```

**Important**: Return types or response models are what filter data ensuring no sensitive information is exposed. And they are used to serialize data with Pydantic (in Rust), this is the main idea that can increase response performance.

The return type doesn't have to be a Pydantic model, it could be a different type, like a list of integers, or a dict, etc.

Justin Van Dort <******@****.***> 1771543004 -0500

    return {"message": result}
```

## SQLModel for SQL databases

When working with SQL databases, prefer using SQLModel as it is integrated with Pydantic and will allow declaring data validation with the same models.

Prefer it over SQLAlchemy.

## HTTPX

Use HTTPX for handling HTTP communication (e.g. with other APIs). It support sync and async usage.

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

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

import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

import org.apache.maven.model.Dependency;
import org.apache.maven.model.DependencyManagement;
import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;

  script.setAttribute("data-modal-border-radius", "0.5rem");
  script.setAttribute("data-modal-header-bg-color", "#009485");
  script.setAttribute("data-modal-title", "FastAPI AI Assistant");
  script.setAttribute("data-modal-title-color", "#FFFFFF");
  script.setAttribute("data-modal-title-font-family", "Roboto, sans-serif");

이것이 어떻게 동작하는지, 그리고 필요하다면 어떻게 변경할 수 있는지 살펴보겠습니다.

## 입력과 출력을 위한 Pydantic 모델 { #pydantic-models-for-input-and-output }

예를 들어, 다음처럼 기본값이 있는 Pydantic 모델이 있다고 해보겠습니다:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### 입력용 모델 { #model-for-input }

이 모델을 다음처럼 입력으로 사용하면:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

			}
		},
	}
	session := DB.Session(&gorm.Session{Logger: tracer})

	DB.Migrator().DropTable(model1)
	var modifySql []string
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	tracer2 := Tracer{

        response_fields = {}
        for additional_status_code, response in self.responses.items():
            assert isinstance(response, dict), "An additional response must be a dict"
            model = response.get("model")
            if model:
                assert is_body_allowed_for_status_code(additional_status_code), (
                    f"Status code {additional_status_code} must not have a response body"
                )

Muitos pacotes que simplificam bastante isso precisam fazer muitas concessões com o modelo de dados, o banco de dados e os recursos disponíveis. E alguns desses pacotes que simplificam demais na verdade têm falhas de segurança subjacentes.

---

O **FastAPI** não faz nenhuma concessão com nenhum banco de dados, modelo de dados ou ferramenta.

@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
    return filter_query
```

Read the new docs: [Query Parameter Models](https://fastapi.tiangolo.com/tutorial/query-param-models/).

#### `Header` Parameter Models

Use Pydantic models for `Header` parameters:

```python
from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel