Merge pull request #502 from iorisa/refactor/pre-commit_shenquan

refactor: pre-commit run --all-files

examples/agent_creator.py

@@ -1,22 +1,22 @@
-'''
+"""
 Filename: MetaGPT/examples/agent_creator.py
 Created Date: Tuesday, September 12th 2023, 3:28:37 pm
 Author: garylin2099
-'''
+"""
 import re
 
-from metagpt.const import PROJECT_ROOT, WORKSPACE_ROOT
 from metagpt.actions import Action
+from metagpt.const import PROJECT_ROOT, WORKSPACE_ROOT
+from metagpt.logs import logger
 from metagpt.roles import Role
 from metagpt.schema import Message
-from metagpt.logs import logger
 
 with open(PROJECT_ROOT / "examples/build_customized_agent.py", "r") as f:
     # use official example script to guide AgentCreator
     MULTI_ACTION_AGENT_CODE_EXAMPLE = f.read()
 
-class CreateAgent(Action):
 
+class CreateAgent(Action):
     PROMPT_TEMPLATE = """
     ### BACKGROUND
     You are using an agent framework called metagpt to write agents capable of different actions,
@@ -34,7 +34,6 @@ class CreateAgent(Action):
     """
 
     async def run(self, example: str, instruction: str):
-
         prompt = self.PROMPT_TEMPLATE.format(example=example, instruction=instruction)
         # logger.info(prompt)
 
@@ -46,13 +45,14 @@ class CreateAgent(Action):
 
     @staticmethod
     def parse_code(rsp):
-        pattern = r'```python(.*)```'
+        pattern = r"```python(.*)```"
         match = re.search(pattern, rsp, re.DOTALL)
         code_text = match.group(1) if match else ""
         with open(WORKSPACE_ROOT / "agent_created_agent.py", "w") as f:
             f.write(code_text)
         return code_text
 
+
 class AgentCreator(Role):
     def __init__(
         self,
@@ -76,11 +76,11 @@ class AgentCreator(Role):
 
         return msg
 
+
 if __name__ == "__main__":
     import asyncio
 
     async def main():
-
         agent_template = MULTI_ACTION_AGENT_CODE_EXAMPLE
 
         creator = AgentCreator(agent_template=agent_template)

examples/build_customized_agent.py

@@ -1,21 +1,21 @@
-'''
+"""
 Filename: MetaGPT/examples/build_customized_agent.py
 Created Date: Tuesday, September 19th 2023, 6:52:25 pm
 Author: garylin2099
-'''
+"""
+import asyncio
 import re
 import subprocess
-import asyncio
 
 import fire
 
 from metagpt.actions import Action
+from metagpt.logs import logger
 from metagpt.roles import Role
 from metagpt.schema import Message
-from metagpt.logs import logger
+
 
 class SimpleWriteCode(Action):
-
     PROMPT_TEMPLATE = """
     Write a python function that can {instruction} and provide two runnnable test cases.
     Return ```python your_code_here ``` with NO other texts,
@@ -35,7 +35,6 @@ class SimpleWriteCode(Action):
         super().__init__(name, context, llm)
 
     async def run(self, instruction: str):
-
         prompt = self.PROMPT_TEMPLATE.format(instruction=instruction)
 
         rsp = await self._aask(prompt)
@@ -46,11 +45,12 @@ class SimpleWriteCode(Action):
 
     @staticmethod
     def parse_code(rsp):
-        pattern = r'```python(.*)```'
+        pattern = r"```python(.*)```"
         match = re.search(pattern, rsp, re.DOTALL)
         code_text = match.group(1) if match else rsp
         return code_text
 
+
 class SimpleRunCode(Action):
     def __init__(self, name="SimpleRunCode", context=None, llm=None):
         super().__init__(name, context, llm)
@@ -61,6 +61,7 @@ class SimpleRunCode(Action):
         logger.info(f"{code_result=}")
         return code_result
 
+
 class SimpleCoder(Role):
     def __init__(
         self,
@@ -75,7 +76,7 @@ class SimpleCoder(Role):
         logger.info(f"{self._setting}: ready to {self._rc.todo}")
         todo = self._rc.todo
 
-        msg = self._rc.memory.get()[-1] # retrieve the latest memory
+        msg = self._rc.memory.get()[-1]  # retrieve the latest memory
         instruction = msg.content
 
         code_text = await SimpleWriteCode().run(instruction)
@@ -83,6 +84,7 @@ class SimpleCoder(Role):
 
         return msg
 
+
 class RunnableCoder(Role):
     def __init__(
         self,
@@ -128,6 +130,7 @@ class RunnableCoder(Role):
             await self._act()
         return Message(content="All job done", role=self.profile)
 
+
 def main(msg="write a function that calculates the sum of a list"):
     # role = SimpleCoder()
     role = RunnableCoder()
@@ -135,5 +138,6 @@ def main(msg="write a function that calculates the sum of a list"):
     result = asyncio.run(role.run(msg))
     logger.info(result)
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     fire.Fire(main)

examples/debate.py

@@ -1,17 +1,19 @@
-'''
+"""
 Filename: MetaGPT/examples/debate.py
 Created Date: Tuesday, September 19th 2023, 6:52:25 pm
 Author: garylin2099
-'''
+"""
 import asyncio
 import platform
+
 import fire
 
-from metagpt.software_company import SoftwareCompany
 from metagpt.actions import Action, BossRequirement
+from metagpt.logs import logger
 from metagpt.roles import Role
 from metagpt.schema import Message
-from metagpt.logs import logger
+from metagpt.software_company import SoftwareCompany
+
 
 class ShoutOut(Action):
     """Action: Shout out loudly in a debate (quarrel)"""
@@ -31,7 +33,6 @@ class ShoutOut(Action):
         super().__init__(name, context, llm)
 
     async def run(self, context: str, name: str, opponent_name: str):
-
         prompt = self.PROMPT_TEMPLATE.format(context=context, name=name, opponent_name=opponent_name)
         # logger.info(prompt)
 
@@ -39,6 +40,7 @@ class ShoutOut(Action):
 
         return rsp
 
+
 class Trump(Role):
     def __init__(
         self,
@@ -55,7 +57,7 @@ class Trump(Role):
     async def _observe(self) -> int:
         await super()._observe()
         # accept messages sent (from opponent) to self, disregard own messages from the last round
-        self._rc.news = [msg for msg in self._rc.news if msg.send_to == self.name]  
+        self._rc.news = [msg for msg in self._rc.news if msg.send_to == self.name]
         return len(self._rc.news)
 
     async def _act(self) -> Message:
@@ -79,6 +81,7 @@ class Trump(Role):
 
         return msg
 
+
 class Biden(Role):
     def __init__(
         self,
@@ -120,10 +123,12 @@ class Biden(Role):
 
         return msg
 
-async def startup(idea: str, investment: float = 3.0, n_round: int = 5,
-                  code_review: bool = False, run_tests: bool = False):
+
+async def startup(
+    idea: str, investment: float = 3.0, n_round: int = 5, code_review: bool = False, run_tests: bool = False
+):
     """We reuse the startup paradigm for roles to interact with each other.
-    Now we run a startup of presidents and watch they quarrel. :) """
+    Now we run a startup of presidents and watch they quarrel. :)"""
     company = SoftwareCompany()
     company.hire([Biden(), Trump()])
     company.invest(investment)
@@ -133,7 +138,7 @@ async def startup(idea: str, investment: float = 3.0, n_round: int = 5,
 
 def main(idea: str, investment: float = 3.0, n_round: int = 10):
     """
-    :param idea: Debate topic, such as "Topic: The U.S. should commit more in climate change fighting" 
+    :param idea: Debate topic, such as "Topic: The U.S. should commit more in climate change fighting"
                  or "Trump: Climate change is a hoax"
     :param investment: contribute a certain dollar amount to watch the debate
     :param n_round: maximum rounds of the debate
@@ -144,5 +149,5 @@ def main(idea: str, investment: float = 3.0, n_round: int = 10):
     asyncio.run(startup(idea, investment, n_round))
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     fire.Fire(main)

examples/invoice_ocr.py

@@ -19,19 +19,15 @@ async def main():
         Path("../tests/data/invoices/invoice-1.pdf"),
         Path("../tests/data/invoices/invoice-2.png"),
         Path("../tests/data/invoices/invoice-3.jpg"),
-        Path("../tests/data/invoices/invoice-4.zip")
+        Path("../tests/data/invoices/invoice-4.zip"),
     ]
     # The absolute path of the file
     absolute_file_paths = [Path.cwd() / path for path in relative_paths]
 
     for path in absolute_file_paths:
         role = InvoiceOCRAssistant()
-        await role.run(Message(
-            content="Invoicing date",
-            instruct_content={"file_path": path}
-        ))
+        await role.run(Message(content="Invoicing date", instruct_content={"file_path": path}))
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(main())
-

examples/llm_hello_world.py

@@ -14,11 +14,11 @@ from metagpt.logs import logger
 async def main():
     llm = LLM()
     claude = Claude()
-    logger.info(await claude.aask('你好，请进行自我介绍'))
-    logger.info(await llm.aask('hello world'))
-    logger.info(await llm.aask_batch(['hi', 'write python hello world.']))
+    logger.info(await claude.aask("你好，请进行自我介绍"))
+    logger.info(await llm.aask("hello world"))
+    logger.info(await llm.aask_batch(["hi", "write python hello world."]))
 
-    hello_msg = [{'role': 'user', 'content': 'count from 1 to 10. split by newline.'}]
+    hello_msg = [{"role": "user", "content": "count from 1 to 10. split by newline."}]
     logger.info(await llm.acompletion(hello_msg))
     logger.info(await llm.acompletion_batch([hello_msg]))
     logger.info(await llm.acompletion_batch_text([hello_msg]))
@@ -27,5 +27,5 @@ async def main():
     await llm.acompletion_text(hello_msg, stream=True)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(main())

examples/research.py

@@ -12,5 +12,5 @@ async def main():
     print(f"save report to {RESEARCH_PATH / f'{topic}.md'}.")
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(main())

examples/search_google.py

@@ -15,5 +15,5 @@ async def main():
     await Searcher().run("What are some good sun protection products?")
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(main())

examples/search_kb.py

@@ -12,7 +12,7 @@ from metagpt.roles import Sales
 
 
 async def search():
-    store = FaissStore(DATA_PATH / 'example.json')
+    store = FaissStore(DATA_PATH / "example.json")
     role = Sales(profile="Sales", store=store)
 
     queries = ["Which facial cleanser is good for oily skin?", "Is L'Oreal good to use?"]
@@ -22,5 +22,5 @@ async def search():
         logger.info(result)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(search())

examples/search_with_specific_engine.py

@@ -6,11 +6,12 @@ from metagpt.tools import SearchEngineType
 
 async def main():
     # Serper API
-    #await Searcher(engine = SearchEngineType.SERPER_GOOGLE).run(["What are some good sun protection products?","What are some of the best beaches?"])
+    # await Searcher(engine = SearchEngineType.SERPER_GOOGLE).run(["What are some good sun protection products?","What are some of the best beaches?"])
     # SerpAPI
-    #await Searcher(engine=SearchEngineType.SERPAPI_GOOGLE).run("What are the best ski brands for skiers?")
+    # await Searcher(engine=SearchEngineType.SERPAPI_GOOGLE).run("What are the best ski brands for skiers?")
     # Google API
     await Searcher(engine=SearchEngineType.DIRECT_GOOGLE).run("What are the most interesting human facts?")
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     asyncio.run(main())

examples/use_off_the_shelf_agent.py

@@ -1,12 +1,13 @@
-'''
+"""
 Filename: MetaGPT/examples/use_off_the_shelf_agent.py
 Created Date: Tuesday, September 19th 2023, 6:52:25 pm
 Author: garylin2099
-'''
+"""
 import asyncio
 
-from metagpt.roles.product_manager import ProductManager
 from metagpt.logs import logger
+from metagpt.roles.product_manager import ProductManager
+
 
 async def main():
     msg = "Write a PRD for a snake game"
@@ -14,5 +15,6 @@ async def main():
     result = await role.run(msg)
     logger.info(result.content[:100])
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     asyncio.run(main())

examples/write_tutorial.py

@@ -16,6 +16,5 @@ async def main():
     await role.run(topic)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(main())
-

metagpt/actions/action_output.py

@@ -23,10 +23,10 @@ class ActionOutput:
     def create_model_class(cls, class_name: str, mapping: Dict[str, Type]):
         new_class = create_model(class_name, **mapping)
 
-        @validator('*', allow_reuse=True)
+        @validator("*", allow_reuse=True)
         def check_name(v, field):
             if field.name not in mapping.keys():
-                raise ValueError(f'Unrecognized block: {field.name}')
+                raise ValueError(f"Unrecognized block: {field.name}")
             return v
 
         @root_validator(pre=True, allow_reuse=True)
@@ -34,10 +34,9 @@ class ActionOutput:
             required_fields = set(mapping.keys())
             missing_fields = required_fields - set(values.keys())
             if missing_fields:
-                raise ValueError(f'Missing fields: {missing_fields}')
+                raise ValueError(f"Missing fields: {missing_fields}")
             return values
 
         new_class.__validator_check_name = classmethod(check_name)
         new_class.__root_validator_check_missing_fields = classmethod(check_missing_fields)
         return new_class
-    

metagpt/actions/add_requirement.py

@@ -10,5 +10,6 @@ from metagpt.actions import Action
 
 class BossRequirement(Action):
     """Boss Requirement without any implementation details"""
+
     async def run(self, *args, **kwargs):
         raise NotImplementedError

metagpt/actions/azure_tts.py

@@ -18,16 +18,13 @@ class AzureTTS(Action):
 
     # Parameters reference: https://learn.microsoft.com/zh-cn/azure/cognitive-services/speech-service/language-support?tabs=tts#voice-styles-and-roles
     def synthesize_speech(self, lang, voice, role, text, output_file):
-        subscription_key = self.config.get('AZURE_TTS_SUBSCRIPTION_KEY')
-        region = self.config.get('AZURE_TTS_REGION')
-        speech_config = SpeechConfig(
-            subscription=subscription_key, region=region)
+        subscription_key = self.config.get("AZURE_TTS_SUBSCRIPTION_KEY")
+        region = self.config.get("AZURE_TTS_REGION")
+        speech_config = SpeechConfig(subscription=subscription_key, region=region)
 
         speech_config.speech_synthesis_voice_name = voice
         audio_config = AudioConfig(filename=output_file)
-        synthesizer = SpeechSynthesizer(
-            speech_config=speech_config,
-            audio_config=audio_config)
+        synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
 
         # if voice=="zh-CN-YunxiNeural":
         ssml_string = f"""
@@ -45,9 +42,4 @@ class AzureTTS(Action):
 
 if __name__ == "__main__":
     azure_tts = AzureTTS("azure_tts")
-    azure_tts.synthesize_speech(
-        "zh-CN",
-        "zh-CN-YunxiNeural",
-        "Boy",
-        "Hello, I am Kaka",
-        "output.wav")
+    azure_tts.synthesize_speech("zh-CN", "zh-CN-YunxiNeural", "Boy", "Hello, I am Kaka", "output.wav")

metagpt/actions/clone_function.py

@@ -1,5 +1,5 @@
-from pathlib import Path
 import traceback
+from pathlib import Path
 
 from metagpt.actions.write_code import WriteCode
 from metagpt.logs import logger
@@ -42,7 +42,7 @@ class CloneFunction(WriteCode):
         prompt = CLONE_PROMPT.format(source_code=source_code, template_func=template_func)
         logger.info(f"query for CloneFunction: \n {prompt}")
         code = await self.write_code(prompt)
-        logger.info(f'CloneFunction code is \n {highlight(code)}')
+        logger.info(f"CloneFunction code is \n {highlight(code)}")
         return code
 
 
@@ -61,5 +61,5 @@ def run_function_script(code_script_path: str, func_name: str, *args, **kwargs):
     """Run function code from script."""
     if isinstance(code_script_path, str):
         code_path = Path(code_script_path)
-    code = code_path.read_text(encoding='utf-8')
+    code = code_path.read_text(encoding="utf-8")
     return run_function_code(code, func_name, *args, **kwargs)

metagpt/actions/debug_error.py

@@ -7,8 +7,8 @@
 """
 import re
 
-from metagpt.logs import logger
 from metagpt.actions.action import Action
+from metagpt.logs import logger
 from metagpt.utils.common import CodeParser
 
 PROMPT_TEMPLATE = """
@@ -24,6 +24,8 @@ The message is as follows:
 Now you should start rewriting the code:
 ## file name of the code to rewrite: Write code with triple quoto. Do your best to implement THIS IN ONLY ONE FILE.
 """
+
+
 class DebugError(Action):
     def __init__(self, name="DebugError", context=None, llm=None):
         super().__init__(name, context, llm)
@@ -33,17 +35,17 @@ class DebugError(Action):
     #              f"\n\n{error}\n\nPlease try to fix the error in this code."
     #     fixed_code = await self._aask(prompt)
     #     return fixed_code
-    
+
     async def run(self, context):
         if "PASS" in context:
             return "", "the original code works fine, no need to debug"
-        
+
         file_name = re.search("## File To Rewrite:\s*(.+\\.py)", context).group(1)
 
         logger.info(f"Debug and rewrite {file_name}")
 
         prompt = PROMPT_TEMPLATE.format(context=context)
-        
+
         rsp = await self._aask(prompt)
 
         code = CodeParser.parse_code(block="", text=rsp)

metagpt/actions/design_api_review.py

@@ -13,10 +13,11 @@ class DesignReview(Action):
         super().__init__(name, context, llm)
 
     async def run(self, prd, api_design):
-        prompt = f"Here is the Product Requirement Document (PRD):\n\n{prd}\n\nHere is the list of APIs designed " \
-                 f"based on this PRD:\n\n{api_design}\n\nPlease review whether this API design meets the requirements" \
-                 f" of the PRD, and whether it complies with good design practices."
+        prompt = (
+            f"Here is the Product Requirement Document (PRD):\n\n{prd}\n\nHere is the list of APIs designed "
+            f"based on this PRD:\n\n{api_design}\n\nPlease review whether this API design meets the requirements"
+            f" of the PRD, and whether it complies with good design practices."
+        )
 
         api_review = await self._aask(prompt)
         return api_review
-    

metagpt/actions/design_filenames.py

@@ -17,8 +17,10 @@ Do not add any other explanations, just return a Python string list."""
 class DesignFilenames(Action):
     def __init__(self, name, context=None, llm=None):
         super().__init__(name, context, llm)
-        self.desc = "Based on the PRD, consider system design, and carry out the basic design of the corresponding " \
-                    "APIs, data structures, and database tables. Please give your design, feedback clearly and in detail."
+        self.desc = (
+            "Based on the PRD, consider system design, and carry out the basic design of the corresponding "
+            "APIs, data structures, and database tables. Please give your design, feedback clearly and in detail."
+        )
 
     async def run(self, prd):
         prompt = f"The following is the Product Requirement Document (PRD):\n\n{prd}\n\n{PROMPT}"
@@ -26,4 +28,3 @@ class DesignFilenames(Action):
         logger.debug(prompt)
         logger.debug(design_filenames)
         return design_filenames
-    

metagpt/actions/detail_mining.py

@@ -6,7 +6,6 @@
 @File    : detail_mining.py
 """
 from metagpt.actions import Action, ActionOutput
-from metagpt.logs import logger
 
