chore(api/tests): apply ruff reformat #7590 (#7591)

Co-authored-by: -LAN- <[email protected]>

api/pyproject.toml

@@ -76,7 +76,6 @@ exclude = [
     "migrations/**/*",
     "services/**/*.py",
     "tasks/**/*.py",
-    "tests/**/*.py",
 ]
 
 [tool.pytest_env]

api/tests/integration_tests/model_runtime/__mock/anthropic.py

@@ -22,76 +22,64 @@
 )
 from anthropic.types.message_delta_event import Delta
 
-MOCK = os.getenv('MOCK_SWITCH', 'false') == 'true'
+MOCK = os.getenv("MOCK_SWITCH", "false") == "true"
 
 
 class MockAnthropicClass:
     @staticmethod
     def mocked_anthropic_chat_create_sync(model: str) -> Message:
         return Message(
-            id='msg-123',
-            type='message',
-            role='assistant',
-            content=[ContentBlock(text='hello, I\'m a chatbot from anthropic', type='text')],
+            id="msg-123",
+            type="message",
+            role="assistant",
+            content=[ContentBlock(text="hello, I'm a chatbot from anthropic", type="text")],
             model=model,
-            stop_reason='stop_sequence',
-            usage=Usage(
-                input_tokens=1,
-                output_tokens=1
-            )
+            stop_reason="stop_sequence",
+            usage=Usage(input_tokens=1, output_tokens=1),
         )
 
     @staticmethod
     def mocked_anthropic_chat_create_stream(model: str) -> Stream[MessageStreamEvent]:
         full_response_text = "hello, I'm a chatbot from anthropic"
 
         yield MessageStartEvent(
-            type='message_start',
+            type="message_start",
             message=Message(
-                id='msg-123',
+                id="msg-123",
                 content=[],
-                role='assistant',
+                role="assistant",
                 model=model,
                 stop_reason=None,
-                type='message',
-                usage=Usage(
-                    input_tokens=1,
-                    output_tokens=1
-                )
-            )
+                type="message",
+                usage=Usage(input_tokens=1, output_tokens=1),
+            ),
         )
 
         index = 0
         for i in range(0, len(full_response_text)):
             yield ContentBlockDeltaEvent(
-                type='content_block_delta',
-                delta=TextDelta(text=full_response_text[i], type='text_delta'),
-                index=index
+                type="content_block_delta", delta=TextDelta(text=full_response_text[i], type="text_delta"), index=index
             )
 
             index += 1
 
         yield MessageDeltaEvent(
-            type='message_delta',
-            delta=Delta(
-                stop_reason='stop_sequence'
-            ),
-            usage=MessageDeltaUsage(
-                output_tokens=1
-            )
+            type="message_delta", delta=Delta(stop_reason="stop_sequence"), usage=MessageDeltaUsage(output_tokens=1)
         )
 
-        yield MessageStopEvent(type='message_stop')
-
-    def mocked_anthropic(self: Messages, *,
-                         max_tokens: int,
-                         messages: Iterable[MessageParam],
-                         model: str,
-                         stream: Literal[True],
-                         **kwargs: Any
-                         ) -> Union[Message, Stream[MessageStreamEvent]]:
+        yield MessageStopEvent(type="message_stop")
+
+    def mocked_anthropic(
+        self: Messages,
+        *,
+        max_tokens: int,
+        messages: Iterable[MessageParam],
+        model: str,
+        stream: Literal[True],
+        **kwargs: Any,
+    ) -> Union[Message, Stream[MessageStreamEvent]]:
         if len(self._client.api_key) < 18:
-            raise anthropic.AuthenticationError('Invalid API key')
+            raise anthropic.AuthenticationError("Invalid API key")
 
         if stream:
             return MockAnthropicClass.mocked_anthropic_chat_create_stream(model=model)
@@ -102,7 +90,7 @@ def mocked_anthropic(self: Messages, *,
 @pytest.fixture
 def setup_anthropic_mock(request, monkeypatch: MonkeyPatch):
     if MOCK:
-        monkeypatch.setattr(Messages, 'create', MockAnthropicClass.mocked_anthropic)
+        monkeypatch.setattr(Messages, "create", MockAnthropicClass.mocked_anthropic)
 
     yield
 

api/tests/integration_tests/model_runtime/__mock/google.py

@@ -12,63 +12,46 @@
 from google.generativeai.types import GenerateContentResponse
 from google.generativeai.types.generation_types import BaseGenerateContentResponse
 
