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better：进一步拆分模型配置

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This commit is contained in:
SengokuCola
2025-05-27 18:35:33 +08:00
parent 52f7cc3762
commit cad9b40bb3
10 changed files with 61 additions and 49 deletions
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2
src/chat/emoji_system/emoji_manager.py
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@@ -374,7 +374,7 @@ class EmojiManager:
self.vlm = LLMRequest(model=global_config.model.vlm, temperature=0.3, max_tokens=1000, request_type="emoji")
self.llm_emotion_judge = LLMRequest(
model=global_config.model.normal, max_tokens=600, request_type="emoji"
model=global_config.model.utils, max_tokens=600, request_type="emoji"
) # 更高的温度，更少的token（后续可以根据情绪来调整温度）
self.emoji_num = 0

6
src/chat/focus_chat/expressors/default_expressor.py
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@@ -192,9 +192,9 @@ class DefaultExpressor:
"""
try:
# 1. 获取情绪影响因子并调整模型温度
arousal_multiplier = mood_manager.get_arousal_multiplier()
current_temp = float(global_config.model.normal["temp"]) * arousal_multiplier
self.express_model.params["temperature"] = current_temp # 动态调整温度
# arousal_multiplier = mood_manager.get_arousal_multiplier()
# current_temp = float(global_config.model.normal["temp"]) * arousal_multiplier
# self.express_model.params["temperature"] = current_temp # 动态调整温度
# 2. 获取信息捕捉器
info_catcher = info_catcher_manager.get_info_catcher(thinking_id)

2
src/chat/focus_chat/info_processors/chattinginfo_processor.py
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@@ -28,7 +28,7 @@ class ChattingInfoProcessor(BaseProcessor):
super().__init__()
# TODO: API-Adapter修改标记
self.model_summary = LLMRequest(
model=global_config.model.observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
model=global_config.model.utils_small, temperature=0.7, max_tokens=300, request_type="chat_observation"
)
async def process_info(

8
src/chat/normal_chat/normal_chat_generator.py
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@@ -20,13 +20,13 @@ class NormalChatGenerator:
model=global_config.model.normal_chat_1,
temperature=0.7,
max_tokens=3000,
request_type="response_reasoning",
request_type="normal_chat_1",
)
self.model_normal = LLMRequest(
model=global_config.model.normal,
temperature=global_config.model.normal["temp"],
model=global_config.model.normal_chat_2,
temperature=global_config.model.normal_chat_2["temp"],
max_tokens=256,
request_type="response_reasoning",
request_type="normal_chat_2",
)
self.model_sum = LLMRequest(