Merge pull request #978 from milvus-io/update-ref

update docs

API_Reference/milvus-sdk-java/v2.5.x/v2/Collections/CollectionSchema/addField.md

@@ -23,6 +23,9 @@ CollectionSchema.addField(AddFieldReq.builder()
     .maxCapacity(Integer maxCapacity)
     .isNullable(Boolean isNullable)
     .defaultValue(DataType dataType)
+    .enableAnalyzer(Boolean enableAnalyzer)
+    .enableMatch(Boolean enableMatch)
+    .analyzerParams(Map<String, Object>, analyzerParams)
 
     .build()
 )
@@ -110,6 +113,45 @@ CollectionSchema.addField(AddFieldReq.builder()
 
     Sets a default value for a specific field in a collection schema when creating it. This is particularly useful when you want certain fields to have an initial value even if no value is explicitly provided during data insertion.
 
+- `enableAnalyzer(Boolean enableAnalyzer)`
+
+    Whether to enable text analysis for the specified `VARCHAR` field. When set to `true`, it instructs Milvus to use a text analyzer, which tokenizes and filters the text content of the field.
+
+- `enableMatch(Boolean enableMatch)`
+
+    Whether to enable keyword matching for the specified `VARCHAR` field. When set to `true`, Milvus creates an inverted index for the field, allowing for quick and efficient keyword lookups. `enableMatch` works in conjunction with `enableAnalyzer` to provide structured term-based text search, with `enableAnalyzer` handling tokenization and `enableMatch` handling the search operations on these tokens.
+
+- `analyzerParams(Map<String, Object>, analyzerParams)`
+
+    Configures the analyzer for text processing, specifically for `DataType.VarChar` fields. This parameter configures tokenizer and filter settings, particularly for text fields used in [keyword matching](https://milvus.io/docs/keyword-match.md) or [full text search](https://milvus.io/docs/full-text-search.md). Depending on the type of analyzer, it can be configured in either of the following methods:
+
+    - Built-in analyzer
+
+        ```java
+        Map<String, Object> analyzerParams = new HashMap<>();
+        analyzerParams.put("type", "english");
+        ```
+
+        - `type` (*String*) -
+
+            Pre-configured analyzer type built into Milvus, which can be used out-of-the-box by specifying its name. Possible values: `standard`, `english`, `chinese`. For more information, refer to [Standard Analyzer](https://milvus.io/docs/standard-analyzer.md), [English Analyzer](https://milvus.io/docs/english-analyzer.md), and [Chinese Analyzer](https://milvus.io/docs/chinese-analyzer.md).
+
+    - Custom analyzer
+
+        ```java
+        Map<String, Object> analyzerParams = new HashMap<>();
+        analyzerParams.put("tokenizer", "standard");
+        analyzerParams.put("filter", Collections.singletonList("lowercase"));
+        ```
+
+        - `tokenizer` (*String*) -
+
+            Defines the tokenizer type. Possible values: `standard` (default), `whitespace`, `jieba`. For more information, refer to [Standard Tokenizer](https://milvus.io/docs/standard-tokenizer.md), [Whitespace Tokenizer](https://milvus.io/docs/whitespace-tokenizer.md), and [Jieba Tokenizer](https://milvus.io/docs/jieba-tokenizer.md).
+
+        - `filter` (*List\<String>*) -
+
+            Lists filters to refine tokens produced by the tokenizer, with options for built-in filters and custom filters. For more information, refer to [Alphanumonly Filter](https://milvus.io/docs/alphanumonly-filer.md) and others.
+
 **RETURNS:**
 
 *void*

API_Reference/milvus-sdk-java/v2.5.x/v2/Collections/CollectionSchema/addFunction.md

