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13 Commits

Author SHA1 Message Date
50c6854964 Merge #4798
4798: Update version for the next release (v1.8.4) in Cargo.toml r=dureuill a=meili-bot

⚠️ This PR is automatically generated. Check the new version is the expected one and Cargo.lock has been updated before merging.

Co-authored-by: dureuill <dureuill@users.noreply.github.com>
2024-07-15 14:09:11 +00:00
f0f02e6412 Merge #4796
4796: Generate vectors in dumps r=dureuill a=dureuill

# Pull Request

## What does this PR do?
1. Add an Index::embeddings method to compute the embeddings of a document
2. Write generated vectors in dumps
3. Remove generated vectors when importing dumps
4. Cherry pick the `ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION` workaround so that the older CI can still build

## Manual Tests (TODO)

- [ ] Import a dump from a v1.8.3 into a v1.8.4 successfully
- [x] Import a dump from a v1.8.4 into a v1.8.4 successfully
- [x] Import a dump from a v1.8.4 into a v1.9.0 successfully
  - [x] generated vectors are not regenerated
  - [x] user provided vectors are still available
  - [x] generated vectors still have the correct value
  - [x] updating a document with generated vectors attempts to regenerate

Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2024-07-15 13:26:30 +00:00
43bf3ff4e0 Update version for the next release (v1.8.4) in Cargo.toml 2024-07-15 10:24:00 +00:00
8fe6d31e01 CI: Add ACTIONS_ALLOW_USE_UNSECURE_NODE_VERSION workaround to keep using Ubuntu 18.04 2024-07-15 12:04:14 +02:00
9ec209bbf4 When importing dumps, remove regenerate: true vectors items 2024-07-15 11:57:11 +02:00
9375b7bba5 Inject generated vectors in dumps 2024-07-15 11:56:39 +02:00
363a5cc590 Retrieve function from v1.9 to get embeddings in documents 2024-07-15 11:56:18 +02:00
7d69953267 Merge #4709
4709: Update version for the next release (v1.8.3) in Cargo.toml r=dureuill a=meili-bot

⚠️ This PR is automatically generated. Check the new version is the expected one and Cargo.lock has been updated before merging.

Co-authored-by: dureuill <dureuill@users.noreply.github.com>
2024-06-19 15:25:38 +00:00
7bd1b7ac43 Merge #4707
4707: Only spawn thread pool once r=irevoire a=dureuill

# Pull Request

## Related issue
Fixes #4692 

## What does this PR do?
- There was a rayon thread pool of 40 threads that would be spawned multiple times per indexing operation.
- Perhaps due to the sheer number of spawned threads, or to a leak in rayon thread pools, the system was unable to reclaim all the spawned threads at a sufficient rate.
- As a result, the stack for the threads would accumulate and consume virtual memory, and eventually physical memory too.
- Fortunately, the pool can actually be created once and then always reused. This PR performs this change.


Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2024-06-19 14:51:06 +00:00
1ff860e0a8 Fixes for Rust v1.79 2024-06-19 15:52:00 +02:00
5d2b172e79 Update version for the next release (v1.8.3) in Cargo.toml 2024-06-19 13:32:04 +00:00
e64d0a206e Don't bind request_threads() to a local variable 2024-06-19 15:23:11 +02:00
6254c7cee1 Only spawn the pool once 2024-06-19 15:17:46 +02:00
202 changed files with 2370 additions and 15902 deletions

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@ -18,9 +18,11 @@ jobs:
timeout-minutes: 180 # 3h
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- name: Run benchmarks - workload ${WORKLOAD_NAME} - branch ${{ github.ref }} - commit ${{ github.sha }}
run: |

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@ -35,17 +35,12 @@ jobs:
fetch-depth: 0 # fetch full history to be able to get main commit sha
ref: ${{ steps.comment-branch.outputs.head_ref }}
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- 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 }}

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@ -12,9 +12,11 @@ jobs:
timeout-minutes: 180 # 3h
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Run benchmarks
- name: Run benchmarks - Dataset ${BENCH_NAME} - Branch main - Commit ${{ github.sha }}

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@ -18,9 +18,11 @@ jobs:
timeout-minutes: 4320 # 72h
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Set variables
- name: Set current branch name

View File

@ -13,9 +13,11 @@ jobs:
runs-on: benchmarks
timeout-minutes: 4320 # 72h
steps:
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- name: Check for Command
id: command

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@ -16,9 +16,11 @@ jobs:
timeout-minutes: 4320 # 72h
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Set variables
- name: Set current branch name

View File

@ -15,9 +15,11 @@ jobs:
runs-on: benchmarks
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Set variables
- name: Set current branch name

View File

@ -15,9 +15,11 @@ jobs:
runs-on: benchmarks
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Set variables
- name: Set current branch name

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@ -15,9 +15,11 @@ jobs:
runs-on: benchmarks
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Set variables
- name: Set current branch name

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@ -18,7 +18,10 @@ jobs:
run: |
apt-get update && apt-get install -y curl
apt-get install build-essential -y
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Install cargo-flaky
run: cargo install cargo-flaky
- name: Run cargo flaky in the dumps

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@ -13,9 +13,11 @@ jobs:
timeout-minutes: 4320 # 72h
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
# Run benchmarks
- name: Run the fuzzer

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@ -27,7 +27,10 @@ jobs:
run: |
apt-get update && apt-get install -y curl
apt-get install build-essential -y
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Install cargo-deb
run: cargo install cargo-deb
- uses: actions/checkout@v3

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@ -47,7 +47,10 @@ jobs:
run: |
apt-get update && apt-get install -y curl
apt-get install build-essential -y
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Build
run: cargo build --release --locked
# No need to upload binaries for dry run (cron)
@ -77,7 +80,10 @@ jobs:
asset_name: meilisearch-windows-amd64.exe
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Build
run: cargo build --release --locked
# No need to upload binaries for dry run (cron)
@ -103,10 +109,12 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v3
- name: Installing Rust toolchain
uses: helix-editor/rust-toolchain@v1
uses: actions-rs/toolchain@v1
with:
toolchain: stable
profile: minimal
target: ${{ matrix.target }}
override: true
- name: Cargo build
uses: actions-rs/cargo@v1
with:
@ -150,10 +158,12 @@ jobs:
add-apt-repository "deb [arch=$(dpkg --print-architecture)] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
apt-get update -y && apt-get install -y docker-ce
- name: Installing Rust toolchain
uses: helix-editor/rust-toolchain@v1
uses: actions-rs/toolchain@v1
with:
toolchain: stable
profile: minimal
target: ${{ matrix.target }}
override: true
- name: Configure target aarch64 GNU
## Environment variable is not passed using env:
## LD gold won't work with MUSL

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@ -80,11 +80,10 @@ jobs:
type=ref,event=tag
type=raw,value=nightly,enable=${{ github.event_name != 'push' }}
type=semver,pattern=v{{major}}.{{minor}},enable=${{ steps.check-tag-format.outputs.stable == 'true' }}
type=semver,pattern=v{{major}},enable=${{ steps.check-tag-format.outputs.stable == 'true' }}
type=raw,value=latest,enable=${{ steps.check-tag-format.outputs.stable == 'true' && steps.check-tag-format.outputs.latest == 'true' }}
- name: Build and push
uses: docker/build-push-action@v6
uses: docker/build-push-action@v5
with:
push: true
platforms: linux/amd64,linux/arm64

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@ -33,7 +33,10 @@ jobs:
apt-get update && apt-get install -y curl
apt-get install build-essential -y
- name: Setup test with Rust stable
uses: helix-editor/rust-toolchain@v1
uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Cache dependencies
uses: Swatinem/rust-cache@v2.7.1
- name: Run cargo check without any default features
@ -58,7 +61,10 @@ jobs:
- uses: actions/checkout@v3
- name: Cache dependencies
uses: Swatinem/rust-cache@v2.7.1
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Run cargo check without any default features
uses: actions-rs/cargo@v1
with:
@ -85,7 +91,10 @@ jobs:
run: |
apt-get update
apt-get install --assume-yes build-essential curl
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Run cargo build with almost all features
run: |
cargo build --workspace --locked --release --features "$(cargo xtask list-features --exclude-feature cuda)"
@ -107,10 +116,13 @@ jobs:
run: |
apt-get update
apt-get install --assume-yes build-essential curl
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Run cargo tree without default features and check lindera is not present
run: |
if cargo tree -f '{p} {f}' -e normal --no-default-features | grep -qz lindera; then
if cargo tree -f '{p} {f}' -e normal --no-default-features | grep -vqz lindera; then
echo "lindera has been found in the sources and it shouldn't"
exit 1
fi
@ -133,7 +145,10 @@ jobs:
run: |
apt-get update && apt-get install -y curl
apt-get install build-essential -y
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
toolchain: stable
override: true
- name: Cache dependencies
uses: Swatinem/rust-cache@v2.7.1
- name: Run tests in debug
@ -147,9 +162,11 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: 1.75.0
override: true
components: clippy
- name: Cache dependencies
uses: Swatinem/rust-cache@v2.7.1
@ -164,10 +181,10 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: nightly-2024-06-25
toolchain: nightly
override: true
components: rustfmt
- name: Cache dependencies

View File

@ -18,9 +18,11 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: helix-editor/rust-toolchain@v1
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- name: Install sd
run: cargo install sd
- name: Update Cargo.toml file

View File

@ -109,12 +109,6 @@ They are JSON files with the following structure (comments are not actually supp
"run_count": 3,
// List of arguments to add to the Meilisearch command line.
"extra_cli_args": ["--max-indexing-threads=1"],
// An expression that can be parsed as a comma-separated list of targets and levels
// as described in [tracing_subscriber's documentation](https://docs.rs/tracing-subscriber/latest/tracing_subscriber/filter/targets/struct.Targets.html#examples).
// The expression is used to filter the spans that are measured for profiling purposes.
// Optional, defaults to "indexing::=trace" (for indexing workloads), common other values is
// "search::=trace"
"target": "indexing::=trace",
// List of named assets that can be used in the commands.
"assets": {
// name of the asset.
@ -193,8 +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",
@ -230,11 +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",

617
Cargo.lock generated

File diff suppressed because it is too large Load Diff

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@ -22,7 +22,7 @@ members = [
]
[workspace.package]
version = "1.9.0"
version = "1.8.4"
authors = [
"Quentin de Quelen <quentin@dequelen.me>",
"Clément Renault <clement@meilisearch.com>",

View File

@ -1,6 +1,9 @@
<p align="center">
<a href="https://www.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=logo" target="_blank">
<img src="assets/meilisearch-logo-kawaii.png">
<a href="https://www.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=logo#gh-light-mode-only" target="_blank">
<img src="assets/meilisearch-logo-light.svg?sanitize=true#gh-light-mode-only">
</a>
<a href="https://www.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=logo#gh-dark-mode-only" target="_blank">
<img src="assets/meilisearch-logo-dark.svg?sanitize=true#gh-dark-mode-only">
</a>
</p>
@ -22,7 +25,7 @@
<p align="center">⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍</p>
[Meilisearch](https://www.meilisearch.com?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=intro) helps you shape a delightful search experience in a snap, offering features that work out of the box to speed up your workflow.
Meilisearch helps you shape a delightful search experience in a snap, offering features that work out-of-the-box to speed up your workflow.
<p align="center" name="demo">
<a href="https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-gif#gh-light-mode-only" target="_blank">
@ -33,18 +36,11 @@
</a>
</p>
## đź–Ą Examples
- [**Movies**](https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=organization) — An application to help you find streaming platforms to watch movies using [hybrid search](https://www.meilisearch.com/solutions/hybrid-search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos).
- [**Ecommerce**](https://ecommerce.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos) — Ecommerce website using disjunctive [facets](https://www.meilisearch.com/docs/learn/fine_tuning_results/faceted_search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos), range and rating filtering, and pagination.
- [**Songs**](https://music.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos) — Search through 47 million of songs.
- [**SaaS**](https://saas.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos) — Search for contacts, deals, and companies in this [multi-tenant](https://www.meilisearch.com/docs/learn/security/multitenancy_tenant_tokens?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demos) CRM application.
See the list of all our example apps in our [demos repository](https://github.com/meilisearch/demos).
🔥 [**Try it!**](https://where2watch.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=demo-link) 🔥
## ✨ Features
- **Hybrid search:** Combine the best of both [semantic](https://www.meilisearch.com/docs/learn/experimental/vector_search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features) & full-text search to get the most relevant results
- **Search-as-you-type:** Find & display results in less than 50 milliseconds to provide an intuitive experience
- **Search-as-you-type:** find search results in less than 50 milliseconds
- **[Typo tolerance](https://www.meilisearch.com/docs/learn/configuration/typo_tolerance?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** get relevant matches even when queries contain typos and misspellings
- **[Filtering](https://www.meilisearch.com/docs/learn/fine_tuning_results/filtering?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features) and [faceted search](https://www.meilisearch.com/docs/learn/fine_tuning_results/faceted_search?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** enhance your users' search experience with custom filters and build a faceted search interface in a few lines of code
- **[Sorting](https://www.meilisearch.com/docs/learn/fine_tuning_results/sorting?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=features):** sort results based on price, date, or pretty much anything else your users need
@ -59,15 +55,15 @@ See the list of all our example apps in our [demos repository](https://github.co
## đź“– Documentation
You can consult Meilisearch's documentation at [meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
You can consult Meilisearch's documentation at [https://www.meilisearch.com/docs](https://www.meilisearch.com/docs/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=docs).
## 🚀 Getting started
For basic instructions on how to set up Meilisearch, add documents to an index, and search for documents, take a look at our [documentation](https://www.meilisearch.com/docs?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=get-started) guide.
For basic instructions on how to set up Meilisearch, add documents to an index, and search for documents, take a look at our [Quick Start](https://www.meilisearch.com/docs/learn/getting_started/quick_start?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=get-started) guide.
## 🌍 Supercharge your Meilisearch experience
## ⚡ Supercharge your Meilisearch experience
Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). Additional features include analytics & monitoring in many regions around the world. No credit card is required.
Say goodbye to server deployment and manual updates with [Meilisearch Cloud](https://www.meilisearch.com/cloud?utm_campaign=oss&utm_source=github&utm_medium=meilisearch). No credit card required.
## đź§° SDKs & integration tools
@ -87,15 +83,15 @@ Finally, for more in-depth information, refer to our articles explaining fundame
## 📊 Telemetry
Meilisearch collects **anonymized** user data to help us improve our product. You can [deactivate this](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) whenever you want.
Meilisearch collects **anonymized** data from users to help us improve our product. You can [deactivate this](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) whenever you want.
To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Remember to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
To request deletion of collected data, please write to us at [privacy@meilisearch.com](mailto:privacy@meilisearch.com). Don't forget to include your `Instance UID` in the message, as this helps us quickly find and delete your data.
If you want to know more about the kind of data we collect and what we use it for, check the [telemetry section](https://www.meilisearch.com/docs/learn/what_is_meilisearch/telemetry?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=telemetry#how-to-disable-data-collection) of our documentation.
## đź“« Get in touch!
Meilisearch is a search engine created by [Meili]([https://www.welcometothejungle.com/en/companies/meilisearch](https://www.meilisearch.com/careers)), a software development company headquartered in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
Meilisearch is a search engine created by [Meili](https://www.welcometothejungle.com/en/companies/meilisearch), a software development company based in France and with team members all over the world. Want to know more about us? [Check out our blog!](https://blog.meilisearch.com/?utm_campaign=oss&utm_source=github&utm_medium=meilisearch&utm_content=contact)
đź—ž [Subscribe to our newsletter](https://meilisearch.us2.list-manage.com/subscribe?u=27870f7b71c908a8b359599fb&id=79582d828e) if you don't want to miss any updates! We promise we won't clutter your mailbox: we only send one edition every two months.
@ -109,11 +105,11 @@ Thank you for your support!
## 👩‍💻 Contributing
Meilisearch is, and will always be, open-source! If you want to contribute to the project, please look at [our contribution guidelines](CONTRIBUTING.md).
Meilisearch is, and will always be, open-source! If you want to contribute to the project, please take a look at [our contribution guidelines](CONTRIBUTING.md).
## 📦 Versioning
Meilisearch releases and their associated binaries are available on the project's [releases page](https://github.com/meilisearch/meilisearch/releases).
Meilisearch releases and their associated binaries are available [in this GitHub page](https://github.com/meilisearch/meilisearch/releases).
The binaries are versioned following [SemVer conventions](https://semver.org/). To know more, read our [versioning policy](https://github.com/meilisearch/engine-team/blob/main/resources/versioning-policy.md).

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@ -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();

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@ -1,783 +0,0 @@
---
source: dump/src/reader/mod.rs
expression: document
---
{
"id": "e3",
"desc": "overriden vector + map",
"_vectors": {
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"toto": [
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]
}
}

View File

@ -1,786 +0,0 @@
---
source: dump/src/reader/mod.rs
expression: document
---
{
"id": "e2",
"desc": "natural vector + map",
"_vectors": {
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"default": {
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View File

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]
],
"regenerate": true
}
}
}

View File

@ -1,780 +0,0 @@
---
source: dump/src/reader/mod.rs
expression: document
---
{
"id": "e0",
"desc": "overriden vector",
"_vectors": {
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]
}
}

View File

@ -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\"\'\"}");
}

View File

@ -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"] }
@ -36,13 +37,11 @@ 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]
arroy = "0.4.0"
big_s = "1.0.2"
crossbeam = "0.8.4"
insta = { version = "1.34.0", features = ["json", "redactions"] }
maplit = "1.0.2"
meili-snap = { path = "../meili-snap" }

View File

@ -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
@ -909,16 +908,13 @@ impl IndexScheduler {
let fields_ids_map = index.fields_ids_map(&rtxn)?;
let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
let embedding_configs = index.embedding_configs(&rtxn)?;
// 3.1. Dump the documents
for ret in index.all_documents(&rtxn)? {
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: {
@ -929,44 +925,20 @@ impl IndexScheduler {
}
let vectors = document
.entry(RESERVED_VECTORS_FIELD_NAME.to_owned())
.entry("_vectors".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());
break 'inject_vectors;
};
for (embedder_name, embeddings) in embeddings {
let user_provided = embedding_configs
.iter()
.find(|conf| conf.name == embedder_name)
.is_some_and(|conf| conf.user_provided.contains(id));
let embeddings = ExplicitVectors {
embeddings: Some(
VectorOrArrayOfVectors::from_array_of_vectors(embeddings),
),
regenerate: !user_provided,
};
vectors.insert(
embedder_name,
serde_json::to_value(embeddings).unwrap(),
);
vectors.entry(embedder_name).or_insert_with(|| {
serde_json::json!({
"embeddings": embeddings,
"regenerate": true
})
});
}
}
@ -1228,6 +1200,8 @@ 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()?;

View File

@ -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 {

View File

@ -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: _,

File diff suppressed because it is too large Load Diff

View File

@ -1,15 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: doc
---
{
"doggo": "Intel",
"breed": "beagle",
"_vectors": {
"noise": [
0.1,
0.2,
0.3
]
}
}

View File

@ -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"
}
}
}

View File

@ -1,15 +0,0 @@
---
source: index-scheduler/src/lib.rs
expression: doc
---
{
"doggo": "kefir",
"breed": "patou",
"_vectors": {
"noise": [
0.1,
0.2,
0.3
]
}
}

View File

@ -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"
}
}

View File

@ -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
}
}

View File

@ -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"
}
}
}

View File

@ -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:
----------------------------------------------------------------------

View File

@ -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
----------------------------------------------------------------------

View File

@ -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:
----------------------------------------------------------------------

View File

@ -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
----------------------------------------------------------------------

View File

@ -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:
----------------------------------------------------------------------

View File

@ -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:
----------------------------------------------------------------------

