# Module okhttp-coroutines

from fastapi.openapi.models import SecurityBase as SecurityBaseModel


class SecurityBase:
    model: SecurityBaseModel

///

## Declarar atributos del modelo { #declare-model-attributes }

Después puedes utilizar `Field` con los atributos del modelo:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` funciona de la misma manera que `Query`, `Path` y `Body`, tiene todos los mismos parámetros, etc.

        }

        return false;
    }

    /**
     * Checks if a model version is eligible for inference optimizations.
     * Models 4.0.0+ are eligible (4.0.0 has limited inference, 4.1.0+ has full inference).
     *
     * @param modelVersion the model version to check
     * @return true if eligible for inference
     */

 */
package org.apache.maven.model.plugin;

import javax.inject.Named;
import javax.inject.Singleton;

import org.apache.maven.model.Build;
import org.apache.maven.model.InputLocation;
import org.apache.maven.model.InputSource;
import org.apache.maven.model.Model;
import org.apache.maven.model.Plugin;
import org.apache.maven.model.PluginManagement;
import org.apache.maven.model.ReportPlugin;

* Recuperar os dados armazenados.
* Colocar esses dados em um modelo do Pydantic.
* Gerar um `dict` sem valores padrão a partir do modelo de entrada (usando `exclude_unset`).
    * Dessa forma, você pode atualizar apenas os valores definidos pelo usuário, em vez de substituir os valores já armazenados com valores padrão em seu modelo.

    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):

        </executions>
      </plugin>
      <plugin>
        <groupId>org.codehaus.modello</groupId>
        <artifactId>modello-maven-plugin</artifactId>
        <configuration>
          <version>1.2.0</version>
          <models>
            <model>../../api/maven-api-cli/src/main/mdo/core-extensions.mdo</model>
          </models>
          <templates>
            <template>reader-stax.vm</template>

Using this same trick, you could use a Pydantic model to define the JSON Schema that is then included in the custom OpenAPI schema section for the *path operation*.

And you could do this even if the data type in the request is not JSON.

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.plugin;

import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles conversion of the <code>&lt;reporting&gt;</code> section into the configuration of Maven Site Plugin 3.x,