* -------------------------------------------------------------
 *   Version: "2.0.0-rc.18"
 *   Repo: https://github.com/Redocly/redoc
 */
!function(e,t){"object"==typeof exports&&"object"==typeof m

...
```

That confirms that you are being able to serve static files from your app, and that you placed the static files for the docs in the correct place.

 * -------------------------------------------------------------
 *   Version: "2.0.0-rc.18"
 *   Repo: https://github.com/Redocly/redoc
 */
!function(e,t){"object"==typeof exports&&"object"==typeof m

...
```

Das zeigt, dass Sie statische Dateien aus Ihrer Anwendung bereitstellen können und dass Sie die statischen Dateien für die Dokumentation an der richtigen Stelle platziert haben.

 * -------------------------------------------------------------
 *   Version: "2.0.0-rc.18"
 *   Repo: https://github.com/Redocly/redoc
 */
!function(e,t){"object"==typeof exports&&"object"==typeof m

...
```

能打开这个文件就表示 FastAPI 应用能提供静态文件服务，并且文档要调用的静态文件放到了正确的位置。

接下来，使用静态文件配置文档。

### 禁用 API 文档

第一步是禁用 API 文档，就是使用 CDN 的默认文档。

    `TFCI` env param pointing to a list of `env` files.
2.  `utilities/setup.sh`, initialized by all top-level scripts, reads and sets
    values from those `TFCI` paths.
    -   `set -a` / `set -o allexport` exports the variables from `env` files so
        all scripts can use them.
    -   `utilities/setup_docker.sh` creates a container called `tf` with all
        `TFCI_` variables shared to it.

```
minio server http://host{1...2}/export{1...8}
```

Expected expansion

```
> http://host1/export1
> http://host2/export1
> http://host1/export2
> http://host2/export2
> http://host1/export3
> http://host2/export3
> http://host1/export4
> http://host2/export4
> http://host1/export5
> http://host2/export5
> http://host1/export6
> http://host2/export6
> http://host1/export7
> http://host2/export7

        "//tensorflow:tf_exported_symbols.lds",
        "//tensorflow:tf_private_symbols.lds",
        "//tensorflow:tf_version_script.lds",
    ],
    dynamic_deps = select({
        "//tensorflow:macos": ["//tensorflow:libtensorflow_framework.%s.dylib" % VERSION],
        "//conditions:default": ["//tensorflow:libtensorflow_framework.so.%s" % VERSION],
    }),
    exports_filter = [
        "//:__subpackages__",

les-2.1\\org.jetbrains\\annotations\\13.0\\919f0dfe192fb4e063e7dacadee7f8bb9a2672a9\\annotations-13.0.jar -Djava.awt.headless=true -D$java.rmi.server.hostname=127.0.0.1 -Xmx1024m -XX:MaxMetaspaceSize=512m -Dkotlin.environment.keepalive -ea --add-exports java.base/sun.nio.ch=ALL-UNNAMED org.jetbrains.kotlin.daemon.KotlinCompileDaemon --daemon-runFilesPath C:\\Users\\tcagent1\\AppData\\Local\\kotlin\\daemon --daemon-autoshutdownIdleSeconds=7200 --daemon-compilerClasspath C:\\tcagent1\\work\\f63322...

const isPathValid = path =>
    checkPath(path && checkPath.convert(path), path, RETURN_FALSE)

factory.isPathValid = isPathValid

// Fixes typescript
factory.default = factory

module.exports = factory

// Windows
// --------------------------------------------------------------
/* istanbul ignore if */
if (
    // Detect `process` so that it can run in browsers.
    typeof process !== 'undefined'

		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}

	// Write success response.
	writeSuccessNoContent(w)
}

// ExportBucketMetadataHandler - exports all bucket metadata as a zipped file
func (a adminAPIHandlers) ExportBucketMetadataHandler(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

	bucket := pathClean(r.Form.Get("bucket"))

        "@com_google_absl//absl/strings",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ],
    alwayslink = 1,
)

exports_files(
    [
        "version_script.lds",
        "exported_symbols.lds",
    ],
    visibility = ["//visibility:public"],
)

filegroup(
    name = "checkpoint_reader_hdrs",
    srcs = [
        "checkpoint_reader.h",