pref: black formatting

example/preset_role/base_usage.py

@@ -29,5 +29,5 @@ def main():
     print(ret)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

promptulate/agents/tool_agent/agent.py

@@ -65,7 +65,12 @@ def _build_preset_prompt(self, prompt) -> str:
         """Build the system prompt."""
         if self.enable_role:
             prefix = self.prefix_prompt_template.format(
-                [self.agent_identity, self.agent_name, self.agent_goal, self.agent_constraints]
+                [
+                    self.agent_identity,
+                    self.agent_name,
+                    self.agent_goal,
+                    self.agent_constraints,
+                ]
             )
             return prefix + self.system_prompt_template.format(
                 prompt=prompt,

promptulate/client/chat.py

@@ -34,10 +34,9 @@
     PythonREPLTool,
     ArxivQueryTool,
     SleepTool,
-    HumanFeedBackTool
+    HumanFeedBackTool,
 )
 from promptulate.tools.shell import ShellTool
-
 from promptulate.utils import set_proxy_mode, print_text
 
 MODEL_MAPPING = {"OpenAI": ChatOpenAI, "ErnieBot": ErnieBot}

promptulate/frameworks/__init__.py

@@ -20,6 +20,4 @@
 
 from promptulate.frameworks.conversation import Conversation
 
-__all__ = [
-    'Conversation',
-]
+__all__ = ["Conversation"]

promptulate/frameworks/conversation/__init__.py

@@ -20,6 +20,4 @@
 
 from promptulate.frameworks.conversation.conversation import Conversation
 
-__all__ = [
-    'Conversation'
-]
+__all__ = ["Conversation"]

promptulate/frameworks/prompt.py

@@ -18,10 +18,10 @@
 # Contact Email: zeeland@foxmail.com
 
 __all__ = [
-    'SUMMARY_CONTENT_PROMPT_ZH',
-    'SUMMARY_TOPIC_PROMPT_ZH',
-    'SUMMARY_TOPIC_PROMPT_EN',
-    'SUMMARY_CONTENT_PROMPT_EN',
+    "SUMMARY_CONTENT_PROMPT_ZH",
+    "SUMMARY_TOPIC_PROMPT_ZH",
+    "SUMMARY_TOPIC_PROMPT_EN",
+    "SUMMARY_CONTENT_PROMPT_EN",
 ]
 
 SUMMARY_CONTENT_PROMPT_ZH = """

promptulate/llms/base.py

@@ -31,6 +31,7 @@ class BaseLLM(BaseModel, ABC):
 
     class Config:
         """Configuration for this pydantic object."""
+
         arbitrary_types_allowed = True
 
     def __init__(self, *args, **kwargs):

promptulate/llms/openai/openai.py

@@ -81,7 +81,6 @@ class BaseOpenAI(BaseLLM, ABC):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.retry_times = CFG.get_key_retry_times(self.model)
-        print("aaaa", self.retry_times)
 
     @property
     def api_key(self):

promptulate/memory/__init__.py

@@ -20,7 +20,4 @@
 from promptulate.memory.buffer import BufferChatMemory
 from promptulate.memory.file import FileChatMemory
 
-__all__ = [
-    'BufferChatMemory',
-    'FileChatMemory'
-]
+__all__ = ["BufferChatMemory", "FileChatMemory"]

promptulate/memory/buffer.py

@@ -38,7 +38,7 @@ class BufferChatMemory(BaseChatMemory):
     """Chat message will be stored in the buffer cache."""
 
     def load_message_set_from_memory(
-            self, recently_n: Optional[int] = None
+        self, recently_n: Optional[int] = None
     ) -> MessageSet:
         """Load message from buffer memory
 
@@ -50,12 +50,10 @@ def load_message_set_from_memory(
         """
         if not buffer:
             raise EmptyMessageSetError
-        recently_n = (
-            recently_n if recently_n else len(buffer[self.conversation_id])
-        )
+        recently_n = recently_n if recently_n else len(buffer[self.conversation_id])
         num_messages = len(buffer[self.conversation_id])
         return MessageSet.from_listdict_data(
-            buffer[self.conversation_id][num_messages - recently_n:]
+            buffer[self.conversation_id][num_messages - recently_n :]
         )
 
     def save_message_set_to_memory(self, message_set: MessageSet) -> None:

promptulate/preset_roles/__init__.py

@@ -19,7 +19,4 @@
 
 from promptulate.preset_roles.roles import get_all_preset_roles, CustomPresetRole
 