 PROMPT_TEMPLATE = """
 ##TOPIC
@@ -41,8 +40,8 @@ OUTPUT_MAPPING = {
 
 
 class DetailMining(Action):
-    """This class allows LLM to further mine noteworthy details based on specific "##TOPIC"(discussion topic) and "##RECORD" (discussion records), thereby deepening the discussion.
-    """
+    """This class allows LLM to further mine noteworthy details based on specific "##TOPIC"(discussion topic) and "##RECORD" (discussion records), thereby deepening the discussion."""
+
     def __init__(self, name="", context=None, llm=None):
         super().__init__(name, context, llm)
 

metagpt/actions/invoice_ocr.py

@@ -10,8 +10,8 @@
 
 import os
 import zipfile
-from pathlib import Path
 from datetime import datetime
+from pathlib import Path
 
 import pandas as pd
 from paddleocr import PaddleOCR
@@ -19,7 +19,10 @@ from paddleocr import PaddleOCR
 from metagpt.actions import Action
 from metagpt.const import INVOICE_OCR_TABLE_PATH
 from metagpt.logs import logger
-from metagpt.prompts.invoice_ocr import EXTRACT_OCR_MAIN_INFO_PROMPT, REPLY_OCR_QUESTION_PROMPT
+from metagpt.prompts.invoice_ocr import (
+    EXTRACT_OCR_MAIN_INFO_PROMPT,
+    REPLY_OCR_QUESTION_PROMPT,
+)
 from metagpt.utils.common import OutputParser
 from metagpt.utils.file import File
 
@@ -183,4 +186,3 @@ class ReplyQuestion(Action):
         prompt = REPLY_OCR_QUESTION_PROMPT.format(query=query, ocr_result=ocr_result, language=self.language)
         resp = await self._aask(prompt=prompt)
         return resp
-

metagpt/actions/prepare_interview.py

@@ -38,4 +38,3 @@ class PrepareInterview(Action):
         prompt = PROMPT_TEMPLATE.format(context=context)
         question_list = await self._aask_v1(prompt)
         return question_list
-

metagpt/actions/research.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import asyncio
-import json
 from typing import Callable
 
 from pydantic import parse_obj_as
@@ -49,7 +48,7 @@ based on the link credibility. If two results have equal credibility, prioritize
 ranked results' indices in JSON format, like [0, 1, 3, 4, ...], without including other words.
 """
 
-WEB_BROWSE_AND_SUMMARIZE_PROMPT = '''### Requirements
+WEB_BROWSE_AND_SUMMARIZE_PROMPT = """### Requirements
 1. Utilize the text in the "Reference Information" section to respond to the question "{query}".
 2. If the question cannot be directly answered using the text, but the text is related to the research topic, please provide \
 a comprehensive summary of the text.
@@ -58,10 +57,10 @@ a comprehensive summary of the text.
 
 ### Reference Information
 {content}
-'''
+"""
 
 
-CONDUCT_RESEARCH_PROMPT = '''### Reference Information
+CONDUCT_RESEARCH_PROMPT = """### Reference Information
 {content}
 
 ### Requirements
@@ -73,11 +72,12 @@ above. The report must meet the following requirements:
 - Present data and findings in an intuitive manner, utilizing feature comparative tables, if applicable.
 - The report should have a minimum word count of 2,000 and be formatted with Markdown syntax following APA style guidelines.
 - Include all source URLs in APA format at the end of the report.
-'''
+"""
 
 
 class CollectLinks(Action):
     """Action class to collect links from a search engine."""
+
     def __init__(
         self,
         name: str = "",
@@ -114,19 +114,24 @@ class CollectLinks(Action):
             keywords = OutputParser.extract_struct(keywords, list)
             keywords = parse_obj_as(list[str], keywords)
         except Exception as e:
-            logger.exception(f"fail to get keywords related to the research topic \"{topic}\" for {e}")
+            logger.exception(f'fail to get keywords related to the research topic "{topic}" for {e}')
             keywords = [topic]
         results = await asyncio.gather(*(self.search_engine.run(i, as_string=False) for i in keywords))
 
         def gen_msg():
             while True:
-                search_results = "\n".join(f"#### Keyword: {i}\n Search Result: {j}\n" for (i, j) in zip(keywords, results))
-                prompt = SUMMARIZE_SEARCH_PROMPT.format(decomposition_nums=decomposition_nums, search_results=search_results)
+                search_results = "\n".join(
+                    f"#### Keyword: {i}\n Search Result: {j}\n" for (i, j) in zip(keywords, results)
+                )
+                prompt = SUMMARIZE_SEARCH_PROMPT.format(
+                    decomposition_nums=decomposition_nums, search_results=search_results
+                )
                 yield prompt
                 remove = max(results, key=len)
                 remove.pop()
                 if len(remove) == 0:
                     break
+
         prompt = reduce_message_length(gen_msg(), self.llm.model, system_text, CONFIG.max_tokens_rsp)
         logger.debug(prompt)
         queries = await self._aask(prompt, [system_text])
@@ -172,6 +177,7 @@ class CollectLinks(Action):
 
 class WebBrowseAndSummarize(Action):
     """Action class to explore the web and provide summaries of articles and webpages."""
+
     def __init__(
         self,
         *args,
@@ -214,7 +220,9 @@ class WebBrowseAndSummarize(Action):
         for u, content in zip([url, *urls], contents):
             content = content.inner_text
             chunk_summaries = []
-            for prompt in generate_prompt_chunk(content, prompt_template, self.llm.model, system_text, CONFIG.max_tokens_rsp):
+            for prompt in generate_prompt_chunk(
+                content, prompt_template, self.llm.model, system_text, CONFIG.max_tokens_rsp
+            ):
                 logger.debug(prompt)
                 summary = await self._aask(prompt, [system_text])
                 if summary == "Not relevant.":
@@ -238,6 +246,7 @@ class WebBrowseAndSummarize(Action):
 
 class ConductResearch(Action):
     """Action class to conduct research and generate a research report."""
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         if CONFIG.model_for_researcher_report:

metagpt/actions/search_and_summarize.py

@@ -140,4 +140,3 @@ class SearchAndSummarize(Action):
         logger.debug(prompt)
         logger.debug(result)
         return result
-    

metagpt/actions/write_code.py

@@ -5,13 +5,14 @@
 @Author  : alexanderwu
 @File    : write_code.py
 """
+from tenacity import retry, stop_after_attempt, wait_fixed
+
 from metagpt.actions import WriteDesign
 from metagpt.actions.action import Action
 from metagpt.const import WORKSPACE_ROOT
 from metagpt.logs import logger
 from metagpt.schema import Message
 from metagpt.utils.common import CodeParser
-from tenacity import retry, stop_after_attempt, wait_fixed
 
 PROMPT_TEMPLATE = """
 NOTICE
@@ -74,9 +75,8 @@ class WriteCode(Action):
 
     async def run(self, context, filename):
         prompt = PROMPT_TEMPLATE.format(context=context, filename=filename)
-        logger.info(f'Writing {filename}..')
+        logger.info(f"Writing {filename}..")
         code = await self.write_code(prompt)
         # code_rsp = await self._aask_v1(prompt, "code_rsp", OUTPUT_MAPPING)
         # self._save(context, filename, code)
         return code
-    

metagpt/actions/write_code_review.py

@@ -6,11 +6,12 @@
 @File    : write_code_review.py
 """
 
+from tenacity import retry, stop_after_attempt, wait_fixed
+
 from metagpt.actions.action import Action
 from metagpt.logs import logger
 from metagpt.schema import Message
 from metagpt.utils.common import CodeParser
-from tenacity import retry, stop_after_attempt, wait_fixed
 
 PROMPT_TEMPLATE = """
 NOTICE
@@ -74,9 +75,8 @@ class WriteCodeReview(Action):
     async def run(self, context, code, filename):
         format_example = FORMAT_EXAMPLE.format(filename=filename)
         prompt = PROMPT_TEMPLATE.format(context=context, code=code, filename=filename, format_example=format_example)
-        logger.info(f'Code review {filename}..')
+        logger.info(f"Code review {filename}..")
         code = await self.write_code(prompt)
         # code_rsp = await self._aask_v1(prompt, "code_rsp", OUTPUT_MAPPING)
         # self._save(context, filename, code)
         return code
-    

metagpt/actions/write_docstring.py

@@ -28,7 +28,7 @@ from metagpt.actions.action import Action
 from metagpt.utils.common import OutputParser
 from metagpt.utils.pycst import merge_docstring
 
-PYTHON_DOCSTRING_SYSTEM = '''### Requirements
+PYTHON_DOCSTRING_SYSTEM = """### Requirements
 1. Add docstrings to the given code following the {style} style.
 2. Replace the function body with an Ellipsis object(...) to reduce output.
 3. If the types are already annotated, there is no need to include them in the docstring.
@@ -48,7 +48,7 @@ class ExampleError(Exception):
 ```python
 {example}
 ```
-'''
+"""
 
 # https://www.sphinx-doc.org/en/master/usage/extensions/napoleon.html
 
@@ -162,7 +162,8 @@ class WriteDocstring(Action):
         self.desc = "Write docstring for code."
 
     async def run(
-        self, code: str,
+        self,
+        code: str,
         system_text: str = PYTHON_DOCSTRING_SYSTEM,
         style: Literal["google", "numpy", "sphinx"] = "google",
     ) -> str:

metagpt/actions/write_prd_review.py

@@ -25,4 +25,3 @@ class WritePRDReview(Action):
         prompt = self.prd_review_prompt_template.format(prd=self.prd)
         review = await self._aask(prompt)
         return review
-    

metagpt/actions/write_tutorial.py

@@ -10,7 +10,7 @@
 from typing import Dict
 
 from metagpt.actions import Action
-from metagpt.prompts.tutorial_assistant import DIRECTORY_PROMPT, CONTENT_PROMPT
+from metagpt.prompts.tutorial_assistant import CONTENT_PROMPT, DIRECTORY_PROMPT
 from metagpt.utils.common import OutputParser
 
 
@@ -65,4 +65,3 @@ class WriteContent(Action):
         """
         prompt = CONTENT_PROMPT.format(topic=topic, language=self.language, directory=self.directory)
         return await self._aask(prompt=prompt)
-

metagpt/config.py

@@ -46,7 +46,7 @@ class Config(metaclass=Singleton):
         self.openai_api_key = self._get("OPENAI_API_KEY")
         self.anthropic_api_key = self._get("Anthropic_API_KEY")
         if (not self.openai_api_key or "YOUR_API_KEY" == self.openai_api_key) and (
-                not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key
+            not self.anthropic_api_key or "YOUR_API_KEY" == self.anthropic_api_key
         ):
             raise NotConfiguredException("Set OPENAI_API_KEY or Anthropic_API_KEY first")
         self.openai_api_base = self._get("OPENAI_API_BASE")

metagpt/document_store/base_store.py

@@ -41,7 +41,7 @@ class LocalStore(BaseStore, ABC):
             self.store = self.write()
 
     def _get_index_and_store_fname(self):
-        fname = self.raw_data.name.split('.')[0]
+        fname = self.raw_data.name.split(".")[0]
         index_file = self.cache_dir / f"{fname}.index"
         store_file = self.cache_dir / f"{fname}.pkl"
         return index_file, store_file
@@ -53,4 +53,3 @@ class LocalStore(BaseStore, ABC):
     @abstractmethod
     def _write(self, docs, metadatas):
         raise NotImplementedError
-    

metagpt/document_store/chromadb_store.py

@@ -10,6 +10,7 @@ import chromadb
 
 class ChromaStore:
     """If inherited from BaseStore, or importing other modules from metagpt, a Python exception occurs, which is strange."""
+
     def __init__(self, name):
         client = chromadb.Client()
         collection = client.create_collection(name)
@@ -22,7 +23,7 @@ class ChromaStore:
             query_texts=[query],
             n_results=n_results,
             where=metadata_filter,  # optional filter
-            where_document=document_filter  # optional filter
+            where_document=document_filter,  # optional filter
         )
         return results
 

metagpt/document_store/document.py

@@ -24,20 +24,20 @@ def validate_cols(content_col: str, df: pd.DataFrame):
 
 def read_data(data_path: Path):
     suffix = data_path.suffix
-    if '.xlsx' == suffix:
+    if ".xlsx" == suffix:
         data = pd.read_excel(data_path)
-    elif '.csv' == suffix:
+    elif ".csv" == suffix:
         data = pd.read_csv(data_path)
-    elif '.json' == suffix:
+    elif ".json" == suffix:
         data = pd.read_json(data_path)
-    elif suffix in ('.docx', '.doc'):
-        data = UnstructuredWordDocumentLoader(str(data_path), mode='elements').load()
-    elif '.txt' == suffix:
+    elif suffix in (".docx", ".doc"):
+        data = UnstructuredWordDocumentLoader(str(data_path), mode="elements").load()
+    elif ".txt" == suffix:
         data = TextLoader(str(data_path)).load()
-        text_splitter = CharacterTextSplitter(separator='\n', chunk_size=256, chunk_overlap=0)
+        text_splitter = CharacterTextSplitter(separator="\n", chunk_size=256, chunk_overlap=0)
         texts = text_splitter.split_documents(data)
         data = texts
-    elif '.pdf' == suffix:
+    elif ".pdf" == suffix:
         data = UnstructuredPDFLoader(str(data_path), mode="elements").load()
     else:
         raise NotImplementedError
@@ -45,8 +45,7 @@ def read_data(data_path: Path):
 
 
 class Document:
-
-    def __init__(self, data_path, content_col='content', meta_col='metadata'):
+    def __init__(self, data_path, content_col="content", meta_col="metadata"):
         self.data = read_data(data_path)
         if isinstance(self.data, pd.DataFrame):
             validate_cols(content_col, self.data)
@@ -79,4 +78,3 @@ class Document:
             return self._get_docs_and_metadatas_by_langchain()
         else:
             raise NotImplementedError
-        

metagpt/document_store/faiss_store.py

@@ -20,7 +20,7 @@ from metagpt.logs import logger
 
 
 class FaissStore(LocalStore):
-    def __init__(self, raw_data: Path, cache_dir=None, meta_col='source', content_col='output'):
+    def __init__(self, raw_data: Path, cache_dir=None, meta_col="source", content_col="output"):
         self.meta_col = meta_col
         self.content_col = content_col
         super().__init__(raw_data, cache_dir)
@@ -50,7 +50,7 @@ class FaissStore(LocalStore):
             pickle.dump(store, f)
         store.index = index
 
-    def search(self, query, expand_cols=False, sep='\n', *args, k=5, **kwargs):
+    def search(self, query, expand_cols=False, sep="\n", *args, k=5, **kwargs):
         rsp = self.store.similarity_search(query, k=k, **kwargs)
         logger.debug(rsp)
         if expand_cols:
@@ -78,8 +78,8 @@ class FaissStore(LocalStore):
         raise NotImplementedError
 
 
-if __name__ == '__main__':
-    faiss_store = FaissStore(DATA_PATH / 'qcs/qcs_4w.json')
-    logger.info(faiss_store.search('Oily Skin Facial Cleanser'))
-    faiss_store.add([f'Oily Skin Facial Cleanser-{i}' for i in range(3)])
-    logger.info(faiss_store.search('Oily Skin Facial Cleanser'))
+if __name__ == "__main__":
+    faiss_store = FaissStore(DATA_PATH / "qcs/qcs_4w.json")
+    logger.info(faiss_store.search("Oily Skin Facial Cleanser"))
+    faiss_store.add([f"Oily Skin Facial Cleanser-{i}" for i in range(3)])
+    logger.info(faiss_store.search("Oily Skin Facial Cleanser"))

metagpt/document_store/milvus_store.py

@@ -12,12 +12,7 @@ from pymilvus import Collection, CollectionSchema, DataType, FieldSchema, connec
 
 from metagpt.document_store.base_store import BaseStore
 
-type_mapping = {
-    int: DataType.INT64,
-    str: DataType.VARCHAR,
-    float: DataType.DOUBLE,
-    np.ndarray: DataType.FLOAT_VECTOR
-}
+type_mapping = {int: DataType.INT64, str: DataType.VARCHAR, float: DataType.DOUBLE, np.ndarray: DataType.FLOAT_VECTOR}
 
 
 def columns_to_milvus_schema(columns: dict, primary_col_name: str = "", desc: str = ""):
@@ -52,17 +47,11 @@ class MilvusStore(BaseStore):
         self.collection = None
 
     def _create_collection(self, name, schema):
-        collection = Collection(
-            name=name,
-            schema=schema,
-            using='default',
-            shards_num=2,
-            consistency_level="Strong"
-        )
+        collection = Collection(name=name, schema=schema, using="default", shards_num=2, consistency_level="Strong")
         return collection
 
     def create_collection(self, name, columns):
-        schema = columns_to_milvus_schema(columns, 'idx')
+        schema = columns_to_milvus_schema(columns, "idx")
         self.collection = self._create_collection(name, schema)
         return self.collection
 
@@ -72,7 +61,7 @@ class MilvusStore(BaseStore):
     def load_collection(self):
         self.collection.load()
 
-    def build_index(self, field='emb'):
+    def build_index(self, field="emb"):
         self.collection.create_index(field, {"index_type": "FLAT", "metric_type": "L2", "params": {}})
 
     def search(self, query: list[list[float]], *args, **kwargs):
@@ -85,11 +74,11 @@ class MilvusStore(BaseStore):
         search_params = {"metric_type": "L2", "params": {"nprobe": 10}}
         results = self.collection.search(
             data=query,
-            anns_field=kwargs.get('field', 'emb'),
+            anns_field=kwargs.get("field", "emb"),
             param=search_params,
             limit=10,
             expr=None,
-            consistency_level="Strong"
+            consistency_level="Strong",
         )
         # FIXME: results contain id, but to get the actual value from the id, we still need to call the query interface
         return results

metagpt/document_store/qdrant_store.py

@@ -10,13 +10,14 @@ from metagpt.document_store.base_store import BaseStore
 @dataclass
 class QdrantConnection:
     """
-   Args:
-       url: qdrant url
-       host: qdrant host
-       port: qdrant port
-       memory: qdrant service use memory mode
-       api_key: qdrant cloud api_key
-   """
+    Args:
+        url: qdrant url
+        host: qdrant host
+        port: qdrant port
+        memory: qdrant service use memory mode
+        api_key: qdrant cloud api_key
+    """
+
     url: str = None
     host: str = None
     port: int = None
@@ -31,9 +32,7 @@ class QdrantStore(BaseStore):
         elif connect.url:
             self.client = QdrantClient(url=connect.url, api_key=connect.api_key)
         elif connect.host and connect.port:
-            self.client = QdrantClient(
-                host=connect.host, port=connect.port, api_key=connect.api_key
-            )
+            self.client = QdrantClient(host=connect.host, port=connect.port, api_key=connect.api_key)
         else:
             raise Exception("please check QdrantConnection.")
 
