Files
zk-data-agent/tests/test_openai_compat.py
T
2026-05-08 12:17:00 +08:00

435 lines
16 KiB
Python

from __future__ import annotations
import json
import unittest
from unittest.mock import patch
from src.openai_compat import (
OpenAICompatClient,
OpenAICompatError,
_anthropic_base_url,
_build_response_format,
_join_url,
_normalize_content,
_optional_int,
_parse_tool_arguments,
_parse_usage,
_temperature_for_model,
_uses_anthropic_messages_api,
)
from src.agent_types import ModelConfig, OutputSchemaConfig, UsageStats
class FakeHTTPResponse:
def __init__(self, payload: dict[str, object]) -> None:
self.payload = payload
def read(self) -> bytes:
return json.dumps(self.payload).encode('utf-8')
def __enter__(self) -> 'FakeHTTPResponse':
return self
def __exit__(self, exc_type, exc, tb) -> None:
return None
class FakeStreamingHTTPResponse:
def __init__(self, payloads: list[dict[str, object]]) -> None:
self.lines: list[bytes] = []
for payload in payloads:
self.lines.append(b'event: message\n')
self.lines.append(f'data: {json.dumps(payload)}\n'.encode('utf-8'))
self.lines.append(b'\n')
def readline(self) -> bytes:
if not self.lines:
return b''
return self.lines.pop(0)
def __enter__(self) -> 'FakeStreamingHTTPResponse':
return self
def __exit__(self, exc_type, exc, tb) -> None:
return None
class TestJoinUrl(unittest.TestCase):
def test_base_with_trailing_slash(self):
self.assertEqual(_join_url('http://localhost:8000/', 'v1/chat'), 'http://localhost:8000/v1/chat')
def test_base_without_trailing_slash(self):
self.assertEqual(_join_url('http://localhost:8000', 'v1/chat'), 'http://localhost:8000/v1/chat')
def test_suffix_with_leading_slash(self):
self.assertEqual(_join_url('http://localhost:8000', '/v1/chat'), 'http://localhost:8000/v1/chat')
class TestNormalizeContent(unittest.TestCase):
def test_string_passthrough(self):
self.assertEqual(_normalize_content('hello'), 'hello')
def test_none_returns_empty(self):
self.assertEqual(_normalize_content(None), '')
def test_list_of_strings_joined(self):
self.assertEqual(_normalize_content(['hello', ' ', 'world']), 'hello world')
def test_list_of_text_dicts(self):
items = [{'type': 'text', 'text': 'hello'}, {'type': 'text', 'text': ' world'}]
self.assertEqual(_normalize_content(items), 'hello world')
def test_list_of_mixed_items(self):
items = ['start ', {'type': 'text', 'text': 'middle'}, ' end']
self.assertEqual(_normalize_content(items), 'start middle end')
def test_non_string_non_list_returns_str(self):
self.assertEqual(_normalize_content(42), '42')
class TestParseToolArguments(unittest.TestCase):
def test_dict_passthrough(self):
d = {'key': 'value'}
self.assertIs(_parse_tool_arguments(d), d)
def test_valid_json_string(self):
self.assertEqual(_parse_tool_arguments('{"a": 1}'), {'a': 1})
def test_empty_string_returns_empty_dict(self):
self.assertEqual(_parse_tool_arguments(''), {})
def test_none_returns_empty_dict(self):
self.assertEqual(_parse_tool_arguments(None), {})
def test_invalid_json_raises(self):
with self.assertRaises(OpenAICompatError):
_parse_tool_arguments('{bad json}')
def test_json_non_dict_raises(self):
with self.assertRaises(OpenAICompatError):
_parse_tool_arguments('[1, 2, 3]')
def test_unsupported_type_raises(self):
with self.assertRaises(OpenAICompatError):
_parse_tool_arguments(12345)
class TestParseUsage(unittest.TestCase):
def test_standard_fields(self):
usage = _parse_usage({'input_tokens': 10, 'output_tokens': 20})
self.assertEqual(usage.input_tokens, 10)
self.assertEqual(usage.output_tokens, 20)
def test_prompt_completion_aliases(self):
usage = _parse_usage({'prompt_tokens': 15, 'completion_tokens': 25})
self.assertEqual(usage.input_tokens, 15)
