enhancement: introduce Ruff for Python linter for reordering and removing unused imports with automated pre-commit and sytle check (#2366)

api/core/agent/agent/calc_token_mixin.py

@@ -1,11 +1,9 @@
 from typing import List, cast
 
 from core.entities.application_entities import ModelConfigEntity
-from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_runtime.entities.message_entities import PromptMessage
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from langchain.schema import BaseMessage
 
 
 class CalcTokenMixin:

api/core/agent/agent/multi_dataset_router_agent.py

@@ -1,10 +1,5 @@
-from typing import Any, List, Optional, Sequence, Tuple, Union, cast
+from typing import Any, List, Optional, Sequence, Tuple, Union
 
-from core.entities.application_entities import ModelConfigEntity
-from core.entities.message_entities import lc_messages_to_prompt_messages
-from core.model_manager import ModelInstance
-from core.model_runtime.entities.message_entities import PromptMessageTool
-from core.third_party.langchain.llms.fake import FakeLLM
 from langchain.agents import BaseSingleActionAgent, OpenAIFunctionsAgent
 from langchain.agents.openai_functions_agent.base import _format_intermediate_steps, _parse_ai_message
 from langchain.callbacks.base import BaseCallbackManager
@@ -14,6 +9,12 @@ from langchain.schema import AgentAction, AgentFinish, AIMessage, SystemMessage
 from langchain.tools import BaseTool
 from pydantic import root_validator
 
+from core.entities.application_entities import ModelConfigEntity
+from core.entities.message_entities import lc_messages_to_prompt_messages
+from core.model_manager import ModelInstance
+from core.model_runtime.entities.message_entities import PromptMessageTool
+from core.third_party.langchain.llms.fake import FakeLLM
+
 
 class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
     """

api/core/agent/agent/openai_function_call.py

@@ -1,4 +1,23 @@
-from typing import Any, List, Optional, Sequence, Tuple, Union, cast
+from typing import Any, List, Optional, Sequence, Tuple, Union
+
+from langchain.agents import BaseSingleActionAgent, OpenAIFunctionsAgent
+from langchain.agents.openai_functions_agent.base import _format_intermediate_steps, _parse_ai_message
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
+from langchain.chat_models.openai import _convert_message_to_dict, _import_tiktoken
+from langchain.memory.prompt import SUMMARY_PROMPT
+from langchain.prompts.chat import BaseMessagePromptTemplate
+from langchain.schema import (
+    AgentAction,
+    AgentFinish,
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    SystemMessage,
+    get_buffer_string,
+)
+from langchain.tools import BaseTool
+from pydantic import root_validator
 
 from core.agent.agent.agent_llm_callback import AgentLLMCallback
 from core.agent.agent.calc_token_mixin import CalcTokenMixin, ExceededLLMTokensLimitError
@@ -7,19 +26,7 @@ from core.entities.application_entities import ModelConfigEntity
 from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.third_party.langchain.llms.fake import FakeLLM
-from langchain.agents import BaseSingleActionAgent, OpenAIFunctionsAgent
-from langchain.agents.openai_functions_agent.base import _format_intermediate_steps, _parse_ai_message
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import Callbacks
-from langchain.chat_models.openai import _convert_message_to_dict, _import_tiktoken
-from langchain.memory.prompt import SUMMARY_PROMPT
-from langchain.prompts.chat import BaseMessagePromptTemplate
-from langchain.schema import (AgentAction, AgentFinish, AIMessage, BaseMessage, HumanMessage, SystemMessage,
-                              get_buffer_string)
-from langchain.tools import BaseTool
-from pydantic import root_validator
 
 
 class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixin):

api/core/agent/agent/structed_multi_dataset_router_agent.py

@@ -1,8 +1,6 @@
 import re
 from typing import Any, List, Optional, Sequence, Tuple, Union, cast
 
-from core.chain.llm_chain import LLMChain
-from core.entities.application_entities import ModelConfigEntity
 from langchain import BasePromptTemplate, PromptTemplate
 from langchain.agents import Agent, AgentOutputParser, StructuredChatAgent
 from langchain.agents.structured_chat.base import HUMAN_MESSAGE_TEMPLATE
@@ -13,6 +11,9 @@ from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, Sy
 from langchain.schema import AgentAction, AgentFinish, OutputParserException
 from langchain.tools import BaseTool
 
+from core.chain.llm_chain import LLMChain
+from core.entities.application_entities import ModelConfigEntity
+
 FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
 The nouns in the format of "Thought", "Action", "Action Input", "Final Answer" must be expressed in English.
 Valid "action" values: "Final Answer" or {tool_names}

api/core/agent/agent/structured_chat.py

@@ -1,11 +1,6 @@
 import re
 from typing import Any, List, Optional, Sequence, Tuple, Union, cast
 
-from core.agent.agent.agent_llm_callback import AgentLLMCallback
-from core.agent.agent.calc_token_mixin import CalcTokenMixin, ExceededLLMTokensLimitError
-from core.chain.llm_chain import LLMChain
-from core.entities.application_entities import ModelConfigEntity
-from core.entities.message_entities import lc_messages_to_prompt_messages
 from langchain import BasePromptTemplate, PromptTemplate
 from langchain.agents import Agent, AgentOutputParser, StructuredChatAgent
 from langchain.agents.structured_chat.base import HUMAN_MESSAGE_TEMPLATE
@@ -14,10 +9,23 @@ from langchain.callbacks.base import BaseCallbackManager
 from langchain.callbacks.manager import Callbacks
 from langchain.memory.prompt import SUMMARY_PROMPT
 from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, SystemMessagePromptTemplate
-from langchain.schema import (AgentAction, AgentFinish, AIMessage, BaseMessage, HumanMessage, OutputParserException,
-                              get_buffer_string)
+from langchain.schema import (
+    AgentAction,
+    AgentFinish,
+    AIMessage,
+    BaseMessage,
+    HumanMessage,
+    OutputParserException,
+    get_buffer_string,
+)
 from langchain.tools import BaseTool
 
+from core.agent.agent.agent_llm_callback import AgentLLMCallback
+from core.agent.agent.calc_token_mixin import CalcTokenMixin, ExceededLLMTokensLimitError
+from core.chain.llm_chain import LLMChain
+from core.entities.application_entities import ModelConfigEntity
+from core.entities.message_entities import lc_messages_to_prompt_messages
+
 FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
 The nouns in the format of "Thought", "Action", "Action Input", "Final Answer" must be expressed in English.
 Valid "action" values: "Final Answer" or {tool_names}

api/core/agent/agent_executor.py

@@ -2,6 +2,12 @@ import enum
 import logging
 from typing import Optional, Union
 
+from langchain.agents import AgentExecutor as LCAgentExecutor
+from langchain.agents import BaseMultiActionAgent, BaseSingleActionAgent
+from langchain.callbacks.manager import Callbacks
+from langchain.tools import BaseTool
+from pydantic import BaseModel, Extra
+
 from core.agent.agent.agent_llm_callback import AgentLLMCallback
 from core.agent.agent.multi_dataset_router_agent import MultiDatasetRouterAgent
 from core.agent.agent.openai_function_call import AutoSummarizingOpenAIFunctionCallAgent
@@ -15,11 +21,6 @@ from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.errors.invoke import InvokeError
 from core.tools.tool.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool
 from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool
-from langchain.agents import AgentExecutor as LCAgentExecutor
-from langchain.agents import BaseMultiActionAgent, BaseSingleActionAgent
-from langchain.callbacks.manager import Callbacks
-from langchain.tools import BaseTool
-from pydantic import BaseModel, Extra
 
 
 class PlanningStrategy(str, enum.Enum):

api/core/app_runner/app_runner.py

@@ -2,9 +2,14 @@ import time
 from typing import Generator, List, Optional, Tuple, Union, cast
 
 from core.application_queue_manager import ApplicationQueueManager, PublishFrom
-from core.entities.application_entities import (ApplicationGenerateEntity, AppOrchestrationConfigEntity,
-                                                ExternalDataVariableEntity, InvokeFrom, ModelConfigEntity,
-                                                PromptTemplateEntity)
+from core.entities.application_entities import (
+    ApplicationGenerateEntity,
+    AppOrchestrationConfigEntity,
+    ExternalDataVariableEntity,
+    InvokeFrom,
+    ModelConfigEntity,
+    PromptTemplateEntity,
+)
 from core.features.annotation_reply import AnnotationReplyFeature
 from core.features.external_data_fetch import ExternalDataFetchFeature
 from core.features.hosting_moderation import HostingModerationFeature

api/core/app_runner/generate_task_pipeline.py

@@ -3,28 +3,42 @@ import logging
 import time
 from typing import Generator, Optional, Union, cast
 
