls 0.21.10",
|
||||
"tokio",
|
||||
"tokio-rustls",
|
||||
]
|
||||
@ -2464,6 +2459,7 @@ dependencies = [
|
||||
"meilisearch-auth",
|
||||
"meilisearch-types",
|
||||
"page_size 0.5.0",
|
||||
"puffin",
|
||||
"rayon",
|
||||
"roaring",
|
||||
"serde",
|
||||
@ -3161,7 +3157,7 @@ checksum = "fc2fb41a9bb4257a3803154bdf7e2df7d45197d1941c9b1a90ad815231630721"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -3187,13 +3183,14 @@ checksum = "f9d642685b028806386b2b6e75685faadd3eb65a85fff7df711ce18446a422da"
|
||||
|
||||
[[package]]
|
||||
name = "lmdb-master-sys"
|
||||
version = "0.2.0"
|
||||
version = "0.1.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "dc9048db3a58c0732d7236abc4909058f9d2708cfb6d7d047eb895fddec6419a"
|
||||
checksum = "629c123f5321b48fa4f8f4d3b868165b748d9ba79c7103fb58e3a94f736bcedd"
|
||||
dependencies = [
|
||||
"cc",
|
||||
"doxygen-rs",
|
||||
"libc",
|
||||
"pkg-config",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -3216,9 +3213,9 @@ checksum = "e34f76eb3611940e0e7d53a9aaa4e6a3151f69541a282fd0dad5571420c53ff1"
|
||||
|
||||
[[package]]
|
||||
name = "lock_api"
|
||||
version = "0.4.11"
|
||||
version = "0.4.10"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "3c168f8615b12bc01f9c17e2eb0cc07dcae1940121185446edc3744920e8ef45"
|
||||
checksum = "c1cc9717a20b1bb222f333e6a92fd32f7d8a18ddc5a3191a11af45dcbf4dcd16"
|
||||
dependencies = [
|
||||
"autocfg",
|
||||
"scopeguard",
|
||||
@ -3230,6 +3227,12 @@ version = "0.4.21"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "90ed8c1e510134f979dbc4f070f87d4313098b704861a105fe34231c70a3901c"
|
||||
|
||||
[[package]]
|
||||
name = "lz4_flex"
|
||||
version = "0.10.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "8b8c72594ac26bfd34f2d99dfced2edfaddfe8a476e3ff2ca0eb293d925c4f83"
|
||||
|
||||
[[package]]
|
||||
name = "macro_rules_attribute"
|
||||
version = "0.2.0"
|
||||
@ -3255,7 +3258,7 @@ dependencies = [
|
||||
"once_cell",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -3334,11 +3337,12 @@ dependencies = [
|
||||
"pin-project-lite",
|
||||
"platform-dirs",
|
||||
"prometheus",
|
||||
"puffin",
|
||||
"rand",
|
||||
"rayon",
|
||||
"regex",
|
||||
"reqwest",
|
||||
"rustls 0.21.12",
|
||||
"rustls 0.21.10",
|
||||
"rustls-pemfile",
|
||||
"segment",
|
||||
"serde",
|
||||
@ -3501,6 +3505,7 @@ dependencies = [
|
||||
"obkv",
|
||||
"once_cell",
|
||||
"ordered-float",
|
||||
"puffin",
|
||||
"rand",
|
||||
"rand_pcg",
|
||||
"rayon",
|
||||
@ -3593,7 +3598,7 @@ checksum = "371717c0a5543d6a800cac822eac735aa7d2d2fbb41002e9856a4089532dbdce"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -3937,7 +3942,7 @@ dependencies = [
|
||||
"pest_meta",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -3991,7 +3996,7 @@ dependencies = [
|
||||
"phf_shared",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -4020,7 +4025,7 @@ checksum = "266c042b60c9c76b8d53061e52b2e0d1116abc57cefc8c5cd671619a56ac3690"
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -4128,9 +4133,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
@ -4171,6 +4176,23 @@ version = "2.28.0"
|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"lz4_flex",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
@ -4185,9 +4207,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
"proc-macro2",
|
||||
]
|
||||
@ -4369,7 +4391,7 @@ dependencies = [
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"serde",
|
||||
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|
||||
@ -4483,9 +4505,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
@ -4495,9 +4517,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
@ -4518,9 +4540,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
|
||||
[[package]]
|
||||
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|
||||
@ -4621,9 +4643,9 @@ checksum = "a3f0bf26fd526d2a95683cd0f87bf103b8539e2ca1ef48ce002d67aad59aa0b4"
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
@ -4639,20 +4661,20 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
@ -4919,7 +4941,7 @@ dependencies = [
|
||||
"proc-macro2",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
@ -4941,9 +4963,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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@ -4967,7 +4989,7 @@ checksum = "c8af7666ab7b6390ab78131fb5b0fce11d6b7a6951602017c35fa82800708971"
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||||
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||||
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||||
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||||
|
||||
[[package]]
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||||
@ -5078,7 +5100,7 @@ checksum = "c61f3ba182994efc43764a46c018c347bc492c79f024e705f46567b418f6d4f7"
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||||
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||||
|
||||
[[package]]
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||||
@ -5221,7 +5243,7 @@ checksum = "5b8a1e28f2deaa14e508979454cb3a223b10b938b45af148bc0986de36f1923b"
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||||
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|
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||||
|
||||
[[package]]
|
||||
@ -5230,7 +5252,7 @@ version = "0.24.1"
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||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
@ -5332,7 +5354,7 @@ checksum = "34704c8d6ebcbc939824180af020566b01a7c01f80641264eba0999f6c2b6be7"
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|
||||
|
||||
[[package]]
|
||||
@ -5447,9 +5469,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
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|
||||
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||||
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||||
|
||||
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||||
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@ -5507,15 +5529,15 @@ checksum = "8ecb6da28b8a351d773b68d5825ac39017e680750f980f3a1a85cd8dd28a47c1"
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
@ -5681,7 +5703,7 @@ dependencies = [
|
||||
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|
||||
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|
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|
||||
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|
||||
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||||
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@ -5715,7 +5737,7 @@ checksum = "e94f17b526d0a461a191c78ea52bbce64071ed5c04c9ffe424dcb38f74171bb7"
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||||
@ -5812,7 +5834,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
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||||
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||||
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||||
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||||
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||||
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||||
|
||||
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|
||||
@ -5821,7 +5843,7 @@ version = "0.52.0"
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||||
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||||
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||||
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||||
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||||
|
||||
[[package]]
|
||||
@ -5848,7 +5870,7 @@ version = "0.52.0"
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||||
|
||||
[[package]]
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||||
@ -5883,17 +5905,17 @@ dependencies = [
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
|
||||
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@ -5910,9 +5932,9 @@ checksum = "91ae572e1b79dba883e0d315474df7305d12f569b400fcf90581b06062f7e1bc"
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||||
|
||||
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||||
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||||
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|
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|
||||
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||||
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||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
@ -5928,9 +5950,9 @@ checksum = "b2ef27e0d7bdfcfc7b868b317c1d32c641a6fe4629c171b8928c7b08d98d7cf3"
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
|
||||
[[package]]
|
||||
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|
||||
@ -5946,9 +5968,9 @@ checksum = "622a1962a7db830d6fd0a69683c80a18fda201879f0f447f065a3b7467daa241"
|
||||
|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
|
||||
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|
||||
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|
||||
@ -5964,9 +5986,9 @@ checksum = "4542c6e364ce21bf45d69fdd2a8e455fa38d316158cfd43b3ac1c5b1b19f8e00"
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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||||
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|
||||
|
||||
[[package]]
|
||||
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|
||||
@ -5982,9 +6004,9 @@ checksum = "ca2b8a661f7628cbd23440e50b05d705db3686f894fc9580820623656af974b1"
|
||||
|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
checksum = "5eee091590e89cc02ad514ffe3ead9eb6b660aedca2183455434b93546371a03"
|
||||
checksum = "3d6fa32db2bc4a2f5abeacf2b69f7992cd09dca97498da74a151a3132c26befd"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_gnullvm"
|
||||
@ -6000,9 +6022,9 @@ checksum = "7896dbc1f41e08872e9d5e8f8baa8fdd2677f29468c4e156210174edc7f7b953"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_gnullvm"
|
||||
version = "0.52.4"
|
||||
version = "0.52.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "77ca79f2451b49fa9e2af39f0747fe999fcda4f5e241b2898624dca97a1f2177"
|
||||
checksum = "1a657e1e9d3f514745a572a6846d3c7aa7dbe1658c056ed9c3344c4109a6949e"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_msvc"
|
||||
@ -6018,9 +6040,9 @@ checksum = "1a515f5799fe4961cb532f983ce2b23082366b898e52ffbce459c86f67c8378a"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_msvc"
|
||||
version = "0.52.4"
|
||||
version = "0.52.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "32b752e52a2da0ddfbdbcc6fceadfeede4c939ed16d13e648833a61dfb611ed8"
|
||||
checksum = "dff9641d1cd4be8d1a070daf9e3773c5f67e78b4d9d42263020c057706765c04"
|
||||
|
||||
[[package]]
|
||||
name = "winnow"
|
||||
@ -6118,7 +6140,7 @@ checksum = "9e6936f0cce458098a201c245a11bef556c6a0181129c7034d10d76d1ec3a2b8"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
"synstructure",
|
||||
]
|
||||
|
||||
@ -6139,7 +6161,7 @@ checksum = "9ce1b18ccd8e73a9321186f97e46f9f04b778851177567b1975109d26a08d2a6"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@ -6159,7 +6181,7 @@ checksum = "e6a647510471d372f2e6c2e6b7219e44d8c574d24fdc11c610a61455782f18c3"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.60",
|
||||
"syn 2.0.58",
|
||||
"synstructure",
|
||||
]
|
||||
|
||||
|
||||
@ -197,140 +197,6 @@ pub(crate) mod test {
|
||||
use super::*;
|
||||
use crate::reader::v6::RuntimeTogglableFeatures;
|
||||
|
||||
#[test]
|
||||
fn import_dump_v6_with_vectors() {
|
||||
// dump containing two indexes
|
||||
//
|
||||
// "vector", configured with an embedder
|
||||
// contains:
|
||||
// - one document with an overriden vector,
|
||||
// - one document with a natural vector
|
||||
// - one document with a _vectors map containing one additional embedder name and a natural vector
|
||||
// - one document with a _vectors map containing one additional embedder name and an overriden vector
|
||||
//
|
||||
// "novector", no embedder
|
||||
// contains:
|
||||
// - a document without vector
|
||||
// - a document with a random _vectors field
|
||||
let dump = File::open("tests/assets/v6-with-vectors.dump").unwrap();
|
||||
let mut dump = DumpReader::open(dump).unwrap();
|
||||
|
||||
// top level infos
|
||||
insta::assert_display_snapshot!(dump.date().unwrap(), @"2024-05-16 15:51:34.151044 +00:00:00");
|
||||
insta::assert_debug_snapshot!(dump.instance_uid().unwrap(), @"None");
|
||||
|
||||
// tasks
|
||||
let tasks = dump.tasks().unwrap().collect::<Result<Vec<_>>>().unwrap();
|
||||
let (tasks, update_files): (Vec<_>, Vec<_>) = tasks.into_iter().unzip();
|
||||
meili_snap::snapshot_hash!(meili_snap::json_string!(tasks), @"278f63325ef06ca04d01df98d8207b94");
|
||||
assert_eq!(update_files.len(), 10);
|
||||
assert!(update_files[0].is_none()); // the dump creation
|
||||
assert!(update_files[1].is_none());
|
||||
assert!(update_files[2].is_none());
|
||||
assert!(update_files[3].is_none());
|
||||
assert!(update_files[4].is_none());
|
||||
assert!(update_files[5].is_none());
|
||||
assert!(update_files[6].is_none());
|
||||
assert!(update_files[7].is_none());
|
||||
assert!(update_files[8].is_none());
|
||||
assert!(update_files[9].is_none());
|
||||
|
||||
// indexes
|
||||
let mut indexes = dump.indexes().unwrap().collect::<Result<Vec<_>>>().unwrap();
|
||||
// the index are not ordered in any way by default
|
||||
indexes.sort_by_key(|index| index.metadata().uid.to_string());
|
||||
|
||||
let mut vector_index = indexes.pop().unwrap();
|
||||
let mut novector_index = indexes.pop().unwrap();
|
||||
assert!(indexes.is_empty());
|
||||
|
||||
// vector
|
||||
|
||||
insta::assert_json_snapshot!(vector_index.metadata(), @r###"
|
||||
{
|
||||
"uid": "vector",
|
||||
"primaryKey": "id",
|
||||
"createdAt": "2024-05-16T15:33:17.240962Z",
|
||||
"updatedAt": "2024-05-16T15:40:55.723052Z"
|
||||
}
|
||||
"###);
|
||||
|
||||
{
|
||||
let documents: Result<Vec<_>> = vector_index.documents().unwrap().collect();
|
||||
let mut documents = documents.unwrap();
|
||||
assert_eq!(documents.len(), 4);
|
||||
|
||||
documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document);
|
||||
}
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document);
|
||||
}
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document);
|
||||
}
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document);
|
||||
}
|
||||
}
|
||||
|
||||
// novector
|
||||
|
||||
insta::assert_json_snapshot!(novector_index.metadata(), @r###"
|
||||
{
|
||||
"uid": "novector",
|
||||
"primaryKey": "id",
|
||||
"createdAt": "2024-05-16T15:33:03.568055Z",
|
||||
"updatedAt": "2024-05-16T15:33:07.530217Z"
|
||||
}
|
||||
"###);
|
||||
|
||||
insta::assert_json_snapshot!(novector_index.settings().unwrap().embedders, @"null");
|
||||
|
||||
{
|
||||
let documents: Result<Vec<_>> = novector_index.documents().unwrap().collect();
|
||||
let mut documents = documents.unwrap();
|
||||
assert_eq!(documents.len(), 2);
|
||||
|
||||
documents.sort_by_key(|doc| doc.get("id").unwrap().to_string());
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document, @r###"
|
||||
{
|
||||
"id": "e1",
|
||||
"other": "random1",
|
||||
"_vectors": "toto"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
{
|
||||
let document = documents.pop().unwrap();
|
||||
insta::assert_json_snapshot!(document, @r###"
|
||||
{
|
||||
"id": "e0",
|
||||
"other": "random0"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
}
|
||||
|
||||
assert_eq!(
|
||||
dump.features().unwrap().unwrap(),
|
||||
RuntimeTogglableFeatures { vector_store: true, ..Default::default() }
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn import_dump_v6_experimental() {
|
||||
let dump = File::open("tests/assets/v6-with-experimental.dump").unwrap();
|
||||
|
||||
@ -1,783 +0,0 @@
|
||||
---
|
||||
source: dump/src/reader/mod.rs
|
||||
expression: document
|
||||
---
|
||||
{
|
||||
"id": "e3",
|
||||
"desc": "overriden vector + map",
|
||||
"_vectors": {
|
||||
"default": [
|
||||
0.2,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
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@ -1,786 +0,0 @@
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@ -1,780 +0,0 @@
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---
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|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1,
|
||||
0.1
|
||||
]
|
||||
}
|
||||
}
|
||||
Binary file not shown.
@ -568,7 +568,7 @@ pub mod tests {
|
||||
insta::assert_display_snapshot!(p(r"title = 'foo\\\\'"), @r#"{title} = {foo\\}"#);
|
||||
insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\'"), @r#"{title} = {foo\\\}"#);
|
||||
insta::assert_display_snapshot!(p(r"title = 'foo\\\\\\\\'"), @r#"{title} = {foo\\\\}"#);
|
||||
// but it also works with other sequences
|
||||
// but it also works with other sequencies
|
||||
insta::assert_display_snapshot!(p(r#"title = 'foo\x20\n\t\"\'"'"#), @"{title} = {foo \n\t\"\'\"}");
|
||||
}
|
||||
|
||||
|
||||
@ -22,6 +22,7 @@ flate2 = "1.0.28"
|
||||
meilisearch-auth = { path = "../meilisearch-auth" }
|
||||
meilisearch-types = { path = "../meilisearch-types" }
|
||||
page_size = "0.5.0"
|
||||
puffin = { version = "0.16.0", features = ["serialization"] }
|
||||
rayon = "1.8.1"
|
||||
roaring = { version = "0.10.2", features = ["serde"] }
|
||||
serde = { version = "1.0.195", features = ["derive"] }
|
||||
@ -36,7 +37,7 @@ time = { version = "0.3.31", features = [
|
||||
"macros",
|
||||
] }
|
||||
tracing = "0.1.40"
|
||||
ureq = "2.9.7"
|
||||
ureq = "2.9.1"
|
||||
uuid = { version = "1.6.1", features = ["serde", "v4"] }
|
||||
|
||||
[dev-dependencies]
|
||||
|
||||
@ -13,7 +13,7 @@ We can combine the two tasks in a single batch:
|
||||
1. import documents X and Y
|
||||
|
||||
Processing this batch is functionally equivalent to processing the two
|
||||
tasks individually, but should be much faster since we are only performing
|
||||
tasks individally, but should be much faster since we are only performing
|
||||
one indexing operation.
|
||||
*/
|
||||
|
||||
@ -31,9 +31,6 @@ use meilisearch_types::milli::heed::CompactionOption;
|
||||
use meilisearch_types::milli::update::{
|
||||
IndexDocumentsConfig, IndexDocumentsMethod, IndexerConfig, Settings as MilliSettings,
|
||||
};
|
||||
use meilisearch_types::milli::vector::parsed_vectors::{
|
||||
ExplicitVectors, VectorOrArrayOfVectors, RESERVED_VECTORS_FIELD_NAME,
|
||||
};
|
||||
use meilisearch_types::milli::{self, Filter};
|
||||
use meilisearch_types::settings::{apply_settings_to_builder, Settings, Unchecked};
|
||||
use meilisearch_types::tasks::{Details, IndexSwap, Kind, KindWithContent, Status, Task};
|
||||
@ -529,6 +526,8 @@ impl IndexScheduler {
|
||||
#[cfg(test)]
|
||||
self.maybe_fail(crate::tests::FailureLocation::InsideCreateBatch)?;
|
||||
|
||||
puffin::profile_function!();
|
||||
|
||||
let enqueued = &self.get_status(rtxn, Status::Enqueued)?;
|
||||
let to_cancel = self.get_kind(rtxn, Kind::TaskCancelation)? & enqueued;
|
||||
|
||||
@ -637,6 +636,8 @@ impl IndexScheduler {
|
||||
self.breakpoint(crate::Breakpoint::InsideProcessBatch);
|
||||
}
|
||||
|
||||
puffin::profile_function!(batch.to_string());
|
||||
|
||||
match batch {
|
||||
Batch::TaskCancelation { mut task, previous_started_at, previous_processing_tasks } => {
|
||||
// 1. Retrieve the tasks that matched the query at enqueue-time.
|
||||
@ -784,12 +785,10 @@ impl IndexScheduler {
|
||||
let dst = temp_snapshot_dir.path().join("auth");
|
||||
fs::create_dir_all(&dst)?;
|
||||
// TODO We can't use the open_auth_store_env function here but we should
|
||||
let auth = unsafe {
|
||||
milli::heed::EnvOpenOptions::new()
|
||||
.map_size(1024 * 1024 * 1024) // 1 GiB
|
||||
.max_dbs(2)
|
||||
.open(&self.auth_path)
|
||||
}?;
|
||||
let auth = milli::heed::EnvOpenOptions::new()
|
||||
.map_size(1024 * 1024 * 1024) // 1 GiB
|
||||
.max_dbs(2)
|
||||
.open(&self.auth_path)?;
|
||||
auth.copy_to_file(dst.join("data.mdb"), CompactionOption::Enabled)?;
|
||||
|
||||
// 5. Copy and tarball the flat snapshot
|
||||
@ -915,55 +914,8 @@ impl IndexScheduler {
|
||||
if self.must_stop_processing.get() {
|
||||
return Err(Error::AbortedTask);
|
||||
}
|
||||
|
||||
let (id, doc) = ret?;
|
||||
|
||||
let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
|
||||
|
||||
'inject_vectors: {
|
||||
let embeddings = index.embeddings(&rtxn, id)?;
|
||||
|
||||
if embeddings.is_empty() {
|
||||
break 'inject_vectors;
|
||||
}
|
||||
|
||||
let vectors = document
|
||||
.entry(RESERVED_VECTORS_FIELD_NAME.to_owned())
|
||||
.or_insert(serde_json::Value::Object(Default::default()));
|
||||
|
||||
let serde_json::Value::Object(vectors) = vectors else {
|
||||
return Err(milli::Error::UserError(
|
||||
milli::UserError::InvalidVectorsMapType {
|
||||
document_id: {
|
||||
if let Ok(Some(Ok(index))) = index
|
||||
.external_id_of(&rtxn, std::iter::once(id))
|
||||
.map(|it| it.into_iter().next())
|
||||
{
|
||||
index
|
||||
} else {
|
||||
format!("internal docid={id}")
|
||||
}
|
||||
},
|
||||
value: vectors.clone(),
|
||||
},
|
||||
)
|
||||
.into());
|
||||
};
|
||||
|
||||
for (embedder_name, embeddings) in embeddings {
|
||||
// don't change the entry if it already exists, because it was user-provided
|
||||
vectors.entry(embedder_name).or_insert_with(|| {
|
||||
let embeddings = ExplicitVectors {
|
||||
embeddings: VectorOrArrayOfVectors::from_array_of_vectors(
|
||||
embeddings,
|
||||
),
|
||||
user_provided: false,
|
||||
};
|
||||
serde_json::to_value(embeddings).unwrap()
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
let (_id, doc) = ret?;
|
||||
let document = milli::obkv_to_json(&all_fields, &fields_ids_map, doc)?;
|
||||
index_dumper.push_document(&document)?;
|
||||
}
|
||||
|
||||
@ -1222,6 +1174,8 @@ impl IndexScheduler {
|
||||
index: &'i Index,
|
||||
operation: IndexOperation,
|
||||
) -> Result<Vec<Task>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
match operation {
|
||||
IndexOperation::DocumentClear { mut tasks, .. } => {
|
||||
let count = milli::update::ClearDocuments::new(index_wtxn, index).execute()?;
|
||||
|
||||
@ -68,6 +68,19 @@ impl RoFeatures {
|
||||
.into())
|
||||
}
|
||||
}
|
||||
|
||||
pub fn check_puffin(&self) -> Result<()> {
|
||||
if self.runtime.export_puffin_reports {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(FeatureNotEnabledError {
|
||||
disabled_action: "Outputting Puffin reports to disk",
|
||||
feature: "export puffin reports",
|
||||
issue_link: "https://github.com/meilisearch/product/discussions/693",
|
||||
}
|
||||
.into())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl FeatureData {
|
||||
|
||||
@ -32,6 +32,7 @@ pub fn snapshot_index_scheduler(scheduler: &IndexScheduler) -> String {
|
||||
features: _,
|
||||
max_number_of_tasks: _,
|
||||
max_number_of_batched_tasks: _,
|
||||
puffin_frame: _,
|
||||
wake_up: _,
|
||||
dumps_path: _,
|
||||
snapshots_path: _,
|
||||
|
||||
@ -33,6 +33,7 @@ pub type Result<T> = std::result::Result<T, Error>;
|
||||
pub type TaskId = u32;
|
||||
|
||||
use std::collections::{BTreeMap, HashMap};
|
||||
use std::fs::File;
|
||||
use std::io::{self, BufReader, Read};
|
||||
use std::ops::{Bound, RangeBounds};
|
||||
use std::path::{Path, PathBuf};
|
||||
@ -58,6 +59,7 @@ use meilisearch_types::milli::vector::{Embedder, EmbedderOptions, EmbeddingConfi
|
||||
use meilisearch_types::milli::{self, CboRoaringBitmapCodec, Index, RoaringBitmapCodec, BEU32};
|
||||
use meilisearch_types::task_view::TaskView;
|
||||
use meilisearch_types::tasks::{Kind, KindWithContent, Status, Task};
|
||||
use puffin::FrameView;
|
||||
use rayon::current_num_threads;
|
||||
use rayon::prelude::{IntoParallelIterator, ParallelIterator};
|
||||
use roaring::RoaringBitmap;
|
||||
@ -342,6 +344,9 @@ pub struct IndexScheduler {
|
||||
/// The Authorization header to send to the webhook URL.
|
||||
pub(crate) webhook_authorization_header: Option<String>,
|
||||
|
||||
/// A frame to output the indexation profiling files to disk.
|
||||
pub(crate) puffin_frame: Arc<puffin::GlobalFrameView>,
|
||||
|
||||
/// The path used to create the dumps.
|
||||
pub(crate) dumps_path: PathBuf,
|
||||
|
||||
@ -396,6 +401,7 @@ impl IndexScheduler {
|
||||
cleanup_enabled: self.cleanup_enabled,
|
||||
max_number_of_tasks: self.max_number_of_tasks,
|
||||
max_number_of_batched_tasks: self.max_number_of_batched_tasks,
|
||||
puffin_frame: self.puffin_frame.clone(),
|
||||
snapshots_path: self.snapshots_path.clone(),
|
||||
dumps_path: self.dumps_path.clone(),
|
||||
auth_path: self.auth_path.clone(),
|
||||
@ -447,12 +453,10 @@ impl IndexScheduler {
|
||||
)
|
||||
};
|
||||
|
||||
let env = unsafe {
|
||||
heed::EnvOpenOptions::new()
|
||||
.max_dbs(11)
|
||||
.map_size(budget.task_db_size)
|
||||
.open(options.tasks_path)
|
||||
}?;
|
||||
let env = heed::EnvOpenOptions::new()
|
||||
.max_dbs(11)
|
||||
.map_size(budget.task_db_size)
|
||||
.open(options.tasks_path)?;
|
||||
|
||||
let features = features::FeatureData::new(&env, options.instance_features)?;
|
||||
|
||||
@ -494,6 +498,7 @@ impl IndexScheduler {
|
||||
env,
|
||||
// we want to start the loop right away in case meilisearch was ctrl+Ced while processing things
|
||||
wake_up: Arc::new(SignalEvent::auto(true)),
|
||||
puffin_frame: Arc::new(puffin::GlobalFrameView::default()),
|
||||
autobatching_enabled: options.autobatching_enabled,
|
||||
cleanup_enabled: options.cleanup_enabled,
|
||||
max_number_of_tasks: options.max_number_of_tasks,
|
||||
@ -580,9 +585,9 @@ impl IndexScheduler {
|
||||
}
|
||||
|
||||
fn is_good_heed(tasks_path: &Path, map_size: usize) -> bool {
|
||||
if let Ok(env) = unsafe {
|
||||
if let Ok(env) =
|
||||
heed::EnvOpenOptions::new().map_size(clamp_to_page_size(map_size)).open(tasks_path)
|
||||
} {
|
||||
{
|
||||
env.prepare_for_closing().wait();
|
||||
true
|
||||
} else {
|
||||
@ -614,6 +619,10 @@ impl IndexScheduler {
|
||||
run.wake_up.wait();
|
||||
|
||||
loop {
|
||||
let puffin_enabled = run.features().check_puffin().is_ok();
|
||||
puffin::set_scopes_on(puffin_enabled);
|
||||
puffin::GlobalProfiler::lock().new_frame();
|
||||
|
||||
match run.tick() {
|
||||
Ok(TickOutcome::TickAgain(_)) => (),
|
||||
Ok(TickOutcome::WaitForSignal) => run.wake_up.wait(),
|
||||
@ -625,6 +634,31 @@ impl IndexScheduler {
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Let's write the previous frame to disk but only if
|
||||
// the user wanted to profile with puffin.
|
||||
if puffin_enabled {
|
||||
let mut frame_view = run.puffin_frame.lock();
|
||||
if !frame_view.is_empty() {
|
||||
let now = OffsetDateTime::now_utc();
|
||||
let mut file = match File::create(format!("{}.puffin", now)) {
|
||||
Ok(file) => file,
|
||||
Err(e) => {
|
||||
tracing::error!("{e}");
|
||||
continue;
|
||||
}
|
||||
};
|
||||
if let Err(e) = frame_view.save_to_writer(&mut file) {
|
||||
tracing::error!("{e}");
|
||||
}
|
||||
if let Err(e) = file.sync_all() {
|
||||
tracing::error!("{e}");
|
||||
}
|
||||
// We erase this frame view as it is no more useful. We want to
|
||||
// measure the new frames now that we exported the previous ones.
|
||||
*frame_view = FrameView::default();
|
||||
}
|
||||
}
|
||||
}
|
||||
})
|
||||
.unwrap();
|
||||
@ -1738,7 +1772,6 @@ mod tests {
|
||||
use big_s::S;
|
||||
use crossbeam::channel::RecvTimeoutError;
|
||||
use file_store::File;
|
||||
use insta::assert_json_snapshot;
|
||||
use meili_snap::{json_string, snapshot};
|
||||
use meilisearch_auth::AuthFilter;
|
||||
use meilisearch_types::document_formats::DocumentFormatError;
|
||||
@ -1816,7 +1849,7 @@ mod tests {
|
||||
|
||||
// To be 100% consistent between all test we're going to start the scheduler right now
|
||||
// and ensure it's in the expected starting state.
|
||||
let breakpoint = match receiver.recv_timeout(std::time::Duration::from_secs(10)) {
|
||||
let breakpoint = match receiver.recv_timeout(std::time::Duration::from_secs(1)) {
|
||||
Ok(b) => b,
|
||||
Err(RecvTimeoutError::Timeout) => {
|
||||
panic!("The scheduler seems to be waiting for a new task while your test is waiting for a breakpoint.")