View File

@ -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();
}
}
}

View File

@ -188,12 +188,6 @@ impl AuthFilter {
self.allow_index_creation && self.is_index_authorized(index)
}
#[inline]
/// Return true if a tenant token was used to generate the search rules.
pub fn is_tenant_token(&self) -> bool {
self.search_rules.is_some()
}
pub fn with_allowed_indexes(allowed_indexes: HashSet<IndexUidPattern>) -> Self {
Self {
search_rules: None,
@ -211,7 +205,6 @@ impl AuthFilter {
.unwrap_or(true)
}
/// Check if the index is authorized by the API key and the tenant token.
pub fn is_index_authorized(&self, index: &str) -> bool {
self.key_authorized_indexes.is_index_authorized(index)
&& self
@ -221,44 +214,6 @@ impl AuthFilter {
.unwrap_or(true)
}
/// Only check if the index is authorized by the API key
pub fn api_key_is_index_authorized(&self, index: &str) -> bool {
self.key_authorized_indexes.is_index_authorized(index)
}
/// Only check if the index is authorized by the tenant token
pub fn tenant_token_is_index_authorized(&self, index: &str) -> bool {
self.search_rules
.as_ref()
.map(|search_rules| search_rules.is_index_authorized(index))
.unwrap_or(true)
}
/// Return the list of authorized indexes by the tenant token if any
pub fn tenant_token_list_index_authorized(&self) -> Vec<String> {
match self.search_rules {
Some(ref search_rules) => {
let mut indexes: Vec<_> = match search_rules {
SearchRules::Set(set) => set.iter().map(|s| s.to_string()).collect(),
SearchRules::Map(map) => map.keys().map(|s| s.to_string()).collect(),
};
indexes.sort_unstable();
indexes
}
None => Vec::new(),
}
}
/// Return the list of authorized indexes by the api key if any
pub fn api_key_list_index_authorized(&self) -> Vec<String> {
let mut indexes: Vec<_> = match self.key_authorized_indexes {
SearchRules::Set(ref set) => set.iter().map(|s| s.to_string()).collect(),
SearchRules::Map(ref map) => map.keys().map(|s| s.to_string()).collect(),
};
indexes.sort_unstable();
indexes
}
pub fn get_index_search_rules(&self, index: &str) -> Option<IndexSearchRules> {
if !self.is_index_authorized(index) {
return None;

View File

@ -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 {

View File

@ -11,7 +11,7 @@ edition.workspace = true
license.workspace = true
[dependencies]
actix-web = { version = "4.6.0", default-features = false }
actix-web = { version = "4.5.1", default-features = false }
anyhow = "1.0.79"
convert_case = "0.6.0"
csv = "1.3.0"
@ -30,12 +30,7 @@ serde_json = "1.0.111"
tar = "0.4.40"
tempfile = "3.9.0"
thiserror = "1.0.56"
time = { version = "0.3.31", features = [
"serde-well-known",
"formatting",
"parsing",
"macros",
] }
time = { version = "0.3.31", features = ["serde-well-known", "formatting", "parsing", "macros"] }
tokio = "1.35"
uuid = { version = "1.6.1", features = ["serde", "v4"] }
@ -54,8 +49,6 @@ chinese-pinyin = ["milli/chinese-pinyin"]
hebrew = ["milli/hebrew"]
# japanese specialized tokenization
japanese = ["milli/japanese"]
# korean specialized tokenization
korean = ["milli/korean"]
# thai specialized tokenization
thai = ["milli/thai"]
# allow greek specialized tokenization

View File

@ -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,
@ -189,6 +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!(InvalidSearchRankingScoreThreshold);
merge_with_error_impl_take_error_message!(InvalidSimilarRankingScoreThreshold);
merge_with_error_impl_take_error_message!(InvalidSimilarId);

View File

@ -222,7 +222,6 @@ InvalidApiKeyUid , InvalidRequest , BAD_REQUEST ;
InvalidContentType , InvalidRequest , UNSUPPORTED_MEDIA_TYPE ;
InvalidDocumentCsvDelimiter , InvalidRequest , BAD_REQUEST ;
InvalidDocumentFields , InvalidRequest , BAD_REQUEST ;
InvalidDocumentRetrieveVectors , InvalidRequest , BAD_REQUEST ;
MissingDocumentFilter , InvalidRequest , BAD_REQUEST ;
InvalidDocumentFilter , InvalidRequest , BAD_REQUEST ;
InvalidDocumentGeoField , InvalidRequest , BAD_REQUEST ;
@ -240,27 +239,18 @@ InvalidIndexUid , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToSearchOn , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToCrop , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToHighlight , InvalidRequest , BAD_REQUEST ;
InvalidSimilarAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
InvalidSimilarRetrieveVectors , InvalidRequest , BAD_REQUEST ;
InvalidSearchAttributesToRetrieve , InvalidRequest , BAD_REQUEST ;
InvalidSearchRankingScoreThreshold , InvalidRequest , BAD_REQUEST ;
InvalidSimilarRankingScoreThreshold , InvalidRequest , BAD_REQUEST ;
InvalidSearchRetrieveVectors , 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 ;
@ -269,18 +259,15 @@ 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 ;
InvalidSearchDistinct , InvalidRequest , BAD_REQUEST ;
InvalidSettingsDisplayedAttributes , InvalidRequest , BAD_REQUEST ;
InvalidSettingsDistinctAttribute , InvalidRequest , BAD_REQUEST ;
InvalidSettingsProximityPrecision , InvalidRequest , BAD_REQUEST ;
InvalidSettingsFaceting , InvalidRequest , BAD_REQUEST ;
InvalidSettingsFilterableAttributes , InvalidRequest , BAD_REQUEST ;
InvalidSettingsPagination , InvalidRequest , BAD_REQUEST ;
InvalidSettingsSearchCutoffMs , InvalidRequest , BAD_REQUEST ;
InvalidSettingsSearchCutoffMs , InvalidRequest , BAD_REQUEST ;
InvalidSettingsEmbedders , InvalidRequest , BAD_REQUEST ;
InvalidSettingsRankingRules , InvalidRequest , BAD_REQUEST ;
InvalidSettingsSearchableAttributes , InvalidRequest , BAD_REQUEST ;
@ -335,8 +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 {
@ -385,7 +371,6 @@ impl ErrorCode for milli::Error {
Code::IndexPrimaryKeyMultipleCandidatesFound
}
UserError::PrimaryKeyCannotBeChanged(_) => Code::IndexPrimaryKeyAlreadyExists,
UserError::InvalidDistinctAttribute { .. } => Code::InvalidSearchDistinct,
UserError::SortRankingRuleMissing => Code::InvalidSearchSort,
UserError::InvalidFacetsDistribution { .. } => Code::InvalidSearchFacets,
UserError::InvalidSortableAttribute { .. } => Code::InvalidSearchSort,
@ -398,8 +383,8 @@ impl ErrorCode for milli::Error {
UserError::CriterionError(_) => Code::InvalidSettingsRankingRules,
UserError::InvalidGeoField { .. } => Code::InvalidDocumentGeoField,
UserError::InvalidVectorDimensions { .. } => Code::InvalidVectorDimensions,
UserError::InvalidVectorsMapType { .. }
| UserError::InvalidVectorsEmbedderConf { .. } => Code::InvalidVectorsType,
UserError::InvalidVectorsMapType { .. } => Code::InvalidVectorsType,
UserError::InvalidVectorsType { .. } => Code::InvalidVectorsType,
UserError::TooManyVectors(_, _) => Code::TooManyVectors,
UserError::SortError(_) => Code::InvalidSearchSort,
UserError::InvalidMinTypoWordLenSetting(_, _) => {
@ -438,6 +423,7 @@ impl ErrorCode for HeedError {
HeedError::Mdb(_)
| HeedError::Encoding(_)
| HeedError::Decoding(_)
| HeedError::InvalidDatabaseTyping
| HeedError::DatabaseClosing
| HeedError::BadOpenOptions { .. } => Code::Internal,
}
@ -502,32 +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 (_)."
)
}
}
impl fmt::Display for deserr_codes::InvalidSearchRankingScoreThreshold {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(
f,
"the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`."
)
}
}
impl fmt::Display for deserr_codes::InvalidSimilarRankingScoreThreshold {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
deserr_codes::InvalidSearchRankingScoreThreshold.fmt(f)
}
}
#[macro_export]
macro_rules! internal_error {
($target:ty : $($other:path), *) => {

View File

@ -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)]

View File

@ -8,7 +8,6 @@ use std::str::FromStr;
use deserr::{DeserializeError, Deserr, ErrorKind, MergeWithError, ValuePointerRef};
use fst::IntoStreamer;
use milli::index::IndexEmbeddingConfig;
use milli::proximity::ProximityPrecision;
use milli::update::Setting;
use milli::{Criterion, CriterionError, Index, DEFAULT_VALUES_PER_FACET};
@ -673,7 +672,7 @@ pub fn settings(
let embedders: BTreeMap<_, _> = index
.embedding_configs(rtxn)?
.into_iter()
.map(|IndexEmbeddingConfig { name, config, .. }| (name, Setting::Set(config.into())))
.map(|(name, config)| (name, Setting::Set(config.into())))
.collect();
let embedders = if embedders.is_empty() { Setting::NotSet } else { Setting::Set(embedders) };

View File

@ -14,20 +14,20 @@ default-run = "meilisearch"
[dependencies]
actix-cors = "0.7.0"
actix-http = { version = "3.7.0", default-features = false, features = [
actix-http = { version = "3.6.0", default-features = false, features = [
"compress-brotli",
"compress-gzip",
"rustls-0_21",
] }
actix-utils = "3.0.1"
actix-web = { version = "4.6.0", default-features = false, features = [
actix-web = { version = "4.5.1", default-features = false, features = [
"macros",
"compress-brotli",
"compress-gzip",
"cookies",
"rustls-0_21",
] }
actix-web-static-files = { version = "4.0.1", optional = true }
actix-web-static-files = { git = "https://github.com/kilork/actix-web-static-files.git", rev = "2d3b6160", optional = true }
anyhow = { version = "1.0.79", features = ["backtrace"] }
async-stream = "0.3.5"
async-trait = "0.1.77"
@ -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"] }
@ -98,26 +99,27 @@ tokio-stream = "0.1.14"
toml = "0.8.8"
uuid = { version = "1.6.1", features = ["serde", "v4"] }
walkdir = "2.4.0"
yaup = "0.2.1"
serde_urlencoded = "0.7.1"
termcolor = "1.4.1"
url = { version = "2.5.0", features = ["serde"] }
tracing = "0.1.40"
tracing-subscriber = { version = "0.3.18", features = ["json"] }
tracing-trace = { version = "0.1.0", path = "../tracing-trace" }
tracing-actix-web = "0.7.10"
tracing-actix-web = "0.7.9"
build-info = { version = "1.7.0", path = "../build-info" }
[dev-dependencies]
actix-rt = "2.9.0"
assert-json-diff = "2.0.2"
brotli = "6.0.0"
brotli = "3.4.0"
insta = "1.34.0"
manifest-dir-macros = "0.1.18"
maplit = "1.0.2"
meili-snap = { path = "../meili-snap" }
temp-env = "0.3.6"
urlencoding = "2.1.3"
yaup = "0.3.1"
yaup = "0.2.1"
[build-dependencies]
anyhow = { version = "1.0.79", optional = true }
@ -150,7 +152,6 @@ chinese = ["meilisearch-types/chinese"]
chinese-pinyin = ["meilisearch-types/chinese-pinyin"]
hebrew = ["meilisearch-types/hebrew"]
japanese = ["meilisearch-types/japanese"]
korean = ["meilisearch-types/korean"]
thai = ["meilisearch-types/thai"]
greek = ["meilisearch-types/greek"]
khmer = ["meilisearch-types/khmer"]
@ -158,5 +159,5 @@ vietnamese = ["meilisearch-types/vietnamese"]
swedish-recomposition = ["meilisearch-types/swedish-recomposition"]
[package.metadata.mini-dashboard]
assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.14/build.zip"
sha1 = "592d1b5a3459d621d0aae1dded8fe3154f5c38fe"
assets-url = "https://github.com/meilisearch/mini-dashboard/releases/download/v0.2.13/build.zip"
sha1 = "e20cc9b390003c6c844f4b8bcc5c5013191a77ff"

View File

@ -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(

View File

@ -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;
@ -74,8 +70,8 @@ pub enum DocumentDeletionKind {
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
pub enum DocumentFetchKind {
PerDocumentId { retrieve_vectors: bool },
Normal { with_filter: bool, limit: usize, offset: usize, retrieve_vectors: bool },
PerDocumentId,
Normal { with_filter: bool, limit: usize, offset: usize },
}
pub trait Analytics: Sync + Send {
@ -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);

View File

@ -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;
}
}
@ -597,9 +566,6 @@ pub struct SearchAggregator {
// every time a request has a filter, this field must be incremented by one
sort_total_number_of_criteria: usize,
// distinct
distinct: bool,
// filter
filter_with_geo_radius: bool,
filter_with_geo_bounding_box: bool,
@ -625,7 +591,6 @@ pub struct SearchAggregator {
// Whether a non-default embedder was specified
embedder: bool,
hybrid: bool,
retrieve_vectors: bool,
// every time a search is done, we increment the counter linked to the used settings
matching_strategy: HashMap<String, usize>,
@ -652,7 +617,6 @@ pub struct SearchAggregator {
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: bool,
}
impl SearchAggregator {
@ -666,7 +630,6 @@ impl SearchAggregator {
page,
hits_per_page,
attributes_to_retrieve: _,
retrieve_vectors,
attributes_to_crop: _,
crop_length,
attributes_to_highlight: _,
@ -675,7 +638,6 @@ impl SearchAggregator {
show_ranking_score_details,
filter,
sort,
distinct,
facets: _,
highlight_pre_tag,
highlight_post_tag,
@ -683,7 +645,6 @@ impl SearchAggregator {
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
} = query;
let mut ret = Self::default();
@ -698,8 +659,6 @@ impl SearchAggregator {
ret.sort_sum_of_criteria_terms = sort.len();
}
ret.distinct = distinct.is_some();
if let Some(ref filter) = filter {
static RE: Lazy<Regex> = Lazy::new(|| Regex::new("AND | OR").unwrap());
ret.filter_total_number_of_criteria = 1;
@ -736,7 +695,6 @@ impl SearchAggregator {
if let Some(ref vector) = vector {
ret.max_vector_size = vector.len();
}
ret.retrieve_vectors |= retrieve_vectors;
if query.is_finite_pagination() {
let limit = hits_per_page.unwrap_or_else(DEFAULT_SEARCH_LIMIT);
@ -759,7 +717,6 @@ impl SearchAggregator {
ret.show_ranking_score = *show_ranking_score;
ret.show_ranking_score_details = *show_ranking_score_details;
ret.ranking_score_threshold = ranking_score_threshold.is_some();
if let Some(hybrid) = hybrid {
ret.semantic_ratio = hybrid.semantic_ratio != DEFAULT_SEMANTIC_RATIO();
@ -804,7 +761,6 @@ impl SearchAggregator {
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
@ -813,7 +769,6 @@ impl SearchAggregator {
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
@ -835,7 +790,6 @@ impl SearchAggregator {
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
} = other;
if self.timestamp.is_none() {
@ -862,9 +816,6 @@ impl SearchAggregator {
self.sort_total_number_of_criteria =
self.sort_total_number_of_criteria.saturating_add(sort_total_number_of_criteria);
// distinct
self.distinct |= distinct;
// filter
self.filter_with_geo_radius |= filter_with_geo_radius;
self.filter_with_geo_bounding_box |= filter_with_geo_bounding_box;
@ -887,7 +838,6 @@ impl SearchAggregator {
// vector
self.max_vector_size = self.max_vector_size.max(max_vector_size);
self.retrieve_vectors |= retrieve_vectors;
self.semantic_ratio |= semantic_ratio;
self.hybrid |= hybrid;
self.embedder |= embedder;
@ -923,7 +873,6 @@ impl SearchAggregator {
// scoring
self.show_ranking_score |= show_ranking_score;
self.show_ranking_score_details |= show_ranking_score_details;
self.ranking_score_threshold |= ranking_score_threshold;
}
pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
@ -936,7 +885,6 @@ impl SearchAggregator {
sort_with_geo_point,
sort_sum_of_criteria_terms,
sort_total_number_of_criteria,
distinct,
filter_with_geo_radius,
filter_with_geo_bounding_box,
filter_sum_of_criteria_terms,
@ -945,7 +893,6 @@ impl SearchAggregator {
attributes_to_search_on_total_number_of_uses,
max_terms_number,
max_vector_size,
retrieve_vectors,
matching_strategy,
max_limit,
max_offset,
@ -967,7 +914,6 @@ impl SearchAggregator {
hybrid,
total_degraded,
total_used_negative_operator,
ranking_score_threshold,
} = self;
if total_received == 0 {
@ -994,7 +940,6 @@ impl SearchAggregator {
"with_geoPoint": sort_with_geo_point,
"avg_criteria_number": format!("{:.2}", sort_sum_of_criteria_terms as f64 / sort_total_number_of_criteria as f64),
},
"distinct": distinct,
"filter": {
"with_geoRadius": filter_with_geo_radius,
"with_geoBoundingBox": filter_with_geo_bounding_box,
@ -1009,7 +954,6 @@ impl SearchAggregator {
},
"vector": {
"max_vector_size": max_vector_size,
"retrieve_vectors": retrieve_vectors,
},
"hybrid": {
"enabled": hybrid,
@ -1040,7 +984,6 @@ impl SearchAggregator {
"scoring": {
"show_ranking_score": show_ranking_score,
"show_ranking_score_details": show_ranking_score_details,
"ranking_score_threshold": ranking_score_threshold,
},
});
@ -1098,7 +1041,6 @@ impl MultiSearchAggregator {
page: _,
hits_per_page: _,
attributes_to_retrieve: _,
retrieve_vectors: _,
attributes_to_crop: _,
crop_length: _,
attributes_to_highlight: _,
@ -1107,7 +1049,6 @@ impl MultiSearchAggregator {
show_matches_position: _,
filter: _,
sort: _,
distinct: _,
facets: _,
highlight_pre_tag: _,
highlight_post_tag: _,
@ -1115,7 +1056,6 @@ impl MultiSearchAggregator {
matching_strategy: _,
attributes_to_search_on: _,
hybrid: _,
ranking_score_threshold: _,
} = query;
index_uid.as_str()
@ -1263,7 +1203,6 @@ impl FacetSearchAggregator {
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
} = query;
let mut ret = Self::default();
@ -1278,8 +1217,7 @@ impl FacetSearchAggregator {
|| filter.is_some()
|| *matching_strategy != MatchingStrategy::default()
|| attributes_to_search_on.is_some()
|| hybrid.is_some()
|| ranking_score_threshold.is_some();
|| hybrid.is_some();
ret
}
@ -1555,9 +1493,6 @@ pub struct DocumentsFetchAggregator {
// if a filter was used
per_filter: bool,
#[serde(rename = "vector.retrieve_vectors")]
retrieve_vectors: bool,
// pagination
#[serde(rename = "pagination.max_limit")]
max_limit: usize,
@ -1567,21 +1502,18 @@ pub struct DocumentsFetchAggregator {
impl DocumentsFetchAggregator {
pub fn from_query(query: &DocumentFetchKind, request: &HttpRequest) -> Self {
let (limit, offset, retrieve_vectors) = match query {
DocumentFetchKind::PerDocumentId { retrieve_vectors } => (1, 0, *retrieve_vectors),
DocumentFetchKind::Normal { limit, offset, retrieve_vectors, .. } => {
(*limit, *offset, *retrieve_vectors)
}
let (limit, offset) = match query {
DocumentFetchKind::PerDocumentId => (1, 0),
DocumentFetchKind::Normal { limit, offset, .. } => (*limit, *offset),
};
Self {
timestamp: Some(OffsetDateTime::now_utc()),
user_agents: extract_user_agents(request).into_iter().collect(),
total_received: 1,
per_document_id: matches!(query, DocumentFetchKind::PerDocumentId { .. }),
per_document_id: matches!(query, DocumentFetchKind::PerDocumentId),
per_filter: matches!(query, DocumentFetchKind::Normal { with_filter, .. } if *with_filter),
max_limit: limit,
max_offset: offset,
retrieve_vectors,
}
}
@ -1595,7 +1527,6 @@ impl DocumentsFetchAggregator {
per_filter,
max_limit,
max_offset,
retrieve_vectors,
} = other;
if self.timestamp.is_none() {
@ -1611,8 +1542,6 @@ impl DocumentsFetchAggregator {
self.max_limit = self.max_limit.max(max_limit);
self.max_offset = self.max_offset.max(max_offset);
self.retrieve_vectors |= retrieve_vectors;
}
pub fn into_event(self, user: &User, event_name: &str) -> Option<Track> {
@ -1629,251 +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,
retrieve_vectors: bool,
// pagination
max_limit: usize,
max_offset: usize,
// formatting
max_attributes_to_retrieve: usize,
// scoring
show_ranking_score: bool,
show_ranking_score_details: bool,
ranking_score_threshold: 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: _,
retrieve_vectors,
show_ranking_score,
show_ranking_score_details,
filter,
ranking_score_threshold,
} = 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.ranking_score_threshold = ranking_score_threshold.is_some();
ret.embedder = embedder.is_some();
ret.retrieve_vectors = *retrieve_vectors;
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,
ranking_score_threshold,
retrieve_vectors,
} = 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;
self.retrieve_vectors |= retrieve_vectors;
// 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;
self.ranking_score_threshold |= ranking_score_threshold;
}
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,
ranking_score_threshold,
retrieve_vectors,
} = 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)),
},
"vector": {
"retrieve_vectors": retrieve_vectors,
},
"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,
"ranking_score_threshold": ranking_score_threshold,
},
});
Some(Track {
timestamp,
user: user.clone(),
event: event_name.to_string(),
properties,
..Default::default()
})
}
}
}

