Update getmeili/meilisearch Docker tag to v1.30.1 #275
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This PR contains the following updates:
v1.13.3->v1.30.1Release Notes
meilisearch/meilisearch (getmeili/meilisearch)
v1.30.1: 🐸Compare Source
What's Changed
🐛 Bug Fixes
Fix task attribution during index swap to prevent cross-index task loss by @YoEight in #6059
This change fixes the parenting of the tasks when doing an index swap.
Hotfix: log a warning when FieldidsWeightsMap is missing entry by @ManyTheFish in #6064
This hotfix avoids the encounter of following error during a search request:
🫂 New Contributors
v1.30.0: 🐸Compare Source
🌈 Improvements
Up and down network scaling
Since v1.19.0, Meilisearch Enterprise Edition allows the automatic sharding of documents over multiple Meilisearch instances, enabling scaling to more documents than a single instance would accommodate.
Meilisearch v1.30.0 adds the ability to modify the number of participants in sharding, without having to start over sending documents to a new cluster containing the number of desired machines.
To make this possible, Meilisearch v1.30.0 introduces breaking changes. These breaking changes only affect the users of the experimental
networkfeature who enabled automatic sharding (network.sharding = true). Users of the stable features are not affected.Usage
Setting up the initial network
PATCH /network:Upgrading from v1.29 or earlier
networkinstance withshardingset totrue, then thenetworkobject will be modified so that the leader is the first remote in alphabetic order. For instance, if you network contains remotes:A,B,C, the leader will be set toA.Adding a new remote
PATCH /networkon the leader with the information about the new remote:ms2).networkTopologyChangetask that will "rebalance" the documents between the existing remotes and the new remote, that is,ms0andms1will send parts of their documents toms2Removing a remote
PATCH /networkon the leader by setting any removed remote tonull:ms2that will then no longer participate in the network).networkTopologyChangetask that will "rebalance" the documents between the remaining remotes, that is,ms2will send its documents betweenms0andms1List of changes
List of changes, some of which are breaking
Networkobject returned or edited by the/networkroute is modified in the following way:shardingboolean is removedleaderfield is added as an optional string. When it is notnull, it has the same effect (and more) than havingsharding: truein the previous iteration of theNetworkobject. The leader is used as a check when receiving task creation requests.versionfield is added as a UUID, defaulting to the null UUID. The version is used when processing tasks.network.leaderis set, calling one of the following routes will fail withnot_a_leadererror if the target'snetwork.selfis not the same as itsnetwork.leader:POST /indexesPATCH/DELETE /indexes/{:indexUid}POST/PUT/DELETE /indexes/{:indexUid}/documentsPOST /indexes/{:indexUid}/documents/deletePOST /indexes/{:indexUid}/documents/delete-batchPOST /indexes/{:indexUid}/documents/editPATCH/DELETE /indexes/{:indexUid}/settingsand settings sub-routesPATCH /networkif the target is the new leaderPOST /swap-indexesleaderis set,PATCH /networkno longer returns aNetworkobject. Rather, it spawns a newNetworkTopologyChangetask, and returns the summarized task view.POST /indexes(new to this PR)PATCH/DELETE /indexes/{:indexUid}(new to this PR)POST/PUT/DELETE /indexes/{:indexUid}/documents(was already the case before this PR)POST /indexes/{:indexUid}/documents/delete(was already the case before this PR)POST /indexes/{:indexUid}/documents/delete-batch(was already the case before this PR)POST /indexes/{:indexUid}/documents/edit(was already the case before this PR)PATCH/DELETE /indexes/{:indexUid}/settingsand settings sub-routes (new to this PR)PATCH /networkif the target is the new leader (new to this PR)POST /swap-indexes(new to this PR)NetworkTopologyChangetasks that perform the following:network.versionlower than the network task's versionnetworkroute with specific headers containing the expected metadataselfandleaderfrom the networkby @dureuill in #6000
🛠️ Maintenance
Asset availability note
🌈 The Meilisearch binary is available again for
meilisearch-enterprise-macos-amd64andmeilisearch-macos-amd64. It was not available for Meilisearch v1.29.Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.29.0...v1.30.0
v1.29.0: 🐑Compare Source
Build compatibility note
The git binary must now be present at build time to populate the
commitSha1field of the/versionfield.This change was made for build performance reasons.
by @dureuill in #6030
🌈 Improvements
Another piece of the settings indexer is available: searchable and exact attributes
The new settings indexer scales better, supports near-instant cancellations and displays the progress of the indexing operation.
