fix format

metagpt/provider/__init__.py

@@ -12,10 +12,4 @@ from metagpt.provider.open_llm_api import OpenLLMGPTAPI
 from metagpt.provider.openai_api import OpenAIGPTAPI
 from metagpt.provider.zhipuai_api import ZhiPuAIGPTAPI
 
-__all__ = [
-    "FireWorksGPTAPI",
-    "GeminiGPTAPI",
-    "OpenLLMGPTAPI",
-    "OpenAIGPTAPI",
-    "ZhiPuAIGPTAPI"
-]
+__all__ = ["FireWorksGPTAPI", "GeminiGPTAPI", "OpenLLMGPTAPI", "OpenAIGPTAPI", "ZhiPuAIGPTAPI"]

metagpt/provider/google_gemini_api.py

@@ -6,8 +6,11 @@ import google.generativeai as genai
 from google.ai import generativelanguage as glm
 from google.generativeai.generative_models import GenerativeModel
 from google.generativeai.types import content_types
-from google.generativeai.types.generation_types import GenerateContentResponse, AsyncGenerateContentResponse
-from google.generativeai.types.generation_types import GenerationConfig
+from google.generativeai.types.generation_types import (
+    AsyncGenerateContentResponse,
+    GenerateContentResponse,
+    GenerationConfig,
+)
 from tenacity import (
     after_log,
     retry,
@@ -29,15 +32,11 @@ class GeminiGenerativeModel(GenerativeModel):
     Will use default GenerativeModel if it fixed.
     """
 
-    def count_tokens(
-            self, contents: content_types.ContentsType
-    ) -> glm.CountTokensResponse:
+    def count_tokens(self, contents: content_types.ContentsType) -> glm.CountTokensResponse:
         contents = content_types.to_contents(contents)
         return self._client.count_tokens(model=self.model_name, contents=contents)
 
-    async def count_tokens_async(
-            self, contents: content_types.ContentsType
-    ) -> glm.CountTokensResponse:
+    async def count_tokens_async(self, contents: content_types.ContentsType) -> glm.CountTokensResponse:
         contents = content_types.to_contents(contents)
         return await self._async_client.count_tokens(model=self.model_name, contents=contents)
 
@@ -68,17 +67,11 @@ class GeminiGPTAPI(BaseGPTAPI):
         return {"role": "model", "parts": [msg]}
 
     def _const_kwargs(self, messages: list[dict], stream: bool = False) -> dict:
-        kwargs = {
-            "contents": messages,
-            "generation_config": GenerationConfig(
-                temperature=0.3
-            ),
-            "stream": stream
-        }
+        kwargs = {"contents": messages, "generation_config": GenerationConfig(temperature=0.3), "stream": stream}
         return kwargs
 
     def _update_costs(self, usage: dict):
-        """ update each request's token cost """
+        """update each request's token cost"""
         if CONFIG.calc_usage:
             try:
                 prompt_tokens = int(usage.get("prompt_tokens", 0))
@@ -94,20 +87,14 @@ class GeminiGPTAPI(BaseGPTAPI):
         req_text = messages[-1]["parts"][0] if messages else ""
         prompt_resp = self.llm.count_tokens(contents={"role": "user", "parts": [{"text": req_text}]})
         completion_resp = self.llm.count_tokens(contents={"role": "model", "parts": [{"text": resp_text}]})
-        usage = {
-            "prompt_tokens": prompt_resp.total_tokens,
-            "completion_tokens": completion_resp.total_tokens
-        }
+        usage = {"prompt_tokens": prompt_resp.total_tokens, "completion_tokens": completion_resp.total_tokens}
         return usage
 
     async def aget_usage(self, messages: list[dict], resp_text: str) -> dict:
         req_text = messages[-1]["parts"][0] if messages else ""
         prompt_resp = await self.llm.count_tokens_async(contents={"role": "user", "parts": [{"text": req_text}]})
         completion_resp = await self.llm.count_tokens_async(contents={"role": "model", "parts": [{"text": resp_text}]})
-        usage = {
-            "prompt_tokens": prompt_resp.total_tokens,
-            "completion_tokens": completion_resp.total_tokens
-        }
+        usage = {"prompt_tokens": prompt_resp.total_tokens, "completion_tokens": completion_resp.total_tokens}
         return usage
 
     def completion(self, messages: list[dict]) -> "GenerateContentResponse":
@@ -126,8 +113,9 @@ class GeminiGPTAPI(BaseGPTAPI):
         return await self._achat_completion(messages)
 
     async def _achat_completion_stream(self, messages: list[dict]) -> str:
-        resp: AsyncGenerateContentResponse = await self.llm.generate_content_async(**self._const_kwargs(messages,
-                                                                                                        stream=True))
+        resp: AsyncGenerateContentResponse = await self.llm.generate_content_async(
+            **self._const_kwargs(messages, stream=True)
+        )
         collected_content = []
         async for chunk in resp:
             content = chunk.text
@@ -144,10 +132,10 @@ class GeminiGPTAPI(BaseGPTAPI):
         wait=wait_random_exponential(min=1, max=60),
         after=after_log(logger, logger.level("WARNING").name),
         retry=retry_if_exception_type(ConnectionError),
-        retry_error_callback=log_and_reraise
+        retry_error_callback=log_and_reraise,
     )
     async def acompletion_text(self, messages: list[dict], stream=False) -> str:
-        """ response in async with stream or non-stream mode """
+        """response in async with stream or non-stream mode"""
         if stream:
             return await self._achat_completion_stream(messages)
         resp = await self._achat_completion(messages)

metagpt/roles/researcher.py

@@ -70,7 +70,7 @@ class Researcher(Role):
         return ret
 
     def research_system_text(self, topic, current_task: Action) -> str:
-        """ BACKWARD compatible
+        """BACKWARD compatible
         This allows sub-class able to define its own system prompt based on topic.
         return the previous implementation to have backward compatible
         Args:

metagpt/tools/web_browser_engine_selenium.py

@@ -106,8 +106,8 @@ def _gen_get_driver_func(browser_type, *args, executable_path=None):
         options.add_argument("--headless")
         options.add_argument("--enable-javascript")
         if browser_type == "chrome":
-            options.add_argument("--disable-gpu") # This flag can help avoid renderer issue
-            options.add_argument("--disable-dev-shm-usage") # Overcome limited resource problems
+            options.add_argument("--disable-gpu")  # This flag can help avoid renderer issue
+            options.add_argument("--disable-dev-shm-usage")  # Overcome limited resource problems
             options.add_argument("--no-sandbox")
         for i in args:
             options.add_argument(i)

metagpt/utils/common.py

@@ -226,7 +226,7 @@ class OutputParser:
 
         if start_index != -1 and end_index != -1:
             # Extract the structure part
-            structure_text = text[start_index: end_index + 1]
+            structure_text = text[start_index : end_index + 1]
 
             try:
                 # Attempt to convert the text to a Python data type using ast.literal_eval

metagpt/utils/token_counter.py

@@ -26,7 +26,7 @@ TOKEN_COSTS = {
     "gpt-4-1106-preview": {"prompt": 0.01, "completion": 0.03},
     "text-embedding-ada-002": {"prompt": 0.0004, "completion": 0.0},
     "chatglm_turbo": {"prompt": 0.0, "completion": 0.00069},  # 32k version, prompt + completion tokens=0.005￥/k-tokens
-    "gemini-pro": {"prompt": 0.00025, "completion": 0.0005}
+    "gemini-pro": {"prompt": 0.00025, "completion": 0.0005},
 }
 
 
@@ -45,7 +45,7 @@ TOKEN_MAX = {
     "gpt-4-1106-preview": 128000,
     "text-embedding-ada-002": 8192,
     "chatglm_turbo": 32768,
-    "gemini-pro": 32768
+    "gemini-pro": 32768,
 }
 
 

tests/metagpt/provider/test_google_gemini_api.py

@@ -2,16 +2,14 @@
 # -*- coding: utf-8 -*-
 # @Desc   : the unittest of google gemini api
 
-import pytest
 from abc import ABC
 from dataclasses import dataclass
 
+import pytest
+
 from metagpt.provider.google_gemini_api import GeminiGPTAPI
 
-
-messages = [
-    {"role": "user", "content": "who are you"}
-]
+messages = [{"role": "user", "content": "who are you"}]
 
 
 @dataclass