diff --git a/learn/ai_powered_search/search_with_user_provided_embeddings.mdx b/learn/ai_powered_search/search_with_user_provided_embeddings.mdx index 1fb3219ec..64e5d881a 100644 --- a/learn/ai_powered_search/search_with_user_provided_embeddings.mdx +++ b/learn/ai_powered_search/search_with_user_provided_embeddings.mdx @@ -28,6 +28,10 @@ curl \ }' ``` + +Embedders with `source: userProvided` are incompatible with `documentTemplate` and `documentTemplateMaxBytes`. + + ## Add documents to Meilisearch Next, use [the `/documents` endpoint](/reference/api/documents?utm_campaign=vector-search&utm_source=docs&utm_medium=vector-search-guide) to upload vectorized documents. Place vector data in your documents' `_vectors` field: diff --git a/reference/api/settings.mdx b/reference/api/settings.mdx index b13f4297f..6e355d52c 100644 --- a/reference/api/settings.mdx +++ b/reference/api/settings.mdx @@ -2668,7 +2668,7 @@ This field is incompatible with `rest` and `userProvided` embedders. ##### `documentTemplate` -`documentTemplate` is a string containing a [Liquid template](https://shopify.github.io/liquid/basics/introduction). Meillisearch interpolates the template for each document and sends the resulting text to the embedder. The embedder then generates document vectors based on this text. +`documentTemplate` is a string containing a [Liquid template](https://shopify.github.io/liquid/basics/introduction). When using an embedding generation service such as OpenAI, Meillisearch interpolates the template for each document and sends the resulting text to the embedder. The embedder then generates document vectors based on this text. If used with a custom embedder, Meilisearch will return an error. You may use the following context values: diff --git a/snippets/samples/code_samples_export_post_1.mdx b/snippets/samples/code_samples_export_post_1.mdx index bd10c5882..c970a6365 100644 --- a/snippets/samples/code_samples_export_post_1.mdx +++ b/snippets/samples/code_samples_export_post_1.mdx @@ -13,4 +13,11 @@ curl \ } }' ``` + +```java Java +Map indexes = new HashMap<>(); +indexes.put("*", ExportIndexFilter.builder().overrideSettings(true).build()); +ExportRequest request = ExportRequest.builder().url("TARGET_INSTANCE_URL").indexes(indexes).build(); +client.export(request); +``` \ No newline at end of file