In those cases, you can use the **official Docker image** that includes **Gunicorn** as a process manager running multiple **Uvicorn worker processes**, and some default settings to adjust the number of workers based on the current CPU cores automatically. I'll tell you more about it below in [Official Docker Image with Gunicorn - Uvicorn](#official-docker-image-with-gunicorn-uvicorn).

        uses: actions/checkout@v4
      - name: Set up Go
        uses: actions/setup-go@v5
        with:
          go-version: 1.21.9
          check-latest: true
      - name: Get official govulncheck
        run: go install golang.org/x/vuln/cmd/govulncheck@latest
        shell: bash
      - name: Run govulncheck
        run: govulncheck -show verbose ./...

)

// For windows our files have .exe additionally.
var minioReleaseWindowsInfoURL = MinioReleaseURL + "minio.exe.sha256sum"

// minioVersionToReleaseTime - parses a standard official release
// MinIO version string.
//
// An official binary's version string is the release time formatted
// with RFC3339 (in UTC) - e.g. `2017-09-29T19:16:56Z`
func minioVersionToReleaseTime(version string) (releaseTime time.Time, err error) {

else
  SHA=$(grep "istio.io/api" go.mod | head -n1 | awk '{ print $2 }')
  if [[ ${SHA} == *"-"* && ! ${SHA} =~ -rc.[0-9]$ && ! ${SHA} =~ -beta.[0-9]$ && ! ${SHA} =~ -alpha.[0-9]$ ]]; then
    # not an official release or release candidate, so get the commit sha
    SHA=$(echo "${SHA}" | awk -F '-' '{ print $NF }')
  fi
fi

if [ -z "${SHA}" ]; then

build:cuda_clang_official --config=cuda_clang
build:cuda_clang_official --action_env=TF_CUDA_VERSION="12"
build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"
build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3"
build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"

# Aprender

Nesta parte da documentação encontramos as seções introdutórias e os tutoriais para aprendermos como usar o **FastAPI**.

Nesses casos, você pode usar a **imagem oficial do Docker** que inclui o **Gunicorn** como um gerenciador de processos executando vários **processos trabalhadores Uvicorn**, e algumas configurações padrão para ajustar o número de trabalhadores com base nos atuais núcleos da CPU automaticamente. Eu vou te contar mais sobre isso abaixo em [Imagem Oficial do Docker com Gunicorn - Uvicorn](#imagem-oficial-do-docker-com-gunicorn-uvicorn).

```Python hl_lines="3"
{!../../../docs_src/configure_swagger_ui/tutorial003.py!}
```

## Other Swagger UI Parameters

To see all the other possible configurations you can use, read the official <a href="https://swagger.io/docs/open-source-tools/swagger-ui/usage/configuration" class="external-link" target="_blank">docs for Swagger UI parameters</a>.

## JavaScript-only settings

[![official project](https://jb.gg/badges/official.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
[![TeamCity (simple build status)](https://img.shields.io/teamcity/http/teamcity.jetbrains.com/s/Kotlin_KotlinPublic_Compiler.svg)](https://teamcity.jetbrains.com/buildConfiguration/Kotlin_KotlinPublic_Compiler?branch=%3Cdefault%3E&buildTypeTab=overview&mode=builds)

That demonstrates how the Proxy (Traefik) uses the path prefix and how the server (Uvicorn) uses the `root_path` from the option `--root-path`.

### Check the docs UI

But here's the fun part. ✨