self.assertEqual(usage.output_tokens, 25)
def test_ollama_aliases(self):
usage = _parse_usage({'prompt_eval_count': 12, 'eval_count': 18})
self.assertEqual(usage.input_tokens, 12)
self.assertEqual(usage.output_tokens, 18)
def test_cache_tokens(self):
usage = _parse_usage({
'input_tokens': 1,
'output_tokens': 1,
'cache_creation_input_tokens': 100,
'cache_read_input_tokens': 200,
})
self.assertEqual(usage.cache_creation_input_tokens, 100)
self.assertEqual(usage.cache_read_input_tokens, 200)
def test_reasoning_tokens_top_level_and_details(self):
usage_top = _parse_usage({'input_tokens': 1, 'output_tokens': 1, 'reasoning_tokens': 50})
self.assertEqual(usage_top.reasoning_tokens, 50)
usage_details = _parse_usage({
'input_tokens': 1,
'output_tokens': 1,
'completion_tokens_details': {'reasoning_tokens': 75},
})
self.assertEqual(usage_details.reasoning_tokens, 75)
def test_non_dict_returns_empty(self):
usage = _parse_usage('not a dict')
self.assertEqual(usage, UsageStats())
def test_string_number_coercion(self):
usage = _parse_usage({'input_tokens': '10', 'output_tokens': '20'})
self.assertEqual(usage.input_tokens, 10)
self.assertEqual(usage.output_tokens, 20)
class TestBuildResponseFormat(unittest.TestCase):
def test_none_returns_none(self):
self.assertIsNone(_build_response_format(None))
def test_valid_schema(self):
schema = OutputSchemaConfig(
name='test_schema',
schema={'type': 'object', 'properties': {'x': {'type': 'integer'}}},
strict=True,
)
result = _build_response_format(schema)
self.assertEqual(result, {
'type': 'json_schema',
'json_schema': {
'name': 'test_schema',
'schema': {'type': 'object', 'properties': {'x': {'type': 'integer'}}},
'strict': True,
},
})
class TestOptionalInt(unittest.TestCase):
def test_int_passthrough(self):
self.assertEqual(_optional_int(42), 42)
def test_float_truncated(self):
self.assertEqual(_optional_int(3.9), 3)
def test_string_parsed(self):
self.assertEqual(_optional_int('7'), 7)
def test_bool_returns_zero(self):
self.assertEqual(_optional_int(True), 0)
self.assertEqual(_optional_int(False), 0)
def test_none_returns_zero(self):
self.assertEqual(_optional_int(None), 0)
def test_invalid_string_returns_zero(self):
self.assertEqual(_optional_int('abc'), 0)
class TestProviderTemperatureFloor(unittest.TestCase):
def test_minimax_temperature_is_clamped_to_provider_minimum(self):
self.assertEqual(_temperature_for_model('minimax/MiniMax-M2.5', 0.0), 0.01)
def test_wenxin_temperature_is_clamped_to_provider_minimum(self):
self.assertEqual(_temperature_for_model('wenxin/ernie-4.0-turbo-128k', 0.0), 0.1)
def test_regular_models_keep_configured_temperature(self):
self.assertEqual(_temperature_for_model('xiaomi/mimo-v2-flash', 0.0), 0.0)
def test_payload_uses_temperature_floor(self):
client = OpenAICompatClient(
ModelConfig(model='minimax/MiniMax-M2.5', temperature=0.0)
)
payload = client._build_payload( # noqa: SLF001 - verify payload compatibility.
messages=[{'role': 'user', 'content': 'hi'}],
tools=[],
stream=False,
output_schema=None,
)
self.assertEqual(payload['temperature'], 0.01)
def test_payload_omits_tool_choice_when_no_tools_are_supplied(self):
client = OpenAICompatClient(ModelConfig(model='azure_openai/gpt-4o-mini'))
payload = client._build_payload( # noqa: SLF001 - verify provider compatibility.
messages=[{'role': 'user', 'content': 'hi'}],
tools=[],
stream=False,
output_schema=None,
)
self.assertNotIn('tools', payload)
self.assertNotIn('tool_choice', payload)
def test_payload_includes_tool_choice_when_tools_are_supplied(self):
client = OpenAICompatClient(ModelConfig(model='azure_openai/gpt-4o-mini'))
payload = client._build_payload( # noqa: SLF001 - verify provider compatibility.