|
||||
@ -1927,7 +1960,7 @@ mod tests {
|
||||
fn advance(&mut self) -> Breakpoint {
|
||||
let (breakpoint_1, b) = match self
|
||||
.test_breakpoint_rcv
|
||||
.recv_timeout(std::time::Duration::from_secs(50))
|
||||
.recv_timeout(std::time::Duration::from_secs(5))
|
||||
{
|
||||
Ok(b) => b,
|
||||
Err(RecvTimeoutError::Timeout) => {
|
||||
@ -1948,7 +1981,7 @@ mod tests {
|
||||
|
||||
let (breakpoint_2, b) = match self
|
||||
.test_breakpoint_rcv
|
||||
.recv_timeout(std::time::Duration::from_secs(50))
|
||||
.recv_timeout(std::time::Duration::from_secs(5))
|
||||
{
|
||||
Ok(b) => b,
|
||||
Err(RecvTimeoutError::Timeout) => {
|
||||
@ -4947,233 +4980,4 @@ mod tests {
|
||||
----------------------------------------------------------------------
|
||||
"###);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn import_vectors() {
|
||||
use meilisearch_types::settings::{Settings, Unchecked};
|
||||
use milli::update::Setting;
|
||||
|
||||
let (index_scheduler, mut handle) = IndexScheduler::test(true, vec![]);
|
||||
|
||||
let mut new_settings: Box<Settings<Unchecked>> = Box::default();
|
||||
let mut embedders = BTreeMap::default();
|
||||
let embedding_settings = milli::vector::settings::EmbeddingSettings {
|
||||
source: Setting::Set(milli::vector::settings::EmbedderSource::Rest),
|
||||
api_key: Setting::Set(S("My super secret")),
|
||||
url: Setting::Set(S("http://localhost:7777")),
|
||||
dimensions: Setting::Set(384),
|
||||
..Default::default()
|
||||
};
|
||||
embedders.insert(S("A_fakerest"), Setting::Set(embedding_settings));
|
||||
|
||||
let embedding_settings = milli::vector::settings::EmbeddingSettings {
|
||||
source: Setting::Set(milli::vector::settings::EmbedderSource::HuggingFace),
|
||||
model: Setting::Set(S("sentence-transformers/all-MiniLM-L6-v2")),
|
||||
revision: Setting::Set(S("e4ce9877abf3edfe10b0d82785e83bdcb973e22e")),
|
||||
document_template: Setting::Set(S("{{doc.doggo}} the {{doc.breed}} best doggo")),
|
||||
..Default::default()
|
||||
};
|
||||
embedders.insert(S("B_small_hf"), Setting::Set(embedding_settings));
|
||||
|
||||
new_settings.embedders = Setting::Set(embedders);
|
||||
|
||||
index_scheduler
|
||||
.register(
|
||||
KindWithContent::SettingsUpdate {
|
||||
index_uid: S("doggos"),
|
||||
new_settings,
|
||||
is_deletion: false,
|
||||
allow_index_creation: true,
|
||||
},
|
||||
None,
|
||||
false,
|
||||
)
|
||||
.unwrap();
|
||||
index_scheduler.assert_internally_consistent();
|
||||
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after_registering_settings_task_vectors");
|
||||
|
||||
{
|
||||
let rtxn = index_scheduler.read_txn().unwrap();
|
||||
let task = index_scheduler.get_task(&rtxn, 0).unwrap().unwrap();
|
||||
let task = meilisearch_types::task_view::TaskView::from_task(&task);
|
||||
insta::assert_json_snapshot!(task.details);
|
||||
}
|
||||
|
||||
handle.advance_n_successful_batches(1);
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "settings_update_processed_vectors");
|
||||
|
||||
{
|
||||
let rtxn = index_scheduler.read_txn().unwrap();
|
||||
let task = index_scheduler.get_task(&rtxn, 0).unwrap().unwrap();
|
||||
let task = meilisearch_types::task_view::TaskView::from_task(&task);
|
||||
insta::assert_json_snapshot!(task.details);
|
||||
}
|
||||
|
||||
let (fakerest_name, simple_hf_name, beagle_embed, lab_embed, patou_embed) = {
|
||||
let index = index_scheduler.index("doggos").unwrap();
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let configs = index.embedding_configs(&rtxn).unwrap();
|
||||
// for consistency with the below
|
||||
#[allow(clippy::get_first)]
|
||||
let (name, fakerest_config) = configs.get(0).unwrap();
|
||||
insta::assert_json_snapshot!(name, @r###""A_fakerest""###);
|
||||
insta::assert_json_snapshot!(fakerest_config.embedder_options);
|
||||
let fakerest_name = name.clone();
|
||||
|
||||
let (name, simple_hf_config) = configs.get(1).unwrap();
|
||||
insta::assert_json_snapshot!(name, @r###""B_small_hf""###);
|
||||
insta::assert_json_snapshot!(simple_hf_config.embedder_options);
|
||||
let simple_hf_name = name.clone();
|
||||
|
||||
let configs = index_scheduler.embedders(configs).unwrap();
|
||||
let (hf_embedder, _) = configs.get(&simple_hf_name).unwrap();
|
||||
let beagle_embed = hf_embedder.embed_one(S("Intel the beagle best doggo")).unwrap();
|
||||
let lab_embed = hf_embedder.embed_one(S("Max the lab best doggo")).unwrap();
|
||||
let patou_embed = hf_embedder.embed_one(S("kefir the patou best doggo")).unwrap();
|
||||
(fakerest_name, simple_hf_name, beagle_embed, lab_embed, patou_embed)
|
||||
};
|
||||
|
||||
// add one doc, specifying vectors
|
||||
|
||||
let doc = serde_json::json!(
|
||||
{
|
||||
"id": 0,
|
||||
"doggo": "Intel",
|
||||
"breed": "beagle",
|
||||
"_vectors": {
|
||||
&fakerest_name: {
|
||||
// this will never trigger regeneration, which is good because we can't actually generate with
|
||||
// this embedder
|
||||
"userProvided": true,
|
||||
"embeddings": beagle_embed,
|
||||
},
|
||||
&simple_hf_name: {
|
||||
// this will be regenerated on updates
|
||||
"userProvided": false,
|
||||
"embeddings": lab_embed,
|
||||
},
|
||||
"noise": [0.1, 0.2, 0.3]
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(0u128).unwrap();
|
||||
let documents_count = read_json(doc.to_string().as_bytes(), &mut file).unwrap();
|
||||
assert_eq!(documents_count, 1);
|
||||
file.persist().unwrap();
|
||||
|
||||
index_scheduler
|
||||
.register(
|
||||
KindWithContent::DocumentAdditionOrUpdate {
|
||||
index_uid: S("doggos"),
|
||||
primary_key: Some(S("id")),
|
||||
method: UpdateDocuments,
|
||||
content_file: uuid,
|
||||
documents_count,
|
||||
allow_index_creation: true,
|
||||
},
|
||||
None,
|
||||
false,
|
||||
)
|
||||
.unwrap();
|
||||
index_scheduler.assert_internally_consistent();
|
||||
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "after adding Intel");
|
||||
|
||||
handle.advance_one_successful_batch();
|
||||
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "adding Intel succeeds");
|
||||
|
||||
// check embeddings
|
||||
{
|
||||
let index = index_scheduler.index("doggos").unwrap();
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let embeddings = index.embeddings(&rtxn, 0).unwrap();
|
||||
|
||||
assert_json_snapshot!(embeddings[&simple_hf_name][0] == lab_embed, @"true");
|
||||
assert_json_snapshot!(embeddings[&fakerest_name][0] == beagle_embed, @"true");
|
||||
|
||||
let doc = index.documents(&rtxn, std::iter::once(0)).unwrap()[0].1;
|
||||
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
|
||||
let doc = obkv_to_json(
|
||||
&[
|
||||
fields_ids_map.id("doggo").unwrap(),
|
||||
fields_ids_map.id("breed").unwrap(),
|
||||
fields_ids_map.id("_vectors").unwrap(),
|
||||
],
|
||||
&fields_ids_map,
|
||||
doc,
|
||||
)
|
||||
.unwrap();
|
||||
assert_json_snapshot!(doc, {"._vectors.A_fakerest.embeddings" => "[vector]"});
|
||||
}
|
||||
|
||||
// update the doc, specifying vectors
|
||||
|
||||
let doc = serde_json::json!(
|
||||
{
|
||||
"id": 0,
|
||||
"doggo": "kefir",
|
||||
"breed": "patou",
|
||||
}
|
||||
);
|
||||
|
||||
let (uuid, mut file) = index_scheduler.create_update_file_with_uuid(1u128).unwrap();
|
||||
let documents_count = read_json(doc.to_string().as_bytes(), &mut file).unwrap();
|
||||
assert_eq!(documents_count, 1);
|
||||
file.persist().unwrap();
|
||||
|
||||
index_scheduler
|
||||
.register(
|
||||
KindWithContent::DocumentAdditionOrUpdate {
|
||||
index_uid: S("doggos"),
|
||||
primary_key: None,
|
||||
method: UpdateDocuments,
|
||||
content_file: uuid,
|
||||
documents_count,
|
||||
allow_index_creation: true,
|
||||
},
|
||||
None,
|
||||
false,
|
||||
)
|
||||
.unwrap();
|
||||
index_scheduler.assert_internally_consistent();
|
||||
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir");
|
||||
|
||||
handle.advance_one_successful_batch();
|
||||
snapshot!(snapshot_index_scheduler(&index_scheduler), name: "Intel to kefir succeeds");
|
||||
|
||||
{
|
||||
// check embeddings
|
||||
{
|
||||
let index = index_scheduler.index("doggos").unwrap();
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let embeddings = index.embeddings(&rtxn, 0).unwrap();
|
||||
|
||||
// automatically changed to patou
|
||||
assert_json_snapshot!(embeddings[&simple_hf_name][0] == patou_embed, @"true");
|
||||
// remained beagle because set to userProvided
|
||||
assert_json_snapshot!(embeddings[&fakerest_name][0] == beagle_embed, @"true");
|
||||
|
||||
let doc = index.documents(&rtxn, std::iter::once(0)).unwrap()[0].1;
|
||||
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
|
||||
let doc = obkv_to_json(
|
||||
&[
|
||||
fields_ids_map.id("doggo").unwrap(),
|
||||
fields_ids_map.id("breed").unwrap(),
|
||||
fields_ids_map.id("_vectors").unwrap(),
|
||||
],
|
||||
&fields_ids_map,
|
||||
doc,
|
||||
)
|
||||
.unwrap();
|
||||
assert_json_snapshot!(doc, {"._vectors.A_fakerest.embeddings" => "[vector]"});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,19 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: doc
|
||||
---
|
||||
{
|
||||
"doggo": "kefir",
|
||||
"breed": "patou",
|
||||
"_vectors": {
|
||||
"A_fakerest": {
|
||||
"embeddings": "[vector]",
|
||||
"userProvided": true
|
||||
},
|
||||
"noise": [
|
||||
0.1,
|
||||
0.2,
|
||||
0.3
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -1,20 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: task.details
|
||||
---
|
||||
{
|
||||
"embedders": {
|
||||
"A_fakerest": {
|
||||
"source": "rest",
|
||||
"apiKey": "MyXXXX...",
|
||||
"dimensions": 384,
|
||||
"url": "http://localhost:7777"
|
||||
},
|
||||
"B_small_hf": {
|
||||
"source": "huggingFace",
|
||||
"model": "sentence-transformers/all-MiniLM-L6-v2",
|
||||
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
|
||||
"documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,23 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: fakerest_config.embedder_options
|
||||
---
|
||||
{
|
||||
"Rest": {
|
||||
"api_key": "My super secret",
|
||||
"distribution": null,
|
||||
"dimensions": 384,
|
||||
"url": "http://localhost:7777",
|
||||
"query": null,
|
||||
"input_field": [
|
||||
"input"
|
||||
],
|
||||
"path_to_embeddings": [
|
||||
"data"
|
||||
],
|
||||
"embedding_object": [
|
||||
"embedding"
|
||||
],
|
||||
"input_type": "text"
|
||||
}
|
||||
}
|
||||
@ -1,11 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: simple_hf_config.embedder_options
|
||||
---
|
||||
{
|
||||
"HuggingFace": {
|
||||
"model": "sentence-transformers/all-MiniLM-L6-v2",
|
||||
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
|
||||
"distribution": null
|
||||
}
|
||||
}
|
||||
@ -1,19 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: doc
|
||||
---
|
||||
{
|
||||
"doggo": "Intel",
|
||||
"breed": "beagle",
|
||||
"_vectors": {
|
||||
"A_fakerest": {
|
||||
"embeddings": "[vector]",
|
||||
"userProvided": true
|
||||
},
|
||||
"noise": [
|
||||
0.1,
|
||||
0.2,
|
||||
0.3
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -1,20 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
expression: task.details
|
||||
---
|
||||
{
|
||||
"embedders": {
|
||||
"A_fakerest": {
|
||||
"source": "rest",
|
||||
"apiKey": "MyXXXX...",
|
||||
"dimensions": 384,
|
||||
"url": "http://localhost:7777"
|
||||
},
|
||||
"B_small_hf": {
|
||||
"source": "huggingFace",
|
||||
"model": "sentence-transformers/all-MiniLM-L6-v2",
|
||||
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
|
||||
"documentTemplate": "{{doc.doggo}} the {{doc.breed}} best doggo"
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,49 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued []
|
||||
succeeded [0,1,2,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"documentAdditionOrUpdate" [1,2,]
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,1,2,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
[timestamp] [2,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
[timestamp] [2,]
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
[timestamp] [2,]
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -1,48 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
2 {uid: 2, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: None, method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000001, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued [2,]
|
||||
succeeded [0,1,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"documentAdditionOrUpdate" [1,2,]
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,1,2,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
[timestamp] [2,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
00000000-0000-0000-0000-000000000001
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -1,45 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, status: succeeded, details: { received_documents: 1, indexed_documents: Some(1) }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued []
|
||||
succeeded [0,1,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"documentAdditionOrUpdate" [1,]
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,1,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
doggos: { number_of_documents: 1, field_distribution: {"_vectors": 1, "breed": 1, "doggo": 1, "id": 1} }
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -1,44 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
1 {uid: 1, status: enqueued, details: { received_documents: 1, indexed_documents: None }, kind: DocumentAdditionOrUpdate { index_uid: "doggos", primary_key: Some("id"), method: UpdateDocuments, content_file: 00000000-0000-0000-0000-000000000000, documents_count: 1, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued [1,]
|
||||
succeeded [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"documentAdditionOrUpdate" [1,]
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,1,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
doggos: { number_of_documents: 0, field_distribution: {} }
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
[timestamp] [1,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
00000000-0000-0000-0000-000000000000
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -1,36 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: enqueued, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -1,40 +0,0 @@
|
||||
---
|
||||
source: index-scheduler/src/lib.rs
|
||||
---
|
||||
### Autobatching Enabled = true
|
||||
### Processing Tasks:
|
||||
[]
|
||||
----------------------------------------------------------------------
|
||||
### All Tasks:
|
||||
0 {uid: 0, status: succeeded, details: { settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> } }, kind: SettingsUpdate { index_uid: "doggos", new_settings: Settings { displayed_attributes: WildcardSetting(NotSet), searchable_attributes: WildcardSetting(NotSet), filterable_attributes: NotSet, sortable_attributes: NotSet, ranking_rules: NotSet, stop_words: NotSet, non_separator_tokens: NotSet, separator_tokens: NotSet, dictionary: NotSet, synonyms: NotSet, distinct_attribute: NotSet, proximity_precision: NotSet, typo_tolerance: NotSet, faceting: NotSet, pagination: NotSet, embedders: Set({"A_fakerest": Set(EmbeddingSettings { source: Set(Rest), model: NotSet, revision: NotSet, api_key: Set("My super secret"), dimensions: Set(384), document_template: NotSet, url: Set("http://localhost:7777"), query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet }), "B_small_hf": Set(EmbeddingSettings { source: Set(HuggingFace), model: Set("sentence-transformers/all-MiniLM-L6-v2"), revision: Set("e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), api_key: NotSet, dimensions: NotSet, document_template: Set("{{doc.doggo}} the {{doc.breed}} best doggo"), url: NotSet, query: NotSet, input_field: NotSet, path_to_embeddings: NotSet, embedding_object: NotSet, input_type: NotSet, distribution: NotSet })}), search_cutoff_ms: NotSet, _kind: PhantomData<meilisearch_types::settings::Unchecked> }, is_deletion: false, allow_index_creation: true }}
|
||||
----------------------------------------------------------------------
|
||||
### Status:
|
||||
enqueued []
|
||||
succeeded [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Kind:
|
||||
"settingsUpdate" [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Tasks:
|
||||
doggos [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Index Mapper:
|
||||
doggos: { number_of_documents: 0, field_distribution: {} }
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Canceled By:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
### Enqueued At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Started At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### Finished At:
|
||||
[timestamp] [0,]
|
||||
----------------------------------------------------------------------
|
||||
### File Store:
|
||||
|
||||
----------------------------------------------------------------------
|
||||
|
||||
@ -272,9 +272,9 @@ pub fn swap_index_uid_in_task(task: &mut Task, swap: (&str, &str)) {
|
||||
}
|
||||
for index_uid in index_uids {
|
||||
if index_uid == swap.0 {
|
||||
swap.1.clone_into(index_uid);
|
||||
*index_uid = swap.1.to_owned();
|
||||
} else if index_uid == swap.1 {
|
||||
swap.0.clone_into(index_uid);
|
||||
*index_uid = swap.0.to_owned();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -49,7 +49,7 @@ pub fn open_auth_store_env(path: &Path) -> milli::heed::Result<milli::heed::Env>
|
||||
let mut options = EnvOpenOptions::new();
|
||||
options.map_size(AUTH_STORE_SIZE); // 1GB
|
||||
options.max_dbs(2);
|
||||
unsafe { options.open(path) }
|
||||
options.open(path)
|
||||
}
|
||||
|
||||
impl HeedAuthStore {
|
||||
|
||||
@ -26,7 +26,7 @@ pub type DeserrQueryParamError<C = BadRequest> = DeserrError<DeserrQueryParam, C
|
||||
|
||||
/// A request deserialization error.
|
||||
///
|
||||
/// The first generic parameter is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
|
||||
/// The first generic paramater is a marker type describing the format of the request: either json (e.g. [`DeserrJson`] or [`DeserrQueryParam`]).
|
||||
/// The second generic parameter is the default error code for the deserialization error, in case it is not given.
|
||||
pub struct DeserrError<Format, C: Default + ErrorCode> {
|
||||
pub msg: String,
|
||||
@ -189,4 +189,3 @@ merge_with_error_impl_take_error_message!(ParseTaskKindError);
|
||||
merge_with_error_impl_take_error_message!(ParseTaskStatusError);
|
||||
merge_with_error_impl_take_error_message!(IndexUidFormatError);
|
||||
merge_with_error_impl_take_error_message!(InvalidSearchSemanticRatio);
|
||||
merge_with_error_impl_take_error_message!(InvalidSimilarId);
|
||||
|
||||
@ -239,23 +239,18 @@ InvalidIndexUid , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchAttributesToSearchOn , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchAttributesToCrop , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchAttributesToHighlight , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchCropLength , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchCropMarker , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchFacets , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchSemanticRatio , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidFacetSearchFacetName , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarId , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchFilter , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarFilter , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchHighlightPostTag , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchHighlightPreTag , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchHitsPerPage , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarLimit , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchLimit , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchMatchingStrategy , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarOffset , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchOffset , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchPage , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchQ , InvalidRequest , BAD_REQUEST ;
|
||||
@ -264,9 +259,7 @@ InvalidFacetSearchName , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchVector , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchShowMatchesPosition , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchShowRankingScore , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarShowRankingScore , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchShowRankingScoreDetails , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSimilarShowRankingScoreDetails , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSearchSort , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSettingsDisplayedAttributes , InvalidRequest , BAD_REQUEST ;
|
||||
InvalidSettingsDistinctAttribute , InvalidRequest , BAD_REQUEST ;
|
||||
@ -329,8 +322,7 @@ UnretrievableErrorCode , InvalidRequest , BAD_REQUEST ;
|
||||
UnsupportedMediaType , InvalidRequest , UNSUPPORTED_MEDIA_TYPE ;
|
||||
|
||||
// Experimental features
|
||||
VectorEmbeddingError , InvalidRequest , BAD_REQUEST ;
|
||||
NotFoundSimilarId , InvalidRequest , BAD_REQUEST
|
||||
VectorEmbeddingError , InvalidRequest , BAD_REQUEST
|
||||
}
|
||||
|
||||
impl ErrorCode for JoinError {
|
||||
@ -392,6 +384,7 @@ impl ErrorCode for milli::Error {
|
||||
UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
|
||||
UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
|
||||
UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
|
||||
UserError::InvalidVectorsType { .. } => Code::InvalidVectorsType,
|
||||
UserError::TooManyVectors(_, _) => Code::TooManyVectors,
|
||||
UserError::SortError(_) => Code::InvalidSearchSort,
|
||||
UserError::InvalidMinTypoWordLenSetting(_, _) => {
|
||||
@ -430,6 +423,7 @@ impl ErrorCode for HeedError {
|
||||
HeedError::Mdb(_)
|
||||
| HeedError::Encoding(_)
|
||||
| HeedError::Decoding(_)
|
||||
| HeedError::InvalidDatabaseTyping
|
||||
| HeedError::DatabaseClosing
|
||||
| HeedError::BadOpenOptions { .. } => Code::Internal,
|
||||
}
|
||||
@ -494,17 +488,6 @@ impl fmt::Display for deserr_codes::InvalidSearchSemanticRatio {
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Display for deserr_codes::InvalidSimilarId {
|
||||
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
||||
write!(
|
||||
f,
|
||||
"the value of `id` is invalid. \
|
||||
A document identifier can be of type integer or string, \
|
||||
only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_)."
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
#[macro_export]
|
||||
macro_rules! internal_error {
|
||||
($target:ty : $($other:path), *) => {
|
||||
|
||||
@ -6,6 +6,7 @@ pub struct RuntimeTogglableFeatures {
|
||||
pub vector_store: bool,
|
||||
pub metrics: bool,
|
||||
pub logs_route: bool,
|
||||
pub export_puffin_reports: bool,
|
||||
}
|
||||
|
||||
#[derive(Default, Debug, Clone, Copy)]
|
||||
|
||||
@ -67,6 +67,7 @@ permissive-json-pointer = { path = "../permissive-json-pointer" }
|
||||
pin-project-lite = "0.2.13"
|
||||
platform-dirs = "0.3.0"
|
||||
prometheus = { version = "0.13.3", features = ["process"] }
|
||||
puffin = { version = "0.16.0", features = ["serialization"] }
|
||||
rand = "0.8.5"
|
||||
rayon = "1.8.0"
|
||||
regex = "1.10.2"
|
||||
@ -74,7 +75,7 @@ reqwest = { version = "0.11.23", features = [
|
||||
"rustls-tls",
|
||||
"json",
|
||||
], default-features = false }
|
||||
rustls = "0.21.12"
|
||||
rustls = "0.21.6"
|
||||
rustls-pemfile = "1.0.2"
|
||||
segment = { version = "0.2.3", optional = true }
|
||||
serde = { version = "1.0.195", features = ["derive"] }
|
||||
|
||||
@ -25,18 +25,6 @@ impl SearchAggregator {
|
||||
pub fn succeed(&mut self, _: &dyn Any) {}
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct SimilarAggregator;
|
||||
|
||||
#[allow(dead_code)]
|
||||
impl SimilarAggregator {
|
||||
pub fn from_query(_: &dyn Any, _: &dyn Any) -> Self {
|
||||
Self
|
||||
}
|
||||
|
||||
pub fn succeed(&mut self, _: &dyn Any) {}
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct MultiSearchAggregator;
|
||||
|
||||
@ -78,8 +66,6 @@ impl Analytics for MockAnalytics {
|
||||
fn publish(&self, _event_name: String, _send: Value, _request: Option<&HttpRequest>) {}
|
||||
fn get_search(&self, _aggregate: super::SearchAggregator) {}
|
||||
fn post_search(&self, _aggregate: super::SearchAggregator) {}
|
||||
fn get_similar(&self, _aggregate: super::SimilarAggregator) {}
|
||||
fn post_similar(&self, _aggregate: super::SimilarAggregator) {}
|
||||
fn post_multi_search(&self, _aggregate: super::MultiSearchAggregator) {}
|
||||
fn post_facet_search(&self, _aggregate: super::FacetSearchAggregator) {}
|
||||
fn add_documents(
|
||||
|
||||
@ -22,8 +22,6 @@ pub type SegmentAnalytics = mock_analytics::MockAnalytics;
|
||||
#[cfg(not(feature = "analytics"))]
|
||||
pub type SearchAggregator = mock_analytics::SearchAggregator;
|
||||
#[cfg(not(feature = "analytics"))]
|
||||
pub type SimilarAggregator = mock_analytics::SimilarAggregator;
|
||||
#[cfg(not(feature = "analytics"))]
|
||||
pub type MultiSearchAggregator = mock_analytics::MultiSearchAggregator;
|
||||
#[cfg(not(feature = "analytics"))]
|
||||
pub type FacetSearchAggregator = mock_analytics::FacetSearchAggregator;
|
||||
@ -34,8 +32,6 @@ pub type SegmentAnalytics = segment_analytics::SegmentAnalytics;
|
||||
#[cfg(feature = "analytics")]
|
||||
pub type SearchAggregator = segment_analytics::SearchAggregator;
|
||||
#[cfg(feature = "analytics")]
|
||||
pub type SimilarAggregator = segment_analytics::SimilarAggregator;
|
||||
#[cfg(feature = "analytics")]
|
||||
pub type MultiSearchAggregator = segment_analytics::MultiSearchAggregator;
|
||||
#[cfg(feature = "analytics")]
|
||||
pub type FacetSearchAggregator = segment_analytics::FacetSearchAggregator;
|
||||
@ -90,12 +86,6 @@ pub trait Analytics: Sync + Send {
|
||||
/// This method should be called to aggregate a post search
|
||||
fn post_search(&self, aggregate: SearchAggregator);
|
||||
|
||||
/// This method should be called to aggregate a get similar request
|
||||
fn get_similar(&self, aggregate: SimilarAggregator);
|
||||
|
||||
/// This method should be called to aggregate a post similar request
|
||||
fn post_similar(&self, aggregate: SimilarAggregator);
|
||||
|
||||
/// This method should be called to aggregate a post array of searches
|
||||
fn post_multi_search(&self, aggregate: MultiSearchAggregator);
|
||||
|
||||
|
||||
@ -36,9 +36,8 @@ use crate::routes::indexes::facet_search::FacetSearchQuery;
|
||||
use crate::routes::{create_all_stats, Stats};
|
||||
use crate::search::{
|
||||
FacetSearchResult, MatchingStrategy, SearchQuery, SearchQueryWithIndex, SearchResult,
|
||||
SimilarQuery, SimilarResult, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER,
|
||||
DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT,
|
||||
DEFAULT_SEMANTIC_RATIO,
|
||||
DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
|
||||
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEMANTIC_RATIO,
|
||||
};
|
||||
use crate::Opt;
|
||||
|
||||
@ -74,8 +73,6 @@ pub enum AnalyticsMsg {
|
||||
BatchMessage(Track),
|
||||
AggregateGetSearch(SearchAggregator),
|
||||
AggregatePostSearch(SearchAggregator),
|
||||
AggregateGetSimilar(SimilarAggregator),
|
||||
AggregatePostSimilar(SimilarAggregator),
|
||||
AggregatePostMultiSearch(MultiSearchAggregator),
|
||||
AggregatePostFacetSearch(FacetSearchAggregator),
|
||||
AggregateAddDocuments(DocumentsAggregator),
|
||||
@ -152,8 +149,6 @@ impl SegmentAnalytics {
|
||||
update_documents_aggregator: DocumentsAggregator::default(),
|
||||
get_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
|
||||
post_fetch_documents_aggregator: DocumentsFetchAggregator::default(),
|
||||
get_similar_aggregator: SimilarAggregator::default(),
|
||||
post_similar_aggregator: SimilarAggregator::default(),
|
||||
});
|
||||
tokio::spawn(segment.run(index_scheduler.clone(), auth_controller.clone()));
|
||||
|
||||
@ -189,14 +184,6 @@ impl super::Analytics for SegmentAnalytics {
|
||||
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSearch(aggregate));
|
||||
}
|
||||
|
||||
fn get_similar(&self, aggregate: SimilarAggregator) {
|
||||
let _ = self.sender.try_send(AnalyticsMsg::AggregateGetSimilar(aggregate));
|
||||
}
|
||||
|
||||
fn post_similar(&self, aggregate: SimilarAggregator) {
|
||||
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostSimilar(aggregate));
|
||||
}
|
||||
|
||||
fn post_facet_search(&self, aggregate: FacetSearchAggregator) {
|
||||
let _ = self.sender.try_send(AnalyticsMsg::AggregatePostFacetSearch(aggregate));
|
||||
}
|
||||
@ -392,8 +379,6 @@ pub struct Segment {
|
||||
update_documents_aggregator: DocumentsAggregator,
|
||||
get_fetch_documents_aggregator: DocumentsFetchAggregator,
|
||||
post_fetch_documents_aggregator: DocumentsFetchAggregator,
|
||||
get_similar_aggregator: SimilarAggregator,
|
||||
post_similar_aggregator: SimilarAggregator,
|
||||
}
|
||||
|
||||
impl Segment {
|
||||
@ -456,8 +441,6 @@ impl Segment {
|
||||
Some(AnalyticsMsg::AggregateUpdateDocuments(agreg)) => self.update_documents_aggregator.aggregate(agreg),
|
||||
Some(AnalyticsMsg::AggregateGetFetchDocuments(agreg)) => self.get_fetch_documents_aggregator.aggregate(agreg),
|
||||
Some(AnalyticsMsg::AggregatePostFetchDocuments(agreg)) => self.post_fetch_documents_aggregator.aggregate(agreg),
|
||||
Some(AnalyticsMsg::AggregateGetSimilar(agreg)) => self.get_similar_aggregator.aggregate(agreg),
|
||||
Some(AnalyticsMsg::AggregatePostSimilar(agreg)) => self.post_similar_aggregator.aggregate(agreg),
|
||||
None => (),
|
||||
}
|
||||
}
|
||||
@ -511,8 +494,6 @@ impl Segment {
|
||||
update_documents_aggregator,
|
||||
get_fetch_documents_aggregator,
|
||||
post_fetch_documents_aggregator,
|
||||
get_similar_aggregator,
|
||||
post_similar_aggregator,
|
||||
} = self;
|
||||
|
||||
if let Some(get_search) =
|
||||
@ -560,18 +541,6 @@ impl Segment {
|
||||
{
|
||||
let _ = self.batcher.push(post_fetch_documents).await;
|
||||
}
|
||||
|
||||
if let Some(get_similar_documents) =
|
||||
take(get_similar_aggregator).into_event(user, "Similar GET")
|
||||
{
|
||||
let _ = self.batcher.push(get_similar_documents).await;
|
||||
}
|
||||
|
||||
if let Some(post_similar_documents) =
|
||||
take(post_similar_aggregator).into_event(user, "Similar POST")
|
||||
{
|
||||
let _ = self.batcher.push(post_similar_documents).await;
|
||||
}
|
||||
let _ = self.batcher.flush().await;
|
||||
}
|
||||
}
|
||||
@ -1589,235 +1558,3 @@ impl DocumentsFetchAggregator {
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct SimilarAggregator {
|
||||
timestamp: Option<OffsetDateTime>,
|
||||
|
||||
// context
|
||||
user_agents: HashSet<String>,
|
||||
|
||||
// requests
|
||||
total_received: usize,
|
||||
total_succeeded: usize,
|
||||
time_spent: BinaryHeap<usize>,
|
||||
|
||||
// filter
|
||||
filter_with_geo_radius: bool,
|
||||
filter_with_geo_bounding_box: bool,
|
||||
// every time a request has a filter, this field must be incremented by the number of terms it contains
|
||||
filter_sum_of_criteria_terms: usize,
|
||||
// every time a request has a filter, this field must be incremented by one
|
||||
filter_total_number_of_criteria: usize,
|
||||
used_syntax: HashMap<String, usize>,
|
||||
|
||||
// Whether a non-default embedder was specified
|
||||
embedder: bool,
|
||||
|
||||
// pagination
|
||||
max_limit: usize,
|
||||
max_offset: usize,
|
||||
|
||||
// formatting
|
||||
max_attributes_to_retrieve: usize,
|
||||
|
||||
// scoring
|
||||
show_ranking_score: bool,
|
||||
show_ranking_score_details: bool,
|
||||
}
|
||||
|
||||
impl SimilarAggregator {
|
||||
#[allow(clippy::field_reassign_with_default)]
|
||||
pub fn from_query(query: &SimilarQuery, request: &HttpRequest) -> Self {
|
||||
let SimilarQuery {
|
||||
id: _,
|
||||
embedder,
|
||||
offset,
|
||||
limit,
|
||||
attributes_to_retrieve: _,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
filter,
|
||||
} = query;
|
||||
|
||||
let mut ret = Self::default();
|
||||
ret.timestamp = Some(OffsetDateTime::now_utc());
|
||||
|
||||
ret.total_received = 1;
|
||||
ret.user_agents = extract_user_agents(request).into_iter().collect();
|
||||
|
||||
if let Some(ref filter) = filter {
|
||||
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
|
||||
ret.filter_total_number_of_criteria = 1;
|
||||
|
||||
let syntax = match filter {
|
||||
Value::String(_) => "string".to_string(),
|
||||
Value::Array(values) => {
|
||||
if values.iter().map(|v| v.to_string()).any(|s| RE.is_match(&s)) {
|
||||
"mixed".to_string()
|
||||
} else {
|
||||
"array".to_string()
|
||||
}
|
||||
}
|
||||
_ => "none".to_string(),
|
||||
};
|
||||
// convert the string to a HashMap
|
||||
ret.used_syntax.insert(syntax, 1);
|
||||
|
||||
let stringified_filters = filter.to_string();
|
||||
ret.filter_with_geo_radius = stringified_filters.contains("_geoRadius(");
|
||||
ret.filter_with_geo_bounding_box = stringified_filters.contains("_geoBoundingBox(");
|
||||
ret.filter_sum_of_criteria_terms = RE.split(&stringified_filters).count();
|
||||
}
|
||||
|
||||
ret.max_limit = *limit;
|
||||
ret.max_offset = *offset;
|
||||
|
||||
ret.show_ranking_score = *show_ranking_score;
|
||||
ret.show_ranking_score_details = *show_ranking_score_details;
|
||||
|
||||
ret.embedder = embedder.is_some();
|
||||
|
||||
ret
|
||||
}
|
||||
|
||||
pub fn succeed(&mut self, result: &SimilarResult) {
|
||||
let SimilarResult { id: _, hits: _, processing_time_ms, hits_info: _ } = result;
|
||||
|
||||
self.total_succeeded = self.total_succeeded.saturating_add(1);
|
||||
|
||||
self.time_spent.push(*processing_time_ms as usize);
|
||||
}
|
||||
|
||||
/// Aggregate one [SimilarAggregator] into another.