View File

@ -98,29 +98,14 @@ impl From<MeilisearchHttpError> for aweb::Error {
impl From<aweb::error::PayloadError> for MeilisearchHttpError {
fn from(error: aweb::error::PayloadError) -> Self {
match error {
aweb::error::PayloadError::Incomplete(_) => MeilisearchHttpError::Payload(
PayloadError::Payload(ActixPayloadError::IncompleteError),
),
_ => MeilisearchHttpError::Payload(PayloadError::Payload(
ActixPayloadError::OtherError(error),
)),
}
MeilisearchHttpError::Payload(PayloadError::Payload(error))
}
}
#[derive(Debug, thiserror::Error)]
pub enum ActixPayloadError {
#[error("The provided payload is incomplete and cannot be parsed")]
IncompleteError,
#[error(transparent)]
OtherError(aweb::error::PayloadError),
}
#[derive(Debug, thiserror::Error)]
pub enum PayloadError {
#[error(transparent)]
Payload(ActixPayloadError),
Payload(aweb::error::PayloadError),
#[error(transparent)]
Json(JsonPayloadError),
#[error(transparent)]
@ -137,15 +122,13 @@ impl ErrorCode for PayloadError {
fn error_code(&self) -> Code {
match self {
PayloadError::Payload(e) => match e {
ActixPayloadError::IncompleteError => Code::BadRequest,
ActixPayloadError::OtherError(error) => match error {
aweb::error::PayloadError::EncodingCorrupted => Code::Internal,
aweb::error::PayloadError::Overflow => Code::PayloadTooLarge,
aweb::error::PayloadError::UnknownLength => Code::Internal,
aweb::error::PayloadError::Http2Payload(_) => Code::Internal,
aweb::error::PayloadError::Io(_) => Code::Internal,
_ => todo!(),
},
aweb::error::PayloadError::Incomplete(_) => Code::Internal,
aweb::error::PayloadError::EncodingCorrupted => Code::Internal,
aweb::error::PayloadError::Overflow => Code::PayloadTooLarge,
aweb::error::PayloadError::UnknownLength => Code::Internal,
aweb::error::PayloadError::Http2Payload(_) => Code::Internal,
aweb::error::PayloadError::Io(_) => Code::Internal,
_ => todo!(),
},
PayloadError::Json(err) => match err {
JsonPayloadError::Overflow { .. } => Code::PayloadTooLarge,

View File

@ -12,8 +12,6 @@ use futures::Future;
use meilisearch_auth::{AuthController, AuthFilter};
use meilisearch_types::error::{Code, ResponseError};
use self::policies::AuthError;
pub struct GuardedData<P, D> {
data: D,
filters: AuthFilter,
@ -37,12 +35,12 @@ impl<P, D> GuardedData<P, D> {
let missing_master_key = auth.get_master_key().is_none();
match Self::authenticate(auth, token, index).await? {
Ok(filters) => match data {
Some(filters) => match data {
Some(data) => Ok(Self { data, filters, _marker: PhantomData }),
None => Err(AuthenticationError::IrretrievableState.into()),
},
Err(_) if missing_master_key => Err(AuthenticationError::MissingMasterKey.into()),
Err(e) => Err(ResponseError::from_msg(e.to_string(), Code::InvalidApiKey)),
None if missing_master_key => Err(AuthenticationError::MissingMasterKey.into()),
None => Err(AuthenticationError::InvalidToken.into()),
}
}
@ -53,12 +51,12 @@ impl<P, D> GuardedData<P, D> {
let missing_master_key = auth.get_master_key().is_none();
match Self::authenticate(auth, String::new(), None).await? {
Ok(filters) => match data {
Some(filters) => match data {
Some(data) => Ok(Self { data, filters, _marker: PhantomData }),
None => Err(AuthenticationError::IrretrievableState.into()),
},
Err(_) if missing_master_key => Err(AuthenticationError::MissingMasterKey.into()),
Err(_) => Err(AuthenticationError::MissingAuthorizationHeader.into()),
None if missing_master_key => Err(AuthenticationError::MissingMasterKey.into()),
None => Err(AuthenticationError::MissingAuthorizationHeader.into()),
}
}
@ -66,7 +64,7 @@ impl<P, D> GuardedData<P, D> {
auth: Data<AuthController>,
token: String,
index: Option<String>,
) -> Result<Result<AuthFilter, AuthError>, ResponseError>
) -> Result<Option<AuthFilter>, ResponseError>
where
P: Policy + 'static,
{
@ -129,14 +127,13 @@ pub trait Policy {
auth: Data<AuthController>,
token: &str,
index: Option<&str>,
) -> Result<AuthFilter, policies::AuthError>;
) -> Option<AuthFilter>;
}
pub mod policies {
use actix_web::web::Data;
use jsonwebtoken::{decode, Algorithm, DecodingKey, Validation};
use meilisearch_auth::{AuthController, AuthFilter, SearchRules};
use meilisearch_types::error::{Code, ErrorCode};
// reexport actions in policies in order to be used in routes configuration.
pub use meilisearch_types::keys::{actions, Action};
use serde::{Deserialize, Serialize};
@ -147,53 +144,11 @@ pub mod policies {
enum TenantTokenOutcome {
NotATenantToken,
Invalid,
Expired,
Valid(Uuid, SearchRules),
}
#[derive(thiserror::Error, Debug)]
pub enum AuthError {
#[error("Tenant token expired. Was valid up to `{exp}` and we're now `{now}`.")]
ExpiredTenantToken { exp: i64, now: i64 },
#[error("The provided API key is invalid.")]
InvalidApiKey,
#[error("The provided tenant token cannot acces the index `{index}`, allowed indexes are {allowed:?}.")]
TenantTokenAccessingnUnauthorizedIndex { index: String, allowed: Vec<String> },
#[error(
"The API key used to generate this tenant token cannot acces the index `{index}`."
)]
TenantTokenApiKeyAccessingnUnauthorizedIndex { index: String },
#[error(
"The API key cannot acces the index `{index}`, authorized indexes are {allowed:?}."
)]
ApiKeyAccessingnUnauthorizedIndex { index: String, allowed: Vec<String> },
#[error("The provided tenant token is invalid.")]
InvalidTenantToken,
#[error("Could not decode tenant token, {0}.")]
CouldNotDecodeTenantToken(jsonwebtoken::errors::Error),
#[error("Invalid action `{0}`.")]
InternalInvalidAction(u8),
}
impl From<jsonwebtoken::errors::Error> for AuthError {
fn from(error: jsonwebtoken::errors::Error) -> Self {
use jsonwebtoken::errors::ErrorKind;
match error.kind() {
ErrorKind::InvalidToken => AuthError::InvalidTenantToken,
_ => AuthError::CouldNotDecodeTenantToken(error),
}
}
}
impl ErrorCode for AuthError {
fn error_code(&self) -> Code {
match self {
AuthError::InternalInvalidAction(_) => Code::Internal,
_ => Code::InvalidApiKey,
}
}
}
fn tenant_token_validation() -> Validation {
let mut validation = Validation::default();
validation.validate_exp = false;
@ -203,15 +158,15 @@ pub mod policies {
}
/// Extracts the key id used to sign the payload, without performing any validation.
fn extract_key_id(token: &str) -> Result<Uuid, AuthError> {
fn extract_key_id(token: &str) -> Option<Uuid> {
let mut validation = tenant_token_validation();
validation.insecure_disable_signature_validation();
let dummy_key = DecodingKey::from_secret(b"secret");
let token_data = decode::<Claims>(token, &dummy_key, &validation)?;
let token_data = decode::<Claims>(token, &dummy_key, &validation).ok()?;
// get token fields without validating it.
let Claims { api_key_uid, .. } = token_data.claims;
Ok(api_key_uid)
Some(api_key_uid)
}
fn is_keys_action(action: u8) -> bool {
@ -232,102 +187,76 @@ pub mod policies {
auth: Data<AuthController>,
token: &str,
index: Option<&str>,
) -> Result<AuthFilter, AuthError> {
) -> Option<AuthFilter> {
// authenticate if token is the master key.
// Without a master key, all routes are accessible except the key-related routes.
if auth.get_master_key().map_or_else(|| !is_keys_action(A), |mk| mk == token) {
return Ok(AuthFilter::default());
return Some(AuthFilter::default());
}
let (key_uuid, search_rules) =
match ActionPolicy::<A>::authenticate_tenant_token(&auth, token) {
Ok(TenantTokenOutcome::Valid(key_uuid, search_rules)) => {
TenantTokenOutcome::Valid(key_uuid, search_rules) => {
(key_uuid, Some(search_rules))
}
Ok(TenantTokenOutcome::NotATenantToken)
| Err(AuthError::InvalidTenantToken) => (
auth.get_optional_uid_from_encoded_key(token.as_bytes())
.map_err(|_e| AuthError::InvalidApiKey)?
.ok_or(AuthError::InvalidApiKey)?,
None,
),
Err(e) => return Err(e),
TenantTokenOutcome::Expired => return None,
TenantTokenOutcome::Invalid => return None,
TenantTokenOutcome::NotATenantToken => {
(auth.get_optional_uid_from_encoded_key(token.as_bytes()).ok()??, None)
}
};
// check that the indexes are allowed
let action = Action::from_repr(A).ok_or(AuthError::InternalInvalidAction(A))?;
let auth_filter = auth
.get_key_filters(key_uuid, search_rules)
.map_err(|_e| AuthError::InvalidApiKey)?;
// First check if the index is authorized in the tenant token, this is a public
// information, we can return a nice error message.
if let Some(index) = index {
if !auth_filter.tenant_token_is_index_authorized(index) {
return Err(AuthError::TenantTokenAccessingnUnauthorizedIndex {
index: index.to_string(),
allowed: auth_filter.tenant_token_list_index_authorized(),
});
}
if !auth_filter.api_key_is_index_authorized(index) {
if auth_filter.is_tenant_token() {
// If the error comes from a tenant token we cannot share the list
// of authorized indexes in the API key. This is not public information.
return Err(AuthError::TenantTokenApiKeyAccessingnUnauthorizedIndex {
index: index.to_string(),
});
} else {
// Otherwise we can share the list
// of authorized indexes in the API key.
return Err(AuthError::ApiKeyAccessingnUnauthorizedIndex {
index: index.to_string(),
allowed: auth_filter.api_key_list_index_authorized(),
});
}
}
}
if auth.is_key_authorized(key_uuid, action, index).unwrap_or(false) {
return Ok(auth_filter);
let action = Action::from_repr(A)?;
let auth_filter = auth.get_key_filters(key_uuid, search_rules).ok()?;
if auth.is_key_authorized(key_uuid, action, index).unwrap_or(false)
&& index.map(|index| auth_filter.is_index_authorized(index)).unwrap_or(true)
{
return Some(auth_filter);
}
Err(AuthError::InvalidApiKey)
None
}
}
impl<const A: u8> ActionPolicy<A> {
fn authenticate_tenant_token(
auth: &AuthController,
token: &str,
) -> Result<TenantTokenOutcome, AuthError> {
fn authenticate_tenant_token(auth: &AuthController, token: &str) -> TenantTokenOutcome {
// Only search action can be accessed by a tenant token.
if A != actions::SEARCH {
return Ok(TenantTokenOutcome::NotATenantToken);
return TenantTokenOutcome::NotATenantToken;
}
let uid = extract_key_id(token)?;
let uid = if let Some(uid) = extract_key_id(token) {
uid
} else {
return TenantTokenOutcome::NotATenantToken;
};
// Check if tenant token is valid.
let key = if let Some(key) = auth.generate_key(uid) {
key
} else {
return Err(AuthError::InvalidTenantToken);
return TenantTokenOutcome::Invalid;
};
let data = decode::<Claims>(
let data = if let Ok(data) = decode::<Claims>(
token,
&DecodingKey::from_secret(key.as_bytes()),
&tenant_token_validation(),
)?;
) {
data
} else {
return TenantTokenOutcome::Invalid;
};
// Check if token is expired.
if let Some(exp) = data.claims.exp {
let now = OffsetDateTime::now_utc().unix_timestamp();
if now > exp {
return Err(AuthError::ExpiredTenantToken { exp, now });
if OffsetDateTime::now_utc().unix_timestamp() > exp {
return TenantTokenOutcome::Expired;
}
}
Ok(TenantTokenOutcome::Valid(uid, data.claims.search_rules))
TenantTokenOutcome::Valid(uid, data.claims.search_rules)
}
}

View File

@ -419,7 +419,41 @@ fn import_dump(
let file = tempfile::tempfile()?;
let mut builder = DocumentsBatchBuilder::new(BufWriter::new(file));
for document in index_reader.documents()? {
builder.append_json_object(&document?)?;
let mut document = document?;
'remove_injected_vectors: {
let Some(vectors) = document.get_mut("_vectors") else {
break 'remove_injected_vectors;
};
let Some(vectors) = vectors.as_object_mut() else { break 'remove_injected_vectors };
vectors.retain(|_embedder, embedding_object| {
// don't touch values that aren't objects
let Some(embedding_object) = embedding_object.as_object() else {
return true;
};
let mut has_regenerate_true = false;
for (field, value) in embedding_object {
match (field.as_str(), value) {
// detected regenerate : true
// if we don't have any superfluous field, we'll remove the entire entry
("regenerate", serde_json::Value::Bool(true)) => {
has_regenerate_true = true;
}
// ignore embeddings
("embeddings", _) => continue,
// any other field: immediately retain the entry
_ => return true,
}
}
// retain the entry unless it has regenerate: true
!has_regenerate_true
})
}
builder.append_json_object(&document)?;
}
// This flush the content of the batch builder.

View File

@ -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(),
);
}

View File

@ -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),
);

View File

@ -16,7 +16,6 @@ use meilisearch_types::error::{Code, ResponseError};
use meilisearch_types::heed::RoTxn;
use meilisearch_types::index_uid::IndexUid;
use meilisearch_types::milli::update::IndexDocumentsMethod;
use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
use meilisearch_types::milli::DocumentId;
use meilisearch_types::star_or::OptionStarOrList;
use meilisearch_types::tasks::KindWithContent;
@ -40,7 +39,7 @@ use crate::extractors::sequential_extractor::SeqHandler;
use crate::routes::{
get_task_id, is_dry_run, PaginationView, SummarizedTaskView, PAGINATION_DEFAULT_LIMIT,
};
use crate::search::{parse_filter, RetrieveVectors};
use crate::search::parse_filter;
use crate::Opt;
static ACCEPTED_CONTENT_TYPE: Lazy<Vec<String>> = Lazy::new(|| {
@ -95,8 +94,6 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
pub struct GetDocument {
#[deserr(default, error = DeserrQueryParamError<InvalidDocumentFields>)]
fields: OptionStarOrList<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidDocumentRetrieveVectors>)]
retrieve_vectors: Param<bool>,
}
pub async fn get_document(
@ -110,20 +107,13 @@ pub async fn get_document(
debug!(parameters = ?params, "Get document");
let index_uid = IndexUid::try_from(index_uid)?;
let GetDocument { fields, retrieve_vectors: param_retrieve_vectors } = params.into_inner();
analytics.get_fetch_documents(&DocumentFetchKind::PerDocumentId, &req);
let GetDocument { fields } = params.into_inner();
let attributes_to_retrieve = fields.merge_star_and_none();
let features = index_scheduler.features();
let retrieve_vectors = RetrieveVectors::new(param_retrieve_vectors.0, features)?;
analytics.get_fetch_documents(
&DocumentFetchKind::PerDocumentId { retrieve_vectors: param_retrieve_vectors.0 },
&req,
);
let index = index_scheduler.index(&index_uid)?;
let document =
retrieve_document(&index, &document_id, attributes_to_retrieve, retrieve_vectors)?;
let document = retrieve_document(&index, &document_id, attributes_to_retrieve)?;
debug!(returns = ?document, "Get document");
Ok(HttpResponse::Ok().json(document))
}
@ -163,8 +153,6 @@ pub struct BrowseQueryGet {
limit: Param<usize>,
#[deserr(default, error = DeserrQueryParamError<InvalidDocumentFields>)]
fields: OptionStarOrList<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidDocumentRetrieveVectors>)]
retrieve_vectors: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidDocumentFilter>)]
filter: Option<String>,
}
@ -178,8 +166,6 @@ pub struct BrowseQuery {
limit: usize,
#[deserr(default, error = DeserrJsonError<InvalidDocumentFields>)]
fields: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidDocumentRetrieveVectors>)]
retrieve_vectors: bool,
#[deserr(default, error = DeserrJsonError<InvalidDocumentFilter>)]
filter: Option<Value>,
}
@ -199,7 +185,6 @@ pub async fn documents_by_query_post(
with_filter: body.filter.is_some(),
limit: body.limit,
offset: body.offset,
retrieve_vectors: body.retrieve_vectors,
},
&req,
);
@ -216,7 +201,7 @@ pub async fn get_documents(
) -> Result<HttpResponse, ResponseError> {
debug!(parameters = ?params, "Get documents GET");
let BrowseQueryGet { limit, offset, fields, retrieve_vectors, filter } = params.into_inner();
let BrowseQueryGet { limit, offset, fields, filter } = params.into_inner();
let filter = match filter {
Some(f) => match serde_json::from_str(&f) {
@ -230,7 +215,6 @@ pub async fn get_documents(
offset: offset.0,
limit: limit.0,
fields: fields.merge_star_and_none(),
retrieve_vectors: retrieve_vectors.0,
filter,
};
@ -239,7 +223,6 @@ pub async fn get_documents(
with_filter: query.filter.is_some(),
limit: query.limit,
offset: query.offset,
retrieve_vectors: query.retrieve_vectors,
},
&req,
);
@ -253,14 +236,10 @@ fn documents_by_query(
query: BrowseQuery,
) -> Result<HttpResponse, ResponseError> {
let index_uid = IndexUid::try_from(index_uid.into_inner())?;
let BrowseQuery { offset, limit, fields, retrieve_vectors, filter } = query;
let features = index_scheduler.features();
let retrieve_vectors = RetrieveVectors::new(retrieve_vectors, features)?;
let BrowseQuery { offset, limit, fields, filter } = query;
let index = index_scheduler.index(&index_uid)?;
let (total, documents) =
retrieve_documents(&index, offset, limit, filter, fields, retrieve_vectors)?;
let (total, documents) = retrieve_documents(&index, offset, limit, filter, fields)?;
let ret = PaginationView::new(offset, limit, total as usize, documents);
@ -600,44 +579,13 @@ fn some_documents<'a, 't: 'a>(
index: &'a Index,
rtxn: &'t RoTxn,
doc_ids: impl IntoIterator<Item = DocumentId> + 'a,
retrieve_vectors: RetrieveVectors,
) -> Result<impl Iterator<Item = Result<Document, ResponseError>> + 'a, ResponseError> {
let fields_ids_map = index.fields_ids_map(rtxn)?;
let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
let embedding_configs = index.embedding_configs(rtxn)?;
Ok(index.iter_documents(rtxn, doc_ids)?.map(move |ret| {
ret.map_err(ResponseError::from).and_then(|(key, document)| -> Result<_, ResponseError> {
let mut document = milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
match retrieve_vectors {
RetrieveVectors::Ignore => {}
RetrieveVectors::Hide => {
document.remove("_vectors");
}
RetrieveVectors::Retrieve => {
let mut vectors = match document.remove("_vectors") {
Some(Value::Object(map)) => map,
_ => Default::default(),
};
for (name, vector) in index.embeddings(rtxn, key)? {
let user_provided = embedding_configs
.iter()
.find(|conf| conf.name == name)
.is_some_and(|conf| conf.user_provided.contains(key));
let embeddings = ExplicitVectors {
embeddings: Some(vector.into()),
regenerate: !user_provided,
};
vectors.insert(
name,
serde_json::to_value(embeddings).map_err(MeilisearchHttpError::from)?,
);
}
document.insert("_vectors".into(), vectors.into());
}
}
Ok(document)
ret.map_err(ResponseError::from).and_then(|(_key, document)| -> Result<_, ResponseError> {
Ok(milli::obkv_to_json(&all_fields, &fields_ids_map, document)?)
})
}))
}
@ -648,7 +596,6 @@ fn retrieve_documents<S: AsRef<str>>(
limit: usize,
filter: Option<Value>,
attributes_to_retrieve: Option<Vec<S>>,
retrieve_vectors: RetrieveVectors,
) -> Result<(u64, Vec<Document>), ResponseError> {
let rtxn = index.read_txn()?;
let filter = &filter;
@ -673,57 +620,53 @@ fn retrieve_documents<S: AsRef<str>>(
let (it, number_of_documents) = {
let number_of_documents = candidates.len();
(
some_documents(
index,
&rtxn,
candidates.into_iter().skip(offset).take(limit),
retrieve_vectors,
)?,
some_documents(index, &rtxn, candidates.into_iter().skip(offset).take(limit))?,
number_of_documents,
)
};
let documents: Vec<_> = it
let documents: Result<Vec<_>, ResponseError> = it
.map(|document| {
Ok(match &attributes_to_retrieve {
Some(attributes_to_retrieve) => permissive_json_pointer::select_values(
&document?,
attributes_to_retrieve.iter().map(|s| s.as_ref()).chain(
(retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors"),
),
attributes_to_retrieve.iter().map(|s| s.as_ref()),
),
None => document?,
})
})
.collect::<Result<_, ResponseError>>()?;
.collect();
Ok((number_of_documents, documents))
Ok((number_of_documents, documents?))
}
fn retrieve_document<S: AsRef<str>>(
index: &Index,
doc_id: &str,
attributes_to_retrieve: Option<Vec<S>>,
retrieve_vectors: RetrieveVectors,
) -> Result<Document, ResponseError> {
let txn = index.read_txn()?;
let fields_ids_map = index.fields_ids_map(&txn)?;
let all_fields: Vec<_> = fields_ids_map.iter().map(|(id, _)| id).collect();
let internal_id = index
.external_documents_ids()
.get(&txn, doc_id)?
.ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))?;
let document = some_documents(index, &txn, Some(internal_id), retrieve_vectors)?
let document = index
.documents(&txn, std::iter::once(internal_id))?
.into_iter()
.next()
.ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))??;
.map(|(_, d)| d)
.ok_or_else(|| MeilisearchHttpError::DocumentNotFound(doc_id.to_string()))?;
let document = meilisearch_types::milli::obkv_to_json(&all_fields, &fields_ids_map, document)?;
let document = match &attributes_to_retrieve {
Some(attributes_to_retrieve) => permissive_json_pointer::select_values(
&document,
attributes_to_retrieve
.iter()
.map(|s| s.as_ref())
.chain((retrieve_vectors == RetrieveVectors::Retrieve).then_some("_vectors")),
attributes_to_retrieve.iter().map(|s| s.as_ref()),
),
None => document,
};

