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66 lines
1.6 KiB
Python
66 lines
1.6 KiB
Python
import os
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from typing import List
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import pytest
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from langchain_openai import OpenAI
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os.environ["OPENAI_API_KEY"] = "foo"
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def test_openai_model_param() -> None:
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llm = OpenAI(model="foo")
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assert llm.model_name == "foo"
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llm = OpenAI(model_name="foo")
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assert llm.model_name == "foo"
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def test_openai_model_kwargs() -> None:
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llm = OpenAI(model_kwargs={"foo": "bar"})
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assert llm.model_kwargs == {"foo": "bar"}
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def test_openai_invalid_model_kwargs() -> None:
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with pytest.raises(ValueError):
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OpenAI(model_kwargs={"model_name": "foo"})
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def test_openai_incorrect_field() -> None:
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with pytest.warns(match="not default parameter"):
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llm = OpenAI(foo="bar")
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assert llm.model_kwargs == {"foo": "bar"}
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@pytest.fixture
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def mock_completion() -> dict:
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return {
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"id": "cmpl-3evkmQda5Hu7fcZavknQda3SQ",
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"object": "text_completion",
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"created": 1689989000,
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"model": "text-davinci-003",
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"choices": [
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{"text": "Bar Baz", "index": 0, "logprobs": None, "finish_reason": "length"}
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],
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"usage": {"prompt_tokens": 1, "completion_tokens": 2, "total_tokens": 3},
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}
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@pytest.mark.parametrize(
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"model",
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[
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"gpt-3.5-turbo-instruct",
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"text-davinci-003",
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],
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)
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def test_get_token_ids(model: str) -> None:
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OpenAI(model=model).get_token_ids("foo")
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return
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def test_custom_token_counting() -> None:
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def token_encoder(text: str) -> List[int]:
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return [1, 2, 3]
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llm = OpenAI(custom_get_token_ids=token_encoder)
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assert llm.get_token_ids("foo") == [1, 2, 3]
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