@@ -58,15 +57,11 @@ class QdrantStore(BaseStore):
         try:
             self.client.get_collection(collection_name)
             if force_recreate:
-                res = self.client.recreate_collection(
-                    collection_name, vectors_config=vectors_config, **kwargs
-                )
+                res = self.client.recreate_collection(collection_name, vectors_config=vectors_config, **kwargs)
                 return res
             return True
         except:  # noqa: E722
-            return self.client.recreate_collection(
-                collection_name, vectors_config=vectors_config, **kwargs
-            )
+            return self.client.recreate_collection(collection_name, vectors_config=vectors_config, **kwargs)
 
     def has_collection(self, collection_name: str):
         try:

metagpt/environment.py

@@ -17,34 +17,34 @@ from metagpt.schema import Message
 
 class Environment(BaseModel):
     """环境，承载一批角色，角色可以向环境发布消息，可以被其他角色观察到
-       Environment, hosting a batch of roles, roles can publish messages to the environment, and can be observed by other roles
-    
+    Environment, hosting a batch of roles, roles can publish messages to the environment, and can be observed by other roles
+
     """
 
     roles: dict[str, Role] = Field(default_factory=dict)
     memory: Memory = Field(default_factory=Memory)
-    history: str = Field(default='')
+    history: str = Field(default="")
 
     class Config:
         arbitrary_types_allowed = True
 
     def add_role(self, role: Role):
         """增加一个在当前环境的角色
-           Add a role in the current environment
+        Add a role in the current environment
         """
         role.set_env(self)
         self.roles[role.profile] = role
 
     def add_roles(self, roles: Iterable[Role]):
         """增加一批在当前环境的角色
-            Add a batch of characters in the current environment
+        Add a batch of characters in the current environment
         """
         for role in roles:
             self.add_role(role)
 
     def publish_message(self, message: Message):
         """向当前环境发布信息
-          Post information to the current environment
+        Post information to the current environment
         """
         # self.message_queue.put(message)
         self.memory.add(message)
@@ -68,12 +68,12 @@ class Environment(BaseModel):
 
     def get_roles(self) -> dict[str, Role]:
         """获得环境内的所有角色
-           Process all Role runs at once
+        Process all Role runs at once
         """
         return self.roles
 
     def get_role(self, name: str) -> Role:
         """获得环境内的指定角色
-           get all the environment roles
+        get all the environment roles
         """
         return self.roles.get(name, None)

metagpt/inspect_module.py

@@ -12,17 +12,17 @@ import metagpt  # replace with your module
 
 
 def print_classes_and_functions(module):
-    """FIXME: NOT WORK.. """
+    """FIXME: NOT WORK.."""
     for name, obj in inspect.getmembers(module):
         if inspect.isclass(obj):
-            print(f'Class: {name}')
+            print(f"Class: {name}")
         elif inspect.isfunction(obj):
-            print(f'Function: {name}')
+            print(f"Function: {name}")
         else:
             print(name)
 
     print(dir(module))
 
 
-if __name__ == '__main__':
-    print_classes_and_functions(metagpt)
+if __name__ == "__main__":
+    print_classes_and_functions(metagpt)

metagpt/llm.py

@@ -12,8 +12,9 @@ from metagpt.provider.openai_api import OpenAIGPTAPI as LLM
 DEFAULT_LLM = LLM()
 CLAUDE_LLM = Claude()
 
+
 async def ai_func(prompt):
     """使用LLM进行QA
-       QA with LLMs
-     """
+    QA with LLMs
+    """
     return await DEFAULT_LLM.aask(prompt)

metagpt/logs.py

@@ -12,13 +12,15 @@ from loguru import logger as _logger
 
 from metagpt.const import PROJECT_ROOT
 
+
 def define_log_level(print_level="INFO", logfile_level="DEBUG"):
     """调整日志级别到level之上
-       Adjust the log level to above level
+    Adjust the log level to above level
     """
     _logger.remove()
     _logger.add(sys.stderr, level=print_level)
-    _logger.add(PROJECT_ROOT / 'logs/log.txt', level=logfile_level)
+    _logger.add(PROJECT_ROOT / "logs/log.txt", level=logfile_level)
     return _logger
 
+
 logger = define_log_level()

metagpt/management/skill_manager.py

@@ -19,8 +19,8 @@ class SkillManager:
 
     def __init__(self):
         self._llm = LLM()
-        self._store = ChromaStore('skill_manager')
-        self._skills: dict[str: Skill] = {}
+        self._store = ChromaStore("skill_manager")
+        self._skills: dict[str:Skill] = {}
 
     def add_skill(self, skill: Skill):
         """
@@ -54,7 +54,7 @@ class SkillManager:
         :param desc: Skill description
         :return: Multiple skills
         """
-        return self._store.search(desc, n_results=n_results)['ids'][0]
+        return self._store.search(desc, n_results=n_results)["ids"][0]
 
     def retrieve_skill_scored(self, desc: str, n_results: int = 2) -> dict:
         """
@@ -75,6 +75,6 @@ class SkillManager:
         logger.info(text)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     manager = SkillManager()
     manager.generate_skill_desc(Action())

metagpt/manager.py

@@ -18,7 +18,7 @@ class Manager:
             "Product Manager": "Architect",
             "Architect": "Engineer",
             "Engineer": "QA Engineer",
-            "QA Engineer": "Product Manager"
+            "QA Engineer": "Product Manager",
         }
         self.prompt_template = """
         Given the following message:
@@ -51,7 +51,7 @@ class Manager:
         # chosen_role_name = self.llm.ask(self.prompt_template.format(context))
 
         # FIXME: 现在通过简单的字典决定流向，但之后还是应该有思考过程
-        #The direction of flow is now determined by a simple dictionary, but there should still be a thought process afterwards
+        # The direction of flow is now determined by a simple dictionary, but there should still be a thought process afterwards
         next_role_profile = self.role_directions[message.role]
         # logger.debug(f"{next_role_profile}")
         for _, role in roles.items():

metagpt/memory/longterm_memory.py

@@ -68,4 +68,3 @@ class LongTermMemory(Memory):
     def clear(self):
         super(LongTermMemory, self).clear()
         self.memory_storage.clean()
-        

metagpt/memory/memory.py

@@ -85,4 +85,3 @@ class Memory:
                 continue
             rsp += self.index[action]
         return rsp
-    

metagpt/memory/memory_storage.py

@@ -2,16 +2,16 @@
 # -*- coding: utf-8 -*-
 # @Desc   : the implement of memory storage
 
-from typing import List
 from pathlib import Path
+from typing import List
 
 from langchain.vectorstores.faiss import FAISS
 
 from metagpt.const import DATA_PATH, MEM_TTL
+from metagpt.document_store.faiss_store import FaissStore
 from metagpt.logs import logger
 from metagpt.schema import Message
-from metagpt.utils.serialize import serialize_message, deserialize_message
-from metagpt.document_store.faiss_store import FaissStore
+from metagpt.utils.serialize import deserialize_message, serialize_message
 
 
 class MemoryStorage(FaissStore):
@@ -34,7 +34,7 @@ class MemoryStorage(FaissStore):
 
     def recover_memory(self, role_id: str) -> List[Message]:
         self.role_id = role_id
-        self.role_mem_path = Path(DATA_PATH / f'role_mem/{self.role_id}/')
+        self.role_mem_path = Path(DATA_PATH / f"role_mem/{self.role_id}/")
         self.role_mem_path.mkdir(parents=True, exist_ok=True)
 
         self.store = self._load()
@@ -51,18 +51,18 @@ class MemoryStorage(FaissStore):
 
     def _get_index_and_store_fname(self):
         if not self.role_mem_path:
-            logger.error(f'You should call {self.__class__.__name__}.recover_memory fist when using LongTermMemory')
+            logger.error(f"You should call {self.__class__.__name__}.recover_memory fist when using LongTermMemory")
             return None, None
-        index_fpath = Path(self.role_mem_path / f'{self.role_id}.index')
-        storage_fpath = Path(self.role_mem_path / f'{self.role_id}.pkl')
+        index_fpath = Path(self.role_mem_path / f"{self.role_id}.index")
+        storage_fpath = Path(self.role_mem_path / f"{self.role_id}.pkl")
         return index_fpath, storage_fpath
 
     def persist(self):
         super(MemoryStorage, self).persist()
-        logger.debug(f'Agent {self.role_id} persist memory into local')
+        logger.debug(f"Agent {self.role_id} persist memory into local")
 
     def add(self, message: Message) -> bool:
-        """ add message into memory storage"""
+        """add message into memory storage"""
         docs = [message.content]
         metadatas = [{"message_ser": serialize_message(message)}]
         if not self.store:
@@ -79,10 +79,7 @@ class MemoryStorage(FaissStore):
         if not self.store:
             return []
 
-        resp = self.store.similarity_search_with_score(
-            query=message.content,
-            k=k
-        )
+        resp = self.store.similarity_search_with_score(query=message.content, k=k)
         # filter the result which score is smaller than the threshold
         filtered_resp = []
         for item, score in resp:
@@ -104,4 +101,3 @@ class MemoryStorage(FaissStore):
 
         self.store = None
         self._initialized = False
-        

metagpt/prompts/invoice_ocr.py

@@ -10,7 +10,9 @@
 
 COMMON_PROMPT = "Now I will provide you with the OCR text recognition results for the invoice."
 
-EXTRACT_OCR_MAIN_INFO_PROMPT = COMMON_PROMPT + """
+EXTRACT_OCR_MAIN_INFO_PROMPT = (
+    COMMON_PROMPT
+    + """
 Please extract the payee, city, total cost, and invoicing date of the invoice.
 
 The OCR data of the invoice are as follows:
@@ -22,8 +24,11 @@ Mandatory restrictions are returned according to the following requirements:
 2. The returned JSON dictionary must be returned in {language}
 3. Mandatory requirement to output in JSON format: {{"收款人":"x","城市":"x","总费用/元":"","开票日期":""}}.
 """
+)
 
-REPLY_OCR_QUESTION_PROMPT = COMMON_PROMPT + """
+REPLY_OCR_QUESTION_PROMPT = (
+    COMMON_PROMPT
+    + """
 Please answer the question: {query}
 
 The OCR data of the invoice are as follows:
@@ -34,6 +39,6 @@ Mandatory restrictions are returned according to the following requirements:
 2. Enforce restrictions on not returning OCR data sent to you.
 3. Return with markdown syntax layout.
 """
+)
 
 INVOICE_OCR_SUCCESS = "Successfully completed OCR text recognition invoice."
-

metagpt/prompts/sales.py

@@ -54,10 +54,12 @@ Conversation history:
 {salesperson_name}: 
 """
 
-conversation_stages = {'1' : "Introduction: Start the conversation by introducing yourself and your company. Be polite and respectful while keeping the tone of the conversation professional. Your greeting should be welcoming. Always clarify in your greeting the reason why you are contacting the prospect.",
-'2': "Qualification: Qualify the prospect by confirming if they are the right person to talk to regarding your product/service. Ensure that they have the authority to make purchasing decisions.",
-'3': "Value proposition: Briefly explain how your product/service can benefit the prospect. Focus on the unique selling points and value proposition of your product/service that sets it apart from competitors.",
-'4': "Needs analysis: Ask open-ended questions to uncover the prospect's needs and pain points. Listen carefully to their responses and take notes.",
-'5': "Solution presentation: Based on the prospect's needs, present your product/service as the solution that can address their pain points.",
-'6': "Objection handling: Address any objections that the prospect may have regarding your product/service. Be prepared to provide evidence or testimonials to support your claims.",
-'7': "Close: Ask for the sale by proposing a next step. This could be a demo, a trial or a meeting with decision-makers. Ensure to summarize what has been discussed and reiterate the benefits."}
+conversation_stages = {
+    "1": "Introduction: Start the conversation by introducing yourself and your company. Be polite and respectful while keeping the tone of the conversation professional. Your greeting should be welcoming. Always clarify in your greeting the reason why you are contacting the prospect.",
+    "2": "Qualification: Qualify the prospect by confirming if they are the right person to talk to regarding your product/service. Ensure that they have the authority to make purchasing decisions.",
+    "3": "Value proposition: Briefly explain how your product/service can benefit the prospect. Focus on the unique selling points and value proposition of your product/service that sets it apart from competitors.",
+    "4": "Needs analysis: Ask open-ended questions to uncover the prospect's needs and pain points. Listen carefully to their responses and take notes.",
+    "5": "Solution presentation: Based on the prospect's needs, present your product/service as the solution that can address their pain points.",
+    "6": "Objection handling: Address any objections that the prospect may have regarding your product/service. Be prepared to provide evidence or testimonials to support your claims.",
+    "7": "Close: Ask for the sale by proposing a next step. This could be a demo, a trial or a meeting with decision-makers. Ensure to summarize what has been discussed and reiterate the benefits.",
+}

metagpt/prompts/tutorial_assistant.py

@@ -12,7 +12,9 @@ You are now a seasoned technical professional in the field of the internet.
 We need you to write a technical tutorial with the topic "{topic}".
 """
 
-DIRECTORY_PROMPT = COMMON_PROMPT + """
+DIRECTORY_PROMPT = (
+    COMMON_PROMPT
+    + """
 Please provide the specific table of contents for this tutorial, strictly following the following requirements:
 1. The output must be strictly in the specified language, {language}.
 2. Answer strictly in the dictionary format like {{"title": "xxx", "directory": [{{"dir 1": ["sub dir 1", "sub dir 2"]}}, {{"dir 2": ["sub dir 3", "sub dir 4"]}}]}}.
@@ -20,8 +22,11 @@ Please provide the specific table of contents for this tutorial, strictly follow
 4. Do not have extra spaces or line breaks.
 5. Each directory title has practical significance.
 """
+)
 
-CONTENT_PROMPT = COMMON_PROMPT + """
+CONTENT_PROMPT = (
+    COMMON_PROMPT
+    + """
 Now I will give you the module directory titles for the topic. 
 Please output the detailed principle content of this title in detail. 
 If there are code examples, please provide them according to standard code specifications. 
@@ -36,4 +41,5 @@ Strictly limit output according to the following requirements:
 3. The output must be strictly in the specified language, {language}.
 4. Do not have redundant output, including concluding remarks.
 5. Strict requirement not to output the topic "{topic}".
-"""
+"""
+)

metagpt/provider/anthropic_api.py

@@ -32,4 +32,3 @@ class Claude2:
             max_tokens_to_sample=1000,
         )
         return res.completion
-    

metagpt/provider/base_chatbot.py

@@ -12,6 +12,7 @@ from dataclasses import dataclass
 @dataclass
 class BaseChatbot(ABC):
     """Abstract GPT class"""
+
     mode: str = "API"
 
     @abstractmethod
@@ -25,4 +26,3 @@ class BaseChatbot(ABC):
     @abstractmethod
     def ask_code(self, msgs: list) -> str:
         """Ask GPT multiple questions and get a piece of code"""
-        

metagpt/provider/base_gpt_api.py

@@ -14,7 +14,8 @@ from metagpt.provider.base_chatbot import BaseChatbot
 
 class BaseGPTAPI(BaseChatbot):
     """GPT API abstract class, requiring all inheritors to provide a series of standard capabilities"""
-    system_prompt = 'You are a helpful assistant.'
+
+    system_prompt = "You are a helpful assistant."
 
