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import annotated_types
import pytest
from pydantic import BaseModel, Field
from fastmcp.utilities.func_metadata import func_metadata
class SomeInputModelA(BaseModel):
pass
class SomeInputModelB(BaseModel):
class InnerModel(BaseModel):
x: int
how_many_shrimp: Annotated[int, Field(description="How many shrimp in the tank???")]
ok: InnerModel
y: None
def complex_arguments_fn(
an_int: int,
must_be_none: None,
must_be_none_dumb_annotation: Annotated[None, "blah"],
list_of_ints: list[int],
# list[str] | str is an interesting case because if it comes in as JSON like
# "[\"a\", \"b\"]" then it will be naively parsed as a string.
list_str_or_str: list[str] | str,
an_int_annotated_with_field: Annotated[
int, Field(description="An int with a field")
],
an_int_annotated_with_field_and_others: Annotated[
int,
str, # Should be ignored, really
Field(description="An int with a field"),
annotated_types.Gt(1),
],
an_int_annotated_with_junk: Annotated[
int,
"123",
456,
],
field_with_default_via_field_annotation_before_nondefault_arg: Annotated[
int, Field(1)
],
unannotated,
my_model_a: SomeInputModelA,
my_model_a_forward_ref: "SomeInputModelA",
my_model_b: SomeInputModelB,
an_int_annotated_with_field_default: Annotated[
int,
Field(1, description="An int with a field"),
],
unannotated_with_default=5,
my_model_a_with_default: SomeInputModelA = SomeInputModelA(), # noqa: B008
an_int_with_default: int = 1,
must_be_none_with_default: None = None,
an_int_with_equals_field: int = Field(1, ge=0),
int_annotated_with_default: Annotated[int, Field(description="hey")] = 5,
) -> str:
_ = (
an_int,
must_be_none,
must_be_none_dumb_annotation,
list_of_ints,
list_str_or_str,
an_int_annotated_with_field,
an_int_annotated_with_field_and_others,
an_int_annotated_with_junk,
field_with_default_via_field_annotation_before_nondefault_arg,
unannotated,
an_int_annotated_with_field_default,
unannotated_with_default,
my_model_a,
my_model_a_forward_ref,
my_model_b,
my_model_a_with_default,
an_int_with_default,
must_be_none_with_default,
an_int_with_equals_field,
int_annotated_with_default,
)
return "ok!"
async def test_complex_function_runtime_arg_validation_non_json():
"""Test that basic non-JSON arguments are validated correctly"""
meta = func_metadata(complex_arguments_fn)
# Test with minimum required arguments
result = await meta.call_fn_with_arg_validation(
complex_arguments_fn,
fn_is_async=False,
arguments_to_validate={
"an_int": 1,
"must_be_none": None,
"must_be_none_dumb_annotation": None,
"list_of_ints": [1, 2, 3],
"list_str_or_str": "hello",
"an_int_annotated_with_field": 42,
"an_int_annotated_with_field_and_others": 5,
"an_int_annotated_with_junk": 100,
"unannotated": "test",
"my_model_a": {},
"my_model_a_forward_ref": {},
"my_model_b": {"how_many_shrimp": 5, "ok": {"x": 1}, "y": None},
},
arguments_to_pass_directly=None,
)
assert result == "ok!"
# Test with invalid types
with pytest.raises(ValueError):
await meta.call_fn_with_arg_validation(
complex_arguments_fn,
fn_is_async=False,
arguments_to_validate={"an_int": "not an int"},
arguments_to_pass_directly=None,
)
async def test_complex_function_runtime_arg_validation_with_json():
"""Test that JSON string arguments are parsed and validated correctly"""
meta = func_metadata(complex_arguments_fn)
result = await meta.call_fn_with_arg_validation(
complex_arguments_fn,
fn_is_async=False,
arguments_to_validate={
"an_int": 1,
"must_be_none": None,
"must_be_none_dumb_annotation": None,
"list_of_ints": "[1, 2, 3]", # JSON string
"list_str_or_str": '["a", "b", "c"]', # JSON string
"an_int_annotated_with_field": 42,
"an_int_annotated_with_field_and_others": "5", # JSON string
"an_int_annotated_with_junk": 100,
"unannotated": "test",
"my_model_a": "{}", # JSON string
"my_model_a_forward_ref": "{}", # JSON string
"my_model_b": '{"how_many_shrimp": 5, "ok": {"x": 1}, "y": null}', # JSON string
},
arguments_to_pass_directly=None,
)
assert result == "ok!"
def test_str_vs_list_str():
"""Test handling of string vs list[str] type annotations.
This is tricky as '"hello"' can be parsed as a JSON string or a Python string.
We want to make sure it's kept as a python string.
"""
def func_with_str_types(str_or_list: str | list[str]):
return str_or_list
meta = func_metadata(func_with_str_types)
# Test string input for union type
result = meta.pre_parse_json({"str_or_list": "hello"})
assert result["str_or_list"] == "hello"
# Test string input that contains valid JSON for union type
# We want to see here that the JSON-vali string is NOT parsed as JSON, but rather
# kept as a raw string
result = meta.pre_parse_json({"str_or_list": '"hello"'})
assert result["str_or_list"] == '"hello"'
# Test list input for union type
result = meta.pre_parse_json({"str_or_list": '["hello", "world"]'})
assert result["str_or_list"] == ["hello", "world"]
def test_str_vs_int():
"""
Test that string values are kept as strings even when they contain numbers,
while numbers are parsed correctly.
