> ## Documentation Index > Fetch the complete documentation index at: https://www.meilisearch.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # List all settings > Returns all settings of the index. Each setting is returned with its current value or the default if not set. ## OpenAPI ````yaml /assets/open-api/meilisearch-openapi-mintlify.json get /indexes/{index_uid}/settings openapi: 3.1.0 info: title: meilisearch description: Meilisearch HTTP server contact: name: Quentin de Quelen email: quentin@dequelen.me license: name: MIT identifier: MIT version: 1.41.0 servers: - url: http://localhost:7700 description: Local server. security: [] tags: - name: Stats description: >- Stats gives extended information and metrics about indexes and the Meilisearch database. - name: Health description: >- The health check endpoint enables you to periodically test the health of your Meilisearch instance. - name: Version description: Returns the version of the running Meilisearch instance. - name: Backups description: >- Meilisearch offers two types of backups: snapshots and dumps. Snapshots are mainly intended as a safeguard, while dumps are useful when migrating Meilisearch. - name: Export description: >- Export documents and settings from this instance to a remote Meilisearch server. - name: Async task management description: >- Routes for listing and managing batches and tasks (asynchronous operations). - name: Chats description: The `/chats` route allows you to manage chat workspaces. - name: Tasks description: >- The tasks route gives information about the progress of the [asynchronous operations](https://docs.meilisearch.com/learn/advanced/asynchronous_operations.html). - name: Batches description: >- Meilisearch groups compatible tasks ([asynchronous operations](https://www.meilisearch.com/docs/learn/async/asynchronous_operations)) into batches for efficient processing. For example, multiple document additions to the same index may be batched together. The /batches routes give information about the progress of these batches and let you monitor batch progress and performance. - name: Indexes description: >- An index is an entity that gathers a set of [documents](https://www.meilisearch.com/docs/learn/getting_started/documents) with its own [settings](https://www.meilisearch.com/docs/reference/api/settings). Learn more about indexes. - name: Documents description: >- Documents are objects composed of fields that can store any type of data. Each field contains an attribute and its associated value. Documents are stored inside [indexes](https://www.meilisearch.com/docs/learn/getting_started/indexes). - name: Facet Search description: >- The `/facet-search` route allows you to search for facet values. Facet search supports prefix search and typo tolerance. The returned hits are sorted lexicographically in ascending order. You can configure how facets are sorted using the sortFacetValuesBy property of the faceting index settings. - name: Similar documents description: >- The /similar route uses AI-powered search to return a number of documents similar to a target document. Meilisearch exposes two routes for retrieving similar documents: POST and GET. In the majority of cases, POST will offer better performance and ease of use. - name: Settings description: >- Configure search and index behavior. Update all settings at once via PATCH /indexes/{indexUid}/settings, or use a sub-route to get, update, or reset a single setting. - name: Search description: >- Meilisearch exposes two routes to perform searches: - A POST route: this is the preferred route when using API authentication, as it allows [preflight request](https://developer.mozilla.org/en-US/docs/Glossary/Preflight_request) caching and better performance. - A GET route: the usage of this route is discouraged, unless you have good reason to do otherwise (specific caching abilities for example) externalDocs: url: https://www.meilisearch.com/docs/reference/api/search description: Search API reference - name: Keys description: >- Manage API `keys` for a Meilisearch instance. Each key has a given set of permissions. You must have the master key or the default admin key to access the keys route. More information about the keys and their rights. Accessing any route under `/keys` without having set a master key will result in an error. - name: Logs description: >- Everything about retrieving or customizing logs. Currently [experimental](https://www.meilisearch.com/docs/learn/experimental/overview). - name: Multi-search description: >- The `/multi-search` route allows you to perform multiple search queries on one or more indexes by bundling them into a single HTTP request. Multi-search is also known as federated search. - name: Experimental features description: >- The `/experimental-features` route allows you to activate or deactivate some of Meilisearch's experimental features. This route is **synchronous**. This means that no task object will be returned, and any activated or deactivated features will be made available or unavailable immediately. - name: Network description: >- The `/network` route allows you to describe the topology of a network of Meilisearch instances. This route is **synchronous**. This means that no task object will be returned, and any change to the network will be made available immediately. - name: Webhooks description: >- The `/webhooks` route allows you to register endpoints to be called once tasks are processed. - name: Dynamic search rules description: >- The `/dynamic-search-rules` route allows you to configure dynamic search rules. paths: /indexes/{index_uid}/settings: get: tags: - Settings summary: List all settings description: >- Returns all settings of the index. Each setting is returned with its current value or the default if not set. operationId: get_all parameters: - name: index_uid in: path description: Unique identifier of the index. required: true schema: type: string example: movies responses: '200': description: >- Returns all settings with their current or default values. Same structure as the PATCH request body. content: application/json: schema: $ref: '#/components/schemas/Settings_Unchecked' example: displayedAttributes: - id - title - description - url searchableAttributes: - title - description filterableAttributes: - release_date - genre