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  1. docs/tr/docs/tutorial/security/simple-oauth2.md

        disabled = user_dict["disabled"],
        hashed_password = user_dict["hashed_password"],
    )
    ```
    
    /// info | Bilgi
    
    `**user_dict` için daha kapsamlı bir açıklama için [**Extra Models** dokümantasyonundaki ilgili bölüme](../extra-models.md#about-user-in-dict) geri dönüp bakın.
    
    ///
    
    ## Token’ı Döndürme { #return-the-token }
    
    `token` endpoint’inin response’u bir JSON object olmalıdır.
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Fri Mar 20 07:53:17 GMT 2026
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  2. docs/zh/docs/tutorial/security/get-current-user.md

    还记得请求体也是使用 Pydantic 模型声明的吧。
    
    放心,因为使用了 `Depends`,**FastAPI** 不会搞混。
    
    ///
    
    /// check | 检查
    
    依赖系统的这种设计方式可以支持不同的依赖项返回同一个 `User` 模型。
    
    而不是局限于只能有一个返回该类型数据的依赖项。
    
    ///
    
    ## 其它模型 { #other-models }
    
    接下来,直接在*路径操作函数*中获取当前用户,并用 `Depends` 在**依赖注入**系统中处理安全机制。
    
    开发者可以使用任何模型或数据满足安全需求(本例中是 Pydantic 的 `User` 模型)。
    
    而且,不局限于只能使用特定的数据模型、类或类型。
    
    不想在模型中使用 `username`,而是使用 `id` 和 `email`?当然可以。这些工具也支持。
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Fri Feb 13 13:37:57 GMT 2026
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  3. docs_src/events/tutorial003_py310.py

        return x * 42
    
    
    ml_models = {}
    
    
    @asynccontextmanager
    async def lifespan(app: FastAPI):
        # Load the ML model
        ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
        yield
        # Clean up the ML models and release the resources
        ml_models.clear()
    
    
    app = FastAPI(lifespan=lifespan)
    
    
    @app.get("/predict")
    async def predict(x: float):
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Thu Feb 12 13:19:43 GMT 2026
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  4. docs/uk/docs/how-to/separate-openapi-schemas.md

    Розгляньмо, як це працює, і як це змінити за потреби.
    
    ## Моделі Pydantic для введення та виведення { #pydantic-models-for-input-and-output }
    
    Припустімо, у вас є модель Pydantic зі значеннями за замовчуванням, наприклад:
    
    {* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}
    
    ### Модель для введення { #model-for-input }
    
    Якщо ви використовуєте цю модель як введення, як тут:
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Sat Feb 14 08:43:14 GMT 2026
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  5. tests/test_openapi_schema_type.py

    import pytest
    from fastapi.openapi.models import Schema, SchemaType
    
    
    @pytest.mark.parametrize(
        "type_value",
        [
            "array",
            ["string", "null"],
            None,
        ],
    )
    def test_allowed_schema_type(
        type_value: SchemaType | list[SchemaType] | None,
    ) -> None:
        """Test that Schema accepts SchemaType, List[SchemaType] and None for type field."""
        schema = Schema(type=type_value)
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Tue Feb 17 09:59:14 GMT 2026
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  6. compat/maven-model-builder/src/site/apt/super-pom.apt.vm

    ~~ under the License.
    
     -----
     Super POM
     -----
     Hervé Boutemy
     -----
     2011-09-12
     -----
    
    Super POM
    
     All models implicitly inherit from a super-POM:
    
    Created: Sun Apr 05 03:35:12 GMT 2026
    - Last Modified: Fri Oct 25 12:31:46 GMT 2024
    - 1K bytes
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  7. docs/tr/docs/tutorial/security/oauth2-jwt.md

    Bunu çok basitleştiren birçok paket, veri modeli, veritabanı ve mevcut özelliklerle ilgili pek çok ödün vermek zorunda kalır. Hatta bazıları işi aşırı basitleştirirken arka planda güvenlik açıkları da barındırır.
    
    ---
    
    **FastAPI**, hiçbir veritabanı, veri modeli veya araç konusunda ödün vermez.
    
    Projenize en uygun olanları seçebilmeniz için size tam esneklik sağlar.
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Fri Mar 20 07:53:17 GMT 2026
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  8. README.md

    ## Resources
    
    *   [TensorFlow.org](https://www.tensorflow.org)
    *   [TensorFlow Tutorials](https://www.tensorflow.org/tutorials/)
    *   [TensorFlow Official Models](https://github.com/tensorflow/models/tree/master/official)
    *   [TensorFlow Examples](https://github.com/tensorflow/examples)
    *   [TensorFlow Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow)
    Created: Tue Apr 07 12:39:13 GMT 2026
    - Last Modified: Thu Apr 02 10:38:57 GMT 2026
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  9. docs/zh-hant/docs/tutorial/testing.md

    * 對於 Cookie(cookies),在 `cookies` 參數中放一個 `dict`。
    
    關於如何把資料傳給後端(使用 `httpx` 或 `TestClient`),更多資訊請參考 [HTTPX 文件](https://www.python-httpx.org)。
    
    /// info
    
    請注意,`TestClient` 接收的是可轉為 JSON 的資料,而不是 Pydantic models。
    
    如果你的測試裡有一個 Pydantic model,並想在測試時把它的資料送給應用,你可以使用[JSON 相容編碼器](encoder.md)中介紹的 `jsonable_encoder`。
    
    ///
    
    ## 執行 { #run-it }
    
    接下來,你只需要安裝 `pytest`。
    
    請先建立並啟用一個[虛擬環境](../virtual-environments.md),然後安裝,例如:
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Fri Mar 20 17:05:38 GMT 2026
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  10. src/main/java/org/codelibs/fess/llm/LlmChatRequest.java

        }
    
        /**
         * Gets the model name.
         *
         * @return the model name
         */
        public String getModel() {
            return model;
        }
    
        /**
         * Sets the model name.
         *
         * @param model the model name
         * @return this request for method chaining
         */
        public LlmChatRequest setModel(final String model) {
            this.model = model;
            return this;
    Created: Tue Mar 31 13:07:34 GMT 2026
    - Last Modified: Thu Mar 05 03:38:31 GMT 2026
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