@Test
    public void testGetKeywordsWithEmptyField() {
        // Test with empty field array
        String query = "test query";
        String[] fields = {};
        List<String> keywords = SuggestUtil.getKeywords(query, fields);
        assertNotNull(keywords);
        assertEquals(0, keywords.size()); // No keywords because no fields match
    }

    @Test
    public void testGetKeywordsWithComplexQuery() {

        SuggestSettings settings = suggester.settings();
        String field = settings.array().get(SuggestSettings.DefaultKeys.SUPPORTED_FIELDS)[0];

        QueryLog[] queryLogs = new QueryLog[3];
        queryLogs[0] = new QueryLog(field + ":検索", null);
        queryLogs[1] = new QueryLog(field + ":fess", null);
        queryLogs[2] = new QueryLog(field + ":エンジン", null);

		}
		_ = stmt.Schema.ParseIndexes()
		field := stmt.Schema.LookUpField(fieldName)
		if field == nil {
			t.Fatalf("%v: failed to find column %q", utils.FileWithLineNum(), fieldName)
		}
		if field.Unique != unique {
			t.Fatalf("%v: %q column %q unique should be %v but got %v", utils.FileWithLineNum(), stmt.Schema.Table, fieldName, unique, field.Unique)
		}
		if field.UniqueIndex != uniqueIndex {

				// Note: Duplicate Columns
				{Field: &schema.Field{Name: "FieldD"}},
			},
		},
		{
			Name:  "uniq_field_e1_e2",
			Class: "UNIQUE",
			Fields: []schema.IndexOption{
				{Field: &schema.Field{Name: "FieldE1"}},
				{Field: &schema.Field{Name: "FieldE2"}},
			},
		},
		{
			Name:  "uniq_field_f1_f2",
			Class: "UNIQUE",
			Fields: []schema.IndexOption{

# Body - Fields { #body-fields }

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

# Body - Поля { #body-fields }

Таким же способом, как вы объявляете дополнительную валидацию и метаданные в параметрах *функции обработки пути* с помощью функций `Query`, `Path` и `Body`, вы можете объявлять валидацию и метаданные внутри Pydantic моделей, используя функцию `Field` из Pydantic.

## Импорт `Field` { #import-field }

Сначала вы должны импортировать его:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Внимание

# 请求体 - 字段 { #body-fields }

与在*路径操作函数*中使用 `Query`、`Path` 、`Body` 声明校验与元数据的方式一样，可以使用 Pydantic 的 `Field` 在 Pydantic 模型内部声明校验和元数据。

## 导入 `Field` { #import-field }

首先，从 Pydantic 中导入 `Field`：

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | 警告

注意，与从 `fastapi` 导入 `Query`，`Path`、`Body` 不同，要直接从 `pydantic` 导入 `Field` 。

///

## 声明模型属性 { #declare-model-attributes }

然后，使用 `Field` 定义模型的属性：

# Body - Alanlar { #body-fields }

`Query`, `Path` ve `Body` ile *path operation function* parametrelerinde ek doğrulama ve metadata tanımlayabildiğiniz gibi, Pydantic modellerinin içinde de Pydantic'in `Field`'ını kullanarak doğrulama ve metadata tanımlayabilirsiniz.

## `Field`'ı import edin { #import-field }

Önce import etmeniz gerekir:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}

/// warning | Uyarı

a pointer type or type parameter. The unqualified type name acts as the field name.
</p>

<pre>
// A struct with four embedded fields of types T1, *T2, P.T3 and *P.T4
struct {
	T1        // field name is T1
	*T2       // field name is T2
	P.T3      // field name is T3
	*P.T4     // field name is T4
	x, y int  // field names are x and y
}
</pre>

<p>

# Body - 欄位 { #body-fields }

就像你可以在「路徑操作函式 (path operation function)」的參數中用 `Query`、`Path` 和 `Body` 宣告額外的驗證與中繼資料一樣，你也可以在 Pydantic 模型中使用 Pydantic 的 `Field` 來宣告驗證與中繼資料。

## 匯入 `Field` { #import-field }

首先，你需要匯入它：

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

請注意，`Field` 是直接從 `pydantic` 匯入的，不像其他（如 `Query`、`Path`、`Body` 等）是從 `fastapi` 匯入。

///

## 宣告模型屬性 { #declare-model-attributes }