+from pydantic import BaseModel
+
 from core.app_runner.moderation_handler import ModerationRule, OutputModerationHandler
 from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.entities.application_entities import ApplicationGenerateEntity, InvokeFrom
-from core.entities.queue_entities import (AnnotationReplyEvent, QueueAgentMessageEvent, QueueAgentThoughtEvent,
-                                          QueueErrorEvent, QueueMessageEndEvent, QueueMessageEvent,
-                                          QueueMessageFileEvent, QueueMessageReplaceEvent, QueuePingEvent,
-                                          QueueRetrieverResourcesEvent, QueueStopEvent)
+from core.entities.queue_entities import (
+    AnnotationReplyEvent,
+    QueueAgentMessageEvent,
+    QueueAgentThoughtEvent,
+    QueueErrorEvent,
+    QueueMessageEndEvent,
+    QueueMessageEvent,
+    QueueMessageFileEvent,
+    QueueMessageReplaceEvent,
+    QueuePingEvent,
+    QueueRetrieverResourcesEvent,
+    QueueStopEvent,
+)
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, PromptMessageContentType, PromptMessageRole,
-                                                          TextPromptMessageContent)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageRole,
+    TextPromptMessageContent,
+)
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.prompt.prompt_template import PromptTemplateParser
 from core.tools.tool_file_manager import ToolFileManager
-from core.tools.tool_manager import ToolManager
 from events.message_event import message_was_created
 from extensions.ext_database import db
 from models.model import Conversation, Message, MessageAgentThought, MessageFile
-from pydantic import BaseModel
 from services.annotation_service import AppAnnotationService
 
 logger = logging.getLogger(__name__)

api/core/app_runner/moderation_handler.py

@@ -3,11 +3,12 @@ import threading
 import time
 from typing import Any, Dict, Optional
 
+from flask import Flask, current_app
+from pydantic import BaseModel
+
 from core.application_queue_manager import PublishFrom
 from core.moderation.base import ModerationAction, ModerationOutputsResult
 from core.moderation.factory import ModerationFactory
-from flask import Flask, current_app
-from pydantic import BaseModel
 
 logger = logging.getLogger(__name__)
 

api/core/application_manager.py

@@ -4,17 +4,30 @@ import threading
 import uuid
 from typing import Any, Generator, Optional, Tuple, Union, cast
 
+from flask import Flask, current_app
+from pydantic import ValidationError
+
 from core.app_runner.assistant_app_runner import AssistantApplicationRunner
 from core.app_runner.basic_app_runner import BasicApplicationRunner
 from core.app_runner.generate_task_pipeline import GenerateTaskPipeline
 from core.application_queue_manager import ApplicationQueueManager, ConversationTaskStoppedException, PublishFrom
-from core.entities.application_entities import (AdvancedChatPromptTemplateEntity,
-                                                AdvancedCompletionPromptTemplateEntity, AgentEntity, AgentPromptEntity,
-                                                AgentToolEntity, ApplicationGenerateEntity,
-                                                AppOrchestrationConfigEntity, DatasetEntity,
-                                                DatasetRetrieveConfigEntity, ExternalDataVariableEntity,
-                                                FileUploadEntity, InvokeFrom, ModelConfigEntity, PromptTemplateEntity,
-                                                SensitiveWordAvoidanceEntity)
+from core.entities.application_entities import (
+    AdvancedChatPromptTemplateEntity,
+    AdvancedCompletionPromptTemplateEntity,
+    AgentEntity,
+    AgentPromptEntity,
+    AgentToolEntity,
+    ApplicationGenerateEntity,
+    AppOrchestrationConfigEntity,
+    DatasetEntity,
+    DatasetRetrieveConfigEntity,
+    ExternalDataVariableEntity,
+    FileUploadEntity,
+    InvokeFrom,
+    ModelConfigEntity,
+    PromptTemplateEntity,
+    SensitiveWordAvoidanceEntity,
+)
 from core.entities.model_entities import ModelStatus
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.file.file_obj import FileObj
@@ -26,10 +39,8 @@ from core.prompt.prompt_template import PromptTemplateParser
 from core.provider_manager import ProviderManager
 from core.tools.prompt.template import REACT_PROMPT_TEMPLATES
 from extensions.ext_database import db
-from flask import Flask, current_app
 from models.account import Account
 from models.model import App, Conversation, EndUser, Message, MessageFile
-from pydantic import ValidationError
 
 logger = logging.getLogger(__name__)
 

api/core/application_queue_manager.py

@@ -3,15 +3,27 @@ import time
 from enum import Enum
 from typing import Any, Generator
 
+from sqlalchemy.orm import DeclarativeMeta
+
 from core.entities.application_entities import InvokeFrom
-from core.entities.queue_entities import (AnnotationReplyEvent, AppQueueEvent, QueueAgentMessageEvent,
-                                          QueueAgentThoughtEvent, QueueErrorEvent, QueueMessage, QueueMessageEndEvent,
-                                          QueueMessageEvent, QueueMessageFileEvent, QueueMessageReplaceEvent,
-                                          QueuePingEvent, QueueRetrieverResourcesEvent, QueueStopEvent)
+from core.entities.queue_entities import (
+    AnnotationReplyEvent,
+    AppQueueEvent,
+    QueueAgentMessageEvent,
+    QueueAgentThoughtEvent,
+    QueueErrorEvent,
+    QueueMessage,
+    QueueMessageEndEvent,
+    QueueMessageEvent,
+    QueueMessageFileEvent,
+    QueueMessageReplaceEvent,
+    QueuePingEvent,
+    QueueRetrieverResourcesEvent,
+    QueueStopEvent,
+)
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
 from extensions.ext_redis import redis_client
 from models.model import MessageAgentThought, MessageFile
-from sqlalchemy.orm import DeclarativeMeta
 
 
 class PublishFrom(Enum):

api/core/callback_handler/agent_loop_gather_callback_handler.py

@@ -3,6 +3,10 @@ import logging
 import time
 from typing import Any, Dict, List, Optional, Union, cast
 
+from langchain.agents import openai_functions_agent, openai_functions_multi_agent
+from langchain.callbacks.base import BaseCallbackHandler
+from langchain.schema import AgentAction, AgentFinish, BaseMessage, LLMResult
+
 from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.callback_handler.entity.agent_loop import AgentLoop
 from core.entities.application_entities import ModelConfigEntity
@@ -10,9 +14,6 @@ from core.model_runtime.entities.llm_entities import LLMResult as RuntimeLLMResu
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from extensions.ext_database import db
-from langchain.agents import openai_functions_agent, openai_functions_multi_agent
-from langchain.callbacks.base import BaseCallbackHandler
-from langchain.schema import AgentAction, AgentFinish, BaseMessage, ChatGeneration, LLMResult
 from models.model import Message, MessageAgentThought, MessageChain
 
 

api/core/callback_handler/index_tool_callback_handler.py

@@ -1,9 +1,10 @@
-from typing import List, Union
+from typing import List
+
+from langchain.schema import Document
 
 from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.entities.application_entities import InvokeFrom
 from extensions.ext_database import db
-from langchain.schema import Document
 from models.dataset import DatasetQuery, DocumentSegment
 from models.model import DatasetRetrieverResource
 

api/core/chain/llm_chain.py

@@ -1,14 +1,15 @@
 from typing import Any, Dict, List, Optional
 
+from langchain import LLMChain as LCLLMChain
+from langchain.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema import Generation, LLMResult
+from langchain.schema.language_model import BaseLanguageModel
+
 from core.agent.agent.agent_llm_callback import AgentLLMCallback
 from core.entities.application_entities import ModelConfigEntity
 from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_manager import ModelInstance
 from core.third_party.langchain.llms.fake import FakeLLM
-from langchain import LLMChain as LCLLMChain
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.schema import Generation, LLMResult
-from langchain.schema.language_model import BaseLanguageModel
 
 
 class LLMChain(LCLLMChain):

api/core/data_loader/file_extractor.py

@@ -3,6 +3,10 @@ from pathlib import Path
 from typing import List, Optional, Union
 
 import requests
+from flask import current_app
+from langchain.document_loaders import Docx2txtLoader, TextLoader
+from langchain.schema import Document
+
 from core.data_loader.loader.csv_loader import CSVLoader
 from core.data_loader.loader.excel import ExcelLoader
 from core.data_loader.loader.html import HTMLLoader
@@ -16,9 +20,6 @@ from core.data_loader.loader.unstructured.unstructured_pptx import UnstructuredP
 from core.data_loader.loader.unstructured.unstructured_text import UnstructuredTextLoader
 from core.data_loader.loader.unstructured.unstructured_xml import UnstructuredXmlLoader
 from extensions.ext_storage import storage
-from flask import current_app
-from langchain.document_loaders import Docx2txtLoader, TextLoader
-from langchain.schema import Document
 from models.model import UploadFile
 