Previously, the new settings indexer was enabled only if the only changes in a settings batch were to embedder settings. In Meilisearch v1.29.0, the new settings indexer will be enabled if the change is any combination of:
searchableAttributesexactAttributesproximityPrecisionembedders(as before)Any other change to settings appearing in a batch will cause the batch to use the legacy settings indexer.
Additionally, the new settings indexer is currently disabled by default for Cloud users.
OSS users who would like to disable the new settings indexer should pass the
MEILI_EXPERIMENTAL_NO_EDITION_2024_FOR_SETTINGSenvironment variable totrue.by @Kerollmops in #5983
Enable the new vector store by default for new indexes
Meilisearch v1.21.0 introduced a new vector store backend providing better performance and relevancy.
Starting with v1.29.0, any newly created index will default to the new backend.
Existing indexes will be left unchanged.
It is still possible to explicitly choose the vector store backend, please refer to the relevant experimental feature discussion page.
by @Kerollmops in #6004
Support more models for
huggingFaceembedderYou can now select models with the XLM Roberta architecture when generating embeddings locally on CPU or GPU with the
huggingFaceembedder.by @qdequele in #6018
🦋 Bug fixes
🔧 Maintenance and Misc.
Last week was a Quality of Life week, and while we still had improvements in the pipe, the bulk of our work was dedicated to maintenance tasks.
Most notably, the CI is now faster, going from over one hour to less than 30 minutes, and also more reliable as it automatically tests the dumpless upgrade.
xtasksub-command to generate prototype tag names with the expected nomenclature by @Kerollmops in #6022Asset availability note
⚠️ The Meilisearch binary is not available for
meilisearch-enterprise-macos-amd64andmeilisearch-macos-amd64due to a compilation oversight. #6037 aims at fixing this for future releases.The more recent
meilisearch-enterprise-macos-apple-siliconandmeilisearch-macos-apple-siliconare fine.Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.28.2...v1.29.0
v1.28.2: 🐩Compare Source
This release fixes a bug affecting the Prometheus metrics route in versions 1.28.0 and 1.28.1, specifically when the instance has too many tasks. The issue is visible as high memory usage and could cause the instance to be OOM-killed. If you are using the /metrics route, we recommend deleting all succeeded or failed tasks in the index using the dedicated route or upgrading to at least v1.28.2.
🐛 Bug fixes
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.28.1...v1.28.2
v1.28.1: 🐩Compare Source
This release features two fixes: one to ensure that we correctly upload the Linux-amd64 binaries for the Community and Enterprise editions, and one contributed by an external developer to ensure that we still return documents that don't contain the sortable attribute after those that do.
🐛 Bug Fixes
🫂 New Contributors
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.28.0...v1.28.1
v1.28.0: 🐩Compare Source
This release introduces improvements to language support and separates the community and enterprise binary editions. We now offer binaries under the BUSL-1.1 license, identified by the "enterprise" term in their names, in addition to our MIT-licensed binaries, which retain their original names. Docker images for the enterprise edition are available in the
getmeili/meilisearch-enterpriserepository.📝 Licensing
✨ Enhancement
🔩 Miscellaneous
🫂 New Contributors
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.27.0...v1.28.0
v1.27.0: 🦮Compare Source
This release improves the batch size for better performance. It also fixes bugs with the embedders that could skip some documents during generation and resolves an issue with the document route that displayed the same documents on multiple pages. It improves the quality of error messages when uploading snapshots to S3, which helps with debugging.
⚙️ Compatibility support
Meilisearch MacOS binaries now generated with MacOS Sonoma (
macos-14)✨ Enhancement
🪲 Bug fixes
available_parallelismth document in a batch was ignored for the purpose of embedding when using a Hugging Face embedder #5976multimodalexp. featureNOT _vectors EXISTSto find documents without vectors./documents/fetchbug that could cause duplicated search results when paginating sorted documents by @ManyTheFish in #5999Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.26.0...v1.27.0
v1.26.0: 🐛Compare Source
✨ Enhancements
Allow to attach custom metadata in the document addition or update tasks
customMetadataquery parameter to any supported route:GET /tasksfor tasks with metadata:by @dureuill in #5963
Support more models for
huggingFaceembedderYou can now select models with the
modernBERTarchitecture when generating embeddings locally on CPU or GPU with thehuggingFaceembedder.This unlocks for instance Ruri v3 and other models
by @hayatosc in #5980
🧪 Experimental: embedder failure modes
You can now decide to ignore some embedder-related errors. Either:
userProvidedembedders)When errors are ignored, the corresponding documents will not have embeddings, but the associated batch of tasks will not be marked as failed.
