remove:移除内部固定温度参数

src/chat/image_system/image_manager.py

@@ -14,7 +14,6 @@ from src.common.database.database import get_db_session
 from src.common.database.database_model import Images, ImageType
 from src.common.data_models.image_data_model import MaiImage
 from src.config.config import global_config
-from src.common.data_models.llm_service_data_models import LLMImageOptions
 from src.services.llm_service import LLMServiceClient
 
 install(extra_lines=3)
@@ -382,7 +381,6 @@ class ImageManager:
             prompt,
             image_base64,
             image_format,
-            options=LLMImageOptions(temperature=0.4),
         )
         description = generation_result.response
         if not description:

src/emoji_system/emoji_manager.py

@@ -14,7 +14,7 @@ from sqlmodel import select
 import Levenshtein
 
 from src.common.data_models.image_data_model import MaiEmoji
-from src.common.data_models.llm_service_data_models import LLMGenerationOptions, LLMImageOptions
+from src.common.data_models.llm_service_data_models import LLMGenerationOptions
 from src.common.database.database import get_db_session, get_db_session_manual
 from src.common.database.database_model import Images, ImageType
 from src.common.logger import get_logger
@@ -778,7 +778,7 @@ class EmojiManager:
 
         decision_result = await emoji_manager_emotion_judge_llm.generate_response(
             emoji_replace_prompt,
-            options=LLMGenerationOptions(temperature=0.8, max_tokens=600),
+            options=LLMGenerationOptions(max_tokens=600),
         )
         decision = decision_result.response
         logger.info(f"[决策] 结果: {decision}")
@@ -853,7 +853,6 @@ class EmojiManager:
                     prompt,
                     image_base64,
                     "jpg",
-                    options=LLMImageOptions(temperature=0.5),
                 )
                 description = description_result.response
             else:
@@ -865,7 +864,6 @@ class EmojiManager:
                     prompt,
                     image_base64,
                     image_format,
-                    options=LLMImageOptions(temperature=0.5),
                 )
                 description = description_result.response
         except Exception as e:
@@ -886,7 +884,6 @@ class EmojiManager:
                     filtration_prompt,
                     image_base64,
                     image_format,
-                    options=LLMImageOptions(temperature=0.3),
                 )
                 llm_response = filtration_result.response
             except Exception as e:

src/emoji_system/maisaka_tool.py

@@ -9,7 +9,6 @@ import random
 from src.chat.message_receive.chat_manager import chat_manager
 from src.cli.maisaka_cli_sender import CLI_PLATFORM_NAME, render_cli_message
 from src.common.data_models.image_data_model import MaiEmoji
-from src.common.data_models.llm_service_data_models import LLMGenerationOptions
 from src.common.logger import get_logger
 from src.common.utils.utils_image import ImageUtils
 from src.services import send_service
@@ -18,7 +17,6 @@ from .emoji_manager import (
     _normalize_emoji_tag_text,
     _serialize_emoji_for_hook,
     emoji_manager,
-    emoji_manager_emotion_judge_llm,
 )
 
 logger = get_logger("emoji_maisaka_tool")
@@ -123,56 +121,6 @@ def _normalize_emotions(emoji: MaiEmoji) -> list[str]:
     return []
 
 
-def _build_recent_context_text(context_texts: Sequence[str], max_items: int = 5) -> str:
-    """构建供情绪判断使用的最近上下文文本。"""
-
-    normalized_items = [str(item).strip() for item in context_texts if str(item).strip()]
-    if not normalized_items:
-        return ""
-    return "\n".join(normalized_items[-max_items:])
-
-
-async def _select_emoji_with_llm(
-    *,
-    sampled_emojis: Sequence[MaiEmoji],
-    reasoning: str,
-    context_text: str,
-) -> tuple[MaiEmoji, str]:
-    """让模型在采样表情中选择更合适的情绪标签。"""
-
-    emotion_map: dict[str, list[MaiEmoji]] = {}
-    for emoji in sampled_emojis:
-        for emotion in _normalize_emotions(emoji):
-            emotion_map.setdefault(emotion, []).append(emoji)
-
-    available_emotions = list(emotion_map.keys())
-    if not available_emotions:
-        return random.choice(list(sampled_emojis)), ""
-
-    prompt = (
-        "你正在为聊天场景选择一个最合适的表情包情绪标签。\n"
-        f"发送原因：{reasoning or '辅助表达当前语气和情绪'}\n"
-        f"最近聊天记录：\n{context_text or '（暂无额外上下文）'}\n\n"
-        "可选情绪标签如下：\n"
-        f"{chr(10).join(available_emotions)}\n\n"
-        "请只返回一个最匹配的情绪标签，不要解释。"
-    )
-
-    try:
-        llm_result = await emoji_manager_emotion_judge_llm.generate_response(
-            prompt,
-            options=LLMGenerationOptions(temperature=0.3, max_tokens=60),
-        )
-        chosen_emotion = (llm_result.response or "").strip().strip("\"'")
-    except Exception as exc:
-        logger.warning(f"使用 LLM 选择表情情绪失败，将回退为随机选择: {exc}")
-        chosen_emotion = ""
-
-    if chosen_emotion and chosen_emotion in emotion_map:
-        return random.choice(emotion_map[chosen_emotion]), chosen_emotion
-    return random.choice(list(sampled_emojis)), ""
-
-
 async def select_emoji_for_maisaka(
     *,
     requested_emotion: str = "",
@@ -182,6 +130,8 @@ async def select_emoji_for_maisaka(
 ) -> tuple[MaiEmoji | None, str]:
     """为 Maisaka 选择一个合适的表情。"""
 