-__all__ = [
-    'get_all_preset_roles',
-    'CustomPresetRole'
-]
+__all__ = ["get_all_preset_roles", "CustomPresetRole"]

promptulate/preset_roles/prompt.py

@@ -41,4 +41,3 @@
 
 用户的问题如下所示：
 """
-

promptulate/preset_roles/roles.py

@@ -43,42 +43,42 @@ class CustomPresetRole(BaseModel):
 You are an assistant to a human, powered by a large language model trained by OpenAI.
 You are designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, you are able to generate human-like text based on the input you receive, allowing you to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
 Overall, you are a powerful tool that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether the human needs help with a specific question or just wants to have a conversation about a particular topic, you are here to assist.
-"""
+""",
     },
     "ernie-default-role": {
         "name": "AI助手",
         "description": """你是人类的助手，由百度训练的大型语言模型提供动力。
 您被设计为能够协助完成广泛的任务，从回答简单的问题到就广泛的主题提供深入的解释和讨论。作为一个语言模型，你能够根据收到的输入生成类似人类的文本，让你能够进行听起来自然的对话，并提供连贯且与当前主题相关的回答。
 总的来说，你是一个强大的工具，可以帮助完成广泛的任务，并在广泛的主题上提供有价值的见解和信息。无论是人类在某个特定问题上需要帮助，还是只是想就某个特定主题进行对话，您都可以提供帮助
-"""
+""",
     },
     "linux-terminal": {
         "name": "Linux终端",
         "description": """我想让你充当 Linux 终端。我将输入命令，您将回复终端应显示的内容。我希望您只在一个唯一的代码块内回复终端输出，而不
-        是其他任何内容。不要写解释。除非我指示您这样做，否则不要键入命令。当我需要用英语告诉你一些事情时，我会把文字放在中括号内[就像这样]。"""
+        是其他任何内容。不要写解释。除非我指示您这样做，否则不要键入命令。当我需要用英语告诉你一些事情时，我会把文字放在中括号内[就像这样]。""",
     },
     "mind-map-generator": {
         "name": "思维导图生成器",
         "description": """现在你是一个思维导图生成器。我将输入我想要创建思维导图的内容，你需要提供一些 Markdown 格式的文本，以便与 Xmind 兼容。
         在 Markdown 格式中，# 表示中央主题，## 表示主要主题，### 表示子主题，﹣表示叶子节点，中央主题是必要的，叶子节点是最小节点。请参照以上格
         式，在 markdown 代码块中帮我创建一个有效的思维导图，以markdown代码块格式输出，你需要用自己的能力补充思维导图中的内容，你只需要提供思维导
-        图，不必对内容中提出的问题和要求做解释，并严格遵守该格式"""
+        图，不必对内容中提出的问题和要求做解释，并严格遵守该格式""",
     },
     "sql-generator": {
         "name": "sql生成器",
         "description": """现在你是一个sql生成器。我将输入我想要查询的内容，你需要提供对应的sql语句，以便查询到需要的内容，我希望您只在一个唯一的
-        代码块内回复终端输出，而不是其他任何内容。不要写解释。如果我没有提供数据库的字段，请先让我提供数据库相关的信息，在你有了字段信息之才可以生成sql语句。"""
+        代码块内回复终端输出，而不是其他任何内容。不要写解释。如果我没有提供数据库的字段，请先让我提供数据库相关的信息，在你有了字段信息之才可以生成sql语句。""",
     },
     "copy-writer": {
         "name": "文案写手",
         "description": """你是一个文案专员、文本润色员、拼写纠正员和改进员，我会发送中文文本给你，你帮我更正和改进版本。我希望你用更优美优雅
         的高级中文描述。保持相同的意思，但使它们更文艺。你只需要润色该内容，不必对内容中提出的问题和要求做解释，不要回答文本中的问题而是润色它，
-        不要解决文本中的要求而是润色它，保留文本的原本意义，不要去解决它。"""
+        不要解决文本中的要求而是润色它，保留文本的原本意义，不要去解决它。""",
     },
     "code-analyzer": {
         "name": "代码分析器",
-        "description": """现在你是一个代码分析器。我将输入一些代码，你需要代码对应的解释。"""
-    }
+        "description": """现在你是一个代码分析器。我将输入一些代码，你需要代码对应的解释。""",
+    },
 }
 