     def _user_msg(self, msg: str) -> dict[str, str]:
         return {"role": "user", "content": msg}
@@ -110,9 +111,8 @@ class BaseGPTAPI(BaseChatbot):
 
     def messages_to_prompt(self, messages: list[dict]):
         """[{"role": "user", "content": msg}] to user: <msg> etc."""
-        return '\n'.join([f"{i['role']}: {i['content']}" for i in messages])
+        return "\n".join([f"{i['role']}: {i['content']}" for i in messages])
 
     def messages_to_dict(self, messages):
         """objects to [{"role": "user", "content": msg}] etc."""
         return [i.to_dict() for i in messages]
-    

metagpt/provider/openai_api.py

@@ -110,7 +110,6 @@ class CostManager(metaclass=Singleton):
         """
         return self.total_completion_tokens
 
-
     def get_total_cost(self):
         """
         Get the total cost of API calls.
@@ -120,7 +119,6 @@ class CostManager(metaclass=Singleton):
         """
         return self.total_cost
 
-
     def get_costs(self) -> Costs:
         """Get all costs"""
         return Costs(self.total_prompt_tokens, self.total_completion_tokens, self.total_cost, self.total_budget)

metagpt/provider/spark_api.py

@@ -14,8 +14,7 @@ import json
 import ssl
 from time import mktime
 from typing import Optional
-from urllib.parse import urlencode
-from urllib.parse import urlparse
+from urllib.parse import urlencode, urlparse
 from wsgiref.handlers import format_date_time
 
 import websocket  # 使用websocket_client
@@ -26,9 +25,8 @@ from metagpt.provider.base_gpt_api import BaseGPTAPI
 
 
 class SparkAPI(BaseGPTAPI):
-
     def __init__(self):
-        logger.warning('当前方法无法支持异步运行。当你使用acompletion时，并不能并行访问。')
+        logger.warning("当前方法无法支持异步运行。当你使用acompletion时，并不能并行访问。")
 
     def ask(self, msg: str) -> str:
         message = [self._default_system_msg(), self._user_msg(msg)]
@@ -49,7 +47,7 @@ class SparkAPI(BaseGPTAPI):
 
     async def acompletion_text(self, messages: list[dict], stream=False) -> str:
         # 不支持
-        logger.error('该功能禁用。')
+        logger.error("该功能禁用。")
         w = GetMessageFromWeb(messages)
         return w.run()
 
@@ -93,29 +91,26 @@ class GetMessageFromWeb:
             signature_origin += "GET " + self.path + " HTTP/1.1"
 
             # 进行hmac-sha256进行加密
-            signature_sha = hmac.new(self.api_secret.encode('utf-8'), signature_origin.encode('utf-8'),
-                                     digestmod=hashlib.sha256).digest()
+            signature_sha = hmac.new(
+                self.api_secret.encode("utf-8"), signature_origin.encode("utf-8"), digestmod=hashlib.sha256
+            ).digest()
 
-            signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding='utf-8')
+            signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding="utf-8")
 
             authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"'
 
-            authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')
+            authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode(encoding="utf-8")
 
             # 将请求的鉴权参数组合为字典
-            v = {
-                "authorization": authorization,
-                "date": date,
-                "host": self.host
-            }
+            v = {"authorization": authorization, "date": date, "host": self.host}
             # 拼接鉴权参数，生成url
-            url = self.spark_url + '?' + urlencode(v)
+            url = self.spark_url + "?" + urlencode(v)
             # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致
             return url
 
     def __init__(self, text):
         self.text = text
-        self.ret = ''
+        self.ret = ""
         self.spark_appid = CONFIG.spark_appid
         self.spark_api_secret = CONFIG.spark_api_secret
         self.spark_api_key = CONFIG.spark_api_key
@@ -124,15 +119,15 @@ class GetMessageFromWeb:
 
     def on_message(self, ws, message):
         data = json.loads(message)
-        code = data['header']['code']
+        code = data["header"]["code"]
 
         if code != 0:
             ws.close()  # 请求错误，则关闭socket
-            logger.critical(f'回答获取失败，响应信息反序列化之后为： {data}')
+            logger.critical(f"回答获取失败，响应信息反序列化之后为： {data}")
             return
         else:
             choices = data["payload"]["choices"]
-            seq = choices["seq"]  # 服务端是流式返回，seq为返回的数据序号
+            # seq = choices["seq"]  # 服务端是流式返回，seq为返回的数据序号
             status = choices["status"]  # 服务端是流式返回，status用于判断信息是否传送完毕
             content = choices["text"][0]["content"]  # 本次接收到的回答文本
             self.ret += content
@@ -142,7 +137,7 @@ class GetMessageFromWeb:
     # 收到websocket错误的处理
     def on_error(self, ws, error):
         # on_message方法处理接收到的信息，出现任何错误，都会调用这个方法
-        logger.critical(f'通讯连接出错，【错误提示: {error}】')
+        logger.critical(f"通讯连接出错，【错误提示: {error}】")
 
     # 收到websocket关闭的处理
     def on_close(self, ws, one, two):
@@ -150,17 +145,12 @@ class GetMessageFromWeb:
 
     # 处理请求数据
     def gen_params(self):
-
         data = {
-            "header": {
-                "app_id": self.spark_appid,
-                "uid": "1234"
-            },
+            "header": {"app_id": self.spark_appid, "uid": "1234"},
             "parameter": {
                 "chat": {
                     # domain为必传参数
                     "domain": self.domain,
-
                     # 以下为可微调，非必传参数
                     # 注意：官方建议，temperature和top_k修改一个即可
                     "max_tokens": 2048,  # 默认2048，模型回答的tokens的最大长度，即允许它输出文本的最长字数
@@ -168,11 +158,7 @@ class GetMessageFromWeb:
                     "top_k": 4,  # 取值为[1，6],默认为4。从k个候选中随机选择一个（非等概率）
                 }
             },
-            "payload": {
-                "message": {
-                    "text": self.text
-                }
-            }
+            "payload": {"message": {"text": self.text}},
         }
         return data
 
@@ -189,17 +175,12 @@ class GetMessageFromWeb:
         return self._run(self.text)
 
     def _run(self, text_list):
-
-        ws_param = self.WsParam(
-            self.spark_appid,
-            self.spark_api_key,
-            self.spark_api_secret,
-            self.spark_url,
-            text_list)
+        ws_param = self.WsParam(self.spark_appid, self.spark_api_key, self.spark_api_secret, self.spark_url, text_list)
         ws_url = ws_param.create_url()
 
         websocket.enableTrace(False)  # 默认禁用 WebSocket 的跟踪功能
-        ws = websocket.WebSocketApp(ws_url, on_message=self.on_message, on_error=self.on_error, on_close=self.on_close,
-                                    on_open=self.on_open)
+        ws = websocket.WebSocketApp(
+            ws_url, on_message=self.on_message, on_error=self.on_error, on_close=self.on_close, on_open=self.on_open
+        )
         ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})
         return self.ret

metagpt/roles/customer_service.py

@@ -24,12 +24,5 @@ DESC = """
 
 
 class CustomerService(Sales):
-    def __init__(
-            self,
-            name="Xiaomei",
-            profile="Human customer service",
-            desc=DESC,
-            store=None
-    ):
+    def __init__(self, name="Xiaomei", profile="Human customer service", desc=DESC, store=None):
         super().__init__(name, profile, desc=desc, store=store)
-        

metagpt/roles/invoice_ocr_assistant.py

@@ -9,7 +9,7 @@
 
 import pandas as pd
 
-from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
+from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, ReplyQuestion
 from metagpt.prompts.invoice_ocr import INVOICE_OCR_SUCCESS
 from metagpt.roles import Role
 from metagpt.schema import Message
@@ -107,4 +107,3 @@ class InvoiceOCRAssistant(Role):
                 break
             msg = await self._act()
         return msg
-

metagpt/roles/prompt.py

@@ -23,6 +23,7 @@ SUFFIX = """Let's begin!
 Question: {input}
 Thoughts: {agent_scratchpad}"""
 
+
 class PromptString(Enum):
     REFLECTION_QUESTIONS = "Here are some statements:\n{memory_descriptions}\n\nBased solely on the information above, what are the 3 most prominent high-level questions we can answer about the topic in the statements?\n\n{format_instructions}"
 
@@ -32,7 +33,7 @@ class PromptString(Enum):
 
     RECENT_ACTIVITY = "Based on the following memory, produce a brief summary of what {full_name} has been up to recently. Do not invent details not explicitly stated in the memory. For any conversation, be sure to mention whether the conversation has concluded or is still ongoing.\n\nMemory: {memory_descriptions}"
 
-    MAKE_PLANS = "You are a plan-generating AI. Your job is to assist the character in formulating new plans based on new information. Given the character's information (profile, objectives, recent activities, current plans, and location context) and their current thought process, produce a new set of plans for them. The final plan should comprise at least {time_window} of activities and no more than 5 individual plans. List the plans in the order they should be executed, with each plan detailing its description, location, start time, stop criteria, and maximum duration.\n\nSample plan: {{\"index\": 1, \"description\": \"Cook dinner\", \"location_id\": \"0a3bc22b-36aa-48ab-adb0-18616004caed\",\"start_time\": \"2022-12-12T20:00:00+00:00\",\"max_duration_hrs\": 1.5, \"stop_condition\": \"Dinner is fully prepared\"}}\'\n\nFor each plan, choose the most appropriate location name from this list: {allowed_location_descriptions}\n\n{format_instructions}\n\nAlways prioritize completing any unfinished conversations.\n\nLet's begin!\n\nName: {full_name}\nProfile: {private_bio}\nObjectives: {directives}\nLocation Context: {location_context}\nCurrent Plans: {current_plans}\nRecent Activities: {recent_activity}\nThought Process: {thought_process}\nIt's essential to encourage the character to collaborate with other characters in their plans.\n\n"
+    MAKE_PLANS = 'You are a plan-generating AI. Your job is to assist the character in formulating new plans based on new information. Given the character\'s information (profile, objectives, recent activities, current plans, and location context) and their current thought process, produce a new set of plans for them. The final plan should comprise at least {time_window} of activities and no more than 5 individual plans. List the plans in the order they should be executed, with each plan detailing its description, location, start time, stop criteria, and maximum duration.\n\nSample plan: {{"index": 1, "description": "Cook dinner", "location_id": "0a3bc22b-36aa-48ab-adb0-18616004caed","start_time": "2022-12-12T20:00:00+00:00","max_duration_hrs": 1.5, "stop_condition": "Dinner is fully prepared"}}\'\n\nFor each plan, choose the most appropriate location name from this list: {allowed_location_descriptions}\n\n{format_instructions}\n\nAlways prioritize completing any unfinished conversations.\n\nLet\'s begin!\n\nName: {full_name}\nProfile: {private_bio}\nObjectives: {directives}\nLocation Context: {location_context}\nCurrent Plans: {current_plans}\nRecent Activities: {recent_activity}\nThought Process: {thought_process}\nIt\'s essential to encourage the character to collaborate with other characters in their plans.\n\n'
 
     EXECUTE_PLAN = "You are a role-playing AI, playing the role of {your_name}, in front of a live audience. Every word you say can be observed by the audience, so make sure you speak often and make it interesting. You cannot interact directly with the audience.\n\nBased on the following context and tools, proceed as if you are {your_name}. Your primary task is to complete the task given below, however, if you are currently in a conversation with another character, you should always complete the conversation first and then proceed with the task. Do not start working while you are engaged in an unfinished conversation. Use your best judgment to determine whether a conversation involves you and whether it is unfinished. You don't need to respond to every message you receive.\n\nThis is a personal profile of your character:\n{your_private_bio}\n\nThis is a description of your location and other nearby characters you can converse with:\n\n{location_context}\n\nThese are some relevant memories:\n```\n{relevant_memories}\n```\n\nThis is some relevant conversation history:\n```\n{conversation_history}\n```\n\nThese are the tools you can use:\n{tools}\n\nYour response should follow the format below:\n\nTask: The task you must complete\nThoughts: What you should think about doing\nAction: The action to take, must be one of these words: [{tool_names}]\nAction Input: Input for the action\nObservation: The result of the action\n... (This Thoughts/Action/Action Input/Observation can be repeated N times)\nThoughts: 'I have completed the task'\nFinal Response: The final response to the task\n\nIf you are not ready with a final response, then you must take an action.\n\nIf you are certain that you cannot complete the task with the tools provided, return 'Final Response: Need Help', however, if you are in conversation with another character, responses like 'I don't know' are valid. During conversations, you should never break character or admit you are an AI.\nIf the task is completed and no specific response is required, return 'Final Response: Done'\nLet's begin!\n\nTask: {input}\n\n{agent_scratchpad}"
 
@@ -40,6 +41,6 @@ class PromptString(Enum):
 
     GOSSIP = "You are {full_name}. \n{memory_descriptions}\n\nBased on the statements above, say a thing or two of interest to others at your location: {other_agent_names}.\nAlways specify their names when referring to others."
 
-    HAS_HAPPENED = "Given the descriptions of the observations of the following characters and the events they are awaiting, indicate whether the character has witnessed the event.\n{format_instructions}\n\nExample:\n\nObservations:\nJoe entered the office at 2023-05-04 08:00:00+00:00\nJoe said hi to Sally at 2023-05-04 08:05:00+00:00\nSally said hello to Joe at 2023-05-04 08:05:30+00:00\nRebecca started working at 2023-05-04 08:10:00+00:00\nJoe made some breakfast at 2023-05-04 08:15:00+00:00\n\nAwaiting: Sally responded to Joe\n\nYour response: '{{\"has_happened\": true, \"date_occured\": 2023-05-04 08:05:30+00:00}}'\n\nLet's begin!\n\nObservations:\n{memory_descriptions}\n\nAwaiting: {event_description}\n"
+    HAS_HAPPENED = 'Given the descriptions of the observations of the following characters and the events they are awaiting, indicate whether the character has witnessed the event.\n{format_instructions}\n\nExample:\n\nObservations:\nJoe entered the office at 2023-05-04 08:00:00+00:00\nJoe said hi to Sally at 2023-05-04 08:05:00+00:00\nSally said hello to Joe at 2023-05-04 08:05:30+00:00\nRebecca started working at 2023-05-04 08:10:00+00:00\nJoe made some breakfast at 2023-05-04 08:15:00+00:00\n\nAwaiting: Sally responded to Joe\n\nYour response: \'{{"has_happened": true, "date_occured": 2023-05-04 08:05:30+00:00}}\'\n\nLet\'s begin!\n\nObservations:\n{memory_descriptions}\n\nAwaiting: {event_description}\n'
 
     OUTPUT_FORMAT = "\n\n(Remember! Make sure your output always adheres to one of the following two formats:\n\nA. If you have completed the task:\nThoughts: 'I have completed the task'\nFinal Response: <str>\n\nB. If you haven't completed the task:\nThoughts: <str>\nAction: <str>\nAction Input: <str>\nObservation: <str>)\n"

metagpt/roles/role.py

@@ -11,12 +11,13 @@ from typing import Iterable, Type
 
 from pydantic import BaseModel, Field
 
+from metagpt.actions import Action, ActionOutput
+
 # from metagpt.environment import Environment
 from metagpt.config import CONFIG
-from metagpt.actions import Action, ActionOutput
 from metagpt.llm import LLM
 from metagpt.logs import logger
-from metagpt.memory import Memory, LongTermMemory
+from metagpt.memory import LongTermMemory, Memory
 from metagpt.schema import Message
 
 PREFIX_TEMPLATE = """You are a {profile}, named {name}, your goal is {goal}, and the constraint is {constraints}. """
@@ -49,6 +50,7 @@ ROLE_TEMPLATE = """Your response should be based on the previous conversation hi
 
 class RoleSetting(BaseModel):
     """Role Settings"""
+
     name: str
     profile: str
     goal: str
@@ -64,7 +66,8 @@ class RoleSetting(BaseModel):
 
 class RoleContext(BaseModel):
     """Role Runtime Context"""
-    env: 'Environment' = Field(default=None)
+
+    env: "Environment" = Field(default=None)
     memory: Memory = Field(default_factory=Memory)
     long_term_memory: LongTermMemory = Field(default_factory=LongTermMemory)
     state: int = Field(default=0)
@@ -128,7 +131,7 @@ class Role:
         logger.debug(self._actions)
         self._rc.todo = self._actions[self._rc.state]
 
-    def set_env(self, env: 'Environment'):
+    def set_env(self, env: "Environment"):
         """Set the environment in which the role works. The role can talk to the environment and can also receive messages by observing."""
         self._rc.env = env
 
@@ -150,12 +153,13 @@ class Role:
             self._set_state(0)
             return
         prompt = self._get_prefix()
-        prompt += STATE_TEMPLATE.format(history=self._rc.history, states="\n".join(self._states),
-                                        n_states=len(self._states) - 1)
+        prompt += STATE_TEMPLATE.format(
+            history=self._rc.history, states="\n".join(self._states), n_states=len(self._states) - 1
+        )
         next_state = await self._llm.aask(prompt)
         logger.debug(f"{prompt=}")
         if not next_state.isdigit() or int(next_state) not in range(len(self._states)):
-            logger.warning(f'Invalid answer of state, {next_state=}')
+            logger.warning(f"Invalid answer of state, {next_state=}")
             next_state = "0"
         self._set_state(int(next_state))
 