Of course, ignoring errors means that it is harder to notice an issue with embedders, so use this feature parsimoniously.
To enable the feature:
MEILI_EXPERIMENTAL_CONFIG_EMBEDDER_FAILURE_MODESand set it to a comma-separated list of errors to ignore, with the possible values:ignore_document_template_failuresto ignore document template failuresignore_embedder_failuresto ignore embedder failuresignore_document_template_failures,ignore_embedder_failuresignores both kinds of failuresby @dureuill in #5984
🧪 Experimental: timeout control for REST embedders
You can now control the duration before a REST embedder request times out.
MEILI_EXPERIMENTAL_REST_EMBEDDER_TIMEOUT_SECONDS, which must be a positive integer.by @dureuill in #5984
🔩 Misc
allocator-api2by @xuhongxu96 in #5969👥 Contributors
Many thanks to our new contributors @hayatosc and @xuhongxu96 ❤️
v1.25.0: 🐈⬛Compare Source
✨ Enhancement
🔬 [Experimental]: Search personalization by @ManyTheFish in #5775
Add the ability to dynamically rerank the search results based on Cohere using a personalized prompt.
For more information on how to set it up, see the dedicated experimental feature discussion.
🔬 [Experimental]: Upload snapshot tarballs to S3 by @Kerollmops in #5948
Add the ability to upload snapshots directly to S3. It has many advantages, such as being able to stream the entire process and effectively utilizing multipart technology to send chunks of data in parallel.
For more information on how to use it, see the dedicated experimental feature discussion.
🪲 Bug fixes
⚠️ [Breaking - Security] Redact Authorization header in webhooks by @dureuill in #5968
The value of the
Authorizationheader is now redacted when getting webhook, getting webhooks, or in the object returned when posting a new webhook or deleting a webhook.Authorizationheader back after it has been redacted🚰 Fix the LMDB fork memory leak by @Kerollmops in #5967
This bug was causing crashes in the recent indexer optimizations. If you deactivated these optimizations by setting the following environment variables:
You can now safely reactivate them without experiencing memory leaks.
🇩🇪 Hotfix German word segmentation by @ManyTheFish in meilisearch/charabia#360
German word segmentation relies on a word dictionary to segment words, but if a word is not part of the dictionary, it is cut into bigrams. The segmenter will now skip segmenting unknown words:
🇨🇳 Prevent splitting of numbers and English words in Chinese text segmentation by @JinheLin in meilisearch/charabia#354
It’s very common for Chinese, numbers, and English to appear together in the same sentence.
We now ensure that numbers and English are not segmented differently between segmenters:
🔩 Miscellaneous
Thanks to @JinheLin, @dureuill, @Kerollmops, and @ManyTheFish for their contribution! 🎉
v1.24.0: 🦞Compare Source
This release features some improvements with the interaction of the vector store and the
searchCutoffMswhen using the"vectorStore": "experimental"index setting. It also introduces the metadata headerMeili-Include-Metadataon the search request that adds a metadata field to the response. These metadatas contains one uid by query and a reminder of theindexUidand its primary key. We also introduced minor bug fixes around the compaction to improve the interaction with task cancellation.✨ Enhancement
🔩 Miscellaneous
👥 New Contributors
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.23.0...v1.24.0
v1.23.0: 🐘Compare Source
This release introduces a new compact route on the index routes, which appends a new compaction task to the queue. Meilisearch uses an LMDB environment by index, and indexes start to fragment after some time. We have noticed that the indexes generally have 30% fragmentation. By defragmenting the environment, we've seen large (2-4x) speed-ups in terms of search and indexation. This is primarily due to the reordering of the LMDB internal pages and the removal of scattered free pages throughout the file, thereby relocating the content to the beginning.
We also worked on parallelizing the post-processing of facets. We noticed that a lot of time was spent iterating over the prefixes of the index in a single-threaded loop. We redesigned this part of the indexation to make it multi-threaded. We have seen a 4x and 6x improvement in terms of time spent on this operation.