|
||||
pub fn aggregate(&mut self, mut other: Self) {
|
||||
let Self {
|
||||
timestamp,
|
||||
user_agents,
|
||||
total_received,
|
||||
total_succeeded,
|
||||
ref mut time_spent,
|
||||
filter_with_geo_radius,
|
||||
filter_with_geo_bounding_box,
|
||||
filter_sum_of_criteria_terms,
|
||||
filter_total_number_of_criteria,
|
||||
used_syntax,
|
||||
max_limit,
|
||||
max_offset,
|
||||
max_attributes_to_retrieve,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
embedder,
|
||||
} = other;
|
||||
|
||||
if self.timestamp.is_none() {
|
||||
self.timestamp = timestamp;
|
||||
}
|
||||
|
||||
// context
|
||||
for user_agent in user_agents.into_iter() {
|
||||
self.user_agents.insert(user_agent);
|
||||
}
|
||||
|
||||
// request
|
||||
self.total_received = self.total_received.saturating_add(total_received);
|
||||
self.total_succeeded = self.total_succeeded.saturating_add(total_succeeded);
|
||||
self.time_spent.append(time_spent);
|
||||
|
||||
// filter
|
||||
self.filter_with_geo_radius |= filter_with_geo_radius;
|
||||
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
|
||||
self.filter_sum_of_criteria_terms =
|
||||
self.filter_sum_of_criteria_terms.saturating_add(filter_sum_of_criteria_terms);
|
||||
self.filter_total_number_of_criteria =
|
||||
self.filter_total_number_of_criteria.saturating_add(filter_total_number_of_criteria);
|
||||
for (key, value) in used_syntax.into_iter() {
|
||||
let used_syntax = self.used_syntax.entry(key).or_insert(0);
|
||||
*used_syntax = used_syntax.saturating_add(value);
|
||||
}
|
||||
|
||||
self.embedder |= embedder;
|
||||
|
||||
// pagination
|
||||
self.max_limit = self.max_limit.max(max_limit);
|
||||
self.max_offset = self.max_offset.max(max_offset);
|
||||
|
||||
// formatting
|
||||
self.max_attributes_to_retrieve =
|
||||
self.max_attributes_to_retrieve.max(max_attributes_to_retrieve);
|
||||
|
||||
// scoring
|
||||
self.show_ranking_score |= show_ranking_score;
|
||||
self.show_ranking_score_details |= show_ranking_score_details;
|
||||
}
|
||||
|
||||
pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
|
||||
let Self {
|
||||
timestamp,
|
||||
user_agents,
|
||||
total_received,
|
||||
total_succeeded,
|
||||
time_spent,
|
||||
filter_with_geo_radius,
|
||||
filter_with_geo_bounding_box,
|
||||
filter_sum_of_criteria_terms,
|
||||
filter_total_number_of_criteria,
|
||||
used_syntax,
|
||||
max_limit,
|
||||
max_offset,
|
||||
max_attributes_to_retrieve,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
embedder,
|
||||
} = self;
|
||||
|
||||
if total_received == 0 {
|
||||
None
|
||||
} else {
|
||||
// we get all the values in a sorted manner
|
||||
let time_spent = time_spent.into_sorted_vec();
|
||||
// the index of the 99th percentage of value
|
||||
let percentile_99th = time_spent.len() * 99 / 100;
|
||||
// We are only interested by the slowest value of the 99th fastest results
|
||||
let time_spent = time_spent.get(percentile_99th);
|
||||
|
||||
let properties = json!({
|
||||
"user-agent": user_agents,
|
||||
"requests": {
|
||||
"99th_response_time": time_spent.map(|t| format!("{:.2}", t)),
|
||||
"total_succeeded": total_succeeded,
|
||||
"total_failed": total_received.saturating_sub(total_succeeded), // just to be sure we never panics
|
||||
"total_received": total_received,
|
||||
},
|
||||
"filter": {
|
||||
"with_geoRadius": filter_with_geo_radius,
|
||||
"with_geoBoundingBox": filter_with_geo_bounding_box,
|
||||
"avg_criteria_number": format!("{:.2}", filter_sum_of_criteria_terms as f64 / filter_total_number_of_criteria as f64),
|
||||
"most_used_syntax": used_syntax.iter().max_by_key(|(_, v)| *v).map(|(k, _)| json!(k)).unwrap_or_else(|| json!(null)),
|
||||
},
|
||||
"hybrid": {
|
||||
"embedder": embedder,
|
||||
},
|
||||
"pagination": {
|
||||
"max_limit": max_limit,
|
||||
"max_offset": max_offset,
|
||||
},
|
||||
"formatting": {
|
||||
"max_attributes_to_retrieve": max_attributes_to_retrieve,
|
||||
},
|
||||
"scoring": {
|
||||
"show_ranking_score": show_ranking_score,
|
||||
"show_ranking_score_details": show_ranking_score_details,
|
||||
},
|
||||
});
|
||||
|
||||
Some(Track {
|
||||
timestamp,
|
||||
user: user.clone(),
|
||||
event: event_name.to_string(),
|
||||
properties,
|
||||
..Default::default()
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -59,12 +59,10 @@ where
|
||||
let request_path = req.path();
|
||||
let is_registered_resource = req.resource_map().has_resource(request_path);
|
||||
if is_registered_resource {
|
||||
let request_pattern = req.match_pattern();
|
||||
let metric_path = request_pattern.as_ref().map_or(request_path, String::as_str);
|
||||
let request_method = req.method().to_string();
|
||||
histogram_timer = Some(
|
||||
crate::metrics::MEILISEARCH_HTTP_RESPONSE_TIME_SECONDS
|
||||
.with_label_values(&[&request_method, metric_path])
|
||||
.with_label_values(&[&request_method, request_path])
|
||||
.start_timer(),
|
||||
);
|
||||
}
|
||||
|
||||
@ -47,6 +47,8 @@ pub struct RuntimeTogglableFeatures {
|
||||
pub metrics: Option<bool>,
|
||||
#[deserr(default)]
|
||||
pub logs_route: Option<bool>,
|
||||
#[deserr(default)]
|
||||
pub export_puffin_reports: Option<bool>,
|
||||
}
|
||||
|
||||
async fn patch_features(
|
||||
@ -66,13 +68,21 @@ async fn patch_features(
|
||||
vector_store: new_features.0.vector_store.unwrap_or(old_features.vector_store),
|
||||
metrics: new_features.0.metrics.unwrap_or(old_features.metrics),
|
||||
logs_route: new_features.0.logs_route.unwrap_or(old_features.logs_route),
|
||||
export_puffin_reports: new_features
|
||||
.0
|
||||
.export_puffin_reports
|
||||
.unwrap_or(old_features.export_puffin_reports),
|
||||
};
|
||||
|
||||
// explicitly destructure for analytics rather than using the `Serialize` implementation, because
|
||||
// the it renames to camelCase, which we don't want for analytics.
|
||||
// **Do not** ignore fields with `..` or `_` here, because we want to add them in the future.
|
||||
let meilisearch_types::features::RuntimeTogglableFeatures { vector_store, metrics, logs_route } =
|
||||
new_features;
|
||||
let meilisearch_types::features::RuntimeTogglableFeatures {
|
||||
vector_store,
|
||||
metrics,
|
||||
logs_route,
|
||||
export_puffin_reports,
|
||||
} = new_features;
|
||||
|
||||
analytics.publish(
|
||||
"Experimental features Updated".to_string(),
|
||||
@ -80,6 +90,7 @@ async fn patch_features(
|
||||
"vector_store": vector_store,
|
||||
"metrics": metrics,
|
||||
"logs_route": logs_route,
|
||||
"export_puffin_reports": export_puffin_reports,
|
||||
}),
|
||||
Some(&req),
|
||||
);
|
||||
|
||||
@ -69,7 +69,7 @@ pub async fn search(
|
||||
|
||||
// Tenant token search_rules.
|
||||
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
|
||||
add_search_rules(&mut search_query.filter, search_rules);
|
||||
add_search_rules(&mut search_query, search_rules);
|
||||
}
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
|
||||
@ -29,7 +29,6 @@ pub mod documents;
|
||||
pub mod facet_search;
|
||||
pub mod search;
|
||||
pub mod settings;
|
||||
pub mod similar;
|
||||
|
||||
pub fn configure(cfg: &mut web::ServiceConfig) {
|
||||
cfg.service(
|
||||
@ -49,7 +48,6 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
|
||||
.service(web::scope("/documents").configure(documents::configure))
|
||||
.service(web::scope("/search").configure(search::configure))
|
||||
.service(web::scope("/facet-search").configure(facet_search::configure))
|
||||
.service(web::scope("/similar").configure(similar::configure))
|
||||
.service(web::scope("/settings").configure(settings::configure)),
|
||||
);
|
||||
}
|
||||
|
||||
@ -196,7 +196,7 @@ pub async fn search_with_url_query(
|
||||
|
||||
// Tenant token search_rules.
|
||||
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
|
||||
add_search_rules(&mut query.filter, search_rules);
|
||||
add_search_rules(&mut query, search_rules);
|
||||
}
|
||||
|
||||
let mut aggregate = SearchAggregator::from_query(&query, &req);
|
||||
@ -235,7 +235,7 @@ pub async fn search_with_post(
|
||||
|
||||
// Tenant token search_rules.
|
||||
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
|
||||
add_search_rules(&mut query.filter, search_rules);
|
||||
add_search_rules(&mut query, search_rules);
|
||||
}
|
||||
|
||||
let mut aggregate = SearchAggregator::from_query(&query, &req);
|
||||
|
||||
@ -1,171 +0,0 @@
|
||||
use actix_web::web::{self, Data};
|
||||
use actix_web::{HttpRequest, HttpResponse};
|
||||
use deserr::actix_web::{AwebJson, AwebQueryParameter};
|
||||
use index_scheduler::IndexScheduler;
|
||||
use meilisearch_types::deserr::query_params::Param;
|
||||
use meilisearch_types::deserr::{DeserrJsonError, DeserrQueryParamError};
|
||||
use meilisearch_types::error::deserr_codes::{
|
||||
InvalidEmbedder, InvalidSimilarAttributesToRetrieve, InvalidSimilarFilter, InvalidSimilarId,
|
||||
InvalidSimilarLimit, InvalidSimilarOffset, InvalidSimilarShowRankingScore,
|
||||
InvalidSimilarShowRankingScoreDetails,
|
||||
};
|
||||
use meilisearch_types::error::{ErrorCode as _, ResponseError};
|
||||
use meilisearch_types::index_uid::IndexUid;
|
||||
use meilisearch_types::keys::actions;
|
||||
use meilisearch_types::serde_cs::vec::CS;
|
||||
use serde_json::Value;
|
||||
use tracing::debug;
|
||||
|
||||
use super::ActionPolicy;
|
||||
use crate::analytics::{Analytics, SimilarAggregator};
|
||||
use crate::extractors::authentication::GuardedData;
|
||||
use crate::extractors::sequential_extractor::SeqHandler;
|
||||
use crate::search::{
|
||||
add_search_rules, perform_similar, SearchKind, SimilarQuery, SimilarResult,
|
||||
DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
|
||||
};
|
||||
|
||||
pub fn configure(cfg: &mut web::ServiceConfig) {
|
||||
cfg.service(
|
||||
web::resource("")
|
||||
.route(web::get().to(SeqHandler(similar_get)))
|
||||
.route(web::post().to(SeqHandler(similar_post))),
|
||||
);
|
||||
}
|
||||
|
||||
pub async fn similar_get(
|
||||
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
|
||||
index_uid: web::Path<String>,
|
||||
params: AwebQueryParameter<SimilarQueryGet, DeserrQueryParamError>,
|
||||
req: HttpRequest,
|
||||
analytics: web::Data<dyn Analytics>,
|
||||
) -> Result<HttpResponse, ResponseError> {
|
||||
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
|
||||
|
||||
let query = params.0.try_into().map_err(|code: InvalidSimilarId| {
|
||||
ResponseError::from_msg(code.to_string(), code.error_code())
|
||||
})?;
|
||||
|
||||
let mut aggregate = SimilarAggregator::from_query(&query, &req);
|
||||
|
||||
debug!(parameters = ?query, "Similar get");
|
||||
|
||||
let similar = similar(index_scheduler, index_uid, query).await;
|
||||
|
||||
if let Ok(similar) = &similar {
|
||||
aggregate.succeed(similar);
|
||||
}
|
||||
analytics.get_similar(aggregate);
|
||||
|
||||
let similar = similar?;
|
||||
|
||||
debug!(returns = ?similar, "Similar get");
|
||||
Ok(HttpResponse::Ok().json(similar))
|
||||
}
|
||||
|
||||
pub async fn similar_post(
|
||||
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
|
||||
index_uid: web::Path<String>,
|
||||
params: AwebJson<SimilarQuery, DeserrJsonError>,
|
||||
req: HttpRequest,
|
||||
analytics: web::Data<dyn Analytics>,
|
||||
) -> Result<HttpResponse, ResponseError> {
|
||||
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
|
||||
|
||||
let query = params.into_inner();
|
||||
debug!(parameters = ?query, "Similar post");
|
||||
|
||||
let mut aggregate = SimilarAggregator::from_query(&query, &req);
|
||||
|
||||
let similar = similar(index_scheduler, index_uid, query).await;
|
||||
|
||||
if let Ok(similar) = &similar {
|
||||
aggregate.succeed(similar);
|
||||
}
|
||||
analytics.post_similar(aggregate);
|
||||
|
||||
let similar = similar?;
|
||||
|
||||
debug!(returns = ?similar, "Similar post");
|
||||
Ok(HttpResponse::Ok().json(similar))
|
||||
}
|
||||
|
||||
async fn similar(
|
||||
index_scheduler: GuardedData<ActionPolicy<{ actions::SEARCH }>, Data<IndexScheduler>>,
|
||||
index_uid: IndexUid,
|
||||
mut query: SimilarQuery,
|
||||
) -> Result<SimilarResult, ResponseError> {
|
||||
let features = index_scheduler.features();
|
||||
|
||||
features.check_vector("Using the similar API")?;
|
||||
|
||||
// Tenant token search_rules.
|
||||
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid) {
|
||||
add_search_rules(&mut query.filter, search_rules);
|
||||
}
|
||||
|
||||
let index = index_scheduler.index(&index_uid)?;
|
||||
|
||||
let (embedder_name, embedder) =
|
||||
SearchKind::embedder(&index_scheduler, &index, query.embedder.as_deref(), None)?;
|
||||
|
||||
tokio::task::spawn_blocking(move || perform_similar(&index, query, embedder_name, embedder))
|
||||
.await?
|
||||
}
|
||||
|
||||
#[derive(Debug, deserr::Deserr)]
|
||||
#[deserr(error = DeserrQueryParamError, rename_all = camelCase, deny_unknown_fields)]
|
||||
pub struct SimilarQueryGet {
|
||||
#[deserr(error = DeserrQueryParamError<InvalidSimilarId>)]
|
||||
id: Param<String>,
|
||||
#[deserr(default = Param(DEFAULT_SEARCH_OFFSET()), error = DeserrQueryParamError<InvalidSimilarOffset>)]
|
||||
offset: Param<usize>,
|
||||
#[deserr(default = Param(DEFAULT_SEARCH_LIMIT()), error = DeserrQueryParamError<InvalidSimilarLimit>)]
|
||||
limit: Param<usize>,
|
||||
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarAttributesToRetrieve>)]
|
||||
attributes_to_retrieve: Option<CS<String>>,
|
||||
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarFilter>)]
|
||||
filter: Option<String>,
|
||||
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScore>)]
|
||||
show_ranking_score: Param<bool>,
|
||||
#[deserr(default, error = DeserrQueryParamError<InvalidSimilarShowRankingScoreDetails>)]
|
||||
show_ranking_score_details: Param<bool>,
|
||||
#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
|
||||
pub embedder: Option<String>,
|
||||
}
|
||||
|
||||
impl TryFrom<SimilarQueryGet> for SimilarQuery {
|
||||
type Error = InvalidSimilarId;
|
||||
|
||||
fn try_from(
|
||||
SimilarQueryGet {
|
||||
id,
|
||||
offset,
|
||||
limit,
|
||||
attributes_to_retrieve,
|
||||
filter,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
embedder,
|
||||
}: SimilarQueryGet,
|
||||
) -> Result<Self, Self::Error> {
|
||||
let filter = match filter {
|
||||
Some(f) => match serde_json::from_str(&f) {
|
||||
Ok(v) => Some(v),
|
||||
_ => Some(Value::String(f)),
|
||||
},
|
||||
None => None,
|
||||
};
|
||||
|
||||
Ok(SimilarQuery {
|
||||
id: id.0.try_into()?,
|
||||
offset: offset.0,
|
||||
limit: limit.0,
|
||||
filter,
|
||||
embedder,
|
||||
attributes_to_retrieve: attributes_to_retrieve.map(|o| o.into_iter().collect()),
|
||||
show_ranking_score: show_ranking_score.0,
|
||||
show_ranking_score_details: show_ranking_score_details.0,
|
||||
})
|
||||
}
|
||||
}
|
||||
@ -67,7 +67,7 @@ pub async fn multi_search_with_post(
|
||||
// Apply search rules from tenant token
|
||||
if let Some(search_rules) = index_scheduler.filters().get_index_search_rules(&index_uid)
|
||||
{
|
||||
add_search_rules(&mut query.filter, search_rules);
|
||||
add_search_rules(&mut query, search_rules);
|
||||
}
|
||||
|
||||
let index = index_scheduler
|
||||
|
||||
@ -11,7 +11,7 @@ use indexmap::IndexMap;
|
||||
use meilisearch_auth::IndexSearchRules;
|
||||
use meilisearch_types::deserr::DeserrJsonError;
|
||||
use meilisearch_types::error::deserr_codes::*;
|
||||
use meilisearch_types::error::{Code, ResponseError};
|
||||
use meilisearch_types::error::ResponseError;
|
||||
use meilisearch_types::heed::RoTxn;
|
||||
use meilisearch_types::index_uid::IndexUid;
|
||||
use meilisearch_types::milli::score_details::{ScoreDetails, ScoringStrategy};
|
||||
@ -231,7 +231,7 @@ impl SearchKind {
|
||||
Ok(Self::Hybrid { embedder_name, embedder, semantic_ratio })
|
||||
}
|
||||
|
||||
pub(crate) fn embedder(
|
||||
fn embedder(
|
||||
index_scheduler: &index_scheduler::IndexScheduler,
|
||||
index: &Index,
|
||||
embedder_name: Option<&str>,
|
||||
@ -417,59 +417,6 @@ impl SearchQueryWithIndex {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Deserr)]
|
||||
#[deserr(error = DeserrJsonError, rename_all = camelCase, deny_unknown_fields)]
|
||||
pub struct SimilarQuery {
|
||||
#[deserr(error = DeserrJsonError<InvalidSimilarId>)]
|
||||
pub id: ExternalDocumentId,
|
||||
#[deserr(default = DEFAULT_SEARCH_OFFSET(), error = DeserrJsonError<InvalidSimilarOffset>)]
|
||||
pub offset: usize,
|
||||
#[deserr(default = DEFAULT_SEARCH_LIMIT(), error = DeserrJsonError<InvalidSimilarLimit>)]
|
||||
pub limit: usize,
|
||||
#[deserr(default, error = DeserrJsonError<InvalidSimilarFilter>)]
|
||||
pub filter: Option<Value>,
|
||||
#[deserr(default, error = DeserrJsonError<InvalidEmbedder>, default)]
|
||||
pub embedder: Option<String>,
|
||||
#[deserr(default, error = DeserrJsonError<InvalidSimilarAttributesToRetrieve>)]
|
||||
pub attributes_to_retrieve: Option<BTreeSet<String>>,
|
||||
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScore>, default)]
|
||||
pub show_ranking_score: bool,
|
||||
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScoreDetails>, default)]
|
||||
pub show_ranking_score_details: bool,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Deserr)]
|
||||
#[deserr(try_from(Value) = TryFrom::try_from -> InvalidSimilarId)]
|
||||
pub struct ExternalDocumentId(String);
|
||||
|
||||
impl AsRef<str> for ExternalDocumentId {
|
||||
fn as_ref(&self) -> &str {
|
||||
&self.0
|
||||
}
|
||||
}
|
||||
|
||||
impl ExternalDocumentId {
|
||||
pub fn into_inner(self) -> String {
|
||||
self.0
|
||||
}
|
||||
}
|
||||
|
||||
impl TryFrom<String> for ExternalDocumentId {
|
||||
type Error = InvalidSimilarId;
|
||||
|
||||
fn try_from(value: String) -> Result<Self, Self::Error> {
|
||||
serde_json::Value::String(value).try_into()
|
||||
}
|
||||
}
|
||||
|
||||
impl TryFrom<Value> for ExternalDocumentId {
|
||||
type Error = InvalidSimilarId;
|
||||
|
||||
fn try_from(value: Value) -> Result<Self, Self::Error> {
|
||||
Ok(Self(milli::documents::validate_document_id_value(value).map_err(|_| InvalidSimilarId)?))