"""
def func_with_str_and_int(a: str, b: int):
return a
meta = func_metadata(func_with_str_and_int)
result = meta.pre_parse_json({"a": "123", "b": 123})
assert result["a"] == "123"
assert result["b"] == 123
def test_skip_names():
"""Test that skipped parameters are not included in the model"""
def func_with_many_params(
keep_this: int, skip_this: str, also_keep: float, also_skip: bool
):
return keep_this, skip_this, also_keep, also_skip
# Skip some parameters
meta = func_metadata(func_with_many_params, skip_names=["skip_this", "also_skip"])
# Check model fields
assert "keep_this" in meta.arg_model.model_fields
assert "also_keep" in meta.arg_model.model_fields
assert "skip_this" not in meta.arg_model.model_fields
assert "also_skip" not in meta.arg_model.model_fields
# Validate that we can call with only non-skipped parameters
model: BaseModel = meta.arg_model.model_validate({"keep_this": 1, "also_keep": 2.5}) # type: ignore
assert model.keep_this == 1 # type: ignore
assert model.also_keep == 2.5 # type: ignore
async def test_lambda_function():
"""Test lambda function schema and validation"""
fn = lambda x, y=5: x # noqa: E731
meta = func_metadata(lambda x, y=5: x)
# Test schema
assert meta.arg_model.model_json_schema() == {
"properties": {
"x": {"title": "x", "type": "string"},
"y": {"default": 5, "title": "y", "type": "string"},
},
"required": ["x"],
"title": "<lambda>Arguments",
"type": "object",
}
async def check_call(args):
return await meta.call_fn_with_arg_validation(
fn,
fn_is_async=False,
arguments_to_validate=args,
arguments_to_pass_directly=None,
)
# Basic calls
assert await check_call({"x": "hello"}) == "hello"
assert await check_call({"x": "hello", "y": "world"}) == "hello"
assert await check_call({"x": '"hello"'}) == '"hello"'
# Missing required arg
with pytest.raises(ValueError):
await check_call({"y": "world"})
def test_complex_function_json_schema():
meta = func_metadata(complex_arguments_fn)
assert meta.arg_model.model_json_schema() == {
"$defs": {
"InnerModel": {
"properties": {"x": {"title": "X", "type": "integer"}},
"required": ["x"],
"title": "InnerModel",
"type": "object",
},
"SomeInputModelA": {
"properties": {},
"title": "SomeInputModelA",
"type": "object",
},
"SomeInputModelB": {
"properties": {
"how_many_shrimp": {
"description": "How many shrimp in the tank???",
"title": "How Many Shrimp",
"type": "integer",
},
"ok": {"$ref": "#/$defs/InnerModel"},
"y": {"title": "Y", "type": "null"},
},
"required": ["how_many_shrimp", "ok", "y"],
"title": "SomeInputModelB",
"type": "object",
},
},
"properties": {
"an_int": {"title": "An Int", "type": "integer"},
"must_be_none": {"title": "Must Be None", "type": "null"},
"must_be_none_dumb_annotation": {
"title": "Must Be None Dumb Annotation",
"type": "null",
},
"list_of_ints": {
"items": {"type": "integer"},
"title": "List Of Ints",
"type": "array",
},
"list_str_or_str": {
"anyOf": [
{"items": {"type": "string"}, "type": "array"},
{"type": "string"},
],
"title": "List Str Or Str",
},
"an_int_annotated_with_field": {
"description": "An int with a field",
"title": "An Int Annotated With Field",
"type": "integer",
},
"an_int_annotated_with_field_and_others": {
"description": "An int with a field",
"exclusiveMinimum": 1,
"title": "An Int Annotated With Field And Others",
"type": "integer",
},
"an_int_annotated_with_junk": {
"title": "An Int Annotated With Junk",
"type": "integer",
},
"field_with_default_via_field_annotation_before_nondefault_arg": {
"default": 1,
"title": "Field With Default Via Field Annotation Before Nondefault Arg",
"type": "integer",
},
"unannotated": {"title": "unannotated", "type": "string"},
"my_model_a": {"$ref": "#/$defs/SomeInputModelA"},
"my_model_a_forward_ref": {"$ref": "#/$defs/SomeInputModelA"},
"my_model_b": {"$ref": "#/$defs/SomeInputModelB"},
"an_int_annotated_with_field_default": {
"default": 1,
"description": "An int with a field",
"title": "An Int Annotated With Field Default",
"type": "integer",
},
"unannotated_with_default": {
"default": 5,
"title": "unannotated_with_default",
"type": "string",
},
"my_model_a_with_default": {
"$ref": "#/$defs/SomeInputModelA",
"default": {},
},
"an_int_with_default": {
"default": 1,
"title": "An Int With Default",
"type": "integer",
},
"must_be_none_with_default": {
"default": None,
"title": "Must Be None With Default",
"type": "null",
},
"an_int_with_equals_field": {
"default": 1,
"minimum": 0,
"title": "An Int With Equals Field",
"type": "integer",
},
"int_annotated_with_default": {
"default": 5,
"description": "hey",
"title": "Int Annotated With Default",
"type": "integer",
},
},
"required": [
"an_int",
"must_be_none",
"must_be_none_dumb_annotation",
"list_of_ints",
"list_str_or_str",
"an_int_annotated_with_field",
"an_int_annotated_with_field_and_others",
"an_int_annotated_with_junk",
"unannotated",
"my_model_a",
"my_model_a_forward_ref",
"my_model_b",
],
"title": "complex_arguments_fnArguments",
"type": "object",
}
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