 SUPPORT_URL_CONTENT_TYPES = ['application/pdf', 'text/plain']

api/core/data_loader/loader/excel.py

@@ -1,4 +1,3 @@
-import json
 import logging
 from typing import List
 

api/core/data_loader/loader/notion.py

@@ -3,10 +3,11 @@ import logging
 from typing import Any, Dict, List, Optional
 
 import requests
-from extensions.ext_database import db
 from flask import current_app
 from langchain.document_loaders.base import BaseLoader
 from langchain.schema import Document
+
+from extensions.ext_database import db
 from models.dataset import Document as DocumentModel
 from models.source import DataSourceBinding
 

api/core/data_loader/loader/pdf.py

@@ -1,10 +1,11 @@
 import logging
 from typing import List, Optional
 
-from extensions.ext_storage import storage
 from langchain.document_loaders import PyPDFium2Loader
 from langchain.document_loaders.base import BaseLoader
 from langchain.schema import Document
+
+from extensions.ext_storage import storage
 from models.model import UploadFile
 
 logger = logging.getLogger(__name__)

api/core/docstore/dataset_docstore.py

@@ -1,12 +1,13 @@
 from typing import Any, Dict, Optional, Sequence, cast
 
+from langchain.schema import Document
+from sqlalchemy import func
+
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from extensions.ext_database import db
-from langchain.schema import Document
 from models.dataset import Dataset, DocumentSegment
-from sqlalchemy import func
 
 
 class DatasetDocumentStore:

api/core/embedding/cached_embedding.py

@@ -1,18 +1,17 @@
 import base64
-import json
 import logging
 from typing import List, Optional, cast
 
 import numpy as np
+from langchain.embeddings.base import Embeddings
+from sqlalchemy.exc import IntegrityError
+
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client
-from langchain.embeddings.base import Embeddings
 from libs import helper
-from models.dataset import Embedding
-from sqlalchemy.exc import IntegrityError
 
 logger = logging.getLogger(__name__)
 

api/core/entities/application_entities.py

@@ -1,11 +1,12 @@
 from enum import Enum
-from typing import Any, Literal, Optional, Union, cast
+from typing import Any, Literal, Optional, Union
+
+from pydantic import BaseModel
 
 from core.entities.provider_configuration import ProviderModelBundle
 from core.file.file_obj import FileObj
 from core.model_runtime.entities.message_entities import PromptMessageRole
 from core.model_runtime.entities.model_entities import AIModelEntity
-from pydantic import BaseModel
 
 
 class ModelConfigEntity(BaseModel):

api/core/entities/message_entities.py

@@ -1,12 +1,19 @@
 import enum
 from typing import Any, cast
 
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, SystemPromptMessage, TextPromptMessageContent,
-                                                          ToolPromptMessage, UserPromptMessage)
 from langchain.schema import AIMessage, BaseMessage, FunctionMessage, HumanMessage, SystemMessage
 from pydantic import BaseModel
 
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+
 
 class PromptMessageFileType(enum.Enum):
     IMAGE = 'image'

api/core/entities/model_entities.py

@@ -1,10 +1,11 @@
 from enum import Enum
 from typing import Optional
 
+from pydantic import BaseModel
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.model_entities import ModelType, ProviderModel
-from core.model_runtime.entities.provider_entities import ProviderEntity, SimpleProviderEntity
-from pydantic import BaseModel
+from core.model_runtime.entities.provider_entities import ProviderEntity
 
 
 class ModelStatus(Enum):

api/core/entities/provider_configuration.py

@@ -4,20 +4,24 @@ import logging
 from json import JSONDecodeError
 from typing import Dict, Iterator, List, Optional, Tuple
 
+from pydantic import BaseModel
+
 from core.entities.model_entities import ModelStatus, ModelWithProviderEntity, SimpleModelProviderEntity
 from core.entities.provider_entities import CustomConfiguration, SystemConfiguration, SystemConfigurationStatus
 from core.helper import encrypter
 from core.helper.model_provider_cache import ProviderCredentialsCache, ProviderCredentialsCacheType
 from core.model_runtime.entities.model_entities import FetchFrom, ModelType
-from core.model_runtime.entities.provider_entities import (ConfigurateMethod, CredentialFormSchema, FormType,
-                                                           ProviderEntity)
+from core.model_runtime.entities.provider_entities import (
+    ConfigurateMethod,
+    CredentialFormSchema,
+    FormType,
+    ProviderEntity,
+)
 from core.model_runtime.model_providers import model_provider_factory
 from core.model_runtime.model_providers.__base.ai_model import AIModel
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
-from core.model_runtime.utils import encoders
 from extensions.ext_database import db
 from models.provider import Provider, ProviderModel, ProviderType, TenantPreferredModelProvider
-from pydantic import BaseModel
 
 logger = logging.getLogger(__name__)
 

api/core/entities/provider_entities.py

@@ -1,9 +1,10 @@
 from enum import Enum
 from typing import Optional
 
+from pydantic import BaseModel
+
 from core.model_runtime.entities.model_entities import ModelType
 from models.provider import ProviderQuotaType
-from pydantic import BaseModel
 
 
 class QuotaUnit(Enum):

api/core/entities/queue_entities.py

@@ -1,9 +1,10 @@
 from enum import Enum
 from typing import Any
 
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
 from pydantic import BaseModel
 
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
+
 
 class QueueEvent(Enum):
     """

api/core/extension/api_based_extension_requestor.py

@@ -1,6 +1,7 @@
 import os
 
 import requests
+
 from models.api_based_extension import APIBasedExtensionPoint
 
 

api/core/features/agent_runner.py

@@ -1,5 +1,7 @@
 import logging
-from typing import List, Optional, cast
+from typing import Optional, cast
+
+from langchain.tools import BaseTool
 
 from core.agent.agent.agent_llm_callback import AgentLLMCallback
 from core.agent.agent_executor import AgentConfiguration, AgentExecutor, PlanningStrategy
@@ -7,20 +9,20 @@ from core.application_queue_manager import ApplicationQueueManager
 from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
-from core.entities.application_entities import (AgentEntity, AgentToolEntity, AppOrchestrationConfigEntity, InvokeFrom,
-                                                ModelConfigEntity)
+from core.entities.application_entities import (
+    AgentEntity,
+    AppOrchestrationConfigEntity,
+    InvokeFrom,
+    ModelConfigEntity,
+)
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.model_entities import ModelFeature, ModelType
 from core.model_runtime.model_providers import model_provider_factory
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool
 from extensions.ext_database import db
-from langchain import WikipediaAPIWrapper
-from langchain.callbacks.base import BaseCallbackHandler
-from langchain.tools import BaseTool, Tool, WikipediaQueryRun
 from models.dataset import Dataset
 from models.model import Message
-from pydantic import BaseModel, Field
 
 logger = logging.getLogger(__name__)
 

api/core/features/annotation_reply.py

@@ -1,13 +1,14 @@
 import logging
 from typing import Optional
 
+from flask import current_app
+
 from core.embedding.cached_embedding import CacheEmbedding
 from core.entities.application_entities import InvokeFrom
 from core.index.vector_index.vector_index import VectorIndex
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from extensions.ext_database import db
-from flask import current_app
 from models.dataset import Dataset
 from models.model import App, AppAnnotationSetting, Message, MessageAnnotation
 from services.annotation_service import AppAnnotationService

