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feat: Support "stop" parameter in remote:vLLM
Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
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4 changed files with 34 additions and 0 deletions
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@ -201,6 +201,7 @@ class SamplingParams(BaseModel):
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max_tokens: Optional[int] = 0
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repetition_penalty: Optional[float] = 1.0
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stop: Optional[List[str]] = None
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class CheckpointQuantizationFormat(Enum):
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@ -147,6 +147,9 @@ def get_sampling_options(params: SamplingParams) -> dict:
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if params.repetition_penalty is not None and params.repetition_penalty != 1.0:
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options["repeat_penalty"] = params.repetition_penalty
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if params.stop is not None:
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options["stop"] = params.stop
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return options
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@ -99,6 +99,30 @@ def test_text_completion_streaming(client_with_models, text_model_id, test_case)
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assert len(content_str) > 10
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@pytest.mark.parametrize(
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"test_case",
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[
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"inference:completion:stop_sequence",
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],
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)
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def test_text_completion_stop_sequence(client_with_models, text_model_id, test_case):
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skip_if_model_doesnt_support_completion(client_with_models, text_model_id)
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tc = TestCase(test_case)
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response = client_with_models.inference.completion(
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content=tc["content"],
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stream=True,
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model_id=text_model_id,
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sampling_params={
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"max_tokens": 50,
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"stop": ["1963"],
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},
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)
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streamed_content = [chunk.delta for chunk in response]
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content_str = "".join(streamed_content).lower().strip()
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assert "1963" not in content_str
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@pytest.mark.parametrize(
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"test_case",
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[
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@ -10,6 +10,12 @@
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"expected": "1963"
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}
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},
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"stop_sequence": {
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"data": {
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"content": "Return the exact same sentence: Michael Jordan was born in 1963",
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"expected": "Michael Jordan was born in"
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}
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},
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"streaming": {
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"data": {
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"content": "Roses are red,"
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