View File

@ -14,8 +14,8 @@ use crate::extractors::authentication::policies::*;
use crate::extractors::authentication::GuardedData;
use crate::routes::indexes::search::search_kind;
use crate::search::{
add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
SearchQuery, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
add_search_rules, perform_facet_search, HybridQuery, MatchingStrategy, SearchQuery,
DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET,
};
use crate::search_queue::SearchQueue;
@ -46,8 +46,6 @@ pub struct FacetSearchQuery {
pub matching_strategy: MatchingStrategy,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
pub attributes_to_search_on: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
pub ranking_score_threshold: Option<RankingScoreThreshold>,
}
pub async fn search(
@ -71,7 +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)?;
@ -105,7 +103,6 @@ impl From<FacetSearchQuery> for SearchQuery {
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
} = value;
SearchQuery {
@ -115,7 +112,6 @@ impl From<FacetSearchQuery> for SearchQuery {
page: None,
hits_per_page: None,
attributes_to_retrieve: None,
retrieve_vectors: false,
attributes_to_crop: None,
crop_length: DEFAULT_CROP_LENGTH(),
attributes_to_highlight: None,
@ -124,7 +120,6 @@ impl From<FacetSearchQuery> for SearchQuery {
show_ranking_score_details: false,
filter,
sort: None,
distinct: None,
facets: None,
highlight_pre_tag: DEFAULT_HIGHLIGHT_PRE_TAG(),
highlight_post_tag: DEFAULT_HIGHLIGHT_POST_TAG(),
@ -133,7 +128,6 @@ impl From<FacetSearchQuery> for SearchQuery {
vector,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
}
}
}

View File

@ -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)),
);
}

View File

@ -19,10 +19,9 @@ use crate::extractors::authentication::GuardedData;
use crate::extractors::sequential_extractor::SeqHandler;
use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
use crate::search::{
add_search_rules, perform_search, HybridQuery, MatchingStrategy, RankingScoreThreshold,
RetrieveVectors, SearchKind, SearchQuery, SemanticRatio, DEFAULT_CROP_LENGTH,
DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG, DEFAULT_HIGHLIGHT_PRE_TAG,
DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
add_search_rules, perform_search, HybridQuery, MatchingStrategy, SearchKind, SearchQuery,
SemanticRatio, DEFAULT_CROP_LENGTH, DEFAULT_CROP_MARKER, DEFAULT_HIGHLIGHT_POST_TAG,
DEFAULT_HIGHLIGHT_PRE_TAG, DEFAULT_SEARCH_LIMIT, DEFAULT_SEARCH_OFFSET, DEFAULT_SEMANTIC_RATIO,
};
use crate::search_queue::SearchQueue;
@ -51,8 +50,6 @@ pub struct SearchQueryGet {
hits_per_page: Option<Param<usize>>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToRetrieve>)]
attributes_to_retrieve: Option<CS<String>>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchRetrieveVectors>)]
retrieve_vectors: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchAttributesToCrop>)]
attributes_to_crop: Option<CS<String>>,
#[deserr(default = Param(DEFAULT_CROP_LENGTH()), error = DeserrQueryParamError<InvalidSearchCropLength>)]
@ -63,8 +60,6 @@ pub struct SearchQueryGet {
filter: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchSort>)]
sort: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchDistinct>)]
distinct: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchShowMatchesPosition>)]
show_matches_position: Param<bool>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchShowRankingScore>)]
@ -87,21 +82,6 @@ pub struct SearchQueryGet {
pub hybrid_embedder: Option<String>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchSemanticRatio>)]
pub hybrid_semantic_ratio: Option<SemanticRatioGet>,
#[deserr(default, error = DeserrQueryParamError<InvalidSearchRankingScoreThreshold>)]
pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
}
#[derive(Debug, Clone, Copy, PartialEq, deserr::Deserr)]
#[deserr(try_from(String) = TryFrom::try_from -> InvalidSearchRankingScoreThreshold)]
pub struct RankingScoreThresholdGet(RankingScoreThreshold);
impl std::convert::TryFrom<String> for RankingScoreThresholdGet {
type Error = InvalidSearchRankingScoreThreshold;
fn try_from(s: String) -> Result<Self, Self::Error> {
let f: f64 = s.parse().map_err(|_| InvalidSearchRankingScoreThreshold)?;
Ok(RankingScoreThresholdGet(RankingScoreThreshold::try_from(f)?))
}
}
#[derive(Debug, Clone, Copy, Default, PartialEq, deserr::Deserr)]
@ -157,13 +137,11 @@ impl From<SearchQueryGet> for SearchQuery {
page: other.page.as_deref().copied(),
hits_per_page: other.hits_per_page.as_deref().copied(),
attributes_to_retrieve: other.attributes_to_retrieve.map(|o| o.into_iter().collect()),
retrieve_vectors: other.retrieve_vectors.0,
attributes_to_crop: other.attributes_to_crop.map(|o| o.into_iter().collect()),
crop_length: other.crop_length.0,
attributes_to_highlight: other.attributes_to_highlight.map(|o| o.into_iter().collect()),
filter,
sort: other.sort.map(|attr| fix_sort_query_parameters(&attr)),
distinct: other.distinct,
show_matches_position: other.show_matches_position.0,
show_ranking_score: other.show_ranking_score.0,
show_ranking_score_details: other.show_ranking_score_details.0,
@ -174,7 +152,6 @@ impl From<SearchQueryGet> for SearchQuery {
matching_strategy: other.matching_strategy,
attributes_to_search_on: other.attributes_to_search_on.map(|o| o.into_iter().collect()),
hybrid,
ranking_score_threshold: other.ranking_score_threshold.map(|o| o.0),
}
}
}
@ -219,7 +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);
@ -228,12 +205,10 @@ pub async fn search_with_url_query(
let features = index_scheduler.features();
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
let retrieve_vector = RetrieveVectors::new(query.retrieve_vectors, features)?;
let _permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(&index, query, search_kind, retrieve_vector)
})
.await?;
let search_result =
tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
if let Ok(ref search_result) = search_result {
aggregate.succeed(search_result);
}
@ -260,7 +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);
@ -270,13 +245,10 @@ pub async fn search_with_post(
let features = index_scheduler.features();
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
let _permit = search_queue.try_get_search_permit().await?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(&index, query, search_kind, retrieve_vectors)
})
.await?;
let search_result =
tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind)).await?;
if let Ok(ref search_result) = search_result {
aggregate.succeed(search_result);
if search_result.degraded {
@ -298,10 +270,11 @@ pub fn search_kind(
features: RoFeatures,
) -> Result<SearchKind, ResponseError> {
if query.vector.is_some() {
features.check_vector("Passing `vector` as a parameter")?;
features.check_vector("Passing `vector` as a query parameter")?;
}
if query.hybrid.is_some() {
features.check_vector("Passing `hybrid` as a parameter")?;
features.check_vector("Passing `hybrid` as a query parameter")?;
}
// regardless of anything, always do a keyword search when we don't have a vector and the query is whitespace or missing

View File

@ -1,192 +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::*;
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, RankingScoreThresholdSimilar, RetrieveVectors, 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()?;
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")?;
let retrieve_vectors = RetrieveVectors::new(query.retrieve_vectors, features)?;
// 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, retrieve_vectors)
})
.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<InvalidSimilarRetrieveVectors>)]
retrieve_vectors: Param<bool>,
#[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<InvalidSimilarRankingScoreThreshold>, default)]
pub ranking_score_threshold: Option<RankingScoreThresholdGet>,
#[deserr(default, error = DeserrQueryParamError<InvalidEmbedder>)]
pub embedder: Option<String>,
}
#[derive(Debug, Clone, Copy, PartialEq, deserr::Deserr)]
#[deserr(try_from(String) = TryFrom::try_from -> InvalidSimilarRankingScoreThreshold)]
pub struct RankingScoreThresholdGet(RankingScoreThresholdSimilar);
impl std::convert::TryFrom<String> for RankingScoreThresholdGet {
type Error = InvalidSimilarRankingScoreThreshold;
fn try_from(s: String) -> Result<Self, Self::Error> {
let f: f64 = s.parse().map_err(|_| InvalidSimilarRankingScoreThreshold)?;
Ok(RankingScoreThresholdGet(RankingScoreThresholdSimilar::try_from(f)?))
}
}
impl TryFrom<SimilarQueryGet> for SimilarQuery {
type Error = ResponseError;
fn try_from(
SimilarQueryGet {
id,
offset,
limit,
attributes_to_retrieve,
retrieve_vectors,
filter,
show_ranking_score,
show_ranking_score_details,
embedder,
ranking_score_threshold,
}: 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().map_err(|code: InvalidSimilarId| {
ResponseError::from_msg(code.to_string(), code.error_code())
})?,
offset: offset.0,
limit: limit.0,
filter,
embedder,
attributes_to_retrieve: attributes_to_retrieve.map(|o| o.into_iter().collect()),
retrieve_vectors: retrieve_vectors.0,
show_ranking_score: show_ranking_score.0,
show_ranking_score_details: show_ranking_score_details.0,
ranking_score_threshold: ranking_score_threshold.map(|x| x.0),
})
}
}

View File

@ -15,7 +15,7 @@ use crate::extractors::authentication::{AuthenticationError, GuardedData};
use crate::extractors::sequential_extractor::SeqHandler;
use crate::routes::indexes::search::search_kind;
use crate::search::{
add_search_rules, perform_search, RetrieveVectors, SearchQueryWithIndex, SearchResultWithIndex,
add_search_rules, perform_search, SearchQueryWithIndex, SearchResultWithIndex,
};
use crate::search_queue::SearchQueue;
@ -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
@ -83,14 +83,11 @@ pub async fn multi_search_with_post(
let search_kind = search_kind(&query, index_scheduler.get_ref(), &index, features)
.with_index(query_index)?;
let retrieve_vector =
RetrieveVectors::new(query.retrieve_vectors, features).with_index(query_index)?;
let search_result = tokio::task::spawn_blocking(move || {
perform_search(&index, query, search_kind, retrieve_vector)
})
.await
.with_index(query_index)?;
let search_result =
tokio::task::spawn_blocking(move || perform_search(&index, query, search_kind))
.await
.with_index(query_index)?;
search_results.push(SearchResultWithIndex {
index_uid: index_uid.into_inner(),