@@ -168,8 +172,12 @@ class Role:
         response = await self._rc.todo.run(self._rc.important_memory)
         # logger.info(response)
         if isinstance(response, ActionOutput):
-            msg = Message(content=response.content, instruct_content=response.instruct_content,
-                        role=self.profile, cause_by=type(self._rc.todo))
+            msg = Message(
+                content=response.content,
+                instruct_content=response.instruct_content,
+                role=self.profile,
+                cause_by=type(self._rc.todo),
+            )
         else:
             msg = Message(content=response, role=self.profile, cause_by=type(self._rc.todo))
         self._rc.memory.add(msg)
@@ -184,15 +192,17 @@ class Role:
         env_msgs = self._rc.env.memory.get()
 
         observed = self._rc.env.memory.get_by_actions(self._rc.watch)
-        
-        self._rc.news = self._rc.memory.find_news(observed)  # find news (previously unseen messages) from observed messages
+
+        self._rc.news = self._rc.memory.find_news(
+            observed
+        )  # find news (previously unseen messages) from observed messages
 
         for i in env_msgs:
             self.recv(i)
 
         news_text = [f"{i.role}: {i.content[:20]}..." for i in self._rc.news]
         if news_text:
-            logger.debug(f'{self._setting} observed: {news_text}')
+            logger.debug(f"{self._setting} observed: {news_text}")
         return len(self._rc.news)
 
     def _publish_message(self, msg):

metagpt/roles/sales.py

@@ -12,16 +12,16 @@ from metagpt.tools import SearchEngineType
 
 class Sales(Role):
     def __init__(
-            self,
-            name="Xiaomei",
-            profile="Retail sales guide",
-            desc="I am a sales guide in retail. My name is Xiaomei. I will answer some customer questions next, and I "
-                 "will answer questions only based on the information in the knowledge base."
-                 "If I feel that you can't get the answer from the reference material, then I will directly reply that"
-                 " I don't know, and I won't tell you that this is from the knowledge base,"
-                 "but pretend to be what I know. Note that each of my replies will be replied in the tone of a "
-                 "professional guide",
-            store=None
+        self,
+        name="Xiaomei",
+        profile="Retail sales guide",
+        desc="I am a sales guide in retail. My name is Xiaomei. I will answer some customer questions next, and I "
+        "will answer questions only based on the information in the knowledge base."
+        "If I feel that you can't get the answer from the reference material, then I will directly reply that"
+        " I don't know, and I won't tell you that this is from the knowledge base,"
+        "but pretend to be what I know. Note that each of my replies will be replied in the tone of a "
+        "professional guide",
+        store=None,
     ):
         super().__init__(name, profile, desc=desc)
         self._set_store(store)
@@ -32,4 +32,3 @@ class Sales(Role):
         else:
             action = SearchAndSummarize()
         self._init_actions([action])
-        

metagpt/roles/seacher.py

@@ -15,7 +15,7 @@ from metagpt.tools import SearchEngineType
 class Searcher(Role):
     """
     Represents a Searcher role responsible for providing search services to users.
-    
+
     Attributes:
         name (str): Name of the searcher.
         profile (str): Role profile.
@@ -23,17 +23,19 @@ class Searcher(Role):
         constraints (str): Constraints or limitations for the searcher.
         engine (SearchEngineType): The type of search engine to use.
     """
-    
-    def __init__(self, 
-                 name: str = 'Alice', 
-                 profile: str = 'Smart Assistant', 
-                 goal: str = 'Provide search services for users',
-                 constraints: str = 'Answer is rich and complete', 
-                 engine=SearchEngineType.SERPAPI_GOOGLE, 
-                 **kwargs) -> None:
+
+    def __init__(
+        self,
+        name: str = "Alice",
+        profile: str = "Smart Assistant",
+        goal: str = "Provide search services for users",
+        constraints: str = "Answer is rich and complete",
+        engine=SearchEngineType.SERPAPI_GOOGLE,
+        **kwargs,
+    ) -> None:
         """
         Initializes the Searcher role with given attributes.
-        
+
         Args:
             name (str): Name of the searcher.
             profile (str): Role profile.
@@ -53,10 +55,14 @@ class Searcher(Role):
         """Performs the search action in a single process."""
         logger.info(f"{self._setting}: ready to {self._rc.todo}")
         response = await self._rc.todo.run(self._rc.memory.get(k=0))
-        
+
         if isinstance(response, ActionOutput):
-            msg = Message(content=response.content, instruct_content=response.instruct_content,
-                          role=self.profile, cause_by=type(self._rc.todo))
+            msg = Message(
+                content=response.content,
+                instruct_content=response.instruct_content,
+                role=self.profile,
+                cause_by=type(self._rc.todo),
+            )
         else:
             msg = Message(content=response, role=self.profile, cause_by=type(self._rc.todo))
         self._rc.memory.add(msg)

metagpt/roles/tutorial_assistant.py

@@ -9,7 +9,7 @@
 from datetime import datetime
 from typing import Dict
 
-from metagpt.actions.write_tutorial import WriteDirectory, WriteContent
+from metagpt.actions.write_tutorial import WriteContent, WriteDirectory
 from metagpt.const import TUTORIAL_PATH
 from metagpt.logs import logger
 from metagpt.roles import Role
@@ -110,5 +110,5 @@ class TutorialAssistant(Role):
                 break
             msg = await self._act()
         root_path = TUTORIAL_PATH / datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
-        await File.write(root_path, f"{self.main_title}.md", self.total_content.encode('utf-8'))
+        await File.write(root_path, f"{self.main_title}.md", self.total_content.encode("utf-8"))
         return msg

metagpt/schema.py

@@ -23,9 +23,10 @@ class RawMessage(TypedDict):
 @dataclass
 class Message:
     """list[<role>: <content>]"""
+
     content: str
     instruct_content: BaseModel = field(default=None)
-    role: str = field(default='user')  # system / user / assistant
+    role: str = field(default="user")  # system / user / assistant
     cause_by: Type["Action"] = field(default="")
     sent_from: str = field(default="")
     send_to: str = field(default="")
@@ -39,45 +40,45 @@ class Message:
         return self.__str__()
 
     def to_dict(self) -> dict:
-        return {
-            "role": self.role,
-            "content": self.content
-        }
+        return {"role": self.role, "content": self.content}
 
 
 @dataclass
 class UserMessage(Message):
     """便于支持OpenAI的消息
-       Facilitate support for OpenAI messages
+    Facilitate support for OpenAI messages
     """
+
     def __init__(self, content: str):
-        super().__init__(content, 'user')
+        super().__init__(content, "user")
 
 
 @dataclass
 class SystemMessage(Message):
     """便于支持OpenAI的消息
-       Facilitate support for OpenAI messages
+    Facilitate support for OpenAI messages
     """
+
     def __init__(self, content: str):
-        super().__init__(content, 'system')
+        super().__init__(content, "system")
 
 
 @dataclass
 class AIMessage(Message):
     """便于支持OpenAI的消息
-       Facilitate support for OpenAI messages
+    Facilitate support for OpenAI messages
     """
+
     def __init__(self, content: str):
-        super().__init__(content, 'assistant')
+        super().__init__(content, "assistant")
 
 
-if __name__ == '__main__':
-    test_content = 'test_message'
+if __name__ == "__main__":
+    test_content = "test_message"
     msgs = [
         UserMessage(test_content),
         SystemMessage(test_content),
         AIMessage(test_content),
-        Message(test_content, role='QA')
+        Message(test_content, role="QA"),
     ]
     logger.info(msgs)

metagpt/software_company.py

@@ -21,6 +21,7 @@ class SoftwareCompany(BaseModel):
     Software Company: Possesses a team, SOP (Standard Operating Procedures), and a platform for instant messaging,
     dedicated to writing executable code.
     """
+
     environment: Environment = Field(default_factory=Environment)
     investment: float = Field(default=10.0)
     idea: str = Field(default="")
@@ -36,11 +37,11 @@ class SoftwareCompany(BaseModel):
         """Invest company. raise NoMoneyException when exceed max_budget."""
         self.investment = investment
         CONFIG.max_budget = investment
-        logger.info(f'Investment: ${investment}.')
+        logger.info(f"Investment: ${investment}.")
 
     def _check_balance(self):
         if CONFIG.total_cost > CONFIG.max_budget:
-            raise NoMoneyException(CONFIG.total_cost, f'Insufficient funds: {CONFIG.max_budget}')
+            raise NoMoneyException(CONFIG.total_cost, f"Insufficient funds: {CONFIG.max_budget}")
 
     def start_project(self, idea):
         """Start a project from publishing boss requirement."""
@@ -59,4 +60,3 @@ class SoftwareCompany(BaseModel):
             self._check_balance()
             await self.environment.run()
         return self.environment.history
-    

metagpt/tools/code_interpreter.py

@@ -1,22 +1,26 @@
+import inspect
 import re
-from typing import List, Callable, Dict
+import textwrap
 from pathlib import Path
+from typing import Callable, Dict, List
 
 import wrapt
-import textwrap
-import inspect
 from interpreter.core.core import Interpreter
 
-from metagpt.logs import logger
+from metagpt.actions.clone_function import (
+    CloneFunction,
+    run_function_code,
+    run_function_script,
+)
 from metagpt.config import CONFIG
+from metagpt.logs import logger
 from metagpt.utils.highlight import highlight
-from metagpt.actions.clone_function import CloneFunction, run_function_code, run_function_script
 
 
 def extract_python_code(code: str):
     """Extract code blocks: If the code comments are the same, only the last code block is kept."""
     # Use regular expressions to match comment blocks and related code.
-    pattern = r'(#\s[^\n]*)\n(.*?)(?=\n\s*#|$)'
+    pattern = r"(#\s[^\n]*)\n(.*?)(?=\n\s*#|$)"
     matches = re.findall(pattern, code, re.DOTALL)
 
     # Extract the last code block when encountering the same comment.
@@ -25,8 +29,8 @@ def extract_python_code(code: str):
         unique_comments[comment] = code_block
 
     # concatenate into functional form
-    result_code = '\n'.join([f"{comment}\n{code_block}" for comment, code_block in unique_comments.items()])
-    header_code = code[:code.find("#")]
+    result_code = "\n".join([f"{comment}\n{code_block}" for comment, code_block in unique_comments.items()])
+    header_code = code[: code.find("#")]
     code = header_code + result_code
 
     logger.info(f"Extract python code: \n {highlight(code)}")
@@ -36,6 +40,7 @@ def extract_python_code(code: str):
 
 class OpenCodeInterpreter(object):
     """https://github.com/KillianLucas/open-interpreter"""
+
     def __init__(self, auto_run: bool = True) -> None:
         interpreter = Interpreter()
         interpreter.auto_run = auto_run
@@ -50,15 +55,16 @@ class OpenCodeInterpreter(object):
         return self.interpreter.chat(query)
 
     @staticmethod
-    def extract_function(query_respond: List, function_name: str, *, language: str = 'python',
-                         function_format: str = None) -> str:
+    def extract_function(
+        query_respond: List, function_name: str, *, language: str = "python", function_format: str = None
+    ) -> str:
         """create a function from query_respond."""
-        if language not in ('python'):
+        if language not in ("python"):
             raise NotImplementedError(f"Not support to parse language {language}!")
 
         # set function form
         if function_format is None:
-            assert language == 'python', f"Expect python language for default function_format, but got {language}."
+            assert language == "python", f"Expect python language for default function_format, but got {language}."
             function_format = """def {function_name}():\n{code}"""
         # Extract the code module in the open-interpreter respond message.
         # The query_respond of open-interpreter before v0.1.4 is:
@@ -68,25 +74,29 @@ class OpenCodeInterpreter(object):
         #   "parsed_arguments": {"language": "python", "code": code of first plan}
         #  ...]
         if "function_call" in query_respond[1]:
-            code = [item['function_call']['parsed_arguments']['code'] for item in query_respond
-                    if "function_call" in item
-                    and "parsed_arguments" in item["function_call"]
-                    and 'language' in item["function_call"]['parsed_arguments']
-                    and item["function_call"]['parsed_arguments']['language'] == language]
+            code = [
+                item["function_call"]["parsed_arguments"]["code"]
+                for item in query_respond
+                if "function_call" in item
+                and "parsed_arguments" in item["function_call"]
+                and "language" in item["function_call"]["parsed_arguments"]
+                and item["function_call"]["parsed_arguments"]["language"] == language
+            ]
         # The query_respond of open-interpreter v0.1.7 is:
         # [{'role': 'user', 'message': your query string},
         #  {'role': 'assistant', 'message': plan from llm, 'language': 'python',
         #   'code': code of first plan, 'output': output of first plan code},
         #  ...]
         elif "code" in query_respond[1]:
-            code = [item['code'] for item in query_respond
-                    if "code" in item
-                    and 'language' in item
-                    and item['language'] == language]
+            code = [
+                item["code"]
+                for item in query_respond
+                if "code" in item and "language" in item and item["language"] == language
+            ]
         else:
             raise ValueError(f"Unexpect message format in query_respond: {query_respond[1].keys()}")
         # add indent.
-        indented_code_str = textwrap.indent("\n".join(code), ' ' * 4)
+        indented_code_str = textwrap.indent("\n".join(code), " " * 4)
         # Return the code after deduplication.
         if language == "python":
             return extract_python_code(function_format.format(function_name=function_name, code=indented_code_str))
@@ -115,13 +125,13 @@ class OpenInterpreterDecorator(object):
 
     def _have_code(self, rsp: List[Dict]):
         # Is there any code generated?
-        return 'code' in rsp[1] and rsp[1]['code'] not in ("", None)
+        return "code" in rsp[1] and rsp[1]["code"] not in ("", None)
 
     def _is_faild_plan(self, rsp: List[Dict]):
         # is faild plan?
-        func_code = OpenCodeInterpreter.extract_function(rsp, 'function')
+        func_code = OpenCodeInterpreter.extract_function(rsp, "function")
         # If there is no more than 1 '\n', the plan execution fails.
-        if isinstance(func_code, str) and func_code.count('\n') <= 1:
+        if isinstance(func_code, str) and func_code.count("\n") <= 1:
             return True
         return False
 
@@ -184,4 +194,5 @@ class OpenInterpreterDecorator(object):
                 logger.error(f"Could not evaluate Python code \n{logger_code}: \nError: {e}")
                 raise Exception("Could not evaluate Python code", e)
             return res
+
         return wrapper(wrapped)

metagpt/tools/prompt_writer.py

@@ -10,8 +10,9 @@ from typing import Union
 
 class GPTPromptGenerator:
     """Using LLM, given an output, request LLM to provide input (supporting instruction, chatbot, and query styles)"""
+
     def __init__(self):
-        self._generators = {i: getattr(self, f"gen_{i}_style") for i in ['instruction', 'chatbot', 'query']}
+        self._generators = {i: getattr(self, f"gen_{i}_style") for i in ["instruction", "chatbot", "query"]}
 
     def gen_instruction_style(self, example):
         """Instruction style: Given an output, request LLM to provide input"""
@@ -35,7 +36,7 @@ Query: X
 Document: {example} What is the detailed query X?
 X:"""
 
-    def gen(self, example: str, style: str = 'all') -> Union[list[str], str]:
+    def gen(self, example: str, style: str = "all") -> Union[list[str], str]:
         """
         Generate one or multiple outputs using the example, allowing LLM to reply with the corresponding input
 
@@ -43,7 +44,7 @@ X:"""
         :param style: (all|instruction|chatbot|query)
         :return: Expected LLM input sample (one or multiple)
         """
-        if style != 'all':
+        if style != "all":
             return self._generators[style](example)
         return [f(example) for f in self._generators.values()]
 

metagpt/tools/sd_engine.py

@@ -120,11 +120,13 @@ def decode_base64_to_image(img, save_name):
     image.save(f"{save_name}.png", pnginfo=pnginfo)
     return pnginfo, image
 
+
 def batch_decode_base64_to_image(imgs, save_dir="", save_name=""):
     for idx, _img in enumerate(imgs):
         save_name = join(save_dir, save_name)
         decode_base64_to_image(_img, save_name=save_name)
 
+
 if __name__ == "__main__":
     engine = SDEngine()
     prompt = "pixel style, game design, a game interface should be minimalistic and intuitive with the score and high score displayed at the top. The snake and its food should be easily distinguishable. The game should have a simple color scheme, with a contrasting color for the snake and its food. Complete interface boundary"

metagpt/tools/search_engine.py

@@ -6,7 +6,7 @@
 @File    : search_engine.py
 """
 import importlib
-from typing import Callable, Coroutine, Literal, overload, Optional, Union
+from typing import Callable, Coroutine, Literal, Optional, Union, overload
 
 from semantic_kernel.skill_definition import sk_function
 
@@ -43,8 +43,8 @@ class SearchEngine:
 
     def __init__(
         self,
-            engine: Optional[SearchEngineType] = None,
-            run_func: Callable[[str, int, bool], Coroutine[None, None, Union[str, list[str]]]] = None,
+        engine: Optional[SearchEngineType] = None,
+        run_func: Callable[[str, int, bool], Coroutine[None, None, Union[str, list[str]]]] = None,
     ):
         engine = engine or CONFIG.search_engine
         if engine == SearchEngineType.SERPAPI_GOOGLE:

metagpt/tools/search_engine_meilisearch.py

@@ -29,7 +29,7 @@ class MeilisearchEngine:
     def add_documents(self, data_source: DataSource, documents: List[dict]):
         index_name = f"{data_source.name}_index"
         if index_name not in self.client.get_indexes():
-            self.client.create_index(uid=index_name, options={'primaryKey': 'id'})
+            self.client.create_index(uid=index_name, options={"primaryKey": "id"})
         index = self.client.get_index(index_name)
         index.add_documents(documents)
         self.set_index(index)
@@ -37,7 +37,7 @@ class MeilisearchEngine:
     def search(self, query):
         try:
             search_results = self._index.search(query)
-            return search_results['hits']
+            return search_results["hits"]
         except Exception as e:
             # Handle MeiliSearch API errors
             print(f"MeiliSearch API error: {e}")

metagpt/tools/translator.py

@@ -6,7 +6,7 @@
 @File    : translator.py
 """
 
-prompt = '''
+prompt = """
 # 指令
 接下来，作为一位拥有20年翻译经验的翻译专家，当我给出英文句子或段落时，你将提供通顺且具有可读性的{LANG}翻译。注意以下要求：
 1. 确保翻译结果流畅且易于理解
@@ -17,11 +17,10 @@ prompt = '''
 {ORIGINAL}
 
