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better：新增config项目

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This commit is contained in:
SengokuCola
2025-04-14 22:09:00 +08:00
parent 53332791e4
commit d9f191705f
11 changed files with 51 additions and 31 deletions
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2
src/plugins/PFC/action_planner.py
View File

@@ -24,7 +24,7 @@ class ActionPlanner:
def __init__(self, stream_id: str):
self.llm = LLM_request(
model=global_config.llm_normal, temperature=0.2, 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

2
src/plugins/PFC/pfc_KnowledgeFetcher.py
View File

@@ -13,7 +13,7 @@ class KnowledgeFetcher:
def __init__(self):
self.llm = LLM_request(
model=global_config.llm_normal, temperature=0.7, 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]:

2
src/plugins/PFC/reply_generator.py
View File

@@ -16,7 +16,7 @@ class ReplyGenerator:
def __init__(self, stream_id: str):
self.llm = LLM_request(
model=global_config.llm_normal, temperature=0.2, 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

2
src/plugins/chat_module/reasoning_chat/reasoning_generator.py
View File

@@ -29,7 +29,7 @@ class ResponseGenerator:
request_type="response_reasoning",
)
self.model_normal = LLM_request(
model=global_config.llm_normal, temperature=0.8, 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(

8
src/plugins/chat_module/think_flow_chat/think_flow_generator.py
View File

@@ -26,7 +26,7 @@ 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=0.15, 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 +49,7 @@ class ResponseGenerator:
if random.random() > 0:
checked = False
current_model = self.model_normal
current_model.temperature = 0.3 * 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"
)
@@ -58,13 +58,13 @@ class ResponseGenerator:
else:
checked = True
current_model = self.model_normal
current_model.temperature = 0.3 * 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"
)
current_model.temperature = 0.3
current_model.temperature = global_config.llm_normal["temp"]
model_checked_response = await self._check_response_with_model(
message, model_response, current_model, thinking_id
)

29
src/plugins/config/config.py
View File

@@ -26,9 +26,9 @@ config_config = LogConfig(
logger = get_module_logger("config", config=config_config)
# 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
is_test = True
is_test = False
mai_version_main = "0.6.2"
mai_version_fix = "snapshot-2"
mai_version_fix = ""
if mai_version_fix:
if is_test:
@@ -196,6 +196,9 @@ class BotConfig:
sub_heart_flow_freeze_time: int = 120 # 子心流冻结时间，超过这个时间没有回复，子心流会冻结，间隔 单位秒
sub_heart_flow_stop_time: int = 600 # 子心流停止时间，超过这个时间没有回复，子心流会停止，间隔 单位秒
heart_flow_update_interval: int = 300 # 心流更新频率，间隔 单位秒
observation_context_size: int = 20 # 心流观察到的最长上下文大小，超过这个值的上下文会被压缩
compressed_length: int = 5 # 不能大于observation_context_size,心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5
compress_length_limit: int = 5 #最多压缩份数，超过该数值的压缩上下文会被删除
# willing
willing_mode: str = "classical" # 意愿模式
@@ -440,6 +443,16 @@ class BotConfig:
config.heart_flow_update_interval = heartflow_config.get(
"heart_flow_update_interval", config.heart_flow_update_interval
)
if config.INNER_VERSION in SpecifierSet(">=1.3.0"):
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.compress_length_limit = heartflow_config.get(
"compress_length_limit", config.compress_length_limit
)
def willing(parent: dict):
willing_config = parent["willing"]
@@ -477,7 +490,7 @@ class BotConfig:
"llm_emotion_judge",
"vlm",
"embedding",
"moderation",
"llm_tool_use",
"llm_observation",
"llm_sub_heartflow",
"llm_heartflow",
@@ -489,7 +502,7 @@ 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}
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
@@ -502,6 +515,7 @@ class BotConfig:
stable_item.append("stream")
pricing_item = ["pri_in", "pri_out"]
# 从配置中原始拷贝稳定字段
for i in stable_item:
# 如果 字段 属于计费项 且获取不到，那默认值是 0
@@ -519,6 +533,13 @@ class BotConfig:
logger.error(f"{item} 中的必要字段不存在，请检查")
raise KeyError(f"{item} 中的必要字段 {e} 不存在，请检查") from e
# 如果配置中有temp参数，就使用配置中的值
if "temp" in cfg_item:
cfg_target["temp"] = cfg_item["temp"]
else:
# 如果没有temp参数，就删除默认值
cfg_target.pop("temp", None)
provider = cfg_item.get("provider")
if provider is None:
logger.error(f"provider 字段在模型配置 {item} 中不存在，请检查")