View File

@ -11,11 +11,10 @@ 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};
use meilisearch_types::milli::vector::parsed_vectors::ExplicitVectors;
use meilisearch_types::milli::vector::Embedder;
use meilisearch_types::milli::{FacetValueHit, OrderBy, SearchForFacetValues, TimeBudget};
use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
@ -60,8 +59,6 @@ pub struct SearchQuery {
pub hits_per_page: Option<usize>,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToRetrieve>)]
pub attributes_to_retrieve: Option<BTreeSet<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchRetrieveVectors>)]
pub retrieve_vectors: bool,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToCrop>)]
pub attributes_to_crop: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchCropLength>, default = DEFAULT_CROP_LENGTH())]
@ -78,8 +75,6 @@ pub struct SearchQuery {
pub filter: Option<Value>,
#[deserr(default, error = DeserrJsonError<InvalidSearchSort>)]
pub sort: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchDistinct>)]
pub distinct: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSearchFacets>)]
pub facets: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchHighlightPreTag>, default = DEFAULT_HIGHLIGHT_PRE_TAG())]
@ -92,44 +87,6 @@ pub struct SearchQuery {
pub matching_strategy: MatchingStrategy,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
pub attributes_to_search_on: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
pub ranking_score_threshold: Option<RankingScoreThreshold>,
}
#[derive(Debug, Clone, Copy, PartialEq, Deserr)]
#[deserr(try_from(f64) = TryFrom::try_from -> InvalidSearchRankingScoreThreshold)]
pub struct RankingScoreThreshold(f64);
impl std::convert::TryFrom<f64> for RankingScoreThreshold {
type Error = InvalidSearchRankingScoreThreshold;
fn try_from(f: f64) -> Result<Self, Self::Error> {
// the suggested "fix" is: `!(0.0..=1.0).contains(&f)`` which is allegedly less readable
#[allow(clippy::manual_range_contains)]
if f > 1.0 || f < 0.0 {
Err(InvalidSearchRankingScoreThreshold)
} else {
Ok(RankingScoreThreshold(f))
}
}
}
#[derive(Debug, Clone, Copy, PartialEq, Deserr)]
#[deserr(try_from(f64) = TryFrom::try_from -> InvalidSimilarRankingScoreThreshold)]
pub struct RankingScoreThresholdSimilar(f64);
impl std::convert::TryFrom<f64> for RankingScoreThresholdSimilar {
type Error = InvalidSimilarRankingScoreThreshold;
fn try_from(f: f64) -> Result<Self, Self::Error> {
// the suggested "fix" is: `!(0.0..=1.0).contains(&f)`` which is allegedly less readable
#[allow(clippy::manual_range_contains)]
if f > 1.0 || f < 0.0 {
Err(InvalidSimilarRankingScoreThreshold)
} else {
Ok(Self(f))
}
}
}
// Since this structure is logged A LOT we're going to reduce the number of things it logs to the bare minimum.
@ -146,7 +103,6 @@ impl fmt::Debug for SearchQuery {
page,
hits_per_page,
attributes_to_retrieve,
retrieve_vectors,
attributes_to_crop,
crop_length,
attributes_to_highlight,
@ -155,14 +111,12 @@ impl fmt::Debug for SearchQuery {
show_ranking_score_details,
filter,
sort,
distinct,
facets,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
matching_strategy,
attributes_to_search_on,
ranking_score_threshold,
} = self;
let mut debug = f.debug_struct("SearchQuery");
@ -180,9 +134,6 @@ impl fmt::Debug for SearchQuery {
if let Some(q) = q {
debug.field("q", &q);
}
if *retrieve_vectors {
debug.field("retrieve_vectors", &retrieve_vectors);
}
if let Some(v) = vector {
if v.len() < 10 {
debug.field("vector", &v);
@ -205,9 +156,6 @@ impl fmt::Debug for SearchQuery {
if let Some(sort) = sort {
debug.field("sort", &sort);
}
if let Some(distinct) = distinct {
debug.field("distinct", &distinct);
}
if let Some(facets) = facets {
debug.field("facets", &facets);
}
@ -240,9 +188,6 @@ impl fmt::Debug for SearchQuery {
debug.field("highlight_pre_tag", &highlight_pre_tag);
debug.field("highlight_post_tag", &highlight_post_tag);
debug.field("crop_marker", &crop_marker);
if let Some(ranking_score_threshold) = ranking_score_threshold {
debug.field("ranking_score_threshold", &ranking_score_threshold);
}
debug.finish()
}
@ -286,7 +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>,
@ -383,8 +328,6 @@ pub struct SearchQueryWithIndex {
pub hits_per_page: Option<usize>,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToRetrieve>)]
pub attributes_to_retrieve: Option<BTreeSet<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchRetrieveVectors>)]
pub retrieve_vectors: bool,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToCrop>)]
pub attributes_to_crop: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchCropLength>, default = DEFAULT_CROP_LENGTH())]
@ -401,8 +344,6 @@ pub struct SearchQueryWithIndex {
pub filter: Option<Value>,
#[deserr(default, error = DeserrJsonError<InvalidSearchSort>)]
pub sort: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchDistinct>)]
pub distinct: Option<String>,
#[deserr(default, error = DeserrJsonError<InvalidSearchFacets>)]
pub facets: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchHighlightPreTag>, default = DEFAULT_HIGHLIGHT_PRE_TAG())]
@ -415,8 +356,6 @@ pub struct SearchQueryWithIndex {
pub matching_strategy: MatchingStrategy,
#[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToSearchOn>, default)]
pub attributes_to_search_on: Option<Vec<String>>,
#[deserr(default, error = DeserrJsonError<InvalidSearchRankingScoreThreshold>, default)]
pub ranking_score_threshold: Option<RankingScoreThreshold>,
}
impl SearchQueryWithIndex {
@ -430,7 +369,6 @@ impl SearchQueryWithIndex {
page,
hits_per_page,
attributes_to_retrieve,
retrieve_vectors,
attributes_to_crop,
crop_length,
attributes_to_highlight,
@ -439,7 +377,6 @@ impl SearchQueryWithIndex {
show_matches_position,
filter,
sort,
distinct,
facets,
highlight_pre_tag,
highlight_post_tag,
@ -447,7 +384,6 @@ impl SearchQueryWithIndex {
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
} = self;
(
index_uid,
@ -459,7 +395,6 @@ impl SearchQueryWithIndex {
page,
hits_per_page,
attributes_to_retrieve,
retrieve_vectors,
attributes_to_crop,
crop_length,
attributes_to_highlight,
@ -468,7 +403,6 @@ impl SearchQueryWithIndex {
show_matches_position,
filter,
sort,
distinct,
facets,
highlight_pre_tag,
highlight_post_tag,
@ -476,7 +410,6 @@ impl SearchQueryWithIndex {
matching_strategy,
attributes_to_search_on,
hybrid,
ranking_score_threshold,
// do not use ..Default::default() here,
// rather add any missing field from `SearchQuery` to `SearchQueryWithIndex`
},
@ -484,63 +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<InvalidSimilarRetrieveVectors>)]
pub retrieve_vectors: bool,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScore>, default)]
pub show_ranking_score: bool,
#[deserr(default, error = DeserrJsonError<InvalidSimilarShowRankingScoreDetails>, default)]
pub show_ranking_score_details: bool,
#[deserr(default, error = DeserrJsonError<InvalidSimilarRankingScoreThreshold>, default)]
pub ranking_score_threshold: Option<RankingScoreThresholdSimilar>,
}
#[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 {
@ -548,8 +424,6 @@ pub enum MatchingStrategy {
Last,
/// All query words are mandatory
All,
/// Remove query words from the most frequent to the least
Frequency,
}
impl Default for MatchingStrategy {
@ -563,7 +437,6 @@ impl From<MatchingStrategy> for TermsMatchingStrategy {
match other {
MatchingStrategy::Last => Self::Last,
MatchingStrategy::All => Self::All,
MatchingStrategy::Frequency => Self::Frequency,
}
}
}
@ -665,16 +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 {
@ -707,8 +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)) => {
@ -735,13 +598,6 @@ fn prepare_search<'t>(
) -> Result<(milli::Search<'t>, bool, usize, usize), MeilisearchHttpError> {
let mut search = index.search(rtxn);
search.time_budget(time_budget);
if let Some(ranking_score_threshold) = query.ranking_score_threshold {
search.ranking_score_threshold(ranking_score_threshold.0);
}
if let Some(distinct) = &query.distinct {
search.distinct(distinct.clone());
}
match search_kind {
SearchKind::KeywordOnly => {
@ -752,15 +608,10 @@ fn prepare_search<'t>(
SearchKind::SemanticOnly { embedder_name, embedder } => {
let vector = match query.vector.clone() {
Some(vector) => vector,
None => {
let span = tracing::trace_span!(target: "search::vector", "embed_one");
let _entered = span.enter();
embedder
.embed_one(query.q.clone().unwrap())
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?
}
None => embedder
.embed_one(query.q.clone().unwrap())
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?,
};
search.semantic(embedder_name.clone(), embedder.clone(), Some(vector));
@ -788,16 +639,11 @@ fn prepare_search<'t>(
.unwrap_or(DEFAULT_PAGINATION_MAX_TOTAL_HITS);
search.exhaustive_number_hits(is_finite_pagination);
search.scoring_strategy(
if query.show_ranking_score
|| query.show_ranking_score_details
|| query.ranking_score_threshold.is_some()
{
ScoringStrategy::Detailed
} else {
ScoringStrategy::Skip
},
);
search.scoring_strategy(if query.show_ranking_score || query.show_ranking_score_details {
ScoringStrategy::Detailed
} else {
ScoringStrategy::Skip
});
// compute the offset on the limit depending on the pagination mode.
let (offset, limit) = if is_finite_pagination {
@ -842,7 +688,6 @@ pub fn perform_search(
index: &Index,
query: SearchQuery,
search_kind: SearchKind,
retrieve_vectors: RetrieveVectors,
) -> Result<SearchResult, MeilisearchHttpError> {
let before_search = Instant::now();
let rtxn = index.read_txn()?;
@ -874,57 +719,131 @@ pub fn perform_search(
SearchKind::Hybrid { semantic_ratio, .. } => search.execute_hybrid(*semantic_ratio)?,
};
let SearchQuery {
q,
limit,
page,
hits_per_page,
attributes_to_retrieve,
// use the enum passed as parameter
retrieve_vectors: _,
attributes_to_crop,
crop_length,
attributes_to_highlight,
show_matches_position,
show_ranking_score,
show_ranking_score_details,
sort,
facets,
highlight_pre_tag,
highlight_post_tag,
crop_marker,
// already used in prepare_search
vector: _,
hybrid: _,
offset: _,
ranking_score_threshold: _,
matching_strategy: _,
attributes_to_search_on: _,
filter: _,
distinct: _,
} = query;
let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
let format = AttributesFormat {
attributes_to_retrieve,
retrieve_vectors,
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)
@ -932,15 +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);
@ -977,7 +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,
@ -988,214 +907,6 @@ pub fn perform_search(
Ok(result)
}
struct AttributesFormat {
attributes_to_retrieve: Option<BTreeSet<String>>,
retrieve_vectors: RetrieveVectors,
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,
}
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum RetrieveVectors {
/// Do not touch the `_vectors` field
///
/// this is the behavior when the vectorStore feature is disabled
Ignore,
/// Remove the `_vectors` field
///
/// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `false`
Hide,
/// Retrieve vectors from the DB and merge them into the `_vectors` field
///
/// this is the behavior when the vectorStore feature is enabled, and `retrieveVectors` is `true`
Retrieve,
}
impl RetrieveVectors {
pub fn new(
retrieve_vector: bool,
features: index_scheduler::RoFeatures,
) -> Result<Self, index_scheduler::Error> {
match (retrieve_vector, features.check_vector("Passing `retrieveVectors` as a parameter")) {
(true, Ok(())) => Ok(Self::Retrieve),
(true, Err(error)) => Err(error),
(false, Ok(())) => Ok(Self::Hide),
(false, Err(_)) => Ok(Self::Ignore),
}
}
}
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<_>>());
let vectors_fid = fields_ids_map.id(milli::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME);
let vectors_is_hidden = match (&displayed_ids, vectors_fid) {
// displayed_ids is a wildcard, so `_vectors` can be displayed regardless of its fid
(None, _) => false,
// displayed_ids is a finite list, and `_vectors` cannot be part of it because it is not an existing field
(Some(_), None) => true,
// displayed_ids is a finit list, so hide if `_vectors` is not part of it
(Some(map), Some(vectors_fid)) => map.contains(&vectors_fid),
};
let retrieve_vectors = if let RetrieveVectors::Retrieve = format.retrieve_vectors {
if vectors_is_hidden {
RetrieveVectors::Hide
} else {
RetrieveVectors::Retrieve
}
} else {
format.retrieve_vectors
};
let displayed_ids =
displayed_ids.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 embedding_configs = index.embedding_configs(rtxn)?;
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)?;
let add_vectors_fid =
vectors_fid.filter(|_fid| retrieve_vectors == RetrieveVectors::Retrieve);
// select the attributes to retrieve
let attributes_to_retrieve = to_retrieve_ids
.iter()
// skip the vectors_fid if RetrieveVectors::Hide
.filter(|fid| match vectors_fid {
Some(vectors_fid) => {
!(retrieve_vectors == RetrieveVectors::Hide && **fid == vectors_fid)
}
None => true,
})
// need to retrieve the existing `_vectors` field if the `RetrieveVectors::Retrieve`
.chain(add_vectors_fid.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);
if retrieve_vectors == RetrieveVectors::Retrieve {
let mut vectors = match document.remove("_vectors") {
Some(Value::Object(map)) => map,
_ => Default::default(),
};
for (name, vector) in index.embeddings(rtxn, id)? {
let user_provided = embedding_configs
.iter()
.find(|conf| conf.name == name)
.is_some_and(|conf| conf.user_provided.contains(id));
let embeddings =
ExplicitVectors { embeddings: Some(vector.into()), regenerate: !user_provided };
vectors.insert(name, serde_json::to_value(embeddings)?);
}
document.insert("_vectors".into(), vectors.into());
}
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,
@ -1230,103 +941,6 @@ pub fn perform_facet_search(
})
}
pub fn perform_similar(
index: &Index,
query: SimilarQuery,
embedder_name: String,
embedder: Arc<Embedder>,
retrieve_vectors: RetrieveVectors,
) -> Result<SimilarResult, ResponseError> {
let before_search = Instant::now();
let rtxn = index.read_txn()?;
let SimilarQuery {
id,
offset,
limit,
filter: _,
embedder: _,
attributes_to_retrieve,
retrieve_vectors: _,
show_ranking_score,
show_ranking_score_details,
ranking_score_threshold,
} = 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);
}
}
if let Some(ranking_score_threshold) = ranking_score_threshold {
similar.ranking_score_threshold(ranking_score_threshold.0);
}
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,
retrieve_vectors,
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 =
@ -1336,23 +950,13 @@ fn insert_geo_distance(sorts: &[String], document: &mut Document) {
// TODO: TAMO: milli encountered an internal error, what do we want to do?
let base = [capture_group[1].parse().unwrap(), capture_group[2].parse().unwrap()];
let geo_point = &document.get("_geo").unwrap_or(&json!(null));
if let Some((lat, lng)) =
extract_geo_value(&geo_point["lat"]).zip(extract_geo_value(&geo_point["lng"]))
{
if let Some((lat, lng)) = geo_point["lat"].as_f64().zip(geo_point["lng"].as_f64()) {
let distance = milli::distance_between_two_points(&base, &[lat, lng]);
document.insert("_geoDistance".to_string(), json!(distance.round() as usize));
}
}
}
fn extract_geo_value(value: &Value) -> Option<f64> {
match value {
Value::Number(n) => n.as_f64(),
Value::String(s) => s.parse().ok(),
_ => None,
}
}
fn compute_formatted_options(
attr_to_highlight: &HashSet<String>,
attr_to_crop: &[String],
@ -1726,54 +1330,4 @@ mod test {
insert_geo_distance(sorters, &mut document);
assert_eq!(document.get("_geoDistance"), None);
}
#[test]
fn test_insert_geo_distance_with_coords_as_string() {
let value: Document = serde_json::from_str(
r#"{
"_geo": {
"lat": "50",
"lng": 3
}
}"#,
)
.unwrap();
let sorters = &["_geoPoint(50,3):desc".to_string()];
let mut document = value.clone();
insert_geo_distance(sorters, &mut document);
assert_eq!(document.get("_geoDistance"), Some(&json!(0)));
let value: Document = serde_json::from_str(
r#"{
"_geo": {
"lat": "50",
"lng": "3"
},
"id": "1"
}"#,
)
.unwrap();
let sorters = &["_geoPoint(50,3):desc".to_string()];
let mut document = value.clone();
insert_geo_distance(sorters, &mut document);
assert_eq!(document.get("_geoDistance"), Some(&json!(0)));
let value: Document = serde_json::from_str(
r#"{
"_geo": {
"lat": 50,
"lng": "3"
},
"id": "1"
}"#,
)
.unwrap();
let sorters = &["_geoPoint(50,3):desc".to_string()];
let mut document = value.clone();
insert_geo_distance(sorters, &mut document);
assert_eq!(document.get("_geoDistance"), Some(&json!(0)));
}
}

View File

@ -86,13 +86,8 @@ 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

View File

@ -78,7 +78,7 @@ pub static ALL_ACTIONS: Lazy<HashSet<&'static str>> = Lazy::new(|| {
});
static INVALID_RESPONSE: Lazy<Value> = Lazy::new(|| {
json!({"message": null,
json!({"message": "The provided API key is invalid.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
@ -119,8 +119,7 @@ async fn error_access_expired_key() {
thread::sleep(time::Duration::new(1, 0));
for (method, route) in AUTHORIZATIONS.keys() {
let (mut response, code) = server.dummy_request(method, route).await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request(method, route).await;
assert_eq!(response, INVALID_RESPONSE.clone(), "on route: {:?} - {:?}", method, route);
assert_eq!(403, code, "{:?}", &response);
@ -150,8 +149,7 @@ async fn error_access_unauthorized_index() {
// filter `products` index routes
.filter(|(_, route)| route.starts_with("/indexes/products"))
{
let (mut response, code) = server.dummy_request(method, route).await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request(method, route).await;
assert_eq!(response, INVALID_RESPONSE.clone(), "on route: {:?} - {:?}", method, route);
assert_eq!(403, code, "{:?}", &response);
@ -178,8 +176,7 @@ async fn error_access_unauthorized_action() {
let key = response["key"].as_str().unwrap();
server.use_api_key(key);
let (mut response, code) = server.dummy_request(method, route).await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request(method, route).await;
assert_eq!(response, INVALID_RESPONSE.clone(), "on route: {:?} - {:?}", method, route);
assert_eq!(403, code, "{:?}", &response);
@ -283,7 +280,7 @@ async fn access_authorized_no_index_restriction() {
route,
action
);
assert_ne!(code, 403, "on route: {:?} - {:?} with action: {:?}", method, route, action);
assert_ne!(code, 403);
}
}
}

View File

@ -1,10 +1,7 @@
use actix_web::test;
use http::StatusCode;
use jsonwebtoken::{EncodingKey, Header};
use meili_snap::*;
use uuid::Uuid;
use crate::common::{Server, Value};
use crate::common::Server;
use crate::json;
#[actix_rt::test]
@ -439,262 +436,3 @@ async fn patch_api_keys_unknown_field() {
}
"###);
}
async fn send_request_with_custom_auth(
app: impl actix_web::dev::Service<
actix_http::Request,
Response = actix_web::dev::ServiceResponse<impl actix_web::body::MessageBody>,
Error = actix_web::Error,
>,
url: &str,
auth: &str,
) -> (Value, StatusCode) {
let req = test::TestRequest::get().uri(url).insert_header(("Authorization", auth)).to_request();
let res = test::call_service(&app, req).await;
let status_code = res.status();
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
(response, status_code)
}
#[actix_rt::test]
async fn invalid_auth_format() {
let server = Server::new_auth().await;
let app = server.init_web_app().await;
let req = test::TestRequest::get().uri("/indexes/dog/documents").to_request();
let res = test::call_service(&app, req).await;
let status_code = res.status();
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(status_code, @"401 Unauthorized");
snapshot!(response, @r###"
{
"message": "The Authorization header is missing. It must use the bearer authorization method.",
"code": "missing_authorization_header",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#missing_authorization_header"
}
"###);
let req = test::TestRequest::get().uri("/indexes/dog/documents").to_request();
let res = test::call_service(&app, req).await;
let status_code = res.status();
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(status_code, @"401 Unauthorized");
snapshot!(response, @r###"
{
"message": "The Authorization header is missing. It must use the bearer authorization method.",
"code": "missing_authorization_header",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#missing_authorization_header"
}
"###);
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/documents", "Bearer").await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The provided API key is invalid.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
}
#[actix_rt::test]
async fn invalid_api_key() {
let server = Server::new_auth().await;
let app = server.init_web_app().await;
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/search", "Bearer kefir").await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The provided API key is invalid.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
let uuid = Uuid::nil();
let key = json!({ "actions": ["search"], "indexes": ["dog"], "expiresAt": null, "uid": uuid.to_string() });
let req = test::TestRequest::post()
.uri("/keys")
.insert_header(("Authorization", "Bearer MASTER_KEY"))
.set_json(&key)
.to_request();
let res = test::call_service(&app, req).await;
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(json_string!(response, { ".createdAt" => "[date]", ".updatedAt" => "[date]" }), @r###"
{
"name": null,
"description": null,
"key": "aeb94973e0b6e912d94165430bbe87dee91a7c4f891ce19050c3910ec96977e9",
"uid": "00000000-0000-0000-0000-000000000000",
"actions": [
"search"
],
"indexes": [
"dog"
],
"expiresAt": null,
"createdAt": "[date]",
"updatedAt": "[date]"
}
"###);
let key = response["key"].as_str().unwrap();
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/doggo/search", &format!("Bearer {key}"))
.await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The API key cannot acces the index `doggo`, authorized indexes are [\"dog\"].",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
}
#[actix_rt::test]
async fn invalid_tenant_token() {
let server = Server::new_auth().await;
let app = server.init_web_app().await;
// The tenant token won't be recognized at all if we're not on a search route
let claims = json!({ "tamo": "kefir" });
let jwt = jsonwebtoken::encode(&Header::default(), &claims, &EncodingKey::from_secret(b"tamo"))
.unwrap();
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/documents", &format!("Bearer {jwt}"))
.await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The provided API key is invalid.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
let claims = json!({ "tamo": "kefir" });
let jwt = jsonwebtoken::encode(&Header::default(), &claims, &EncodingKey::from_secret(b"tamo"))
.unwrap();
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/search", &format!("Bearer {jwt}")).await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "Could not decode tenant token, JSON error: missing field `searchRules` at line 1 column 16.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
// The error messages are not ideal but that's expected since we cannot _yet_ use deserr
let claims = json!({ "searchRules": "kefir" });
let jwt = jsonwebtoken::encode(&Header::default(), &claims, &EncodingKey::from_secret(b"tamo"))
.unwrap();
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/search", &format!("Bearer {jwt}")).await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "Could not decode tenant token, JSON error: data did not match any variant of untagged enum SearchRules at line 1 column 23.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
let uuid = Uuid::nil();
let claims = json!({ "searchRules": ["kefir"], "apiKeyUid": uuid.to_string() });
let jwt = jsonwebtoken::encode(&Header::default(), &claims, &EncodingKey::from_secret(b"tamo"))
.unwrap();
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/search", &format!("Bearer {jwt}")).await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "Could not decode tenant token, InvalidSignature.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
// ~~ For the next tests we first need a valid API key
let key = json!({ "actions": ["search"], "indexes": ["dog"], "expiresAt": null, "uid": uuid.to_string() });
let req = test::TestRequest::post()
.uri("/keys")
.insert_header(("Authorization", "Bearer MASTER_KEY"))
.set_json(&key)
.to_request();
let res = test::call_service(&app, req).await;
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(json_string!(response, { ".createdAt" => "[date]", ".updatedAt" => "[date]" }), @r###"
{
"name": null,
"description": null,
"key": "aeb94973e0b6e912d94165430bbe87dee91a7c4f891ce19050c3910ec96977e9",
"uid": "00000000-0000-0000-0000-000000000000",
"actions": [
"search"
],
"indexes": [
"dog"
],
"expiresAt": null,
"createdAt": "[date]",
"updatedAt": "[date]"
}
"###);
let key = response["key"].as_str().unwrap();
let claims = json!({ "searchRules": ["doggo", "catto"], "apiKeyUid": uuid.to_string() });
let jwt = jsonwebtoken::encode(
&Header::default(),
&claims,
&EncodingKey::from_secret(key.as_bytes()),
)
.unwrap();
// Try to access an index that is not authorized by the tenant token
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/dog/search", &format!("Bearer {jwt}")).await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The provided tenant token cannot acces the index `dog`, allowed indexes are [\"catto\", \"doggo\"].",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
// Try to access an index that *is* authorized by the tenant token but not by the api key used to generate the tt
let (response, status_code) =
send_request_with_custom_auth(&app, "/indexes/doggo/search", &format!("Bearer {jwt}"))
.await;
snapshot!(status_code, @"403 Forbidden");
snapshot!(response, @r###"
{
"message": "The API key used to generate this tenant token cannot acces the index `doggo`.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
}
"###);
}

View File

@ -53,8 +53,7 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
});
static INVALID_RESPONSE: Lazy<Value> = Lazy::new(|| {
json!({
"message": null,
json!({"message": "The provided API key is invalid.",
"code": "invalid_api_key",
"type": "auth",
"link": "https://docs.meilisearch.com/errors#invalid_api_key"
@ -192,9 +191,7 @@ macro_rules! compute_forbidden_search {
server.use_api_key(&web_token);
let index = server.index("sales");
index
.search(json!({}), |mut response, code| {
// We don't assert anything on the message since it may change between cases
response["message"] = serde_json::json!(null);
.search(json!({}), |response, code| {
assert_eq!(
response,
INVALID_RESPONSE.clone(),
@ -498,8 +495,7 @@ async fn error_access_forbidden_routes() {
for ((method, route), actions) in AUTHORIZATIONS.iter() {
if !actions.contains("search") {
let (mut response, code) = server.dummy_request(method, route).await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request(method, route).await;
assert_eq!(response, INVALID_RESPONSE.clone());
assert_eq!(code, 403);
}
@ -533,16 +529,14 @@ async fn error_access_expired_parent_key() {
server.use_api_key(&web_token);
// test search request while parent_key is not expired
let (mut response, code) = server.dummy_request("POST", "/indexes/products/search").await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request("POST", "/indexes/products/search").await;
assert_ne!(response, INVALID_RESPONSE.clone());
assert_ne!(code, 403);
// wait until the key is expired.
thread::sleep(time::Duration::new(1, 0));
let (mut response, code) = server.dummy_request("POST", "/indexes/products/search").await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request("POST", "/indexes/products/search").await;
assert_eq!(response, INVALID_RESPONSE.clone());
assert_eq!(code, 403);
}
@ -591,8 +585,7 @@ async fn error_access_modified_token() {
.join(".");
server.use_api_key(&altered_token);
let (mut response, code) = server.dummy_request("POST", "/indexes/products/search").await;
response["message"] = serde_json::json!(null);
let (response, code) = server.dummy_request("POST", "/indexes/products/search").await;
assert_eq!(response, INVALID_RESPONSE.clone());
assert_eq!(code, 403);
}