✨ Improvements
🦋 Bug Fixes
🔩 Miscellenaous
New Contributors
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.22.1...v1.23.0
v1.22.3: 🐦🔥Compare Source
This version contains a minor fix that affects remote federated search users. If you are not a remote federated search user, it is not necessary to migrate from v1.22.x.
🦋 Bugfixes
MEILI_EXPERIMENTAL_REMOTE_SEARCH_TIMEOUT_SECONDSto a positive integer value. Please note that no CLI flag or configuration entry is available. By @dureuill in #5932v1.22.2: 🐦🔥Compare Source
🦋 Bugfixes
v1.22.1Compare Source
🐛 Bug Fixes
❤️ Huge thanks to our contributors: @dureuill and @irevoire.
v1.22.0: 🐦🔥Compare Source
🚀 Enhancements
_geojsonfield filterable_geojsonfield filled with a valid geojson_geoPolygonfilter, or the old_geoBoudingBoxand_geoPointsfilter🐛 Bug Fixes
❤️ Huge thanks to our contributors: @nnethercott, @Kerollmops, @ManyTheFish, @dureuill and @irevoire.
Full Changelog: https://github.com/meilisearch/meilisearch/compare/v1.21.0...v1.22.0
v1.21.0: 🐷Compare Source
🚀 Enhancements
vectorStoreSettingexperimental featurevectorSettingindex setting to"experimental"for the indexes where you want to try the new vector store🐛 Bug Fixes
decoding errorwhen upgrading with arestembedder (#5886) @dureuill.❤️ Huge thanks to our contributors: @ja7ad, @agourlay, @Kerollmops, @ManyTheFish, @dureuill and @irevoire.
v1.20.0: 🦟Compare Source
🚀 Enhancements
🐛 Bug Fixes
🔒 Security
⚙️ Maintenance/misc
❤️ Huge thanks to our contributors: @ManyTheFish, @arithmeticmean, @curquiza, @dureuill, @irevoire, @shreeup and dependabot[bot].
v1.19.1: 🪸Compare Source
🐛 Performance improvements
Enhance hybrid search with filter performances
In previous versions of Meilisearch, mixing hybrid search with filters, as shown below, could multiply the search time by hundreds.
Meilisearch will now directly compute the semantic distance with the filtered candidates if only a few candidates come from the filter, instead of searching for the closest embeddings matching the filter in the vector database.
v1.19.0: 🪸Compare Source
🚀 Enhancements
Automatically shard documents to scale horizontally
Meilisearch can now automatically distribute documents between multiple instances using the new sharding feature.
Find a guide on implementing sharding in the documentation.
Added in #5784 by @dureuill
🐛 Bug Fixes
❤️ Huge thanks to our contributors: @Kerollmops, @dureuill and @martin-g.
v1.18.0: 🕷️Compare Source
🚀 Enhancements
queryVectorin the search response when usingretrieveVectors(#5778) @Mubelotix❤️ Huge thanks to our contributors: @Kerollmops, @Mubelotix, @irevoire and @qdequele.
v1.17.1: 🐀Compare Source
🚀 Enhancements
⚙️ Maintenance/misc
v1.17.0: 🐀Compare Source
Enhancements
Check the in progress documentation (PR merged soon)
STARTS_WITHfilter by @Mubelotix in #5783No need to activate the experimental feature anymore to use this operator 🎉
Bugs
PATCHby @Mubelotix in #5807⚠️ This fix leads to a breaking change on:
PUT→PATCH. Integrations and SDKs will adapt to this change.snapshotCreationtask being included in snapshot by @Mubelotix in #5773Maintenance
v1.16.0: 🦚Compare Source
Meilisearch v1.16 introduces two main features: multimodal embeddings and a new
/exportroute. Multimodal embeddings use AI-powered search to index images in addition to textual documents. The/exportroute simplifies migrating from a local Meilisearch instance to Meilisearch Cloud.🧰 All official Meilisearch integrations (including SDKs, clients, and other tools) are compatible with this Meilisearch release. Integration deployment happens between 4 to 48 hours after a new version becomes available.
Some SDKs might not include all new features. Consult the project repository for detailed information. Is a feature you need missing from your chosen SDK? Create an issue letting us know you need it, or, for open-source karma points, open a PR implementing it (we'll love you for that ❤️).
New features and updates 🔥
Experimental feature: Multimodal embeddings
v1.16 allows indexing and searching non-textual documents, as well as performing searches with image queries. This new feature uses multimodal embedders to provide a common semantic representation for images, texts, and any other piece of data.