api/core/features/assistant_base_runner.py

@@ -8,8 +8,14 @@ from core.app_runner.app_runner import AppRunner
 from core.application_queue_manager import ApplicationQueueManager
 from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import (AgentEntity, AgentToolEntity, ApplicationGenerateEntity,
-                                                AppOrchestrationConfigEntity, InvokeFrom, ModelConfigEntity)
+from core.entities.application_entities import (
+    AgentEntity,
+    AgentToolEntity,
+    ApplicationGenerateEntity,
+    AppOrchestrationConfigEntity,
+    InvokeFrom,
+    ModelConfigEntity,
+)
 from core.file.message_file_parser import FileTransferMethod
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
@@ -18,8 +24,12 @@ from core.model_runtime.entities.message_entities import PromptMessage, PromptMe
 from core.model_runtime.entities.model_entities import ModelFeature
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.tools.entities.tool_entities import (ToolInvokeMessage, ToolInvokeMessageBinary, ToolParameter,
-                                               ToolRuntimeVariablePool)
+from core.tools.entities.tool_entities import (
+    ToolInvokeMessage,
+    ToolInvokeMessageBinary,
+    ToolParameter,
+    ToolRuntimeVariablePool,
+)
 from core.tools.tool.dataset_retriever_tool import DatasetRetrieverTool
 from core.tools.tool.tool import Tool
 from core.tools.tool_file_manager import ToolFileManager

api/core/features/assistant_cot_runner.py

@@ -1,18 +1,27 @@
 import json
-import logging
 import re
 from typing import Dict, Generator, List, Literal, Union
 
 from core.application_queue_manager import PublishFrom
 from core.entities.application_entities import AgentPromptEntity, AgentScratchpadUnit
 from core.features.assistant_base_runner import BaseAssistantApplicationRunner
-from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.tools.errors import (ToolInvokeError, ToolNotFoundError, ToolNotSupportedError, ToolParameterValidationError,
-                               ToolProviderCredentialValidationError, ToolProviderNotFoundError)
+from core.tools.errors import (
+    ToolInvokeError,
+    ToolNotFoundError,
+    ToolNotSupportedError,
+    ToolParameterValidationError,
+    ToolProviderCredentialValidationError,
+    ToolProviderNotFoundError,
+)
 from models.model import Conversation, Message
 
 

api/core/features/assistant_fc_runner.py

@@ -4,12 +4,23 @@ from typing import Any, Dict, Generator, List, Tuple, Union
 
 from core.application_queue_manager import PublishFrom
 from core.features.assistant_base_runner import BaseAssistantApplicationRunner
-from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, ToolPromptMessage, UserPromptMessage)
-from core.tools.errors import (ToolInvokeError, ToolNotFoundError, ToolNotSupportedError, ToolParameterValidationError,
-                               ToolProviderCredentialValidationError, ToolProviderNotFoundError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.tools.errors import (
+    ToolInvokeError,
+    ToolNotFoundError,
+    ToolNotSupportedError,
+    ToolParameterValidationError,
+    ToolProviderCredentialValidationError,
+    ToolProviderNotFoundError,
+)
 from models.model import Conversation, Message, MessageAgentThought
 
 logger = logging.getLogger(__name__)

api/core/features/dataset_retrieval.py

@@ -1,5 +1,7 @@
 from typing import List, Optional, cast
 
+from langchain.tools import BaseTool
+
 from core.agent.agent_executor import AgentConfiguration, AgentExecutor, PlanningStrategy
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.entities.application_entities import DatasetEntity, DatasetRetrieveConfigEntity, InvokeFrom, ModelConfigEntity
@@ -9,7 +11,6 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 from core.tools.tool.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool
 from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool
 from extensions.ext_database import db
-from langchain.tools import BaseTool
 from models.dataset import Dataset
 
 

api/core/features/external_data_fetch.py

@@ -4,9 +4,10 @@ import logging
 from concurrent.futures import ThreadPoolExecutor
 from typing import Optional, Tuple
 
+from flask import Flask, current_app
+
 from core.entities.application_entities import ExternalDataVariableEntity
 from core.external_data_tool.factory import ExternalDataToolFactory
-from flask import Flask, current_app
 
 logger = logging.getLogger(__name__)
 

api/core/file/file_obj.py

@@ -1,11 +1,12 @@
 import enum
 from typing import Optional
 
+from pydantic import BaseModel
+
 from core.file.upload_file_parser import UploadFileParser
 from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from extensions.ext_database import db
 from models.model import UploadFile
-from pydantic import BaseModel
 
 
 class FileType(enum.Enum):

api/core/file/message_file_parser.py

@@ -1,6 +1,7 @@
 from typing import Dict, List, Optional, Union
 
 import requests
+
 from core.file.file_obj import FileBelongsTo, FileObj, FileTransferMethod, FileType
 from extensions.ext_database import db
 from models.account import Account

api/core/file/upload_file_parser.py

@@ -6,9 +6,10 @@ import os
 import time
 from typing import Optional
 
-from extensions.ext_storage import storage
 from flask import current_app
 
+from extensions.ext_storage import storage
+
 IMAGE_EXTENSIONS = ['jpg', 'jpeg', 'png', 'webp', 'gif', 'svg']
 IMAGE_EXTENSIONS.extend([ext.upper() for ext in IMAGE_EXTENSIONS])
 

api/core/generator/llm_generator.py

@@ -1,6 +1,8 @@
 import json
 import logging
 
+from langchain.schema import OutputParserException
+
 from core.model_manager import ModelManager
 from core.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage
 from core.model_runtime.entities.model_entities import ModelType
@@ -9,7 +11,6 @@ from core.prompt.output_parser.rule_config_generator import RuleConfigGeneratorO
 from core.prompt.output_parser.suggested_questions_after_answer import SuggestedQuestionsAfterAnswerOutputParser
 from core.prompt.prompt_template import PromptTemplateParser
 from core.prompt.prompts import CONVERSATION_TITLE_PROMPT, GENERATOR_QA_PROMPT
-from langchain.schema import OutputParserException
 
 
 class LLMGenerator:

api/core/helper/ssrf_proxy.py

@@ -2,11 +2,16 @@
 Proxy requests to avoid SSRF
 """
 
-from httpx import get as _get, post as _post, put as _put, patch as _patch, head as _head, options as _options
-from requests import delete as _delete
-
 import os
 
+from httpx import get as _get
+from httpx import head as _head
+from httpx import options as _options
+from httpx import patch as _patch
+from httpx import post as _post
+from httpx import put as _put
+from requests import delete as _delete
+
 SSRF_PROXY_HTTP_URL = os.getenv('SSRF_PROXY_HTTP_URL', '')
 SSRF_PROXY_HTTPS_URL = os.getenv('SSRF_PROXY_HTTPS_URL', '')
 

api/core/hosting_configuration.py

@@ -1,10 +1,11 @@
 from typing import Optional
 
+from flask import Config, Flask
+from pydantic import BaseModel
+
 from core.entities.provider_entities import QuotaUnit, RestrictModel
 from core.model_runtime.entities.model_entities import ModelType
-from flask import Config, Flask
 from models.provider import ProviderQuotaType
-from pydantic import BaseModel
 
 
 class HostingQuota(BaseModel):

api/core/index/base.py

@@ -4,6 +4,7 @@ from abc import ABC, abstractmethod
 from typing import Any, List
 
 from langchain.schema import BaseRetriever, Document
+
 from models.dataset import Dataset
 
 

api/core/index/index.py

@@ -1,10 +1,11 @@
+from flask import current_app
+from langchain.embeddings import OpenAIEmbeddings
+
 from core.embedding.cached_embedding import CacheEmbedding
 from core.index.keyword_table_index.keyword_table_index import KeywordTableConfig, KeywordTableIndex
 from core.index.vector_index.vector_index import VectorIndex
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
-from flask import current_app
-from langchain.embeddings import OpenAIEmbeddings
 from models.dataset import Dataset
 
 

api/core/index/keyword_table_index/jieba_keyword_table_handler.py

@@ -2,9 +2,10 @@ import re
 from typing import Set
 
 import jieba
-from core.index.keyword_table_index.stopwords import STOPWORDS
 from jieba.analyse import default_tfidf
 
+from core.index.keyword_table_index.stopwords import STOPWORDS
+
 
 class JiebaKeywordTableHandler:
 

api/core/index/keyword_table_index/keyword_table_index.py

@@ -2,12 +2,13 @@ import json
 from collections import defaultdict
 from typing import Any, Dict, List, Optional
 