View File

@ -109,11 +109,9 @@ static NESTED_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
fn invalid_response(query_index: Option<usize>) -> Value {
let message = if let Some(query_index) = query_index {
json!(format!("Inside `.queries[{query_index}]`: The provided API key is invalid."))
format!("Inside `.queries[{query_index}]`: The provided API key is invalid.")
} else {
// if it's anything else we simply return null and will tests all the
// error messages somewhere else
json!(null)
"The provided API key is invalid.".to_string()
};
json!({"message": message,
"code": "invalid_api_key",
@ -416,10 +414,7 @@ macro_rules! compute_forbidden_single_search {
for (tenant_token, failed_query_index) in $tenant_tokens.iter().zip(failed_query_indexes.into_iter()) {
let web_token = generate_tenant_token(&uid, &key, tenant_token.clone());
server.use_api_key(&web_token);
let (mut response, code) = server.multi_search(json!({"queries" : [{"indexUid": "sales"}]})).await;
if failed_query_index.is_none() && !response["message"].is_null() {
response["message"] = serde_json::json!(null);
}
let (response, code) = server.multi_search(json!({"queries" : [{"indexUid": "sales"}]})).await;
assert_eq!(
response,
invalid_response(failed_query_index),
@ -474,13 +469,10 @@ macro_rules! compute_forbidden_multiple_search {
for (tenant_token, failed_query_index) in $tenant_tokens.iter().zip(failed_query_indexes.into_iter()) {
let web_token = generate_tenant_token(&uid, &key, tenant_token.clone());
server.use_api_key(&web_token);
let (mut response, code) = server.multi_search(json!({"queries" : [
let (response, code) = server.multi_search(json!({"queries" : [
{"indexUid": "sales"},
{"indexUid": "products"},
]})).await;
if failed_query_index.is_none() && !response["message"].is_null() {
response["message"] = serde_json::json!(null);
}
assert_eq!(
response,
invalid_response(failed_query_index),
@ -1081,20 +1073,18 @@ async fn error_access_expired_parent_key() {
server.use_api_key(&web_token);
// test search request while parent_key is not expired
let (mut response, code) = server
let (response, code) = server
.multi_search(json!({"queries" : [{"indexUid": "sales"}, {"indexUid": "products"}]}))
.await;
response["message"] = serde_json::json!(null);
assert_ne!(response, invalid_response(None));
assert_ne!(code, 403);
// wait until the key is expired.
thread::sleep(time::Duration::new(1, 0));
let (mut response, code) = server
let (response, code) = server
.multi_search(json!({"queries" : [{"indexUid": "sales"}, {"indexUid": "products"}]}))
.await;
response["message"] = serde_json::json!(null);
assert_eq!(response, invalid_response(None));
assert_eq!(code, 403);
}
@ -1144,9 +1134,8 @@ async fn error_access_modified_token() {
.join(".");
server.use_api_key(&altered_token);
let (mut response, code) =
let (response, code) =
server.multi_search(json!({"queries" : [{"indexUid": "products"}]})).await;
response["message"] = serde_json::json!(null);
assert_eq!(response, invalid_response(None));
assert_eq!(code, 403);
}

View File

@ -182,10 +182,14 @@ impl Index<'_> {
self.service.get(url).await
}
pub async fn get_document(&self, id: u64, options: Option<Value>) -> (Value, StatusCode) {
pub async fn get_document(
&self,
id: u64,
options: Option<GetDocumentOptions>,
) -> (Value, StatusCode) {
let mut url = format!("/indexes/{}/documents/{}", urlencode(self.uid.as_ref()), id);
if let Some(options) = options {
write!(url, "{}", yaup::to_string(&options).unwrap()).unwrap();
if let Some(fields) = options.and_then(|o| o.fields) {
let _ = write!(url, "?fields={}", fields.join(","));
}
self.service.get(url).await
}
@ -201,11 +205,18 @@ impl Index<'_> {
}
pub async fn get_all_documents(&self, options: GetAllDocumentsOptions) -> (Value, StatusCode) {
let url = format!(
"/indexes/{}/documents{}",
urlencode(self.uid.as_ref()),
yaup::to_string(&options).unwrap()
);
let mut url = format!("/indexes/{}/documents?", urlencode(self.uid.as_ref()));
if let Some(limit) = options.limit {
let _ = write!(url, "limit={}&", limit);
}
if let Some(offset) = options.offset {
let _ = write!(url, "offset={}&", offset);
}
if let Some(attributes_to_retrieve) = options.attributes_to_retrieve {
let _ = write!(url, "fields={}&", attributes_to_retrieve.join(","));
}
self.service.get(url).await
}
@ -365,44 +376,7 @@ impl Index<'_> {
}
pub async fn search_get(&self, query: &str) -> (Value, StatusCode) {
let url = format!("/indexes/{}/search{}", urlencode(self.uid.as_ref()), query);
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);
let url = format!("/indexes/{}/search?{}", urlencode(self.uid.as_ref()), query);
self.service.get(url).await
}
@ -424,14 +398,13 @@ impl Index<'_> {
}
}
#[derive(Debug, Default, serde::Serialize)]
#[serde(rename_all = "camelCase")]
pub struct GetAllDocumentsOptions {
#[serde(skip_serializing_if = "Option::is_none")]
pub limit: Option<usize>,
#[serde(skip_serializing_if = "Option::is_none")]
pub offset: Option<usize>,
#[serde(skip_serializing_if = "Option::is_none")]
pub struct GetDocumentOptions {
pub fields: Option<Vec<&'static str>>,
pub retrieve_vectors: bool,
}
#[derive(Debug, Default)]
pub struct GetAllDocumentsOptions {
pub limit: Option<usize>,
pub offset: Option<usize>,
pub attributes_to_retrieve: Option<Vec<&'static str>>,
}

View File

@ -6,7 +6,7 @@ pub mod service;
use std::fmt::{self, Display};
#[allow(unused)]
pub use index::GetAllDocumentsOptions;
pub use index::{GetAllDocumentsOptions, GetDocumentOptions};
use meili_snap::json_string;
use serde::{Deserialize, Serialize};
#[allow(unused)]
@ -42,12 +42,6 @@ impl std::ops::Deref for Value {
}
}
impl std::ops::DerefMut for Value {
fn deref_mut(&mut self) -> &mut Self::Target {
&mut self.0
}
}
impl PartialEq<serde_json::Value> for Value {
fn eq(&self, other: &serde_json::Value) -> bool {
&self.0 == other
@ -71,7 +65,7 @@ impl Display for Value {
write!(
f,
"{}",
json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]", ".processingTimeMs" => "[duration]" })
json_string!(self, { ".enqueuedAt" => "[date]", ".startedAt" => "[date]", ".finishedAt" => "[date]", ".duration" => "[duration]" })
)
}
}

View File

@ -183,58 +183,6 @@ async fn add_single_document_gzip_encoded() {
}
"###);
}
#[actix_rt::test]
async fn add_single_document_gzip_encoded_with_incomplete_error() {
let document = json!("kefir");
// this is a what is expected and should work
let server = Server::new().await;
let app = server.init_web_app().await;
// post
let document = serde_json::to_string(&document).unwrap();
let req = test::TestRequest::post()
.uri("/indexes/dog/documents")
.set_payload(document.to_string())
.insert_header(("content-type", "application/json"))
.insert_header(("content-encoding", "gzip"))
.to_request();
let res = test::call_service(&app, req).await;
let status_code = res.status();
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(status_code, @"400 Bad Request");
snapshot!(json_string!(response),
@r###"
{
"message": "The provided payload is incomplete and cannot be parsed",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
}
"###);
// put
let req = test::TestRequest::put()
.uri("/indexes/dog/documents")
.set_payload(document.to_string())
.insert_header(("content-type", "application/json"))
.insert_header(("content-encoding", "gzip"))
.to_request();
let res = test::call_service(&app, req).await;
let status_code = res.status();
let body = test::read_body(res).await;
let response: Value = serde_json::from_slice(&body).unwrap_or_default();
snapshot!(status_code, @"400 Bad Request");
snapshot!(json_string!(response),
@r###"
{
"message": "The provided payload is incomplete and cannot be parsed",
"code": "bad_request",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#bad_request"
}
"###);
}
/// Here we try document request with every encoding
#[actix_rt::test]
@ -1092,52 +1040,6 @@ async fn document_addition_with_primary_key() {
"###);
}
#[actix_rt::test]
async fn document_addition_with_huge_int_primary_key() {
let server = Server::new().await;
let index = server.index("test");
let documents = json!([
{
"primary": 14630868576586246730u64,
"content": "foo",
}
]);
let (response, code) = index.add_documents(documents, Some("primary")).await;
snapshot!(code, @"202 Accepted");
let response = index.wait_task(response.uid()).await;
snapshot!(response,
@r###"
{
"uid": 0,
"indexUid": "test",
"status": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 1,
"indexedDocuments": 1
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}
"###);
let (response, code) = index.get_document(14630868576586246730u64, None).await;
snapshot!(code, @"200 OK");
snapshot!(json_string!(response),
@r###"
{
"primary": 14630868576586246730,
"content": "foo"
}
"###);
}
#[actix_rt::test]
async fn replace_document() {
let server = Server::new().await;

View File

@ -719,7 +719,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!(null)).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type: expected an object, but found null",
"code": "bad_request",
@ -730,7 +730,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!({ "offset": "doggo" })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.offset`: expected a positive integer, but found a string: `\"doggo\"`",
"code": "invalid_document_offset",
@ -741,7 +741,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!({ "limit": "doggo" })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.limit`: expected a positive integer, but found a string: `\"doggo\"`",
"code": "invalid_document_limit",
@ -752,7 +752,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!({ "fields": "doggo" })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.fields`: expected an array, but found a string: `\"doggo\"`",
"code": "invalid_document_fields",
@ -763,7 +763,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!({ "filter": true })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Invalid syntax for the filter parameter: `expected String, Array, found: true`.",
"code": "invalid_document_filter",
@ -774,7 +774,7 @@ async fn fetch_document_by_filter() {
let (response, code) = index.get_document_by_filter(json!({ "filter": "cool doggo" })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"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 `cool doggo`.\n1:11 cool doggo",
"code": "invalid_document_filter",
@ -786,7 +786,7 @@ async fn fetch_document_by_filter() {
let (response, code) =
index.get_document_by_filter(json!({ "filter": "doggo = bernese" })).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
snapshot!(json_string!(response), @r###"
{
"message": "Attribute `doggo` is not filterable. Available filterable attributes are: `color`.\n1:6 doggo = bernese",
"code": "invalid_document_filter",
@ -795,70 +795,3 @@ async fn fetch_document_by_filter() {
}
"###);
}
#[actix_rt::test]
async fn retrieve_vectors() {
let server = Server::new().await;
let index = server.index("doggo");
// GET ALL DOCUMENTS BY QUERY
let (response, _code) = index.get_all_documents_raw("?retrieveVectors=tamo").await;
snapshot!(response, @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `tamo` as a boolean, expected either `true` or `false`",
"code": "invalid_document_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_all_documents_raw("?retrieveVectors=true").await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter 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"
}
"###);
// FETCH ALL DOCUMENTS BY POST
let (response, _code) =
index.get_document_by_filter(json!({ "retrieveVectors": "tamo" })).await;
snapshot!(response, @r###"
{
"message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"tamo\"`",
"code": "invalid_document_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_document_by_filter(json!({ "retrieveVectors": true })).await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter 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"
}
"###);
// GET A SINGLE DOCUMENT
let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": "tamo"}))).await;
snapshot!(response, @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `tamo` as a boolean, expected either `true` or `false`",
"code": "invalid_document_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_document_retrieve_vectors"
}
"###);
let (response, _code) = index.get_document(0, Some(json!({"retrieveVectors": true}))).await;
snapshot!(response, @r###"
{
"message": "Passing `retrieveVectors` as a parameter 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"
}
"###);
}

View File

@ -4,7 +4,7 @@ use meili_snap::*;
use urlencoding::encode as urlencode;
use crate::common::encoder::Encoder;
use crate::common::{GetAllDocumentsOptions, Server, Value};
use crate::common::{GetAllDocumentsOptions, GetDocumentOptions, Server, Value};
use crate::json;
// TODO: partial test since we are testing error, amd error is not yet fully implemented in
@ -59,7 +59,8 @@ async fn get_document() {
})
);
let (response, code) = index.get_document(0, Some(json!({ "fields": ["id"] }))).await;
let (response, code) =
index.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["id"]) })).await;
assert_eq!(code, 200);
assert_eq!(
response,
@ -68,8 +69,9 @@ async fn get_document() {
})
);
let (response, code) =
index.get_document(0, Some(json!({ "fields": ["nested.content"] }))).await;
let (response, code) = index
.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["nested.content"]) }))
.await;
assert_eq!(code, 200);
assert_eq!(
response,
@ -209,7 +211,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions {
fields: Some(vec!["name"]),
attributes_to_retrieve: Some(vec!["name"]),
..Default::default()
})
.await;
@ -223,19 +225,9 @@ async fn test_get_all_documents_attributes_to_retrieve() {
assert_eq!(response["limit"], json!(20));
assert_eq!(response["total"], json!(77));
let (response, code) = index.get_all_documents_raw("?fields=").await;
assert_eq!(code, 200);
assert_eq!(response["results"].as_array().unwrap().len(), 20);
for results in response["results"].as_array().unwrap() {
assert_eq!(results.as_object().unwrap().keys().count(), 0);
}
assert_eq!(response["offset"], json!(0));
assert_eq!(response["limit"], json!(20));
assert_eq!(response["total"], json!(77));
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions {
fields: Some(vec!["wrong"]),
attributes_to_retrieve: Some(vec![]),
..Default::default()
})
.await;
@ -250,7 +242,22 @@ async fn test_get_all_documents_attributes_to_retrieve() {
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions {
fields: Some(vec!["name", "tags"]),
attributes_to_retrieve: Some(vec!["wrong"]),
..Default::default()
})
.await;
assert_eq!(code, 200);
assert_eq!(response["results"].as_array().unwrap().len(), 20);
for results in response["results"].as_array().unwrap() {
assert_eq!(results.as_object().unwrap().keys().count(), 0);
}
assert_eq!(response["offset"], json!(0));
assert_eq!(response["limit"], json!(20));
assert_eq!(response["total"], json!(77));
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions {
attributes_to_retrieve: Some(vec!["name", "tags"]),
..Default::default()
})
.await;
@ -263,7 +270,10 @@ async fn test_get_all_documents_attributes_to_retrieve() {
}
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions { fields: Some(vec!["*"]), ..Default::default() })
.get_all_documents(GetAllDocumentsOptions {
attributes_to_retrieve: Some(vec!["*"]),
..Default::default()
})
.await;
assert_eq!(code, 200);
assert_eq!(response["results"].as_array().unwrap().len(), 20);
@ -273,7 +283,7 @@ async fn test_get_all_documents_attributes_to_retrieve() {
let (response, code) = index
.get_all_documents(GetAllDocumentsOptions {
fields: Some(vec!["*", "wrong"]),
attributes_to_retrieve: Some(vec!["*", "wrong"]),
..Default::default()
})
.await;
@ -306,10 +316,12 @@ async fn get_document_s_nested_attributes_to_retrieve() {
assert_eq!(code, 202);
index.wait_task(1).await;
let (response, code) = index.get_document(0, Some(json!({ "fields": ["content"] }))).await;
let (response, code) =
index.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
assert_eq!(code, 200);
assert_eq!(response, json!({}));
let (response, code) = index.get_document(1, Some(json!({ "fields": ["content"] }))).await;
let (response, code) =
index.get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content"]) })).await;
assert_eq!(code, 200);
assert_eq!(
response,
@ -321,7 +333,9 @@ async fn get_document_s_nested_attributes_to_retrieve() {
})
);
let (response, code) = index.get_document(0, Some(json!({ "fields": ["content.truc"] }))).await;
let (response, code) = index
.get_document(0, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
.await;
assert_eq!(code, 200);
assert_eq!(
response,
@ -329,7 +343,9 @@ async fn get_document_s_nested_attributes_to_retrieve() {
"content.truc": "foobar",
})
);
let (response, code) = index.get_document(1, Some(json!({ "fields": ["content.truc"] }))).await;
let (response, code) = index
.get_document(1, Some(GetDocumentOptions { fields: Some(vec!["content.truc"]) }))
.await;
assert_eq!(code, 200);
assert_eq!(
response,
@ -524,207 +540,3 @@ async fn get_document_by_filter() {
}
"###);
}
#[actix_rt::test]
async fn get_document_with_vectors() {
let server = Server::new().await;
let index = server.index("doggo");
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,
}
},
}))
.await;
snapshot!(code, @"202 Accepted");
server.wait_task(response.uid()).await;
let documents = json!([
{"id": 0, "name": "kefir", "_vectors": { "manual": [0, 0, 0] }},
{"id": 1, "name": "echo", "_vectors": { "manual": null }},
]);
let (value, code) = index.add_documents(documents, None).await;
snapshot!(code, @"202 Accepted");
index.wait_task(value.uid()).await;
// by default you shouldn't see the `_vectors` object
let (documents, _code) = index.get_all_documents(Default::default()).await;
snapshot!(json_string!(documents), @r###"
{
"results": [
{
"id": 0,
"name": "kefir"
},
{
"id": 1,
"name": "echo"
}
],
"offset": 0,
"limit": 20,
"total": 2
}
"###);
let (documents, _code) = index.get_document(0, None).await;
snapshot!(json_string!(documents), @r###"
{
"id": 0,
"name": "kefir"
}
"###);
// if we try to retrieve the vectors with the `fields` parameter they
// still shouldn't be displayed
let (documents, _code) = index
.get_all_documents(GetAllDocumentsOptions {
fields: Some(vec!["name", "_vectors"]),
..Default::default()
})
.await;
snapshot!(json_string!(documents), @r###"
{
"results": [
{
"name": "kefir"
},
{
"name": "echo"
}
],
"offset": 0,
"limit": 20,
"total": 2
}
"###);
let (documents, _code) =
index.get_document(0, Some(json!({"fields": ["name", "_vectors"]}))).await;
snapshot!(json_string!(documents), @r###"
{
"name": "kefir"
}
"###);
// If we specify the retrieve vectors boolean and nothing else we should get the vectors
let (documents, _code) = index
.get_all_documents(GetAllDocumentsOptions { retrieve_vectors: true, ..Default::default() })
.await;
snapshot!(json_string!(documents), @r###"
{
"results": [
{
"id": 0,
"name": "kefir",
"_vectors": {
"manual": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": false
}
}
},
{
"id": 1,
"name": "echo",
"_vectors": {}
}
],
"offset": 0,
"limit": 20,
"total": 2
}
"###);
let (documents, _code) = index.get_document(0, Some(json!({"retrieveVectors": true}))).await;
snapshot!(json_string!(documents), @r###"
{
"id": 0,
"name": "kefir",
"_vectors": {
"manual": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": false
}
}
}
"###);
// If we specify the retrieve vectors boolean and exclude vectors form the `fields` we should still get the vectors
let (documents, _code) = index
.get_all_documents(GetAllDocumentsOptions {
retrieve_vectors: true,
fields: Some(vec!["name"]),
..Default::default()
})
.await;
snapshot!(json_string!(documents), @r###"
{
"results": [
{
"name": "kefir",
"_vectors": {
"manual": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": false
}
}
},
{
"name": "echo",
"_vectors": {}
}
],
"offset": 0,
"limit": 20,
"total": 2
}
"###);
let (documents, _code) =
index.get_document(0, Some(json!({"retrieveVectors": true, "fields": ["name"]}))).await;
snapshot!(json_string!(documents), @r###"
{
"name": "kefir",
"_vectors": {
"manual": {
"embeddings": [
[
0.0,
0.0,
0.0
]
],
"regenerate": false
}
}
}
"###);
}