sortableAttributes: - release_date rankingRules: - words - typo - proximity - attributeRank - sort - wordPosition - exactness stopWords: - the - a nonSeparatorTokens: - '@' - '#' separatorTokens: - '|' dictionary: - J. R. R. synonyms: phone: - iPhone distinctAttribute: null typoTolerance: enabled: true minWordSizeForTypos: oneTypo: 5 twoTypos: 9 disableOnWords: [] disableOnAttributes: - title disableOnNumbers: false faceting: maxValuesPerFacet: 100 sortFacetValuesBy: genre: count pagination: maxTotalHits: 1000 proximityPrecision: byWord embedders: default: source: openAi model: text-embedding-3-small documentTemplate: '{{doc.title}}: {{doc.overview}}' searchCutoffMs: null localizedAttributes: - locales: - jpn attributePatterns: - '*_ja' facetSearch: true prefixSearch: indexingTime chat: description: A comprehensive movie database documentTemplateMaxBytes: 400 searchParameters: limit: 20 '401': description: The authorization header is missing. content: application/json: schema: $ref: '#/components/schemas/ResponseError' example: 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 '404': description: Index not found. content: application/json: schema: $ref: '#/components/schemas/ResponseError' example: message: Index `movies` not found. code: index_not_found type: invalid_request link: https://docs.meilisearch.com/errors#index_not_found security: - Bearer: - settings.get - settings.* - '*' x-codeSamples: - lang: cURL source: |- curl \ -X GET 'MEILISEARCH_URL/indexes/movies/settings' - lang: JS source: client.index('movies').getSettings() - lang: PHP source: $client->index('movies')->getSettings(); - lang: Python source: client.index('movies').get_settings() - lang: Java source: client.index("movies").getSettings(); - lang: Ruby source: client.index('movies').settings - lang: Go source: client.Index("movies").GetSettings() - lang: C# source: await client.Index("movies").GetSettingsAsync(); - lang: Rust source: |- let settings: Settings = client .index("movies") .get_settings() .await .unwrap(); - lang: Dart source: await client.index('movies').getSettings(); - lang: Swift source: |- client.index("movies").getSettings { (result) in switch result { case .success(let setting): print(setting) case .failure(let error): print(error) } } components: schemas: Settings_Unchecked: type: object description: >- Index settings: every option you can configure for search and index behavior. Used as the request body for PATCH settings. Only the fields you send are updated; pass `null` to reset a setting to its default. See also: [Configuring index settings on the Cloud](https://www.meilisearch.com/docs/learn/configuration/configuring_index_settings). properties: displayedAttributes: type: - array - 'null' items: type: string description: >- Fields returned in search results. Affects only search endpoints, not get-document endpoints. See [displayed and searchable attributes](https://www.meilisearch.com/docs/learn/relevancy/displayed_searchable_attributes). example: - id - title - description - url default: - '*' searchableAttributes: type: - array - 'null' items: type: string description: >- Fields searched for query words, in order of importance. Defines [attribute ranking order](https://www.meilisearch.com/docs/learn/relevancy/attribute_ranking_order). See [displayed and searchable attributes](https://www.meilisearch.com/docs/learn/relevancy/displayed_searchable_attributes). example: - title - description default: - '*' filterableAttributes: type: - array - 'null' items: $ref: '#/components/schemas/FilterableAttributesRule' description: >- Attributes that can be used as [filters](https://www.meilisearch.com/docs/learn/filtering_and_sorting/filter_search_results) and [facets](https://www.meilisearch.com/docs/learn/filtering_and_sorting/search_with_facet_filters). Strings or objects with `attributePatterns` and `features`. example: - release_date - genre default: [] sortableAttributes: type: - array - 'null' items: type: string description: >- Attributes that can be used to [sort search results](https://www.meilisearch.com/docs/learn/filtering_and_sorting/sort_search_results). example: - release_date default: [] foreignKeys: type: - array - 'null' items: $ref: '#/components/schemas/ForeignKey' description: Foreign keys to use for cross-index filtering search. example: - foreignIndexUid: products fieldName: productId rankingRules: type: - array - 'null' items: type: string description: >- [Ranking rules](https://www.meilisearch.com/docs/learn/relevancy/ranking_rules) in order of importance. Built-in rules and custom sort rules (`attribute:asc` or `attribute:desc`). example: - words - typo - proximity - attributeRank - sort - wordPosition - exactness default: - words - typo - proximity - attributeRank - sort - wordPosition - exactness stopWords: type: - array - 'null' items: type: string description: Words ignored when present in search queries. example: - the - a default: [] nonSeparatorTokens: type: - array - 'null' items: type: string description: >- Characters that are not treated as word separators. Removed from the default separator set. example: - '@' - '#' default: [] separatorTokens: type: - array - 'null' items: type: string description: >- Characters that delimit words. Added on top of the default separators. example: - '|' default: [] dictionary: type: - array - 'null' items: type: string description: >- Strings Meilisearch parses as a single term. Useful for names or domain terms. example: - J. R. R. default: [] synonyms: type: - object - 'null' description: >- Pairs of words or phrases treated as equivalent for search. Key maps to an array of [synonyms](https://www.meilisearch.com/docs/learn/relevancy/synonyms). default: {} additionalProperties: type: array items: type: string propertyNames: type: string example: phone: - iPhone distinctAttribute: type: - string - 'null' description: >- Field whose value must be unique in the returned documents. One document per distinct value. See [distinct attribute](https://www.meilisearch.com/docs/learn/relevancy/distinct_attribute). example: sku proximityPrecision: type: - string - 'null' description: >- Precision for the proximity ranking rule and phrase search: `byWord` (exact distance) or `byAttribute` (same attribute). default: byWord example: byWord typoTolerance: oneOf: - type: 'null' - $ref: '#/components/schemas/TypoSettings' description: >- [Typo tolerance](https://www.meilisearch.com/docs/learn/relevancy/typo_tolerance_settings): enable/disable, minimum word length for typos, and where to disable it. default: enabled: true minWordSizeForTypos: oneTypo: 5 twoTypos: 9 disableOnWords: [] disableOnAttributes: [] disableOnNumbers: false faceting: oneOf: - type: 'null' - $ref: '#/components/schemas/FacetingSettings' description: >- Related to [faceting](https://www.meilisearch.com/docs/learn/filtering_and_sorting/search_with_facet_filters): max facet values per facet and how facet values are sorted. default: maxValuesPerFacet: 100 sortFacetValuesBy: '*': alpha pagination: oneOf: - type: 'null' - $ref: '#/components/schemas/PaginationSettings' description: >- Related to [pagination](https://www.meilisearch.com/docs/guides/front_end/pagination): maximum number of results a search can return. default: maxTotalHits: 1000 embedders: type: - object - 'null' description: >- [Embedders](https://www.meilisearch.com/docs/learn/ai_powered_search/getting_started_with_ai_search) used for semantic and [hybrid search](https://www.meilisearch.com/docs/learn/ai_powered_search/getting_started_with_ai_search). Map of embedder name to config (`source`, `model`, `documentTemplate`, etc.). default: {} additionalProperties: $ref: '#/components/schemas/EmbeddingSettings' propertyNames: type: string example: default: source: openAi model: text-embedding-3-small documentTemplate: '{{doc.title}}: {{doc.overview}}' searchCutoffMs: type: - integer - 'null' format: u-int64 description: >- Maximum duration of a search in milliseconds. If reached, the search stops and returns results computed so far. When null, 1500 ms is used. example: 1500 minimum: 0 localizedAttributes: type: - array - 'null' items: $ref: '#/components/schemas/LocalizedAttributesRuleView' description: >- Locales and attribute patterns for [language-specific tokenization](https://www.meilisearch.com/docs/learn/resources/language). Affects searchable, filterable, and sortable attributes. example: - locales: - jpn attributePatterns: - '*_ja' default: [] facetSearch: type: - boolean - 'null' description: >- When true, [facet search](https://www.meilisearch.com/docs/learn/filtering_and_sorting/search_with_facet_filters) is enabled. When false, the facet-search endpoint is disabled. default: true example: true prefixSearch: oneOf: - type: 'null' - $ref: '#/components/schemas/PrefixSearchSettings' description: >- When to compute prefix matches: `indexingTime` or `disabled`. `disabled` speeds up indexing but reduces relevancy. default: indexingTime chat: oneOf: - type: 'null' - $ref: '#/components/schemas/ChatSettings' description: >- [Chat (conversation)](https://www.meilisearch.com/docs/learn/chat/getting_started_with_chat) settings: index description, document template, and search parameters used when the LLM queries this index. default: {} ResponseError: type: object required: - message - code - type - link properties: message: type: string description: The error message. code: $ref: '#/components/schemas/Code' description: The error code. type: $ref: '#/components/schemas/ErrorType' description: The error type. link: type: string description: A link to the documentation about this specific error. FilterableAttributesRule: oneOf: - type: string - $ref: '#/components/schemas/FilterableAttributesPatterns' ForeignKey: type: object required: - foreignIndexUid - fieldName properties: foreignIndexUid: type: string fieldName: type: string additionalProperties: false TypoSettings: type: object description: 'Typo tolerance: how spelling mistakes in queries are handled.' properties: enabled: type: - boolean - 'null' description: >- When true, typo tolerance is enabled. When false, only exact matches are returned. default: true example: true minWordSizeForTypos: oneOf: - type: 'null' - $ref: '#/components/schemas/MinWordSizeTyposSetting' description: >- Minimum word length before typos are allowed. Contains `oneTypo` (min length for 1 typo) and `twoTypos` (min length for 2 typos). Example: `{ "oneTypo": 5, "twoTypos": 9 }`. default: oneTypo: 5 twoTypos: 9 disableOnWords: type: - array - 'null' items: type: string description: >- Words for which typo tolerance is disabled. Use for brand names or terms that must match exactly. example: - iPhone - phone default: [] uniqueItems: true disableOnAttributes: type: - array - 'null' items: type: string description: >- Attributes for which typo tolerance is disabled. Those attributes only return exact matches. Useful for fields like product codes or IDs. example: - uuid - url default: [] uniqueItems: true disableOnNumbers: type: - boolean - 'null' description: >- When true, typo tolerance is disabled on numeric tokens. For example, 123 will not match 132. default: false example: false additionalProperties: false FacetingSettings: type: object description: 'Faceting: maximum number of facet values and how they are sorted.' properties: maxValuesPerFacet: type: - integer - 'null' description: >- Maximum number of facet values returned per facet. Values are sorted in ascending lexicographical order. default: 100 example: 100 minimum: 0 sortFacetValuesBy: type: - object - 'null' description: >- Sort order per facet: by descending count (`count`) or ascending alphanumeric (`alpha`). Key `*` applies to all facets. default: '*': alpha additionalProperties: $ref: '#/components/schemas/FacetValuesSort' propertyNames: type: string example: '*': alpha additionalProperties: false PaginationSettings: type: object description: 'Pagination: cap on how many results a search can return.' properties: maxTotalHits: type: - integer - 'null' description: >- Maximum number of search results Meilisearch can return. Limit and offset cannot go beyond this value. default: 1000 example: 1000 minimum: 0 additionalProperties: false EmbeddingSettings: type: object description: >- Embedder configuration for [AI-powered / hybrid search](https://www.meilisearch.com/docs/learn/ai_powered_search/getting_started_with_ai_search). properties: source: oneOf: - type: 'null' - $ref: '#/components/schemas/EmbedderSource' description: >- Embedding provider. - `openAi`: integration with OpenAI. Use `rest` for OpenAI-like APIs. - `huggingFace`: download a model from [Hugging Face](https://huggingface.co/), then