+from langchain.schema import BaseRetriever, Document
+from pydantic import BaseModel, Extra, Field
+
 from core.index.base import BaseIndex
 from core.index.keyword_table_index.jieba_keyword_table_handler import JiebaKeywordTableHandler
 from extensions.ext_database import db
-from langchain.schema import BaseRetriever, Document
 from models.dataset import Dataset, DatasetKeywordTable, DocumentSegment
-from pydantic import BaseModel, Extra, Field
 
 
 class KeywordTableConfig(BaseModel):

api/core/index/vector_index/base.py

@@ -3,14 +3,14 @@ import logging
 from abc import abstractmethod
 from typing import Any, List, cast
 
-from core.index.base import BaseIndex
-from extensions.ext_database import db
 from langchain.embeddings.base import Embeddings
 from langchain.schema import BaseRetriever, Document
 from langchain.vectorstores import VectorStore
-from models.dataset import Dataset, DatasetCollectionBinding
+
+from core.index.base import BaseIndex
+from extensions.ext_database import db
+from models.dataset import Dataset, DatasetCollectionBinding, DocumentSegment
 from models.dataset import Document as DatasetDocument
-from models.dataset import DocumentSegment
 
 
 class BaseVectorIndex(BaseIndex):

api/core/index/vector_index/milvus_vector_index.py

@@ -1,13 +1,14 @@
 from typing import Any, List, cast
 
+from langchain.embeddings.base import Embeddings
+from langchain.schema import Document
+from langchain.vectorstores import VectorStore
+from pydantic import BaseModel, root_validator
+
 from core.index.base import BaseIndex
 from core.index.vector_index.base import BaseVectorIndex
 from core.vector_store.milvus_vector_store import MilvusVectorStore
-from langchain.embeddings.base import Embeddings
-from langchain.schema import Document
-from langchain.vectorstores import VectorStore
 from models.dataset import Dataset
-from pydantic import BaseModel, root_validator
 
 
 class MilvusConfig(BaseModel):

api/core/index/vector_index/qdrant_vector_index.py

@@ -2,16 +2,17 @@ import os
 from typing import Any, List, Optional, cast
 
 import qdrant_client
+from langchain.embeddings.base import Embeddings
+from langchain.schema import Document
+from langchain.vectorstores import VectorStore
+from pydantic import BaseModel
+from qdrant_client.http.models import HnswConfigDiff
+
 from core.index.base import BaseIndex
 from core.index.vector_index.base import BaseVectorIndex
 from core.vector_store.qdrant_vector_store import QdrantVectorStore
 from extensions.ext_database import db
-from langchain.embeddings.base import Embeddings
-from langchain.schema import BaseRetriever, Document
-from langchain.vectorstores import VectorStore
 from models.dataset import Dataset, DatasetCollectionBinding
-from pydantic import BaseModel
-from qdrant_client.http.models import HnswConfigDiff
 
 
 class QdrantConfig(BaseModel):

api/core/index/vector_index/vector_index.py

@@ -1,9 +1,10 @@
 import json
 
+from flask import current_app
+from langchain.embeddings.base import Embeddings
+
 from core.index.vector_index.base import BaseVectorIndex
 from extensions.ext_database import db
-from flask import current_app
-from langchain.embeddings.base import Embeddings
 from models.dataset import Dataset, Document
 
 

api/core/index/vector_index/weaviate_vector_index.py

@@ -2,14 +2,15 @@ from typing import Any, List, Optional, cast
 
 import requests
 import weaviate
+from langchain.embeddings.base import Embeddings
+from langchain.schema import Document
+from langchain.vectorstores import VectorStore
+from pydantic import BaseModel, root_validator
+
 from core.index.base import BaseIndex
 from core.index.vector_index.base import BaseVectorIndex
 from core.vector_store.weaviate_vector_store import WeaviateVectorStore
-from langchain.embeddings.base import Embeddings
-from langchain.schema import BaseRetriever, Document
-from langchain.vectorstores import VectorStore
 from models.dataset import Dataset
-from pydantic import BaseModel, root_validator
 
 
 class WeaviateConfig(BaseModel):

api/core/indexing_runner.py

@@ -5,7 +5,13 @@ import re
 import threading
 import time
 import uuid
-from typing import AbstractSet, Any, Collection, List, Literal, Optional, Type, Union, cast
+from typing import List, Optional, cast
+
+from flask import Flask, current_app
+from flask_login import current_user
+from langchain.schema import Document
+from langchain.text_splitter import TextSplitter
+from sqlalchemy.orm.exc import ObjectDeletedError
 
 from core.data_loader.file_extractor import FileExtractor
 from core.data_loader.loader.notion import NotionLoader
@@ -17,22 +23,15 @@ from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities.model_entities import ModelType, PriceType
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
-from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer
 from core.spiltter.fixed_text_splitter import EnhanceRecursiveCharacterTextSplitter, FixedRecursiveCharacterTextSplitter
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client
 from extensions.ext_storage import storage
-from flask import Flask, current_app
-from flask_login import current_user
-from langchain.schema import Document
-from langchain.text_splitter import TS, TextSplitter, TokenTextSplitter
 from libs import helper
-from models.dataset import Dataset, DatasetProcessRule
+from models.dataset import Dataset, DatasetProcessRule, DocumentSegment
 from models.dataset import Document as DatasetDocument
-from models.dataset import DocumentSegment
 from models.model import UploadFile
 from models.source import DataSourceBinding
-from sqlalchemy.orm.exc import ObjectDeletedError
 
 
 class IndexingRunner:

api/core/memory/token_buffer_memory.py

@@ -1,7 +1,12 @@
 from core.file.message_file_parser import MessageFileParser
 from core.model_manager import ModelInstance
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageRole,
-                                                          TextPromptMessageContent, UserPromptMessage)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageRole,
+    TextPromptMessageContent,
+    UserPromptMessage,
+)
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.model_providers import model_provider_factory
 from extensions.ext_database import db

api/core/model_runtime/entities/llm_entities.py

@@ -2,9 +2,10 @@ from decimal import Decimal
 from enum import Enum
 from typing import Optional
 
+from pydantic import BaseModel
+
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage
 from core.model_runtime.entities.model_entities import ModelUsage, PriceInfo
-from pydantic import BaseModel
 
 
 class LLMMode(Enum):

api/core/model_runtime/entities/model_entities.py

@@ -2,9 +2,10 @@ from decimal import Decimal
 from enum import Enum
 from typing import Any, Optional
 
-from core.model_runtime.entities.common_entities import I18nObject
 from pydantic import BaseModel
 
+from core.model_runtime.entities.common_entities import I18nObject
+
 
 class ModelType(Enum):
     """

api/core/model_runtime/entities/provider_entities.py

@@ -1,9 +1,10 @@
 from enum import Enum
 from typing import Optional
 
+from pydantic import BaseModel
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.model_entities import AIModelEntity, ModelType, ProviderModel
-from pydantic import BaseModel
 
 
 class ConfigurateMethod(Enum):

api/core/model_runtime/entities/text_embedding_entities.py

@@ -1,8 +1,9 @@
 from decimal import Decimal
 
-from core.model_runtime.entities.model_entities import ModelUsage
 from pydantic import BaseModel
 
+from core.model_runtime.entities.model_entities import ModelUsage
+
 
 class EmbeddingUsage(ModelUsage):
     """

api/core/model_runtime/model_providers/__base/ai_model.py

@@ -4,10 +4,18 @@ from abc import ABC, abstractmethod
 from typing import Optional
 
 import yaml
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom, ModelType,
-                                                        PriceConfig, PriceInfo, PriceType)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    DefaultParameterName,
+    FetchFrom,
+    ModelType,
+    PriceConfig,
+    PriceInfo,
+    PriceType,
+)
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
 from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer
 

api/core/model_runtime/model_providers/__base/large_language_model.py

@@ -9,8 +9,13 @@ from core.model_runtime.callbacks.base_callback import Callback
 from core.model_runtime.callbacks.logging_callback import LoggingCallback
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, PromptMessageTool
-from core.model_runtime.entities.model_entities import (ModelPropertyKey, ModelType, ParameterRule, ParameterType,
-                                                        PriceType)
+from core.model_runtime.entities.model_entities import (
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+    PriceType,
+)
 from core.model_runtime.model_providers.__base.ai_model import AIModel
 
 logger = logging.getLogger(__name__)

api/core/model_runtime/model_providers/__base/model_provider.py

@@ -1,9 +1,10 @@
 import importlib
 import os
 from abc import ABC, abstractmethod
-from typing import Dict, Optional
+from typing import Dict
 
 import yaml
+
 from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
 from core.model_runtime.entities.provider_entities import ProviderEntity
 from core.model_runtime.model_providers.__base.ai_model import AIModel

api/core/model_runtime/model_providers/anthropic/llm/llm.py

@@ -3,14 +3,26 @@ from typing import Generator, List, Optional, Union
 import anthropic
 from anthropic import Anthropic, Stream
 from anthropic.types import Completion, completion_create_params
+from httpx import Timeout
+
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from httpx import Timeout
 
 
 class AnthropicLargeLanguageModel(LargeLanguageModel):

api/core/model_runtime/model_providers/azure_openai/_common.py

@@ -1,9 +1,16 @@
 import openai
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
-from core.model_runtime.model_providers.azure_openai._constant import AZURE_OPENAI_API_VERSION
 from httpx import Timeout
 