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Copy, Clone, PartialEq, Eq, Deserr)]
|
||||
#[deserr(rename_all = camelCase)]
|
||||
pub enum MatchingStrategy {
|
||||
@ -591,16 +538,6 @@ impl fmt::Debug for SearchResult {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Serialize, Debug, Clone, PartialEq)]
|
||||
#[serde(rename_all = "camelCase")]
|
||||
pub struct SimilarResult {
|
||||
pub hits: Vec<SearchHit>,
|
||||
pub id: String,
|
||||
pub processing_time_ms: u128,
|
||||
#[serde(flatten)]
|
||||
pub hits_info: HitsInfo,
|
||||
}
|
||||
|
||||
#[derive(Serialize, Debug, Clone, PartialEq)]
|
||||
#[serde(rename_all = "camelCase")]
|
||||
pub struct SearchResultWithIndex {
|
||||
@ -633,8 +570,8 @@ pub struct FacetSearchResult {
|
||||
}
|
||||
|
||||
/// Incorporate search rules in search query
|
||||
pub fn add_search_rules(filter: &mut Option<Value>, rules: IndexSearchRules) {
|
||||
*filter = match (filter.take(), rules.filter) {
|
||||
pub fn add_search_rules(query: &mut SearchQuery, rules: IndexSearchRules) {
|
||||
query.filter = match (query.filter.take(), rules.filter) {
|
||||
(None, rules_filter) => rules_filter,
|
||||
(filter, None) => filter,
|
||||
(Some(filter), Some(rules_filter)) => {
|
||||
@ -782,52 +719,131 @@ pub fn perform_search(
|
||||
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
|
||||
};
|
||||
|
||||
let SearchQuery {
|
||||
q,
|
||||
vector: _,
|
||||
hybrid: _,
|
||||
// already computed from prepare_search
|
||||
offset: _,
|
||||
limit,
|
||||
page,
|
||||
hits_per_page,
|
||||
attributes_to_retrieve,
|
||||
attributes_to_crop,
|
||||
crop_length,
|
||||
attributes_to_highlight,
|
||||
show_matches_position,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
filter: _,
|
||||
sort,
|
||||
facets,
|
||||
highlight_pre_tag,
|
||||
highlight_post_tag,
|
||||
crop_marker,
|
||||
matching_strategy: _,
|
||||
attributes_to_search_on: _,
|
||||
} = query;
|
||||
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
|
||||
|
||||
let format = AttributesFormat {
|
||||
attributes_to_retrieve,
|
||||
attributes_to_highlight,
|
||||
attributes_to_crop,
|
||||
crop_length,
|
||||
crop_marker,
|
||||
highlight_pre_tag,
|
||||
highlight_post_tag,
|
||||
show_matches_position,
|
||||
sort,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
let displayed_ids = index
|
||||
.displayed_fields_ids(&rtxn)?
|
||||
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
|
||||
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
|
||||
|
||||
let fids = |attrs: &BTreeSet<String>| {
|
||||
let mut ids = BTreeSet::new();
|
||||
for attr in attrs {
|
||||
if attr == "*" {
|
||||
ids = displayed_ids.clone();
|
||||
break;
|
||||
}
|
||||
|
||||
if let Some(id) = fields_ids_map.id(attr) {
|
||||
ids.insert(id);
|
||||
}
|
||||
}
|
||||
ids
|
||||
};
|
||||
|
||||
let documents =
|
||||
make_hits(index, &rtxn, format, matching_words, documents_ids, document_scores)?;
|
||||
// The attributes to retrieve are the ones explicitly marked as to retrieve (all by default),
|
||||
// but these attributes must be also be present
|
||||
// - in the fields_ids_map
|
||||
// - in the displayed attributes
|
||||
let to_retrieve_ids: BTreeSet<_> = query
|
||||
.attributes_to_retrieve
|
||||
.as_ref()
|
||||
.map(fids)
|
||||
.unwrap_or_else(|| displayed_ids.clone())
|
||||
.intersection(&displayed_ids)
|
||||
.cloned()
|
||||
.collect();
|
||||
|
||||
let attr_to_highlight = query.attributes_to_highlight.unwrap_or_default();
|
||||
|
||||
let attr_to_crop = query.attributes_to_crop.unwrap_or_default();
|
||||
|
||||
// Attributes in `formatted_options` correspond to the attributes that will be in `_formatted`
|
||||
// These attributes are:
|
||||
// - the attributes asked to be highlighted or cropped (with `attributesToCrop` or `attributesToHighlight`)
|
||||
// - the attributes asked to be retrieved: these attributes will not be highlighted/cropped
|
||||
// But these attributes must be also present in displayed attributes
|
||||
let formatted_options = compute_formatted_options(
|
||||
&attr_to_highlight,
|
||||
&attr_to_crop,
|
||||
query.crop_length,
|
||||
&to_retrieve_ids,
|
||||
&fields_ids_map,
|
||||
&displayed_ids,
|
||||
);
|
||||
|
||||
let mut tokenizer_builder = TokenizerBuilder::default();
|
||||
tokenizer_builder.create_char_map(true);
|
||||
|
||||
let script_lang_map = index.script_language(&rtxn)?;
|
||||
if !script_lang_map.is_empty() {
|
||||
tokenizer_builder.allow_list(&script_lang_map);
|
||||
}
|
||||
|
||||
let separators = index.allowed_separators(&rtxn)?;
|
||||
let separators: Option<Vec<_>> =
|
||||
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
|
||||
if let Some(ref separators) = separators {
|
||||
tokenizer_builder.separators(separators);
|
||||
}
|
||||
|
||||
let dictionary = index.dictionary(&rtxn)?;
|
||||
let dictionary: Option<Vec<_>> =
|
||||
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
|
||||
if let Some(ref dictionary) = dictionary {
|
||||
tokenizer_builder.words_dict(dictionary);
|
||||
}
|
||||
|
||||
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
|
||||
formatter_builder.crop_marker(query.crop_marker);
|
||||
formatter_builder.highlight_prefix(query.highlight_pre_tag);
|
||||
formatter_builder.highlight_suffix(query.highlight_post_tag);
|
||||
|
||||
let mut documents = Vec::new();
|
||||
let documents_iter = index.documents(&rtxn, documents_ids)?;
|
||||
|
||||
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
|
||||
// First generate a document with all the displayed fields
|
||||
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
|
||||
|
||||
// select the attributes to retrieve
|
||||
let attributes_to_retrieve = to_retrieve_ids
|
||||
.iter()
|
||||
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
|
||||
let mut document =
|
||||
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
|
||||
|
||||
let (matches_position, formatted) = format_fields(
|
||||
&displayed_document,
|
||||
&fields_ids_map,
|
||||
&formatter_builder,
|
||||
&formatted_options,
|
||||
query.show_matches_position,
|
||||
&displayed_ids,
|
||||
)?;
|
||||
|
||||
if let Some(sort) = query.sort.as_ref() {
|
||||
insert_geo_distance(sort, &mut document);
|
||||
}
|
||||
|
||||
let ranking_score =
|
||||
query.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
|
||||
let ranking_score_details =
|
||||
query.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
|
||||
|
||||
let hit = SearchHit {
|
||||
document,
|
||||
formatted,
|
||||
matches_position,
|
||||
ranking_score_details,
|
||||
ranking_score,
|
||||
};
|
||||
documents.push(hit);
|
||||
}
|
||||
|
||||
let number_of_hits = min(candidates.len() as usize, max_total_hits);
|
||||
let hits_info = if is_finite_pagination {
|
||||
let hits_per_page = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
|
||||
let hits_per_page = query.hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
|
||||
// If hit_per_page is 0, then pages can't be computed and so we respond 0.
|
||||
let total_pages = (number_of_hits + hits_per_page.saturating_sub(1))
|
||||
.checked_div(hits_per_page)
|
||||
@ -835,15 +851,15 @@ pub fn perform_search(
|
||||
|
||||
HitsInfo::Pagination {
|
||||
hits_per_page,
|
||||
page: page.unwrap_or(1),
|
||||
page: query.page.unwrap_or(1),
|
||||
total_pages,
|
||||
total_hits: number_of_hits,
|
||||
}
|
||||
} else {
|
||||
HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits }
|
||||
HitsInfo::OffsetLimit { limit: query.limit, offset, estimated_total_hits: number_of_hits }
|
||||
};
|
||||
|
||||
let (facet_distribution, facet_stats) = match facets {
|
||||
let (facet_distribution, facet_stats) = match query.facets {
|
||||
Some(ref fields) => {
|
||||
let mut facet_distribution = index.facets_distribution(&rtxn);
|
||||
|
||||
@ -880,7 +896,7 @@ pub fn perform_search(
|
||||
let result = SearchResult {
|
||||
hits: documents,
|
||||
hits_info,
|
||||
query: q.unwrap_or_default(),
|
||||
query: query.q.unwrap_or_default(),
|
||||
processing_time_ms: before_search.elapsed().as_millis(),
|
||||
facet_distribution,
|
||||
facet_stats,
|
||||
@ -891,130 +907,6 @@ pub fn perform_search(
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
struct AttributesFormat {
|
||||
attributes_to_retrieve: Option<BTreeSet<String>>,
|
||||
attributes_to_highlight: Option<HashSet<String>>,
|
||||
attributes_to_crop: Option<Vec<String>>,
|
||||
crop_length: usize,
|
||||
crop_marker: String,
|
||||
highlight_pre_tag: String,
|
||||
highlight_post_tag: String,
|
||||
show_matches_position: bool,
|
||||
sort: Option<Vec<String>>,
|
||||
show_ranking_score: bool,
|
||||
show_ranking_score_details: bool,
|
||||
}
|
||||
|
||||
fn make_hits(
|
||||
index: &Index,
|
||||
rtxn: &RoTxn<'_>,
|
||||
format: AttributesFormat,
|
||||
matching_words: milli::MatchingWords,
|
||||
documents_ids: Vec<u32>,
|
||||
document_scores: Vec<Vec<ScoreDetails>>,
|
||||
) -> Result<Vec<SearchHit>, MeilisearchHttpError> {
|
||||
let fields_ids_map = index.fields_ids_map(rtxn).unwrap();
|
||||
let displayed_ids = index
|
||||
.displayed_fields_ids(rtxn)?
|
||||
.map(|fields| fields.into_iter().collect::<BTreeSet<_>>())
|
||||
.unwrap_or_else(|| fields_ids_map.iter().map(|(id, _)| id).collect());
|
||||
let fids = |attrs: &BTreeSet<String>| {
|
||||
let mut ids = BTreeSet::new();
|
||||
for attr in attrs {
|
||||
if attr == "*" {
|
||||
ids.clone_from(&displayed_ids);
|
||||
break;
|
||||
}
|
||||
|
||||
if let Some(id) = fields_ids_map.id(attr) {
|
||||
ids.insert(id);
|
||||
}
|
||||
}
|
||||
ids
|
||||
};
|
||||
let to_retrieve_ids: BTreeSet<_> = format
|
||||
.attributes_to_retrieve
|
||||
.as_ref()
|
||||
.map(fids)
|
||||
.unwrap_or_else(|| displayed_ids.clone())
|
||||
.intersection(&displayed_ids)
|
||||
.cloned()
|
||||
.collect();
|
||||
let attr_to_highlight = format.attributes_to_highlight.unwrap_or_default();
|
||||
let attr_to_crop = format.attributes_to_crop.unwrap_or_default();
|
||||
let formatted_options = compute_formatted_options(
|
||||
&attr_to_highlight,
|
||||
&attr_to_crop,
|
||||
format.crop_length,
|
||||
&to_retrieve_ids,
|
||||
&fields_ids_map,
|
||||
&displayed_ids,
|
||||
);
|
||||
let mut tokenizer_builder = TokenizerBuilder::default();
|
||||
tokenizer_builder.create_char_map(true);
|
||||
let script_lang_map = index.script_language(rtxn)?;
|
||||
if !script_lang_map.is_empty() {
|
||||
tokenizer_builder.allow_list(&script_lang_map);
|
||||
}
|
||||
let separators = index.allowed_separators(rtxn)?;
|
||||
let separators: Option<Vec<_>> =
|
||||
separators.as_ref().map(|x| x.iter().map(String::as_str).collect());
|
||||
if let Some(ref separators) = separators {
|
||||
tokenizer_builder.separators(separators);
|
||||
}
|
||||
let dictionary = index.dictionary(rtxn)?;
|
||||
let dictionary: Option<Vec<_>> =
|
||||
dictionary.as_ref().map(|x| x.iter().map(String::as_str).collect());
|
||||
if let Some(ref dictionary) = dictionary {
|
||||
tokenizer_builder.words_dict(dictionary);
|
||||
}
|
||||
let mut formatter_builder = MatcherBuilder::new(matching_words, tokenizer_builder.build());
|
||||
formatter_builder.crop_marker(format.crop_marker);
|
||||
formatter_builder.highlight_prefix(format.highlight_pre_tag);
|
||||
formatter_builder.highlight_suffix(format.highlight_post_tag);
|
||||
let mut documents = Vec::new();
|
||||
let documents_iter = index.documents(rtxn, documents_ids)?;
|
||||
for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
|
||||
// First generate a document with all the displayed fields
|
||||
let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
|
||||
|
||||
// select the attributes to retrieve
|
||||
let attributes_to_retrieve = to_retrieve_ids
|
||||
.iter()
|
||||
.map(|&fid| fields_ids_map.name(fid).expect("Missing field name"));
|
||||
let mut document =
|
||||
permissive_json_pointer::select_values(&displayed_document, attributes_to_retrieve);
|
||||
|
||||
let (matches_position, formatted) = format_fields(
|
||||
&displayed_document,
|
||||
&fields_ids_map,
|
||||
&formatter_builder,
|
||||
&formatted_options,
|
||||
format.show_matches_position,
|
||||
&displayed_ids,
|
||||
)?;
|
||||
|
||||
if let Some(sort) = format.sort.as_ref() {
|
||||
insert_geo_distance(sort, &mut document);
|
||||
}
|
||||
|
||||
let ranking_score =
|
||||
format.show_ranking_score.then(|| ScoreDetails::global_score(score.iter()));
|
||||
let ranking_score_details =
|
||||
format.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
|
||||
|
||||
let hit = SearchHit {
|
||||
document,
|
||||
formatted,
|
||||
matches_position,
|
||||
ranking_score_details,
|
||||
ranking_score,
|
||||
};
|
||||
documents.push(hit);
|
||||
}
|
||||
Ok(documents)
|
||||
}
|
||||
|
||||
pub fn perform_facet_search(
|
||||
index: &Index,
|
||||
search_query: SearchQuery,
|
||||
@ -1049,95 +941,6 @@ pub fn perform_facet_search(
|
||||
})
|
||||
}
|
||||
|
||||
pub fn perform_similar(
|
||||
index: &Index,
|
||||
query: SimilarQuery,
|
||||
embedder_name: String,
|
||||
embedder: Arc<Embedder>,
|
||||
) -> Result<SimilarResult, ResponseError> {
|
||||
let before_search = Instant::now();
|
||||
let rtxn = index.read_txn()?;
|
||||
|
||||
let SimilarQuery {
|
||||
id,
|
||||
offset,
|
||||
limit,
|
||||
filter: _,
|
||||
embedder: _,
|
||||
attributes_to_retrieve,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
} = query;
|
||||
|
||||
// using let-else rather than `?` so that the borrow checker identifies we're always returning here,
|
||||
// preventing a use-after-move
|
||||
let Some(internal_id) = index.external_documents_ids().get(&rtxn, &id)? else {
|
||||
return Err(ResponseError::from_msg(
|
||||
MeilisearchHttpError::DocumentNotFound(id.into_inner()).to_string(),
|
||||
Code::NotFoundSimilarId,
|
||||
));
|
||||
};
|
||||
|
||||
let mut similar =
|
||||
milli::Similar::new(internal_id, offset, limit, index, &rtxn, embedder_name, embedder);
|
||||
|
||||
if let Some(ref filter) = query.filter {
|
||||
if let Some(facets) = parse_filter(filter)
|
||||
// inject InvalidSimilarFilter code
|
||||
.map_err(|e| ResponseError::from_msg(e.to_string(), Code::InvalidSimilarFilter))?
|
||||
{
|
||||
similar.filter(facets);
|
||||
}
|
||||
}
|
||||
|
||||
let milli::SearchResult {
|
||||
documents_ids,
|
||||
matching_words: _,
|
||||
candidates,
|
||||
document_scores,
|
||||
degraded: _,
|
||||
used_negative_operator: _,
|
||||
} = similar.execute().map_err(|err| match err {
|
||||
milli::Error::UserError(milli::UserError::InvalidFilter(_)) => {
|
||||
ResponseError::from_msg(err.to_string(), Code::InvalidSimilarFilter)
|
||||
}
|
||||
err => err.into(),
|
||||
})?;
|
||||
|
||||
let format = AttributesFormat {
|
||||
attributes_to_retrieve,
|
||||
attributes_to_highlight: None,
|
||||
attributes_to_crop: None,
|
||||
crop_length: DEFAULT_CROP_LENGTH(),
|
||||
crop_marker: DEFAULT_CROP_MARKER(),
|
||||
highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
|
||||
highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
|
||||
show_matches_position: false,
|
||||
sort: None,
|
||||
show_ranking_score,
|
||||
show_ranking_score_details,
|
||||
};
|
||||
|
||||
let hits = make_hits(index, &rtxn, format, Default::default(), documents_ids, document_scores)?;
|
||||
|
||||
let max_total_hits = index
|
||||
.pagination_max_total_hits(&rtxn)
|
||||
.map_err(milli::Error::from)?
|
||||
.map(|x| x as usize)
|
||||
.unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
|
||||
|
||||
let number_of_hits = min(candidates.len() as usize, max_total_hits);
|
||||
let hits_info = HitsInfo::OffsetLimit { limit, offset, estimated_total_hits: number_of_hits };
|
||||
|
||||
let result = SimilarResult {
|
||||
hits,
|
||||
hits_info,
|
||||
id: id.into_inner(),
|
||||
processing_time_ms: before_search.elapsed().as_millis(),
|
||||
};
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
fn insert_geo_distance(sorts: &[String], document: &mut Document) {
|
||||
lazy_static::lazy_static! {
|
||||
static ref GEO_REGEX: Regex =
|
||||
|
||||
@ -85,13 +85,8 @@ impl SearchQueue {
|
||||
},
|
||||
|
||||
search_request = receive_new_searches.recv() => {
|
||||
let search_request = match search_request {
|
||||
Some(search_request) => search_request,
|
||||
// This should never happen while actix-web is running, but it's not a reason to crash
|
||||
// and it can generate a lot of noise in the tests.
|
||||
None => continue,
|
||||
};
|
||||
|
||||
// this unwrap is safe because we're sure the `SearchQueue` still lives somewhere in actix-web
|
||||
let search_request = search_request.unwrap();
|
||||
if searches_running < usize::from(parallelism) && queue.is_empty() {
|
||||
searches_running += 1;
|
||||
// if the search requests die it's not a hard error on our side
|
||||
|
||||
@ -380,43 +380,6 @@ impl Index<'_> {
|
||||
self.service.get(url).await
|
||||
}
|
||||
|
||||
/// Performs both GET and POST similar queries
|
||||
pub async fn similar(
|
||||
&self,
|
||||
query: Value,
|
||||
test: impl Fn(Value, StatusCode) + UnwindSafe + Clone,
|
||||
) {
|
||||
let post = self.similar_post(query.clone()).await;
|
||||
|
||||
let query = yaup::to_string(&query).unwrap();
|
||||
let get = self.similar_get(&query).await;
|
||||
|
||||
insta::allow_duplicates! {
|
||||
let (response, code) = post;
|
||||
let t = test.clone();
|
||||
if let Err(e) = catch_unwind(move || t(response, code)) {
|
||||
eprintln!("Error with post search");
|
||||
resume_unwind(e);
|
||||
}
|
||||
|
||||
let (response, code) = get;
|
||||
if let Err(e) = catch_unwind(move || test(response, code)) {
|
||||
eprintln!("Error with get search");
|
||||
resume_unwind(e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub async fn similar_post(&self, query: Value) -> (Value, StatusCode) {
|
||||
let url = format!("/indexes/{}/similar", urlencode(self.uid.as_ref()));
|
||||
self.service.post_encoded(url, query, self.encoder).await
|
||||
}
|
||||
|
||||
pub async fn similar_get(&self, query: &str) -> (Value, StatusCode) {
|
||||
let url = format!("/indexes/{}/similar?{}", urlencode(self.uid.as_ref()), query);
|
||||
self.service.get(url).await
|
||||
}
|
||||
|
||||
pub async fn facet_search(&self, query: Value) -> (Value, StatusCode) {
|
||||
let url = format!("/indexes/{}/facet-search", urlencode(self.uid.as_ref()));
|
||||
self.service.post_encoded(url, query, self.encoder).await
|
||||
|
||||
@ -1859,7 +1859,8 @@ async fn import_dump_v6_containing_experimental_features() {
|
||||
{
|
||||
"vectorStore": false,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
|
||||
@ -20,7 +20,8 @@ async fn experimental_features() {
|
||||
{
|
||||
"vectorStore": false,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -31,7 +32,8 @@ async fn experimental_features() {
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -42,7 +44,8 @@ async fn experimental_features() {
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -54,7 +57,8 @@ async fn experimental_features() {
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -66,7 +70,8 @@ async fn experimental_features() {
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
}
|
||||
@ -85,7 +90,8 @@ async fn experimental_feature_metrics() {
|
||||
{
|
||||
"vectorStore": false,
|
||||
"metrics": true,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -140,7 +146,7 @@ async fn errors() {
|
||||
meili_snap::snapshot!(code, @"400 Bad Request");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
|
||||
{
|
||||
"message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`",
|
||||
"message": "Unknown field `NotAFeature`: expected one of `vectorStore`, `metrics`, `logsRoute`, `exportPuffinReports`",
|
||||
"code": "bad_request",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#bad_request"
|
||||
|
||||
@ -8,7 +8,6 @@ mod index;
|
||||
mod logs;
|
||||
mod search;
|
||||
mod settings;
|
||||
mod similar;
|
||||
mod snapshot;
|
||||
mod stats;
|
||||
mod swap_indexes;
|
||||
|
||||
@ -5,10 +5,7 @@ use crate::common::index::Index;
|
||||
use crate::common::{Server, Value};
|
||||
use crate::json;
|
||||
|
||||
async fn index_with_documents_user_provided<'a>(
|
||||
server: &'a Server,
|
||||
documents: &Value,
|
||||
) -> Index<'a> {
|
||||
async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
|
||||
let index = server.index("test");
|
||||
|
||||
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
@ -18,7 +15,8 @@ async fn index_with_documents_user_provided<'a>(
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
@ -36,38 +34,7 @@ async fn index_with_documents_user_provided<'a>(
|
||||
index
|
||||
}
|
||||
|
||||
async fn index_with_documents_hf<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
|
||||
let index = server.index("test");
|
||||
|
||||
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
meili_snap::snapshot!(code, @"200 OK");
|
||||
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({ "embedders": {"default": {
|
||||
"source": "huggingFace",
|
||||
"model": "sentence-transformers/all-MiniLM-L6-v2",
|
||||
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
|
||||
"documentTemplate": "{{doc.title}}, {{doc.desc}}"
|
||||
}}} ))
|
||||
.await;
|
||||
assert_eq!(202, code, "{:?}", response);
|
||||
index.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.add_documents(documents.clone(), None).await;
|
||||
assert_eq!(202, code, "{:?}", response);
|
||||
index.wait_task(response.uid()).await;
|
||||
index
|
||||
}
|
||||
|
||||
static SIMPLE_SEARCH_DOCUMENTS_VEC: Lazy<Value> = Lazy::new(|| {
|
||||
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
|
||||
json!([
|
||||
{
|
||||
"title": "Shazam!",
|
||||
@ -89,7 +56,7 @@ static SIMPLE_SEARCH_DOCUMENTS_VEC: Lazy<Value> = Lazy::new(|| {
|
||||
}])
|
||||
});
|
||||
|
||||
static SINGLE_DOCUMENT_VEC: Lazy<Value> = Lazy::new(|| {
|
||||
static SINGLE_DOCUMENT: Lazy<Value> = Lazy::new(|| {
|
||||
json!([{
|
||||
"title": "Shazam!",
|
||||
"desc": "a Captain Marvel ersatz",
|
||||
@ -98,29 +65,10 @@ static SINGLE_DOCUMENT_VEC: Lazy<Value> = Lazy::new(|| {
|
||||
}])
|
||||
});
|
||||
|
||||
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
|
||||
json!([
|
||||
{
|
||||
"title": "Shazam!",
|
||||
"desc": "a Captain Marvel ersatz",
|
||||
"id": "1",
|
||||
},
|
||||
{
|
||||
"title": "Captain Planet",
|
||||
"desc": "He's not part of the Marvel Cinematic Universe",
|
||||
"id": "2",
|
||||
},
|
||||
{
|
||||
"title": "Captain Marvel",
|
||||
"desc": "a Shazam ersatz",
|
||||
"id": "3",
|
||||
}])
|
||||
});
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn simple_search() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
@ -137,8 +85,8 @@ async fn simple_search() {
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"2");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"1");
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
@ -150,59 +98,10 @@ async fn simple_search() {
|
||||
snapshot!(response["semanticHitCount"], @"3");
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn simple_search_hf() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_hf(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
let (response, code) =
|
||||
index.search_post(json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}})).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"0");
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
// disable ranking score as the vectors between architectures are not equal
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.55}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"1");
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.8}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"3");
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Movie World", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"3");
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
json!({"q": "Wonder replacement", "hybrid": {"semanticRatio": 0.2}, "showRankingScore": false}),
|
||||
)
|
||||
.await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"3");
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn distribution_shift() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
let search = json!({"q": "Captain", "vector": [1.0, 1.0], "showRankingScore": true, "hybrid": {"semanticRatio": 1.0}});
|
||||
let (response, code) = index.search_post(search.clone()).await;
|
||||
@ -234,7 +133,7 @@ async fn distribution_shift() {
|
||||
#[actix_rt::test]
|
||||
async fn highlighter() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
|
||||
@ -285,7 +184,7 @@ async fn highlighter() {
|
||||
#[actix_rt::test]
|
||||
async fn invalid_semantic_ratio() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
@ -357,7 +256,7 @@ async fn invalid_semantic_ratio() {
|
||||
#[actix_rt::test]
|
||||
async fn single_document() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SINGLE_DOCUMENT_VEC).await;
|
||||
let index = index_with_documents(&server, &SINGLE_DOCUMENT).await;
|
||||
|
||||
let (response, code) = index
|
||||
.search_post(
|
||||
@ -373,7 +272,7 @@ async fn single_document() {
|
||||
#[actix_rt::test]
|
||||
async fn query_combination() {
|
||||
let server = Server::new().await;
|
||||
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
|
||||
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
|
||||
|
||||
// search without query and vector, but with hybrid => still placeholder
|
||||
let (response, code) = index
|
||||
@ -432,7 +331,7 @@ async fn query_combination() {
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9242424242424242}]"###);
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.996969696969697},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.996969696969697},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.8848484848484849}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"null");
|
||||
|
||||
// query + vector, no hybrid keyword =>
|
||||
@ -475,6 +374,6 @@ async fn query_combination() {
|
||||
.await;
|
||||
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9242424242424242}]"###);
|
||||
snapshot!(response["hits"], @r###"[{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.9848484848484848}]"###);
|
||||
snapshot!(response["semanticHitCount"], @"0");
|
||||
}
|
||||
|
||||
@ -680,26 +680,6 @@ async fn search_facet_distribution() {
|
||||
},
|
||||
)
|
||||
.await;
|
||||
|
||||
index.update_settings(json!({"filterableAttributes": ["doggos.name"]})).await;
|
||||
index.wait_task(5).await;
|
||||
|
||||
index
|
||||
.search(
|
||||
json!({
|
||||
"facets": ["doggos.name"]
|
||||
}),
|
||||
|response, code| {
|
||||
assert_eq!(code, 200, "{}", response);
|
||||
let dist = response["facetDistribution"].as_object().unwrap();
|
||||
assert_eq!(dist.len(), 1);
|
||||
assert_eq!(
|
||||
dist["doggos.name"],
|
||||
json!({ "bobby": 1, "buddy": 1, "gros bill": 1, "turbo": 1, "fast": 1})
|
||||
);
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
@ -915,9 +895,9 @@ async fn test_score_details() {
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
231.0,
|
||||
32.0
|
||||
-100,
|
||||
231,
|
||||
32
|
||||
]
|
||||
},
|
||||
"_rankingScoreDetails": {
|
||||
@ -941,7 +921,7 @@ async fn test_score_details() {
|
||||
"order": 3,
|
||||
"attributeRankingOrderScore": 1.0,
|
||||
"queryWordDistanceScore": 0.8095238095238095,
|
||||
"score": 0.8095238095238095
|
||||
"score": 0.9727891156462584
|
||||
},
|
||||
"exactness": {
|
||||
"order": 4,
|
||||
@ -1116,9 +1096,9 @@ async fn experimental_feature_vector_store() {
|
||||
"id": "287947",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
1.0,
|
||||
2.0,
|
||||
3.0
|
||||
1,
|
||||
2,
|
||||
3
|
||||
]
|
||||
},
|
||||
"_rankingScore": 1.0
|
||||
@ -1128,9 +1108,9 @@ async fn experimental_feature_vector_store() {
|
||||
"id": "299537",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
1.0,
|
||||
2.0,
|
||||
54.0
|
||||
1,
|
||||
2,
|
||||
54
|
||||
]
|
||||
},
|
||||
"_rankingScore": 0.9129111766815186
|
||||
@ -1140,9 +1120,9 @@ async fn experimental_feature_vector_store() {
|
||||
"id": "450465",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
340.0,
|
||||
90.0
|
||||
-100,
|
||||
340,
|
||||
90
|
||||
]
|
||||
},
|
||||
"_rankingScore": 0.8106412887573242
|
||||
@ -1152,9 +1132,9 @@ async fn experimental_feature_vector_store() {
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
231.0,
|
||||
32.0
|
||||
-100,
|
||||
231,
|
||||
32
|
||||
]
|
||||
},
|
||||
"_rankingScore": 0.7412010431289673
|
||||
@ -1164,9 +1144,9 @@ async fn experimental_feature_vector_store() {
|
||||
"id": "522681",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
10.0,
|
||||
-23.0,
|
||||
32.0
|
||||
10,
|
||||
-23,
|
||||
32
|
||||
]
|
||||
},
|
||||
"_rankingScore": 0.6972063183784485
|
||||
@ -1425,9 +1405,9 @@ async fn simple_search_with_strange_synonyms() {
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
231.0,
|
||||
32.0
|
||||
-100,
|
||||
231,
|
||||
32
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -1446,9 +1426,9 @@ async fn simple_search_with_strange_synonyms() {
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
231.0,
|
||||
32.0
|
||||
-100,
|
||||
231,
|
||||
32
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -1467,9 +1447,9 @@ async fn simple_search_with_strange_synonyms() {
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
231.0,
|
||||
32.0
|
||||
-100,
|
||||
231,
|
||||
32
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
@ -75,9 +75,9 @@ async fn simple_search_single_index() {
|
||||
"id": "450465",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
340.0,
|
||||
90.0
|
||||
-100,
|
||||
340,
|
||||
90
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -96,9 +96,9 @@ async fn simple_search_single_index() {
|
||||
"id": "299537",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
1.0,
|
||||
2.0,
|
||||
54.0
|
||||
1,
|
||||
2,
|
||||
54
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -194,9 +194,9 @@ async fn simple_search_two_indexes() {
|
||||
"id": "450465",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-100.0,
|
||||
340.0,
|
||||
90.0
|
||||
-100,
|
||||
340,
|
||||
90
|
||||
]
|
||||
}
|
||||
}
|
||||
@ -227,9 +227,9 @@ async fn simple_search_two_indexes() {
|
||||
"cattos": "pésti",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
1.0,
|
||||
2.0,
|
||||
3.0
|
||||
1,
|
||||
2,
|
||||
3
|
||||
]
|
||||
}
|
||||
},
|
||||
@ -249,9 +249,9 @@ async fn simple_search_two_indexes() {
|
||||
],
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
1.0,
|
||||
2.0,
|
||||
54.0
|
||||
1,
|
||||
2,
|
||||
54
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
@ -285,10 +285,10 @@ async fn attributes_ranking_rule_order() {
|
||||
@r###"
|
||||
[
|
||||
{
|
||||
"id": "1"
|
||||
"id": "2"
|
||||
},
|
||||
{
|
||||
"id": "2"
|
||||
"id": "1"
|
||||
}
|
||||
]
|
||||
"###
|
||||
|
||||
@ -98,7 +98,8 @@ async fn secrets_are_hidden_in_settings() {
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
"logsRoute": false,
|
||||
"exportPuffinReports": false
|
||||
}
|
||||
"###);
|
||||
|
||||
|
||||
@ -1,696 +0,0 @@
|
||||
use meili_snap::*;
|
||||
|
||||
use super::DOCUMENTS;
|
||||
use crate::common::Server;
|
||||
use crate::json;
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_unexisting_index() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Index `test` not found.",
|
||||
"code": "index_not_found",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#index_not_found"
|
||||
});
|
||||
|
||||
index
|
||||
.similar(json!({"id": 287947}), |response, code| {
|
||||
assert_eq!(code, 404);
|
||||
assert_eq!(response, expected_response);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_unexisting_parameter() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 287947, "marin": "hello"}), |response, code| {
|
||||
assert_eq!(code, 400, "{}", response);
|
||||
assert_eq!(response["code"], "bad_request");
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_feature_not_enabled() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Using the similar API requires enabling the `vector store` experimental feature. See https://github.com/meilisearch/product/discussions/677",
|
||||
"code": "feature_not_enabled",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#feature_not_enabled"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_bad_id() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": ["doggo"]})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
|
||||
"code": "invalid_similar_id",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_id"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_invalid_id() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": "http://invalid-docid/"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value at `.id`: the value of `id` is invalid. A document identifier can be of type integer or string, only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and underscores (_).",
|
||||
"code": "invalid_similar_id",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_id"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_not_found_id() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": "definitely-doesnt-exist"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Document `definitely-doesnt-exist` not found.",
|
||||
"code": "not_found_similar_id",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#not_found_similar_id"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_bad_offset() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947, "offset": "doggo"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value type at `.offset`: expected a positive integer, but found a string: `\"doggo\"`",
|
||||
"code": "invalid_similar_offset",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index.similar_get("id=287947&offset=doggo").await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value in parameter `offset`: could not parse `doggo` as a positive integer",
|
||||
"code": "invalid_similar_offset",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_offset"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_bad_limit() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({"id": 287947, "limit": "doggo"})).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value type at `.limit`: expected a positive integer, but found a string: `\"doggo\"`",
|
||||
"code": "invalid_similar_limit",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index.similar_get("id=287946&limit=doggo").await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid value in parameter `limit`: could not parse `doggo` as a positive integer",
|
||||
"code": "invalid_similar_limit",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_limit"
|
||||
}
|
||||
"###);
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn similar_bad_filter() {
|
||||
// Since a filter is deserialized as a json Value it will never fail to deserialize.
|
||||
// Thus the error message is not generated by deserr but written by us.
