🤖 自动格式化代码 [skip ci]

src/heart_flow/sub_heartflow.py

@@ -79,7 +79,10 @@ class SubHeartflow:
         self.past_mind = []
         self.current_state: CurrentState = CurrentState()
         self.llm_model = LLM_request(
-            model=global_config.llm_sub_heartflow, temperature=global_config.llm_sub_heartflow["temp"], max_tokens=600, request_type="sub_heart_flow"
+            model=global_config.llm_sub_heartflow,
+            temperature=global_config.llm_sub_heartflow["temp"],
+            max_tokens=600,
+            request_type="sub_heart_flow",
         )
 
         self.main_heartflow_info = ""

src/plugins/PFC/action_planner.py

@@ -24,7 +24,10 @@ class ActionPlanner:
 
     def __init__(self, stream_id: str):
         self.llm = LLM_request(
-            model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=1000, request_type="action_planning"
+            model=global_config.llm_normal,
+            temperature=global_config.llm_normal["temp"],
+            max_tokens=1000,
+            request_type="action_planning",
         )
         self.personality_info = Individuality.get_instance().get_prompt(type="personality", x_person=2, level=2)
         self.name = global_config.BOT_NICKNAME

src/plugins/PFC/pfc_KnowledgeFetcher.py

@@ -13,7 +13,10 @@ class KnowledgeFetcher:
 
     def __init__(self):
         self.llm = LLM_request(
-            model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=1000, request_type="knowledge_fetch"
+            model=global_config.llm_normal,
+            temperature=global_config.llm_normal["temp"],
+            max_tokens=1000,
+            request_type="knowledge_fetch",
         )
 
     async def fetch(self, query: str, chat_history: List[Message]) -> Tuple[str, str]:

src/plugins/PFC/reply_generator.py

@@ -16,7 +16,10 @@ class ReplyGenerator:
 
     def __init__(self, stream_id: str):
         self.llm = LLM_request(
-            model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=300, request_type="reply_generation"
+            model=global_config.llm_normal,
+            temperature=global_config.llm_normal["temp"],
+            max_tokens=300,
+            request_type="reply_generation",
         )
         self.personality_info = Individuality.get_instance().get_prompt(type="personality", x_person=2, level=2)
         self.name = global_config.BOT_NICKNAME

src/plugins/chat_module/reasoning_chat/reasoning_generator.py

@@ -29,7 +29,10 @@ class ResponseGenerator:
             request_type="response_reasoning",
         )
         self.model_normal = LLM_request(
-            model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=256, request_type="response_reasoning"
+            model=global_config.llm_normal,
+            temperature=global_config.llm_normal["temp"],
+            max_tokens=256,
+            request_type="response_reasoning",
         )
 
         self.model_sum = LLM_request(

src/plugins/chat_module/think_flow_chat/think_flow_generator.py

@@ -26,7 +26,10 @@ logger = get_module_logger("llm_generator", config=llm_config)
 class ResponseGenerator:
     def __init__(self):
         self.model_normal = LLM_request(
-            model=global_config.llm_normal, temperature=global_config.llm_normal["temp"], max_tokens=256, request_type="response_heartflow"
+            model=global_config.llm_normal,
+            temperature=global_config.llm_normal["temp"],
+            max_tokens=256,
+            request_type="response_heartflow",
         )
 
         self.model_sum = LLM_request(
@@ -49,7 +52,9 @@ class ResponseGenerator:
             if random.random() > 0:
                 checked = False
                 current_model = self.model_normal
-                current_model.temperature = global_config.llm_normal["temp"] * arousal_multiplier  # 激活度越高，温度越高
+                current_model.temperature = (
+                    global_config.llm_normal["temp"] * arousal_multiplier
+                )  # 激活度越高，温度越高
                 model_response = await self._generate_response_with_model(
                     message, current_model, thinking_id, mode="normal"
                 )
@@ -58,7 +63,9 @@ class ResponseGenerator:
             else:
                 checked = True
                 current_model = self.model_normal
-                current_model.temperature = global_config.llm_normal["temp"] * arousal_multiplier  # 激活度越高，温度越高
+                current_model.temperature = (
+                    global_config.llm_normal["temp"] * arousal_multiplier
+                )  # 激活度越高，温度越高
                 print(f"生成{message.processed_plain_text}回复温度是：{current_model.temperature}")
                 model_response = await self._generate_response_with_model(
                     message, current_model, thinking_id, mode="simple"

src/plugins/config/config.py

@@ -447,9 +447,7 @@ class BotConfig:
                 config.observation_context_size = heartflow_config.get(
                     "observation_context_size", config.observation_context_size
                 )
-                config.compressed_length = heartflow_config.get(
-                    "compressed_length", config.compressed_length
-                )
+                config.compressed_length = heartflow_config.get("compressed_length", config.compressed_length)
                 config.compress_length_limit = heartflow_config.get(
                     "compress_length_limit", config.compress_length_limit
                 )
@@ -502,7 +500,15 @@ class BotConfig:
 
                     # base_url 的例子： SILICONFLOW_BASE_URL
                     # key 的例子： SILICONFLOW_KEY
-                    cfg_target = {"name": "", "base_url": "", "key": "", "stream": False, "pri_in": 0, "pri_out": 0, "temp": 0.7}
+                    cfg_target = {
+                        "name": "",
+                        "base_url": "",
+                        "key": "",
+                        "stream": False,
+                        "pri_in": 0,
+                        "pri_out": 0,
+                        "temp": 0.7,
+                    }
 
                     if config.INNER_VERSION in SpecifierSet("<=0.0.0"):
                         cfg_target = cfg_item