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from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from lm_eval.models.openai_completions import LocalCompletionsAPI
@pytest.fixture
def api():
return LocalCompletionsAPI(
base_url="http://test-url.com", tokenizer_backend=None, model="gpt-3.5-turbo"
)
@pytest.fixture
def api_tokenized():
return LocalCompletionsAPI(
base_url="http://test-url.com",
model="EleutherAI/pythia-1b",
tokenizer_backend="huggingface",
)
@pytest.fixture
def api_batch_ssl_tokenized():
return LocalCompletionsAPI(
base_url="https://test-url.com",
model="EleutherAI/pythia-1b",
verify_certificate=False,
num_concurrent=2,
tokenizer_backend="huggingface",
)
def test_create_payload_generate(api):
messages = ["Generate a story"]
gen_kwargs = {
"max_tokens": 100,
"temperature": 0.7,
"until": ["The End"],
"do_sample": True,
"seed": 1234,
}
payload = api._create_payload(messages, generate=True, gen_kwargs=gen_kwargs)
assert payload == {
"prompt": ["Generate a story"],
"model": "gpt-3.5-turbo",
"max_tokens": 100,
"temperature": 0.7,
"stop": ["The End"],
"seed": 1234,
}
def test_create_payload_loglikelihood(api):
messages = ["The capital of France is"]
payload = api._create_payload(messages, generate=False, gen_kwargs=None)
assert payload == {
"model": "gpt-3.5-turbo",
"prompt": ["The capital of France is"],
"max_tokens": 1,
"logprobs": 1,
"echo": True,
"temperature": 0,
"seed": 1234,
}
@pytest.mark.parametrize(
"input_messages, generate, gen_kwargs, expected_payload",
[
(
["Hello, how are"],
True,
{"max_gen_toks": 100, "temperature": 0.7, "until": ["hi"]},
{
"prompt": "Hello, how are",
"model": "gpt-3.5-turbo",
"max_tokens": 100,
"temperature": 0.7,
"stop": ["hi"],
"seed": 1234,
},
),
(
["Hello, how are", "you"],
True,
{},
{
"prompt": "Hello, how are",
"model": "gpt-3.5-turbo",
"max_tokens": 256,
"temperature": 0,
"stop": [],
"seed": 1234,
},
),
],
)
def test_model_generate_call_usage(
api, input_messages, generate, gen_kwargs, expected_payload
):
with patch("requests.post") as mock_post:
mock_response = MagicMock()
mock_response.json.return_value = {"result": "success"}
mock_post.return_value = mock_response
# Act
result = api.model_call(
input_messages, generate=generate, gen_kwargs=gen_kwargs
)
# Assert
mock_post.assert_called_once()
_, kwargs = mock_post.call_args
assert "json" in kwargs
assert kwargs["json"] == expected_payload
assert result == {"result": "success"}
@pytest.mark.parametrize(
"input_messages, generate, gen_kwargs, expected_payload",
[
(
[[1, 2, 3, 4, 5]],
False,
None,
{
"model": "EleutherAI/pythia-1b",
"prompt": [[1, 2, 3, 4, 5]],
"max_tokens": 1,
"logprobs": 1,
"echo": True,
"seed": 1234,
"temperature": 0,
},
),
],
)
def test_model_tokenized_call_usage(
api_tokenized, input_messages, generate, gen_kwargs, expected_payload
):
with patch("requests.post") as mock_post:
mock_response = MagicMock()
mock_response.json.return_value = {"result": "success"}
mock_post.return_value = mock_response
# Act
result = api_tokenized.model_call(
input_messages, generate=generate, gen_kwargs=gen_kwargs
)
# Assert
mock_post.assert_called_once()
_, kwargs = mock_post.call_args
assert "json" in kwargs
assert kwargs["json"] == expected_payload
assert result == {"result": "success"}
class DummyAsyncContextManager:
def __init__(self, result):
self.result = result
async def __aenter__(self):
return self.result
async def __aexit__(self, exc_type, exc, tb):
pass
@pytest.mark.parametrize(
"expected_inputs, expected_ctxlens, expected_cache_keys",
[
(
[
[1, 2, 3, 4, 5],
[6, 7, 8, 9, 10],
[11, 12, 13, 14, 15],
[16, 17, 18, 19, 20],
],
[3, 3, 3, 3],
["cache_key1", "cache_key2", "cache_key3", "cache_key4"],
),
],
)
def test_get_batched_requests_with_no_ssl(
api_batch_ssl_tokenized, expected_inputs, expected_ctxlens, expected_cache_keys
):
with (
patch(
"lm_eval.models.api_models.TCPConnector", autospec=True
) as mock_connector,
patch(
"lm_eval.models.api_models.ClientSession", autospec=True
) as mock_client_session,
patch(
"lm_eval.models.openai_completions.LocalCompletionsAPI.parse_logprobs",
autospec=True,
) as mock_parse,
):
mock_session_instance = AsyncMock()
mock_post_response = AsyncMock()
mock_post_response.status = 200
mock_post_response.ok = True
mock_post_response.json = AsyncMock(return_value={"mocked": "response"})
mock_post_response.raise_for_status = lambda: None
mock_session_instance.post = lambda *args, **kwargs: DummyAsyncContextManager(
mock_post_response
)
mock_client_session.return_value.__aenter__.return_value = mock_session_instance
mock_parse.return_value = [(1.23, True), (4.56, False)]
async def run():
return await api_batch_ssl_tokenized.get_batched_requests(
expected_inputs,
expected_cache_keys,
generate=False,
ctxlens=expected_ctxlens,
)
result_batches = asyncio.run(run())
mock_connector.assert_called_with(limit=2, ssl=False)
assert result_batches
|