compute embeddings on the local CPU/GPU. - `ollama`: integration with [ollama](https://ollama.com/). - `rest`: configurable integration with a remote embedder via its REST API. - `composite`: combine two embedding providers at indexing and search time. The generated embeddings must be **exactly the same** regardless of the embedding provider. - `userProvided`: manually provide embeddings in documents. - Determines which other fields are required or allowed. - 🏗️ Changing the value of this parameter always regenerates embeddings. default: openAi model: type: - string - 'null' description: >- Model name. - Available for `openAi`, `huggingFace`, `ollama`. - Mandatory for `ollama`. - For `openAi`/`huggingFace` optional with defaults. - 🏗️ Changing the value of this parameter always regenerates embeddings. example: text-embedding-3-small revision: type: - string - 'null' description: >- Model revision (e.g. Hugging Face commit SHA). - Only available for `huggingFace`. - If unset, latest is used. - 🏗️ Changing the value of this parameter always regenerates embeddings pooling: oneOf: - type: 'null' - $ref: '#/components/schemas/OverridePooling' description: >- Pooling method when computing embedding locally. - Only available for `huggingFace`. - `useModel`: automatically determine the pooling method depending on the chosen model (recommended). - `forceMean`: always use mean pooling. - `forceCls`: always use CLS pooling. - 🏗️ Changing the value of this parameter always regenerates embeddings default: useModel apiKey: type: - string - 'null' description: >- API key sent to the embedder. - If not set for source `openAi`, the key is read from the `OPENAI_API_KEY` then `MEILI_OPENAI_API_KEY` environment variables. - If not set for other sources, no bearer token is sent. - This setting is partially hidden when returned by the settings - 🌱 Changing the value of this parameter never regenerates embeddings dimensions: type: - integer - 'null' description: >- Number of dimensions of the embedding vectors. - Available for `userProvided`, `openAi`, `ollama`, `rest`. - Mandatory for `userProvided`. - For `openAi`/`ollama`/`rest` inferred if omitted. - 🏗️ For `openAi`, changing the value of this parameter always regenerates embeddings - 🌱 For other sources, changing the value of this parameter never regenerates embeddings example: 1536 minimum: 0 binaryQuantized: type: - boolean - 'null' description: >- When true, vectors are stored as 1-bit (smaller, faster, less precise). - Available for all sources. - Irreversible once enabled. - 🏗️ When set to true, embeddings are not regenerated, but they are binary quantized, which takes time. default: false documentTemplate: type: - string - 'null' description: >- [Liquid template](https://shopify.github.io/liquid/) to build the text sent to the embedder for each document. - Available for `openAi`, `huggingFace`, `ollama`, `rest`. - 🏗️ When modified, embeddings are regenerated for documents whose rendering through the template produces a different text. example: '{{doc.title}}: {{doc.overview}}' documentTemplateMaxBytes: type: - integer - 'null' description: >- Max size in bytes of the rendered document template. Longer output is truncated. - Available for `openAi`, `huggingFace`, `ollama`, `rest`. - 🏗️ When increased, embeddings are regenerated for documents whose rendering through the template produces a different text. - 🌱 When decreased, embeddings are never regenerated default: 400 example: 400 minimum: 0 url: type: - string - 'null' description: >- URL of the embedder API. - Mandatory for `rest`. Optional for `openAi` and `ollama`. - 🌱 When modified for `openAi``, embeddings are never regenerated - 🏗️ When modified for `ollama` and `rest`, embeddings are always regenerated - If targetting URL resolving to a non-global IP (such as `localhost`), make sure that `--experimental-allowed-ip-networks` allows it. For details on how use this parameter, refer to [this documentation](https://www.meilisearch.com/docs/learn/self_hosted/configure_meilisearch_at_launch#allow-requests-to-private-networks). example: http://localhost:11434/api/embeddings indexingFragments: type: - object - 'null' description: >- Fragments (with [Liquid](https://shopify.github.io/liquid/)) sent to the embedder at indexing time. For `rest` with multimodal; key is fragment name, value the payload. See also [Image search with multimodal embeddings](https://www.meilisearch.com/docs/learn/ai_powered_search/image_search_with_multimodal_embeddings) - 🏗️ When a fragment is deleted by passing `null` to its name, the corresponding embeddings are removed from documents. - 🏗️ When a fragment is modified, the corresponding embeddings are regenerated if their rendered version changes. default: {} additionalProperties: {} propertyNames: type: string searchFragments: type: - object - 'null' description: >- Fragments (with [Liquid](https://shopify.github.io/liquid/)) sent to the embedder at search time. For `rest` with multimodal. See also [Image search with multimodal embeddings](https://www.meilisearch.com/docs/learn/ai_powered_search/image_search_with_multimodal_embeddings) - 🌱 Changing the value of this parameter never regenerates embeddings default: {} additionalProperties: {} propertyNames: type: string request: description: >- Request body template for `rest` embedder. See also [Configure a REST embedder](https://www.meilisearch.com/docs/learn/ai_powered_search/configure_rest_embedder) - Use `"{{text}}"` for the input. - Mandatory for `rest`. - 🏗️ Changing the value of this parameter always regenerates embeddings response: description: >- Response template for `rest` embedder. See also [Configure a REST embedder](https://www.meilisearch.com/docs/learn/ai_powered_search/configure_rest_embedder) - Use `"{{embedding}}"` where the embedding array is. - Mandatory for `rest`. headers: type: - object - 'null' description: >- Extra HTTP headers sent to the embedder. - Available for `rest`. - 🌱 Changing the value of this parameter never regenerates embeddings additionalProperties: type: string propertyNames: type: string searchEmbedder: oneOf: - type: 'null' - $ref: '#/components/schemas/SubEmbeddingSettings' description: >- Embedder used at search time when using a composite embedder. Same sub-parameters as a top-level embedder (`source`, `model`, `url`, etc.); no `documentTemplate`/`documentTemplateMaxBytes`. indexingEmbedder: oneOf: - type: 'null' - $ref: '#/components/schemas/SubEmbeddingSettings' description: >- Embedder used at indexing time when using a composite embedder. Same sub-parameters as a top-level embedder (`source`, `model`, `documentTemplate`, `url`, etc.). distribution: oneOf: - type: 'null' - $ref: '#/components/schemas/DistributionShift' description: >- Affine transform (mean, sigma) applied to the semantic score to make it more comparable with the ranking score. See also [this article](https://www.meilisearch.com/blog/fixing-hybrid-search#making-the-scores-comparable). - Available for all sources. - 🌱 Changing the value of this parameter never regenerates embeddings additionalProperties: false LocalizedAttributesRuleView: type: object description: >- Defines a rule for associating specific locales (languages) with attributes. This allows Meilisearch to use language-specific tokenization and processing for matched attributes, improving search quality for multilingual content. required: - attributePatterns - locales properties: attributePatterns: type: array items: type: string description: >- Patterns to match attribute names. Use `*` as a wildcard to match any characters. For example, `["title_*", "description"]` matches `title_en`, `title_fr`, and `description`. example: - '*_ja' locales: type: array items: $ref: '#/components/schemas/Locale' description: >- The list of locales (languages) to apply to matching attributes. When these attributes are indexed, Meilisearch will use language-specific tokenization rules. Examples: `["en", "fr"]` or `["jpn", "zho"]`. PrefixSearchSettings: type: string enum: - indexingTime - disabled ChatSettings: type: object description: >- [Chat (conversation)](https://www.meilisearch.com/docs/learn/chat/getting_started_with_chat) settings: how the index is described to the LLM and how it is queried. properties: description: type: - string - 'null' description: >- Index description shown to the LLM so it can decide when and how to query this index. default: '' example: >- A comprehensive movie database containing titles, overviews, genres, and release dates documentTemplate: type: - string - 'null' description: >- Liquid template that defines the text sent to the LLM for each document. example: >- {% for field in fields %}{% if field.is_searchable and field.value != nil %}{{ field.name }}: {{ field.value }} {% endif %}{% endfor %} documentTemplateMaxBytes: type: - integer - 'null' description: >- Maximum size in bytes of the rendered document template. Longer text is truncated. default: 400 example: 400 minimum: 0 searchParameters: oneOf: - type: 'null' - $ref: '#/components/schemas/ChatSearchParams' description: >- Search parameters used when the LLM queries this index (`hybrid`, `limit`, `sort`, `distinct`, etc.). default: {} additionalProperties: false Code: type: string enum: - api_key_already_exists - api_key_not_found - bad_parameter - bad_request - database_size_limit_reached - document_not_found - dump_already_processing - dump_not_found - dump_process_failed - duplicate_index_found - immutable_api_key_actions - immutable_api_key_created_at - immutable_api_key_expires_at - immutable_api_key_indexes - immutable_api_key_key - immutable_api_key_uid - immutable_api_key_updated_at - immutable_index_created_at - immutable_index_updated_at - import_task_already_received - import_task_unknown_remote - receive_import_finished_unknown_remote - import_task_without_network_task - index_already_exists - index_creation_failed - index_not_found - index_primary_key_already_exists - index_primary_key_multiple_candidates_found - index_primary_key_no_candidate_found - internal - invalid_api_key - invalid_api_key_actions - invalid_api_key_description - invalid_api_key_expires_at - invalid_api_key_indexes - invalid_api_key_limit - invalid_api_key_name - invalid_api_key_offset - invalid_api_key_uid - invalid_content_type - invalid_document_csv_delimiter - invalid_document_fields - invalid_document_retrieve_vectors - missing_document_filter - missing_document_edition_function - inconsistent_document_change_headers - invalid_document_filter - invalid_document_sort - invalid_document_geo_field - invalid_document_geojson_field - invalid_header_value - invalid_vector_dimensions - invalid_vectors_type - invalid_document_id - invalid_document_ids - invalid_document_limit - invalid_document_offset - invalid_search_embedder - invalid_similar_embedder - invalid_search_hybrid_query - invalid_index_limit - invalid_index_offset - invalid_index_primary_key - invalid_index_custom_metadata - invalid_skip_creation - invalid_index_uid - invalid_multi_search_facets - invalid_multi_search_facets_by_index - invalid_multi_search_facet_order - invalid_multi_search_query_personalization - invalid_multi_search_query_show_performance_details - invalid_multi_search_federated - invalid_multi_search_federation_options - invalid_multi_search_max_values_per_facet - invalid_multi_search_merge_facets - invalid_multi_search_query_facets - invalid_multi_search_distinct - invalid_multi_search_query_pagination - invalid_multi_search_query_ranking_rules - invalid_multi_search_query_position - invalid_multi_search_remote - invalid_multi_search_weight - invalid_network_leader - invalid_network_remotes - invalid_network_shards - invalid_network_self - invalid_network_search_api_key - invalid_network_write_api_key - invalid_network_url - invalid_search_attributes_to_search_on - invalid_search_attributes_to_crop - invalid_search_attributes_to_highlight - invalid_similar_attributes_to_retrieve - invalid_similar_retrieve_vectors - invalid_search_attributes_to_retrieve - invalid_search_ranking_score_threshold - invalid_similar_ranking_score_threshold - invalid_search_retrieve_vectors - invalid_search_crop_length - invalid_search_crop_marker - invalid_search_facets - invalid_search_semantic_ratio - invalid_search_locales - invalid_facet_search_exhaustive_facet_count - invalid_facet_search_facet_name - invalid_similar_id - invalid_search_filter - invalid_similar_filter - invalid_search_highlight_post_tag - invalid_search_highlight_pre_tag - invalid_search_hits_per_page - invalid_similar_limit - invalid_search_limit - invalid_search_matching_strategy - invalid_similar_offset - invalid_search_offset - invalid_search_page - invalid_search_q - invalid_facet_search_query - invalid_facet_search_name - facet_search_disabled - invalid_search_vector - invalid_search_media - invalid_search_show_matches_position - invalid_search_show_ranking_score - invalid_similar_show_ranking_score - invalid_search_show_ranking_score_details - invalid_search_show_performance_details - invalid_search_use_network - invalid_similar_show_ranking_score_details - invalid_similar_show_performance_details - invalid_search_sort - invalid_search_distinct - invalid_search_personalize - invalid_search_personalize_user_context - invalid_search_media_and_vector - invalid_settings_displayed_attributes - invalid_settings_distinct_attribute - invalid_settings_proximity_precision - invalid_settings_facet_search - invalid_settings_prefix_search - invalid_settings_faceting - invalid_settings_filterable_attributes - invalid_settings_foreign_keys - invalid_settings_pagination - invalid_settings_search_cutoff_ms - invalid_settings_embedders - invalid_settings_ranking_rules - invalid_settings_searchable_attributes - invalid_settings_sortable_attributes - invalid_settings_stop_words - invalid_settings_non_separator_tokens - invalid_settings_separator_tokens - invalid_settings_dictionary - invalid_settings_synonyms - invalid_settings_typo_tolerance - invalid_settings_localized_attributes - invalid_state - invalid_store_file - invalid_swap_duplicate_index_found - invalid_swap_indexes - invalid_swap_rename - invalid_task_after_enqueued_at - invalid_task_after_finished_at - invalid_task_after_started_at - invalid_task_before_enqueued_at - invalid_task_before_finished_at - invalid_task_before_started_at - invalid_task_canceled_by - invalid_task_from - invalid_task_limit - invalid_task_reverse - invalid_task_statuses - invalid_task_types - invalid_task_uids - invalid_batch_uids - io_error - feature_not_enabled - malformed_payload - max_fields_limit_exceeded - missing_api_key_actions - missing_api_key_expires_at - missing_api_key_indexes - missing_authorization_header - missing_content_type - missing_document_id - missing_facet_search_facet_name - missing_index_uid - missing_master_key - missing_network_url - missing_payload - missing_search_hybrid - missing_swap_indexes - missing_task_filters - network_version_mismatch - no_space_left_on_device - not_leader - payload_too_large - remote_bad_response - remote_bad_request - remote_could_not_send_request - remote_invalid_api_key - remote_remote_error - remote_timeout - too_many_search_requests - task_not_found - task_file_not_found - batch_not_found - too_many_open_files - too_many_vectors - unexpected_network_previous_remotes - network_version_too_old - unprocessed_network_task - unretrievable_document - unretrievable_error_code - unsupported_media_type - invalid_s3_snapshot_request - invalid_s3_snapshot_parameters - s3_snapshot_server_error - vector_embedding_error - not_found_similar_id - invalid_document_edition_context - invalid_document_edition_function_filter - edit_documents_by_function_error - invalid_settings_index_chat - invalid_export_url - invalid_export_api_key - invalid_export_payload_size - invalid_export_indexes_patterns - invalid_export_index_filter - invalid_export_index_override_settings - unimplemented_external_function_calling - unimplemented_non_streaming_chat_completions - unimplemented_multi_choice_chat_completions - chat_not_found - invalid_chat_setting_document_template - invalid_chat_completion_org_id - invalid_chat_completion_project_id - invalid_chat_completion_api_version - invalid_chat_completion_deployment_id - invalid_chat_completion_source - invalid_chat_completion_base_api - invalid_chat_completion_api_key - invalid_chat_completion_prompts - invalid_chat_completion_system_prompt - invalid_chat_completion_search_description_prompt - invalid_chat_completion_search_query_param_prompt - invalid_chat_completion_search_filter_param_prompt - invalid_chat_completion_search_index_uid_param_prompt - invalid_chat_completion_pre_query_prompt - invalid_index_fields_filter - invalid_index_fields_filter_attribute_patterns - invalid_index_fields_filter_displayed - invalid_index_fields_filter_searchable - invalid_index_fields_filter_sortable - invalid_index_fields_filter_distinct - invalid_index_fields_filter_ranking_rule - invalid_index_fields_filter_filterable - requires_enterprise_edition - invalid_webhooks - invalid_webhook_url - invalid_webhook_headers - immutable_webhook - invalid_webhook_uuid - webhook_not_found - immutable_webhook_uuid - immutable_webhook_is_editable - invalid_dynamic_search_rule_offset - invalid_dynamic_search_rule_limit - invalid_dynamic_search_rule_filter - invalid_dynamic_search_rule_description - invalid_dynamic_search_rule_priority - invalid_dynamic_search_rule_active - invalid_dynamic_search_rule_conditions - invalid_dynamic_search_rule_actions - invalid_dynamic_search_rule_filter_attribute_patterns - invalid_dynamic_search_rule_filter_active - dynamic_search_rule_not_found ErrorType: type: string enum: - internal - invalid_request - auth - system FilterableAttributesPatterns: type: object description: |- Defines a set of attribute patterns with specific filtering and faceting features. This allows fine-grained control over which operations are allowed on matched attributes. required: - attributePatterns properties: attributePatterns: type: array items: type: string description: >- Patterns to match attribute names. Use `*` as a wildcard to match any characters. For example, `["price_*", "stock"]` matches `price_usd`, `price_eur`, and `stock`. features: $ref: '#/components/schemas/FilterableAttributesFeatures' description: |- The filtering and faceting features enabled for attributes matching these patterns. If not specified, defaults to equality filtering enabled. additionalProperties: false MinWordSizeTyposSetting: type: object description: >- Minimum word length required before typos are allowed. This helps prevent matching very short words with typos, which can lead to irrelevant results. properties: oneTypo: type: - integer - 'null' format: u-int8 description: >- Minimum word length to accept one typo. Shorter words must match exactly. For example, if set to 5, "apple" can have one typo but "app" cannot. default: 5 example: 5 minimum: 0 twoTypos: type: - integer - 