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.model_providers.azure_openai._constant import AZURE_OPENAI_API_VERSION
+
 
 class _CommonAzureOpenAI:
     @staticmethod

api/core/model_runtime/model_providers/azure_openai/_constant.py

@@ -1,9 +1,18 @@
+from pydantic import BaseModel
+
 from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE
 from core.model_runtime.entities.llm_entities import LLMMode
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom, I18nObject,
-                                                        ModelFeature, ModelPropertyKey, ModelType, ParameterRule,
-                                                        PriceConfig)
-from pydantic import BaseModel
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    DefaultParameterName,
+    FetchFrom,
+    I18nObject,
+    ModelFeature,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    PriceConfig,
+)
 
 AZURE_OPENAI_API_VERSION = '2023-12-01-preview'
 

api/core/model_runtime/model_providers/azure_openai/llm/llm.py

@@ -3,22 +3,30 @@ import logging
 from typing import Generator, List, Optional, Union, cast
 
 import tiktoken
-from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, PromptMessageContentType, PromptMessageTool,
-                                                          SystemPromptMessage, TextPromptMessageContent,
-                                                          ToolPromptMessage, UserPromptMessage)
-from core.model_runtime.entities.model_entities import AIModelEntity, ModelPropertyKey
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI
-from core.model_runtime.model_providers.azure_openai._constant import LLM_BASE_MODELS, AzureBaseModel
 from openai import AzureOpenAI, Stream
 from openai.types import Completion
 from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall
 from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall
 from openai.types.chat.chat_completion_message import FunctionCall
 
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageTool,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import AIModelEntity, ModelPropertyKey
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI
+from core.model_runtime.model_providers.azure_openai._constant import LLM_BASE_MODELS, AzureBaseModel
+
 logger = logging.getLogger(__name__)
 
 

api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py

@@ -5,13 +5,14 @@ from typing import Optional, Tuple, Union
 
 import numpy as np
 import tiktoken
+from openai import AzureOpenAI
+
 from core.model_runtime.entities.model_entities import AIModelEntity, PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI
 from core.model_runtime.model_providers.azure_openai._constant import EMBEDDING_BASE_MODELS, AzureBaseModel
-from openai import AzureOpenAI
 
 
 class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):

api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo.py

@@ -1,18 +1,19 @@
 from enum import Enum
 from hashlib import md5
 from json import dumps, loads
-from os.path import join
-from time import time
-from typing import Any, Dict, Generator, List, Optional, Union
+from typing import Any, Dict, Generator, List, Union
 
-from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (BadRequestError,
-                                                                                   InsufficientAccountBalance,
-                                                                                   InternalServerError,
-                                                                                   InvalidAPIKeyError,
-                                                                                   InvalidAuthenticationError,
-                                                                                   RateLimitReachedError)
 from requests import post
 
+from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (
+    BadRequestError,
+    InsufficientAccountBalance,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
+
 
 class BaichuanMessage:
     class Role(Enum):

api/core/model_runtime/model_providers/baichuan/llm/llm.py

@@ -1,20 +1,33 @@
-from typing import Generator, List, Optional, Union, cast
+from typing import Generator, List, cast
 
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.baichuan.llm.baichuan_tokenizer import BaichuanTokenizer
 from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo import BaichuanMessage, BaichuanModel
-from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (BadRequestError,
-                                                                                   InsufficientAccountBalance,
-                                                                                   InternalServerError,
-                                                                                   InvalidAPIKeyError,
-                                                                                   InvalidAuthenticationError,
-                                                                                   RateLimitReachedError)
+from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (
+    BadRequestError,
+    InsufficientAccountBalance,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
 
 
 class BaichuanLarguageModel(LargeLanguageModel):

api/core/model_runtime/model_providers/baichuan/text_embedding/text_embedding.py

@@ -1,21 +1,30 @@
 import time
-from json import dumps, loads
+from json import dumps
 from typing import Optional, Tuple
 
+from requests import post
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from core.model_runtime.model_providers.baichuan.llm.baichuan_tokenizer import BaichuanTokenizer
-from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (BadRequestError,
-                                                                                   InsufficientAccountBalance,
-                                                                                   InternalServerError,
-                                                                                   InvalidAPIKeyError,
-                                                                                   InvalidAuthenticationError,
-                                                                                   RateLimitReachedError)
-from requests import post
+from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import (
+    BadRequestError,
+    InsufficientAccountBalance,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
 
 
 class BaichuanTextEmbeddingModel(TextEmbeddingModel):

api/core/model_runtime/model_providers/bedrock/llm/llm.py

@@ -4,13 +4,30 @@ from typing import Generator, List, Optional, Union
 
 import boto3
 from botocore.config import Config
-from botocore.exceptions import (ClientError, EndpointConnectionError, NoRegionError, ServiceNotInRegionError,
-                                 UnknownServiceError)
+from botocore.exceptions import (
+    ClientError,
+    EndpointConnectionError,
+    NoRegionError,
+    ServiceNotInRegionError,
+    UnknownServiceError,
+)
+
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 

api/core/model_runtime/model_providers/chatglm/llm/llm.py

@@ -1,23 +1,44 @@
 import logging
-from json import dumps
 from os.path import join
 from typing import Generator, List, Optional, cast
 
+from httpx import Timeout
+from openai import (
+    APIConnectionError,
+    APITimeoutError,
+    AuthenticationError,
+    ConflictError,
+    InternalServerError,
+    NotFoundError,
+    OpenAI,
+    PermissionDeniedError,
+    RateLimitError,
+    Stream,
+    UnprocessableEntityError,
+)
+from openai.types.chat import ChatCompletion, ChatCompletionChunk
+from openai.types.chat.chat_completion_message import FunctionCall
+
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageFunction,
-                                                          PromptMessageTool, SystemPromptMessage, ToolPromptMessage,
-                                                          UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils import helper
-from httpx import Timeout
-from openai import (APIConnectionError, APITimeoutError, AuthenticationError, ConflictError, InternalServerError,
-                    NotFoundError, OpenAI, PermissionDeniedError, RateLimitError, Stream, UnprocessableEntityError)
-from openai.types.chat import ChatCompletion, ChatCompletionChunk
-from openai.types.chat.chat_completion_message import FunctionCall
-from requests import post
 
 logger = logging.getLogger(__name__)
 

api/core/model_runtime/model_providers/cohere/llm/llm.py

@@ -5,14 +5,26 @@ import cohere
 from cohere.responses import Chat, Generations
 from cohere.responses.chat import StreamEnd, StreamingChat, StreamTextGeneration
 from cohere.responses.generation import StreamingGenerations, StreamingText
+
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage,
-                                                          PromptMessageContentType, PromptMessageTool,
-                                                          SystemPromptMessage, TextPromptMessageContent,
-                                                          UserPromptMessage)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageTool,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    UserPromptMessage,
+)
 from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 

api/core/model_runtime/model_providers/cohere/rerank/rerank.py

@@ -1,9 +1,16 @@
 from typing import Optional
 
 import cohere
+
 from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.rerank_model import RerankModel
 

api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py

@@ -4,10 +4,17 @@ from typing import Optional, Tuple
 import cohere
 import numpy as np
 from cohere.responses import Tokens
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 

api/core/model_runtime/model_providers/google/llm/llm.py

@@ -4,18 +4,30 @@ from typing import Generator, List, Optional, Union
 import google.api_core.exceptions as exceptions
 import google.generativeai as genai
 import google.generativeai.client as client
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage,
-                                                          PromptMessageContentType, PromptMessageRole,
-                                                          PromptMessageTool, SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
-from core.model_runtime.model_providers import google
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from google.generativeai.types import ContentType, GenerateContentResponse, HarmBlockThreshold, HarmCategory
 from google.generativeai.types.content_types import to_part
 
