docs: update feature coverage for 2.6 APIs (#552)

Signed-off-by: ryjiang <jiangruiyi@gmail.com>

Author: shanghaikid

docs/content/advanced/full-text-search.mdx

@@ -25,13 +25,33 @@ console.log('Results:', result.results);
 // Each text input produces an AnalyzerResult with tokens
 ```
 
+You can also test analyzers that are configured on a collection field, request detailed token data, and include token hashes:
+
+```javascript
+const result = await client.runAnalyzer({
+  db_name: 'default',
+  collection_name: 'articles',
+  field_name: 'body',
+  analyzer_names: ['english_analyzer'],
+  text: ['Running analyzers with offsets and hashes'],
+  with_detail: true,
+  with_hash: true,
+});
+
+result.results[0].tokens.forEach(token => {
+  console.log(token.token, token.start_offset, token.end_offset, token.hash);
+});
+```
+
+`runAnalyzer()` accepts either `analyzer_params` for an ad-hoc analyzer configuration or collection context fields (`db_name`, `collection_name`, `field_name`, `analyzer_names`) to use analyzers defined in a schema.
+
 ### Analyzer Types
 
-| Type | Description |
-|------|-------------|
+| Type       | Description                              |
+| ---------- | ---------------------------------------- |
 | `standard` | Standard tokenizer with lowercase filter |
-| `english` | English-specific tokenizer with stemming |
-| `chinese` | Chinese text tokenizer |
+| `english`  | English-specific tokenizer with stemming |
+| `chinese`  | Chinese text tokenizer                   |
 
 ## Creating a Full-Text Search Collection
 
@@ -44,9 +64,24 @@ const client = new MilvusClient({ address: 'localhost:19530' });
 await client.createCollection({
   collection_name: 'articles',
   fields: [
-    { name: 'id', data_type: DataType.Int64, is_primary_key: true, autoID: true },
-    { name: 'title', data_type: DataType.VarChar, max_length: 256, enable_analyzer: true },
-    { name: 'body', data_type: DataType.VarChar, max_length: 10000, enable_analyzer: true },
+    {
+      name: 'id',
+      data_type: DataType.Int64,
+      is_primary_key: true,
+      autoID: true,
+    },
+    {
+      name: 'title',
+      data_type: DataType.VarChar,
+      max_length: 256,
+      enable_analyzer: true,
+    },
+    {
+      name: 'body',
+      data_type: DataType.VarChar,
+      max_length: 10000,
+      enable_analyzer: true,
+    },
     { name: 'sparse_vector', data_type: DataType.SparseFloatVector },
   ],
   functions: [
@@ -96,8 +131,14 @@ await client.loadCollectionSync({ collection_name: 'articles' });
 await client.insert({
   collection_name: 'articles',
   data: [
-    { title: 'Introduction to Machine Learning', body: 'Machine learning is a branch of AI...' },
-    { title: 'Deep Learning Basics', body: 'Deep learning uses neural networks...' },
+    {
+      title: 'Introduction to Machine Learning',
+      body: 'Machine learning is a branch of AI...',
+    },
+    {
+      title: 'Deep Learning Basics',
+      body: 'Deep learning uses neural networks...',
+    },
   ],
 });
 
@@ -129,7 +170,7 @@ const results = await client.search({
   limit: 10,
   output_fields: ['title', 'body'],
   highlighter: {
-    type: 0,  // HighlightType.Lexical
+    type: 0, // HighlightType.Lexical
     pre_tags: ['<em>'],
     post_tags: ['</em>'],
     fragment_size: 100,
@@ -150,7 +191,7 @@ const results = await client.search({
   limit: 10,
   output_fields: ['title', 'body'],
   highlighter: {
-    type: 1,  // HighlightType.Semantic
+    type: 1, // HighlightType.Semantic
     queries: ['machine learning'],
     input_fields: ['body'],
     pre_tags: ['<mark>'],
@@ -160,6 +201,25 @@ const results = await client.search({
 });
 ```
 
+### Highlight Results
+
+Search hits include highlight data when highlighting is enabled. Each highlighted field contains text fragments and optional scores.
+
+```javascript
+results.results.forEach(hit => {
+  console.log('Title:', hit.title);
+  console.log('Highlight:', hit.highlight);
+
+  const bodyHighlight = hit.highlight?.body;
+  bodyHighlight?.fragments.forEach((fragment, index) => {
+    console.log('Fragment:', fragment);
+    console.log('Score:', bodyHighlight.scores?.[index]);
+  });
+});
+```
+
+For lexical highlighting, set `highlight_search_text: true` to include the matched search text in highlight output when supported by Milvus. For semantic highlighting, set `highlight_only: true` to return only highlighted fragments instead of the full source text.
+
 ## Managing Collection Functions
 
 ```javascript

docs/content/core-concepts/client-configuration.mdx

@@ -69,23 +69,23 @@ const client = new MilvusClient({
     rootCertPath: '/path/to/ca.pem',
     // Or certificate buffer
     rootCert: Buffer.from('...'),
-    
+
     // Private key path (for client authentication)
     privateKeyPath: '/path/to/key.pem',
     // Or private key buffer
     privateKey: Buffer.from('...'),
-    
+
     // Certificate chain path
     certChainPath: '/path/to/cert.pem',
     // Or certificate buffer
     certChain: Buffer.from('...'),
-    
+
     // Server name for SNI
     serverName: 'milvus.example.com',
-    
+
     // Skip certificate verification (not recommended for production)
     skipCertCheck: false,
-    
+
     // Additional verify options
     verifyOptions: {},
   },
@@ -171,6 +171,22 @@ const client = new MilvusClient({
 });
 ```
 
