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chore: cleanup ruff flake8-simplify linter rules (#8286)

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Co-authored-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
Bowen Liang 2024-09-12 12:55:45 +08:00 committed by GitHub
parent 0bb7569d46
commit 0f14873255
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GPG Key ID: B5690EEEBB952194
34 changed files with 108 additions and 136 deletions
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2
api/core/app/task_pipeline/based_generate_task_pipeline.py
View File

@ -65,7 +65,7 @@ class BasedGenerateTaskPipeline:
if isinstance(e, InvokeAuthorizationError):
err = InvokeAuthorizationError("Incorrect API key provided")
elif isinstance(e, InvokeError) or isinstance(e, ValueError):
elif isinstance(e, InvokeError | ValueError):
err = e
else:
err = Exception(e.description if getattr(e, "description", None) is not None else str(e))

4
api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo.py
View File

@ -45,7 +45,7 @@ class BaichuanModel:
parameters: dict[str, Any],
tools: Optional[list[PromptMessageTool]] = None,
) -> dict[str, Any]:
if model in self._model_mapping.keys():
if model in self._model_mapping:
# the LargeLanguageModel._code_block_mode_wrapper() method will remove the response_format of parameters.
# we need to rename it to res_format to get its value
if parameters.get("res_format") == "json_object":
@ -94,7 +94,7 @@ class BaichuanModel:
timeout: int,
tools: Optional[list[PromptMessageTool]] = None,
) -> Union[Iterator, dict]:
if model in self._model_mapping.keys():
if model in self._model_mapping:
api_base = "https://api.baichuan-ai.com/v1/chat/completions"
else:
raise BadRequestError(f"Unknown model: {model}")

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

@ -337,9 +337,7 @@ class GoogleLargeLanguageModel(LargeLanguageModel):
message_text = f"{human_prompt} {content}"
elif isinstance(message, AssistantPromptMessage):
message_text = f"{ai_prompt} {content}"
elif isinstance(message, SystemPromptMessage):
message_text = f"{human_prompt} {content}"
elif isinstance(message, ToolPromptMessage):
elif isinstance(message, SystemPromptMessage | ToolPromptMessage):
message_text = f"{human_prompt} {content}"
else:
raise ValueError(f"Got unknown type {message}")

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

@ -442,9 +442,7 @@ class OCILargeLanguageModel(LargeLanguageModel):
message_text = f"{human_prompt} {content}"
elif isinstance(message, AssistantPromptMessage):
message_text = f"{ai_prompt} {content}"
elif isinstance(message, SystemPromptMessage):
message_text = f"{human_prompt} {content}"
elif isinstance(message, ToolPromptMessage):
elif isinstance(message, SystemPromptMessage | ToolPromptMessage):
message_text = f"{human_prompt} {content}"
else:
raise ValueError(f"Got unknown type {message}")

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

@ -350,9 +350,7 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
break
elif isinstance(message, AssistantPromptMessage):
message_text = f"{ai_prompt} {content}"
elif isinstance(message, SystemPromptMessage):
message_text = content
elif isinstance(message, ToolPromptMessage):
elif isinstance(message, SystemPromptMessage | ToolPromptMessage):
message_text = content
else:
raise ValueError(f"Got unknown type {message}")

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

@ -633,9 +633,7 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
message_text = f"{human_prompt} {content}"
elif isinstance(message, AssistantPromptMessage):
message_text = f"{ai_prompt} {content}"
elif isinstance(message, SystemPromptMessage):
message_text = f"{human_prompt} {content}"
elif isinstance(message, ToolPromptMessage):
elif isinstance(message, SystemPromptMessage | ToolPromptMessage):
message_text = f"{human_prompt} {content}"
else:
raise ValueError(f"Got unknown type {message}")

6
api/core/model_runtime/model_providers/xinference/llm/llm.py
View File

@ -272,11 +272,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
"""
text = ""
for item in message:
if isinstance(item, UserPromptMessage):
text += item.content
elif isinstance(item, SystemPromptMessage):
text += item.content
elif isinstance(item, AssistantPromptMessage):
if isinstance(item, UserPromptMessage | SystemPromptMessage | AssistantPromptMessage):
text += item.content
else:
raise NotImplementedError(f"PromptMessage type {type(item)} is not supported")

11
api/core/model_runtime/model_providers/zhipuai/llm/llm.py
View File

@ -209,9 +209,10 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
):
new_prompt_messages[-1].content += "\n\n" + copy_prompt_message.content
else:
if copy_prompt_message.role == PromptMessageRole.USER:
new_prompt_messages.append(copy_prompt_message)
elif copy_prompt_message.role == PromptMessageRole.TOOL:
if (
copy_prompt_message.role == PromptMessageRole.USER
or copy_prompt_message.role == PromptMessageRole.TOOL
):
new_prompt_messages.append(copy_prompt_message)
elif copy_prompt_message.role == PromptMessageRole.SYSTEM:
new_prompt_message = SystemPromptMessage(content=copy_prompt_message.content)
@ -461,9 +462,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
message_text = f"{human_prompt} {content}"
elif isinstance(message, AssistantPromptMessage):
message_text = f"{ai_prompt} {content}"
elif isinstance(message, SystemPromptMessage):
message_text = content
elif isinstance(message, ToolPromptMessage):
elif isinstance(message, SystemPromptMessage | ToolPromptMessage):
message_text = content
else:
raise ValueError(f"Got unknown type {message}")

13
api/core/moderation/keywords/keywords.py
View File

@ -56,14 +56,7 @@ class KeywordsModeration(Moderation):
)
def _is_violated(self, inputs: dict, keywords_list: list) -> bool:
for value in inputs.values():
if self._check_keywords_in_value(keywords_list, value):
return True
return any(self._check_keywords_in_value(keywords_list, value) for value in inputs.values())
return False
def _check_keywords_in_value(self, keywords_list, value):
for keyword in keywords_list:
if keyword.lower() in value.lower():
return True
return False
def _check_keywords_in_value(self, keywords_list, value) -> bool:
return any(keyword.lower() in value.lower() for keyword in keywords_list)

2
api/core/ops/ops_trace_manager.py
View File

@ -223,7 +223,7 @@ class OpsTraceManager:
:return:
"""
# auth check
if tracing_provider not in provider_config_map.keys() and tracing_provider is not None:
if tracing_provider not in provider_config_map and tracing_provider is not None:
raise ValueError(f"Invalid tracing provider: {tracing_provider}")
app_config: App = db.session.query(App).filter(App.id == app_id).first()

6
api/core/rag/datasource/vdb/relyt/relyt_vector.py
View File

@ -127,8 +127,7 @@ class RelytVector(BaseVector):
)
chunks_table_data = []
with self.client.connect() as conn:
with conn.begin():
with self.client.connect() as conn, conn.begin():
for document, metadata, chunk_id, embedding in zip(texts, metadatas, ids, embeddings):
chunks_table_data.append(
{
@ -186,8 +185,7 @@ class RelytVector(BaseVector):
)
try:
with self.client.connect() as conn:
with conn.begin():
with self.client.connect() as conn, conn.begin():
delete_condition = chunks_table.c.id.in_(ids)
conn.execute(chunks_table.delete().where(delete_condition))
return True

5
api/core/rag/datasource/vdb/tencent/tencent_vector.py
View File

@ -63,10 +63,7 @@ class TencentVector(BaseVector):
def _has_collection(self) -> bool:
collections = self._db.list_collections()
for collection in collections:
if collection.collection_name == self._collection_name:
return True
return False
return any(collection.collection_name == self._collection_name for collection in collections)
def _create_collection(self, dimension: int) -> None:
lock_name = "vector_indexing_lock_{}".format(self._collection_name)

