direction TB
        subgraph V2["Pydantic-v2-Modell"]
            V1Field["Pydantic-v1-Modell"]
        end
        subgraph V1["Pydantic-v1-Modell"]
            V2Field["Pydantic-v2-Modell"]
        end
    end

    style V2 fill:#f9fff3
    style V1 fill:#fff6f0
    style V1Field fill:#fff6f0
    style V2Field fill:#f9fff3
```

        Union[Literal["function", "request"], None],
        Doc(
            """
            Mainly for dependencies with `yield`, define when the dependency function
            should start (the code before `yield`) and when it should end (the code
            after `yield`).

            * `"function"`: start the dependency before the *path operation function*

    # Core Vocabulary
    schema_: Optional[str] = Field(default=None, alias="$schema")
    vocabulary: Optional[str] = Field(default=None, alias="$vocabulary")
    id: Optional[str] = Field(default=None, alias="$id")
    anchor: Optional[str] = Field(default=None, alias="$anchor")
    dynamicAnchor: Optional[str] = Field(default=None, alias="$dynamicAnchor")
    ref: Optional[str] = Field(default=None, alias="$ref")

                    "application code is raising an exception and a dependency with yield "
                    "has a block with a bare except, or a block with except Exception, "
                    "and is not raising the exception again. Read more about it in the "
                    "docs: https://fastapi.tiangolo.com/tutorial/dependencies/dependencies-with-yield/#dependencies-with-yield-and-except"
                )

        # Same as in Starlette

        else "validation"
    )
    field_alias = (
        (field.validation_alias or field.alias)
        if field.mode == "validation"
        else (field.serialization_alias or field.alias)
    )

    # This expects that GenerateJsonSchema was already used to generate the definitions
    json_schema = field_mapping[(field, override_mode or field.mode)]

                is_scalar_field(field)
                or is_scalar_sequence_field(field)
                or (
                    lenient_issubclass(field.type_, BaseModel)
                    # For Pydantic v1
                    and getattr(field, "shape", 1) == 1
                )
            )

    return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)

    from fastapi._compat import v2

    field_info = FieldInfo(annotation=Union[list[str], None])
    field = v2.ModelField(name="items", field_info=field_info)
    result = v2.serialize_sequence_value(field=field, value=["a", "b", "c"])
    assert result == ["a", "b", "c"]
    assert isinstance(result, list)


@needs_py310

from typing import Annotated

import pytest
from dirty_equals import IsOneOf
from fastapi import FastAPI, Query
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/required-list-str")
async def read_required_list_str(p: Annotated[list[str], Query()]):
    return {"p": p}

from typing import Annotated

import pytest
from dirty_equals import IsOneOf
from fastapi import FastAPI, Query
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/required-str")
async def read_required_str(p: str):
    return {"p": p}

from typing import Annotated

import pytest
from dirty_equals import IsOneOf
from fastapi import FastAPI, Form
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/required-str", operation_id="required_str")