messages=[{'role': 'user', 'content': 'hi'}],
tools=[{'type': 'function', 'function': {'name': 'noop', 'parameters': {}}}],
stream=False,
output_schema=None,
)
self.assertIn('tools', payload)
self.assertEqual(payload['tool_choice'], 'auto')
class TestAnthropicMessagesRouting(unittest.TestCase):
def test_ppio_pa_claude_uses_anthropic_messages_api(self):
self.assertTrue(
_uses_anthropic_messages_api(
'ppio/pa/claude-opus-4-7',
'http://model.mify.ai.srv/v1',
)
)
self.assertFalse(
_uses_anthropic_messages_api(
'ppio/gemini-2.5-pro',
'http://model.mify.ai.srv/v1',
)
)
def test_anthropic_base_url_is_derived_from_openai_base(self):
self.assertEqual(
_anthropic_base_url('http://model.mify.ai.srv/v1'),
'http://model.mify.ai.srv/anthropic',
)
self.assertEqual(
_anthropic_base_url('http://model.mify.ai.srv/anthropic'),
'http://model.mify.ai.srv/anthropic',
)
def test_anthropic_complete_converts_tools_and_parses_tool_use(self):
recorded: dict[str, object] = {}
def fake_urlopen(request_obj, timeout=None): # noqa: ANN001
recorded['url'] = request_obj.full_url
recorded['payload'] = json.loads(request_obj.data.decode('utf-8'))
return FakeHTTPResponse(
{
'id': 'msg_1',
'type': 'message',
'role': 'assistant',
'content': [
{'type': 'text', 'text': '我来读取文件。'},
{
'type': 'tool_use',
'id': 'toolu_1',
'name': 'read_file',
'input': {'path': 'hello.txt'},
},
],
'stop_reason': 'tool_use',
'usage': {'input_tokens': 10, 'output_tokens': 4},
}
)
client = OpenAICompatClient(
ModelConfig(
model='ppio/pa/claude-opus-4-7',
base_url='http://model.mify.ai.srv/v1',
api_key='token',
)
)
with patch('src.openai_compat.request.urlopen', side_effect=fake_urlopen):
turn = client.complete(
messages=[
{'role': 'system', 'content': '你是工具型助手。'},
{'role': 'user', 'content': '读取 hello.txt'},
],
tools=[
{
'type': 'function',
'function': {
'name': 'read_file',
'description': '读取文件',
'parameters': {
'type': 'object',
'properties': {'path': {'type': 'string'}},
'required': ['path'],
},
},
}
],
)
self.assertEqual(
recorded['url'],
'http://model.mify.ai.srv/anthropic/v1/messages',
)
payload = recorded['payload']
self.assertEqual(payload['model'], 'ppio/pa/claude-opus-4-7')
self.assertEqual(payload['system'], '你是工具型助手。')
self.assertEqual(payload['tools'][0]['name'], 'read_file')
self.assertEqual(payload['tools'][0]['input_schema']['required'], ['path'])
self.assertEqual(turn.content, '我来读取文件。')
self.assertEqual(turn.finish_reason, 'tool_use')
self.assertEqual(turn.tool_calls[0].id, 'toolu_1')
self.assertEqual(turn.tool_calls[0].arguments, {'path': 'hello.txt'})
self.assertEqual(turn.usage.input_tokens, 10)
def test_anthropic_stream_parses_text_usage_and_tool_use(self):
payloads = [
{
'type': 'message_start',
'message': {'usage': {'input_tokens': 7, 'output_tokens': 1}},
},
{
'type': 'content_block_start',
'index': 0,
'content_block': {'type': 'text', 'text': ''},
},
{
'type': 'content_block_delta',
'index': 0,
'delta': {'type': 'text_delta', 'text': '读取'},
},
{
'type': 'content_block_start',
'index': 1,
'content_block': {
'type': 'tool_use',
'id': 'toolu_1',
'name': 'read_file',
'input': {},
},
},
{
'type': 'content_block_delta',
'index': 1,
'delta': {'type': 'input_json_delta', 'partial_json': '{"path":'},
},
{
'type': 'content_block_delta',
'index': 1,
'delta': {'type': 'input_json_delta', 'partial_json': '"hello.txt"}'},
},
{
'type': 'message_delta',
'delta': {'stop_reason': 'tool_use'},
'usage': {'output_tokens': 5},
},
{'type': 'message_stop'},
]
def fake_urlopen(request_obj, timeout=None): # noqa: ANN001
return FakeStreamingHTTPResponse(payloads)
client = OpenAICompatClient(
ModelConfig(
model='ppio/pa/claude-opus-4-7',
base_url='http://model.mify.ai.srv/v1',
api_key='token',
)
)
with patch('src.openai_compat.request.urlopen', side_effect=fake_urlopen):
events = list(
client.stream(
messages=[{'role': 'user', 'content': '读取 hello.txt'}],
tools=[
{
'type': 'function',
'function': {
'name': 'read_file',
'parameters': {'type': 'object'},
},
}
],
)
)
self.assertEqual(events[0].type, 'message_start')
self.assertEqual(
''.join(event.delta for event in events if event.type == 'content_delta'),
'读取',
)
tool_events = [event for event in events if event.type == 'tool_call_delta']
self.assertEqual(tool_events[0].tool_call_index, 0)
self.assertEqual(tool_events[0].tool_call_id, 'toolu_1')
self.assertEqual(tool_events[0].tool_name, 'read_file')
self.assertEqual(
''.join(event.arguments_delta for event in tool_events),
'{"path":"hello.txt"}',
)
self.assertTrue(any(event.type == 'usage' for event in events))
self.assertEqual(events[-1].type, 'message_stop')
self.assertEqual(events[-1].finish_reason, 'tool_use')
if __name__ == '__main__':
unittest.main()