-current_api_key = ''
+current_api_key = ""
+
 
 class MockGoogleResponseClass:
     _done = False
 
     def __iter__(self):
-        full_response_text = 'it\'s google!'
+        full_response_text = "it's google!"
 
         for i in range(0, len(full_response_text) + 1, 1):
             if i == len(full_response_text):
                 self._done = True
                 yield GenerateContentResponse(
-                    done=True,
-                    iterator=None,
-                    result=glm.GenerateContentResponse({
-
-                    }),
-                    chunks=[]
+                    done=True, iterator=None, result=glm.GenerateContentResponse({}), chunks=[]
                 )
             else:
                 yield GenerateContentResponse(
-                    done=False,
-                    iterator=None,
-                    result=glm.GenerateContentResponse({
-
-                    }),
-                    chunks=[]
+                    done=False, iterator=None, result=glm.GenerateContentResponse({}), chunks=[]
                 )
 
+
 class MockGoogleResponseCandidateClass:
-    finish_reason = 'stop'
+    finish_reason = "stop"
 
     @property
     def content(self) -> gag_content.Content:
-        return gag_content.Content(
-            parts=[
-                gag_content.Part(text='it\'s google!')
-            ]
-        )
+        return gag_content.Content(parts=[gag_content.Part(text="it's google!")])
+
 
 class MockGoogleClass:
     @staticmethod
     def generate_content_sync() -> GenerateContentResponse:
-        return GenerateContentResponse(
-            done=True,
-            iterator=None,
-            result=glm.GenerateContentResponse({
-
-            }),
-            chunks=[]
-        )
+        return GenerateContentResponse(done=True, iterator=None, result=glm.GenerateContentResponse({}), chunks=[])
 
     @staticmethod
     def generate_content_stream() -> Generator[GenerateContentResponse, None, None]:
         return MockGoogleResponseClass()
 
-    def generate_content(self: GenerativeModel,
+    def generate_content(
+        self: GenerativeModel,
         contents: content_types.ContentsType,
         *,
         generation_config: generation_config_types.GenerationConfigType | None = None,
@@ -79,21 +62,21 @@ def generate_content(self: GenerativeModel,
         global current_api_key
 
         if len(current_api_key) < 16:
-            raise Exception('Invalid API key')
+            raise Exception("Invalid API key")
 
         if stream:
             return MockGoogleClass.generate_content_stream()
-        
+
         return MockGoogleClass.generate_content_sync()
-    
+
     @property
     def generative_response_text(self) -> str:
-        return 'it\'s google!'
-    
+        return "it's google!"
+
     @property
     def generative_response_candidates(self) -> list[MockGoogleResponseCandidateClass]:
         return [MockGoogleResponseCandidateClass()]
-    
+
     def make_client(self: _ClientManager, name: str):
         global current_api_key
 
@@ -121,7 +104,8 @@ def nop(self, *args, **kwargs):
 
         if not self.default_metadata:
             return client
-
+
+
 @pytest.fixture
 def setup_google_mock(request, monkeypatch: MonkeyPatch):
     monkeypatch.setattr(BaseGenerateContentResponse, "text", MockGoogleClass.generative_response_text)
@@ -131,4 +115,4 @@ def setup_google_mock(request, monkeypatch: MonkeyPatch):
 
     yield
 
-    monkeypatch.undo()
+    monkeypatch.undo()

api/tests/integration_tests/model_runtime/__mock/huggingface.py

@@ -6,14 +6,15 @@
 
 from tests.integration_tests.model_runtime.__mock.huggingface_chat import MockHuggingfaceChatClass
 
-MOCK = os.getenv('MOCK_SWITCH', 'false').lower() == 'true'
+MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true"
+
 
 @pytest.fixture
 def setup_huggingface_mock(request, monkeypatch: MonkeyPatch):
     if MOCK:
         monkeypatch.setattr(InferenceClient, "text_generation", MockHuggingfaceChatClass.text_generation)
-    
+
     yield
 
     if MOCK:
-        monkeypatch.undo()
+        monkeypatch.undo()

api/tests/integration_tests/model_runtime/__mock/huggingface_chat.py

@@ -22,10 +22,8 @@ def generate_create_sync(model: str) -> TextGenerationResponse:
             details=Details(
                 finish_reason="length",
                 generated_tokens=6,
-                tokens=[
-                    Token(id=0, text="You", logprob=0.0, special=False) for i in range(0, 6)
-                ]
-            )
+                tokens=[Token(id=0, text="You", logprob=0.0, special=False) for i in range(0, 6)],
+            ),
         )
 