+### Connect Reserved Options
+
+Use `option` to pass reserved key-value metadata in the initial Milvus `Connect` request. These values are sent as `client_info.reserved` and are useful for deployment-specific routing, attribution, or internal integrations.
+
+```javascript
+const client = new MilvusClient({
+  address: 'localhost:19530',
+  option: {
+    app: 'recommendation-service',
+    environment: 'production',
+  },
+});
+```
+
+`option` values must be strings.
+
 ## Environment-Specific Configuration
 
 ### Development
@@ -217,32 +233,32 @@ const client = new MilvusClient({
 const client = new MilvusClient({
   // Required
   address: 'localhost:19530',
-  
+
   // Authentication (choose one)
   username: 'root',
   password: 'Milvus',
   // OR
   token: 'api-key',
-  
+
   // SSL/TLS
   ssl: true,
   tls: {
     rootCertPath: '/path/to/ca.pem',
     serverName: 'milvus.example.com',
   },
-  
+
   // Timeouts and retries
   timeout: 30000,
   maxRetries: 3,
   retryDelay: 1000,
-  
+
   // Database
   database: 'default',
-  
+
   // Logging
   logLevel: 'info',
   logPrefix: 'milvus',
-  
+
   // Connection pooling
   pool: {
     min: 2,
@@ -263,6 +279,7 @@ interface ClientConfig {
   username?: string;
   password?: string;
   channelOptions?: ChannelOptions;
+  option?: Record<string, string>;
   timeout?: number | string;
   maxRetries?: number;
   retryDelay?: number;
@@ -307,6 +324,7 @@ await client.createCollection({
 ```
 
 **Features:**
+
 - Automatic timestamp: Every request includes `client-request-unixmsec`
 - Trace ID support: Add `client_request_id` or `client-request-id` to track requests
 - Global support: All API methods automatically support trace IDs
@@ -319,4 +337,3 @@ For more details, see [Request Tracing](../advanced/advanced-features#request-tr
 - Learn about [Data Types & Schemas](./data-types-schemas)
 - Explore [Collection Management](./collection-management)
 - Check out [Best Practices](./best-practices) for production configurations
-

docs/content/core-concepts/data-types-schemas.mdx

@@ -144,15 +144,22 @@ Sparse vectors store only non-zero values with their indices. Commonly used for
 Sparse vectors can be inserted in two formats:
 
 **Dictionary format** (recommended):
+
 ```javascript
 // Keys are indices, values are float weights
 { 10: 0.5, 100: 0.3, 500: 0.8, 1200: 0.1 }
 ```
 
 **Array of tuples format:**
+
 ```javascript
 // [index, value] pairs
-[[10, 0.5], [100, 0.3], [500, 0.8], [1200, 0.1]]
+[
+  [10, 0.5],
+  [100, 0.3],
+  [500, 0.8],
+  [1200, 0.1],
+];
 ```
 
 Note: Dimension is determined automatically from the maximum index across all vectors.
@@ -193,6 +200,29 @@ BFloat16 vector:
 }
 ```
 
+#### Nullable Vector Fields
+
+Vector fields can be marked as nullable. Insert or upsert `null` for rows that do not have an embedding yet; query and search results return `null` for those fields.
+
+```javascript
+{
+  name: 'optional_embedding',
+  data_type: DataType.FloatVector,
+  dim: 128,
+  nullable: true,
+}
+
+await client.insert({
+  collection_name: 'my_collection',
+  data: [
+    { id: 1, optional_embedding: [/* 128 floats */] },
+    { id: 2, optional_embedding: null },
+  ],
+});
+```
+
+Nullable vector payloads are supported for `FloatVector`, `BinaryVector`, `Float16Vector`, `BFloat16Vector`, `SparseFloatVector`, and `Int8Vector`.
+
 ### Complex Types
 
 #### Array
@@ -208,6 +238,35 @@ Array of scalar values:
 }
 ```
 
+#### ArrayOfVector
+
+`DataType.ArrayOfVector` stores multiple vectors in a single field value. This is useful for documents split into chunks, multi-vector embeddings, or struct array payloads that contain vector arrays.
+
+```javascript
+{
+  name: 'chunk_embeddings',
+  data_type: DataType.ArrayOfVector,
+  element_type: DataType.FloatVector,
+  dim: 128,
+  max_capacity: 32,
+}
+
+await client.insert({
+  collection_name: 'my_collection',
+  data: [
+    {
+      id: 1,
+      chunk_embeddings: [
+        [/* first 128-d vector */],
+        [/* second 128-d vector */],
+      ],
+    },
+  ],
+});
+```
+
+Supported element vector types include dense, binary, float16, bfloat16, sparse, and int8 vector payloads where supported by Milvus.
+
 #### Struct
 
 Nested structure:
@@ -237,6 +296,9 @@ Each field in a collection schema must include:
   autoID: false,                // Optional: auto-generate IDs
   max_length: 256,              // Required for VarChar
   dim: 128,                     // Required for vector types
+  nullable: false,              // Optional: allow null values
+  default_value: undefined,     // Optional scalar default value
+  external_field: undefined,    // Optional: source field name for external collections
 }
 ```
 
@@ -364,9 +426,11 @@ await client.insert({
   collection_name: 'my_collection',
   data: [
     {
-      vector: [/* ... */],
+      vector: [
+        /* ... */
+      ],
       dynamic_field_1: 'value1', // Automatically added
-      dynamic_field_2: 123,      // Automatically added
+      dynamic_field_2: 123, // Automatically added
     },
   ],
 });
@@ -395,4 +459,3 @@ The SDK validates schemas before creating collections. Common validation errors:
 - Learn about [Collection Management](./collection-management)
 - Explore [Data Operations](./data-operations-insert)
 - Check out [Best Practices](./best-practices)
-