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageRole,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+
 logger = logging.getLogger(__name__)
 
 class GoogleLargeLanguageModel(LargeLanguageModel):

api/core/model_runtime/model_providers/huggingface_hub/_common.py

@@ -1,6 +1,7 @@
-from core.model_runtime.errors.invoke import InvokeBadRequestError, InvokeError
 from huggingface_hub.utils import BadRequestError, HfHubHTTPError
 
+from core.model_runtime.errors.invoke import InvokeBadRequestError, InvokeError
+
 
 class _CommonHuggingfaceHub:
 

api/core/model_runtime/model_providers/huggingface_hub/llm/llm.py

@@ -1,18 +1,30 @@
 from typing import Generator, List, Optional, Union
 
+from huggingface_hub import InferenceClient
+from huggingface_hub.hf_api import HfApi
+from huggingface_hub.utils import BadRequestError
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom,
-                                                        ModelPropertyKey, ModelType, ParameterRule)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    DefaultParameterName,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.huggingface_hub._common import _CommonHuggingfaceHub
-from huggingface_hub import InferenceClient
-from huggingface_hub.hf_api import HfApi
-from huggingface_hub.utils import BadRequestError
 
 
 class HuggingfaceHubLargeLanguageModel(_CommonHuggingfaceHub, LargeLanguageModel):

api/core/model_runtime/model_providers/huggingface_hub/text_embedding/text_embedding.py

@@ -4,13 +4,14 @@ from typing import Optional
 
 import numpy as np
 import requests
+from huggingface_hub import HfApi, InferenceClient
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType, PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from core.model_runtime.model_providers.huggingface_hub._common import _CommonHuggingfaceHub
-from huggingface_hub import HfApi, InferenceClient
 
 HUGGINGFACE_ENDPOINT_API = 'https://api.endpoints.huggingface.cloud/v2/endpoint/'
 

api/core/model_runtime/model_providers/jina/text_embedding/text_embedding.py

@@ -2,14 +2,21 @@ import time
 from json import JSONDecodeError, dumps
 from typing import Optional
 
+from requests import post
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from core.model_runtime.model_providers.jina.text_embedding.jina_tokenizer import JinaTokenizer
-from requests import post
 
 
 class JinaTextEmbeddingModel(TextEmbeddingModel):

api/core/model_runtime/model_providers/localai/llm/llm.py

@@ -1,24 +1,53 @@
 from os.path import join
-from typing import Generator, List, Optional, Union, cast
+from typing import Generator, List, cast
 
-from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.entities.model_entities import (AIModelEntity, FetchFrom, ModelPropertyKey, ModelType,
-                                                        ParameterRule, ParameterType)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.model_runtime.utils import helper
 from httpx import Timeout
-from openai import (APIConnectionError, APITimeoutError, AuthenticationError, ConflictError, InternalServerError,
-                    NotFoundError, OpenAI, PermissionDeniedError, RateLimitError, Stream, UnprocessableEntityError)
+from openai import (
+    APIConnectionError,
+    APITimeoutError,
+    AuthenticationError,
+    ConflictError,
+    InternalServerError,
+    NotFoundError,
+    OpenAI,
+    PermissionDeniedError,
+    RateLimitError,
+    Stream,
+    UnprocessableEntityError,
+)
 from openai.types.chat import ChatCompletion, ChatCompletionChunk
 from openai.types.chat.chat_completion_message import FunctionCall
 from openai.types.completion import Completion
 
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.model_runtime.utils import helper
+
 
 class LocalAILarguageModel(LargeLanguageModel):
     def _invoke(self, model: str, credentials: dict, 

api/core/model_runtime/model_providers/localai/localai.py

@@ -1,7 +1,5 @@
 import logging
 
-from core.model_runtime.entities.model_entities import ModelType
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
 
 logger = logging.getLogger(__name__)

api/core/model_runtime/model_providers/localai/text_embedding/text_embedding.py

@@ -3,13 +3,20 @@ from json import JSONDecodeError, dumps
 from os.path import join
 from typing import Optional
 
+from requests import post
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
-from requests import post
 
 
 class LocalAITextEmbeddingModel(TextEmbeddingModel):

api/core/model_runtime/model_providers/minimax/llm/chat_completion.py

@@ -1,14 +1,18 @@
-from hashlib import md5
 from json import dumps, loads
-from time import time
 from typing import Any, Dict, Generator, List, Union
 
-from core.model_runtime.model_providers.minimax.llm.errors import (BadRequestError, InsufficientAccountBalanceError,
-                                                                   InternalServerError, InvalidAPIKeyError,
-                                                                   InvalidAuthenticationError, RateLimitReachedError)
-from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
 from requests import Response, post
 
+from core.model_runtime.model_providers.minimax.llm.errors import (
+    BadRequestError,
+    InsufficientAccountBalanceError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
+from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
+
 
 class MinimaxChatCompletion(object):
     """

api/core/model_runtime/model_providers/minimax/llm/chat_completion_pro.py

@@ -1,14 +1,18 @@
-from hashlib import md5
 from json import dumps, loads
-from time import time
 from typing import Any, Dict, Generator, List, Union
 
-from core.model_runtime.model_providers.minimax.llm.errors import (BadRequestError, InsufficientAccountBalanceError,
-                                                                   InternalServerError, InvalidAPIKeyError,
-                                                                   InvalidAuthenticationError, RateLimitReachedError)
-from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
 from requests import Response, post
 
+from core.model_runtime.model_providers.minimax.llm.errors import (
+    BadRequestError,
+    InsufficientAccountBalanceError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
+from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
+
 
 class MinimaxChatCompletionPro(object):
     """

api/core/model_runtime/model_providers/minimax/llm/llm.py

@@ -1,17 +1,34 @@
 from typing import Generator, List
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, ToolPromptMessage, UserPromptMessage)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    SystemPromptMessage,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.minimax.llm.chat_completion import MinimaxChatCompletion
 from core.model_runtime.model_providers.minimax.llm.chat_completion_pro import MinimaxChatCompletionPro
-from core.model_runtime.model_providers.minimax.llm.errors import (BadRequestError, InsufficientAccountBalanceError,
-                                                                   InternalServerError, InvalidAPIKeyError,
-                                                                   InvalidAuthenticationError, RateLimitReachedError)
+from core.model_runtime.model_providers.minimax.llm.errors import (
+    BadRequestError,
+    InsufficientAccountBalanceError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
 from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage
 
 

api/core/model_runtime/model_providers/minimax/text_embedding/text_embedding.py

@@ -1,17 +1,29 @@
 import time
-from json import dumps, loads
+from json import dumps
 from typing import Optional
 
+from requests import post
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
-from core.model_runtime.model_providers.minimax.llm.errors import (BadRequestError, InsufficientAccountBalanceError,
-                                                                   InternalServerError, InvalidAPIKeyError,
-                                                                   InvalidAuthenticationError, RateLimitReachedError)
-from requests import post
+from core.model_runtime.model_providers.minimax.llm.errors import (
+    BadRequestError,
+    InsufficientAccountBalanceError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
 
 
 class MinimaxTextEmbeddingModel(TextEmbeddingModel):

api/core/model_runtime/model_providers/model_provider_factory.py

@@ -5,12 +5,13 @@ from collections import OrderedDict
 from typing import Optional
 
 import yaml
+from pydantic import BaseModel
+
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.entities.provider_entities import ProviderConfig, ProviderEntity, SimpleProviderEntity
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
 from core.model_runtime.schema_validators.model_credential_schema_validator import ModelCredentialSchemaValidator
 from core.model_runtime.schema_validators.provider_credential_schema_validator import ProviderCredentialSchemaValidator
-from pydantic import BaseModel
 
 logger = logging.getLogger(__name__)
 

api/core/model_runtime/model_providers/moonshot/llm/llm.py

@@ -1,7 +1,7 @@
-from typing import List, Optional, Union, Generator
+from typing import Generator, List, Optional, Union
 
 from core.model_runtime.entities.llm_entities import LLMResult
-from core.model_runtime.entities.message_entities import (PromptMessage, PromptMessageTool)
+from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
 from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
 