         return response
@@ -36,26 +34,23 @@ def generate_create_stream(model: str) -> Generator[TextGenerationStreamResponse
 
         for i in range(0, len(full_text)):
             response = TextGenerationStreamResponse(
-                token = Token(id=i, text=full_text[i], logprob=0.0, special=False),
+                token=Token(id=i, text=full_text[i], logprob=0.0, special=False),
             )
             response.generated_text = full_text[i]
-            response.details = StreamDetails(finish_reason='stop_sequence', generated_tokens=1)
+            response.details = StreamDetails(finish_reason="stop_sequence", generated_tokens=1)
 
             yield response
 
-    def text_generation(self: InferenceClient, prompt: str, *,
-        stream: Literal[False] = ...,
-        model: Optional[str] = None,
-        **kwargs: Any
+    def text_generation(
+        self: InferenceClient, prompt: str, *, stream: Literal[False] = ..., model: Optional[str] = None, **kwargs: Any
     ) -> Union[TextGenerationResponse, Generator[TextGenerationStreamResponse, None, None]]:
         # check if key is valid
-        if not re.match(r'Bearer\shf\-[a-zA-Z0-9]{16,}', self.headers['authorization']):
-            raise BadRequestError('Invalid API key')
-        
+        if not re.match(r"Bearer\shf\-[a-zA-Z0-9]{16,}", self.headers["authorization"]):
+            raise BadRequestError("Invalid API key")
+
         if model is None:
-            raise BadRequestError('Invalid model')
-        
+            raise BadRequestError("Invalid model")
+
         if stream:
             return MockHuggingfaceChatClass.generate_create_stream(model)
         return MockHuggingfaceChatClass.generate_create_sync(model)
-

api/tests/integration_tests/model_runtime/__mock/huggingface_tei.py

@@ -5,10 +5,10 @@ class MockTEIClass:
     @staticmethod
     def get_tei_extra_parameter(server_url: str, model_name: str) -> TeiModelExtraParameter:
         # During mock, we don't have a real server to query, so we just return a dummy value
-        if 'rerank' in model_name:
-            model_type = 'reranker'
+        if "rerank" in model_name:
+            model_type = "reranker"
         else:
-            model_type = 'embedding'
+            model_type = "embedding"
 
         return TeiModelExtraParameter(model_type=model_type, max_input_length=512, max_client_batch_size=1)
 
@@ -17,16 +17,16 @@ def invoke_tokenize(server_url: str, texts: list[str]) -> list[list[dict]]:
         # Use space as token separator, and split the text into tokens
         tokenized_texts = []
         for text in texts:
-            tokens = text.split(' ')
+            tokens = text.split(" ")
             current_index = 0
             tokenized_text = []
             for idx, token in enumerate(tokens):
                 s_token = {
-                    'id': idx,
-                    'text': token,
-                    'special': False,
-                    'start': current_index,
-                    'stop': current_index + len(token),
+                    "id": idx,
+                    "text": token,
+                    "special": False,
+                    "start": current_index,
+                    "stop": current_index + len(token),
                 }
                 current_index += len(token) + 1
                 tokenized_text.append(s_token)
@@ -55,18 +55,18 @@ def invoke_embeddings(server_url: str, texts: list[str]) -> dict:
             embedding = [0.1] * 768
             embeddings.append(
                 {
-                    'object': 'embedding',
-                    'embedding': embedding,
-                    'index': idx,
+                    "object": "embedding",
+                    "embedding": embedding,
+                    "index": idx,
                 }
             )
         return {
-            'object': 'list',
-            'data': embeddings,
-            'model': 'MODEL_NAME',
-            'usage': {
-                'prompt_tokens': sum(len(text.split(' ')) for text in texts),
-                'total_tokens': sum(len(text.split(' ')) for text in texts),
+            "object": "list",
+            "data": embeddings,
+            "model": "MODEL_NAME",
+            "usage": {
+                "prompt_tokens": sum(len(text.split(" ")) for text in texts),
+                "total_tokens": sum(len(text.split(" ")) for text in texts),
             },
         }
 
@@ -83,9 +83,9 @@ def invoke_rerank(server_url: str, query: str, texts: list[str]) -> list[dict]:
         for idx, text in enumerate(texts):
             reranked_docs.append(
                 {
-                    'index': idx,
-                    'text': text,
-                    'score': 0.9,
+                    "index": idx,
+                    "text": text,
+                    "score": 0.9,
                 }
             )
             # For mock, only return the first document