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

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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
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api/core/agent/agent/agent_llm_callback.py
+5 -5
View File
@@ -1,5 +1,5 @@
import logging
from typing import List, Optional
from typing import Optional
from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
from core.model_runtime.callbacks.base_callback import Callback
@@ -17,7 +17,7 @@ class AgentLLMCallback(Callback):
def on_before_invoke(self, llm_instance: AIModel, model: str, credentials: dict,
prompt_messages: list[PromptMessage], model_parameters: dict,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
stream: bool = True, user: Optional[str] = None) -> None:
"""
Before invoke callback
@@ -38,7 +38,7 @@ class AgentLLMCallback(Callback):
def on_new_chunk(self, llm_instance: AIModel, chunk: LLMResultChunk, model: str, credentials: dict,
prompt_messages: list[PromptMessage], model_parameters: dict,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
stream: bool = True, user: Optional[str] = None):
"""
On new chunk callback
@@ -58,7 +58,7 @@ class AgentLLMCallback(Callback):
def on_after_invoke(self, llm_instance: AIModel, result: LLMResult, model: str, credentials: dict,
prompt_messages: list[PromptMessage], model_parameters: dict,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
stream: bool = True, user: Optional[str] = None) -> None:
"""
After invoke callback
@@ -80,7 +80,7 @@ class AgentLLMCallback(Callback):
def on_invoke_error(self, llm_instance: AIModel, ex: Exception, model: str, credentials: dict,
prompt_messages: list[PromptMessage], model_parameters: dict,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
stream: bool = True, user: Optional[str] = None) -> None:
"""
Invoke error callback
api/core/agent/agent/calc_token_mixin.py
+2 -2
View File
@@ -1,4 +1,4 @@
from typing import List, cast
from typing import cast
from core.entities.application_entities import ModelConfigEntity
from core.model_runtime.entities.message_entities import PromptMessage
@@ -8,7 +8,7 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
class CalcTokenMixin:
def get_message_rest_tokens(self, model_config: ModelConfigEntity, messages: List[PromptMessage], **kwargs) -> int:
def get_message_rest_tokens(self, model_config: ModelConfigEntity, messages: list[PromptMessage], **kwargs) -> int:
"""
Got the rest tokens available for the model after excluding messages tokens and completion max tokens
api/core/agent/agent/multi_dataset_router_agent.py
+6 -5
View File
@@ -1,4 +1,5 @@
from typing import Any, List, Optional, Sequence, Tuple, Union
from collections.abc import Sequence
from typing import Any, Optional, Union
from langchain.agents import BaseSingleActionAgent, OpenAIFunctionsAgent
from langchain.agents.openai_functions_agent.base import _format_intermediate_steps, _parse_ai_message
@@ -42,7 +43,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -85,7 +86,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
def real_plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -146,7 +147,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
async def aplan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -158,7 +159,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
model_config: ModelConfigEntity,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
),
api/core/agent/agent/openai_function_call.py
+8 -7
View File
@@ -1,4 +1,5 @@
from typing import Any, List, Optional, Sequence, Tuple, Union
from collections.abc import Sequence
from typing import Any, Optional, Union
from langchain.agents import BaseSingleActionAgent, OpenAIFunctionsAgent
from langchain.agents.openai_functions_agent.base import _format_intermediate_steps, _parse_ai_message
@@ -51,7 +52,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
model_config: ModelConfigEntity,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
),
@@ -125,7 +126,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -207,7 +208,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
def return_stopped_response(
self,
early_stopping_method: str,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
**kwargs: Any,
) -> AgentFinish:
try:
@@ -215,7 +216,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
except ValueError:
return AgentFinish({"output": "I'm sorry, I don't know how to respond to that."}, "")
def summarize_messages_if_needed(self, messages: List[PromptMessage], **kwargs) -> List[PromptMessage]:
def summarize_messages_if_needed(self, messages: list[PromptMessage], **kwargs) -> list[PromptMessage]:
# calculate rest tokens and summarize previous function observation messages if rest_tokens < 0
rest_tokens = self.get_message_rest_tokens(
self.model_config,
@@ -264,7 +265,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
return new_messages
def predict_new_summary(
self, messages: List[BaseMessage], existing_summary: str
self, messages: list[BaseMessage], existing_summary: str
) -> str:
new_lines = get_buffer_string(
messages,
@@ -275,7 +276,7 @@ class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, CalcTokenMixi
chain = LLMChain(model_config=self.summary_model_config, prompt=SUMMARY_PROMPT)
return chain.predict(summary=existing_summary, new_lines=new_lines)
def get_num_tokens_from_messages(self, model_config: ModelConfigEntity, messages: List[BaseMessage], **kwargs) -> int:
def get_num_tokens_from_messages(self, model_config: ModelConfigEntity, messages: list[BaseMessage], **kwargs) -> int:
"""Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package.