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
snapshot!(code, @"202 Accepted");
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let (response, code) = index.similar_post(json!({ "id": 287947, "filter": true })).await;
|
||||
snapshot!(code, @"400 Bad Request");
|
||||
snapshot!(json_string!(response), @r###"
|
||||
{
|
||||
"message": "Invalid syntax for the filter parameter: `expected String, Array, found: true`.",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
}
|
||||
"###);
|
||||
// Can't make the `filter` fail with a get search since it'll accept anything as a strings.
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_invalid_syntax_object() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "title & Glass"}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_invalid_syntax_array() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Was expecting an operation `=`, `!=`, `>=`, `>`, `<=`, `<`, `IN`, `NOT IN`, `TO`, `EXISTS`, `NOT EXISTS`, `IS NULL`, `IS NOT NULL`, `IS EMPTY`, `IS NOT EMPTY`, `_geoRadius`, or `_geoBoundingBox` at `title & Glass`.\n1:14 title & Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["title & Glass"]}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_invalid_syntax_string() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Found unexpected characters at the end of the filter: `XOR title = Glass`. You probably forgot an `OR` or an `AND` rule.\n15:32 title = Glass XOR title = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(
|
||||
json!({"id": 287947, "filter": "title = Glass XOR title = Glass"}),
|
||||
|response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
},
|
||||
)
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_invalid_attribute_array() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["many = Glass"]}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_invalid_attribute_string() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "Attribute `many` is not filterable. Available filterable attributes are: `title`.\n1:5 many = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "many = Glass"}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_geo_attribute_array() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geo = Glass"]}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_geo_attribute_string() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geo` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:13 _geo = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geo = Glass"}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_attribute_array() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geoDistance = Glass"]}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_attribute_string() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geoDistance` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:21 _geoDistance = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geoDistance = Glass"}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_geo_point_array() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": ["_geoPoint = Glass"]}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter_reserved_geo_point_string() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
server.set_features(json!({"vectorStore": true})).await;
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
let expected_response = json!({
|
||||
"message": "`_geoPoint` is a reserved keyword and thus can't be used as a filter expression. Use the `_geoRadius(latitude, longitude, distance)` or `_geoBoundingBox([latitude, longitude], [latitude, longitude])` built-in rules to filter on `_geo` coordinates.\n1:18 _geoPoint = Glass",
|
||||
"code": "invalid_similar_filter",
|
||||
"type": "invalid_request",
|
||||
"link": "https://docs.meilisearch.com/errors#invalid_similar_filter"
|
||||
});
|
||||
index
|
||||
.similar(json!({"id": 287947, "filter": "_geoPoint = Glass"}), |response, code| {
|
||||
assert_eq!(response, expected_response);
|
||||
assert_eq!(code, 400);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
@ -1,373 +0,0 @@
|
||||
mod errors;
|
||||
|
||||
use meili_snap::{json_string, snapshot};
|
||||
use once_cell::sync::Lazy;
|
||||
|
||||
use crate::common::{Server, Value};
|
||||
use crate::json;
|
||||
|
||||
static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
|
||||
json!([
|
||||
{
|
||||
"title": "Shazam!",
|
||||
"release_year": 2019,
|
||||
"id": "287947",
|
||||
// Three semantic properties:
|
||||
// 1. magic, anything that reminds you of magic
|
||||
// 2. authority, anything that inspires command
|
||||
// 3. horror, anything that inspires fear or dread
|
||||
"_vectors": { "manual": [0.8, 0.4, -0.5]},
|
||||
},
|
||||
{
|
||||
"title": "Captain Marvel",
|
||||
"release_year": 2019,
|
||||
"id": "299537",
|
||||
"_vectors": { "manual": [0.6, 0.8, -0.2] },
|
||||
},
|
||||
{
|
||||
"title": "Escape Room",
|
||||
"release_year": 2019,
|
||||
"id": "522681",
|
||||
"_vectors": { "manual": [0.1, 0.6, 0.8] },
|
||||
},
|
||||
{
|
||||
"title": "How to Train Your Dragon: The Hidden World",
|
||||
"release_year": 2019,
|
||||
"id": "166428",
|
||||
"_vectors": { "manual": [0.7, 0.7, -0.4] },
|
||||
},
|
||||
{
|
||||
"title": "All Quiet on the Western Front",
|
||||
"release_year": 1930,
|
||||
"id": "143",
|
||||
"_vectors": { "manual": [-0.5, 0.3, 0.85] },
|
||||
}
|
||||
])
|
||||
});
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn basic() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(value, @r###"
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 143}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "Escape Room",
|
||||
"release_year": 2019,
|
||||
"id": "522681",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.1,
|
||||
0.6,
|
||||
0.8
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "Captain Marvel",
|
||||
"release_year": 2019,
|
||||
"id": "299537",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.6,
|
||||
0.8,
|
||||
-0.2
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "How to Train Your Dragon: The Hidden World",
|
||||
"release_year": 2019,
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.7,
|
||||
0.7,
|
||||
-0.4
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "Shazam!",
|
||||
"release_year": 2019,
|
||||
"id": "287947",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.8,
|
||||
0.4,
|
||||
-0.5
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": "299537"}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "How to Train Your Dragon: The Hidden World",
|
||||
"release_year": 2019,
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.7,
|
||||
0.7,
|
||||
-0.4
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "Shazam!",
|
||||
"release_year": 2019,
|
||||
"id": "287947",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.8,
|
||||
0.4,
|
||||
-0.5
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "Escape Room",
|
||||
"release_year": 2019,
|
||||
"id": "522681",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.1,
|
||||
0.6,
|
||||
0.8
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "All Quiet on the Western Front",
|
||||
"release_year": 1930,
|
||||
"id": "143",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-0.5,
|
||||
0.3,
|
||||
0.85
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn filter() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(value, @r###"
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title", "release_year"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 522681, "filter": "release_year = 2019"}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "Captain Marvel",
|
||||
"release_year": 2019,
|
||||
"id": "299537",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.6,
|
||||
0.8,
|
||||
-0.2
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "How to Train Your Dragon: The Hidden World",
|
||||
"release_year": 2019,
|
||||
"id": "166428",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.7,
|
||||
0.7,
|
||||
-0.4
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"title": "Shazam!",
|
||||
"release_year": 2019,
|
||||
"id": "287947",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.8,
|
||||
0.4,
|
||||
-0.5
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 522681, "filter": "release_year < 2000"}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "All Quiet on the Western Front",
|
||||
"release_year": 1930,
|
||||
"id": "143",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
-0.5,
|
||||
0.3,
|
||||
0.85
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
|
||||
#[actix_rt::test]
|
||||
async fn limit_and_offset() {
|
||||
let server = Server::new().await;
|
||||
let index = server.index("test");
|
||||
let (value, code) = server.set_features(json!({"vectorStore": true})).await;
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(value, @r###"
|
||||
{
|
||||
"vectorStore": true,
|
||||
"metrics": false,
|
||||
"logsRoute": false
|
||||
}
|
||||
"###);
|
||||
|
||||
let (response, code) = index
|
||||
.update_settings(json!({
|
||||
"embedders": {
|
||||
"manual": {
|
||||
"source": "userProvided",
|
||||
"dimensions": 3,
|
||||
}
|
||||
},
|
||||
"filterableAttributes": ["title"]}))
|
||||
.await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
server.wait_task(response.uid()).await;
|
||||
|
||||
let documents = DOCUMENTS.clone();
|
||||
let (value, code) = index.add_documents(documents, None).await;
|
||||
snapshot!(code, @"202 Accepted");
|
||||
index.wait_task(value.uid()).await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 143, "limit": 1}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "Escape Room",
|
||||
"release_year": 2019,
|
||||
"id": "522681",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.1,
|
||||
0.6,
|
||||
0.8
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
|
||||
index
|
||||
.similar(json!({"id": 143, "limit": 1, "offset": 1}), |response, code| {
|
||||
snapshot!(code, @"200 OK");
|
||||
snapshot!(json_string!(response["hits"]), @r###"
|
||||
[
|
||||
{
|
||||
"title": "Captain Marvel",
|
||||
"release_year": 2019,
|
||||
"id": "299537",
|
||||
"_vectors": {
|
||||
"manual": [
|
||||
0.6,
|
||||
0.8,
|
||||
-0.2
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
"###);
|
||||
})
|
||||
.await;
|
||||
}
|
||||
@ -1,5 +1,6 @@
|
||||
use std::time::Duration;
|
||||
|
||||
use actix_rt::time::sleep;
|
||||
use meili_snap::{json_string, snapshot};
|
||||
use meilisearch::option::ScheduleSnapshot;
|
||||
use meilisearch::Opt;
|
||||
@ -52,29 +53,11 @@ async fn perform_snapshot() {
|
||||
|
||||
index.load_test_set().await;
|
||||
|
||||
let (task, code) = server.index("test1").create(Some("prim")).await;
|
||||
meili_snap::snapshot!(code, @"202 Accepted");
|
||||
server.index("test1").create(Some("prim")).await;
|
||||
|
||||
index.wait_task(task.uid()).await;
|
||||
index.wait_task(2).await;
|
||||
|
||||
// wait for the _next task_ to process, aka the snapshot that should be enqueued at some point
|
||||
|
||||
println!("waited for the next task to finish");
|
||||
let now = std::time::Instant::now();
|
||||
let next_task = task.uid() + 1;
|
||||
loop {
|
||||
let (value, code) = index.get_task(next_task).await;
|
||||
dbg!(&value);
|
||||
if code != 404 && value["status"].as_str() == Some("succeeded") {
|
||||
break;
|
||||
}
|
||||
|
||||
if now.elapsed() > Duration::from_secs(30) {
|
||||
panic!("The snapshot didn't schedule in 30s even though it was supposed to be scheduled every 2s: {}",
|
||||
serde_json::to_string_pretty(&value).unwrap()
|
||||
);
|
||||
}
|
||||
}
|
||||
sleep(Duration::from_secs(2)).await;
|
||||
|
||||
let temp = tempfile::tempdir().unwrap();
|
||||
|
||||
|
||||
@ -80,7 +80,9 @@ fn main() -> anyhow::Result<()> {
|
||||
/// Clears the task queue located at `db_path`.
|
||||
fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
|
||||
let path = db_path.join("tasks");
|
||||
let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&path) }
|
||||
let env = EnvOpenOptions::new()
|
||||
.max_dbs(100)
|
||||
.open(&path)
|
||||
.with_context(|| format!("While trying to open {:?}", path.display()))?;
|
||||
|
||||
eprintln!("Deleting tasks from the database...");
|
||||
@ -127,7 +129,7 @@ fn clear_task_queue(db_path: PathBuf) -> anyhow::Result<()> {
|
||||
}
|
||||
}
|
||||
|
||||
eprintln!("Successfully deleted {count} content files from disk!");
|
||||
eprintln!("Sucessfully deleted {count} content files from disk!");
|
||||
|
||||
Ok(())
|
||||
}
|
||||
@ -191,7 +193,9 @@ fn export_a_dump(
|
||||
FileStore::new(db_path.join("update_files")).context("While opening the FileStore")?;
|
||||
|
||||
let index_scheduler_path = db_path.join("tasks");
|
||||
let env = unsafe { EnvOpenOptions::new().max_dbs(100).open(&index_scheduler_path) }
|
||||
let env = EnvOpenOptions::new()
|
||||
.max_dbs(100)
|
||||
.open(&index_scheduler_path)
|
||||
.with_context(|| format!("While trying to open {:?}", index_scheduler_path.display()))?;
|
||||
|
||||
eprintln!("Dumping the keys...");
|
||||
|
||||
@ -30,7 +30,7 @@ grenad = { version = "0.4.6", default-features = false, features = [
|
||||
"rayon",
|
||||
"tempfile",
|
||||
] }
|
||||
heed = { version = "0.20.1", default-features = false, features = [
|
||||
heed = { version = "0.20.0-alpha.9", default-features = false, features = [
|
||||
"serde-json",
|
||||
"serde-bincode",
|
||||
"read-txn-no-tls",
|
||||
@ -67,6 +67,9 @@ filter-parser = { path = "../filter-parser" }
|
||||
# documents words self-join
|
||||
itertools = "0.11.0"
|
||||
|
||||
# profiling
|
||||
puffin = "0.16.0"
|
||||
|
||||
csv = "1.3.0"
|
||||
candle-core = { version = "0.4.1" }
|
||||
candle-transformers = { version = "0.4.1" }
|
||||
@ -79,10 +82,10 @@ hf-hub = { git = "https://github.com/dureuill/hf-hub.git", branch = "rust_tls",
|
||||
] }
|
||||
tiktoken-rs = "0.5.8"
|
||||
liquid = "0.26.4"
|
||||
arroy = "0.3.1"
|
||||
arroy = "0.2.0"
|
||||
rand = "0.8.5"
|
||||
tracing = "0.1.40"
|
||||
ureq = { version = "2.9.7", features = ["json"] }
|
||||
ureq = { version = "2.9.6", features = ["json"] }
|
||||
url = "2.5.0"
|
||||
|
||||
[dev-dependencies]
|
||||
|
||||
@ -48,8 +48,8 @@ fn main() -> Result<(), Box<dyn Error>> {
|
||||
|
||||
let start = Instant::now();
|
||||
|
||||
let mut ctx = SearchContext::new(&index, &txn)?;
|
||||
let universe = filtered_universe(ctx.index, ctx.txn, &None)?;
|
||||
let mut ctx = SearchContext::new(&index, &txn);
|
||||
let universe = filtered_universe(&ctx, &None)?;
|
||||
|
||||
let docs = execute_search(
|
||||
&mut ctx,
|
||||
|
||||
3
milli/fuzz/.gitignore
vendored
3
milli/fuzz/.gitignore
vendored
@ -1,3 +0,0 @@
|
||||
target
|
||||
corpus
|
||||
artifacts
|
||||
@ -203,7 +203,7 @@ fn parse_csv_header(header: &str) -> (&str, AllowedType) {
|
||||
"string" => (field_name, AllowedType::String),
|
||||
"boolean" => (field_name, AllowedType::Boolean),
|
||||
"number" => (field_name, AllowedType::Number),
|
||||
// if the pattern isn't recognized, we keep the whole field.
|
||||
// if the pattern isn't reconized, we keep the whole field.
|
||||
_otherwise => (header, AllowedType::String),
|
||||
},
|
||||
None => (header, AllowedType::String),
|
||||
|
||||
@ -12,10 +12,7 @@ use bimap::BiHashMap;
|
||||
pub use builder::DocumentsBatchBuilder;
|
||||
pub use enriched::{EnrichedDocument, EnrichedDocumentsBatchCursor, EnrichedDocumentsBatchReader};
|
||||
use obkv::KvReader;
|
||||
pub use primary_key::{
|
||||
validate_document_id_value, DocumentIdExtractionError, FieldIdMapper, PrimaryKey,
|
||||
DEFAULT_PRIMARY_KEY,
|
||||
};
|
||||
pub use primary_key::{DocumentIdExtractionError, FieldIdMapper, PrimaryKey, DEFAULT_PRIMARY_KEY};
|
||||
pub use reader::{DocumentsBatchCursor, DocumentsBatchCursorError, DocumentsBatchReader};
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
|
||||
@ -60,7 +60,7 @@ impl<'a> PrimaryKey<'a> {
|
||||
Some(document_id_bytes) => {
|
||||
let document_id = serde_json::from_slice(document_id_bytes)
|
||||
.map_err(InternalError::SerdeJson)?;
|
||||
match validate_document_id_value(document_id) {
|
||||
match validate_document_id_value(document_id)? {
|
||||
Ok(document_id) => Ok(Ok(document_id)),
|
||||
Err(user_error) => {
|
||||
Ok(Err(DocumentIdExtractionError::InvalidDocumentId(user_error)))
|
||||
@ -88,7 +88,7 @@ impl<'a> PrimaryKey<'a> {
|
||||
}
|
||||
|
||||
match matching_documents_ids.pop() {
|
||||
Some(document_id) => match validate_document_id_value(document_id) {
|
||||
Some(document_id) => match validate_document_id_value(document_id)? {
|
||||
Ok(document_id) => Ok(Ok(document_id)),
|
||||
Err(user_error) => {
|
||||
Ok(Err(DocumentIdExtractionError::InvalidDocumentId(user_error)))
|
||||
@ -159,14 +159,14 @@ fn validate_document_id(document_id: &str) -> Option<&str> {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn validate_document_id_value(document_id: Value) -> StdResult<String, UserError> {
|
||||
pub fn validate_document_id_value(document_id: Value) -> Result<StdResult<String, UserError>> {
|
||||
match document_id {
|
||||
Value::String(string) => match validate_document_id(&string) {
|
||||
Some(s) if s.len() == string.len() => Ok(string),
|
||||
Some(s) => Ok(s.to_string()),
|
||||
None => Err(UserError::InvalidDocumentId { document_id: Value::String(string) }),
|
||||
Some(s) if s.len() == string.len() => Ok(Ok(string)),
|
||||
Some(s) => Ok(Ok(s.to_string())),
|
||||
None => Ok(Err(UserError::InvalidDocumentId { document_id: Value::String(string) })),
|
||||
},
|
||||
Value::Number(number) if number.is_i64() => Ok(number.to_string()),
|
||||
content => Err(UserError::InvalidDocumentId { document_id: content }),
|
||||
Value::Number(number) if number.is_i64() => Ok(Ok(number.to_string())),
|
||||
content => Ok(Err(UserError::InvalidDocumentId { document_id: content })),
|
||||
}
|
||||
}
|
||||
|
||||
@ -32,8 +32,6 @@ pub enum InternalError {
|
||||
DatabaseClosing,
|
||||
#[error("Missing {} in the {db_name} database.", key.unwrap_or("key"))]
|
||||
DatabaseMissingEntry { db_name: &'static str, key: Option<&'static str> },
|
||||
#[error("Missing {key} in the fieldids weights mapping.")]
|
||||
FieldidsWeightsMapMissingEntry { key: FieldId },
|
||||
#[error(transparent)]
|
||||
FieldIdMapMissingEntry(#[from] FieldIdMapMissingEntry),
|
||||
#[error("Missing {key} in the field id mapping.")]
|
||||
@ -48,6 +46,8 @@ pub enum InternalError {
|
||||
GrenadInvalidFormatVersion,
|
||||
#[error("Invalid merge while processing {process}")]
|
||||
IndexingMergingKeys { process: &'static str },
|
||||
#[error("{}", HeedError::InvalidDatabaseTyping)]
|
||||
InvalidDatabaseTyping,
|
||||
#[error(transparent)]
|
||||
RayonThreadPool(#[from] ThreadPoolBuildError),
|
||||
#[error(transparent)]
|
||||
@ -117,8 +117,10 @@ only composed of alphanumeric characters (a-z A-Z 0-9), hyphens (-) and undersco
|
||||
InvalidGeoField(#[from] GeoError),
|
||||
#[error("Invalid vector dimensions: expected: `{}`, found: `{}`.", .expected, .found)]
|
||||
InvalidVectorDimensions { expected: usize, found: usize },
|
||||
#[error("The `_vectors.{subfield}` field in the document with id: `{document_id}` is not an array. Was expecting an array of floats or an array of arrays of floats but instead got `{value}`.")]
|
||||
InvalidVectorsType { document_id: Value, value: Value, subfield: String },
|
||||
#[error("The `_vectors` field in the document with id: `{document_id}` is not an object. Was expecting an object with a key for each embedder with manually provided vectors, but instead got `{value}`")]
|
||||
InvalidVectorsMapType { document_id: String, value: Value },
|
||||
InvalidVectorsMapType { document_id: Value, value: Value },
|
||||
#[error("{0}")]
|
||||
InvalidFilter(String),
|
||||
#[error("Invalid type for filter subexpression: expected: {}, found: {1}.", .0.join(", "))]
|
||||
@ -425,6 +427,7 @@ impl From<HeedError> for Error {
|
||||
// TODO use the encoding
|
||||
HeedError::Encoding(_) => InternalError(Serialization(Encoding { db_name: None })),
|
||||
HeedError::Decoding(_) => InternalError(Serialization(Decoding { db_name: None })),
|
||||
HeedError::InvalidDatabaseTyping => InternalError(InvalidDatabaseTyping),
|
||||
HeedError::DatabaseClosing => InternalError(DatabaseClosing),
|
||||
HeedError::BadOpenOptions { .. } => UserError(InvalidLmdbOpenOptions),
|
||||
}
|
||||
|
||||
@ -1,48 +0,0 @@
|
||||
//! The fieldids weights map is in charge of storing linking the searchable fields with their weights.
|
||||
|
||||
use std::collections::HashMap;
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use crate::{FieldId, FieldsIdsMap, Weight};
|
||||
|
||||
#[derive(Debug, Default, Serialize, Deserialize)]
|
||||
pub struct FieldidsWeightsMap {
|
||||
map: HashMap<FieldId, Weight>,
|
||||
}
|
||||
|
||||
impl FieldidsWeightsMap {
|
||||
/// Insert a field id -> weigth into the map.
|
||||
/// If the map did not have this key present, `None` is returned.
|
||||
/// If the map did have this key present, the value is updated, and the old value is returned.
|
||||
pub fn insert(&mut self, fid: FieldId, weight: Weight) -> Option<Weight> {
|
||||
self.map.insert(fid, weight)
|
||||
}
|
||||
|
||||
/// Create the map from the fields ids maps.
|
||||
/// Should only be called in the case there are NO searchable attributes.
|
||||
/// All the fields will be inserted in the order of the fields ids map with a weight of 0.
|
||||
pub fn from_field_id_map_without_searchable(fid_map: &FieldsIdsMap) -> Self {
|
||||
FieldidsWeightsMap { map: fid_map.ids().map(|fid| (fid, 0)).collect() }
|
||||
}
|
||||
|
||||
/// Removes a field id from the map, returning the associated weight previously in the map.
|
||||
pub fn remove(&mut self, fid: FieldId) -> Option<Weight> {
|
||||
self.map.remove(&fid)
|
||||
}
|
||||
|
||||
/// Returns weight corresponding to the key.
|
||||
pub fn weight(&self, fid: FieldId) -> Option<Weight> {
|
||||
self.map.get(&fid).copied()
|
||||
}
|
||||
|
||||
/// Returns highest weight contained in the map if any.
|
||||
pub fn max_weight(&self) -> Option<Weight> {
|
||||
self.map.values().copied().max()
|
||||
}
|
||||
|
||||
/// Return an iterator visiting all field ids in arbitrary order.
|
||||
pub fn ids(&self) -> impl Iterator<Item = FieldId> + '_ {
|
||||
self.map.keys().copied()
|
||||
}
|
||||
}
|
||||
@ -195,7 +195,7 @@ mod tests {
|
||||
fn merge_cbo_roaring_bitmaps() {
|
||||
let mut buffer = Vec::new();
|
||||
|
||||
let small_data = [
|
||||
let small_data = vec![
|
||||
RoaringBitmap::from_sorted_iter(1..4).unwrap(),
|
||||
RoaringBitmap::from_sorted_iter(2..5).unwrap(),
|
||||
RoaringBitmap::from_sorted_iter(4..6).unwrap(),
|
||||
@ -209,7 +209,7 @@ mod tests {
|
||||
let expected = RoaringBitmap::from_sorted_iter(1..6).unwrap();
|
||||
assert_eq!(bitmap, expected);
|
||||
|
||||
let medium_data = [
|
||||
let medium_data = vec![
|
||||
RoaringBitmap::from_sorted_iter(1..4).unwrap(),
|
||||
RoaringBitmap::from_sorted_iter(2..5).unwrap(),
|
||||
RoaringBitmap::from_sorted_iter(4..8).unwrap(),
|
||||
|
||||
@ -1,6 +1,5 @@
|
||||
use std::borrow::Cow;
|
||||
use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet};
|
||||
use std::convert::TryInto;
|
||||
use std::fs::File;
|
||||
use std::path::Path;
|
||||
|
||||
@ -23,12 +22,11 @@ use crate::heed_codec::{
|
||||
};
|
||||
use crate::order_by_map::OrderByMap;
|
||||
use crate::proximity::ProximityPrecision;
|
||||
use crate::vector::{Embedding, EmbeddingConfig};
|
||||
use crate::vector::EmbeddingConfig;
|
||||
use crate::{
|
||||
default_criteria, CboRoaringBitmapCodec, Criterion, DocumentId, ExternalDocumentsIds,
|
||||
FacetDistribution, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldIdWordCountCodec,
|
||||
FieldidsWeightsMap, GeoPoint, ObkvCodec, Result, RoaringBitmapCodec, RoaringBitmapLenCodec,
|
||||
Search, U8StrStrCodec, Weight, BEU16, BEU32, BEU64,
|
||||
FacetDistribution, FieldDistribution, FieldId, FieldIdWordCountCodec, GeoPoint, ObkvCodec,
|
||||
Result, RoaringBitmapCodec, RoaringBitmapLenCodec, Search, U8StrStrCodec, BEU16, BEU32, BEU64,
|
||||
};
|
||||
|
||||
pub const DEFAULT_MIN_WORD_LEN_ONE_TYPO: u8 = 5;
|
||||
@ -44,7 +42,6 @@ pub mod main_key {
|
||||
pub const SORTABLE_FIELDS_KEY: &str = "sortable-fields";
|
||||
pub const FIELD_DISTRIBUTION_KEY: &str = "fields-distribution";
|
||||
pub const FIELDS_IDS_MAP_KEY: &str = "fields-ids-map";
|
||||
pub const FIELDIDS_WEIGHTS_MAP_KEY: &str = "fieldids-weights-map";
|
||||
pub const GEO_FACETED_DOCUMENTS_IDS_KEY: &str = "geo-faceted-documents-ids";
|
||||
pub const GEO_RTREE_KEY: &str = "geo-rtree";
|
||||
pub const PRIMARY_KEY_KEY: &str = "primary-key";
|
||||
@ -184,7 +181,7 @@ impl Index {
|
||||
|
||||
options.max_dbs(25);
|
||||
|
||||
let env = unsafe { options.open(path) }?;
|
||||
let env = options.open(path)?;
|
||||
let mut wtxn = env.write_txn()?;
|
||||
let main = env.database_options().name(MAIN).create(&mut wtxn)?;
|
||||
let word_docids = env.create_database(&mut wtxn, Some(WORD_DOCIDS))?;
|
||||
@ -294,11 +291,6 @@ impl Index {
|
||||
self.env.read_txn()
|
||||
}
|
||||
|
||||
/// Create a static read transaction to be able to read the index without keeping a reference to it.
|
||||
pub fn static_read_txn(&self) -> heed::Result<RoTxn<'static>> {
|
||||
self.env.clone().static_read_txn()
|
||||
}
|
||||
|
||||
/// Returns the canonicalized path where the heed `Env` of this `Index` lives.
