| | |
| | |
| | |
| | from datetime import datetime |
| | from typing import Iterator |
| | from unittest.mock import MagicMock, patch |
| |
|
| | import pytest |
| | from openai import Stream |
| | from openai.types.chat import ChatCompletionChunk |
| | from openai.types.chat.chat_completion_chunk import Choice, ChoiceDelta |
| |
|
| |
|
| | @pytest.fixture |
| | def mock_auto_tokenizer(): |
| | """ |
| | In the original mock_auto_tokenizer fixture, we were mocking the transformers.AutoTokenizer.from_pretrained |
| | method directly, but we were not providing a return value for this method. Therefore, when from_pretrained |
| | was called within HuggingFaceTGIChatGenerator, it returned None because that's the default behavior of a |
| | MagicMock object when a return value isn't specified. |
| | |
| | We will update the mock_auto_tokenizer fixture to return a MagicMock object when from_pretrained is called |
| | in another PR. For now, we will use this fixture to mock the AutoTokenizer.from_pretrained method. |
| | """ |
| |
|
| | with patch("transformers.AutoTokenizer.from_pretrained", autospec=True) as mock_from_pretrained: |
| | mock_tokenizer = MagicMock() |
| | mock_from_pretrained.return_value = mock_tokenizer |
| | yield mock_tokenizer |
| |
|
| |
|
| | @pytest.fixture |
| | def mock_chat_completion_chunk(): |
| | """ |
| | Mock the OpenAI API completion chunk response and reuse it for tests |
| | """ |
| |
|
| | class MockStream(Stream[ChatCompletionChunk]): |
| | def __init__(self, mock_chunk: ChatCompletionChunk, client=None, *args, **kwargs): |
| | client = client or MagicMock() |
| | super().__init__(client=client, *args, **kwargs) |
| | self.mock_chunk = mock_chunk |
| |
|
| | def __stream__(self) -> Iterator[ChatCompletionChunk]: |
| | |
| | yield self.mock_chunk |
| |
|
| | with patch("openai.resources.chat.completions.Completions.create") as mock_chat_completion_create: |
| | completion = ChatCompletionChunk( |
| | id="foo", |
| | model="gpt-4", |
| | object="chat.completion.chunk", |
| | choices=[ |
| | Choice( |
| | finish_reason="stop", logprobs=None, index=0, delta=ChoiceDelta(content="Hello", role="assistant") |
| | ) |
| | ], |
| | created=int(datetime.now().timestamp()), |
| | usage={"prompt_tokens": 57, "completion_tokens": 40, "total_tokens": 97}, |
| | ) |
| | mock_chat_completion_create.return_value = MockStream(completion, cast_to=None, response=None, client=None) |
| | yield mock_chat_completion_create |
| |
|