'null' format: u-int8 description: >- Minimum word length to accept two typos. Must be greater than or equal to `oneTypo`. For example, if set to 9, "computing" can have two typos. default: 9 example: 9 minimum: 0 additionalProperties: false FacetValuesSort: type: string enum: - alpha - count EmbedderSource: type: string enum: - openAi - huggingFace - ollama - userProvided - rest - composite OverridePooling: type: string enum: - useModel - forceCls - forceMean SubEmbeddingSettings: type: object description: >- Sub-embedder config for composite embedders. Used by `indexingEmbedder` (vectorize documents at index time) and `searchEmbedder` (vectorize queries at search time). Same fields as a top-level embedder, except no `binaryQuantized`, `distribution`, `documentTemplate`/`documentTemplateMaxBytes` for searchEmbedder. properties: source: oneOf: - type: 'null' - $ref: '#/components/schemas/EmbedderSource' description: >- Embedding provider. - `openAi`: integration with OpenAI. Use `rest` for OpenAI-like APIs. - `huggingFace`: download a model from [Hugging Face](https://huggingface.co/), then compute embeddings on the local CPU/GPU. - `ollama`: integration with [ollama](https://ollama.com/). - `rest`: configurable integration with a remote embedder via its REST API. - `userProvided`: manually provide embeddings in documents. - Determines which other fields are required or allowed. - 🏗️ Changing the value of this parameter always regenerates embeddings. default: openAi model: type: - string - 'null' description: >- Model name. - Available for `openAi`, `huggingFace`, `ollama`. - Mandatory for `ollama`. - For `openAi`/`huggingFace` optional with defaults. - 🏗️ Changing the value of this parameter always regenerates embeddings. example: text-embedding-3-small revision: type: - string - 'null' description: >- Model revision (e.g. Hugging Face commit SHA). - Only available for `huggingFace`. - If unset, latest is used. - 🏗️ Changing the value of this parameter always regenerates embeddings example: 617ca489d9e86b49b8167676d8220688b99db36e pooling: oneOf: - type: 'null' - $ref: '#/components/schemas/OverridePooling' description: >- Pooling method when computing embedding locally. - Only available for `huggingFace`. - `useModel`: automatically determine the pooling method depending on the chosen model (recommended). - `forceMean`: always use mean pooling. - `forceCls`: always use CLS pooling. - 🏗️ Changing the value of this parameter always regenerates embeddings default: useModel apiKey: type: - string - 'null' description: >- API key sent to the embedder. - If not set for source `openAi`, the key is read from the `OPENAI_API_KEY` then `MEILI_OPENAI_API_KEY` environment variables. - If not set for other sources, no bearer token is sent. - This setting is partially hidden when returned by the settings - 🌱 Changing the value of this parameter never regenerates embeddings example: your-api-key dimensions: type: - integer - 'null' description: >- Number of dimensions of the embedding vectors. - Available for `userProvided`, `openAi`, `ollama`, `rest`. - Mandatory for `userProvided`. - For `openAi`/`ollama`/`rest` inferred if omitted. - 🏗️ For `openAi`, changing the value of this parameter always regenerates embeddings - 🌱 For other sources, changing the value of this parameter never regenerates embeddings example: 1536 minimum: 0 documentTemplate: type: - string - 'null' description: >- [Liquid template](https://shopify.github.io/liquid/) to build the text sent to the embedder for each document. - Only available for `indexingEmbedder`, not `searchEmbedder`. - Available for `openAi`, `huggingFace`, `ollama`, `rest`. - 🏗️ When modified, embeddings are regenerated for documents whose rendering through the template produces a different text. example: '{{doc.title}}: {{doc.overview}}' documentTemplateMaxBytes: type: - integer - 'null' description: >- Max size in bytes of the rendered document template. Longer output is truncated. - Only available for `indexingEmbedder`, not `searchEmbedder`. - Available for `openAi`, `huggingFace`, `ollama`, `rest`. - 🏗️ When increased, embeddings are regenerated for documents whose rendering through the template produces a different text. - 🌱 When decreased, embeddings are never regenerated default: 400 example: 400 minimum: 0 url: type: - string - 'null' description: >- URL of the embedder API. - Mandatory for `rest`. Optional for `openAi` and `ollama`. - 🌱 When modified for `openAi``, embeddings are never regenerated - 🏗️ When modified for `ollama` and `rest`, embeddings are always regenerated - If targetting URL resolving to a non-global IP (such as `localhost`), make sure that `--experimental-allowed-ip-networks` allows it. For details on how use this parameter, refer to [this documentation](https://www.meilisearch.com/docs/learn/self_hosted/configure_meilisearch_at_launch#allow-requests-to-private-networks). example: http://localhost:11434/api/embeddings indexingFragments: type: - object - 'null' description: >- Fragments (with [Liquid](https://shopify.github.io/liquid/)) sent to the embedder at indexing time. For `rest` with multimodal; key is fragment name, value the payload. See also [Image search with multimodal embeddings](https://www.meilisearch.com/docs/learn/ai_powered_search/image_search_with_multimodal_embeddings) - Only available for `indexingEmbedder`, not `searchEmbedder`. - 🏗️ When a fragment is deleted by passing `null` to its name, the corresponding embeddings are removed from documents. - 🏗️ When a fragment is modified, the corresponding embeddings are regenerated if their rendered version changes. default: {} additionalProperties: {} propertyNames: type: string searchFragments: type: - object - 'null' description: >- Fragments (with [Liquid](https://shopify.github.io/liquid/)) sent to the embedder at search time. For `rest` with multimodal. See also [Image search with multimodal embeddings](https://www.meilisearch.com/docs/learn/ai_powered_search/image_search_with_multimodal_embeddings) - 🌱 Changing the value of this parameter never regenerates embeddings default: {} additionalProperties: {} propertyNames: type: string request: description: >- Request body template for `rest` embedder. See also [Configure a REST embedder](https://www.meilisearch.com/docs/learn/ai_powered_search/configure_rest_embedder) - Use `"{{text}}"` for the input. - Mandatory for `rest`. - 🏗️ Changing the value of this parameter always regenerates embeddings response: description: >- Response template for `rest` embedder. See also [Configure a REST embedder](https://www.meilisearch.com/docs/learn/ai_powered_search/configure_rest_embedder) - Use `"{{embedding}}"` where the embedding array is. - Mandatory for `rest`. headers: type: - object - 'null' description: >- Extra HTTP headers sent to the embedder. - Available for `rest`. - 🌱 Changing the value of this parameter never regenerates embeddings additionalProperties: type: string propertyNames: type: string additionalProperties: false DistributionShift: type: object description: >- Describes the mean and sigma of distribution of embedding similarity in the embedding space. The intended use is to make the similarity score more comparable to the regular ranking score. This allows to correct effects where results are too "packed" around a certain value. required: - current_mean - current_sigma properties: current_mean: type: number format: float description: >- Value where the results are "packed". Similarity scores are translated so that they are packed around 0.5 instead current_sigma: type: number format: float description: >- standard deviation of a similarity score. Set below 0.4 to make the results less packed around the mean, and above 0.4 to make them more packed. Locale: type: string enum: - af - ak - am - ar - az - be - bn - bg - ca - cs - da - de - el - en - eo - et - fi - fr - gu - he - hi - hr - hu - hy - id - it - jv - ja - kn - ka - km - ko - la - lv - lt - ml - mr - mk - my - ne - nl - nb - or - pa - fa - pl - pt - ro - ru - si - sk - sl - sn - es - sr - sv - ta - te - tl - th - tk - tr - uk - ur - uz - vi - yi - zh - zu - afr - aka - amh - ara - aze - bel - ben - bul - cat - ces - dan - deu - ell - eng - epo - est - fin - fra - guj - heb - hin - hrv - hun - hye - ind - ita - jav - jpn - kan - kat - khm - kor - lat - lav - lit - mal - mar - mkd - mya - nep - nld - nob - ori - pan - pes - pol - por - ron - rus - sin - slk - slv - sna - spa - srp - swe - tam - tel - tgl - tha - tuk - tur - ukr - urd - uzb - vie - yid - zho - zul - cmn ChatSearchParams: type: object description: Search parameters applied when the LLM queries this index. properties: hybrid: oneOf: - type: 'null' - $ref: '#/components/schemas/HybridQuery' description: >- Hybrid search: mix of keyword and semantic search. Requires an embedder (set via `embedder` and optionally `semanticRatio`). limit: type: - integer - 'null' description: >- Maximum number of documents returned per search performed by the LLM. example: 20 minimum: 0 sort: type: - array - 'null' items: type: string description: >- Sort order: array of strings like `attribute:asc` or `attribute:desc`. example: - price:asc - rating:desc distinct: type: - string - 'null' description: Attribute used to return at most one document per distinct value. example: sku matchingStrategy: oneOf: - type: 'null' - $ref: '#/components/schemas/MatchingStrategy' description: 'How query terms are matched: `last`, `all`, or `frequency`.' attributesToSearchOn: type: - array - 'null' items: type: string description: >- Attributes on which to run the search. If unset, all searchable attributes are used. example: - title - description rankingScoreThreshold: oneOf: - type: 'null' - $ref: '#/components/schemas/RankingScoreThreshold' description: >- Minimum ranking score (0.0–1.0) for a document to be included. Lower scores are excluded. additionalProperties: false FilterableAttributesFeatures: type: object description: >- Controls which filtering and faceting operations are enabled for matching attributes. This allows restricting certain operations on specific fields for security or performance reasons. properties: facetSearch: type: boolean description: |- When `true`, allows searching within facet values for matching attributes. This enables the facet search feature which lets users search for specific facet values. Defaults to `false`. filter: $ref: '#/components/schemas/FilterFeatures' description: |- Controls which filter operators are allowed for matching attributes. See `FilterFeatures` for available options. additionalProperties: false HybridQuery: type: object description: 'Hybrid search: balance between keyword and semantic search.' required: - embedder properties: semanticRatio: type: number format: float description: Balance between keyword (0.0) and semantic (1.0) search. example: 0.5 embedder: type: string description: >- Name of the embedder from the index embedders setting (`embedder` in JSON). Used to vectorize the query. example: default MatchingStrategy: type: string description: >- This is unfortunately a duplication of the struct in . The reason why it is duplicated is because milli cannot depend on meilisearch. It would be cyclic imports. enum: - last - all - frequency RankingScoreThreshold: type: number format: double FilterFeatures: type: object description: |- Controls which filter operators are allowed for an attribute. This provides fine-grained control over filtering capabilities. properties: equality: type: boolean description: |- When `true`, enables equality operators: `=`, `!=`, and `IN`. These allow filtering for exact matches or membership in a set of values. Also enables `IS EMPTY`, `IS NULL`, and `EXISTS` operators. Defaults to `true`. comparison: type: boolean description: |- When `true`, enables comparison operators: `<`, `>`, `<=`, `>=`, and `TO` (range). These allow filtering based on numeric or string comparisons. Defaults to `false`. additionalProperties: false securitySchemes: Bearer: type: http scheme: bearer bearerFormat: Uuidv4, string or JWT description: >- An API key is a token that you provide when making API calls. Read more about [how to secure your project](https://www.meilisearch.com/docs/learn/security/basic_security). Include the API key to the `Authorization` header, for instance: ```bash -H 'Authorization: Bearer 6436fc5237b0d6e0d64253fbaac21d135012ecf1' ``` If you use a SDK, ensure you instantiate the client with the API key, for instance with [JS SDK](https://github.com/meilisearch/meilisearch-js): ```js const client = new Meilisearch({ host: 'MEILISEARCH_URL', apiKey: '6436fc5237b0d6e0d64253fbaac21d135012ecf1' }); ``` ````