|
||||
pub fn path(&self) -> &Path {
|
||||
self.env.path()
|
||||
@ -422,65 +414,6 @@ impl Index {
|
||||
.unwrap_or_default())
|
||||
}
|
||||
|
||||
/* fieldids weights map */
|
||||
// This maps the fields ids to their weights.
|
||||
// Their weights is defined by the ordering of the searchable attributes.
|
||||
|
||||
/// Writes the fieldids weights map which associates the field ids to their weights
|
||||
pub(crate) fn put_fieldids_weights_map(
|
||||
&self,
|
||||
wtxn: &mut RwTxn,
|
||||
map: &FieldidsWeightsMap,
|
||||
) -> heed::Result<()> {
|
||||
self.main.remap_types::<Str, SerdeJson<_>>().put(
|
||||
wtxn,
|
||||
main_key::FIELDIDS_WEIGHTS_MAP_KEY,
|
||||
map,
|
||||
)
|
||||
}
|
||||
|
||||
/// Get the fieldids weights map which associates the field ids to their weights
|
||||
pub fn fieldids_weights_map(&self, rtxn: &RoTxn) -> heed::Result<FieldidsWeightsMap> {
|
||||
self.main
|
||||
.remap_types::<Str, SerdeJson<_>>()
|
||||
.get(rtxn, main_key::FIELDIDS_WEIGHTS_MAP_KEY)?
|
||||
.map(Ok)
|
||||
.unwrap_or_else(|| {
|
||||
Ok(FieldidsWeightsMap::from_field_id_map_without_searchable(
|
||||
&self.fields_ids_map(rtxn)?,
|
||||
))
|
||||
})
|
||||
}
|
||||
|
||||
/// Delete the fieldsids weights map
|
||||
pub fn delete_fieldids_weights_map(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
|
||||
self.main.remap_key_type::<Str>().delete(wtxn, main_key::FIELDIDS_WEIGHTS_MAP_KEY)
|
||||
}
|
||||
|
||||
pub fn searchable_fields_and_weights<'a>(
|
||||
&self,
|
||||
rtxn: &'a RoTxn,
|
||||
) -> Result<Vec<(Cow<'a, str>, FieldId, Weight)>> {
|
||||
let fid_map = self.fields_ids_map(rtxn)?;
|
||||
let weight_map = self.fieldids_weights_map(rtxn)?;
|
||||
let searchable = self.searchable_fields(rtxn)?;
|
||||
|
||||
searchable
|
||||
.into_iter()
|
||||
.map(|field| -> Result<_> {
|
||||
let fid = fid_map.id(&field).ok_or_else(|| FieldIdMapMissingEntry::FieldName {
|
||||
field_name: field.to_string(),
|
||||
process: "searchable_fields_and_weights",
|
||||
})?;
|
||||
let weight = weight_map
|
||||
.weight(fid)
|
||||
.ok_or(InternalError::FieldidsWeightsMapMissingEntry { key: fid })?;
|
||||
|
||||
Ok((field, fid, weight))
|
||||
})
|
||||
.collect()
|
||||
}
|
||||
|
||||
/* geo rtree */
|
||||
|
||||
/// Writes the provided `rtree` which associates coordinates to documents ids.
|
||||
@ -645,42 +578,33 @@ impl Index {
|
||||
wtxn: &mut RwTxn,
|
||||
user_fields: &[&str],
|
||||
fields_ids_map: &FieldsIdsMap,
|
||||
) -> Result<()> {
|
||||
) -> heed::Result<()> {
|
||||
// We can write the user defined searchable fields as-is.
|
||||
self.put_user_defined_searchable_fields(wtxn, user_fields)?;
|
||||
|
||||
let mut weights = FieldidsWeightsMap::default();
|
||||
|
||||
// Now we generate the real searchable fields:
|
||||
// 1. Take the user defined searchable fields as-is to keep the priority defined by the attributes criterion.
|
||||
// 2. Iterate over the user defined searchable fields.
|
||||
// 3. If a user defined field is a subset of a field defined in the fields_ids_map
|
||||
// (ie doggo.name is a subset of doggo) right after doggo and with the same weight.
|
||||
let mut real_fields = Vec::new();
|
||||
// (ie doggo.name is a subset of doggo) then we push it at the end of the fields.
|
||||
let mut real_fields = user_fields.to_vec();
|
||||
|
||||
for (id, field_from_map) in fields_ids_map.iter() {
|
||||
for (weight, user_field) in user_fields.iter().enumerate() {
|
||||
for field_from_map in fields_ids_map.names() {
|
||||
for user_field in user_fields {
|
||||
if crate::is_faceted_by(field_from_map, user_field)
|
||||
&& !real_fields.contains(&field_from_map)
|
||||
&& !user_fields.contains(&field_from_map)
|
||||
{
|
||||
real_fields.push(field_from_map);
|
||||
|
||||
let weight: u16 =
|
||||
weight.try_into().map_err(|_| UserError::AttributeLimitReached)?;
|
||||
weights.insert(id, weight);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
self.put_searchable_fields(wtxn, &real_fields)?;
|
||||
self.put_fieldids_weights_map(wtxn, &weights)?;
|
||||
Ok(())
|
||||
self.put_searchable_fields(wtxn, &real_fields)
|
||||
}
|
||||
|
||||
pub(crate) fn delete_all_searchable_fields(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
|
||||
let did_delete_searchable = self.delete_searchable_fields(wtxn)?;
|
||||
let did_delete_user_defined = self.delete_user_defined_searchable_fields(wtxn)?;
|
||||
self.delete_fieldids_weights_map(wtxn)?;
|
||||
Ok(did_delete_searchable || did_delete_user_defined)
|
||||
}
|
||||
|
||||
@ -699,31 +623,28 @@ impl Index {
|
||||
}
|
||||
|
||||
/// Returns the searchable fields, those are the fields that are indexed,
|
||||
pub fn searchable_fields<'t>(&self, rtxn: &'t RoTxn) -> heed::Result<Vec<Cow<'t, str>>> {
|
||||
/// if the searchable fields aren't there it means that **all** the fields are indexed.
|
||||
pub fn searchable_fields<'t>(&self, rtxn: &'t RoTxn) -> heed::Result<Option<Vec<&'t str>>> {
|
||||
self.main
|
||||
.remap_types::<Str, SerdeBincode<Vec<&'t str>>>()
|
||||
.get(rtxn, main_key::SEARCHABLE_FIELDS_KEY)?
|
||||
.map(|fields| Ok(fields.into_iter().map(Cow::Borrowed).collect()))
|
||||
.unwrap_or_else(|| {
|
||||
Ok(self
|
||||
.fields_ids_map(rtxn)?
|
||||
.names()
|
||||
.map(|field| Cow::Owned(field.to_string()))
|
||||
.collect())
|
||||
})
|
||||
.get(rtxn, main_key::SEARCHABLE_FIELDS_KEY)
|
||||
}
|
||||
|
||||
/// Identical to `searchable_fields`, but returns the ids instead.
|
||||
pub fn searchable_fields_ids(&self, rtxn: &RoTxn) -> Result<Vec<FieldId>> {
|
||||
let fields = self.searchable_fields(rtxn)?;
|
||||
let fields_ids_map = self.fields_ids_map(rtxn)?;
|
||||
let mut fields_ids = Vec::new();
|
||||
for name in fields {
|
||||
if let Some(field_id) = fields_ids_map.id(&name) {
|
||||
fields_ids.push(field_id);
|
||||
pub fn searchable_fields_ids(&self, rtxn: &RoTxn) -> Result<Option<Vec<FieldId>>> {
|
||||
match self.searchable_fields(rtxn)? {
|
||||
Some(fields) => {
|
||||
let fields_ids_map = self.fields_ids_map(rtxn)?;
|
||||
let mut fields_ids = Vec::new();
|
||||
for name in fields {
|
||||
if let Some(field_id) = fields_ids_map.id(name) {
|
||||
fields_ids.push(field_id);
|
||||
}
|
||||
}
|
||||
Ok(Some(fields_ids))
|
||||
}
|
||||
None => Ok(None),
|
||||
}
|
||||
Ok(fields_ids)
|
||||
}
|
||||
|
||||
/// Writes the searchable fields, when this list is specified, only these are indexed.
|
||||
@ -1595,22 +1516,6 @@ impl Index {
|
||||
.unwrap_or_default())
|
||||
}
|
||||
|
||||
pub fn arroy_readers<'a>(
|
||||
&'a self,
|
||||
rtxn: &'a RoTxn<'a>,
|
||||
embedder_id: u8,
|
||||
) -> impl Iterator<Item = Result<arroy::Reader<arroy::distances::Angular>>> + 'a {
|
||||
crate::vector::arroy_db_range_for_embedder(embedder_id).map_while(move |k| {
|
||||
arroy::Reader::open(rtxn, k, self.vector_arroy)
|
||||
.map(Some)
|
||||
.or_else(|e| match e {
|
||||
arroy::Error::MissingMetadata => Ok(None),
|
||||
e => Err(e.into()),
|
||||
})
|
||||
.transpose()
|
||||
})
|
||||
}
|
||||
|
||||
pub(crate) fn put_search_cutoff(&self, wtxn: &mut RwTxn<'_>, cutoff: u64) -> heed::Result<()> {
|
||||
self.main.remap_types::<Str, BEU64>().put(wtxn, main_key::SEARCH_CUTOFF, &cutoff)
|
||||
}
|
||||
@ -1622,44 +1527,6 @@ impl Index {
|
||||
pub(crate) fn delete_search_cutoff(&self, wtxn: &mut RwTxn<'_>) -> heed::Result<bool> {
|
||||
self.main.remap_key_type::<Str>().delete(wtxn, main_key::SEARCH_CUTOFF)
|
||||
}
|
||||
|
||||
pub fn embeddings(
|
||||
&self,
|
||||
rtxn: &RoTxn<'_>,
|
||||
docid: DocumentId,
|
||||
) -> Result<BTreeMap<String, Vec<Embedding>>> {
|
||||
let mut res = BTreeMap::new();
|
||||
for row in self.embedder_category_id.iter(rtxn)? {
|
||||
let (embedder_name, embedder_id) = row?;
|
||||
let embedder_id = (embedder_id as u16) << 8;
|
||||
let mut embeddings = Vec::new();
|
||||
'vectors: for i in 0..=u8::MAX {
|
||||
let reader = arroy::Reader::open(rtxn, embedder_id | (i as u16), self.vector_arroy)
|
||||
.map(Some)
|
||||
.or_else(|e| match e {
|
||||
arroy::Error::MissingMetadata => Ok(None),
|
||||
e => Err(e),
|
||||
})
|
||||
.transpose();
|
||||
|
||||
let Some(reader) = reader else {
|
||||
break 'vectors;
|
||||
};
|
||||
|
||||
let embedding = reader?.item_vector(rtxn, docid)?;
|
||||
if let Some(embedding) = embedding {
|
||||
embeddings.push(embedding)
|
||||
} else {
|
||||
break 'vectors;
|
||||
}
|
||||
}
|
||||
|
||||
if !embeddings.is_empty() {
|
||||
res.insert(embedder_name.to_owned(), embeddings);
|
||||
}
|
||||
}
|
||||
Ok(res)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@ -1843,14 +1710,10 @@ pub(crate) mod tests {
|
||||
]))
|
||||
.unwrap();
|
||||
|
||||
db_snap!(index, field_distribution, @r###"
|
||||
age 1 |
|
||||
id 2 |
|
||||
name 2 |
|
||||
"###);
|
||||
db_snap!(index, field_distribution, 1);
|
||||
|
||||
db_snap!(index, word_docids,
|
||||
@r###"
|
||||
@r###"
|
||||
1 [0, ]
|
||||
2 [1, ]
|
||||
20 [1, ]
|
||||
@ -1859,6 +1722,18 @@ pub(crate) mod tests {
|
||||
"###
|
||||
);
|
||||
|
||||
db_snap!(index, field_distribution);
|
||||
|
||||
db_snap!(index, field_distribution,
|
||||
@r###"
|
||||
age 1 |
|
||||
id 2 |
|
||||
name 2 |
|
||||
"###
|
||||
);
|
||||
|
||||
// snapshot_index!(&index, "1", include: "^field_distribution$");
|
||||
|
||||
// we add all the documents a second time. we are supposed to get the same
|
||||
// field_distribution in the end
|
||||
index
|
||||
@ -1945,7 +1820,7 @@ pub(crate) mod tests {
|
||||
// ensure we get the right real searchable fields + user defined searchable fields
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let real = index.searchable_fields(&rtxn).unwrap();
|
||||
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
|
||||
assert_eq!(real, &["doggo", "name", "doggo.name", "doggo.age"]);
|
||||
|
||||
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
|
||||
@ -1965,7 +1840,7 @@ pub(crate) mod tests {
|
||||
// ensure we get the right real searchable fields + user defined searchable fields
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let real = index.searchable_fields(&rtxn).unwrap();
|
||||
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
|
||||
assert_eq!(real, &["doggo", "name"]);
|
||||
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
|
||||
assert_eq!(user_defined, &["doggo", "name"]);
|
||||
@ -1981,7 +1856,7 @@ pub(crate) mod tests {
|
||||
// ensure we get the right real searchable fields + user defined searchable fields
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
|
||||
let real = index.searchable_fields(&rtxn).unwrap();
|
||||
let real = index.searchable_fields(&rtxn).unwrap().unwrap();
|
||||
assert_eq!(real, &["doggo", "name", "doggo.name", "doggo.age"]);
|
||||
|
||||
let user_defined = index.user_defined_searchable_fields(&rtxn).unwrap().unwrap();
|
||||
@ -2520,14 +2395,6 @@ pub(crate) mod tests {
|
||||
11 0
|
||||
4 1
|
||||
"###);
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 primary_key |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["primary_key"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
"###);
|
||||
|
||||
index
|
||||
.add_documents(documents!([
|
||||
@ -2543,16 +2410,6 @@ pub(crate) mod tests {
|
||||
11 0
|
||||
4 1
|
||||
"###);
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 primary_key |
|
||||
1 a |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
1 0 |
|
||||
"###);
|
||||
|
||||
index.delete_documents(Default::default());
|
||||
|
||||
@ -2563,16 +2420,6 @@ pub(crate) mod tests {
|
||||
11 0
|
||||
4 1
|
||||
"###);
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 primary_key |
|
||||
1 a |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
1 0 |
|
||||
"###);
|
||||
|
||||
index
|
||||
.add_documents(documents!([
|
||||
@ -2588,16 +2435,6 @@ pub(crate) mod tests {
|
||||
11 0
|
||||
4 1
|
||||
"###);
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 primary_key |
|
||||
1 a |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["primary_key", "a"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
1 0 |
|
||||
"###);
|
||||
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let search = Search::new(&rtxn, &index);
|
||||
@ -2683,104 +2520,4 @@ pub(crate) mod tests {
|
||||
|
||||
db_snap!(index, geo_faceted_documents_ids); // ensure that no documents were inserted
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn swapping_searchable_attributes() {
|
||||
// See https://github.com/meilisearch/meilisearch/issues/4484
|
||||
|
||||
let index = TempIndex::new();
|
||||
|
||||
index
|
||||
.update_settings(|settings| {
|
||||
settings.set_searchable_fields(vec![S("name")]);
|
||||
settings.set_filterable_fields(HashSet::from([S("age")]));
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
index
|
||||
.add_documents(documents!({ "id": 1, "name": "Many", "age": 28, "realName": "Maxime" }))
|
||||
.unwrap();
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 name |
|
||||
1 id |
|
||||
2 age |
|
||||
3 realName |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["name"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
"###);
|
||||
|
||||
index
|
||||
.update_settings(|settings| {
|
||||
settings.set_searchable_fields(vec![S("name"), S("realName")]);
|
||||
settings.set_filterable_fields(HashSet::from([S("age")]));
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
// The order of the field id map shouldn't change
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 name |
|
||||
1 id |
|
||||
2 age |
|
||||
3 realName |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["name", "realName"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
0 0 |
|
||||
3 1 |
|
||||
"###);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn attribute_weights_after_swapping_searchable_attributes() {
|
||||
// See https://github.com/meilisearch/meilisearch/issues/4484
|
||||
|
||||
let index = TempIndex::new();
|
||||
|
||||
index
|
||||
.update_settings(|settings| {
|
||||
settings.set_searchable_fields(vec![S("name"), S("beverage")]);
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
index
|
||||
.add_documents(documents!([
|
||||
{ "id": 0, "name": "kefir", "beverage": "water" },
|
||||
{ "id": 1, "name": "tamo", "beverage": "kefir" }
|
||||
]))
|
||||
.unwrap();
|
||||
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let mut search = index.search(&rtxn);
|
||||
let results = search.query("kefir").execute().unwrap();
|
||||
|
||||
// We should find kefir the dog first
|
||||
insta::assert_debug_snapshot!(results.documents_ids, @r###"
|
||||
[
|
||||
0,
|
||||
1,
|
||||
]
|
||||
"###);
|
||||
|
||||
index
|
||||
.update_settings(|settings| {
|
||||
settings.set_searchable_fields(vec![S("beverage"), S("name")]);
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let mut search = index.search(&rtxn);
|
||||
let results = search.query("kefir").execute().unwrap();
|
||||
|
||||
// We should find tamo first
|
||||
insta::assert_debug_snapshot!(results.documents_ids, @r###"
|
||||
[
|
||||
1,
|
||||
0,
|
||||
]
|
||||
"###);
|
||||
}
|
||||
}
|
||||
|
||||
@ -28,7 +28,6 @@ pub mod vector;
|
||||
#[cfg(test)]
|
||||
#[macro_use]
|
||||
pub mod snapshot_tests;
|
||||
mod fieldids_weights_map;
|
||||
|
||||
use std::collections::{BTreeMap, HashMap};
|
||||
use std::convert::{TryFrom, TryInto};
|
||||
@ -53,7 +52,6 @@ pub use self::error::{
|
||||
Error, FieldIdMapMissingEntry, InternalError, SerializationError, UserError,
|
||||
};
|
||||
pub use self::external_documents_ids::ExternalDocumentsIds;
|
||||
pub use self::fieldids_weights_map::FieldidsWeightsMap;
|
||||
pub use self::fields_ids_map::FieldsIdsMap;
|
||||
pub use self::heed_codec::{
|
||||
BEU16StrCodec, BEU32StrCodec, BoRoaringBitmapCodec, BoRoaringBitmapLenCodec,
|
||||
@ -63,7 +61,6 @@ pub use self::heed_codec::{
|
||||
};
|
||||
pub use self::index::Index;
|
||||
pub use self::search::facet::{FacetValueHit, SearchForFacetValues};
|
||||
pub use self::search::similar::Similar;
|
||||
pub use self::search::{
|
||||
FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy,
|
||||
Search, SearchResult, SemanticSearch, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET,
|
||||
@ -80,7 +77,6 @@ pub type FastMap4<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher32>>;
|
||||
pub type FastMap8<K, V> = HashMap<K, V, BuildHasherDefault<FxHasher64>>;
|
||||
pub type FieldDistribution = BTreeMap<String, u64>;
|
||||
pub type FieldId = u16;
|
||||
pub type Weight = u16;
|
||||
pub type Object = serde_json::Map<String, serde_json::Value>;
|
||||
pub type Position = u32;
|
||||
pub type RelativePosition = u16;
|
||||
@ -355,13 +351,43 @@ pub fn is_faceted(field: &str, faceted_fields: impl IntoIterator<Item = impl AsR
|
||||
/// assert!(!is_faceted_by("animaux.chien", "animaux.chie"));
|
||||
/// ```
|
||||
pub fn is_faceted_by(field: &str, facet: &str) -> bool {
|
||||
field.starts_with(facet) && field[facet.len()..].chars().next().map_or(true, |c| c == '.')
|
||||
field.starts_with(facet)
|
||||
&& field[facet.len()..].chars().next().map(|c| c == '.').unwrap_or(true)
|
||||
}
|
||||
|
||||
pub fn normalize_facet(original: &str) -> String {
|
||||
CompatibilityDecompositionNormalizer.normalize_str(original.trim()).to_lowercase()
|
||||
}
|
||||
|
||||
/// Represents either a vector or an array of multiple vectors.
|
||||
#[derive(serde::Serialize, serde::Deserialize, Debug)]
|
||||
#[serde(transparent)]
|
||||
pub struct VectorOrArrayOfVectors {
|
||||
#[serde(with = "either::serde_untagged_optional")]
|
||||
inner: Option<either::Either<Vec<f32>, Vec<Vec<f32>>>>,
|
||||
}
|
||||
|
||||
impl VectorOrArrayOfVectors {
|
||||
pub fn into_array_of_vectors(self) -> Option<Vec<Vec<f32>>> {
|
||||
match self.inner? {
|
||||
either::Either::Left(vector) => Some(vec![vector]),
|
||||
either::Either::Right(vectors) => Some(vectors),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Normalize a vector by dividing the dimensions by the length of it.
|
||||
pub fn normalize_vector(mut vector: Vec<f32>) -> Vec<f32> {
|
||||
let squared: f32 = vector.iter().map(|x| x * x).sum();
|
||||
let length = squared.sqrt();
|
||||
if length <= f32::EPSILON {
|
||||
vector
|
||||
} else {
|
||||
vector.iter_mut().for_each(|x| *x /= length);
|
||||
vector
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use serde_json::json;
|
||||
|
||||
@ -24,7 +24,6 @@ pub mod facet;
|
||||
mod fst_utils;
|
||||
pub mod hybrid;
|
||||
pub mod new;
|
||||
pub mod similar;
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct SemanticSearch {
|
||||
@ -148,21 +147,21 @@ impl<'a> Search<'a> {
|
||||
|
||||
pub fn execute_for_candidates(&self, has_vector_search: bool) -> Result<RoaringBitmap> {
|
||||
if has_vector_search {
|
||||
let ctx = SearchContext::new(self.index, self.rtxn)?;
|
||||
filtered_universe(ctx.index, ctx.txn, &self.filter)
|
||||
let ctx = SearchContext::new(self.index, self.rtxn);
|
||||
filtered_universe(&ctx, &self.filter)
|
||||
} else {
|
||||
Ok(self.execute()?.candidates)
|
||||
}
|
||||
}
|
||||
|
||||
pub fn execute(&self) -> Result<SearchResult> {
|
||||
let mut ctx = SearchContext::new(self.index, self.rtxn)?;
|
||||
let mut ctx = SearchContext::new(self.index, self.rtxn);
|
||||
|
||||
if let Some(searchable_attributes) = self.searchable_attributes {
|
||||
ctx.attributes_to_search_on(searchable_attributes)?;
|
||||
ctx.searchable_attributes(searchable_attributes)?;
|
||||
}
|
||||
|
||||
let universe = filtered_universe(ctx.index, ctx.txn, &self.filter)?;
|
||||
let universe = filtered_universe(&ctx, &self.filter)?;
|
||||
let PartialSearchResult {
|
||||
located_query_terms,
|
||||
candidates,
|
||||
|
||||
@ -101,7 +101,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
|
||||
|
||||
let mut ranking_rule_universes: Vec<RoaringBitmap> =
|
||||
vec![RoaringBitmap::default(); ranking_rules_len];
|
||||
ranking_rule_universes[0].clone_from(universe);
|
||||
ranking_rule_universes[0] = universe.clone();
|
||||
let mut cur_ranking_rule_index = 0;
|
||||
|
||||
/// Finish iterating over the current ranking rule, yielding
|
||||
@ -232,7 +232,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
|
||||
}
|
||||
|
||||
cur_ranking_rule_index += 1;
|
||||
ranking_rule_universes[cur_ranking_rule_index].clone_from(&next_bucket.candidates);
|
||||
ranking_rule_universes[cur_ranking_rule_index] = next_bucket.candidates.clone();
|
||||
logger.start_iteration_ranking_rule(
|
||||
cur_ranking_rule_index,
|
||||
ranking_rules[cur_ranking_rule_index].as_ref(),
|
||||
|
||||
@ -163,7 +163,7 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
Some(restricted_fids) => {
|
||||
let interned = self.word_interner.get(word).as_str();
|
||||
let keys: Vec<_> =
|
||||
restricted_fids.tolerant.iter().map(|(fid, _)| (interned, *fid)).collect();
|
||||
restricted_fids.tolerant.iter().map(|fid| (interned, *fid)).collect();
|
||||
|
||||
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
|
||||
self.txn,
|
||||
@ -192,7 +192,7 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
Some(restricted_fids) => {
|
||||
let interned = self.word_interner.get(word).as_str();
|
||||
let keys: Vec<_> =
|
||||
restricted_fids.exact.iter().map(|(fid, _)| (interned, *fid)).collect();
|
||||
restricted_fids.exact.iter().map(|fid| (interned, *fid)).collect();
|
||||
|
||||
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
|
||||
self.txn,
|
||||
@ -242,7 +242,7 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
Some(restricted_fids) => {
|
||||
let interned = self.word_interner.get(prefix).as_str();
|
||||
let keys: Vec<_> =
|
||||
restricted_fids.tolerant.iter().map(|(fid, _)| (interned, *fid)).collect();
|
||||
restricted_fids.tolerant.iter().map(|fid| (interned, *fid)).collect();
|
||||
|
||||
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
|
||||
self.txn,
|
||||
@ -271,7 +271,7 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
Some(restricted_fids) => {
|
||||
let interned = self.word_interner.get(prefix).as_str();
|
||||
let keys: Vec<_> =
|
||||
restricted_fids.exact.iter().map(|(fid, _)| (interned, *fid)).collect();
|
||||
restricted_fids.exact.iter().map(|fid| (interned, *fid)).collect();
|
||||
|
||||
DatabaseCache::get_value_from_keys::<_, _, CboRoaringBitmapCodec>(
|
||||
self.txn,
|
||||
@ -315,7 +315,11 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
.map_err(heed::Error::Decoding)?
|
||||
} else {
|
||||
// Compute the distance at the attribute level and store it in the cache.
|
||||
let fids = self.index.searchable_fields_ids(self.txn)?;
|
||||
let fids = if let Some(fids) = self.index.searchable_fields_ids(self.txn)? {
|
||||
fids
|
||||
} else {
|
||||
self.index.fields_ids_map(self.txn)?.ids().collect()
|
||||
};
|
||||
let mut docids = RoaringBitmap::new();
|
||||
for fid in fids {
|
||||
// for each field, intersect left word bitmap and right word bitmap,
|
||||
@ -404,7 +408,11 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
let prefix_docids = match proximity_precision {
|
||||
ProximityPrecision::ByAttribute => {
|
||||
// Compute the distance at the attribute level and store it in the cache.
|
||||
let fids = self.index.searchable_fields_ids(self.txn)?;
|
||||
let fids = if let Some(fids) = self.index.searchable_fields_ids(self.txn)? {
|
||||
fids
|
||||
} else {
|
||||
self.index.fields_ids_map(self.txn)?.ids().collect()
|
||||
};
|
||||
let mut prefix_docids = RoaringBitmap::new();
|
||||
// for each field, intersect left word bitmap and right word bitmap,
|
||||
// then merge the result in a global bitmap before storing it in the cache.
|
||||
|
||||
@ -184,7 +184,13 @@ impl State {
|
||||
return Ok(State::Empty(query_graph.clone()));
|
||||
}
|
||||
|
||||
let searchable_fields_ids = ctx.index.searchable_fields_ids(ctx.txn)?;
|
||||
let searchable_fields_ids = {
|
||||
if let Some(fids) = ctx.index.searchable_fields_ids(ctx.txn)? {
|
||||
fids
|
||||
} else {
|
||||
ctx.index.fields_ids_map(ctx.txn)?.ids().collect()
|
||||
}
|
||||
};
|
||||
|
||||
let mut candidates_per_attribute = Vec::with_capacity(searchable_fields_ids.len());
|
||||
// then check that there exists at least one attribute that has all of the terms
|
||||
|
||||
@ -42,7 +42,7 @@ fn facet_number_values<'a>(
|
||||
}
|
||||
|
||||
/// Define the strategy used by the geo sort.
|
||||
/// The parameter represents the cache size, and, in the case of the Dynamic strategy,
|
||||
/// The paramater represents the cache size, and, in the case of the Dynamic strategy,
|
||||
/// the point where we move from using the iterative strategy to the rtree.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub enum Strategy {
|
||||
|
||||
@ -258,7 +258,7 @@ pub(crate) mod tests {
|
||||
fn matching_words() {
|
||||
let temp_index = temp_index_with_documents();
|
||||
let rtxn = temp_index.read_txn().unwrap();
|
||||
let mut ctx = SearchContext::new(&temp_index, &rtxn).unwrap();
|
||||
let mut ctx = SearchContext::new(&temp_index, &rtxn);
|
||||
let mut builder = TokenizerBuilder::default();
|
||||
let tokenizer = builder.build();
|
||||
let tokens = tokenizer.tokenize("split this world");
|
||||
|
||||
@ -134,7 +134,7 @@ impl<'t> Matcher<'t, '_> {
|
||||
for (token_position, word_position, word) in words_positions {
|
||||
partial = match partial.match_token(word) {
|
||||
// token matches the partial match, but the match is not full,
|
||||
// we temporarily save the current token then we try to match the next one.
|
||||
// we temporarly save the current token then we try to match the next one.
