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chore(lint): fix quotes for f-string formatting by bumping ruff to 0.9.x (#12702)

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This commit is contained in:
Bowen Liang
2025-01-21 10:12:29 +08:00
committed by GitHub
parent 925d69a2ee
commit 166221d784
46 changed files with 120 additions and 131 deletions
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2
api/core/model_runtime/model_providers/azure_openai/llm/llm.py
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@@ -108,7 +108,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
if not ai_model_entity:
raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
try:
client = AzureOpenAI(**self._to_credential_kwargs(credentials))

2
api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py
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@@ -130,7 +130,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
raise CredentialsValidateFailedError("Base Model Name is required")
if not self._get_ai_model_entity(credentials["base_model_name"], model):
raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
try:
credentials_kwargs = self._to_credential_kwargs(credentials)

4
api/core/model_runtime/model_providers/huggingface_hub/text_embedding/text_embedding.py
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@@ -162,9 +162,9 @@ class HuggingfaceHubTextEmbeddingModel(_CommonHuggingfaceHub, TextEmbeddingModel
@staticmethod
def _check_endpoint_url_model_repository_name(credentials: dict, model_name: str):
try:
url = f'{HUGGINGFACE_ENDPOINT_API}{credentials["huggingface_namespace"]}'
url = f"{HUGGINGFACE_ENDPOINT_API}{credentials['huggingface_namespace']}"
headers = {
"Authorization": f'Bearer {credentials["huggingfacehub_api_token"]}',
"Authorization": f"Bearer {credentials['huggingfacehub_api_token']}",
"Content-Type": "application/json",
}

3
api/core/model_runtime/model_providers/tongyi/llm/llm.py
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@@ -257,8 +257,7 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
for index, response in enumerate(responses):
if response.status_code not in {200, HTTPStatus.OK}:
raise ServiceUnavailableError(
f"Failed to invoke model {model}, status code: {response.status_code}, "
f"message: {response.message}"
f"Failed to invoke model {model}, status code: {response.status_code}, message: {response.message}"
)
resp_finish_reason = response.output.choices[0].finish_reason

2
api/core/model_runtime/model_providers/triton_inference_server/llm/llm.py
View File

@@ -146,7 +146,7 @@ class TritonInferenceAILargeLanguageModel(LargeLanguageModel):
elif credentials["completion_type"] == "completion":
completion_type = LLMMode.COMPLETION.value
else:
raise ValueError(f'completion_type {credentials["completion_type"]} is not supported')
raise ValueError(f"completion_type {credentials['completion_type']} is not supported")
entity = AIModelEntity(
model=model,

10
api/core/model_runtime/model_providers/wenxin/_common.py
View File

@@ -41,15 +41,15 @@ class BaiduAccessToken:
resp = response.json()
if "error" in resp:
if resp["error"] == "invalid_client":
raise InvalidAPIKeyError(f'Invalid API key or secret key: {resp["error_description"]}')
raise InvalidAPIKeyError(f"Invalid API key or secret key: {resp['error_description']}")
elif resp["error"] == "unknown_error":
raise InternalServerError(f'Internal server error: {resp["error_description"]}')
raise InternalServerError(f"Internal server error: {resp['error_description']}")
elif resp["error"] == "invalid_request":
raise BadRequestError(f'Bad request: {resp["error_description"]}')
raise BadRequestError(f"Bad request: {resp['error_description']}")
elif resp["error"] == "rate_limit_exceeded":
raise RateLimitReachedError(f'Rate limit reached: {resp["error_description"]}')
raise RateLimitReachedError(f"Rate limit reached: {resp['error_description']}")
else:
raise Exception(f'Unknown error: {resp["error_description"]}')
raise Exception(f"Unknown error: {resp['error_description']}")
return resp["access_token"]

4
api/core/model_runtime/model_providers/xinference/llm/llm.py
View File

@@ -406,7 +406,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
elif credentials["completion_type"] == "completion":
completion_type = LLMMode.COMPLETION.value
else:
raise ValueError(f'completion_type {credentials["completion_type"]} is not supported')
raise ValueError(f"completion_type {credentials['completion_type']} is not supported")
else:
extra_args = XinferenceHelper.get_xinference_extra_parameter(
server_url=credentials["server_url"],
@@ -472,7 +472,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
api_key = credentials.get("api_key") or "abc"
client = OpenAI(
base_url=f'{credentials["server_url"]}/v1',
base_url=f"{credentials['server_url']}/v1",
api_key=api_key,
max_retries=int(credentials.get("max_retries") or DEFAULT_MAX_RETRIES),
timeout=int(credentials.get("invoke_timeout") or DEFAULT_INVOKE_TIMEOUT),