Usage
First, enable the
multimodalexperimental feature:Next, pick an embedder provider that supports multimodal embeddings such as Cohere or VoyageAI to start building the embedding configuration.
The following is an example configuration for multimodal embedder using VoyageAI:
The configuration above sets up Meilisearch to generate vectors for two fields:
textandposter. It also allows users to perform searches with an image URL, a raw image, or regular text.Use the new
mediasearch parameter together with one of thesearchFragmentsyou specified in your embedder to search with an image:You can also perform a text search with
qandhybrid:Meilisearch performs searches all fields with embeddings when parsing
hybridqueries targeting indexes with multimodal embedders.For more information about this feature, please refer to its public usage page
Done by @dureuill in #5596
The new
/exportroutev1.16 introduces a new
/exportroute that allows transferring documents between instances without having to create a dump or a snapshot. This feature is particularly useful when migrating from a local machine to Meilisearch Cloud.Usage
To transfer data between instances, query
/exportand point itsurlparameter to the URL of the target instance:This will generate an export and task start migrating data between instances. Depending on the target instance, you may also have to supply an API key with full admin permissions in the
apiKeyparameter. Consult the documentation for an exhaustive list of accepted parameters.If the request fails, Meilisearch will retry a few times before setting its status to failed. You may also cancel an export task manually. In this case, Meilisearch will interrupt the task locally, but not in the target instance.
Done by @kerollmops with the help of @mubelotix in #5670
Other improvements
attributes_to_search_onby @lblack00 in #5548Fixes 🐞
base_urlwhen used with OpenAI clients by @diksipav in #5692--experimental-limit-batched-tasks-total-sizeby @Kerollmops in #5705disableOnNumbersnot being affected by typo tolerance settings resets by @Nymuxyzo in #5702{}in index chat settings would incorrectly set the limit to 20 instead of resetting to empty defaultsMisc
GITHUB_TOKENsecret for thedb change checkworkflow by @martin-g in #5632❤️ Thanks again to our external contributors:
v1.15.2: 🦘Compare Source
This patch release introduces a major fix and some minor fixes.
Major fix: searchable attributes database bug
Some searchable fields were removed from the searchable databases when they were removed from the
filterableAttributessetting.This made them unsearchable, although they were still precise in the
searchableAttributessetting.Fixed by @ManyTheFish in #5660
Minor fixes
v1.15.1: 🦘Compare Source
Meilisearch v1.15.1 adds new experimental conversational features and enables LLM-driven chat features.
🧰 All official Meilisearch integrations (including SDKs, clients, and other tools) are compatible with this Meilisearch release. Integration deployment takes 4 to 48 hours after a new version becomes available.
Some SDKs might not include all new features. Please look over the project repository for detailed information. Is a feature you need missing from your chosen SDK? Create an issue letting us know you need it, or, for open-source karma points, open a PR implementing it (we'll love you for that ❤️).
Chat with your indexes
After enabling the experimental chat feature, you can create a chat workspace with the appropriate settings.
We have a guide on how to set up a good chat interface for your indexes.
Then by using the official OpenAI SDK you'll be able to chat with your indexes.
Done by @Kerollmops in #5556.
v1.15.0: 🦘Compare Source
Meilisearch v1.15 adds a new typo tolerance setting, allowing you to disable typo tolerance for numbers. It also enables comparison operators for string filters.
🧰 All official Meilisearch integrations (including SDKs, clients, and other tools) are compatible with this Meilisearch release. Integration deployment takes 4 to 48 hours after a new version becomes available.
Some SDKs might not include all new features. Please look over the project repository for detailed information. Is a feature you need missing from your chosen SDK? Create an issue letting us know you need it, or, for open-source karma points, open a PR implementing it (we'll love you for that ❤️).
New features and updates 🔥
Disable typo tolerance for numbers
Set
typoTolerance.disableOnNumberstotrueto disable typo tolerance for numbers:Deactivating the typo tolerance on numbers can be helpful when trying to reduce false positives, such as a query term
2024returning results that include2025and2004. It may also improve indexing performance.Done by @ManyTheFish in #5494.
Lexicographic string filters
This release allows you to filter strings lexicographically by enabling comparison operators (<, <=, >, >=, TO) on string values:
This new feature can be particularly useful when filtering human-readable dates.
Done by @dureuill in #5535.