|
||||
Some(MatchType::Partial(partial)) => {
|
||||
potential_matches.push((token_position, word_position, partial.char_len()));
|
||||
partial
|
||||
@ -506,8 +506,8 @@ mod tests {
|
||||
|
||||
impl<'a> MatcherBuilder<'a> {
|
||||
fn new_test(rtxn: &'a heed::RoTxn, index: &'a TempIndex, query: &str) -> Self {
|
||||
let mut ctx = SearchContext::new(index, rtxn).unwrap();
|
||||
let universe = filtered_universe(ctx.index, ctx.txn, &None).unwrap();
|
||||
let mut ctx = SearchContext::new(index, rtxn);
|
||||
let universe = filtered_universe(&ctx, &None).unwrap();
|
||||
let crate::search::PartialSearchResult { located_query_terms, .. } = execute_search(
|
||||
&mut ctx,
|
||||
Some(query),
|
||||
@ -722,7 +722,7 @@ mod tests {
|
||||
@"…void void void void void split the world void void"
|
||||
);
|
||||
|
||||
// Text containing matches with different density.
|
||||
// Text containing matches with diferent density.
|
||||
let text = "split void the void void world void void void void void void void void void void split the world void void";
|
||||
let mut matcher = builder.build(text);
|
||||
// crop should return 10 last words with a marker at the start.
|
||||
|
||||
@ -49,12 +49,13 @@ pub use self::geo_sort::Strategy as GeoSortStrategy;
|
||||
use self::graph_based_ranking_rule::Words;
|
||||
use self::interner::Interned;
|
||||
use self::vector_sort::VectorSort;
|
||||
use crate::error::FieldIdMapMissingEntry;
|
||||
use crate::score_details::{ScoreDetails, ScoringStrategy};
|
||||
use crate::search::new::distinct::apply_distinct_rule;
|
||||
use crate::vector::Embedder;
|
||||
use crate::{
|
||||
AscDesc, DocumentId, FieldId, Filter, Index, Member, Result, TermsMatchingStrategy, TimeBudget,
|
||||
UserError, Weight,
|
||||
UserError,
|
||||
};
|
||||
|
||||
/// A structure used throughout the execution of a search query.
|
||||
@ -70,21 +71,8 @@ pub struct SearchContext<'ctx> {
|
||||
}
|
||||
|
||||
impl<'ctx> SearchContext<'ctx> {
|
||||
pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Result<Self> {
|
||||
let searchable_fids = index.searchable_fields_and_weights(txn)?;
|
||||
let exact_attributes_ids = index.exact_attributes_ids(txn)?;
|
||||
|
||||
let mut exact = Vec::new();
|
||||
let mut tolerant = Vec::new();
|
||||
for (_name, fid, weight) in searchable_fids {
|
||||
if exact_attributes_ids.contains(&fid) {
|
||||
exact.push((fid, weight));
|
||||
} else {
|
||||
tolerant.push((fid, weight));
|
||||
}
|
||||
}
|
||||
|
||||
Ok(Self {
|
||||
pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Self {
|
||||
Self {
|
||||
index,
|
||||
txn,
|
||||
db_cache: <_>::default(),
|
||||
@ -93,39 +81,42 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
term_interner: <_>::default(),
|
||||
phrase_docids: <_>::default(),
|
||||
restricted_fids: None,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
pub fn attributes_to_search_on(
|
||||
&mut self,
|
||||
attributes_to_search_on: &'ctx [String],
|
||||
) -> Result<()> {
|
||||
let user_defined_searchable = self.index.user_defined_searchable_fields(self.txn)?;
|
||||
let searchable_fields_weights = self.index.searchable_fields_and_weights(self.txn)?;
|
||||
pub fn searchable_attributes(&mut self, searchable_attributes: &'ctx [String]) -> Result<()> {
|
||||
let fids_map = self.index.fields_ids_map(self.txn)?;
|
||||
let searchable_names = self.index.searchable_fields(self.txn)?;
|
||||
let exact_attributes_ids = self.index.exact_attributes_ids(self.txn)?;
|
||||
|
||||
let mut wildcard = false;
|
||||
|
||||
let mut restricted_fids = RestrictedFids::default();
|
||||
for field_name in attributes_to_search_on {
|
||||
let mut contains_wildcard = false;
|
||||
for field_name in searchable_attributes {
|
||||
if field_name == "*" {
|
||||
wildcard = true;
|
||||
// we cannot early exit as we want to returns error in case of unknown fields
|
||||
contains_wildcard = true;
|
||||
continue;
|
||||
}
|
||||
let searchable_weight =
|
||||
searchable_fields_weights.iter().find(|(name, _, _)| name == field_name);
|
||||
let (fid, weight) = match searchable_weight {
|
||||
let searchable_contains_name =
|
||||
searchable_names.as_ref().map(|sn| sn.iter().any(|name| name == field_name));
|
||||
let fid = match (fids_map.id(field_name), searchable_contains_name) {
|
||||
// The Field id exist and the field is searchable
|
||||
Some((_name, fid, weight)) => (*fid, *weight),
|
||||
// The field is not searchable but the user didn't define any searchable attributes
|
||||
None if user_defined_searchable.is_none() => continue,
|
||||
(Some(fid), Some(true)) | (Some(fid), None) => fid,
|
||||
// The field is searchable but the Field id doesn't exist => Internal Error
|
||||
(None, Some(true)) => {
|
||||
return Err(FieldIdMapMissingEntry::FieldName {
|
||||
field_name: field_name.to_string(),
|
||||
process: "search",
|
||||
}
|
||||
.into())
|
||||
}
|
||||
// The field is not searchable, but the searchableAttributes are set to * => ignore field
|
||||
(None, None) => continue,
|
||||
// The field is not searchable => User error
|
||||
None => {
|
||||
let (valid_fields, hidden_fields) = self.index.remove_hidden_fields(
|
||||
self.txn,
|
||||
searchable_fields_weights.iter().map(|(name, _, _)| name),
|
||||
)?;
|
||||
(_fid, Some(false)) => {
|
||||
let (valid_fields, hidden_fields) = match searchable_names {
|
||||
Some(sn) => self.index.remove_hidden_fields(self.txn, sn)?,
|
||||
None => self.index.remove_hidden_fields(self.txn, fids_map.names())?,
|
||||
};
|
||||
|
||||
let field = field_name.to_string();
|
||||
return Err(UserError::InvalidSearchableAttribute {
|
||||
@ -138,17 +129,13 @@ impl<'ctx> SearchContext<'ctx> {
|
||||
};
|
||||
|
||||
if exact_attributes_ids.contains(&fid) {
|
||||
restricted_fids.exact.push((fid, weight));
|
||||
restricted_fids.exact.push(fid);
|
||||
} else {
|
||||
restricted_fids.tolerant.push((fid, weight));
|
||||
restricted_fids.tolerant.push(fid);
|
||||
};
|
||||
}
|
||||
|
||||
if wildcard {
|
||||
self.restricted_fids = None;
|
||||
} else {
|
||||
self.restricted_fids = Some(restricted_fids);
|
||||
}
|
||||
self.restricted_fids = (!contains_wildcard).then_some(restricted_fids);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
@ -171,13 +158,13 @@ impl Word {
|
||||
|
||||
#[derive(Debug, Clone, Default)]
|
||||
pub struct RestrictedFids {
|
||||
pub tolerant: Vec<(FieldId, Weight)>,
|
||||
pub exact: Vec<(FieldId, Weight)>,
|
||||
pub tolerant: Vec<FieldId>,
|
||||
pub exact: Vec<FieldId>,
|
||||
}
|
||||
|
||||
impl RestrictedFids {
|
||||
pub fn contains(&self, fid: &FieldId) -> bool {
|
||||
self.tolerant.iter().any(|(id, _)| id == fid) || self.exact.iter().any(|(id, _)| id == fid)
|
||||
self.tolerant.contains(fid) || self.exact.contains(fid)
|
||||
}
|
||||
}
|
||||
|
||||
@ -543,15 +530,11 @@ fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn filtered_universe(
|
||||
index: &Index,
|
||||
txn: &RoTxn<'_>,
|
||||
filters: &Option<Filter>,
|
||||
) -> Result<RoaringBitmap> {
|
||||
pub fn filtered_universe(ctx: &SearchContext, filters: &Option<Filter>) -> Result<RoaringBitmap> {
|
||||
Ok(if let Some(filters) = filters {
|
||||
filters.evaluate(txn, index)?
|
||||
filters.evaluate(ctx.txn, ctx.index)?
|
||||
} else {
|
||||
index.documents_ids(txn)?
|
||||
ctx.index.documents_ids(ctx.txn)?
|
||||
})
|
||||
}
|
||||
|
||||
|
||||
@ -119,7 +119,7 @@ pub fn located_query_terms_from_tokens(
|
||||
if let Some(located_query_term) = phrase.build(ctx) {
|
||||
// as we are evaluating a negative operator we put the phrase
|
||||
// in the negative one *but* we don't reset the negative operator
|
||||
// as we are immediately starting a new negative phrase.
|
||||
// as we are immediatly starting a new negative phrase.
|
||||
if negative_phrase {
|
||||
negative_phrases.push(located_query_term);
|
||||
} else {
|
||||
@ -366,7 +366,7 @@ mod tests {
|
||||
let tokens = tokenizer.tokenize(".");
|
||||
let index = temp_index_with_documents();
|
||||
let rtxn = index.read_txn()?;
|
||||
let mut ctx = SearchContext::new(&index, &rtxn)?;
|
||||
let mut ctx = SearchContext::new(&index, &rtxn);
|
||||
// panics with `attempt to add with overflow` before <https://github.com/meilisearch/meilisearch/issues/3785>
|
||||
let ExtractedTokens { query_terms, .. } =
|
||||
located_query_terms_from_tokens(&mut ctx, tokens, None)?;
|
||||
|
||||
@ -7,12 +7,12 @@ use crate::search::new::interner::{DedupInterner, Interned};
|
||||
use crate::search::new::query_term::LocatedQueryTermSubset;
|
||||
use crate::search::new::resolve_query_graph::compute_query_term_subset_docids_within_field_id;
|
||||
use crate::search::new::SearchContext;
|
||||
use crate::{FieldId, InternalError, Result};
|
||||
use crate::Result;
|
||||
|
||||
#[derive(Clone, PartialEq, Eq, Hash)]
|
||||
pub struct FidCondition {
|
||||
term: LocatedQueryTermSubset,
|
||||
fid: Option<FieldId>,
|
||||
fid: u16,
|
||||
}
|
||||
|
||||
pub enum FidGraph {}
|
||||
@ -26,15 +26,13 @@ impl RankingRuleGraphTrait for FidGraph {
|
||||
universe: &RoaringBitmap,
|
||||
) -> Result<ComputedCondition> {
|
||||
let FidCondition { term, .. } = condition;
|
||||
|
||||
let docids = if let Some(fid) = condition.fid {
|
||||
// maybe compute_query_term_subset_docids_within_field_id should accept a universe as argument
|
||||
let docids =
|
||||
compute_query_term_subset_docids_within_field_id(ctx, &term.term_subset, fid)?;
|
||||
docids & universe
|
||||
} else {
|
||||
RoaringBitmap::new()
|
||||
};
|
||||
// maybe compute_query_term_subset_docids_within_field_id should accept a universe as argument
|
||||
let mut docids = compute_query_term_subset_docids_within_field_id(
|
||||
ctx,
|
||||
&term.term_subset,
|
||||
condition.fid,
|
||||
)?;
|
||||
docids &= universe;
|
||||
|
||||
Ok(ComputedCondition {
|
||||
docids,
|
||||
@ -70,29 +68,34 @@ impl RankingRuleGraphTrait for FidGraph {
|
||||
all_fields.extend(fields);
|
||||
}
|
||||
|
||||
let weights_map = ctx.index.fieldids_weights_map(ctx.txn)?;
|
||||
|
||||
let mut edges = vec![];
|
||||
for fid in all_fields.iter().copied() {
|
||||
let weight = weights_map
|
||||
.weight(fid)
|
||||
.ok_or(InternalError::FieldidsWeightsMapMissingEntry { key: fid })?;
|
||||
edges.push((
|
||||
weight as u32 * term.term_ids.len() as u32,
|
||||
conditions_interner.insert(FidCondition { term: term.clone(), fid: Some(fid) }),
|
||||
fid as u32 * term.term_ids.len() as u32,
|
||||
conditions_interner.insert(FidCondition { term: term.clone(), fid }),
|
||||
));
|
||||
}
|
||||
|
||||
// always lookup the max_fid if we don't already and add an artificial condition for max scoring
|
||||
let max_weight: Option<u16> = weights_map.max_weight();
|
||||
let max_fid: Option<u16> = {
|
||||
if let Some(max_fid) = ctx
|
||||
.index
|
||||
.searchable_fields_ids(ctx.txn)?
|
||||
.map(|field_ids| field_ids.into_iter().max())
|
||||
{
|
||||
max_fid
|
||||
} else {
|
||||
ctx.index.fields_ids_map(ctx.txn)?.ids().max()
|
||||
}
|
||||
};
|
||||
|
||||
if let Some(max_weight) = max_weight {
|
||||
if !all_fields.contains(&max_weight) {
|
||||
if let Some(max_fid) = max_fid {
|
||||
if !all_fields.contains(&max_fid) {
|
||||
edges.push((
|
||||
max_weight as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
|
||||
max_fid as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
|
||||
conditions_interner.insert(FidCondition {
|
||||
term: term.clone(), // TODO remove this ugly clone
|
||||
fid: None,
|
||||
fid: max_fid,
|
||||
}),
|
||||
));
|
||||
}
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
use crate::index::tests::TempIndex;
|
||||
use crate::{db_snap, Criterion, Search, SearchResult, TermsMatchingStrategy};
|
||||
use crate::{Criterion, Search, SearchResult, TermsMatchingStrategy};
|
||||
|
||||
fn create_index() -> TempIndex {
|
||||
let index = TempIndex::new();
|
||||
@ -131,19 +131,6 @@ fn test_attribute_fid_simple() {
|
||||
#[test]
|
||||
fn test_attribute_fid_ngrams() {
|
||||
let index = create_index();
|
||||
db_snap!(index, fields_ids_map, @r###"
|
||||
0 id |
|
||||
1 title |
|
||||
2 description |
|
||||
3 plot |
|
||||
"###);
|
||||
db_snap!(index, searchable_fields, @r###"["title", "description", "plot"]"###);
|
||||
db_snap!(index, fieldids_weights_map, @r###"
|
||||
fid weight
|
||||
1 0 |
|
||||
2 1 |
|
||||
3 2 |
|
||||
"###);
|
||||
|
||||
let txn = index.read_txn().unwrap();
|
||||
|
||||
|
||||
@ -1,244 +0,0 @@
|
||||
---
|
||||
source: milli/src/search/new/tests/attribute_fid.rs
|
||||
expression: "format!(\"{document_ids_scores:#?}\")"
|
||||
---
|
||||
[
|
||||
(
|
||||
2,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 19,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 91,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
6,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 15,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 81,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
5,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 14,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 79,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
4,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 13,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 77,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
3,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 12,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 83,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
9,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 11,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 75,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
8,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 10,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 79,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
7,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 10,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 73,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
11,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 7,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 77,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
10,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 6,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 81,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
13,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 6,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 81,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
12,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 6,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 78,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
14,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 5,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 75,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
(
|
||||
0,
|
||||
[
|
||||
Fid(
|
||||
Rank {
|
||||
rank: 1,
|
||||
max_rank: 19,
|
||||
},
|
||||
),
|
||||
Position(
|
||||
Rank {
|
||||
rank: 91,
|
||||
max_rank: 91,
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
]
|
||||
@ -49,8 +49,19 @@ impl<Q: RankingRuleQueryTrait> VectorSort<Q> {
|
||||
ctx: &mut SearchContext<'_>,
|
||||
vector_candidates: &RoaringBitmap,
|
||||
) -> Result<()> {
|
||||
let readers: std::result::Result<Vec<_>, _> =
|
||||
ctx.index.arroy_readers(ctx.txn, self.embedder_index).collect();
|
||||
let writer_index = (self.embedder_index as u16) << 8;
|
||||
let readers: std::result::Result<Vec<_>, _> = (0..=u8::MAX)
|
||||
.map_while(|k| {
|
||||
arroy::Reader::open(ctx.txn, writer_index | (k as u16), ctx.index.vector_arroy)
|
||||
.map(Some)
|
||||
.or_else(|e| match e {
|
||||
arroy::Error::MissingMetadata => Ok(None),
|
||||
e => Err(e),
|
||||
})
|
||||
.transpose()
|
||||
})
|
||||
.collect();
|
||||
|
||||
let readers = readers?;
|
||||
|
||||
let target = &self.target;
|
||||
|
||||
@ -1,111 +0,0 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use ordered_float::OrderedFloat;
|
||||
use roaring::RoaringBitmap;
|
||||
|
||||
use crate::score_details::{self, ScoreDetails};
|
||||
use crate::vector::Embedder;
|
||||
use crate::{filtered_universe, DocumentId, Filter, Index, Result, SearchResult};
|
||||
|
||||
pub struct Similar<'a> {
|
||||
id: DocumentId,
|
||||
// this should be linked to the String in the query
|
||||
filter: Option<Filter<'a>>,
|
||||
offset: usize,
|
||||
limit: usize,
|
||||
rtxn: &'a heed::RoTxn<'a>,
|
||||
index: &'a Index,
|
||||
embedder_name: String,
|
||||
embedder: Arc<Embedder>,
|
||||
}
|
||||
|
||||
impl<'a> Similar<'a> {
|
||||
pub fn new(
|
||||
id: DocumentId,
|
||||
offset: usize,
|
||||
limit: usize,
|
||||
index: &'a Index,
|
||||
rtxn: &'a heed::RoTxn<'a>,
|
||||
embedder_name: String,
|
||||
embedder: Arc<Embedder>,
|
||||
) -> Self {
|
||||
Self { id, filter: None, offset, limit, rtxn, index, embedder_name, embedder }
|
||||
}
|
||||
|
||||
pub fn filter(&mut self, filter: Filter<'a>) -> &mut Self {
|
||||
self.filter = Some(filter);
|
||||
self
|
||||
}
|
||||
|
||||
pub fn execute(&self) -> Result<SearchResult> {
|
||||
let universe = filtered_universe(self.index, self.rtxn, &self.filter)?;
|
||||
|
||||
let embedder_index =
|
||||
self.index
|
||||
.embedder_category_id
|
||||
.get(self.rtxn, &self.embedder_name)?
|
||||
.ok_or_else(|| crate::UserError::InvalidEmbedder(self.embedder_name.to_owned()))?;
|
||||
|
||||
let readers: std::result::Result<Vec<_>, _> =
|
||||
self.index.arroy_readers(self.rtxn, embedder_index).collect();
|
||||
|
||||
let readers = readers?;
|
||||
|
||||
let mut results = Vec::new();
|
||||
|
||||
for reader in readers.iter() {
|
||||
let nns_by_item = reader.nns_by_item(
|
||||
self.rtxn,
|
||||
self.id,
|
||||
self.limit + self.offset + 1,
|
||||
None,
|
||||
Some(&universe),
|
||||
)?;
|
||||
if let Some(mut nns_by_item) = nns_by_item {
|
||||
results.append(&mut nns_by_item);
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
results.sort_unstable_by_key(|(_, distance)| OrderedFloat(*distance));
|
||||
|
||||
let mut documents_ids = Vec::with_capacity(self.limit);
|
||||
let mut document_scores = Vec::with_capacity(self.limit);
|
||||
// list of documents we've already seen, so that we don't return the same document multiple times.
|
||||
// initialized to the target document, that we never want to return.
|
||||
let mut documents_seen = RoaringBitmap::new();
|
||||
documents_seen.insert(self.id);
|
||||
|
||||
for (docid, distance) in results
|
||||
.into_iter()
|
||||
// skip documents we've already seen & mark that we saw the current document
|
||||
.filter(|(docid, _)| documents_seen.insert(*docid))
|
||||
.skip(self.offset)
|
||||
// take **after** filter and skip so that we get exactly limit elements if available
|
||||
.take(self.limit)
|
||||
{
|
||||
documents_ids.push(docid);
|
||||
|
||||
let score = 1.0 - distance;
|
||||
let score = self
|
||||
.embedder
|
||||
.distribution()
|
||||
.map(|distribution| distribution.shift(score))
|
||||
.unwrap_or(score);
|
||||
|
||||
let score = ScoreDetails::Vector(score_details::Vector { similarity: Some(score) });
|
||||
|
||||
document_scores.push(vec![score]);
|
||||
}
|
||||
|
||||
Ok(SearchResult {
|
||||
matching_words: Default::default(),
|
||||
candidates: universe,
|
||||
documents_ids,
|
||||
document_scores,
|
||||
degraded: false,
|
||||
used_negative_operator: false,
|
||||
})
|
||||
}
|
||||
}
|
||||
@ -308,25 +308,6 @@ pub fn snap_fields_ids_map(index: &Index) -> String {
|
||||
}
|
||||
snap
|
||||
}
|
||||
pub fn snap_fieldids_weights_map(index: &Index) -> String {
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let weights_map = index.fieldids_weights_map(&rtxn).unwrap();
|
||||
|
||||
let mut snap = String::new();
|
||||
writeln!(&mut snap, "fid weight").unwrap();
|
||||
let mut field_ids: Vec<_> = weights_map.ids().collect();
|
||||
field_ids.sort();
|
||||
for field_id in field_ids {
|
||||
let weight = weights_map.weight(field_id).unwrap();
|
||||
writeln!(&mut snap, "{field_id:<3} {weight:<3} |").unwrap();
|
||||
}
|
||||
snap
|
||||
}
|
||||
pub fn snap_searchable_fields(index: &Index) -> String {
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let searchable_fields = index.searchable_fields(&rtxn).unwrap();
|
||||
format!("{searchable_fields:?}")
|
||||
}
|
||||
pub fn snap_geo_faceted_documents_ids(index: &Index) -> String {
|
||||
let rtxn = index.read_txn().unwrap();
|
||||
let geo_faceted_documents_ids = index.geo_faceted_documents_ids(&rtxn).unwrap();
|
||||
@ -488,12 +469,6 @@ macro_rules! full_snap_of_db {
|
||||
($index:ident, fields_ids_map) => {{
|
||||
$crate::snapshot_tests::snap_fields_ids_map(&$index)
|
||||
}};
|
||||
($index:ident, fieldids_weights_map) => {{
|
||||
$crate::snapshot_tests::snap_fieldids_weights_map(&$index)
|
||||
}};
|
||||
($index:ident, searchable_fields) => {{
|
||||
$crate::snapshot_tests::snap_searchable_fields(&$index)
|
||||
}};
|
||||
($index:ident, geo_faceted_documents_ids) => {{
|
||||
$crate::snapshot_tests::snap_geo_faceted_documents_ids(&$index)
|
||||
}};
|
||||
|
||||
@ -21,6 +21,8 @@ impl<'t, 'i> ClearDocuments<'t, 'i> {
|
||||
name = "clear_documents"
|
||||
)]
|
||||
pub fn execute(self) -> Result<u64> {
|
||||
puffin::profile_function!();
|
||||
|
||||
self.index.set_updated_at(self.wtxn, &OffsetDateTime::now_utc())?;
|
||||
let Index {
|
||||
env: _env,
|
||||
|
||||
@ -499,7 +499,7 @@ impl FacetsUpdateIncrementalInner {
|
||||
ModificationResult::Expand | ModificationResult::Reduce { .. }
|
||||
)
|
||||
{
|
||||
// if any modification occurred, insert it in the database.
|
||||
// if any modification occured, insert it in the database.
|
||||
self.db.put(txn, &insertion_key.as_ref(), &updated_value)?;
|
||||
Ok(insertion_key_modification)
|
||||
} else {
|
||||
|
||||
@ -379,7 +379,7 @@ pub(crate) mod test_helpers {
|
||||
let mut options = heed::EnvOpenOptions::new();
|
||||
let options = options.map_size(4096 * 4 * 1000 * 100);
|
||||
let tempdir = tempfile::TempDir::new().unwrap();
|
||||
let env = unsafe { options.open(tempdir.path()) }.unwrap();
|
||||
let env = options.open(tempdir.path()).unwrap();
|
||||
let mut wtxn = env.write_txn().unwrap();
|
||||
let content = env.create_database(&mut wtxn, None).unwrap();
|
||||
wtxn.commit().unwrap();
|
||||
|
||||
@ -29,6 +29,8 @@ pub fn enrich_documents_batch<R: Read + Seek>(
|
||||
autogenerate_docids: bool,
|
||||
reader: DocumentsBatchReader<R>,
|
||||
) -> Result<StdResult<EnrichedDocumentsBatchReader<R>, UserError>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let (mut cursor, mut documents_batch_index) = reader.into_cursor_and_fields_index();
|
||||
|
||||
let mut external_ids = tempfile::tempfile().map(BufWriter::new).map(grenad::Writer::new)?;
|
||||
|
||||
@ -29,6 +29,8 @@ pub fn extract_docid_word_positions<R: io::Read + io::Seek>(
|
||||
settings_diff: &InnerIndexSettingsDiff,
|
||||
max_positions_per_attributes: Option<u32>,
|
||||
) -> Result<(grenad::Reader<BufReader<File>>, ScriptLanguageDocidsMap)> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_positions_per_attributes = max_positions_per_attributes
|
||||
.map_or(MAX_POSITION_PER_ATTRIBUTE, |max| max.min(MAX_POSITION_PER_ATTRIBUTE));
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
@ -184,7 +186,7 @@ fn searchable_fields_changed(
|
||||
) -> bool {
|
||||
let searchable_fields = &settings_diff.new.searchable_fields_ids;
|
||||
for (field_id, field_bytes) in obkv.iter() {
|
||||
if searchable_fields.contains(&field_id) {
|
||||
if searchable_fields.as_ref().map_or(true, |sf| sf.contains(&field_id)) {
|
||||
let del_add = KvReaderDelAdd::new(field_bytes);
|
||||
match (del_add.get(DelAdd::Deletion), del_add.get(DelAdd::Addition)) {
|
||||
// if both fields are None, check the next field.
|
||||
@ -296,7 +298,7 @@ fn lang_safe_tokens_from_document<'a>(
|
||||
/// Extract words mapped with their positions of a document.
|
||||
fn tokens_from_document<'a>(
|
||||
obkv: &KvReader<FieldId>,
|
||||
searchable_fields: &[FieldId],
|
||||
searchable_fields: &Option<Vec<FieldId>>,
|
||||
tokenizer: &Tokenizer,
|
||||
max_positions_per_attributes: u32,
|
||||
del_add: DelAdd,
|
||||
@ -307,7 +309,7 @@ fn tokens_from_document<'a>(
|
||||
let mut document_writer = KvWriterU16::new(&mut buffers.obkv_buffer);
|
||||
for (field_id, field_bytes) in obkv.iter() {
|
||||
// if field is searchable.
|
||||
if searchable_fields.as_ref().contains(&field_id) {
|
||||
if searchable_fields.as_ref().map_or(true, |sf| sf.contains(&field_id)) {
|
||||
// extract deletion or addition only.
|
||||
if let Some(field_bytes) = KvReaderDelAdd::new(field_bytes).get(del_add) {
|
||||
// parse json.
|
||||
|
||||
@ -23,6 +23,8 @@ pub fn extract_facet_number_docids<R: io::Read + io::Seek>(
|
||||
indexer: GrenadParameters,
|
||||
_settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
|
||||
let mut facet_number_docids_sorter = create_sorter(
|
||||
|
||||
@ -28,6 +28,8 @@ pub fn extract_facet_string_docids<R: io::Read + io::Seek>(
|
||||
indexer: GrenadParameters,
|
||||
_settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<(grenad::Reader<BufReader<File>>, grenad::Reader<BufReader<File>>)> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
let options = NormalizerOption { lossy: true, ..Default::default() };
|
||||
|
||||
|
||||
@ -37,7 +37,7 @@ pub struct ExtractedFacetValues {
|
||||
|
||||
/// Extracts the facet values of each faceted field of each document.
|
||||
///
|
||||
/// Returns the generated grenad reader containing the docid the fid and the original value as key
|
||||
/// Returns the generated grenad reader containing the docid the fid and the orginal value as key
|
||||
/// and the normalized value as value extracted from the given chunk of documents.
|
||||
/// We need the fid of the geofields to correctly parse them as numbers if they were sent as strings initially.
|
||||
#[tracing::instrument(level = "trace", skip_all, target = "indexing::extract")]
|
||||
@ -47,6 +47,8 @@ pub fn extract_fid_docid_facet_values<R: io::Read + io::Seek>(
|
||||
settings_diff: &InnerIndexSettingsDiff,
|
||||
geo_fields_ids: Option<(FieldId, FieldId)>,
|
||||
) -> Result<ExtractedFacetValues> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
|
||||
let mut fid_docid_facet_numbers_sorter = create_sorter(
|
||||
|
||||
@ -26,6 +26,8 @@ pub fn extract_fid_word_count_docids<R: io::Read + io::Seek>(
|
||||
indexer: GrenadParameters,
|
||||
_settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
|
||||
let mut fid_word_count_docids_sorter = create_sorter(
|
||||
|
||||
@ -20,6 +20,8 @@ pub fn extract_geo_points<R: io::Read + io::Seek>(
|
||||
primary_key_id: FieldId,
|
||||
(lat_fid, lng_fid): (FieldId, FieldId),
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let mut writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
|
||||
@ -10,16 +10,16 @@ use bytemuck::cast_slice;
|
||||
use grenad::Writer;
|
||||
use itertools::EitherOrBoth;
|
||||
use ordered_float::OrderedFloat;
|
||||
use serde_json::Value;
|
||||
use serde_json::{from_slice, Value};
|
||||
|
||||
use super::helpers::{create_writer, writer_into_reader, GrenadParameters};
|
||||
use crate::error::UserError;
|
||||
use crate::prompt::Prompt;
|
||||
use crate::update::del_add::{DelAdd, KvReaderDelAdd, KvWriterDelAdd};
|
||||
use crate::update::index_documents::helpers::try_split_at;
|
||||
use crate::update::settings::InnerIndexSettingsDiff;
|
||||
use crate::vector::parsed_vectors::{ParsedVectorsDiff, RESERVED_VECTORS_FIELD_NAME};
|
||||
use crate::vector::Embedder;
|
||||
use crate::{DocumentId, Result, ThreadPoolNoAbort};
|
||||
use crate::{DocumentId, InternalError, Result, ThreadPoolNoAbort, VectorOrArrayOfVectors};
|
||||
|
||||
/// The length of the elements that are always in the buffer when inserting new values.
