chore: skip unnecessary key checks prior to accessing a dictionary (#4497)

This commit is contained in:
Bowen Liang
2024-05-19 18:30:45 +08:00
committed by GitHub
parent aa13d14019
commit 04ad46dd31
30 changed files with 45 additions and 44 deletions

View File

@@ -11,7 +11,7 @@ class SensitiveWordAvoidanceConfigManager:
if not sensitive_word_avoidance_dict:
return None
if 'enabled' in sensitive_word_avoidance_dict and sensitive_word_avoidance_dict['enabled']:
if sensitive_word_avoidance_dict.get('enabled'):
return SensitiveWordAvoidanceEntity(
type=sensitive_word_avoidance_dict.get('type'),
config=sensitive_word_avoidance_dict.get('config'),

View File

@@ -14,7 +14,7 @@ class FileUploadConfigManager:
"""
file_upload_dict = config.get('file_upload')
if file_upload_dict:
if 'image' in file_upload_dict and file_upload_dict['image']:
if file_upload_dict.get('image'):
if 'enabled' in file_upload_dict['image'] and file_upload_dict['image']['enabled']:
image_config = {
'number_limits': file_upload_dict['image']['number_limits'],

View File

@@ -9,7 +9,7 @@ class MoreLikeThisConfigManager:
more_like_this = False
more_like_this_dict = config.get('more_like_this')
if more_like_this_dict:
if 'enabled' in more_like_this_dict and more_like_this_dict['enabled']:
if more_like_this_dict.get('enabled'):
more_like_this = True
return more_like_this

View File

@@ -4,7 +4,7 @@ class RetrievalResourceConfigManager:
show_retrieve_source = False
retriever_resource_dict = config.get('retriever_resource')
if retriever_resource_dict:
if 'enabled' in retriever_resource_dict and retriever_resource_dict['enabled']:
if retriever_resource_dict.get('enabled'):
show_retrieve_source = True
return show_retrieve_source

View File

@@ -9,7 +9,7 @@ class SpeechToTextConfigManager:
speech_to_text = False
speech_to_text_dict = config.get('speech_to_text')
if speech_to_text_dict:
if 'enabled' in speech_to_text_dict and speech_to_text_dict['enabled']:
if speech_to_text_dict.get('enabled'):
speech_to_text = True
return speech_to_text

View File

@@ -9,7 +9,7 @@ class SuggestedQuestionsAfterAnswerConfigManager:
suggested_questions_after_answer = False
suggested_questions_after_answer_dict = config.get('suggested_questions_after_answer')
if suggested_questions_after_answer_dict:
if 'enabled' in suggested_questions_after_answer_dict and suggested_questions_after_answer_dict['enabled']:
if suggested_questions_after_answer_dict.get('enabled'):
suggested_questions_after_answer = True
return suggested_questions_after_answer

View File

@@ -12,7 +12,7 @@ class TextToSpeechConfigManager:
text_to_speech = False
text_to_speech_dict = config.get('text_to_speech')
if text_to_speech_dict:
if 'enabled' in text_to_speech_dict and text_to_speech_dict['enabled']:
if text_to_speech_dict.get('enabled'):
text_to_speech = TextToSpeechEntity(
enabled=text_to_speech_dict.get('enabled'),
voice=text_to_speech_dict.get('voice'),

View File

@@ -66,7 +66,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
conversation = self._get_conversation_by_user(app_model, args.get('conversation_id'), user)
# parse files
files = args['files'] if 'files' in args and args['files'] else []
files = args['files'] if args.get('files') else []
message_file_parser = MessageFileParser(tenant_id=app_model.tenant_id, app_id=app_model.id)
file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False)
if file_extra_config:

View File

@@ -83,7 +83,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
)
# parse files
files = args['files'] if 'files' in args and args['files'] else []
files = args['files'] if args.get('files') else []
message_file_parser = MessageFileParser(tenant_id=app_model.tenant_id, app_id=app_model.id)
file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict())
if file_extra_config:

