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"""Unit tests for define_tool"""

import json

import pytest

from pydantic import BaseModel, Field

from copilot import define_tool

from copilot.tools import (

ToolInvocation,

ToolResult,

_normalize_result,

convert_mcp_call_tool_result,

)

class TestDefineTool:

def test_creates_tool_with_correct_name_and_description(self):

class Params(BaseModel):

query: str

@define_tool("search", description="Search for something")

def search(params: Params, invocation: ToolInvocation) -> str:

return "result"

assert search.name == "search"

assert search.description == "Search for something"

assert search.handler is not None

assert search.parameters is not None

def test_infers_name_from_function(self):

class Params(BaseModel):

query: str

@define_tool(description="Search for something")

def my_search_tool(params: Params) -> str:

return "result"

assert my_search_tool.name == "my_search_tool"

def test_generates_schema_from_pydantic_model(self):

class Params(BaseModel):

city: str = Field(description="City name")

unit: str = Field(description="Temperature unit")

@define_tool("get_weather", description="Get weather")

def get_weather(params: Params, invocation: ToolInvocation) -> str:

return "sunny"

schema = get_weather.parameters

assert schema is not None

assert schema["type"] == "object"

assert "city" in schema["properties"]

assert "unit" in schema["properties"]

assert schema["properties"]["city"]["description"] == "City name"

async def test_handler_receives_typed_arguments(self):

class Params(BaseModel):

received_params = None

@define_tool("test", description="Test tool")

def test_tool(params: Params, invocation: ToolInvocation) -> str:

nonlocal received_params

received_params = params

return "ok"

invocation = ToolInvocation(

session_id="session-1",

tool_call_id="call-1",

tool_name="test",

arguments={"name": "Alice", "count": 42},

)

await test_tool.handler(invocation)

assert received_params is not None

assert received_params.name == "Alice"

assert received_params.count == 42

async def test_handler_receives_invocation(self):

class Params(BaseModel):

pass

received_inv = None

@define_tool("test", description="Test tool")

def test_tool(params: Params, invocation: ToolInvocation) -> str:

nonlocal received_inv

received_inv = invocation

return "ok"

invocation = ToolInvocation(

session_id="session-123",

tool_call_id="call-456",

tool_name="test",

arguments={},

)

await test_tool.handler(invocation)

assert received_inv.session_id == "session-123"

assert received_inv.tool_call_id == "call-456"

async def test_zero_param_handler(self):

"""Handler with no parameters: def handler() -> str"""

called = False

@define_tool("test", description="Test tool")

def test_tool() -> str:

nonlocal called

called = True

return "ok"

invocation = ToolInvocation(

session_id="s1",

tool_call_id="c1",

tool_name="test",

arguments={},

)

result = await test_tool.handler(invocation)

assert called

assert result.text_result_for_llm == "ok"

async def test_invocation_only_handler(self):

"""Handler with only invocation: def handler(invocation) -> str"""

received_inv = None

@define_tool("test", description="Test tool")

def test_tool(invocation: ToolInvocation) -> str:

nonlocal received_inv

received_inv = invocation

return "ok"

invocation = ToolInvocation(

session_id="s1",

tool_call_id="c1",

tool_name="test",

arguments={},

)

await test_tool.handler(invocation)

assert received_inv is not None

assert received_inv.session_id == "s1"

async def test_params_only_handler(self):

"""Handler with only params: def handler(params) -> str"""

class Params(BaseModel):

value: str

received_params = None

@define_tool("test", description="Test tool")

def test_tool(params: Params) -> str:

nonlocal received_params

received_params = params

return "ok"

invocation = ToolInvocation(

session_id="s1",

tool_call_id="c1",

tool_name="test",

arguments={"value": "hello"},

)

await test_tool.handler(invocation)

assert received_params is not None

assert received_params.value == "hello"

async def test_handler_error_is_hidden_from_llm(self):

class Params(BaseModel):

pass

@define_tool("failing", description="A failing tool")

def failing_tool(params: Params, invocation: ToolInvocation) -> str:

raise ValueError("secret error message")

invocation = ToolInvocation(

session_id="s1",

tool_call_id="c1",

tool_name="failing",

arguments={},

)

result = await failing_tool.handler(invocation)

assert result.result_type == "failure"

assert "secret error message" not in result.text_result_for_llm

assert "error" in result.text_result_for_llm.lower()