@@ -0,0 +1,73 @@
+# addFunction()
+
+This operation adds a function to convert raw data into vector representations.
+
+```java
+public CollectionSchema addFunction(Function function)
+```
+
+## Request Syntax
+
+```java
+addFunction(Function.builder()
+        .functionType(FunctionType functionType)
+        .name(String name)
+        .inputFieldNames(List<String> inputFieldNames)
+        .outputFieldNames(List<String> outputFieldNames)
+        .description(String description)
+        .build());
+```
+
+**BUILDER METHODS:**
+
+- `functionType(FunctionType functionType)`
+
+    The type of function for processing raw data. Possible values:
+
+    - `FunctionType.BM25`: Uses the BM25 algorithm for generating sparse embeddings from a `VARCHAR` field.
+
+- `name(String name)`
+
+    The name of the function. This identifier is used to reference the function within queries and collections.
+
+- `inputFieldNames(List<String> inputFieldNames)`
+
+    The name of the field containing the raw data that requires conversion to vector representation. For functions using `FunctionType.BM25`, this parameter accepts only one field name.
+
+- `outputFieldNames(List<String> outputFieldNames)`
+
+    The name of the field where the generated embeddings will be stored. This should correspond to a vector field defined in the collection schema. For functions using `FunctionType.BM25`, this parameter accepts only one field name.
+
+- `description(String description)`
+
+    A brief description of the function’s purpose. This can be useful for documentation or clarity in larger projects and defaults to an empty string.
+
+**RETURN TYPE:**
+
+*Function*
+
+**RETURNS:**
+
+A `Function` object
+
+**EXCEPTIONS:**
+
+- **MilvusClientExceptions**
+
+    This exception will be raised when any error occurs during this operation.
+
+## Example
+
+```java
+import io.milvus.common.clientenum.FunctionType;
+import io.milvus.v2.service.collection.request.CreateCollectionReq.Function;
+
+import java.util.*;
+
+schema.addFunction(Function.builder()
+        .functionType(FunctionType.BM25)
+        .name("text_bm25_emb")
+        .inputFieldNames(Collections.singletonList("text"))
+        .outputFieldNames(Collections.singletonList("vector"))
+        .build());
+```

API_Reference/milvus-sdk-java/v2.5.x/v2/Collections/Function.md

@@ -0,0 +1,69 @@
+# Function
+
+A `Function` instance for generating vector embeddings from user-provided raw data in Milvus.
+
+```java
+io.milvus.v2.service.collection.request.CreateCollectionReq.Function
+```
+
+## Constructor
+
+This constructor initializes a new `Function` instance designed to transform user's raw data into vector embeddings. This is achieved through an automated process that simplifies similarity search operations.
+
+```java
+CreateCollectionReq.Function.builder()
+    .name(String name)
+    .description(String description)
+    .functionType(FunctionType functionType)
+    .inputFieldNames(List<String> inputFieldNames)
+    .outputFieldNames(List<String> outputFieldNames)
+```
+
+**BUILDER METHODS:**
+
+- `name(String name)`
+
+    The name of the function. This identifier is used to reference the function within queries and collections.
+
+- `description(String description)`
+
+    A brief description of the function's purpose. This can be useful for documentation or clarity in larger projects and defaults to an empty string.
+
+- `functionType(FunctionType functionType)`
+
+    The type of function for processing raw data. Possible values:
+
+    - `FunctionType.BM25`: Uses the BM25 algorithm for generating sparse embeddings from a `VARCHAR` field.
+
+- `inputFieldNames(List<String> inputFieldNames)`
+
+    The name of the field containing the raw data that requires conversion to vector representation. For functions using `FunctionType.BM25`, this parameter accepts only one field name.
+
+- `outputFieldNames(List<String> outputFieldNames)`
+
+    The name of the field where the generated embeddings will be stored. This should correspond to a vector field defined in the collection schema. For functions using `FunctionType.BM25`, this parameter accepts only one field name.
+
+**RETURN TYPE:**
+
+*Function*
+
+**RETURNS:**
+
+A `Function` object that can be registered with a Milvus collection, facilitating automatic embedding generation during data insertion.
+
+**EXCEPTIONS:**
+
+- **MilvusClientExceptions**
+
+    This exception will be raised when any error occurs during this operation.
+
+## Example
+
+```java
+CreateCollectionReq.Function.builder()
+    .functionType(FunctionType.BM25)
+    .name("text_bm25_emb")
+    .inputFieldNames(Collections.singletonList("text"))
+    .outputFieldNames(Collections.singletonList("vector"))
+    .build());
+```

API_Reference/milvus-sdk-java/v2.5.x/v2/Collections/FunctionType.md

@@ -0,0 +1,13 @@
+# FunctionType
+
+This is an enumeration that provides the following constants.
+
+## Constants
+
+- BM25
+
+    Sets the function type to **BM25**.
+
+- Unknown
+
+    Sets the function type to **Unknown**.

API_Reference/milvus-sdk-java/v2.5.x/v2/Management/IndexParam.md

@@ -34,7 +34,9 @@ IndexParam.builder()
 
 - `metricType(IndexParam.MetricType metricType)`
 
-    The distance metric to use for the index. Possible values are **L2**, **IP**, **COSINE**, **HAMMING**, and **JACCARD**.
+    The algorithm that is used to measure similarity between vectors. Possible values: `IP`, `L2`, `COSINE`, `HAMMING`, `JACCARD`, `BM25` (used only for full text search). For more information, refer to [Metric Types](https://milvus.io/docs/metric.md).
+
+    This is available only when the specified field is a vector field.
 
 - `extraParams(Map<String, Object> extraParams)`
 

API_Reference/pymilvus/v2.5.x/MilvusClient/Function/Function.md

@@ -1,6 +1,6 @@
 # Function
 
-A `Function` instance for generating vector embeddings from user-provided raw text data in Milvus.
+A `Function` instance for generating vector embeddings from user-provided raw data in Milvus.
 
 ```python
 class pymilvus.Function
@@ -27,7 +27,7 @@ Function(
 
     **[REQUIRED]**
 
-      The name of the function. This identifier is used to reference the function within queries and collections.
+    The name of the function. This identifier is used to reference the function within queries and collections.
 
 - `function_type` (*FunctionType*) -
 

API_Reference/pymilvus/v2.5.x/MilvusClient/Management/add_index.md

@@ -30,9 +30,9 @@ IndexParams.add_index(
 
 - **metric_type** (*str*) -
 
-    The algorithm that is used to measure similarity between vectors. Possible values: `IP`, `L2`, `COSINE`, `HAMMING`, `JACCARD`, `BM25`. For more information, refer to [Metric Types](https://milvus.io/docs/metric.md).
+    The algorithm that is used to measure similarity between vectors. Possible values: `IP`, `L2`, `COSINE`, `HAMMING`, `JACCARD`, `BM25` (used only for full text search). For more information, refer to [Metric Types](https://milvus.io/docs/metric.md).
 
-    This is available only when the specified field is a vector field. 
+    This is available only when the specified field is a vector field.
 
 - **params** (*dict*) -
 

API_Reference_MDX/milvus-restful/v2.5.x/v2/Collection (v2)/List.mdx

@@ -15,6 +15,6 @@ import RestSpecs from '@site/src/components/RestSpecs';
 
 <RestSpecs specs={specs} endpoint={endpoint} method={method} target="milvus" lang="en-US" />
 
-export const specs = {"summary":"List Collections","deprecated":false,"description":"This operation lists all collection names.","x-i18n":{"zh-CN":{"summary":"查看 Collection 列表","description":"列出所有 Collection 名称。"}},"tags":["Collection Operations (V2)"],"parameters":[{"name":"Authorization","in":"header","description":"The authentication token should be <include target=\"zilliz\">an API key with appropriate privileges or </include>a pair of colon-joined username and password, like `username:password`.","required":true,"example":"Bearer {{TOKEN}}","schema":{"type":"string"},"x-i18n":{"zh-CN":{"description":"认证令牌，应为<include target=\"zilliz\">具备适当权限的 API 密钥或</include>用冒号分隔的用户名和密码，如 `username:password`。"}}}],"requestBody":{"content":{"application/json":{"schema":{"type":"object","properties":{"dbName":{"type":"string","description":"The name of an existing database.","x-i18n":{"zh-CN":{"description":"现有数据库名称。"