View File

@@ -80,7 +80,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
)
# parse files
files = args['files'] if 'files' in args and args['files'] else []
files = args['files'] if args.get('files') else []
message_file_parser = MessageFileParser(tenant_id=app_model.tenant_id, app_id=app_model.id)
file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict())
if file_extra_config:

View File

@@ -75,7 +75,7 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
)
# parse files
files = args['files'] if 'files' in args and args['files'] else []
files = args['files'] if args.get('files') else []
message_file_parser = MessageFileParser(tenant_id=app_model.tenant_id, app_id=app_model.id)
file_extra_config = FileUploadConfigManager.convert(override_model_config_dict or app_model_config.to_dict())
if file_extra_config:

View File

@@ -49,7 +49,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
inputs = args['inputs']
# parse files
files = args['files'] if 'files' in args and args['files'] else []
files = args['files'] if args.get('files') else []
message_file_parser = MessageFileParser(tenant_id=app_model.tenant_id, app_id=app_model.id)
file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False)
if file_extra_config:

View File

@@ -121,13 +121,13 @@ class DatasetDocumentStore:
enabled=False,
created_by=self._user_id,
)
if 'answer' in doc.metadata and doc.metadata['answer']:
if doc.metadata.get('answer'):
segment_document.answer = doc.metadata.pop('answer', '')
db.session.add(segment_document)
else:
segment_document.content = doc.page_content
if 'answer' in doc.metadata and doc.metadata['answer']:
if doc.metadata.get('answer'):
segment_document.answer = doc.metadata.pop('answer', '')
segment_document.index_node_hash = doc.metadata['doc_hash']
segment_document.word_count = len(doc.page_content)

View File

@@ -418,7 +418,7 @@ class IndexingRunner:
if separator:
separator = separator.replace('\\n', '\n')
if 'chunk_overlap' in segmentation and segmentation['chunk_overlap']:
if segmentation.get('chunk_overlap'):
chunk_overlap = segmentation['chunk_overlap']
else:
chunk_overlap = 0

View File

@@ -146,7 +146,7 @@ class AnthropicLargeLanguageModel(LargeLanguageModel):
"""
Code block mode wrapper for invoking large language model
"""
if 'response_format' in model_parameters and model_parameters['response_format']:
if model_parameters.get('response_format'):
stop = stop or []
# chat model
self._transform_chat_json_prompts(
@@ -408,7 +408,7 @@ class AnthropicLargeLanguageModel(LargeLanguageModel):
"max_retries": 1,
}
if 'anthropic_api_url' in credentials and credentials['anthropic_api_url']:
if credentials.get('anthropic_api_url'):
credentials['anthropic_api_url'] = credentials['anthropic_api_url'].rstrip('/')
credentials_kwargs['base_url'] = credentials['anthropic_api_url']

View File

@@ -89,7 +89,7 @@ class BaichuanModel:
# save stop reason temporarily
stop_reason = ''
for choice in choices:
if 'finish_reason' in choice and choice['finish_reason']:
if choice.get('finish_reason'):
stop_reason = choice['finish_reason']
if len(choice['delta']['content']) == 0:

View File

@@ -43,7 +43,7 @@ class MinimaxChatCompletionPro:
if 'top_p' in model_parameters and type(model_parameters['top_p']) == float:
extra_kwargs['top_p'] = model_parameters['top_p']
if 'plugin_web_search' in model_parameters and model_parameters['plugin_web_search']:
if model_parameters.get('plugin_web_search'):
extra_kwargs['plugins'] = [
'plugin_web_search'
]
@@ -158,7 +158,7 @@ class MinimaxChatCompletionPro:
self._handle_error(code, msg)
# final chunk
if data['reply'] or 'usage' in data and data['usage']:
if data['reply'] or data.get('usage'):
total_tokens = data['usage']['total_tokens']
minimax_message = MinimaxMessage(
role=MinimaxMessage.Role.ASSISTANT.value,