6
api/core/rag/datasource/vdb/tidb_vector/tidb_vector.py
View File

@ -124,8 +124,7 @@ class TiDBVector(BaseVector):
texts = [d.page_content for d in documents]
chunks_table_data = []
with self._engine.connect() as conn:
with conn.begin():
with self._engine.connect() as conn, conn.begin():
for id, text, meta, embedding in zip(ids, texts, metas, embeddings):
chunks_table_data.append({"id": id, "vector": embedding, "text": text, "meta": meta})
@ -160,8 +159,7 @@ class TiDBVector(BaseVector):
raise ValueError("No ids provided to delete.")
table = self._table(self._dimension)
try:
with self._engine.connect() as conn:
with conn.begin():
with self._engine.connect() as conn, conn.begin():
delete_condition = table.c.id.in_(ids)
conn.execute(table.delete().where(delete_condition))
return True

3
api/core/rag/extractor/word_extractor.py
View File

@ -48,7 +48,8 @@ class WordExtractor(BaseExtractor):
raise ValueError(f"Check the url of your file; returned status code {r.status_code}")
self.web_path = self.file_path
self.temp_file = tempfile.NamedTemporaryFile()
# TODO: use a better way to handle the file
self.temp_file = tempfile.NamedTemporaryFile() # noqa: SIM115
self.temp_file.write(r.content)
self.file_path = self.temp_file.name
elif not os.path.isfile(self.file_path):

4
api/core/rag/rerank/weight_rerank.py
View File

@ -120,8 +120,8 @@ class WeightRerankRunner:
intersection = set(vec1.keys()) & set(vec2.keys())
numerator = sum(vec1[x] * vec2[x] for x in intersection)
sum1 = sum(vec1[x] ** 2 for x in vec1.keys())
sum2 = sum(vec2[x] ** 2 for x in vec2.keys())
sum1 = sum(vec1[x] ** 2 for x in vec1)
sum2 = sum(vec2[x] ** 2 for x in vec2)
denominator = math.sqrt(sum1) * math.sqrt(sum2)
if not denominator:

4
api/core/rag/retrieval/dataset_retrieval.py
View File

@ -581,8 +581,8 @@ class DatasetRetrieval:
intersection = set(vec1.keys()) & set(vec2.keys())
numerator = sum(vec1[x] * vec2[x] for x in intersection)
sum1 = sum(vec1[x] ** 2 for x in vec1.keys())
sum2 = sum(vec2[x] ** 2 for x in vec2.keys())
sum1 = sum(vec1[x] ** 2 for x in vec1)
sum2 = sum(vec2[x] ** 2 for x in vec2)
denominator = math.sqrt(sum1) * math.sqrt(sum2)
if not denominator:

4
api/core/tools/provider/builtin/hap/tools/list_worksheet_records.py
View File

@ -201,9 +201,7 @@ class ListWorksheetRecordsTool(BuiltinTool):
elif value.startswith('[{"organizeId"'):
value = json.loads(value)
value = "、".join([item["organizeName"] for item in value])
elif value.startswith('[{"file_id"'):
value = ""
elif value == "[]":
elif value.startswith('[{"file_id"') or value == "[]":
value = ""
elif hasattr(value, "accountId"):
value = value["fullname"]

2
api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.py
View File

@ -35,7 +35,7 @@ class NovitaAiModelQueryTool(BuiltinTool):
models_data=[],
headers=headers,
params=params,
recursive=False if result_type == "first sd_name" or result_type == "first name sd_name pair" else True,
recursive=not (result_type == "first sd_name" or result_type == "first name sd_name pair"),
)
result_str = ""

2
api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.py
View File

@ -39,7 +39,7 @@ class QRCodeGeneratorTool(BuiltinTool):
# get error_correction
error_correction = tool_parameters.get("error_correction", "")
if error_correction not in self.error_correction_levels.keys():
if error_correction not in self.error_correction_levels:
return self.create_text_message("Invalid parameter error_correction")
try:

20
api/core/tools/provider/builtin/searchapi/tools/google.py
View File

@ -44,36 +44,36 @@ class SearchAPI:
@staticmethod
def _process_response(res: dict, type: str) -> str:
"""Process response from SearchAPI."""
if "error" in res.keys():
if "error" in res:
raise ValueError(f"Got error from SearchApi: {res['error']}")
toret = ""
if type == "text":
if "answer_box" in res.keys() and "answer" in res["answer_box"].keys():
if "answer_box" in res and "answer" in res["answer_box"]:
toret += res["answer_box"]["answer"] + "\n"
if "answer_box" in res.keys() and "snippet" in res["answer_box"].keys():
if "answer_box" in res and "snippet" in res["answer_box"]:
toret += res["answer_box"]["snippet"] + "\n"
if "knowledge_graph" in res.keys() and "description" in res["knowledge_graph"].keys():
if "knowledge_graph" in res and "description" in res["knowledge_graph"]:
toret += res["knowledge_graph"]["description"] + "\n"
if "organic_results" in res.keys() and "snippet" in res["organic_results"][0].keys():
if "organic_results" in res and "snippet" in res["organic_results"][0]:
for item in res["organic_results"]:
toret += "content: " + item["snippet"] + "\n" + "link: " + item["link"] + "\n"
if toret == "":
toret = "No good search result found"
elif type == "link":
if "answer_box" in res.keys() and "organic_result" in res["answer_box"].keys():
if "title" in res["answer_box"]["organic_result"].keys():
if "answer_box" in res and "organic_result" in res["answer_box"]:
if "title" in res["answer_box"]["organic_result"]:
toret = f"[{res['answer_box']['organic_result']['title']}]({res['answer_box']['organic_result']['link']})\n"
elif "organic_results" in res.keys() and "link" in res["organic_results"][0].keys():
elif "organic_results" in res and "link" in res["organic_results"][0]:
toret = ""
for item in res["organic_results"]:
toret += f"[{item['title']}]({item['link']})\n"
elif "related_questions" in res.keys() and "link" in res["related_questions"][0].keys():
elif "related_questions" in res and "link" in res["related_questions"][0]:
toret = ""
for item in res["related_questions"]:
toret += f"[{item['title']}]({item['link']})\n"
elif "related_searches" in res.keys() and "link" in res["related_searches"][0].keys():
elif "related_searches" in res and "link" in res["related_searches"][0]:
toret = ""
for item in res["related_searches"]:
toret += f"[{item['title']}]({item['link']})\n"

6
api/core/tools/provider/builtin/searchapi/tools/google_jobs.py
View File

@ -44,12 +44,12 @@ class SearchAPI:
@staticmethod
def _process_response(res: dict, type: str) -> str:
"""Process response from SearchAPI."""
if "error" in res.keys():
if "error" in res:
raise ValueError(f"Got error from SearchApi: {res['error']}")
toret = ""
if type == "text":
if "jobs" in res.keys() and "title" in res["jobs"][0].keys():
if "jobs" in res and "title" in res["jobs"][0]:
for item in res["jobs"]:
toret += (
"title: "
@ -65,7 +65,7 @@ class SearchAPI:
toret = "No good search result found"
elif type == "link":
if "jobs" in res.keys() and "apply_link" in res["jobs"][0].keys():
if "jobs" in res and "apply_link" in res["jobs"][0]:
for item in res["jobs"]:
toret += f"[{item['title']} - {item['company_name']}]({item['apply_link']})\n"
else:

10
api/core/tools/provider/builtin/searchapi/tools/google_news.py
View File

@ -44,25 +44,25 @@ class SearchAPI:
@staticmethod
def _process_response(res: dict, type: str) -> str:
"""Process response from SearchAPI."""
if "error" in res.keys():
if "error" in res:
raise ValueError(f"Got error from SearchApi: {res['error']}")
toret = ""
if type == "text":
if "organic_results" in res.keys() and "snippet" in res["organic_results"][0].keys():
if "organic_results" in res and "snippet" in res["organic_results"][0]:
for item in res["organic_results"]:
toret += "content: " + item["snippet"] + "\n" + "link: " + item["link"] + "\n"
if "top_stories" in res.keys() and "title" in res["top_stories"][0].keys():
if "top_stories" in res and "title" in res["top_stories"][0]:
for item in res["top_stories"]:
toret += "title: " + item["title"] + "\n" + "link: " + item["link"] + "\n"
if toret == "":
toret = "No good search result found"
elif type == "link":
if "organic_results" in res.keys() and "title" in res["organic_results"][0].keys():
if "organic_results" in res and "title" in res["organic_results"][0]:
for item in res["organic_results"]:
toret += f"[{item['title']}]({item['link']})\n"
elif "top_stories" in res.keys() and "title" in res["top_stories"][0].keys():
elif "top_stories" in res and "title" in res["top_stories"][0]:
for item in res["top_stories"]:
toret += f"[{item['title']}]({item['link']})\n"
else:

4
api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.py
View File

@ -44,11 +44,11 @@ class SearchAPI:
@staticmethod
def _process_response(res: dict) -> str:
"""Process response from SearchAPI."""
if "error" in res.keys():
if "error" in res:
raise ValueError(f"Got error from SearchApi: {res['error']}")
toret = ""
if "transcripts" in res.keys() and "text" in res["transcripts"][0].keys():
if "transcripts" in res and "text" in res["transcripts"][0]:
for item in res["transcripts"]:
toret += item["text"] + " "
if toret == "":

2
api/core/tools/provider/builtin/stability/tools/text2image.py
View File

@ -35,7 +35,7 @@ class StableDiffusionTool(BuiltinTool, BaseStabilityAuthorization):
if model in ["sd3", "sd3-turbo"]:
payload["model"] = tool_parameters.get("model")
if not model == "sd3-turbo":
if model != "sd3-turbo":
payload["negative_prompt"] = tool_parameters.get("negative_prompt", "")
response = post(

3
api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.py
View File

@ -206,8 +206,7 @@ class StableDiffusionTool(BuiltinTool):
# Convert image to RGB and save as PNG
try:
with Image.open(io.BytesIO(image_binary)) as image:
with io.BytesIO() as buffer:
with Image.open(io.BytesIO(image_binary)) as image, io.BytesIO() as buffer:
image.convert("RGB").save(buffer, format="PNG")
image_binary = buffer.getvalue()
except Exception as e:

2
api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.py
View File

@ -27,7 +27,7 @@ class WikipediaAPIWrapper:
self.doc_content_chars_max = doc_content_chars_max
def run(self, query: str, lang: str = "") -> str:
if lang in wikipedia.languages().keys():
if lang in wikipedia.languages():
self.lang = lang
wikipedia.set_lang(self.lang)

4
api/core/tools/utils/message_transformer.py
View File

@ -19,9 +19,7 @@ class ToolFileMessageTransformer:
result = []
for message in messages:
if message.type == ToolInvokeMessage.MessageType.TEXT:
result.append(message)
elif message.type == ToolInvokeMessage.MessageType.LINK:
if message.type == ToolInvokeMessage.MessageType.TEXT or message.type == ToolInvokeMessage.MessageType.LINK:
result.append(message)
elif message.type == ToolInvokeMessage.MessageType.IMAGE:
# try to download image

4
api/core/workflow/graph_engine/entities/graph.py
View File

@ -224,9 +224,7 @@ class Graph(BaseModel):
"""
leaf_node_ids = []
for node_id in self.node_ids:
if node_id not in self.edge_mapping:
leaf_node_ids.append(node_id)
elif (
if node_id not in self.edge_mapping or (
len(self.edge_mapping[node_id]) == 1
and self.edge_mapping[node_id][0].target_node_id == self.root_node_id
):