Other improvements
batchStrategyfield in the batches stats by @dureuill in #5488, #5530, and #5588/networkURL validation error message format by @CodeMan62 in #5486Fixes 🐞
_matchesPositionlength calculation to improve client-side cropping by @shaokeyibb in #5446_georanking rule by @HDT3213 in #5487MEILI_EXPERIMENTAL_MAX_NUMBER_OF_BATCHED_TASKSto 0 results in Meilisearch never processing any kind of task. By @irevoire in #55650formaxTotalHitsin the index settings by @irevoire in #5566documentTemplates that use array filters on documents (e.g.join) by @dureuill in #5593Misc
❤️ Thanks again to our external contributors:
v1.14.0: 🦫Compare Source
Meilisearch v1.14 gives more granular control over which parts of filters you can disable for indexing performance optimization. This release also includes composite embedders, which can improve embedding generation during search and indexing, and a new route to retrieve multiple documents by their IDs.
🧰 All official Meilisearch integrations (including SDKs, clients, and other tools) are compatible with this Meilisearch release. Integration deployment happens between 4 to 48 hours after a new version becomes available.
Some SDKs might not include all new features. Consult the project repository for detailed information. Is a feature you need missing from your chosen SDK? Create an issue letting us know you need it, or, for open-source karma points, open a PR implementing it (we'll love you for that ❤️).
New features and updates 🔥
Granular filterable attribute settings
v1.14 gives you more control over which types of filter you want to disable in your searches. This allows you to further optimize indexing speeds by letting you activate only the filter features you need.
Use
PATCH /indexes/INDEX_NAME/settingsto specify which filters you want to enable for each attribute in your documents:For more details about this feature, please refer to the dedicated documentation page.
Done by @ManyTheFish in #5254.
Composite embedders
This feature allows using different embedders at search and indexing time. This can be useful when optimizing AI-powered search performance. For example, you may prefer to use:
To use the feature, follow these steps:
Composite embeddersfeature with the Meilisearch Cloud interface, or with the/experimental-featuresroute:sourceto"composite"and defining onesearchEmbedderand oneindexingEmbedder:indexingEmbedderduring indexing andsearchEmbedderwhen responding to user queriesFor more details about this feature, please refer to its public usage page.
Done by @dureuill in #5371 and #5401.
Retrieve multiple documents by ID
It is now possible to retrieve multiple documents by their IDs:
Done by @dureuill in #5384.
Other improvements
/documentsrequests using eitherPUTorPOSTby @Kerollmops in #5293/batchesroute by @Kerollmops in #5356 and #5364exhaustiveFacetCountparameter to/facet-searchroute to retrieve an exhaustive facet count by @ManyTheFish in #5369Fixes
disabledOnAttributessettings by @ManyTheFish in #5415 (fixes #5347 and #5452)rankingScoreThresholdno longer causes_rankingScoreto be miscalculated by @barloes and @dureuill in #5313_vectorsby @dureuill in #5478Misc
❤️ Thanks again to our external contributors:
Configuration
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f4462d07ced88272f9f3Update getmeili/meilisearch Docker tag to v1.24.0to Update getmeili/meilisearch Docker tag to v1.25.0d88272f9f3d897a7c843Update getmeili/meilisearch Docker tag to v1.25.0to Update getmeili/meilisearch Docker tag to v1.26.0d897a7c843c49ea78d00Update getmeili/meilisearch Docker tag to v1.26.0to Update getmeili/meilisearch Docker tag to v1.27.0c49ea78d00528ac4b28dUpdate getmeili/meilisearch Docker tag to v1.27.0to Update getmeili/meilisearch Docker tag to v1.28.0Update getmeili/meilisearch Docker tag to v1.28.0to Update getmeili/meilisearch Docker tag to v1.28.1528ac4b28d9b548f14399b548f1439351c097219Update getmeili/meilisearch Docker tag to v1.28.1to Update getmeili/meilisearch Docker tag to v1.28.2351c0972193fc45ed6d6Update getmeili/meilisearch Docker tag to v1.28.2to Update getmeili/meilisearch Docker tag to v1.29.03fc45ed6d6909843f299Update getmeili/meilisearch Docker tag to v1.29.0to Update getmeili/meilisearch Docker tag to v1.30.0909843f2995477eed35cUpdate getmeili/meilisearch Docker tag to v1.30.0to Update getmeili/meilisearch Docker tag to v1.30.1View command line instructions
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