|
||||
const TRUNCATE_SIZE: usize = size_of::<DocumentId>();
|
||||
@ -31,10 +31,6 @@ pub struct ExtractedVectorPoints {
|
||||
pub remove_vectors: grenad::Reader<BufReader<File>>,
|
||||
// docid -> prompt
|
||||
pub prompts: grenad::Reader<BufReader<File>>,
|
||||
|
||||
// embedder
|
||||
pub embedder_name: String,
|
||||
pub embedder: Arc<Embedder>,
|
||||
}
|
||||
|
||||
enum VectorStateDelta {
|
||||
@ -69,19 +65,6 @@ impl VectorStateDelta {
|
||||
}
|
||||
}
|
||||
|
||||
struct EmbedderVectorExtractor {
|
||||
embedder_name: String,
|
||||
embedder: Arc<Embedder>,
|
||||
prompt: Arc<Prompt>,
|
||||
|
||||
// (docid, _index) -> KvWriterDelAdd -> Vector
|
||||
manual_vectors_writer: Writer<BufWriter<File>>,
|
||||
// (docid) -> (prompt)
|
||||
prompts_writer: Writer<BufWriter<File>>,
|
||||
// (docid) -> ()
|
||||
remove_vectors_writer: Writer<BufWriter<File>>,
|
||||
}
|
||||
|
||||
/// Extracts the embedding vector contained in each document under the `_vectors` field.
|
||||
///
|
||||
/// Returns the generated grenad reader containing the docid as key associated to the Vec<f32>
|
||||
@ -90,52 +73,34 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
|
||||
obkv_documents: grenad::Reader<R>,
|
||||
indexer: GrenadParameters,
|
||||
settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<Vec<ExtractedVectorPoints>> {
|
||||
let reindex_vectors = settings_diff.reindex_vectors();
|
||||
prompt: &Prompt,
|
||||
embedder_name: &str,
|
||||
) -> Result<ExtractedVectorPoints> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let old_fields_ids_map = &settings_diff.old.fields_ids_map;
|
||||
let new_fields_ids_map = &settings_diff.new.fields_ids_map;
|
||||
// the vector field id may have changed
|
||||
let old_vectors_fid = old_fields_ids_map.id(RESERVED_VECTORS_FIELD_NAME);
|
||||
// filter the old vector fid if the settings has been changed forcing reindexing.
|
||||
let old_vectors_fid = old_vectors_fid.filter(|_| !reindex_vectors);
|
||||
|
||||
let new_vectors_fid = new_fields_ids_map.id(RESERVED_VECTORS_FIELD_NAME);
|
||||
// (docid, _index) -> KvWriterDelAdd -> Vector
|
||||
let mut manual_vectors_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
|
||||
let mut extractors = Vec::new();
|
||||
for (embedder_name, (embedder, prompt)) in
|
||||
settings_diff.new.embedding_configs.clone().into_iter()
|
||||
{
|
||||
// (docid, _index) -> KvWriterDelAdd -> Vector
|
||||
let manual_vectors_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
// (docid) -> (prompt)
|
||||
let mut prompts_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
|
||||
// (docid) -> (prompt)
|
||||
let prompts_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
|
||||
// (docid) -> ()
|
||||
let remove_vectors_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
|
||||
extractors.push(EmbedderVectorExtractor {
|
||||
embedder_name,
|
||||
embedder,
|
||||
prompt,
|
||||
manual_vectors_writer,
|
||||
prompts_writer,
|
||||
remove_vectors_writer,
|
||||
});
|
||||
}
|
||||
// (docid) -> ()
|
||||
let mut remove_vectors_writer = create_writer(
|
||||
indexer.chunk_compression_type,
|
||||
indexer.chunk_compression_level,
|
||||
tempfile::tempfile()?,
|
||||
);
|
||||
|
||||
let mut key_buffer = Vec::new();
|
||||
let mut cursor = obkv_documents.into_cursor()?;
|
||||
@ -149,138 +114,152 @@ pub fn extract_vector_points<R: io::Read + io::Seek>(
|
||||
key_buffer.clear();
|
||||
key_buffer.extend_from_slice(docid_bytes);
|
||||
|
||||
// since we only need the primary key when we throw an error we create this getter to
|
||||
// since we only needs the primary key when we throw an error we create this getter to
|
||||
// lazily get it when needed
|
||||
let document_id = || -> Value { from_utf8(external_id_bytes).unwrap().into() };
|
||||
|
||||
let mut parsed_vectors = ParsedVectorsDiff::new(obkv, old_vectors_fid, new_vectors_fid)
|
||||
.map_err(|error| error.to_crate_error(document_id().to_string()))?;
|
||||
// the vector field id may have changed
|
||||
let old_vectors_fid = old_fields_ids_map.id("_vectors");
|
||||
// filter the old vector fid if the settings has been changed forcing reindexing.
|
||||
let old_vectors_fid = old_vectors_fid.filter(|_| !settings_diff.reindex_vectors());
|
||||
|
||||
for EmbedderVectorExtractor {
|
||||
embedder_name,
|
||||
embedder: _,
|
||||
prompt,
|
||||
manual_vectors_writer,
|
||||
prompts_writer,
|
||||
remove_vectors_writer,
|
||||
} in extractors.iter_mut()
|
||||
{
|
||||
let delta = match parsed_vectors.remove(embedder_name) {
|
||||
(Some(old), Some(new)) => {
|
||||
// no autogeneration
|
||||
let del_vectors = old.into_array_of_vectors();
|
||||
let add_vectors = new.into_array_of_vectors();
|
||||
let new_vectors_fid = new_fields_ids_map.id("_vectors");
|
||||
let vectors_field = {
|
||||
let del = old_vectors_fid
|
||||
.and_then(|vectors_fid| obkv.get(vectors_fid))
|
||||
.map(KvReaderDelAdd::new)
|
||||
.map(|obkv| to_vector_map(obkv, DelAdd::Deletion, &document_id))
|
||||
.transpose()?
|
||||
.flatten();
|
||||
let add = new_vectors_fid
|
||||
.and_then(|vectors_fid| obkv.get(vectors_fid))
|
||||
.map(KvReaderDelAdd::new)
|
||||
.map(|obkv| to_vector_map(obkv, DelAdd::Addition, &document_id))
|
||||
.transpose()?
|
||||
.flatten();
|
||||
(del, add)
|
||||
};
|
||||
|
||||
if add_vectors.len() > usize::from(u8::MAX) {
|
||||
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
|
||||
document_id().to_string(),
|
||||
add_vectors.len(),
|
||||
)));
|
||||
}
|
||||
let (del_map, add_map) = vectors_field;
|
||||
|
||||
VectorStateDelta::ManualDelta(del_vectors, add_vectors)
|
||||
let del_value = del_map.and_then(|mut map| map.remove(embedder_name));
|
||||
let add_value = add_map.and_then(|mut map| map.remove(embedder_name));
|
||||
|
||||
let delta = match (del_value, add_value) {
|
||||
(Some(old), Some(new)) => {
|
||||
// no autogeneration
|
||||
let del_vectors = extract_vectors(old, document_id, embedder_name)?;
|
||||
let add_vectors = extract_vectors(new, document_id, embedder_name)?;
|
||||
|
||||
if add_vectors.len() > usize::from(u8::MAX) {
|
||||
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
|
||||
document_id().to_string(),
|
||||
add_vectors.len(),
|
||||
)));
|
||||
}
|
||||
(Some(_old), None) => {
|
||||
// Do we keep this document?
|
||||
let document_is_kept = obkv
|
||||
.iter()
|
||||
.map(|(_, deladd)| KvReaderDelAdd::new(deladd))
|
||||
.any(|deladd| deladd.get(DelAdd::Addition).is_some());
|
||||
if document_is_kept {
|
||||
// becomes autogenerated
|
||||
VectorStateDelta::NowGenerated(prompt.render(
|
||||
obkv,
|
||||
DelAdd::Addition,
|
||||
new_fields_ids_map,
|
||||
)?)
|
||||
|
||||
VectorStateDelta::ManualDelta(del_vectors, add_vectors)
|
||||
}
|
||||
(Some(_old), None) => {
|
||||
// Do we keep this document?
|
||||
let document_is_kept = obkv
|
||||
.iter()
|
||||
.map(|(_, deladd)| KvReaderDelAdd::new(deladd))
|
||||
.any(|deladd| deladd.get(DelAdd::Addition).is_some());
|
||||
if document_is_kept {
|
||||
// becomes autogenerated
|
||||
VectorStateDelta::NowGenerated(prompt.render(
|
||||
obkv,
|
||||
DelAdd::Addition,
|
||||
new_fields_ids_map,
|
||||
)?)
|
||||
} else {
|
||||
VectorStateDelta::NowRemoved
|
||||
}
|
||||
}
|
||||
(None, Some(new)) => {
|
||||
// was possibly autogenerated, remove all vectors for that document
|
||||
let add_vectors = extract_vectors(new, document_id, embedder_name)?;
|
||||
if add_vectors.len() > usize::from(u8::MAX) {
|
||||
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
|
||||
document_id().to_string(),
|
||||
add_vectors.len(),
|
||||
)));
|
||||
}
|
||||
|
||||
VectorStateDelta::WasGeneratedNowManual(add_vectors)
|
||||
}
|
||||
(None, None) => {
|
||||
// Do we keep this document?
|
||||
let document_is_kept = obkv
|
||||
.iter()
|
||||
.map(|(_, deladd)| KvReaderDelAdd::new(deladd))
|
||||
.any(|deladd| deladd.get(DelAdd::Addition).is_some());
|
||||
|
||||
if document_is_kept {
|
||||
// Don't give up if the old prompt was failing
|
||||
let old_prompt = Some(prompt)
|
||||
// TODO: this filter works because we erase the vec database when a embedding setting changes.
|
||||
// When vector pipeline will be optimized, this should be removed.
|
||||
.filter(|_| !settings_diff.reindex_vectors())
|
||||
.map(|p| {
|
||||
p.render(obkv, DelAdd::Deletion, old_fields_ids_map).unwrap_or_default()
|
||||
});
|
||||
let new_prompt = prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
|
||||
if old_prompt.as_ref() != Some(&new_prompt) {
|
||||
let old_prompt = old_prompt.unwrap_or_default();
|
||||
tracing::trace!(
|
||||
"🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
|
||||
);
|
||||
VectorStateDelta::NowGenerated(new_prompt)
|
||||
} else {
|
||||
VectorStateDelta::NowRemoved
|
||||
tracing::trace!("âŹď¸Ź Prompt unmodified, skipping");
|
||||
VectorStateDelta::NoChange
|
||||
}
|
||||
} else {
|
||||
VectorStateDelta::NowRemoved
|
||||
}
|
||||
(None, Some(new)) => {
|
||||
// was possibly autogenerated, remove all vectors for that document
|
||||
let add_vectors = new.into_array_of_vectors();
|
||||
if add_vectors.len() > usize::from(u8::MAX) {
|
||||
return Err(crate::Error::UserError(crate::UserError::TooManyVectors(
|
||||
document_id().to_string(),
|
||||
add_vectors.len(),
|
||||
)));
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
VectorStateDelta::WasGeneratedNowManual(add_vectors)
|
||||
}
|
||||
(None, None) => {
|
||||
// Do we keep this document?
|
||||
let document_is_kept = obkv
|
||||
.iter()
|
||||
.map(|(_, deladd)| KvReaderDelAdd::new(deladd))
|
||||
.any(|deladd| deladd.get(DelAdd::Addition).is_some());
|
||||
|
||||
if document_is_kept {
|
||||
// Don't give up if the old prompt was failing
|
||||
let old_prompt = Some(&prompt)
|
||||
// TODO: this filter works because we erase the vec database when a embedding setting changes.
|
||||
// When vector pipeline will be optimized, this should be removed.
|
||||
.filter(|_| !settings_diff.reindex_vectors())
|
||||
.map(|p| {
|
||||
p.render(obkv, DelAdd::Deletion, old_fields_ids_map)
|
||||
.unwrap_or_default()
|
||||
});
|
||||
let new_prompt =
|
||||
prompt.render(obkv, DelAdd::Addition, new_fields_ids_map)?;
|
||||
if old_prompt.as_ref() != Some(&new_prompt) {
|
||||
let old_prompt = old_prompt.unwrap_or_default();
|
||||
tracing::trace!(
|
||||
"🚀 Changing prompt from\n{old_prompt}\n===to===\n{new_prompt}"
|
||||
);
|
||||
VectorStateDelta::NowGenerated(new_prompt)
|
||||
} else {
|
||||
tracing::trace!("âŹď¸Ź Prompt unmodified, skipping");
|
||||
VectorStateDelta::NoChange
|
||||
}
|
||||
} else {
|
||||
VectorStateDelta::NowRemoved
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// and we finally push the unique vectors into the writer
|
||||
push_vectors_diff(
|
||||
remove_vectors_writer,
|
||||
prompts_writer,
|
||||
manual_vectors_writer,
|
||||
&mut key_buffer,
|
||||
delta,
|
||||
reindex_vectors,
|
||||
)?;
|
||||
}
|
||||
// and we finally push the unique vectors into the writer
|
||||
push_vectors_diff(
|
||||
&mut remove_vectors_writer,
|
||||
&mut prompts_writer,
|
||||
&mut manual_vectors_writer,
|
||||
&mut key_buffer,
|
||||
delta,
|
||||
settings_diff,
|
||||
)?;
|
||||
}
|
||||
|
||||
let mut results = Vec::new();
|
||||
Ok(ExtractedVectorPoints {
|
||||
// docid, _index -> KvWriterDelAdd -> Vector
|
||||
manual_vectors: writer_into_reader(manual_vectors_writer)?,
|
||||
// docid -> ()
|
||||
remove_vectors: writer_into_reader(remove_vectors_writer)?,
|
||||
// docid -> prompt
|
||||
prompts: writer_into_reader(prompts_writer)?,
|
||||
})
|
||||
}
|
||||
|
||||
for EmbedderVectorExtractor {
|
||||
embedder_name,
|
||||
embedder,
|
||||
prompt: _,
|
||||
manual_vectors_writer,
|
||||
prompts_writer,
|
||||
remove_vectors_writer,
|
||||
} in extractors
|
||||
{
|
||||
results.push(ExtractedVectorPoints {
|
||||
// docid, _index -> KvWriterDelAdd -> Vector
|
||||
manual_vectors: writer_into_reader(manual_vectors_writer)?,
|
||||
// docid -> ()
|
||||
remove_vectors: writer_into_reader(remove_vectors_writer)?,
|
||||
// docid -> prompt
|
||||
prompts: writer_into_reader(prompts_writer)?,
|
||||
|
||||
embedder,
|
||||
embedder_name,
|
||||
})
|
||||
}
|
||||
|
||||
Ok(results)
|
||||
fn to_vector_map(
|
||||
obkv: KvReaderDelAdd,
|
||||
side: DelAdd,
|
||||
document_id: &impl Fn() -> Value,
|
||||
) -> Result<Option<serde_json::Map<String, Value>>> {
|
||||
Ok(if let Some(value) = obkv.get(side) {
|
||||
let Ok(value) = from_slice(value) else {
|
||||
let value = from_slice(value).map_err(InternalError::SerdeJson)?;
|
||||
return Err(crate::Error::UserError(UserError::InvalidVectorsMapType {
|
||||
document_id: document_id(),
|
||||
value,
|
||||
}));
|
||||
};
|
||||
Some(value)
|
||||
} else {
|
||||
None
|
||||
})
|
||||
}
|
||||
|
||||
/// Computes the diff between both Del and Add numbers and
|
||||
@ -291,13 +270,14 @@ fn push_vectors_diff(
|
||||
manual_vectors_writer: &mut Writer<BufWriter<File>>,
|
||||
key_buffer: &mut Vec<u8>,
|
||||
delta: VectorStateDelta,
|
||||
reindex_vectors: bool,
|
||||
settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<()> {
|
||||
puffin::profile_function!();
|
||||
let (must_remove, prompt, (mut del_vectors, mut add_vectors)) = delta.into_values();
|
||||
if must_remove
|
||||
// TODO: the below condition works because we erase the vec database when a embedding setting changes.
|
||||
// When vector pipeline will be optimized, this should be removed.
|
||||
&& !reindex_vectors
|
||||
&& !settings_diff.reindex_vectors()
|
||||
{
|
||||
key_buffer.truncate(TRUNCATE_SIZE);
|
||||
remove_vectors_writer.insert(&key_buffer, [])?;
|
||||
@ -328,7 +308,7 @@ fn push_vectors_diff(
|
||||
EitherOrBoth::Left(vector) => {
|
||||
// TODO: the below condition works because we erase the vec database when a embedding setting changes.
|
||||
// When vector pipeline will be optimized, this should be removed.
|
||||
if !reindex_vectors {
|
||||
if !settings_diff.reindex_vectors() {
|
||||
// We insert only the Del part of the Obkv to inform
|
||||
// that we only want to remove all those vectors.
|
||||
let mut obkv = KvWriterDelAdd::memory();
|
||||
@ -356,6 +336,26 @@ fn compare_vectors(a: &[f32], b: &[f32]) -> Ordering {
|
||||
a.iter().copied().map(OrderedFloat).cmp(b.iter().copied().map(OrderedFloat))
|
||||
}
|
||||
|
||||
/// Extracts the vectors from a JSON value.
|
||||
fn extract_vectors(
|
||||
value: Value,
|
||||
document_id: impl Fn() -> Value,
|
||||
name: &str,
|
||||
) -> Result<Vec<Vec<f32>>> {
|
||||
// FIXME: ugly clone of the vectors here
|
||||
match serde_json::from_value(value.clone()) {
|
||||
Ok(vectors) => {
|
||||
Ok(VectorOrArrayOfVectors::into_array_of_vectors(vectors).unwrap_or_default())
|
||||
}
|
||||
Err(_) => Err(UserError::InvalidVectorsType {
|
||||
document_id: document_id(),
|
||||
value,
|
||||
subfield: name.to_owned(),
|
||||
}
|
||||
.into()),
|
||||
}
|
||||
}
|
||||
|
||||
#[tracing::instrument(level = "trace", skip_all, target = "indexing::extract")]
|
||||
pub fn extract_embeddings<R: io::Read + io::Seek>(
|
||||
// docid, prompt
|
||||
@ -364,6 +364,7 @@ pub fn extract_embeddings<R: io::Read + io::Seek>(
|
||||
embedder: Arc<Embedder>,
|
||||
request_threads: &ThreadPoolNoAbort,
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
let n_chunks = embedder.chunk_count_hint(); // chunk level parallelism
|
||||
let n_vectors_per_chunk = embedder.prompt_count_in_chunk_hint(); // number of vectors in a single chunk
|
||||
|
||||
|
||||
@ -36,6 +36,8 @@ pub fn extract_word_docids<R: io::Read + io::Seek>(
|
||||
grenad::Reader<BufReader<File>>,
|
||||
grenad::Reader<BufReader<File>>,
|
||||
)> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
|
||||
let mut word_fid_docids_sorter = create_sorter(
|
||||
@ -165,6 +167,8 @@ fn words_into_sorter(
|
||||
add_words: &BTreeSet<Vec<u8>>,
|
||||
word_fid_docids_sorter: &mut grenad::Sorter<MergeFn>,
|
||||
) -> Result<()> {
|
||||
puffin::profile_function!();
|
||||
|
||||
use itertools::merge_join_by;
|
||||
use itertools::EitherOrBoth::{Both, Left, Right};
|
||||
|
||||
|
||||
@ -26,6 +26,7 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
|
||||
indexer: GrenadParameters,
|
||||
settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
let any_deletion = settings_diff.old.proximity_precision == ProximityPrecision::ByWord;
|
||||
let any_addition = settings_diff.new.proximity_precision == ProximityPrecision::ByWord;
|
||||
|
||||
@ -70,6 +71,8 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
|
||||
|
||||
// if we change document, we fill the sorter
|
||||
if current_document_id.map_or(false, |id| id != document_id) {
|
||||
puffin::profile_scope!("Document into sorter");
|
||||
|
||||
// FIXME: span inside of a hot loop might degrade performance and create big reports
|
||||
let span = tracing::trace_span!(target: "indexing::details", "document_into_sorter");
|
||||
let _entered = span.enter();
|
||||
@ -160,6 +163,7 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
|
||||
}
|
||||
|
||||
if let Some(document_id) = current_document_id {
|
||||
puffin::profile_scope!("Final document into sorter");
|
||||
// FIXME: span inside of a hot loop might degrade performance and create big reports
|
||||
let span = tracing::trace_span!(target: "indexing::details", "final_document_into_sorter");
|
||||
let _entered = span.enter();
|
||||
@ -172,6 +176,7 @@ pub fn extract_word_pair_proximity_docids<R: io::Read + io::Seek>(
|
||||
)?;
|
||||
}
|
||||
{
|
||||
puffin::profile_scope!("sorter_into_reader");
|
||||
// FIXME: span inside of a hot loop might degrade performance and create big reports
|
||||
let span = tracing::trace_span!(target: "indexing::details", "sorter_into_reader");
|
||||
let _entered = span.enter();
|
||||
|
||||
@ -25,6 +25,8 @@ pub fn extract_word_position_docids<R: io::Read + io::Seek>(
|
||||
indexer: GrenadParameters,
|
||||
_settings_diff: &InnerIndexSettingsDiff,
|
||||
) -> Result<grenad::Reader<BufReader<File>>> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let max_memory = indexer.max_memory_by_thread();
|
||||
|
||||
let mut word_position_docids_sorter = create_sorter(
|
||||
@ -102,6 +104,8 @@ fn words_position_into_sorter(
|
||||
add_word_positions: &BTreeSet<(u16, Vec<u8>)>,
|
||||
word_position_docids_sorter: &mut grenad::Sorter<MergeFn>,
|
||||
) -> Result<()> {
|
||||
puffin::profile_function!();
|
||||
|
||||
use itertools::merge_join_by;
|
||||
use itertools::EitherOrBoth::{Both, Left, Right};
|
||||
|
||||
|
||||
@ -47,6 +47,8 @@ pub(crate) fn data_from_obkv_documents(
|
||||
settings_diff: Arc<InnerIndexSettingsDiff>,
|
||||
max_positions_per_attributes: Option<u32>,
|
||||
) -> Result<()> {
|
||||
puffin::profile_function!();
|
||||
|
||||
let (original_pipeline_result, flattened_pipeline_result): (Result<_>, Result<_>) = rayon::join(
|
||||
|| {
|
||||
original_obkv_chunks
|
||||
@ -88,6 +90,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
lmdb_writer_sx.clone(),
|
||||
extract_fid_word_count_docids,
|
||||
TypedChunk::FieldIdWordCountDocids,
|
||||
"field-id-wordcount-docids",
|
||||
);
|
||||
run_extraction_task::<
|
||||
_,
|
||||
@ -114,6 +117,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
word_fid_docids_reader,
|
||||
}
|
||||
},
|
||||
"word-docids",
|
||||
);
|
||||
|
||||
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
|
||||
@ -123,6 +127,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
lmdb_writer_sx.clone(),
|
||||
extract_word_position_docids,
|
||||
TypedChunk::WordPositionDocids,
|
||||
"word-position-docids",
|
||||
);
|
||||
|
||||
run_extraction_task::<
|
||||
@ -136,6 +141,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
lmdb_writer_sx.clone(),
|
||||
extract_facet_string_docids,
|
||||
TypedChunk::FieldIdFacetStringDocids,
|
||||
"field-id-facet-string-docids",
|
||||
);
|
||||
|
||||
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
|
||||
@ -145,6 +151,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
lmdb_writer_sx.clone(),
|
||||
extract_facet_number_docids,
|
||||
TypedChunk::FieldIdFacetNumberDocids,
|
||||
"field-id-facet-number-docids",
|
||||
);
|
||||
|
||||
run_extraction_task::<_, _, grenad::Reader<BufReader<File>>>(
|
||||
@ -154,6 +161,7 @@ pub(crate) fn data_from_obkv_documents(
|
||||
lmdb_writer_sx.clone(),
|
||||
extract_word_pair_proximity_docids,
|
||||
TypedChunk::WordPairProximityDocids,
|
||||
"word-pair-proximity-docids",
|
||||
);
|
||||
}
|
||||
|
||||
@ -177,6 +185,7 @@ fn run_extraction_task<FE, FS, M>(
|
||||
lmdb_writer_sx: Sender<Result<TypedChunk>>,
|
||||
extract_fn: FE,
|
||||
serialize_fn: FS,
|
||||
name: &'static str,
|
||||
) where
|
||||
FE: Fn(
|
||||
grenad::Reader<CursorClonableMmap>,
|
||||
@ -194,7 +203,7 @@ fn run_extraction_task<FE, FS, M>(
|
||||
rayon::spawn(move || {
|
||||
let child_span = tracing::trace_span!(target: "indexing::extract::details", parent: ¤t_span, "extract_multiple_chunks");
|
||||
let _entered = child_span.enter();
|
||||
|
||||
puffin::profile_scope!("extract_multiple_chunks", name);
|
||||
match extract_fn(chunk, indexer, &settings_diff) {
|
||||
Ok(chunk) => {
|
||||
let _ = lmdb_writer_sx.send(Ok(serialize_fn(chunk)));
|
||||
@ -217,31 +226,30 @@ fn send_original_documents_data(
|
||||
let original_documents_chunk =
|
||||
original_documents_chunk.and_then(|c| unsafe { as_cloneable_grenad(&c) })?;
|
||||
|
||||
let request_threads = ThreadPoolNoAbortBuilder::new()
|
||||
.num_threads(crate::vector::REQUEST_PARALLELISM)
|
||||
.thread_name(|index| format!("embedding-request-{index}"))
|
||||
.build()?;
|
||||
let documents_chunk_cloned = original_documents_chunk.clone();
|
||||
let lmdb_writer_sx_cloned = lmdb_writer_sx.clone();
|
||||
|
||||
let index_vectors = (settings_diff.reindex_vectors() || !settings_diff.settings_update_only())
|
||||
// no point in indexing vectors without embedders
|
||||
&& (!settings_diff.new.embedding_configs.inner_as_ref().is_empty());
|
||||
let new_embedding_configs = settings_diff.new.embedding_configs.clone();
|
||||
|
||||
if index_vectors {
|
||||
if (settings_diff.reindex_vectors() || !settings_diff.settings_update_only())
|
||||
&& new_embedding_configs.get_default().is_some()
|
||||
{
|
||||
let request_threads = ThreadPoolNoAbortBuilder::new()
|
||||
.num_threads(crate::vector::REQUEST_PARALLELISM)
|
||||
.thread_name(|index| format!("embedding-request-{index}"))
|
||||
.build()?;
|
||||
let settings_diff = settings_diff.clone();
|
||||
|
||||
let original_documents_chunk = original_documents_chunk.clone();
|
||||
let lmdb_writer_sx = lmdb_writer_sx.clone();
|
||||
rayon::spawn(move || {
|
||||
match extract_vector_points(original_documents_chunk.clone(), indexer, &settings_diff) {
|
||||
Ok(extracted_vectors) => {
|
||||
for ExtractedVectorPoints {
|
||||
manual_vectors,
|
||||
remove_vectors,
|
||||
prompts,
|
||||
embedder_name,
|
||||
embedder,
|
||||
} in extracted_vectors
|
||||
{
|
||||
for (name, (embedder, prompt)) in settings_diff.new.embedding_configs.clone() {
|
||||
let result = extract_vector_points(
|
||||
documents_chunk_cloned.clone(),
|
||||
indexer,
|
||||
&settings_diff,
|
||||
&prompt,
|
||||
&name,
|
||||
);
|
||||
match result {
|
||||
Ok(ExtractedVectorPoints { manual_vectors, remove_vectors, prompts }) => {
|
||||
let embeddings = match extract_embeddings(
|
||||
prompts,
|
||||
indexer,
|
||||
@ -250,26 +258,28 @@ fn send_original_documents_data(
|
||||
) {
|
||||
Ok(results) => Some(results),
|
||||
Err(error) => {
|
||||
let _ = lmdb_writer_sx.send(Err(error));
|
||||
let _ = lmdb_writer_sx_cloned.send(Err(error));
|
||||
None
|
||||
}
|
||||
};
|
||||
|
||||
if !(remove_vectors.is_empty()
|
||||
&& manual_vectors.is_empty()
|
||||
&& embeddings.as_ref().map_or(true, |e| e.is_empty()))
|
||||
{
|
||||
let _ = lmdb_writer_sx.send(Ok(TypedChunk::VectorPoints {
|
||||
let _ = lmdb_writer_sx_cloned.send(Ok(TypedChunk::VectorPoints {
|
||||
remove_vectors,
|
||||
embeddings,
|
||||
expected_dimension: embedder.dimensions(),
|
||||
manual_vectors,
|
||||
embedder_name,
|
||||
embedder_name: name,
|
||||
}));
|
||||
}
|
||||
}
|
||||
}
|
||||
Err(error) => {
|
||||
let _ = lmdb_writer_sx.send(Err(error));
|
||||
|
||||
Err(error) => {
|
||||
let _ = lmdb_writer_sx_cloned.send(Err(error));
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user