hz/ebiz-dify-ai
1
0
Fork 0
mirror of http://112.124.100.131/huang.ze/ebiz-dify-ai.git synced 2025-12-15 13:56:53 +08:00
Code Issues Packages Projects Releases Wiki Activity

chore: apply ruff's pyupgrade linter rules to modernize Python code with targeted version (#2419)

Browse Source
This commit is contained in:
Bowen Liang
2024-02-09 15:21:33 +08:00
committed by GitHub
parent 589099a005
commit 063191889d
246 changed files with 912 additions and 937 deletions
Download Patch File Download Diff File Expand all files Collapse all files

21
api/core/features/assistant_cot_runner.py
View File

@@ -1,6 +1,7 @@
import json
import re
from typing import Dict, Generator, List, Literal, Union
from collections.abc import Generator
from typing import Literal, Union
from core.application_queue_manager import PublishFrom
from core.entities.application_entities import AgentPromptEntity, AgentScratchpadUnit
@@ -29,7 +30,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
def run(self, conversation: Conversation,
message: Message,
query: str,
inputs: Dict[str, str],
inputs: dict[str, str],
) -> Union[Generator, LLMResult]:
"""
Run Cot agent application
@@ -37,7 +38,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
app_orchestration_config = self.app_orchestration_config
self._repack_app_orchestration_config(app_orchestration_config)
agent_scratchpad: List[AgentScratchpadUnit] = []
agent_scratchpad: list[AgentScratchpadUnit] = []
# check model mode
if self.app_orchestration_config.model_config.mode == "completion":
@@ -56,7 +57,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
prompt_messages = self.history_prompt_messages
# convert tools into ModelRuntime Tool format
prompt_messages_tools: List[PromptMessageTool] = []
prompt_messages_tools: list[PromptMessageTool] = []
tool_instances = {}
for tool in self.app_orchestration_config.agent.tools if self.app_orchestration_config.agent else []:
try:
@@ -83,7 +84,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
}
final_answer = ''
def increase_usage(final_llm_usage_dict: Dict[str, LLMUsage], usage: LLMUsage):
def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage):
if not final_llm_usage_dict['usage']:
final_llm_usage_dict['usage'] = usage
else:
@@ -493,7 +494,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
if not next_iteration.find("{{observation}}") >= 0:
raise ValueError("{{observation}} is required in next_iteration")
def _convert_scratchpad_list_to_str(self, agent_scratchpad: List[AgentScratchpadUnit]) -> str:
def _convert_scratchpad_list_to_str(self, agent_scratchpad: list[AgentScratchpadUnit]) -> str:
"""
convert agent scratchpad list to str
"""
@@ -506,13 +507,13 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
return result
def _organize_cot_prompt_messages(self, mode: Literal["completion", "chat"],
prompt_messages: List[PromptMessage],
tools: List[PromptMessageTool],
agent_scratchpad: List[AgentScratchpadUnit],
prompt_messages: list[PromptMessage],
tools: list[PromptMessageTool],
agent_scratchpad: list[AgentScratchpadUnit],
agent_prompt_message: AgentPromptEntity,
instruction: str,
input: str,
) -> List[PromptMessage]:
) -> list[PromptMessage]:
"""
organize chain of thought prompt messages, a standard prompt message is like:
Respond to the human as helpfully and accurately as possible.