 # 译文
-'''
+"""
 
 
 class Translator:
-
     @classmethod
-    def translate_prompt(cls, original, lang='中文'):
-        return prompt.format(LANG=lang, ORIGINAL=original)
+    def translate_prompt(cls, original, lang="中文"):
+        return prompt.format(LANG=lang, ORIGINAL=original)

metagpt/tools/ut_writer.py

@@ -6,7 +6,7 @@ from pathlib import Path
 
 from metagpt.provider.openai_api import OpenAIGPTAPI as GPTAPI
 
-ICL_SAMPLE = '''Interface definition:
+ICL_SAMPLE = """Interface definition:
 ```text
 Interface Name: Element Tagging
 Interface Path: /projects/{project_key}/node-tags
@@ -60,20 +60,20 @@ def test_node_tags(project_key, nodes, operations, expected_msg):
 # 3. If comments are needed, use Chinese.
 
 # If you understand, please wait for me to give the interface definition and just answer "Understood" to save tokens.
-'''
+"""
 
-ACT_PROMPT_PREFIX = '''Refer to the test types: such as missing request parameters, field boundary verification, incorrect field type.
+ACT_PROMPT_PREFIX = """Refer to the test types: such as missing request parameters, field boundary verification, incorrect field type.
 Please output 10 test cases within one `@pytest.mark.parametrize` scope.
 ```text
-'''
+"""
 
-YFT_PROMPT_PREFIX = '''Refer to the test types: such as SQL injection, cross-site scripting (XSS), unauthorized access and privilege escalation, 
+YFT_PROMPT_PREFIX = """Refer to the test types: such as SQL injection, cross-site scripting (XSS), unauthorized access and privilege escalation, 
 authentication and authorization, parameter verification, exception handling, file upload and download.
 Please output 10 test cases within one `@pytest.mark.parametrize` scope.
 ```text
-'''
+"""
 
-OCR_API_DOC = '''```text
+OCR_API_DOC = """```text
 Interface Name: OCR recognition
 Interface Path: /api/v1/contract/treaty/task/ocr
 Method: POST
@@ -96,14 +96,20 @@ code	integer	Yes
 message	string	Yes		
 data	object	Yes		
 ```
-'''
+"""
 
 
 class UTGenerator:
     """UT Generator: Construct UT through API documentation"""
 
-    def __init__(self, swagger_file: str, ut_py_path: str, questions_path: str,
-                 chatgpt_method: str = "API", template_prefix=YFT_PROMPT_PREFIX) -> None:
+    def __init__(
+        self,
+        swagger_file: str,
+        ut_py_path: str,
+        questions_path: str,
+        chatgpt_method: str = "API",
+        template_prefix=YFT_PROMPT_PREFIX,
+    ) -> None:
         """Initialize UT Generator
 
         Args:
@@ -274,7 +280,7 @@ class UTGenerator:
 
     def gpt_msgs_to_code(self, messages: list) -> str:
         """Choose based on different calling methods"""
-        result = ''
+        result = ""
         if self.chatgpt_method == "API":
             result = GPTAPI().ask_code(msgs=messages)
 

metagpt/utils/file.py

@@ -6,9 +6,10 @@
 @File    : file.py
 @Describe : General file operations.
 """
-import aiofiles
 from pathlib import Path
 
+import aiofiles
+
 from metagpt.logs import logger
 
 
@@ -66,10 +67,9 @@ class File:
                     if not chunk:
                         break
                     chunks.append(chunk)
-                content = b''.join(chunks)
+                content = b"".join(chunks)
                 logger.debug(f"Successfully read file, the path of file: {file_path}")
                 return content
         except Exception as e:
             logger.error(f"Error reading file: {e}")
             raise e
-

metagpt/utils/highlight.py

@@ -1,22 +1,22 @@
 # 添加代码语法高亮显示
 from pygments import highlight as highlight_
+from pygments.formatters import HtmlFormatter, TerminalFormatter
 from pygments.lexers import PythonLexer, SqlLexer
-from pygments.formatters import TerminalFormatter, HtmlFormatter
 
 
-def highlight(code: str, language: str = 'python', formatter: str = 'terminal'):
+def highlight(code: str, language: str = "python", formatter: str = "terminal"):
     # 指定要高亮的语言
-    if language.lower() == 'python':
+    if language.lower() == "python":
         lexer = PythonLexer()
-    elif language.lower() == 'sql':
+    elif language.lower() == "sql":
         lexer = SqlLexer()
     else:
         raise ValueError(f"Unsupported language: {language}")
 
     # 指定输出格式
-    if formatter.lower() == 'terminal':
+    if formatter.lower() == "terminal":
         formatter = TerminalFormatter()
-    elif formatter.lower() == 'html':
+    elif formatter.lower() == "html":
         formatter = HtmlFormatter()
     else:
         raise ValueError(f"Unsupported formatter: {formatter}")

metagpt/utils/mmdc_ink.py

@@ -6,9 +6,9 @@
 @File    : mermaid.py
 """
 import base64
-import os
 
-from aiohttp import ClientSession,ClientError
+from aiohttp import ClientError, ClientSession
+
 from metagpt.logs import logger
 
 
@@ -29,7 +29,7 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix):
                 async with session.get(url) as response:
                     if response.status == 200:
                         text = await response.content.read()
-                        with open(output_file, 'wb') as f:
+                        with open(output_file, "wb") as f:
                             f.write(text)
                         logger.info(f"Generating {output_file}..")
                     else:

metagpt/utils/mmdc_playwright.py

@@ -8,10 +8,13 @@
 
 import os
 from urllib.parse import urljoin
+
 from playwright.async_api import async_playwright
+
 from metagpt.logs import logger
 
-async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048, height=2048)-> int:
+
+async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048, height=2048) -> int:
     """
     Converts the given Mermaid code to various output formats and saves them to files.
 
@@ -24,66 +27,72 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
     Returns:
         int: Returns 1 if the conversion and saving were successful, -1 otherwise.
     """
-    suffixes=['png', 'svg', 'pdf']
+    suffixes = ["png", "svg", "pdf"]
     __dirname = os.path.dirname(os.path.abspath(__file__))
 
     async with async_playwright() as p:
         browser = await p.chromium.launch()
         device_scale_factor = 1.0
         context = await browser.new_context(
-                viewport={'width': width, 'height': height},
-                device_scale_factor=device_scale_factor,
-            )
+            viewport={"width": width, "height": height},
+            device_scale_factor=device_scale_factor,
+        )
         page = await context.new_page()
 
         async def console_message(msg):
             logger.info(msg.text)
-        page.on('console', console_message)
+
+        page.on("console", console_message)
 
         try:
-            await page.set_viewport_size({'width': width, 'height': height})
+            await page.set_viewport_size({"width": width, "height": height})
 
-            mermaid_html_path = os.path.abspath(
-                os.path.join(__dirname, 'index.html'))
-            mermaid_html_url = urljoin('file:', mermaid_html_path)
+            mermaid_html_path = os.path.abspath(os.path.join(__dirname, "index.html"))
+            mermaid_html_url = urljoin("file:", mermaid_html_path)
             await page.goto(mermaid_html_url)
             await page.wait_for_load_state("networkidle")
 
             await page.wait_for_selector("div#container", state="attached")
-            mermaid_config = {}
+            # mermaid_config = {}
             background_color = "#ffffff"
-            my_css = ""
+            # my_css = ""
             await page.evaluate(f'document.body.style.background = "{background_color}";')
 
-            metadata = await page.evaluate('''async ([definition, mermaidConfig, myCSS, backgroundColor]) => {
-                const { mermaid, zenuml } = globalThis;
-                await mermaid.registerExternalDiagrams([zenuml]);
-                mermaid.initialize({ startOnLoad: false, ...mermaidConfig });
-                const { svg } = await mermaid.render('my-svg', definition, document.getElementById('container'));
-                document.getElementById('container').innerHTML = svg;
-                const svgElement = document.querySelector('svg');
-                svgElement.style.backgroundColor = backgroundColor;
+            # metadata = await page.evaluate(
+            #     """async ([definition, mermaidConfig, myCSS, backgroundColor]) => {
+            #     const { mermaid, zenuml } = globalThis;
+            #     await mermaid.registerExternalDiagrams([zenuml]);
+            #     mermaid.initialize({ startOnLoad: false, ...mermaidConfig });
+            #     const { svg } = await mermaid.render('my-svg', definition, document.getElementById('container'));
+            #     document.getElementById('container').innerHTML = svg;
+            #     const svgElement = document.querySelector('svg');
+            #     svgElement.style.backgroundColor = backgroundColor;
+            #
+            #     if (myCSS) {
+            #         const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
+            #         style.appendChild(document.createTextNode(myCSS));
+            #         svgElement.appendChild(style);
+            #     }
+            #
+            # }""",
+            #     [mermaid_code, mermaid_config, my_css, background_color],
+            # )
 
-                if (myCSS) {
-                    const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
-                    style.appendChild(document.createTextNode(myCSS));
-                    svgElement.appendChild(style);
-                }
-
-            }''', [mermaid_code, mermaid_config, my_css, background_color])
-
-            if 'svg' in suffixes :
-                svg_xml = await page.evaluate('''() => {
+            if "svg" in suffixes:
+                svg_xml = await page.evaluate(
+                    """() => {
                     const svg = document.querySelector('svg');
                     const xmlSerializer = new XMLSerializer();
                     return xmlSerializer.serializeToString(svg);
-                }''')
+                }"""
+                )
                 logger.info(f"Generating {output_file_without_suffix}.svg..")
-                with open(f'{output_file_without_suffix}.svg', 'wb') as f:
-                    f.write(svg_xml.encode('utf-8'))
+                with open(f"{output_file_without_suffix}.svg", "wb") as f:
+                    f.write(svg_xml.encode("utf-8"))
 
-            if  'png' in suffixes:
-                clip = await page.evaluate('''() => {
+            if "png" in suffixes:
+                clip = await page.evaluate(
+                    """() => {
                     const svg = document.querySelector('svg');
                     const rect = svg.getBoundingClientRect();
                     return {
@@ -92,16 +101,17 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
                         width: Math.ceil(rect.width),
                         height: Math.ceil(rect.height)
                     };
-                }''')
-                await page.set_viewport_size({'width': clip['x'] + clip['width'], 'height': clip['y'] + clip['height']})
-                screenshot = await page.screenshot(clip=clip, omit_background=True, scale='device')
+                }"""
+                )
+                await page.set_viewport_size({"width": clip["x"] + clip["width"], "height": clip["y"] + clip["height"]})
+                screenshot = await page.screenshot(clip=clip, omit_background=True, scale="device")
                 logger.info(f"Generating {output_file_without_suffix}.png..")
-                with open(f'{output_file_without_suffix}.png', 'wb') as f:
+                with open(f"{output_file_without_suffix}.png", "wb") as f:
                     f.write(screenshot)
-            if 'pdf' in suffixes:
+            if "pdf" in suffixes:
                 pdf_data = await page.pdf(scale=device_scale_factor)
                 logger.info(f"Generating {output_file_without_suffix}.pdf..")
-                with open(f'{output_file_without_suffix}.pdf', 'wb') as f:
+                with open(f"{output_file_without_suffix}.pdf", "wb") as f:
                     f.write(pdf_data)
             return 0
         except Exception as e:

metagpt/utils/mmdc_pyppeteer.py

@@ -7,11 +7,14 @@
 """
 import os
 from urllib.parse import urljoin
-from pyppeteer import launch
-from metagpt.logs import logger
-from metagpt.config import CONFIG
 
-async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048, height=2048)-> int:
+from pyppeteer import launch
+
+from metagpt.config import CONFIG
+from metagpt.logs import logger
+
+
+async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048, height=2048) -> int:
     """
     Converts the given Mermaid code to various output formats and saves them to files.
 
@@ -24,15 +27,15 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
     Returns:
         int: Returns 1 if the conversion and saving were successful, -1 otherwise.
     """
-    suffixes = ['png', 'svg', 'pdf']   
+    suffixes = ["png", "svg", "pdf"]
     __dirname = os.path.dirname(os.path.abspath(__file__))
 
-    
     if CONFIG.pyppeteer_executable_path:
-        browser = await launch(headless=True,
-                            executablePath=CONFIG.pyppeteer_executable_path,
-                            args=['--disable-extensions',"--no-sandbox"] 
-                            )
+        browser = await launch(
+            headless=True,
+            executablePath=CONFIG.pyppeteer_executable_path,
+            args=["--disable-extensions", "--no-sandbox"],
+        )
     else:
         logger.error("Please set the environment variable:PYPPETEER_EXECUTABLE_PATH.")
         return -1
@@ -41,50 +44,56 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
 
     async def console_message(msg):
         logger.info(msg.text)
-    page.on('console', console_message)
+
+    page.on("console", console_message)
 
     try:
-        await page.setViewport(viewport={'width': width, 'height': height, 'deviceScaleFactor': device_scale_factor})
+        await page.setViewport(viewport={"width": width, "height": height, "deviceScaleFactor": device_scale_factor})
 
-        mermaid_html_path = os.path.abspath(
-            os.path.join(__dirname, 'index.html'))
-        mermaid_html_url = urljoin('file:', mermaid_html_path)
+        mermaid_html_path = os.path.abspath(os.path.join(__dirname, "index.html"))
+        mermaid_html_url = urljoin("file:", mermaid_html_path)
         await page.goto(mermaid_html_url)
 
         await page.querySelector("div#container")
-        mermaid_config = {}
+        # mermaid_config = {}
         background_color = "#ffffff"
-        my_css = ""
+        # my_css = ""
         await page.evaluate(f'document.body.style.background = "{background_color}";')
 
-        metadata = await page.evaluate('''async ([definition, mermaidConfig, myCSS, backgroundColor]) => {
-            const { mermaid, zenuml } = globalThis;
-            await mermaid.registerExternalDiagrams([zenuml]);
-            mermaid.initialize({ startOnLoad: false, ...mermaidConfig });
-            const { svg } = await mermaid.render('my-svg', definition, document.getElementById('container'));
-            document.getElementById('container').innerHTML = svg;
-            const svgElement = document.querySelector('svg');
-            svgElement.style.backgroundColor = backgroundColor;
+        # metadata = await page.evaluate(
+        #     """async ([definition, mermaidConfig, myCSS, backgroundColor]) => {
+        #     const { mermaid, zenuml } = globalThis;
+        #     await mermaid.registerExternalDiagrams([zenuml]);
+        #     mermaid.initialize({ startOnLoad: false, ...mermaidConfig });
+        #     const { svg } = await mermaid.render('my-svg', definition, document.getElementById('container'));
+        #     document.getElementById('container').innerHTML = svg;
+        #     const svgElement = document.querySelector('svg');
+        #     svgElement.style.backgroundColor = backgroundColor;
+        #
+        #     if (myCSS) {
+        #         const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
+        #         style.appendChild(document.createTextNode(myCSS));
+        #         svgElement.appendChild(style);
+        #     }
+        # }""",
+        #     [mermaid_code, mermaid_config, my_css, background_color],
+        # )
 
-            if (myCSS) {
-                const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
-                style.appendChild(document.createTextNode(myCSS));
-                svgElement.appendChild(style);
-            }
-        }''', [mermaid_code, mermaid_config, my_css, background_color])
-
-        if 'svg' in suffixes :
-            svg_xml = await page.evaluate('''() => {
+        if "svg" in suffixes:
+            svg_xml = await page.evaluate(
+                """() => {
                 const svg = document.querySelector('svg');
                 const xmlSerializer = new XMLSerializer();
                 return xmlSerializer.serializeToString(svg);
-            }''')
+            }"""
+            )
             logger.info(f"Generating {output_file_without_suffix}.svg..")
-            with open(f'{output_file_without_suffix}.svg', 'wb') as f:
-                f.write(svg_xml.encode('utf-8'))
+            with open(f"{output_file_without_suffix}.svg", "wb") as f:
+                f.write(svg_xml.encode("utf-8"))
 
-        if  'png' in suffixes:
-            clip = await page.evaluate('''() => {
+        if "png" in suffixes:
+            clip = await page.evaluate(
+                """() => {
                 const svg = document.querySelector('svg');
                 const rect = svg.getBoundingClientRect();
                 return {
@@ -93,16 +102,23 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
                     width: Math.ceil(rect.width),
                     height: Math.ceil(rect.height)
                 };
-            }''')
-            await page.setViewport({'width': clip['x'] + clip['width'], 'height': clip['y'] + clip['height'], 'deviceScaleFactor': device_scale_factor})
-            screenshot = await page.screenshot(clip=clip, omit_background=True, scale='device')
+            }"""
+            )
+            await page.setViewport(
+                {
+                    "width": clip["x"] + clip["width"],
+                    "height": clip["y"] + clip["height"],
+                    "deviceScaleFactor": device_scale_factor,
+                }
+            )
+            screenshot = await page.screenshot(clip=clip, omit_background=True, scale="device")
             logger.info(f"Generating {output_file_without_suffix}.png..")
-            with open(f'{output_file_without_suffix}.png', 'wb') as f:
+            with open(f"{output_file_without_suffix}.png", "wb") as f:
                 f.write(screenshot)
-        if 'pdf' in suffixes:
+        if "pdf" in suffixes:
             pdf_data = await page.pdf(scale=device_scale_factor)
             logger.info(f"Generating {output_file_without_suffix}.pdf..")
-            with open(f'{output_file_without_suffix}.pdf', 'wb') as f:
+            with open(f"{output_file_without_suffix}.pdf", "wb") as f:
                 f.write(pdf_data)
         return 0
     except Exception as e:
@@ -110,4 +126,3 @@ async def mermaid_to_file(mermaid_code, output_file_without_suffix, width=2048,
         return -1
     finally:
         await browser.close()
-

metagpt/utils/parse_html.py

@@ -16,7 +16,7 @@ class WebPage(BaseModel):
     class Config:
         underscore_attrs_are_private = True
 
-    _soup : Optional[BeautifulSoup] = None
+    _soup: Optional[BeautifulSoup] = None
     _title: Optional[str] = None
 
     @property
@@ -24,7 +24,7 @@ class WebPage(BaseModel):
         if self._soup is None:
             self._soup = BeautifulSoup(self.html, "html.parser")
         return self._soup
-    
+
     @property
     def title(self):
         if self._title is None:

metagpt/utils/pycst.py

@@ -37,12 +37,12 @@ def get_docstring_statement(body: DocstringNode) -> cst.SimpleStatementLine:
 
     if not isinstance(expr, cst.Expr):
         return None
-    
+
     val = expr.value
     if not isinstance(val, (cst.SimpleString, cst.ConcatenatedString)):
         return None
-    
-    evaluated_value = val.evaluated_value    
+
+    evaluated_value = val.evaluated_value
     if isinstance(evaluated_value, bytes):
         return None
 
