🎨 style: format codes

astrbot/core/pipeline/process_stage/method/llm_request.py

@@ -292,9 +292,7 @@ class LLMRequestSubStage(Stage):
 
             # tool calls result
             if req.tool_calls_result:
-                contexts.extend(
-                    req.tool_calls_result.to_openai_messages()
-                )
+                contexts.extend(req.tool_calls_result.to_openai_messages())
 
             contexts.append(
                 {"role": "assistant", "content": llm_response.completion_text}

astrbot/core/provider/sources/anthropic_source.py

@@ -104,7 +104,7 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
         func_tool: FuncCall = None,
         contexts=[],
         system_prompt=None,
-        tool_calls_result: ToolCallsResult=None,
+        tool_calls_result: ToolCallsResult = None,
         **kwargs,
     ) -> LLMResponse:
         if not prompt:

astrbot/core/provider/sources/gemini_source.py

@@ -162,7 +162,9 @@ class ProviderGoogleGenAI(Provider):
                             {
                                 "functionCall": {
                                     "name": tool_call["function"]["name"],
-                                    "args": json.loads(tool_call["function"]["arguments"]),
+                                    "args": json.loads(
+                                        tool_call["function"]["arguments"]
+                                    ),
                                 }
                             }
                         )
@@ -204,7 +206,9 @@ class ProviderGoogleGenAI(Provider):
                 llm_response.role = "tool"
                 llm_response.tools_call_args.append(candidate["functionCall"]["args"])
                 llm_response.tools_call_name.append(candidate["functionCall"]["name"])
-                llm_response.tools_call_ids.append(candidate["functionCall"]["name"])  # 没有 tool id
+                llm_response.tools_call_ids.append(
+                    candidate["functionCall"]["name"]
+                )  # 没有 tool id
 
         llm_response.completion_text = llm_response.completion_text.strip()
         return llm_response