}},"x-include-target":["milvus"]}}},"examples":{"1":{"summary":"milvus","x-include-target":["milvus"],"value":{"dbName":"_default"}},"2":{"summary":"zilliz","x-include-target":["zilliz"],"value":{}}}}}},"responses":{"200":{"description":"This operation lists all collections in the database used in the current connection.","x-i18n":{"zh-CN":{"description":"该操作列出当前连接中使用的数据库中的所有 Collection。"}},"content":{"application/json":{"schema":{"oneOf":[{"x-tab-label":"success","type":"object","properties":{"code":{"description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}},"type":"integer"},"data":{"type":"array","items":{"type":"string","description":"A collection name.","x-i18n":{"zh-CN":{"description":"Collection 名称。"}}},"description":"Response payload which is a list of collection names.","x-i18n":{"zh-CN":{"description":"响应载荷，一个 Collection 名称列表。"}}}}},{"x-tab-label":"failure","description":"Returns an error message.","x-i18n":{"zh-CN":{"description":"返回错误消息。"}},"x-i18n-langs":["zh-CN"],"type":"object","properties":{"code":{"type":"integer","description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}}},"message":{"type":"string","description":"Error message.","x-i18n":{"zh-CN":{"description":"错误描述。"}}}}}]},"examples":{"1":{"summary":"success","x-target-response":"OPTION 1","value":{"code":0,"data":["quick_setup_new","customized_setup_1","customized_setup_2"]}},"2":{"summary":"failure","x-target-response":"OPTION 2","value":{"code":0,"message":"The token is illegal."}}}}}}},"security":[]}
+export const specs = {"summary":"List Collections","deprecated":false,"description":"This operation lists all collection names.","x-i18n":{"zh-CN":{"summary":"查看 Collection 列表","description":"列出所有 Collection 名称。"}},"tags":["Collection Operations (V2)"],"parameters":[{"name":"Authorization","in":"header","description":"The authentication token should be <include target=\"zilliz\">an API key with appropriate privileges or </include>a pair of colon-joined username and password, like `username:password`.","required":true,"example":"Bearer {{TOKEN}}","schema":{"type":"string"},"x-i18n":{"zh-CN":{"description":"认证令牌，应为<include target=\"zilliz\">具备适当权限的 API 密钥或</include>用冒号分隔的用户名和密码，如 `username:password`。"}}}],"requestBody":{"content":{"application/json":{"schema":{"type":"object","properties":{"dbName":{"type":"string","description":"The name of an existing database.","x-i18n":{"zh-CN":{"description":"现有数据库名称。"}}}}},"example":{"dbName":"_default"}}}},"responses":{"200":{"description":"This operation lists all collections in the database used in the current connection.","x-i18n":{"zh-CN":{"description":"该操作列出当前连接中使用的数据库中的所有 Collection。"}},"content":{"application/json":{"schema":{"oneOf":[{"x-tab-label":"success","type":"object","properties":{"code":{"description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}},"type":"integer"},"data":{"type":"array","items":{"type":"string","description":"A collection name.","x-i18n":{"zh-CN":{"description":"Collection 名称。"}}},"description":"Response payload which is a list of collection names.","x-i18n":{"zh-CN":{"description":"响应载荷，一个 Collection 名称列表。"}}}}},{"x-tab-label":"failure","description":"Returns an error message.","x-i18n":{"zh-CN":{"description":"返回错误消息。"}},"x-i18n-langs":["zh-CN"],"type":"object","properties":{"code":{"type":"integer","description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}}},"message":{"type":"string","description":"Error message.","x-i18n":{"zh-CN":{"description":"错误描述。"}}}}}]},"examples":{"1":{"summary":"success","x-target-response":"OPTION 1","value":{"code":0,"data":["quick_setup_new","customized_setup_1","customized_setup_2"]}},"2":{"summary":"failure","x-target-response":"OPTION 2","value":{"code":0,"message":"The token is illegal."}}}}}}},"security":[]}