View File

@@ -25,7 +25,7 @@ class _CommonOpenAI:
"max_retries": 1,
}
if 'openai_api_base' in credentials and credentials['openai_api_base']:
if credentials.get('openai_api_base'):
credentials['openai_api_base'] = credentials['openai_api_base'].rstrip('/')
credentials_kwargs['base_url'] = credentials['openai_api_base'] + '/v1'

View File

@@ -180,7 +180,7 @@ class OpenLLMGenerate:
completion_usage += len(token_ids)
message = OpenLLMGenerateMessage(content=text, role=OpenLLMGenerateMessage.Role.ASSISTANT.value)
if 'finish_reason' in choice and choice['finish_reason']:
if choice.get('finish_reason'):
finish_reason = choice['finish_reason']
prompt_token_ids = data['prompt_token_ids']
message.stop_reason = finish_reason

View File

@@ -124,7 +124,7 @@ class DatasetRetrieval:
document_score_list = {}
for item in all_documents:
if 'score' in item.metadata and item.metadata['score']:
if item.metadata.get('score'):
document_score_list[item.metadata['doc_id']] = item.metadata['score']
document_context_list = []

View File

@@ -70,7 +70,7 @@ class StableDiffusionTool(BuiltinTool):
if not base_url:
return self.create_text_message('Please input base_url')
if 'model' in tool_parameters and tool_parameters['model']:
if tool_parameters.get('model'):
self.runtime.credentials['model'] = tool_parameters['model']
model = self.runtime.credentials.get('model', None)

View File

@@ -48,7 +48,7 @@ class WolframAlphaTool(BuiltinTool):
if 'success' not in response_data['queryresult'] or response_data['queryresult']['success'] != True:
query_result = response_data.get('queryresult', {})
if 'error' in query_result and query_result['error']:
if query_result.get('error'):
if 'msg' in query_result['error']:
if query_result['error']['msg'] == 'Invalid appid':
raise ToolProviderCredentialValidationError('Invalid appid')

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@@ -79,7 +79,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
document_score_list = {}
for item in all_documents:
if 'score' in item.metadata and item.metadata['score']:
if item.metadata.get('score'):
document_score_list[item.metadata['doc_id']] = item.metadata['score']
document_context_list = []

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@@ -87,7 +87,7 @@ class DatasetRetrieverTool(DatasetRetrieverBaseTool):
document_score_list = {}
if dataset.indexing_technique != "economy":
for item in documents:
if 'score' in item.metadata and item.metadata['score']:
if item.metadata.get('score'):
document_score_list[item.metadata['doc_id']] = item.metadata['score']
document_context_list = []
index_node_ids = [document.metadata['doc_id'] for document in documents]

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@@ -132,17 +132,17 @@ def extract_using_readabilipy(html):
}
# Populate article fields from readability fields where present
if input_json:
if "title" in input_json and input_json["title"]:
if input_json.get("title"):
article_json["title"] = input_json["title"]
if "byline" in input_json and input_json["byline"]:
if input_json.get("byline"):
article_json["byline"] = input_json["byline"]
if "date" in input_json and input_json["date"]:
if input_json.get("date"):
article_json["date"] = input_json["date"]
if "content" in input_json and input_json["content"]:
if input_json.get("content"):
article_json["content"] = input_json["content"]
article_json["plain_content"] = plain_content(article_json["content"], False, False)
article_json["plain_text"] = extract_text_blocks_as_plain_text(article_json["plain_content"])
if "textContent" in input_json and input_json["textContent"]:
if input_json.get("textContent"):
article_json["plain_text"] = input_json["textContent"]
article_json["plain_text"] = re.sub(r'\n\s*\n', '\n', article_json["plain_text"])

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@@ -143,7 +143,7 @@ class KnowledgeRetrievalNode(BaseNode):
if all_documents:
document_score_list = {}
for item in all_documents:
if 'score' in item.metadata and item.metadata['score']:
if item.metadata.get('score'):
document_score_list[item.metadata['doc_id']] = item.metadata['score']
index_node_ids = [document.metadata['doc_id'] for document in all_documents]