@@ -56,6 +56,7 @@ class DocstringCollector(cst.CSTVisitor):
         stack: A list to keep track of the current path in the CST.
         docstrings: A dictionary mapping paths in the CST to their corresponding docstrings.
     """
+
     def __init__(self):
         self.stack: list[str] = []
         self.docstrings: dict[tuple[str, ...], cst.SimpleStatementLine] = {}
@@ -96,6 +97,7 @@ class DocstringTransformer(cst.CSTTransformer):
         stack: A list to keep track of the current path in the CST.
         docstrings: A dictionary mapping paths in the CST to their corresponding docstrings.
     """
+
     def __init__(
         self,
         docstrings: dict[tuple[str, ...], cst.SimpleStatementLine],
@@ -125,7 +127,9 @@ class DocstringTransformer(cst.CSTTransformer):
         key = tuple(self.stack)
         self.stack.pop()
 
-        if hasattr(updated_node, "decorators") and any((i.decorator.value == "overload") for i in updated_node.decorators):
+        if hasattr(updated_node, "decorators") and any(
+            (i.decorator.value == "overload") for i in updated_node.decorators
+        ):
             return updated_node
 
         statement = self.docstrings.get(key)

metagpt/utils/read_document.py

@@ -8,6 +8,7 @@
 
 import docx
 
+
 def read_docx(file_path: str) -> list:
     """Open a docx file"""
     doc = docx.Document(file_path)

metagpt/utils/singleton.py

@@ -20,4 +20,3 @@ class Singleton(abc.ABCMeta, type):
         if cls not in cls._instances:
             cls._instances[cls] = super(Singleton, cls).__call__(*args, **kwargs)
         return cls._instances[cls]
-    

metagpt/utils/special_tokens.py

@@ -1,4 +1,4 @@
 # token to separate different code messages in a WriteCode Message content
-MSG_SEP = "#*000*#" 
+MSG_SEP = "#*000*#"
 # token to seperate file name and the actual code text in a code message
 FILENAME_CODE_SEP = "#*001*#"

metagpt/utils/text.py

@@ -3,7 +3,12 @@ from typing import Generator, Sequence
 from metagpt.utils.token_counter import TOKEN_MAX, count_string_tokens
 
 
-def reduce_message_length(msgs: Generator[str, None, None], model_name: str, system_text: str, reserved: int = 0,) -> str:
+def reduce_message_length(
+    msgs: Generator[str, None, None],
+    model_name: str,
+    system_text: str,
+    reserved: int = 0,
+) -> str:
     """Reduce the length of concatenated message segments to fit within the maximum token size.
 
     Args:
@@ -49,9 +54,9 @@ def generate_prompt_chunk(
     current_token = 0
     current_lines = []
 
-    reserved = reserved + count_string_tokens(prompt_template+system_text, model_name)
+    reserved = reserved + count_string_tokens(prompt_template + system_text, model_name)
     # 100 is a magic number to ensure the maximum context length is not exceeded
-    max_token = TOKEN_MAX.get(model_name, 2048) - reserved - 100  
+    max_token = TOKEN_MAX.get(model_name, 2048) - reserved - 100
 
     while paragraphs:
         paragraph = paragraphs.pop(0)
@@ -103,7 +108,7 @@ def decode_unicode_escape(text: str) -> str:
     return text.encode("utf-8").decode("unicode_escape", "ignore")
 
 
-def _split_by_count(lst: Sequence , count: int):
+def _split_by_count(lst: Sequence, count: int):
     avg = len(lst) // count
     remainder = len(lst) % count
     start = 0

requirements.txt

@@ -44,3 +44,4 @@ ta==0.10.2
 semantic-kernel==0.3.13.dev0
 wrapt==1.15.0
 websocket-client==0.58.0
+

tests/conftest.py

@@ -6,14 +6,14 @@
 @File    : conftest.py
 """
 
+import asyncio
+import re
 from unittest.mock import Mock
 
 import pytest
 
 from metagpt.logs import logger
 from metagpt.provider.openai_api import OpenAIGPTAPI as GPTAPI
-import asyncio
-import re
 
 
 class Context:

tests/metagpt/actions/mock.py

@@ -311,12 +311,10 @@ TASKS = [
     "添加数据API：接受用户输入的文档库，对文档库进行索引\n- 使用MeiliSearch连接并添加文档库",
     "搜索API：接收用户输入的关键词，返回相关的搜索结果\n- 使用MeiliSearch连接并使用接口获得对应数据",
     "多条件筛选API：接收用户选择的筛选条件，返回符合条件的搜索结果。\n- 使用MeiliSearch进行筛选并返回符合条件的搜索结果",
-    "智能推荐API：根据用户的搜索历史记录和搜索行为，推荐相关的搜索结果。"
+    "智能推荐API：根据用户的搜索历史记录和搜索行为，推荐相关的搜索结果。",
 ]
 
-TASKS_2 = [
-    "完成main.py的功能"
-]
+TASKS_2 = ["完成main.py的功能"]
 
 SEARCH_CODE_SAMPLE = """
 import requests
@@ -460,7 +458,7 @@ if __name__ == '__main__':
         print('No results found.')
 '''
 
-MEILI_CODE = '''import meilisearch
+MEILI_CODE = """import meilisearch
 from typing import List
 
 
@@ -496,9 +494,9 @@ if __name__ == '__main__':
 
     # 添加文档库到搜索引擎
     search_engine.add_documents(books_data_source, documents)
-'''
+"""
 
-MEILI_ERROR = '''/usr/local/bin/python3.9 /Users/alexanderwu/git/metagpt/examples/search/meilisearch_index.py
+MEILI_ERROR = """/usr/local/bin/python3.9 /Users/alexanderwu/git/metagpt/examples/search/meilisearch_index.py
 Traceback (most recent call last):
   File "/Users/alexanderwu/git/metagpt/examples/search/meilisearch_index.py", line 44, in <module>
     search_engine.add_documents(books_data_source, documents)
@@ -506,7 +504,7 @@ Traceback (most recent call last):
     index = self.client.get_or_create_index(index_name)
 AttributeError: 'Client' object has no attribute 'get_or_create_index'
 
-Process finished with exit code 1'''
+Process finished with exit code 1"""
 
 MEILI_CODE_REFINED = """
 """

tests/metagpt/actions/test_action_output.py

@@ -9,18 +9,21 @@ from typing import List, Tuple
 
 from metagpt.actions import ActionOutput
 
-t_dict = {"Required Python third-party packages": "\"\"\"\nflask==1.1.2\npygame==2.0.1\n\"\"\"\n",
-          "Required Other language third-party packages": "\"\"\"\nNo third-party packages required for other languages.\n\"\"\"\n",
-          "Full API spec": "\"\"\"\nopenapi: 3.0.0\ninfo:\n  title: Web Snake Game API\n  version: 1.0.0\npaths:\n  /game:\n    get:\n      summary: Get the current game state\n      responses:\n        '200':\n          description: A JSON object of the game state\n    post:\n      summary: Send a command to the game\n      requestBody:\n        required: true\n        content:\n          application/json:\n            schema:\n              type: object\n              properties:\n                command:\n                  type: string\n      responses:\n        '200':\n          description: A JSON object of the updated game state\n\"\"\"\n",
-          "Logic Analysis": [
-              ["app.py", "Main entry point for the Flask application. Handles HTTP requests and responses."],
-              ["game.py", "Contains the Game and Snake classes. Handles the game logic."],
-              ["static/js/script.js", "Handles user interactions and updates the game UI."],
-              ["static/css/styles.css", "Defines the styles for the game UI."],
-              ["templates/index.html", "The main page of the web application. Displays the game UI."]],
-          "Task list": ["game.py", "app.py", "static/css/styles.css", "static/js/script.js", "templates/index.html"],
-          "Shared Knowledge": "\"\"\"\n'game.py' contains the Game and Snake classes which are responsible for the game logic. The Game class uses an instance of the Snake class.\n\n'app.py' is the main entry point for the Flask application. It creates an instance of the Game class and handles HTTP requests and responses.\n\n'static/js/script.js' is responsible for handling user interactions and updating the game UI based on the game state returned by 'app.py'.\n\n'static/css/styles.css' defines the styles for the game UI.\n\n'templates/index.html' is the main page of the web application. It displays the game UI and loads 'static/js/script.js' and 'static/css/styles.css'.\n\"\"\"\n",
-          "Anything UNCLEAR": "We need clarification on how the high score should be stored. Should it persist across sessions (stored in a database or a file) or should it reset every time the game is restarted? Also, should the game speed increase as the snake grows, or should it remain constant throughout the game?"}
+t_dict = {
+    "Required Python third-party packages": '"""\nflask==1.1.2\npygame==2.0.1\n"""\n',
+    "Required Other language third-party packages": '"""\nNo third-party packages required for other languages.\n"""\n',
+    "Full API spec": '"""\nopenapi: 3.0.0\ninfo:\n  title: Web Snake Game API\n  version: 1.0.0\npaths:\n  /game:\n    get:\n      summary: Get the current game state\n      responses:\n        \'200\':\n          description: A JSON object of the game state\n    post:\n      summary: Send a command to the game\n      requestBody:\n        required: true\n        content:\n          application/json:\n            schema:\n              type: object\n              properties:\n                command:\n                  type: string\n      responses:\n        \'200\':\n          description: A JSON object of the updated game state\n"""\n',
+    "Logic Analysis": [
+        ["app.py", "Main entry point for the Flask application. Handles HTTP requests and responses."],
+        ["game.py", "Contains the Game and Snake classes. Handles the game logic."],
+        ["static/js/script.js", "Handles user interactions and updates the game UI."],
+        ["static/css/styles.css", "Defines the styles for the game UI."],
+        ["templates/index.html", "The main page of the web application. Displays the game UI."],
+    ],
+    "Task list": ["game.py", "app.py", "static/css/styles.css", "static/js/script.js", "templates/index.html"],
+    "Shared Knowledge": "\"\"\"\n'game.py' contains the Game and Snake classes which are responsible for the game logic. The Game class uses an instance of the Snake class.\n\n'app.py' is the main entry point for the Flask application. It creates an instance of the Game class and handles HTTP requests and responses.\n\n'static/js/script.js' is responsible for handling user interactions and updating the game UI based on the game state returned by 'app.py'.\n\n'static/css/styles.css' defines the styles for the game UI.\n\n'templates/index.html' is the main page of the web application. It displays the game UI and loads 'static/js/script.js' and 'static/css/styles.css'.\n\"\"\"\n",
+    "Anything UNCLEAR": "We need clarification on how the high score should be stored. Should it persist across sessions (stored in a database or a file) or should it reset every time the game is restarted? Also, should the game speed increase as the snake grows, or should it remain constant throughout the game?",
+}
 
 WRITE_TASKS_OUTPUT_MAPPING = {
     "Required Python third-party packages": (str, ...),
@@ -45,6 +48,6 @@ def test_create_model_class_with_mapping():
     assert value == ["game.py", "app.py", "static/css/styles.css", "static/js/script.js", "templates/index.html"]
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     test_create_model_class()
     test_create_model_class_with_mapping()

tests/metagpt/actions/test_azure_tts.py

@@ -10,12 +10,7 @@ from metagpt.actions.azure_tts import AzureTTS
 
 def test_azure_tts():
     azure_tts = AzureTTS("azure_tts")
-    azure_tts.synthesize_speech(
-        "zh-CN",
-        "zh-CN-YunxiNeural",
-        "Boy",
-        "你好，我是卡卡",
-        "output.wav")
+    azure_tts.synthesize_speech("zh-CN", "zh-CN-YunxiNeural", "Boy", "你好，我是卡卡", "output.wav")
 
     # 运行需要先配置 SUBSCRIPTION_KEY
     # TODO: 这里如果要检验，还要额外加上对应的asr，才能确保前后生成是接近一致的，但现在还没有

tests/metagpt/actions/test_clone_function.py

@@ -2,7 +2,6 @@ import pytest
 
 from metagpt.actions.clone_function import CloneFunction, run_function_code
 
-
 source_code = """
 import pandas as pd
 import ta
@@ -31,14 +30,18 @@ def get_expected_res():
     import ta
 
     # 读取股票数据
-    stock_data = pd.read_csv('./tests/data/baba_stock.csv')
+    stock_data = pd.read_csv("./tests/data/baba_stock.csv")
     stock_data.head()
     # 计算简单移动平均线
-    stock_data['SMA'] = ta.trend.sma_indicator(stock_data['Close'], window=6)
-    stock_data[['Date', 'Close', 'SMA']].head()
+    stock_data["SMA"] = ta.trend.sma_indicator(stock_data["Close"], window=6)
+    stock_data[["Date", "Close", "SMA"]].head()
     # 计算布林带
-    stock_data['bb_upper'], stock_data['bb_middle'], stock_data['bb_lower'] = ta.volatility.bollinger_hband_indicator(stock_data['Close'], window=20), ta.volatility.bollinger_mavg(stock_data['Close'], window=20), ta.volatility.bollinger_lband_indicator(stock_data['Close'], window=20)
-    stock_data[['Date', 'Close', 'bb_upper', 'bb_middle', 'bb_lower']].head()
+    stock_data["bb_upper"], stock_data["bb_middle"], stock_data["bb_lower"] = (
+        ta.volatility.bollinger_hband_indicator(stock_data["Close"], window=20),
+        ta.volatility.bollinger_mavg(stock_data["Close"], window=20),
+        ta.volatility.bollinger_lband_indicator(stock_data["Close"], window=20),
+    )
+    stock_data[["Date", "Close", "bb_upper", "bb_middle", "bb_lower"]].head()
     return stock_data
 
 
@@ -46,9 +49,9 @@ def get_expected_res():
 async def test_clone_function():
     clone = CloneFunction()
     code = await clone.run(template_code, source_code)
-    assert 'def ' in code
-    stock_path = './tests/data/baba_stock.csv'
-    df, msg = run_function_code(code, 'stock_indicator', stock_path)
+    assert "def " in code
+    stock_path = "./tests/data/baba_stock.csv"
+    df, msg = run_function_code(code, "stock_indicator", stock_path)
     assert not msg
     expected_df = get_expected_res()
     assert df.equals(expected_df)

tests/metagpt/actions/test_debug_error.py

@@ -144,12 +144,12 @@ Engineer
 ---
 '''
 
+
 @pytest.mark.asyncio
 async def test_debug_error():
-
     debug_error = DebugError("debug_error")
 
     file_name, rewritten_code = await debug_error.run(context=EXAMPLE_MSG_CONTENT)
 
-    assert "class Player" in rewritten_code # rewrite the same class
-    assert "while self.score > 21" in rewritten_code # a key logic to rewrite to (original one is "if self.score > 12")
+    assert "class Player" in rewritten_code  # rewrite the same class
+    assert "while self.score > 21" in rewritten_code  # a key logic to rewrite to (original one is "if self.score > 12")

tests/metagpt/actions/test_detail_mining.py

@@ -10,6 +10,7 @@ import pytest
 from metagpt.actions.detail_mining import DetailMining
 from metagpt.logs import logger
 
+
 @pytest.mark.asyncio
 async def test_detail_mining():
     topic = "如何做一个生日蛋糕"
@@ -17,7 +18,6 @@ async def test_detail_mining():
     detail_mining = DetailMining("detail_mining")
     rsp = await detail_mining.run(topic=topic, record=record)
     logger.info(f"{rsp.content=}")
-    
-    assert '##OUTPUT' in rsp.content
-    assert '蛋糕' in rsp.content
 
+    assert "##OUTPUT" in rsp.content
+    assert "蛋糕" in rsp.content

tests/metagpt/actions/test_invoice_ocr.py

@@ -8,12 +8,11 @@
 """
 
 import os
-from typing import List
-
-import pytest
 from pathlib import Path
 
-from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
+import pytest
+
+from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, ReplyQuestion
 