Official documentation: https://github.com/openai/openai-cookbook/blob/
api/core/agent/agent/structed_multi_dataset_router_agent.py
+9 -8
View File
@@ -1,5 +1,6 @@
import re
from typing import Any, List, Optional, Sequence, Tuple, Union, cast
from collections.abc import Sequence
from typing import Any, Optional, Union, cast
from langchain import BasePromptTemplate, PromptTemplate
from langchain.agents import Agent, AgentOutputParser, StructuredChatAgent
@@ -68,7 +69,7 @@ class StructuredMultiDatasetRouterAgent(StructuredChatAgent):
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -125,8 +126,8 @@ class StructuredMultiDatasetRouterAgent(StructuredChatAgent):
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
input_variables: Optional[list[str]] = None,
memory_prompts: Optional[list[BasePromptTemplate]] = None,
) -> BasePromptTemplate:
tool_strings = []
for tool in tools:
@@ -153,7 +154,7 @@ class StructuredMultiDatasetRouterAgent(StructuredChatAgent):
tools: Sequence[BaseTool],
prefix: str = PREFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
input_variables: Optional[list[str]] = None,
) -> PromptTemplate:
"""Create prompt in the style of the zero shot agent.
@@ -180,7 +181,7 @@ Thought: {agent_scratchpad}
return PromptTemplate(template=template, input_variables=input_variables)
def _construct_scratchpad(
self, intermediate_steps: List[Tuple[AgentAction, str]]
self, intermediate_steps: list[tuple[AgentAction, str]]
) -> str:
agent_scratchpad = ""
for action, observation in intermediate_steps:
@@ -213,8 +214,8 @@ Thought: {agent_scratchpad}
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
input_variables: Optional[list[str]] = None,
memory_prompts: Optional[list[BasePromptTemplate]] = None,
**kwargs: Any,
) -> Agent:
"""Construct an agent from an LLM and tools."""
api/core/agent/agent/structured_chat.py
+11 -10
View File
@@ -1,5 +1,6 @@
import re
from typing import Any, List, Optional, Sequence, Tuple, Union, cast
from collections.abc import Sequence
from typing import Any, Optional, Union, cast
from langchain import BasePromptTemplate, PromptTemplate
from langchain.agents import Agent, AgentOutputParser, StructuredChatAgent
@@ -82,7 +83,7 @@ class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
def plan(
self,
intermediate_steps: List[Tuple[AgentAction, str]],
intermediate_steps: list[tuple[AgentAction, str]],
callbacks: Callbacks = None,
**kwargs: Any,
) -> Union[AgentAction, AgentFinish]:
@@ -127,7 +128,7 @@ class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
return AgentFinish({"output": "I'm sorry, the answer of model is invalid, "
"I don't know how to respond to that."}, "")
def summarize_messages(self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs):
def summarize_messages(self, intermediate_steps: list[tuple[AgentAction, str]], **kwargs):
if len(intermediate_steps) >= 2 and self.summary_model_config:
should_summary_intermediate_steps = intermediate_steps[self.moving_summary_index:-1]
should_summary_messages = [AIMessage(content=observation)
@@ -154,7 +155,7 @@ class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
return self.get_full_inputs([intermediate_steps[-1]], **kwargs)
def predict_new_summary(
self, messages: List[BaseMessage], existing_summary: str
self, messages: list[BaseMessage], existing_summary: str
) -> str:
new_lines = get_buffer_string(
messages,
@@ -173,8 +174,8 @@ class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
input_variables: Optional[list[str]] = None,
memory_prompts: Optional[list[BasePromptTemplate]] = None,
) -> BasePromptTemplate:
tool_strings = []
for tool in tools:
@@ -200,7 +201,7 @@ class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
tools: Sequence[BaseTool],
prefix: str = PREFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
input_variables: Optional[list[str]] = None,
) -> PromptTemplate:
"""Create prompt in the style of the zero shot agent.
@@ -227,7 +228,7 @@ Thought: {agent_scratchpad}
return PromptTemplate(template=template, input_variables=input_variables)
def _construct_scratchpad(
self, intermediate_steps: List[Tuple[AgentAction, str]]
self, intermediate_steps: list[tuple[AgentAction, str]]
) -> str:
agent_scratchpad = ""
for action, observation in intermediate_steps:
@@ -260,8 +261,8 @@ Thought: {agent_scratchpad}
suffix: str = SUFFIX,
human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variables: Optional[List[str]] = None,
memory_prompts: Optional[List[BasePromptTemplate]] = None,
input_variables: Optional[list[str]] = None,
memory_prompts: Optional[list[BasePromptTemplate]] = None,
agent_llm_callback: Optional[AgentLLMCallback] = None,
**kwargs: Any,
) -> Agent: