"{\"match_phrase\":{\"content\":{\"query\":\"aaa\",\"slop\":0,\"zero_terms_query\":\"NONE\",\"boost\":1.0}}}", //
                "content:aaa");
        assertQueryBuilder(DefaultQueryBuilder.class,

                        "200": {
                            "description": "Successful Response",
                            "content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

def test_file_path():
    response = client.get("/files/home/johndoe/myfile.txt")
    print(response.content)
    assert response.status_code == 200, response.text
    assert response.json() == {"file_path": "home/johndoe/myfile.txt"}


def test_root_file_path():
    response = client.get("/files//home/johndoe/myfile.txt")
    print(response.content)
    assert response.status_code == 200, response.text

                        "200": {
                            "description": "Successful Response",
                            "content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

                        "200": {
                            "description": "Successful Response",
                            "content": {"application/json": {"schema": {}}},
                        },
                        "422": {
                            "description": "Validation Error",
                            "content": {
                                "application/json": {
                                    "schema": {

Then we use the request directly, and extract the body as `bytes`. This means that FastAPI won't even try to parse the request payload as JSON.

And then in our code, we parse that YAML content directly, and then we are again using the same Pydantic model to validate the YAML content:

//// tab | Pydantic v2

```Python hl_lines="26-33"
{!> ../../docs_src/path_operation_advanced_configuration/tutorial007.py!}
```

////

                                    <label for="doc.content" class="col-sm-3 text-sm-right col-form-label">content</label>
                                    <div class="col-sm-9">
                                        <la:errors property="doc.content"/>
                                        <la:text styleId="doc.content" property="doc.content" styleClass="form-control"/>
                                    </div>

            "/items/": {
                "post": {
                    "responses": {
                        "200": {
                            "description": "Successful Response",
                            "content": {
                                "application/json": {
                                    "schema": {"$ref": "#/components/schemas/Item"}
                                }
                            },

// or Adobe Acrobat (though not necessarily limited to these), permission to handle data across domains.
// When clients request content hosted on a particular source domain and that content make requests
// directed towards a domain other than its own, the remote domain needs to host a cross-domain

    <jsp:include page="/WEB-INF/view/common/admin/sidebar.jsp">
        <jsp:param name="menuCategoryType" value="system"/>
        <jsp:param name="menuType" value="dict"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>