 
 @pytest.mark.asyncio
@@ -22,7 +21,7 @@ from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
     [
         "../../data/invoices/invoice-3.jpg",
         "../../data/invoices/invoice-4.zip",
-    ]
+    ],
 )
 async def test_invoice_ocr(invoice_path: str):
     invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
@@ -35,18 +34,8 @@ async def test_invoice_ocr(invoice_path: str):
 @pytest.mark.parametrize(
     ("invoice_path", "expected_result"),
     [
-        (
-            "../../data/invoices/invoice-1.pdf",
-            [
-                {
-                    "收款人": "小明",
-                    "城市": "深圳市",
-                    "总费用/元": "412.00",
-                    "开票日期": "2023年02月03日"
-                }
-            ]
-        ),
-    ]
+        ("../../data/invoices/invoice-1.pdf", [{"收款人": "小明", "城市": "深圳市", "总费用/元": "412.00", "开票日期": "2023年02月03日"}]),
+    ],
 )
 async def test_generate_table(invoice_path: str, expected_result: list[dict]):
     invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
@@ -59,9 +48,7 @@ async def test_generate_table(invoice_path: str, expected_result: list[dict]):
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     ("invoice_path", "query", "expected_result"),
-    [
-        ("../../data/invoices/invoice-1.pdf", "Invoicing date", "2023年02月03日")
-    ]
+    [("../../data/invoices/invoice-1.pdf", "Invoicing date", "2023年02月03日")],
 )
 async def test_reply_question(invoice_path: str, query: dict, expected_result: str):
     invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
@@ -69,4 +56,3 @@ async def test_reply_question(invoice_path: str, query: dict, expected_result: s
     ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
     result = await ReplyQuestion().run(query=query, ocr_result=ocr_result)
     assert expected_result in result
-

tests/metagpt/actions/test_ui_design.py

@@ -4,7 +4,7 @@
 #
 from tests.metagpt.roles.ui_role import UIDesign
 
-llm_resp= '''
+llm_resp = """
     # UI Design Description
 ```The user interface for the snake game will be designed in a way that is simple, clean, and intuitive. The main elements of the game such as the game grid, snake, food, score, and game over message will be clearly defined and easy to understand. The game grid will be centered on the screen with the score displayed at the top. The game controls will be intuitive and easy to use. The design will be modern and minimalist with a pleasing color scheme.```
 
@@ -98,12 +98,13 @@ body {
     left: 50%;
     transform: translate(-50%, -50%);
     font-size: 3em;
-    '''
+    """
+
 
 def test_ui_design_parse_css():
     ui_design_work = UIDesign(name="UI design action")
 
-    css = '''
+    css = """
     body {
     display: flex;
     flex-direction: column;
@@ -160,14 +161,14 @@ def test_ui_design_parse_css():
     left: 50%;
     transform: translate(-50%, -50%);
     font-size: 3em;
-    '''
-    assert ui_design_work.parse_css_code(context=llm_resp)==css
+    """
+    assert ui_design_work.parse_css_code(context=llm_resp) == css
 
 
 def test_ui_design_parse_html():
     ui_design_work = UIDesign(name="UI design action")
 
-    html = '''
+    html = """
     <!DOCTYPE html>
 <html lang="en">
 <head>
@@ -184,8 +185,5 @@ def test_ui_design_parse_html():
     <div class="game-over">Game Over</div>
 </body>
 </html>
-    '''
-    assert ui_design_work.parse_css_code(context=llm_resp)==html
-
-
-
+    """
+    assert ui_design_work.parse_css_code(context=llm_resp) == html

tests/metagpt/actions/test_write_code.py

@@ -22,13 +22,13 @@ async def test_write_code():
     logger.info(code)
 
     # 我们不能精确地预测生成的代码，但我们可以检查某些关键字
-    assert 'def add' in code
-    assert 'return' in code
+    assert "def add" in code
+    assert "return" in code
 
 
 @pytest.mark.asyncio
 async def test_write_code_directly():
-    prompt = WRITE_CODE_PROMPT_SAMPLE + '\n' + TASKS_2[0]
+    prompt = WRITE_CODE_PROMPT_SAMPLE + "\n" + TASKS_2[0]
     llm = LLM()
     rsp = await llm.aask(prompt)
     logger.info(rsp)

tests/metagpt/actions/test_write_docstring.py

@@ -2,7 +2,7 @@ import pytest
 
 from metagpt.actions.write_docstring import WriteDocstring
 
-code = '''
+code = """
 def add_numbers(a: int, b: int):
     return a + b
 
@@ -14,7 +14,7 @@ class Person:
 
     def greet(self):
         return f"Hello, my name is {self.name} and I am {self.age} years old."
-'''
+"""
 
 
 @pytest.mark.asyncio
@@ -25,7 +25,7 @@ class Person:
         ("numpy", "Parameters"),
         ("sphinx", ":param name:"),
     ],
-    ids=["google", "numpy", "sphinx"]
+    ids=["google", "numpy", "sphinx"],
 )
 async def test_write_docstring(style: str, part: str):
     ret = await WriteDocstring().run(code, style=style)

tests/metagpt/actions/test_write_tutorial.py

@@ -9,14 +9,11 @@ from typing import Dict
 
 import pytest
 
-from metagpt.actions.write_tutorial import WriteDirectory, WriteContent
+from metagpt.actions.write_tutorial import WriteContent, WriteDirectory
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize(
-    ("language", "topic"),
-    [("English", "Write a tutorial about Python")]
-)
+@pytest.mark.parametrize(("language", "topic"), [("English", "Write a tutorial about Python")])
 async def test_write_directory(language: str, topic: str):
     ret = await WriteDirectory(language=language).run(topic=topic)
     assert isinstance(ret, dict)
@@ -30,7 +27,7 @@ async def test_write_directory(language: str, topic: str):
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     ("language", "topic", "directory"),
-    [("English", "Write a tutorial about Python", {"Introduction": ["What is Python?", "Why learn Python?"]})]
+    [("English", "Write a tutorial about Python", {"Introduction": ["What is Python?", "Why learn Python?"]})],
 )
 async def test_write_content(language: str, topic: str, directory: Dict):
     ret = await WriteContent(language=language, directory=directory).run(topic=topic)

tests/metagpt/document_store/test_chromadb_store.py

@@ -12,12 +12,12 @@ from metagpt.document_store.chromadb_store import ChromaStore
 def test_chroma_store():
     """FIXME：chroma使用感觉很诡异，一用Python就挂，测试用例里也是"""
     # 创建 ChromaStore 实例，使用 'sample_collection' 集合
-    document_store = ChromaStore('sample_collection_1')
+    document_store = ChromaStore("sample_collection_1")
 
     # 使用 write 方法添加多个文档
-    document_store.write(["This is document1", "This is document2"],
-                [{"source": "google-docs"}, {"source": "notion"}],
-                ["doc1", "doc2"])
+    document_store.write(
+        ["This is document1", "This is document2"], [{"source": "google-docs"}, {"source": "notion"}], ["doc1", "doc2"]
+    )
 
     # 使用 add 方法添加一个文档
     document_store.add("This is document3", {"source": "notion"}, "doc3")

tests/metagpt/document_store/test_faiss_store.py

@@ -39,11 +39,11 @@ user: 没有了
 
 @pytest.mark.asyncio
 async def test_faiss_store_search():
-    store = FaissStore(DATA_PATH / 'qcs/qcs_4w.json')
-    store.add(['油皮洗面奶'])
+    store = FaissStore(DATA_PATH / "qcs/qcs_4w.json")
+    store.add(["油皮洗面奶"])
     role = Sales(store=store)
 
-    queries = ['油皮洗面奶', '介绍下欧莱雅的']
+    queries = ["油皮洗面奶", "介绍下欧莱雅的"]
     for query in queries:
         rsp = await role.run(query)
         assert rsp
@@ -60,7 +60,10 @@ def customer_service():
 async def test_faiss_store_customer_service():
     allq = [
         # ["我的餐怎么两小时都没到", "退货吧"],
-        ["你好收不到取餐码，麻烦帮我开箱", "14750187158", ]
+        [
+            "你好收不到取餐码，麻烦帮我开箱",
+            "14750187158",
+        ]
     ]
     role = customer_service()
     for queries in allq:
@@ -71,4 +74,4 @@ async def test_faiss_store_customer_service():
 
 def test_faiss_store_no_file():
     with pytest.raises(FileNotFoundError):
-        FaissStore(DATA_PATH / 'wtf.json')
+        FaissStore(DATA_PATH / "wtf.json")

tests/metagpt/document_store/test_lancedb_store.py

@@ -5,27 +5,33 @@
 @Author  : unkn-wn (Leon Yee)
 @File    : test_lancedb_store.py
 """
-from metagpt.document_store.lancedb_store import LanceStore
-import pytest
 import random
 
+import pytest
+
+from metagpt.document_store.lancedb_store import LanceStore
+
+
 @pytest
 def test_lance_store():
-
     # This simply establishes the connection to the database, so we can drop the table if it exists
-    store = LanceStore('test')
+    store = LanceStore("test")
 
-    store.drop('test')
+    store.drop("test")
 
-    store.write(data=[[random.random() for _ in range(100)] for _ in range(2)],
-            metadatas=[{"source": "google-docs"}, {"source": "notion"}],
-            ids=["doc1", "doc2"])
+    store.write(
+        data=[[random.random() for _ in range(100)] for _ in range(2)],
+        metadatas=[{"source": "google-docs"}, {"source": "notion"}],
+        ids=["doc1", "doc2"],
+    )
 
     store.add(data=[random.random() for _ in range(100)], metadata={"source": "notion"}, _id="doc3")
 
     result = store.search([random.random() for _ in range(100)], n_results=3)
-    assert(len(result) == 3)
+    assert len(result) == 3
 
     store.delete("doc2")
-    result = store.search([random.random() for _ in range(100)], n_results=3, where="source = 'notion'", metric='cosine')
-    assert(len(result) == 1)
+    result = store.search(
+        [random.random() for _ in range(100)], n_results=3, where="source = 'notion'", metric="cosine"
+    )
+    assert len(result) == 1

tests/metagpt/document_store/test_milvus_store.py

@@ -12,7 +12,7 @@ import numpy as np
 from metagpt.document_store.milvus_store import MilvusConnection, MilvusStore
 from metagpt.logs import logger
 
-book_columns = {'idx': int, 'name': str, 'desc': str, 'emb': np.ndarray, 'price': float}
+book_columns = {"idx": int, "name": str, "desc": str, "emb": np.ndarray, "price": float}
 book_data = [
     [i for i in range(10)],
     [f"book-{i}" for i in range(10)],
@@ -25,12 +25,12 @@ book_data = [
 def test_milvus_store():
     milvus_connection = MilvusConnection(alias="default", host="192.168.50.161", port="30530")
     milvus_store = MilvusStore(milvus_connection)
-    milvus_store.drop('Book')
-    milvus_store.create_collection('Book', book_columns)
+    milvus_store.drop("Book")
+    milvus_store.create_collection("Book", book_columns)
     milvus_store.add(book_data)
-    milvus_store.build_index('emb')
+    milvus_store.build_index("emb")
     milvus_store.load_collection()
 
-    results = milvus_store.search([[1.0, 1.0]], field='emb')
+    results = milvus_store.search([[1.0, 1.0]], field="emb")
     logger.info(results)
     assert results

tests/metagpt/document_store/test_qdrant_store.py

@@ -24,9 +24,7 @@ random.seed(seed_value)
 vectors = [[random.random() for _ in range(2)] for _ in range(10)]
 
 points = [
-    PointStruct(
-        id=idx, vector=vector, payload={"color": "red", "rand_number": idx % 10}
-    )
+    PointStruct(id=idx, vector=vector, payload={"color": "red", "rand_number": idx % 10})
     for idx, vector in enumerate(vectors)
 ]
 
@@ -57,9 +55,7 @@ def test_milvus_store():
     results = qdrant_store.search(
         "Book",
         query=[1.0, 1.0],
-        query_filter=Filter(
-            must=[FieldCondition(key="rand_number", range=Range(gte=8))]
-        ),
+        query_filter=Filter(must=[FieldCondition(key="rand_number", range=Range(gte=8))]),
     )
     assert results[0]["id"] == 8
     assert results[0]["score"] == 0.9100373450784073
@@ -68,9 +64,7 @@ def test_milvus_store():
     results = qdrant_store.search(
         "Book",
         query=[1.0, 1.0],
-        query_filter=Filter(
-            must=[FieldCondition(key="rand_number", range=Range(gte=8))]
-        ),
+        query_filter=Filter(must=[FieldCondition(key="rand_number", range=Range(gte=8))]),
         return_vector=True,
     )
     assert results[0]["vector"] == [0.35037919878959656, 0.9366079568862915]

tests/metagpt/management/test_skill_manager.py

@@ -30,7 +30,7 @@ def test_skill_manager():
 
     rsp = manager.retrieve_skill("写测试用例")
     logger.info(rsp)
-    assert rsp[0] == 'WriteTest'
+    assert rsp[0] == "WriteTest"
 
     rsp = manager.retrieve_skill_scored("写PRD")
     logger.info(rsp)

tests/metagpt/memory/test_longterm_memory.py

@@ -2,11 +2,11 @@
 # -*- coding: utf-8 -*-
 # @Desc   : unittest of `metagpt/memory/longterm_memory.py`
 
-from metagpt.config import CONFIG
-from metagpt.schema import Message
 from metagpt.actions import BossRequirement
-from metagpt.roles.role import RoleContext
+from metagpt.config import CONFIG
 from metagpt.memory import LongTermMemory
+from metagpt.roles.role import RoleContext
+from metagpt.schema import Message
 
 
 def test_ltm_search():
@@ -14,25 +14,25 @@ def test_ltm_search():
     openai_api_key = CONFIG.openai_api_key
     assert len(openai_api_key) > 20
 
-    role_id = 'UTUserLtm(Product Manager)'
+    role_id = "UTUserLtm(Product Manager)"
     rc = RoleContext(watch=[BossRequirement])
     ltm = LongTermMemory()
     ltm.recover_memory(role_id, rc)
 
-    idea = 'Write a cli snake game'
-    message = Message(role='BOSS', content=idea, cause_by=BossRequirement)
+    idea = "Write a cli snake game"
+    message = Message(role="BOSS", content=idea, cause_by=BossRequirement)
     news = ltm.find_news([message])
     assert len(news) == 1
     ltm.add(message)
 
-    sim_idea = 'Write a game of cli snake'
-    sim_message = Message(role='BOSS', content=sim_idea, cause_by=BossRequirement)
+    sim_idea = "Write a game of cli snake"
+    sim_message = Message(role="BOSS", content=sim_idea, cause_by=BossRequirement)
     news = ltm.find_news([sim_message])
     assert len(news) == 0
     ltm.add(sim_message)
 
-    new_idea = 'Write a 2048 web game'
-    new_message = Message(role='BOSS', content=new_idea, cause_by=BossRequirement)
+    new_idea = "Write a 2048 web game"
+    new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
     news = ltm.find_news([new_message])
     assert len(news) == 1
     ltm.add(new_message)
@@ -47,8 +47,8 @@ def test_ltm_search():
     news = ltm_new.find_news([sim_message])
     assert len(news) == 0
 
-    new_idea = 'Write a Battle City'
-    new_message = Message(role='BOSS', content=new_idea, cause_by=BossRequirement)
+    new_idea = "Write a Battle City"
+    new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
     news = ltm_new.find_news([new_message])
     assert len(news) == 1
 

tests/metagpt/memory/test_memory_storage.py

@@ -4,17 +4,16 @@
 
 from typing import List
 
+from metagpt.actions import BossRequirement, WritePRD
+from metagpt.actions.action_output import ActionOutput
 from metagpt.memory.memory_storage import MemoryStorage
 from metagpt.schema import Message
-from metagpt.actions import BossRequirement
-from metagpt.actions import WritePRD
-from metagpt.actions.action_output import ActionOutput
 
 
 def test_idea_message():
-    idea = 'Write a cli snake game'
-    role_id = 'UTUser1(Product Manager)'
-    message = Message(role='BOSS', content=idea, cause_by=BossRequirement)
+    idea = "Write a cli snake game"
+    role_id = "UTUser1(Product Manager)"
+    message = Message(role="BOSS", content=idea, cause_by=BossRequirement)
 
     memory_storage: MemoryStorage = MemoryStorage()
     messages = memory_storage.recover_memory(role_id)
@@ -23,13 +22,13 @@ def test_idea_message():
     memory_storage.add(message)
     assert memory_storage.is_initialized is True
 
-    sim_idea = 'Write a game of cli snake'
-    sim_message = Message(role='BOSS', content=sim_idea, cause_by=BossRequirement)
+    sim_idea = "Write a game of cli snake"
+    sim_message = Message(role="BOSS", content=sim_idea, cause_by=BossRequirement)
     new_messages = memory_storage.search(sim_message)
-    assert len(new_messages) == 0   # similar, return []
+    assert len(new_messages) == 0  # similar, return []
 
-    new_idea = 'Write a 2048 web game'
-    new_message = Message(role='BOSS', content=new_idea, cause_by=BossRequirement)
+    new_idea = "Write a 2048 web game"
+    new_message = Message(role="BOSS", content=new_idea, cause_by=BossRequirement)
     new_messages = memory_storage.search(new_message)
     assert new_messages[0].content == message.content
 
@@ -38,22 +37,15 @@ def test_idea_message():
 
 
 def test_actionout_message():
-    out_mapping = {
-        'field1': (str, ...),
-        'field2': (List[str], ...)
-    }
-    out_data = {
-        'field1': 'field1 value',
-        'field2': ['field2 value1', 'field2 value2']
-    }
-    ic_obj = ActionOutput.create_model_class('prd', out_mapping)
+    out_mapping = {"field1": (str, ...), "field2": (List[str], ...)}
+    out_data = {"field1": "field1 value", "field2": ["field2 value1", "field2 value2"]}
+    ic_obj = ActionOutput.create_model_class("prd", out_mapping)
 
-    role_id = 'UTUser2(Architect)'
-    content = 'The boss has requested the creation of a command-line interface (CLI) snake game'
-    message = Message(content=content,
-                      instruct_content=ic_obj(**out_data),
-                      role='user',
-                      cause_by=WritePRD)  # WritePRD as test action
+    role_id = "UTUser2(Architect)"
+    content = "The boss has requested the creation of a command-line interface (CLI) snake game"
+    message = Message(
+        content=content, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD
+    )  # WritePRD as test action
 
     memory_storage: MemoryStorage = MemoryStorage()
     messages = memory_storage.recover_memory(role_id)
@@ -62,19 +54,13 @@ def test_actionout_message():
     memory_storage.add(message)
     assert memory_storage.is_initialized is True
 
-    sim_conent = 'The request is command-line interface (CLI) snake game'
-    sim_message = Message(content=sim_conent,
-                          instruct_content=ic_obj(**out_data),
-                          role='user',
-                          cause_by=WritePRD)
+    sim_conent = "The request is command-line interface (CLI) snake game"
+    sim_message = Message(content=sim_conent, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD)
     new_messages = memory_storage.search(sim_message)
-    assert len(new_messages) == 0   # similar, return []
+    assert len(new_messages) == 0  # similar, return []
 
-    new_conent = 'Incorporate basic features of a snake game such as scoring and increasing difficulty'
-    new_message = Message(content=new_conent,
-                          instruct_content=ic_obj(**out_data),
-                          role='user',
-                          cause_by=WritePRD)
+    new_conent = "Incorporate basic features of a snake game such as scoring and increasing difficulty"
+    new_message = Message(content=new_conent, instruct_content=ic_obj(**out_data), role="user", cause_by=WritePRD)
     new_messages = memory_storage.search(new_message)
     assert new_messages[0].content == message.content