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from unittest.mock import 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",
)
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"}
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