 

api/core/model_runtime/model_providers/moonshot/moonshot.py

@@ -1,6 +1,6 @@
 import logging
 
-from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
+from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
 

api/core/model_runtime/model_providers/ollama/llm/llm.py

@@ -6,16 +6,38 @@ from typing import Generator, List, Optional, Union, cast
 from urllib.parse import urljoin
 
 import requests
+
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, PromptMessageContentType, PromptMessageTool,
-                                                          SystemPromptMessage, TextPromptMessageContent,
-                                                          UserPromptMessage)
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom, I18nObject,
-                                                        ModelFeature, ModelPropertyKey, ModelType, ParameterRule,
-                                                        ParameterType, PriceConfig)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageTool,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    DefaultParameterName,
+    FetchFrom,
+    I18nObject,
+    ModelFeature,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+    PriceConfig,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 

api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py

@@ -7,12 +7,25 @@ from urllib.parse import urljoin
 
 import numpy as np
 import requests
+
 from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.model_entities import (AIModelEntity, FetchFrom, ModelPropertyKey, ModelType,
-                                                        PriceConfig, PriceType)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    PriceConfig,
+    PriceType,
+)
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 

api/core/model_runtime/model_providers/openai/_common.py

@@ -1,8 +1,15 @@
 import openai
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
 from httpx import Timeout
 
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+
 
 class _CommonOpenAI:
     def _to_credential_kwargs(self, credentials: dict) -> dict:

api/core/model_runtime/model_providers/openai/llm/llm.py

@@ -2,23 +2,29 @@ import logging
 from typing import Generator, List, Optional, Union, cast
 
 import tiktoken
-from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, PromptMessageContentType,
-                                                          PromptMessageFunction, PromptMessageTool, SystemPromptMessage,
-                                                          TextPromptMessageContent, ToolPromptMessage,
-                                                          UserPromptMessage)
-from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType, PriceConfig
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.model_runtime.model_providers.openai._common import _CommonOpenAI
-from core.model_runtime.utils import helper
 from openai import OpenAI, Stream
 from openai.types import Completion
 from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall
 from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall
 from openai.types.chat.chat_completion_message import FunctionCall
 
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    PromptMessageContentType,
+    PromptMessageTool,
+    SystemPromptMessage,
+    TextPromptMessageContent,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType, PriceConfig
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.model_runtime.model_providers.openai._common import _CommonOpenAI
+
 logger = logging.getLogger(__name__)
 
 

api/core/model_runtime/model_providers/openai/moderation/moderation.py

@@ -1,11 +1,12 @@
 from typing import Optional
 
+from openai import OpenAI
+from openai.types import ModerationCreateResponse
+
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.moderation_model import ModerationModel
 from core.model_runtime.model_providers.openai._common import _CommonOpenAI
-from openai import OpenAI
-from openai.types import ModerationCreateResponse
 
 
 class OpenAIModerationModel(_CommonOpenAI, ModerationModel):

api/core/model_runtime/model_providers/openai/speech2text/speech2text.py

@@ -1,9 +1,10 @@
 from typing import IO, Optional
 
+from openai import OpenAI
+
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel
 from core.model_runtime.model_providers.openai._common import _CommonOpenAI
-from openai import OpenAI
 
 
 class OpenAISpeech2TextModel(_CommonOpenAI, Speech2TextModel):

api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py

@@ -4,12 +4,13 @@ from typing import Optional, Tuple, Union
 
 import numpy as np
 import tiktoken
+from openai import OpenAI
+
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
 from core.model_runtime.model_providers.openai._common import _CommonOpenAI
-from openai import OpenAI
 
 
 class OpenAITextEmbeddingModel(_CommonOpenAI, TextEmbeddingModel):

api/core/model_runtime/model_providers/openai/tts/tts.py

@@ -3,13 +3,14 @@ from functools import reduce
 from io import BytesIO
 from typing import Optional
 
+from flask import Response, stream_with_context
+from openai import OpenAI
+from pydub import AudioSegment
+
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.tts_model import TTSModel
 from core.model_runtime.model_providers.openai._common import _CommonOpenAI
-from flask import Response, stream_with_context
-from openai import OpenAI
-from pydub import AudioSegment
 
 
 class OpenAIText2SpeechModel(_CommonOpenAI, TTSModel):

api/core/model_runtime/model_providers/openai_api_compatible/_common.py

@@ -1,13 +1,14 @@
-from decimal import Decimal
 
 import requests
-from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.llm_entities import LLMMode
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom,
-                                                        ModelPropertyKey, ModelType, ParameterRule, ParameterType,
-                                                        PriceConfig)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 
 
 class _CommonOAI_API_Compat:

api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py

@@ -5,15 +5,31 @@ from typing import Generator, List, Optional, Union, cast
 from urllib.parse import urljoin
 
 import requests
+
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, ImagePromptMessageContent,
-                                                          PromptMessage, PromptMessageContent, PromptMessageContentType,
-                                                          PromptMessageFunction, PromptMessageTool, SystemPromptMessage,
-                                                          ToolPromptMessage, UserPromptMessage)
-from core.model_runtime.entities.model_entities import (AIModelEntity, DefaultParameterName, FetchFrom,
-                                                        ModelPropertyKey, ModelType, ParameterRule, ParameterType,
-                                                        PriceConfig)
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    ImagePromptMessageContent,
+    PromptMessage,
+    PromptMessageContent,
+    PromptMessageContentType,
+    PromptMessageFunction,
+    PromptMessageTool,
+    SystemPromptMessage,
+    ToolPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    DefaultParameterName,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+    PriceConfig,
+)
 from core.model_runtime.errors.invoke import InvokeError
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel

api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.py

@@ -1,7 +1,5 @@
 import logging
 
-from core.model_runtime.entities.model_entities import ModelType
-from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
 
 logger = logging.getLogger(__name__)

api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py

@@ -6,9 +6,16 @@ from urllib.parse import urljoin
 
 import numpy as np
 import requests
+
 from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.model_entities import (AIModelEntity, FetchFrom, ModelPropertyKey, ModelType,
-                                                        PriceConfig, PriceType)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    PriceConfig,
+    PriceType,
+)
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel

api/core/model_runtime/model_providers/openllm/llm/llm.py

@@ -1,22 +1,40 @@
-from typing import Generator, List, Optional, Union
+from typing import Generator, List
 
 from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
-from core.model_runtime.entities.message_entities import (AssistantPromptMessage, PromptMessage, PromptMessageTool,
-                                                          SystemPromptMessage, UserPromptMessage)
-from core.model_runtime.entities.model_entities import (AIModelEntity, FetchFrom, ModelPropertyKey, ModelType,
-                                                        ParameterRule, ParameterType)
-from core.model_runtime.errors.invoke import (InvokeAuthorizationError, InvokeBadRequestError, InvokeConnectionError,
-                                              InvokeError, InvokeRateLimitError, InvokeServerUnavailableError)
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    PromptMessage,
+    PromptMessageTool,
+    UserPromptMessage,
+)
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+)
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.openllm.llm.openllm_generate import OpenLLMGenerate, OpenLLMGenerateMessage
-from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import (BadRequestError,
-                                                                                    InsufficientAccountBalanceError,
-                                                                                    InternalServerError,
-                                                                                    InvalidAPIKeyError,
-                                                                                    InvalidAuthenticationError,
-                                                                                    RateLimitReachedError)
+from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import (
+    BadRequestError,
+    InsufficientAccountBalanceError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
 
 
 class OpenLLMLargeLanguageModel(LargeLanguageModel):

api/core/model_runtime/model_providers/openllm/llm/openllm_generate.py

@@ -2,15 +2,15 @@ from enum import Enum
 from json import dumps, loads
 from typing import Any, Dict, Generator, List, Union
 
-from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import (BadRequestError,
-                                                                                    InsufficientAccountBalanceError,
-                                                                                    InternalServerError,
-                                                                                    InvalidAPIKeyError,
-                                                                                    InvalidAuthenticationError,
-                                                                                    RateLimitReachedError)
 from requests import Response, post
 from requests.exceptions import ConnectionError, InvalidSchema, MissingSchema
 
+from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import (
+    BadRequestError,
+    InternalServerError,
+    InvalidAuthenticationError,
+)
+
 
 class OpenLLMGenerateMessage:
     class Role(Enum):