Initial Checks

• I have searched Google & GitHub for similar requests and couldn't find anything
• I have read and followed the docs and still think this feature is missing

Description

When using a TypeAdapter on a callable (or using the @validate_call()) decorator, validation from JSON is limited:

from pydantic import TypeAdapter
from pydantic_core import ArgsKwargs

def f(a: int, /, *, b: int):
    ...

ta = TypeAdapter(f)

# From Python, you use `ArgsKwargs`:
ta.validate_python(ArgsKwargs((1,), {'b': 1})

# No way to validate from JSON
ta.validate_json('{"a": 1, "b": 2}')  # error

The idea would be to introduce a flag on the arguments_schema(), so that we can validate like this:

def f(a: int, /, *, b: int):
    ...

...
ta.validate_json('{"a": 1, "b": 2}')

def f(*args: int, **kwargs: str):
    ...

...
ta.validate_json('{"args": [1, 2, 3], "kwargs": {"a": "string"}}')

This should work as parameter names should be unique. Note that while something like this could also be done for kwargs:

def f(*args: int, **kwargs: str):
    ...

...
ta.validate_json('{"args": [1, 2, 3], "a": "string"')

This won't play well if you have a parameter named a.

Affected Components

• Compatibility between releases
• Data validation/parsing
• Data serialization - .model_dump() and .model_dump_json()
• JSON Schema
• Dataclasses
• Model Config
• Field Types - adding or changing a particular data type
• Function validation decorator
• Generic Models
• Other Model behaviour - model_construct(), pickling, private attributes, ORM mode
• Plugins and integration with other tools - mypy, FastAPI, python-devtools, Hypothesis, VS Code, PyCharm, etc.