# But the actual error is stored internally

assert result.error == "secret error message"

async def test_function_style_api(self):

class Params(BaseModel):

value: str

tool = define_tool(

"my_tool",

description="My tool",

handler=lambda params, inv: params.value.upper(),

params_type=Params,

)

assert tool.name == "my_tool"

assert tool.description == "My tool"

result = await tool.handler(

ToolInvocation(

session_id="s",

tool_call_id="c",

tool_name="my_tool",

arguments={"value": "hello"},

)

assert result.text_result_for_llm == "HELLO"

def test_function_style_requires_name(self):

class Params(BaseModel):

value: str

with pytest.raises(ValueError, match="name is required"):

define_tool(

description="My tool",

handler=lambda params, inv: params.value.upper(),

params_type=Params,

)

class TestNormalizeResult:

def test_none_returns_empty_success(self):

result = _normalize_result(None)

assert result.text_result_for_llm == ""

assert result.result_type == "success"

def test_string_passes_through(self):

result = _normalize_result("hello world")

assert result.text_result_for_llm == "hello world"

assert result.result_type == "success"

def test_tool_result_passes_through(self):

input_result = ToolResult(

text_result_for_llm="custom",

result_type="failure",

error="some error",

)

result = _normalize_result(input_result)

assert result.text_result_for_llm == "custom"

assert result.result_type == "failure"

def test_dict_is_json_serialized(self):

result = _normalize_result({"key": "value", "num": 42})

parsed = json.loads(result.text_result_for_llm)

assert parsed == {"key": "value", "num": 42}

assert result.result_type == "success"

def test_list_is_json_serialized(self):

result = _normalize_result(["a", "b", "c"])

assert result.text_result_for_llm == '["a", "b", "c"]'

assert result.result_type == "success"

def test_pydantic_model_is_serialized(self):

class Response(BaseModel):

status: str

result = _normalize_result(Response(status="ok", count=5))

parsed = json.loads(result.text_result_for_llm)

assert parsed == {"status": "ok", "count": 5}

def test_list_of_pydantic_models_is_serialized(self):

class Item(BaseModel):

value: int

items = [Item(name="a", value=1), Item(name="b", value=2)]

result = _normalize_result(items)

parsed = json.loads(result.text_result_for_llm)

assert parsed == [{"name": "a", "value": 1}, {"name": "b", "value": 2}]

assert result.result_type == "success"

def test_raises_for_unserializable_value(self):

# Functions cannot be JSON serialized

with pytest.raises(TypeError, match="Failed to serialize"):

_normalize_result(lambda x: x)

class TestConvertMcpCallToolResult:

def test_text_only_call_tool_result(self):

result = convert_mcp_call_tool_result(

{

"content": [{"type": "text", "text": "hello"}],

}

)

assert result.text_result_for_llm == "hello"

assert result.result_type == "success"

def test_multiple_text_blocks(self):

result = convert_mcp_call_tool_result(

{

"content": [

{"type": "text", "text": "line 1"},

{"type": "text", "text": "line 2"},

}

)

assert result.text_result_for_llm == "line 1\nline 2"

def test_is_error_maps_to_failure(self):

result = convert_mcp_call_tool_result(

{

"content": [{"type": "text", "text": "oops"}],

"isError": True,

}

)

assert result.result_type == "failure"

def test_is_error_false_maps_to_success(self):

result = convert_mcp_call_tool_result(

{

"content": [{"type": "text", "text": "ok"}],

"isError": False,

}

)

assert result.result_type == "success"

def test_image_content_to_binary(self):

result = convert_mcp_call_tool_result(

{

"content": [{"type": "image", "data": "base64data", "mimeType": "image/png"}],

}

)

assert result.binary_results_for_llm is not None

assert len(result.binary_results_for_llm) == 1

assert result.binary_results_for_llm[0].data == "base64data"

assert result.binary_results_for_llm[0].mime_type == "image/png"

assert result.binary_results_for_llm[0].type == "image"

def test_resource_text_to_text_result(self):

result = convert_mcp_call_tool_result(

{

"content": [

{

"type": "resource",

"resource": {"uri": "file:///data.txt", "text": "file contents"},

}

)

assert result.text_result_for_llm == "file contents"

def test_resource_blob_to_binary(self):

result = convert_mcp_call_tool_result(

{

"content": [

{

"type": "resource",

"resource": {

"uri": "file:///img.png",

"blob": "blobdata",

"mimeType": "image/png",

}

)

assert result.binary_results_for_llm is not None

assert len(result.binary_results_for_llm) == 1

assert result.binary_results_for_llm[0].data == "blobdata"

assert result.binary_results_for_llm[0].mime_type == "image/png"

assert result.binary_results_for_llm[0].description == "file:///img.png"

def test_resource_blob_defaults_missing_or_empty_mime_type(self):

result = convert_mcp_call_tool_result(

{

"content": [

{

"type": "resource",

"resource": {"uri": "file:///data.bin", "blob": "binarydata"},

{

"type": "resource",

"resource": {

"uri": "file:///empty-mime.bin",

"blob": "binarydata2",

"mimeType": "",

}

)

assert result.binary_results_for_llm is not None

assert len(result.binary_results_for_llm) == 2

assert result.binary_results_for_llm[0].mime_type == "application/octet-stream"

assert result.binary_results_for_llm[1].mime_type == "application/octet-stream"

def test_empty_content_array(self):

result = convert_mcp_call_tool_result({"content": []})

assert result.text_result_for_llm == ""

assert result.result_type == "success"

def test_call_tool_result_dict_is_json_serialized_by_normalize(self):

"""_normalize_result does NOT auto-detect MCP results; it JSON-serializes them."""

result = _normalize_result({"content": [{"type": "text", "text": "hello"}]})

parsed = json.loads(result.text_result_for_llm)

assert parsed == {"content": [{"type": "text", "text": "hello"}]}

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