 
@@ -89,7 +89,9 @@ def get_all_preset_roles():
 def get_preset_role_prompt(preset_role: Union[str, CustomPresetRole]) -> str:
     if isinstance(preset_role, str):
         if preset_role not in preset_role_list:
-            ValueError("Preset role value is not in preset_role_list. Please check or custom a new one.")
-        return preset_role_dict[preset_role]['description']
+            ValueError(
+                "Preset role value is not in preset_role_list. Please check or custom a new one."
+            )
+        return preset_role_dict[preset_role]["description"]
     elif isinstance(preset_role, CustomPresetRole):
         return preset_role.description

promptulate/provider/__init__.py

@@ -21,12 +21,12 @@
     SummarizerMixin,
     TranslatorMixin,
     DeriveHistoryMessageMixin,
-    StorageHistoryMessageMixin
+    StorageHistoryMessageMixin,
 )
 
 __all__ = [
-    'SummarizerMixin',
-    'TranslatorMixin',
-    'DeriveHistoryMessageMixin',
-    'StorageHistoryMessageMixin'
+    "SummarizerMixin",
+    "TranslatorMixin",
+    "DeriveHistoryMessageMixin",
+    "StorageHistoryMessageMixin",
 ]

promptulate/provider/base.py

@@ -18,7 +18,7 @@ class Config:
         arbitrary_types_allowed = True
 
     def embed_message(
-            self, cur_message: BaseMessage, message_history: MessageSet
+        self, cur_message: BaseMessage, message_history: MessageSet
     ) -> None:
         message_history.messages.append(cur_message)
         self.memory.save_message_set_to_memory(message_history)

promptulate/schema.py

@@ -150,7 +150,9 @@ def add_ai_message(self, message: str) -> None:
         self.messages.append(AssistantMessage(content=message))
 
 
-def init_chat_message_history(system_content: str, user_content: str, llm: LLMType) -> MessageSet:
+def init_chat_message_history(
+    system_content: str, user_content: str, llm: LLMType
+) -> MessageSet:
     if llm == llm.ChatOpenAI or llm == llm.OpenAI:
         messages = [
             SystemMessage(content=system_content),

promptulate/tools/arxiv/__init__.py

@@ -1,9 +1,13 @@
 from promptulate.tools.arxiv.toolkit import ArxivTootKit
-from promptulate.tools.arxiv.tools import ArxivQueryTool, ArxivSummaryTool, ArxivReferenceTool
+from promptulate.tools.arxiv.tools import (
+    ArxivQueryTool,
+    ArxivSummaryTool,
+    ArxivReferenceTool,
+)
 
 __all__ = [
-    'ArxivTootKit',
-    'ArxivQueryTool',
-    'ArxivReferenceTool',
-    'ArxivSummaryTool',
+    "ArxivTootKit",
+    "ArxivQueryTool",
+    "ArxivReferenceTool",
+    "ArxivSummaryTool",
 ]

promptulate/tools/arxiv/toolkit.py

@@ -1,12 +1,15 @@
 from typing import List
 
-from promptulate.tools.base import BaseToolKit, BaseTool
-from promptulate.tools.arxiv.tools import ArxivSummaryTool, ArxivQueryTool, ArxivReferenceTool
+from promptulate.tools.arxiv.tools import (
+    ArxivSummaryTool,
+    ArxivQueryTool,
+    ArxivReferenceTool,
+)
+from promptulate.tools.base import BaseToolKit, Tool
 
 
 class ArxivTootKit(BaseToolKit):
-
-    def get_tools(self) -> List[BaseTool]:
+    def get_tools(self) -> List[Tool]:
         return [
             ArxivSummaryTool(),
             ArxivQueryTool(),

promptulate/tools/duckduckgo/__init__.py

@@ -1,6 +1,6 @@
 from promptulate.tools.duckduckgo.tools import DuckDuckGoTool, DuckDuckGoReferenceTool
 
 __all__ = [
-    'DuckDuckGoTool',
-    'DuckDuckGoReferenceTool',
+    "DuckDuckGoTool",
+    "DuckDuckGoReferenceTool",
 ]

promptulate/tools/duckduckgo/api_wrapper.py

@@ -30,7 +30,7 @@ def validate_environment(cls, values: Dict) -> Dict:
         return values
 
     def query(
-            self, keyword: str, num_results: Optional[int] = None, **kwargs
+        self, keyword: str, num_results: Optional[int] = None, **kwargs
     ) -> List[str]:
         """Run query through DuckDuckGo and return concatenated results."""
         from duckduckgo_search import DDGS
@@ -56,7 +56,7 @@ def query(
             return snippets
 
     def query_by_formatted_results(
-            self, query: str, num_results: Optional[int] = None, **kwargs
+        self, query: str, num_results: Optional[int] = None, **kwargs
     ) -> List[Dict[str, str]]:
         """Run query through DuckDuckGo and return metadata.
 