View File

@ -1859,7 +1859,8 @@ async fn import_dump_v6_containing_experimental_features() {
{
"vectorStore": false,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);
@ -1938,210 +1939,3 @@ async fn import_dump_v6_containing_experimental_features() {
})
.await;
}
// In this test we must generate the dump ourselves to ensure the
// `user provided` vectors are well set
#[actix_rt::test]
#[cfg_attr(target_os = "windows", ignore)]
async fn generate_and_import_dump_containing_vectors() {
let temp = tempfile::tempdir().unwrap();
let mut opt = default_settings(temp.path());
let server = Server::new_with_options(opt.clone()).await.unwrap();
let (code, _) = server.set_features(json!({"vectorStore": true})).await;
snapshot!(code, @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let index = server.index("pets");
let (response, code) = index
.update_settings(json!(
{
"embedders": {
"doggo_embedder": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.doggo}}",
}
}
}
))
.await;
snapshot!(code, @"202 Accepted");
let response = index.wait_task(response.uid()).await;
snapshot!(response);
let (response, code) = index
.add_documents(
json!([
{"id": 0, "doggo": "kefir", "_vectors": { "doggo_embedder": vec![0; 384] }},
{"id": 1, "doggo": "echo", "_vectors": { "doggo_embedder": { "regenerate": false, "embeddings": vec![1; 384] }}},
{"id": 2, "doggo": "intel", "_vectors": { "doggo_embedder": { "regenerate": true, "embeddings": vec![2; 384] }}},
{"id": 3, "doggo": "bill", "_vectors": { "doggo_embedder": { "regenerate": true }}},
{"id": 4, "doggo": "max" },
]),
None,
)
.await;
snapshot!(code, @"202 Accepted");
let response = index.wait_task(response.uid()).await;
snapshot!(response);
let (response, code) = server.create_dump().await;
snapshot!(code, @"202 Accepted");
let response = index.wait_task(response.uid()).await;
snapshot!(response["status"], @r###""succeeded""###);
// ========= We made a dump, now we should clear the DB and try to import our dump
drop(server);
tokio::fs::remove_dir_all(&opt.db_path).await.unwrap();
let dump_name = format!("{}.dump", response["details"]["dumpUid"].as_str().unwrap());
let dump_path = opt.dump_dir.join(dump_name);
assert!(dump_path.exists(), "path: `{}`", dump_path.display());
opt.import_dump = Some(dump_path);
// NOTE: We shouldn't have to change the database path but I lost one hour
// because of a « bad path » error and that fixed it.
opt.db_path = temp.path().join("data.ms");
let mut server = Server::new_auth_with_options(opt, temp).await;
server.use_api_key("MASTER_KEY");
let (indexes, code) = server.list_indexes(None, None).await;
assert_eq!(code, 200, "{indexes}");
snapshot!(indexes["results"].as_array().unwrap().len(), @"1");
snapshot!(indexes["results"][0]["uid"], @r###""pets""###);
snapshot!(indexes["results"][0]["primaryKey"], @r###""id""###);
let (response, code) = server.get_features().await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
}
"###);
let index = server.index("pets");
let (response, code) = index.settings().await;
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"displayedAttributes": [
"*"
],
"searchableAttributes": [
"*"
],
"filterableAttributes": [],
"sortableAttributes": [],
"rankingRules": [
"words",
"typo",
"proximity",
"attribute",
"sort",
"exactness"
],
"stopWords": [],
"nonSeparatorTokens": [],
"separatorTokens": [],
"dictionary": [],
"synonyms": {},
"distinctAttribute": null,
"proximityPrecision": "byWord",
"typoTolerance": {
"enabled": true,
"minWordSizeForTypos": {
"oneTypo": 5,
"twoTypos": 9
},
"disableOnWords": [],
"disableOnAttributes": []
},
"faceting": {
"maxValuesPerFacet": 100,
"sortFacetValuesBy": {
"*": "alpha"
}
},
"pagination": {
"maxTotalHits": 1000
},
"embedders": {
"doggo_embedder": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.doggo}}"
}
},
"searchCutoffMs": null
}
"###);
index
.search(json!({"retrieveVectors": true}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"], { "[]._vectors.doggo_embedder.embeddings" => "[vector]" }), @r###"
[
{
"id": 0,
"doggo": "kefir",
"_vectors": {
"doggo_embedder": {
"embeddings": "[vector]",
"regenerate": false
}
}
},
{
"id": 1,
"doggo": "echo",
"_vectors": {
"doggo_embedder": {
"embeddings": "[vector]",
"regenerate": false
}
}
},
{
"id": 2,
"doggo": "intel",
"_vectors": {
"doggo_embedder": {
"embeddings": "[vector]",
"regenerate": true
}
}
},
{
"id": 3,
"doggo": "bill",
"_vectors": {
"doggo_embedder": {
"embeddings": "[vector]",
"regenerate": true
}
}
},
{
"id": 4,
"doggo": "max",
"_vectors": {
"doggo_embedder": {
"embeddings": "[vector]",
"regenerate": true
}
}
}
]
"###);
})
.await;
}

View File

@ -1,25 +0,0 @@
---
source: meilisearch/tests/dumps/mod.rs
---
{
"uid": 0,
"indexUid": "pets",
"status": "succeeded",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"embedders": {
"doggo_embedder": {
"source": "huggingFace",
"model": "sentence-transformers/all-MiniLM-L6-v2",
"revision": "e4ce9877abf3edfe10b0d82785e83bdcb973e22e",
"documentTemplate": "{{doc.doggo}}"
}
}
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}

View File

@ -1,19 +0,0 @@
---
source: meilisearch/tests/dumps/mod.rs
---
{
"uid": 1,
"indexUid": "pets",
"status": "succeeded",
"type": "documentAdditionOrUpdate",
"canceledBy": null,
"details": {
"receivedDocuments": 5,
"indexedDocuments": 5
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}

View File

@ -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"

View File

@ -8,12 +8,10 @@ mod index;
mod logs;
mod search;
mod settings;
mod similar;
mod snapshot;
mod stats;
mod swap_indexes;
mod tasks;
mod vector;
// Tests are isolated by features in different modules to allow better readability, test
// targetability, and improved incremental compilation times.

View File

@ -107,39 +107,6 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
])
});
static NESTED_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"id": 1,
"description": "Leather Jacket",
"brand": "Lee Jeans",
"product_id": "123456",
"color": { "main": "Brown", "pattern": "stripped" },
},
{
"id": 2,
"description": "Leather Jacket",
"brand": "Lee Jeans",
"product_id": "123456",
"color": { "main": "Black", "pattern": "stripped" },
},
{
"id": 3,
"description": "Leather Jacket",
"brand": "Lee Jeans",
"product_id": "123456",
"color": { "main": "Blue", "pattern": "used" },
},
{
"id": 4,
"description": "T-Shirt",
"brand": "Nike",
"product_id": "789012",
"color": { "main": "Blue", "pattern": "stripped" },
}
])
});
static DOCUMENT_PRIMARY_KEY: &str = "id";
static DOCUMENT_DISTINCT_KEY: &str = "product_id";
@ -272,35 +239,3 @@ async fn distinct_search_with_pagination_no_ranking() {
snapshot!(response["totalPages"], @"2");
snapshot!(response["totalHits"], @"6");
}
#[actix_rt::test]
async fn distinct_at_search_time() {
let server = Server::new().await;
let index = server.index("tamo");
let documents = NESTED_DOCUMENTS.clone();
index.add_documents(documents, Some(DOCUMENT_PRIMARY_KEY)).await;
let (task, _) = index.update_settings_filterable_attributes(json!(["color.main"])).await;
let task = index.wait_task(task.uid()).await;
snapshot!(task, name: "succeed");
fn get_hits(response: &Value) -> Vec<String> {
let hits_array = response["hits"]
.as_array()
.unwrap_or_else(|| panic!("{}", &serde_json::to_string_pretty(&response).unwrap()));
hits_array
.iter()
.map(|h| h[DOCUMENT_PRIMARY_KEY].as_number().unwrap().to_string())
.collect::<Vec<_>>()
}
let (response, code) =
index.search_post(json!({"page": 1, "hitsPerPage": 3, "distinct": "color.main"})).await;
let hits = get_hits(&response);
snapshot!(code, @"200 OK");
snapshot!(hits.len(), @"3");
snapshot!(format!("{:?}", hits), @r###"["1", "2", "3"]"###);
snapshot!(response["page"], @"1");
snapshot!(response["totalPages"], @"1");
snapshot!(response["totalHits"], @"3");
}

View File

@ -71,7 +71,7 @@ async fn search_bad_offset() {
}
"###);
let (response, code) = index.search_get("?offset=doggo").await;
let (response, code) = index.search_get("offset=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -99,7 +99,7 @@ async fn search_bad_limit() {
}
"###);
let (response, code) = index.search_get("?limit=doggo").await;
let (response, code) = index.search_get("limit=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -127,7 +127,7 @@ async fn search_bad_page() {
}
"###);
let (response, code) = index.search_get("?page=doggo").await;
let (response, code) = index.search_get("page=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -155,7 +155,7 @@ async fn search_bad_hits_per_page() {
}
"###);
let (response, code) = index.search_get("?hitsPerPage=doggo").await;
let (response, code) = index.search_get("hitsPerPage=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -167,74 +167,6 @@ async fn search_bad_hits_per_page() {
"###);
}
#[actix_rt::test]
async fn search_bad_attributes_to_retrieve() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index.search_post(json!({"attributesToRetrieve": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.attributesToRetrieve`: expected an array, but found a string: `\"doggo\"`",
"code": "invalid_search_attributes_to_retrieve",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_attributes_to_retrieve"
}
"###);
// Can't make the `attributes_to_retrieve` fail with a get search since it'll accept anything as an array of strings.
}
#[actix_rt::test]
async fn search_bad_retrieve_vectors() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index.search_post(json!({"retrieveVectors": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"doggo\"`",
"code": "invalid_search_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
}
"###);
let (response, code) = index.search_post(json!({"retrieveVectors": [true]})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found an array: `[true]`",
"code": "invalid_search_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
}
"###);
let (response, code) = index.search_get("?retrieveVectors=").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `` as a boolean, expected either `true` or `false`",
"code": "invalid_search_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
}
"###);
let (response, code) = index.search_get("?retrieveVectors=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `doggo` as a boolean, expected either `true` or `false`",
"code": "invalid_search_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_retrieve_vectors"
}
"###);
}
#[actix_rt::test]
async fn search_bad_attributes_to_crop() {
let server = Server::new().await;
@ -269,7 +201,7 @@ async fn search_bad_crop_length() {
}
"###);
let (response, code) = index.search_get("?cropLength=doggo").await;
let (response, code) = index.search_get("cropLength=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -359,7 +291,7 @@ async fn search_bad_show_matches_position() {
}
"###);
let (response, code) = index.search_get("?showMatchesPosition=doggo").await;
let (response, code) = index.search_get("showMatchesPosition=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -389,40 +321,6 @@ async fn search_bad_facets() {
// Can't make the `attributes_to_highlight` fail with a get search since it'll accept anything as an array of strings.
}
#[actix_rt::test]
async fn search_bad_threshold() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index.search_post(json!({"rankingScoreThreshold": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.rankingScoreThreshold`: expected a number, but found a string: `\"doggo\"`",
"code": "invalid_search_ranking_score_threshold",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_ranking_score_threshold"
}
"###);
}
#[actix_rt::test]
async fn search_invalid_threshold() {
let server = Server::new().await;
let index = server.index("test");
let (response, code) = index.search_post(json!({"rankingScoreThreshold": 42})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value at `.rankingScoreThreshold`: the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`.",
"code": "invalid_search_ranking_score_threshold",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_ranking_score_threshold"
}
"###);
}
#[actix_rt::test]
async fn search_non_filterable_facets() {
let server = Server::new().await;
@ -442,7 +340,7 @@ async fn search_non_filterable_facets() {
}
"###);
let (response, code) = index.search_get("?facets=doggo").await;
let (response, code) = index.search_get("facets=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -472,7 +370,7 @@ async fn search_non_filterable_facets_multiple_filterable() {
}
"###);
let (response, code) = index.search_get("?facets=doggo").await;
let (response, code) = index.search_get("facets=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -502,7 +400,7 @@ async fn search_non_filterable_facets_no_filterable() {
}
"###);
let (response, code) = index.search_get("?facets=doggo").await;
let (response, code) = index.search_get("facets=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -532,7 +430,7 @@ async fn search_non_filterable_facets_multiple_facets() {
}
"###);
let (response, code) = index.search_get("?facets=doggo,neko").await;
let (response, code) = index.search_get("facets=doggo,neko").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
@ -607,7 +505,7 @@ async fn search_bad_matching_strategy() {
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`, `frequency`",
"message": "Unknown value `doggo` at `.matchingStrategy`: expected one of `last`, `all`",
"code": "invalid_search_matching_strategy",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@ -625,11 +523,11 @@ async fn search_bad_matching_strategy() {
}
"###);
let (response, code) = index.search_get("?matchingStrategy=doggo").await;
let (response, code) = index.search_get("matchingStrategy=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`, `frequency`",
"message": "Unknown value `doggo` for parameter `matchingStrategy`: expected one of `last`, `all`",
"code": "invalid_search_matching_strategy",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_matching_strategy"
@ -1140,66 +1038,3 @@ async fn search_on_unknown_field_plus_joker() {
)
.await;
}
#[actix_rt::test]
async fn distinct_at_search_time() {
let server = Server::new().await;
let index = server.index("tamo");
let (task, _) = index.create(None).await;
let task = index.wait_task(task.uid()).await;
snapshot!(task, name: "task-succeed");
let (response, code) =
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. This index does not have configured filterable attributes.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
}
"###);
let (task, _) = index.update_settings_filterable_attributes(json!(["color", "machin"])).await;
index.wait_task(task.uid()).await;
let (response, code) =
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, machin`.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
}
"###);
let (task, _) = index.update_settings_displayed_attributes(json!(["color"])).await;
index.wait_task(task.uid()).await;
let (response, code) =
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": "doggo.truc"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Attribute `doggo.truc` is not filterable and thus, cannot be used as distinct attribute. Available filterable attributes are: `color, <..hidden-attributes>`.",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
}
"###);
let (response, code) =
index.search_post(json!({"page": 0, "hitsPerPage": 2, "distinct": true})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(response, @r###"
{
"message": "Invalid value type at `.distinct`: expected a string, but found a boolean: `true`",
"code": "invalid_search_distinct",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_search_distinct"
}
"###);
}

View File

@ -150,8 +150,7 @@ async fn bug_4640() {
"_geo": {
"lat": "45.4777599",
"lng": "9.1967508"
},
"_geoDistance": 0
}
},
{
"id": 1,

View File

@ -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",
@ -98,145 +65,48 @@ 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(
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
json!({"q": "Captain", "vector": [1.0, 1.0], "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","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}}},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}}}]"###);
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]}},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]}}]"###);
snapshot!(response["semanticHitCount"], @"0");
let (response, code) = index
.search_post(
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true, "retrieveVectors": true}),
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.5}, "showRankingScore": true}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"2");
let (response, code) = index
.search_post(
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true, "retrieveVectors": true}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"3");
}
#[actix_rt::test]
async fn limit_offset() {
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let (response, code) = index
.search_post(
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true, "offset": 1, "limit": 1}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}}}]"###);
snapshot!(response["semanticHitCount"], @"0");
assert_eq!(response["hits"].as_array().unwrap().len(), 1);
let server = Server::new().await;
let index = index_with_documents_user_provided(&server, &SIMPLE_SEARCH_DOCUMENTS_VEC).await;
let (response, code) = index
.search_post(
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.9}, "retrieveVectors": true, "offset": 1, "limit": 1}),
)
.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":{"embeddings":[[1.0,2.0]],"regenerate":false}}}]"###);
snapshot!(response["semanticHitCount"], @"1");
assert_eq!(response["hits"].as_array().unwrap().len(), 1);
}
#[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["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(
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.8}, "showRankingScore": false}),
json!({"q": "Captain", "vector": [1.0, 1.0], "hybrid": {"semanticRatio": 0.8}, "showRankingScore": true}),
)
.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["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":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
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}, "retrieveVectors": true});
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;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.9472135901451112}]"###);
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":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.9472135901451112}]"###);
let (response, code) = index
.update_settings(json!({
@ -257,34 +127,31 @@ async fn distribution_shift() {
let (response, code) = index.search_post(search).await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.19161224365234375},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.1920928955078125e-7},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.1920928955078125e-7}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.19161224365234375},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.1920928955078125e-7},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.1920928955078125e-7}]"###);
}
#[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],
"hybrid": {"semanticRatio": 0.2},
"retrieveVectors": true,
"attributesToHighlight": [
"desc",
"_vectors",
"attributesToHighlight": [
"desc"
],
"highlightPreTag": "**BEGIN**",
"highlightPostTag": "**END**",
"highlightPreTag": "**BEGIN**",
"highlightPostTag": "**END**"
}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1"}},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2"}}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":["2.0","3.0"]}}},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}}},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}}}]"###);
snapshot!(response["semanticHitCount"], @"0");
let (response, code) = index
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
"hybrid": {"semanticRatio": 0.8},
"retrieveVectors": true,
"showRankingScore": true,
"attributesToHighlight": [
"desc"
@ -294,14 +161,13 @@ async fn highlighter() {
}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2"},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1"},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"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]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the **BEGIN**Marvel**END** Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a **BEGIN**Captain**END** **BEGIN**Marvel**END** ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"3");
// no highlighting on full semantic
let (response, code) = index
.search_post(json!({"q": "Captain Marvel", "vector": [1.0, 1.0],
"hybrid": {"semanticRatio": 1.0},
"retrieveVectors": true,
"showRankingScore": true,
"attributesToHighlight": [
"desc"
@ -311,14 +177,14 @@ async fn highlighter() {
}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_formatted":{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3"},"_rankingScore":0.990290343761444},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_formatted":{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2"},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_formatted":{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1"},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_formatted":{"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]},"_formatted":{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":["1.0","2.0"]}},"_rankingScore":0.974341630935669},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_formatted":{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":["1.0","3.0"]}},"_rankingScore":0.9472135901451112}]"###);
snapshot!(response["semanticHitCount"], @"3");
}
#[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(
@ -390,45 +256,45 @@ 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(
json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
json!({"vector": [1.0, 3.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
)
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"][0], @r###"{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0}"###);
snapshot!(response["hits"][0], @r###"{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0}"###);
snapshot!(response["semanticHitCount"], @"1");
}
#[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
.search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
snapshot!(response["semanticHitCount"], @"null");
// same with a different semantic ratio
let (response, code) = index
.search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"hybrid": {"semanticRatio": 0.76}, "showRankingScore": true}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
snapshot!(response["semanticHitCount"], @"null");
// wrong vector dimensions
let (response, code) = index
.search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"vector": [1.0, 0.0, 1.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
.await;
snapshot!(code, @"400 Bad Request");
@ -443,34 +309,34 @@ async fn query_combination() {
// full vector
let (response, code) = index
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.7773500680923462},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.7236068248748779},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":0.6581138968467712}]"###);
snapshot!(response["hits"], @r###"[{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":0.7773500680923462},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":0.7236068248748779},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":0.6581138968467712}]"###);
snapshot!(response["semanticHitCount"], @"3");
// full keyword, without a query
let (response, code) = index
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true}))
.await;
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":1.0}]"###);
snapshot!(response["hits"], @r###"[{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":[1.0,3.0]},"_rankingScore":1.0},{"title":"Captain Planet","desc":"He's not part of the Marvel Cinematic Universe","id":"2","_vectors":{"default":[1.0,2.0]},"_rankingScore":1.0},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":[2.0,3.0]},"_rankingScore":1.0}]"###);
snapshot!(response["semanticHitCount"], @"null");
// query + vector, full keyword => keyword
let (response, code) = index
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "hybrid": {"semanticRatio": 0.0}, "showRankingScore": true}))
.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":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Captain Marvel","desc":"a Shazam ersatz","id":"3","_vectors":{"default":{"embeddings":[[2.0,3.0]],"regenerate":false}},"_rankingScore":0.9848484848484848},{"title":"Shazam!","desc":"a Captain Marvel ersatz","id":"1","_vectors":{"default":{"embeddings":[[1.0,3.0]],"regenerate":false}},"_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 =>
let (response, code) = index
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true, "retrieveVectors": true}))
.search_post(json!({"q": "Captain", "vector": [1.0, 0.0], "showRankingScore": true}))
.await;
snapshot!(code, @"400 Bad Request");
@ -486,7 +352,7 @@ async fn query_combination() {
// full vector, without a vector => error
let (response, code) = index
.search_post(
json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true, "retrieveVectors": true}),
json!({"q": "Captain", "hybrid": {"semanticRatio": 1.0}, "showRankingScore": true}),
)
.await;
@ -503,93 +369,11 @@ async fn query_combination() {
// hybrid without a vector => full keyword
let (response, code) = index
.search_post(
json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true, "retrieveVectors": true}),
json!({"q": "Planet", "hybrid": {"semanticRatio": 0.99}, "showRankingScore": true}),
)
.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":{"embeddings":[[1.0,2.0]],"regenerate":false}},"_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");
}
#[actix_rt::test]
async fn retrieve_vectors() {
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}, "retrieveVectors": true}),
)
.await;
snapshot!(code, @"200 OK");
insta::assert_json_snapshot!(response["hits"], {"[]._vectors.default.embeddings" => "[vectors]"}, @r###"
[
{
"title": "Captain Planet",
"desc": "He's not part of the Marvel Cinematic Universe",
"id": "2",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
},
{
"title": "Captain Marvel",
"desc": "a Shazam ersatz",
"id": "3",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
},
{
"title": "Shazam!",
"desc": "a Captain Marvel ersatz",
"id": "1",
"_vectors": {
"default": {
"embeddings": "[vectors]",
"regenerate": true
}
}
}
]
"###);
// remove `_vectors` from displayed attributes
let (response, code) =
index.update_settings(json!({ "displayedAttributes": ["id", "title", "desc"]} )).await;
assert_eq!(202, code, "{:?}", response);
index.wait_task(response.uid()).await;
let (response, code) = index
.search_post(
json!({"q": "Captain", "hybrid": {"semanticRatio": 0.2}, "retrieveVectors": true}),
)
.await;
snapshot!(code, @"200 OK");
insta::assert_json_snapshot!(response["hits"], {"[]._vectors.default.embeddings" => "[vectors]"}, @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"
}
]
"###);
}

View File

@ -1,128 +0,0 @@
use meili_snap::snapshot;
use once_cell::sync::Lazy;
use crate::common::index::Index;
use crate::common::{Server, Value};
use crate::json;
async fn index_with_documents<'a>(server: &'a Server, documents: &Value) -> Index<'a> {
let index = server.index("test");
index.add_documents(documents.clone(), None).await;
index.wait_task(0).await;
index
}
static SIMPLE_SEARCH_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Shazam!",
"id": "1",
},
{
"title": "Captain Planet",
"id": "2",
},
{
"title": "Captain Marvel",
"id": "3",
},
{
"title": "a Captain Marvel ersatz",
"id": "4"
},
{
"title": "He's not part of the Marvel Cinematic Universe",
"id": "5"
},
{
"title": "a Shazam ersatz, but better than Captain Planet",
"id": "6"
},
{
"title": "Capitain CAAAAAVEEERNE!!!!",
"id": "7"
}
])
});
#[actix_rt::test]
async fn simple_search() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"2"},{"id":"6"},{"id":"7"}]"###);
})
.await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
})
.await;
index
.search(json!({"q": "Captain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}
#[actix_rt::test]
async fn search_with_typo() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"7"},{"id":"2"},{"id":"6"}]"###);
})
.await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"}]"###);
})
.await;
index
.search(json!({"q": "Capitain Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}
#[actix_rt::test]
async fn search_with_unknown_word() {
let server = Server::new().await;
let index = index_with_documents(&server, &SIMPLE_SEARCH_DOCUMENTS).await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "last", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"2"},{"id":"3"},{"id":"4"},{"id":"6"},{"id":"7"}]"###);
})
.await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "all", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @"[]");
})
.await;
index
.search(json!({"q": "Captain Supercopter Marvel", "matchingStrategy": "frequency", "attributesToRetrieve": ["id"]}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(response["hits"], @r###"[{"id":"3"},{"id":"4"},{"id":"5"}]"###);
})
.await;
}

View File

@ -7,7 +7,6 @@ mod facet_search;
mod formatted;
mod geo;
mod hybrid;
mod matching_strategy;
mod multi;
mod pagination;
mod restrict_searchable;
@ -48,31 +47,6 @@ static DOCUMENTS: Lazy<Value> = Lazy::new(|| {
])
});
static SCORE_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
},
{
"title": "Batman the dark knight returns: Part 2",
"id": "B",
},
{
"title": "Batman Returns",
"id": "C",
},
{
"title": "Batman",
"id": "D",
},
{
"title": "Badman",
"id": "E",
}
])
});
static NESTED_DOCUMENTS: Lazy<Value> = Lazy::new(|| {
json!([
{
@ -301,7 +275,7 @@ async fn negative_special_cases_search() {
index.add_documents(documents, None).await;
index.wait_task(0).await;
index.update_settings(json!({"synonyms": { "escape": ["gläss"] }})).await;
index.update_settings(json!({"synonyms": { "escape": ["glass"] }})).await;
index.wait_task(1).await;
// There is a synonym for escape -> glass but we don't want "escape", only the derivates: glass
@ -706,26 +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]
@ -941,9 +895,9 @@ async fn test_score_details() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
},
"_rankingScoreDetails": {
@ -967,7 +921,7 @@ async fn test_score_details() {
"order": 3,
"attributeRankingOrderScore": 1.0,
"queryWordDistanceScore": 0.8095238095238095,
"score": 0.8095238095238095
"score": 0.9727891156462584
},
"exactness": {
"order": 4,
@ -985,213 +939,6 @@ async fn test_score_details() {
.await;
}
#[actix_rt::test]
async fn test_score() {
let server = Server::new().await;
let index = server.index("test");
let documents = SCORE_DOCUMENTS.clone();
let res = index.add_documents(json!(documents), None).await;
index.wait_task(res.0.uid()).await;
index
.search(
json!({
"q": "Badman the dark knight returns 1",
"showRankingScore": true,
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
"_rankingScore": 0.9746605609456898
},
{
"title": "Batman the dark knight returns: Part 2",
"id": "B",
"_rankingScore": 0.8055252965383685
},
{
"title": "Badman",
"id": "E",
"_rankingScore": 0.16666666666666666
},
{
"title": "Batman Returns",
"id": "C",
"_rankingScore": 0.07702020202020202
},
{
"title": "Batman",
"id": "D",
"_rankingScore": 0.07702020202020202
}
]
"###);
},
)
.await;
}
#[actix_rt::test]
async fn test_score_threshold() {
let query = "Badman dark returns 1";
let server = Server::new().await;
let index = server.index("test");
let documents = SCORE_DOCUMENTS.clone();
let res = index.add_documents(json!(documents), None).await;
index.wait_task(res.0.uid()).await;
index
.search(
json!({
"q": query,
"showRankingScore": true,
"rankingScoreThreshold": 0.0
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"5");
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
"_rankingScore": 0.93430081300813
},
{
"title": "Batman the dark knight returns: Part 2",
"id": "B",
"_rankingScore": 0.6685627880184332
},
{
"title": "Badman",
"id": "E",
"_rankingScore": 0.25
},
{
"title": "Batman Returns",
"id": "C",
"_rankingScore": 0.11553030303030302
},
{
"title": "Batman",
"id": "D",
"_rankingScore": 0.11553030303030302
}
]
"###);
},
)
.await;
index
.search(
json!({
"q": query,
"showRankingScore": true,
"rankingScoreThreshold": 0.2
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"3"###);
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
"_rankingScore": 0.93430081300813
},
{
"title": "Batman the dark knight returns: Part 2",
"id": "B",
"_rankingScore": 0.6685627880184332
},
{
"title": "Badman",
"id": "E",
"_rankingScore": 0.25
}
]
"###);
},
)
.await;
index
.search(
json!({
"q": query,
"showRankingScore": true,
"rankingScoreThreshold": 0.5
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"2"###);
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
"_rankingScore": 0.93430081300813
},
{
"title": "Batman the dark knight returns: Part 2",
"id": "B",
"_rankingScore": 0.6685627880184332
}
]
"###);
},
)
.await;
index
.search(
json!({
"q": query,
"showRankingScore": true,
"rankingScoreThreshold": 0.8
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"1"###);
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @r###"
[
{
"title": "Batman the dark knight returns: Part 1",
"id": "A",
"_rankingScore": 0.93430081300813
}
]
"###);
},
)
.await;
index
.search(
json!({
"q": query,
"showRankingScore": true,
"rankingScoreThreshold": 1.0
}),
|response, code| {
meili_snap::snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @r###"0"###);
// nobody is perfect
meili_snap::snapshot!(meili_snap::json_string!(response["hits"]), @"[]");
},
)
.await;
}
#[actix_rt::test]
async fn test_degraded_score_details() {
let server = Server::new().await;
@ -1290,38 +1037,21 @@ async fn experimental_feature_vector_store() {
index.add_documents(json!(documents), None).await;
index.wait_task(0).await;
index
.search(json!({
let (response, code) = index
.search_post(json!({
"vector": [1.0, 2.0, 3.0],
"showRankingScore": true
}), |response, code|{
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Passing `vector` as a parameter 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"
}
"###);
})
.await;
index
.search(json!({
"retrieveVectors": true,
"showRankingScore": true
}), |response, code|{
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Passing `retrieveVectors` as a parameter 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"
}
"###);
})
}))
.await;
meili_snap::snapshot!(code, @"400 Bad Request");
meili_snap::snapshot!(meili_snap::json_string!(response), @r###"
{
"message": "Passing `vector` as a query parameter 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"
}
"###);
let (response, code) = server.set_features(json!({"vectorStore": true})).await;
meili_snap::snapshot!(code, @"200 OK");
@ -1354,7 +1084,6 @@ async fn experimental_feature_vector_store() {
.search_post(json!({
"vector": [1.0, 2.0, 3.0],
"showRankingScore": true,
"retrieveVectors": true,
}))
.await;
@ -1366,16 +1095,11 @@ async fn experimental_feature_vector_store() {
"title": "Shazam!",
"id": "287947",
"_vectors": {
"manual": {
"embeddings": [
[
1.0,
2.0,
3.0
]
],
"regenerate": false
}
"manual": [
1,
2,
3
]
},
"_rankingScore": 1.0
},
@ -1383,16 +1107,11 @@ async fn experimental_feature_vector_store() {
"title": "Captain Marvel",
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
1.0,
2.0,
54.0
]
],
"regenerate": false
}
"manual": [
1,
2,
54
]
},
"_rankingScore": 0.9129111766815186
},
@ -1400,16 +1119,11 @@ async fn experimental_feature_vector_store() {
"title": "Gläss",
"id": "450465",
"_vectors": {
"manual": {
"embeddings": [
[
-100.0,
340.0,
90.0
]
],
"regenerate": false
}
"manual": [
-100,
340,
90
]
},
"_rankingScore": 0.8106412887573242
},
@ -1417,16 +1131,11 @@ async fn experimental_feature_vector_store() {
"title": "How to Train Your Dragon: The Hidden World",
"id": "166428",
"_vectors": {
"manual": {
"embeddings": [
[
-100.0,
231.0,
32.0
]
],
"regenerate": false
}
"manual": [
-100,
231,
32
]
},
"_rankingScore": 0.7412010431289673
},
@ -1434,16 +1143,11 @@ async fn experimental_feature_vector_store() {
"title": "Escape Room",
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
10.0,
-23.0,
32.0
]
],
"regenerate": false
}
"manual": [
10,
-23,
32
]
},
"_rankingScore": 0.6972063183784485
}
@ -1701,9 +1405,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}
@ -1722,9 +1426,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}
@ -1743,9 +1447,9 @@ async fn simple_search_with_strange_synonyms() {
"id": "166428",
"_vectors": {
"manual": [
-100.0,
231.0,
32.0
-100,
231,
32
]
}
}

View File

@ -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
]
}
}

View File

@ -285,10 +285,10 @@ async fn attributes_ranking_rule_order() {
@r###"
[
{
"id": "1"
"id": "2"
},
{
"id": "2"
"id": "1"
}
]
"###

View File

@ -1,20 +0,0 @@
---
source: meilisearch/tests/search/distinct.rs
---
{
"uid": 1,
"indexUid": "tamo",
"status": "succeeded",
"type": "settingsUpdate",
"canceledBy": null,
"details": {
"filterableAttributes": [
"color.main"
]
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}

View File

@ -1,18 +0,0 @@
---
source: meilisearch/tests/search/errors.rs
---
{
"uid": 0,
"indexUid": "tamo",
"status": "succeeded",
"type": "indexCreation",
"canceledBy": null,
"details": {
"primaryKey": null
},
"error": null,
"duration": "[duration]",
"enqueuedAt": "[date]",
"startedAt": "[date]",
"finishedAt": "[date]"
}

View File

@ -98,7 +98,8 @@ async fn secrets_are_hidden_in_settings() {
{
"vectorStore": true,
"metrics": false,
"logsRoute": false
"logsRoute": false,
"exportPuffinReports": false
}
"###);

View File

@ -1,809 +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_bad_ranking_score_threshold() {
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!({"rankingScoreThreshold": ["doggo"]})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.rankingScoreThreshold`: expected a number, but found an array: `[\"doggo\"]`",
"code": "invalid_similar_ranking_score_threshold",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_ranking_score_threshold"
}
"###);
}
#[actix_rt::test]
async fn similar_invalid_ranking_score_threshold() {
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!({"rankingScoreThreshold": 42})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value at `.rankingScoreThreshold`: the value of `rankingScoreThreshold` is invalid, expected a float between `0.0` and `1.0`.",
"code": "invalid_similar_ranking_score_threshold",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_ranking_score_threshold"
}
"###);
}
#[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;
}
#[actix_rt::test]
async fn similar_bad_retrieve_vectors() {
let server = Server::new().await;
server.set_features(json!({"vectorStore": true})).await;
let index = server.index("test");
let (response, code) = index.similar_post(json!({"retrieveVectors": "doggo"})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found a string: `\"doggo\"`",
"code": "invalid_similar_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
}
"###);
let (response, code) = index.similar_post(json!({"retrieveVectors": [true]})).await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value type at `.retrieveVectors`: expected a boolean, but found an array: `[true]`",
"code": "invalid_similar_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
}
"###);
let (response, code) = index.similar_get("?retrieveVectors=").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `` as a boolean, expected either `true` or `false`",
"code": "invalid_similar_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
}
"###);
let (response, code) = index.similar_get("?retrieveVectors=doggo").await;
snapshot!(code, @"400 Bad Request");
snapshot!(json_string!(response), @r###"
{
"message": "Invalid value in parameter `retrieveVectors`: could not parse `doggo` as a boolean, expected either `true` or `false`",
"code": "invalid_similar_retrieve_vectors",
"type": "invalid_request",
"link": "https://docs.meilisearch.com/errors#invalid_similar_retrieve_vectors"
}
"###);
}

View File

@ -1,731 +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, "retrieveVectors": true}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
}
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
}
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": {
"embeddings": [
[
0.699999988079071,
0.699999988079071,
-0.4000000059604645
]
],
"regenerate": false
}
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": {
"embeddings": [
[
0.800000011920929,
0.4000000059604645,
-0.5
]
],
"regenerate": false
}
}
}
]
"###);
})
.await;
index
.similar(json!({"id": "299537", "retrieveVectors": true}), |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": {
"embeddings": [
[
0.699999988079071,
0.699999988079071,
-0.4000000059604645
]
],
"regenerate": false
}
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": {
"embeddings": [
[
0.800000011920929,
0.4000000059604645,
-0.5
]
],
"regenerate": false
}
}
},
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
}
},
{
"title": "All Quiet on the Western Front",
"release_year": 1930,
"id": "143",
"_vectors": {
"manual": {
"embeddings": [
[
-0.5,
0.30000001192092896,
0.8500000238418579
]
],
"regenerate": false
}
}
}
]
"###);
})
.await;
}
#[actix_rt::test]
async fn ranking_score_threshold() {
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, "showRankingScore": true, "rankingScoreThreshold": 0, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"4");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
},
"_rankingScore": 0.890957772731781
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
},
"_rankingScore": 0.39060014486312866
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": {
"embeddings": [
[
0.699999988079071,
0.699999988079071,
-0.4000000059604645
]
],
"regenerate": false
}
},
"_rankingScore": 0.2819308042526245
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": {
"embeddings": [
[
0.800000011920929,
0.4000000059604645,
-0.5
]
],
"regenerate": false
}
},
"_rankingScore": 0.1662663221359253
}
]
"###);
},
)
.await;
index
.similar(
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.2, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"3");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
},
"_rankingScore": 0.890957772731781
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
},
"_rankingScore": 0.39060014486312866
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": {
"embeddings": [
[
0.699999988079071,
0.699999988079071,
-0.4000000059604645
]
],
"regenerate": false
}
},
"_rankingScore": 0.2819308042526245
}
]
"###);
},
)
.await;
index
.similar(
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.3, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"2");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
},
"_rankingScore": 0.890957772731781
},
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
},
"_rankingScore": 0.39060014486312866
}
]
"###);
},
)
.await;
index
.similar(
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.6, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
meili_snap::snapshot!(meili_snap::json_string!(response["estimatedTotalHits"]), @"1");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
},
"_rankingScore": 0.890957772731781
}
]
"###);
},
)
.await;
index
.similar(
json!({"id": 143, "showRankingScore": true, "rankingScoreThreshold": 0.9, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @"[]");
},
)
.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", "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
}
},
{
"title": "How to Train Your Dragon: The Hidden World",
"release_year": 2019,
"id": "166428",
"_vectors": {
"manual": {
"embeddings": [
[
0.699999988079071,
0.699999988079071,
-0.4000000059604645
]
],
"regenerate": false
}
}
},
{
"title": "Shazam!",
"release_year": 2019,
"id": "287947",
"_vectors": {
"manual": {
"embeddings": [
[
0.800000011920929,
0.4000000059604645,
-0.5
]
],
"regenerate": false
}
}
}
]
"###);
},
)
.await;
index
.similar(
json!({"id": 522681, "filter": "release_year < 2000", "retrieveVectors": true}),
|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": {
"embeddings": [
[
-0.5,
0.30000001192092896,
0.8500000238418579
]
],
"regenerate": false
}
}
}
]
"###);
},
)
.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, "retrieveVectors": true}), |response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Escape Room",
"release_year": 2019,
"id": "522681",
"_vectors": {
"manual": {
"embeddings": [
[
0.10000000149011612,
0.6000000238418579,
0.800000011920929
]
],
"regenerate": false
}
}
}
]
"###);
})
.await;
index
.similar(
json!({"id": 143, "limit": 1, "offset": 1, "retrieveVectors": true}),
|response, code| {
snapshot!(code, @"200 OK");
snapshot!(json_string!(response["hits"]), @r###"
[
{
"title": "Captain Marvel",
"release_year": 2019,
"id": "299537",
"_vectors": {
"manual": {
"embeddings": [
[
0.6000000238418579,
0.800000011920929,
-0.20000000298023224
]
],
"regenerate": false
}
}
}
]
"###);
},
)
.await;
}

View File

@ -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;
@ -31,7 +32,6 @@ macro_rules! verify_snapshot {
}
#[actix_rt::test]
#[cfg_attr(target_os = "windows", ignore)]
async fn perform_snapshot() {
let temp = tempfile::tempdir().unwrap();
let snapshot_dir = tempfile::tempdir().unwrap();
@ -53,29 +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();

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