2
api/core/workflow/nodes/answer/answer_stream_generate_router.py
View File

@ -24,7 +24,7 @@ class AnswerStreamGeneratorRouter:
# parse stream output node value selectors of answer nodes
answer_generate_route: dict[str, list[GenerateRouteChunk]] = {}
for answer_node_id, node_config in node_id_config_mapping.items():
if not node_config.get("data", {}).get("type") == NodeType.ANSWER.value:
if node_config.get("data", {}).get("type") != NodeType.ANSWER.value:
continue
# get generate route for stream output

2
api/core/workflow/nodes/end/end_stream_generate_router.py
View File

@ -17,7 +17,7 @@ class EndStreamGeneratorRouter:
# parse stream output node value selector of end nodes
end_stream_variable_selectors_mapping: dict[str, list[list[str]]] = {}
for end_node_id, node_config in node_id_config_mapping.items():
if not node_config.get("data", {}).get("type") == NodeType.END.value:
if node_config.get("data", {}).get("type") != NodeType.END.value:
continue
# skip end node in parallel

2
api/core/workflow/nodes/tool/entities.py
View File

@ -20,7 +20,7 @@ class ToolEntity(BaseModel):
if not isinstance(value, dict):
raise ValueError("tool_configurations must be a dictionary")
for key in values.data.get("tool_configurations", {}).keys():
for key in values.data.get("tool_configurations", {}):
value = values.data.get("tool_configurations", {}).get(key)
if not isinstance(value, str | int | float | bool):
raise ValueError(f"{key} must be a string")

15
api/pyproject.toml
View File

@ -17,14 +17,12 @@ select = [
"F", # pyflakes rules
"I", # isort rules
"N", # pep8-naming
"UP", # pyupgrade rules
"RUF019", # unnecessary-key-check
"RUF100", # unused-noqa
"RUF101", # redirected-noqa
"S506", # unsafe-yaml-load
"SIM116", # if-else-block-instead-of-dict-lookup
"SIM401", # if-else-block-instead-of-dict-get
"SIM910", # dict-get-with-none-default
"SIM", # flake8-simplify rules
"UP", # pyupgrade rules
"W191", # tab-indentation
"W605", # invalid-escape-sequence
]
@ -50,6 +48,15 @@ ignore = [
"B905", # zip-without-explicit-strict
"N806", # non-lowercase-variable-in-function
"N815", # mixed-case-variable-in-class-scope
"SIM102", # collapsible-if
"SIM103", # needless-bool
"SIM105", # suppressible-exception
"SIM107", # return-in-try-except-finally
"SIM108", # if-else-block-instead-of-if-exp
"SIM113", # eumerate-for-loop
"SIM117", # multiple-with-statements
"SIM210", # if-expr-with-true-false
"SIM300", # yoda-conditions
]
[tool.ruff.lint.per-file-ignores]

4
api/services/file_service.py
View File

@ -56,9 +56,7 @@ class FileService:
if etl_type == "Unstructured"
else ALLOWED_EXTENSIONS + IMAGE_EXTENSIONS
)
if extension.lower() not in allowed_extensions:
raise UnsupportedFileTypeError()
elif only_image and extension.lower() not in IMAGE_EXTENSIONS:
if extension.lower() not in allowed_extensions or only_image and extension.lower() not in IMAGE_EXTENSIONS:
raise UnsupportedFileTypeError()
# read file content

4
api/services/ops_service.py
View File

@ -54,7 +54,7 @@ class OpsService:
:param tracing_config: tracing config
:return:
"""
if tracing_provider not in provider_config_map.keys() and tracing_provider:
if tracing_provider not in provider_config_map and tracing_provider:
return {"error": f"Invalid tracing provider: {tracing_provider}"}
config_class, other_keys = (
@ -113,7 +113,7 @@ class OpsService:
:param tracing_config: tracing config
:return:
"""
if tracing_provider not in provider_config_map.keys():
if tracing_provider not in provider_config_map:
raise ValueError(f"Invalid tracing provider: {tracing_provider}")
# check if trace config already exists