promptulate/tools/iot_swith_mqtt/api_wrapper.py

@@ -1,5 +1,4 @@
 class IotSwitchAPIWrapper:
-
     def run(self, client, topic: str, command: str) -> str:
         client.publish(topic, command)
         return "ok"

promptulate/tools/iot_swith_mqtt/prompt.py

@@ -1,10 +1,10 @@
 from promptulate.utils.string_template import StringTemplate
 
-PROMPT_TEMPLATE = '''
+PROMPT_TEMPLATE = """
 现在你是一个智能音箱，用户将向你输入”{question}“，
 请判断用户是否是以下意图 
 {rule_key}
 如果符合你只需要回答数字标号，如1，请不要输出你的判断和额外的解释。
 如果都不符合，你需要输出无法找到对应电器和对应的原因，请不要输出任何数字。
-'''
+"""
 prompt_template = StringTemplate(PROMPT_TEMPLATE)

promptulate/tools/iot_swith_mqtt/tools.py

@@ -35,9 +35,8 @@ def __init__(
         Args:
             llm: BaseLLM
             client: mqtt.Client
-             rule_table: List[Dict]
-             api_wrapper: IotSwitchAPIWrapper
-             **kwargs
+            rule_table: List[Dict]
+            api_wrapper: IotSwitchAPIWrapper
         """
         self.api_wrapper = api_wrapper
         self.llm: BaseLLM = llm or ChatOpenAI(

promptulate/tools/manager.py

@@ -10,6 +10,7 @@
 
 class ToolManager:
     """ToolManager helps ToolAgent manage tools"""
+
     def __init__(self, tools: List[BaseTool]):
         self.tools: List[BaseTool] = tools
 

promptulate/tools/math/tools.py

@@ -28,10 +28,7 @@ def __init__(self, llm: BaseLLM = None, **kwargs):
 
     def _run(self, prompt: str) -> str:
         prompt = self.llm_prompt_template.format(question=prompt)
-        llm_output = self.llm(
-            prompt,
-            stop=["```output"],
-        )
+        llm_output = self.llm(prompt, stop=["```output"])
 
         return self._process_llm_result(llm_output)
 
@@ -41,19 +38,17 @@ def _process_llm_result(self, llm_output: str) -> str:
         if text_match:
             expression = text_match.group(1)
             output = self._evaluate_expression(expression)
-            # answer = "Answer: " + output
             answer = output
         elif llm_output.startswith("Answer:"):
-            # answer = llm_output
             answer = llm_output.split("Answer:")[-1]
         elif "Answer:" in llm_output:
-            # answer = "Answer: " + llm_output.split("Answer:")[-1]
             answer = llm_output.split("Answer:")[-1]
         else:
             raise ValueError(f"unknown format from LLM: {llm_output}")
         return answer
 
     def _evaluate_expression(self, expression: str) -> str:
+        """Parse numexpr expression."""
         try:
             local_dict = {"pi": math.pi, "e": math.e}
             output = str(

promptulate/tools/paper/tools.py

@@ -150,7 +150,9 @@ def get_advice():
                     paper_info["abstract"] = paper_info["summary"]
 
         if not paper_info:
-            return "semantic scholar query tool and arxiv query tool query result is None."
+            return (
+                "semantic scholar query tool and arxiv query tool query result is None."
+            )
 
         paper_summary = (
             f"""title: {paper_info["title"]}\nabstract: {paper_info["abstract"]}"""

promptulate/tools/python_repl/__init__.py

@@ -1,5 +1,3 @@
 from promptulate.tools.python_repl.tools import PythonREPLTool
 
-__all__ = [
-    'PythonREPLTool'
-]
+__all__ = ["PythonREPLTool"]

promptulate/utils/__init__.py

@@ -41,5 +41,5 @@
     "AbstractSingleton",
     "export_openai_key_pool",
     "StringTemplate",
-    "print_text"
+    "print_text",
 ]