+    del reasoning, context_texts
+
     available_emojis = list(emoji_manager.emojis)
     if not available_emojis:
         return None, ""
@@ -200,12 +150,7 @@ async def select_emoji_for_maisaka(
         available_emojis,
         min(max(sample_size, 1), len(available_emojis)),
     )
-    context_text = _build_recent_context_text(context_texts or [])
-    return await _select_emoji_with_llm(
-        sampled_emojis=sampled_emojis,
-        reasoning=reasoning,
-        context_text=context_text,
-    )
+    return random.choice(sampled_emojis), ""
 
 
 async def send_emoji_for_maisaka(

src/maisaka/builtin_tool/reply.py

@@ -24,7 +24,6 @@ async def _run_expression_selector(tool_ctx: BuiltinToolRuntimeContext, system_p
         system_prompt=system_prompt,
         request_kind="expression_selector",
         max_tokens=256,
-        temperature=0.1,
     )
     return (response.content or "").strip()
 

src/maisaka/chat_loop_service.py

@@ -187,7 +187,6 @@ class MaisakaChatLoopService:
         chat_system_prompt: Optional[str] = None,
         session_id: Optional[str] = None,
         is_group_chat: Optional[bool] = None,
-        temperature: float = 0.5,
         max_tokens: int = 2048,
     ) -> None:
         """初始化 Maisaka 对话循环服务。
@@ -196,11 +195,9 @@ class MaisakaChatLoopService:
             chat_system_prompt: 可选的系统提示词。
             session_id: 当前会话 ID，用于匹配会话级额外提示。
             is_group_chat: 当前会话是否为群聊。
-            temperature: 规划器温度参数。
             max_tokens: 规划器最大输出长度。
         """
 
-        self._temperature = temperature
         self._max_tokens = max_tokens
         self._is_group_chat = is_group_chat
         self._session_id = session_id or ""
@@ -546,7 +543,6 @@ class MaisakaChatLoopService:
             message_factory=message_factory,
             options=LLMGenerationOptions(
                 tool_options=all_tools if all_tools else None,
-                temperature=self._temperature,
                 max_tokens=self._max_tokens,
                 response_format=response_format,
                 interrupt_flag=self._interrupt_flag,

src/maisaka/reasoning_engine.py

@@ -138,7 +138,6 @@ class MaisakaReasoningEngine:
             request_kind="timing_gate",
             interrupt_flag=None,
             max_tokens=TIMING_GATE_MAX_TOKENS,
-            temperature=0.1,
             tool_definitions=tool_definitions,
         )
 

src/maisaka/runtime.py

@@ -566,7 +566,6 @@ class MaisakaHeartFlowChatting:
         interrupt_flag: asyncio.Event | None = None,
         max_tokens: int = 512,
         response_format: RespFormat | None = None,
-        temperature: float = 0.2,
         tool_definitions: Optional[Sequence[ToolDefinitionInput]] = None,
     ) -> ChatResponse:
         """运行一个复制上下文的临时子代理，并在完成后立即销毁。"""
@@ -584,7 +583,6 @@ class MaisakaHeartFlowChatting:
             chat_system_prompt=system_prompt,
             session_id=self.session_id,
             is_group_chat=self.chat_stream.is_group_session,
-            temperature=temperature,
             max_tokens=max_tokens,
         )
         sub_agent.set_interrupt_flag(interrupt_flag)
@@ -611,7 +609,6 @@ class MaisakaHeartFlowChatting:
             request_kind="reply_effect_judge",
             extra_messages=[judge_message],
             max_tokens=900,
-            temperature=0.1,
             tool_definitions=[],
         )
         return (response.content or "").strip()