 export const endpoint = "/v2/vectordb/collections/list"
 export const method = "post"

API_Reference_MDX/milvus-restful/v2.5.x/v2/Database (v2)/alter.mdx

@@ -0,0 +1,20 @@
+---
+displayed_sidebar: restfulSidebar
+sidebar_positition: 10
+slug: /restful/alter
+title: "Alter | RESTful"
+description: "This operation modifies a new database. | RESTful"
+hide_table_of_contents: true
+sidebar_label: "Alter"
+sidebar_custom_props: { badges: ['post']}
+---
+
+# Alter
+
+import RestSpecs from '@site/src/components/RestSpecs';
+
+<RestSpecs specs={specs} endpoint={endpoint} method={method} target="milvus" lang="en-US" />
+
+export const specs = {"summary":"Alter","deprecated":false,"description":"This operation modifies a new database.","x-i18n":{"zh-CN":{"summary":"修改数据库","description":"此操作用于修改指定数据库。"}},"tags":["Database Operations (V2)"],"x-include-target":["milvus"],"parameters":[{"name":"Authorization","in":"header","description":"The authentication token should be <include target=\"zilliz\">an API key with appropriate privileges or </include>a pair of colon-joined username and password, like `username:password`.","required":true,"example":"Bearer {{TOKEN}}","schema":{"type":"string"},"x-i18n":{"zh-CN":{"description":"认证令牌，应为<include target=\"zilliz\">具备适当权限的 API 密钥或</include>用冒号分隔的用户名和密码，如 `username:password`。"}}}],"requestBody":{"content":{"application/json":{"schema":{"type":"object","properties":{"dbName":{"type":"string","description":"The name of the database to modify.","x-i18n":{"zh-CN":{"description":"待修改数据库名称。"}}},"properties":{"type":"object","description":"Database properties to modify. For example, you can reset the `mmap.enabled` property to `false` to disable the mmap feature for the collections in the database.","x-i18n":{"zh-CN":{"description":"待修改的数据库属性。例如，可以重新设置 `mmap.enabled` 属性为 `false` 以禁用数据库中 Collection 的 mmap 特性。"}}}},"required":["dbName"]},"example":{"dbName":"test","properties":{"mmap.enabled":true}}}}},"responses":{"200":{"description":"Returns an empty object.","x-i18n":{"zh-CN":{"description":"返回空对象。"}},"content":{"application/json":{"schema":{"oneOf":[{"x-tab-label":"success","type":"object","properties":{"code":{"type":"integer","description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}}},"data":{"type":"object","description":"Response payload which is an empty object.","x-i18n":{"zh-CN":{"description":"响应载荷，为空对象。"}},"properties":{}}}},{"x-tab-label":"failure","description":"Returns an error message.","x-i18n":{"zh-CN":{"description":"返回错误消息。"}},"x-i18n-langs":["zh-CN"],"type":"object","properties":{"code":{"type":"integer","description":"Response code.","x-i18n":{"zh-CN":{"description":"响应码。"}}},"message":{"type":"string","description":"Error message.","x-i18n":{"zh-CN":{"description":"错误描述。"}}}}}]},"examples":{"1":{"summary":"success","x-target-response":"OPTION 1","value":{"code":0,"data":{}}},"2":{"summary":"failure","x-target-response":"OPTION 2","value":{"code":0,"message":"The token is illegal."}}}}}}}}
+export const endpoint = "/v2/vectordb/databases/alter"
+export const method = "post"