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remove：无用配置，整理配置文件

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This commit is contained in:
SengokuCola
2026-04-07 14:30:23 +08:00
parent 50a51757a8
commit f2b64cc58c
17 changed files with 159 additions and 1654 deletions
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12
src/config/config.py
View File

@@ -27,14 +27,15 @@ from .official_configs import (
MaiSakaConfig,
MaimMessageConfig,
MCPConfig,
PluginRuntimeConfig,
MemoryConfig,
MessageReceiveConfig,
PersonalityConfig,
PluginRuntimeConfig,
RelationshipConfig,
ResponsePostProcessConfig,
ResponseSplitterConfig,
TelemetryConfig,
VisualConfig,
VoiceConfig,
WebUIConfig,
)
@@ -55,7 +56,7 @@ CONFIG_DIR: Path = PROJECT_ROOT / "config"
BOT_CONFIG_PATH: Path = (CONFIG_DIR / "bot_config.toml").resolve().absolute()
MODEL_CONFIG_PATH: Path = (CONFIG_DIR / "model_config.toml").resolve().absolute()
MMC_VERSION: str = "1.0.0"
CONFIG_VERSION: str = "8.3.4"
CONFIG_VERSION: str = "8.4.1"
MODEL_CONFIG_VERSION: str = "1.13.1"
logger = get_logger("config")
@@ -73,6 +74,9 @@ class Config(ConfigBase):
personality: PersonalityConfig = Field(default_factory=PersonalityConfig)
"""人格配置类"""
visual: VisualConfig = Field(default_factory=VisualConfig)
"""视觉配置类"""
expression: ExpressionConfig = Field(default_factory=ExpressionConfig)
"""表达配置类"""
@@ -474,6 +478,10 @@ def load_config_from_file(
if env_migration.migrated:
logger.warning(f"检测到旧版环境变量绑定配置，已迁移到主配置: {env_migration.reason}")
config_data = env_migration.data
legacy_migration = try_migrate_legacy_bot_config_dict(config_data)
if legacy_migration.migrated:
logger.warning(t("config.legacy_migrated", reason=legacy_migration.reason))
config_data = legacy_migration.data
# 保留一份“干净”的原始数据副本，避免第一次 from_dict 过程中对 dict 的就地修改
original_data: dict[str, Any] = copy.deepcopy(config_data)
try:

80
src/config/legacy_migration.py
View File

@@ -75,6 +75,18 @@ def _migrate_env_value(section: dict[str, Any], key: str, parsed_env_value: Any,
return True
def _move_section_key(source: dict[str, Any], target: dict[str, Any], key: str) -> bool:
"""将配置项从旧分组移动到新分组，若新分组已有值则保留新值。"""
if key not in source:
return False
if key not in target:
target[key] = source[key]
source.pop(key, None)
return True
def _parse_triplet_target(s: str) -> Optional[dict[str, str]]:
"""
解析 "platform:id:type" -> {platform,item_id,rule_type}
@@ -273,6 +285,21 @@ def _migrate_extra_prompt_list(exp: dict[str, Any], key: str) -> bool:
return True
def _parse_multimodal_replyer(v: Any) -> Optional[bool]:
"""兼容旧 replyer_generator_type 到布尔开关的迁移。"""
if isinstance(v, bool):
return v
if not isinstance(v, str):
return None
normalized_value = v.strip().lower()
if normalized_value == "multimodal":
return True
if normalized_value == "legacy":
return False
return None
def migrate_legacy_bind_env_to_bot_config_dict(data: dict[str, Any]) -> MigrationResult:
"""将旧版环境变量中的绑定地址迁移到主配置结构。"""
@@ -351,12 +378,61 @@ def try_migrate_legacy_bot_config_dict(data: dict[str, Any]) -> MigrationResult:
migrated_any = True
reasons.append("chat.private_plan_style_removed")
personality = _as_dict(data.get("personality"))
visual = _as_dict(data.get("visual"))
if visual is None and (
(personality is not None and "visual_style" in personality)
or "multimodal_planner" in chat
or "replyer_generator_type" in chat
):
visual = {}
data["visual"] = visual
if visual is not None and personality is not None and "visual_style" in personality:
if "visual_style" not in visual:
visual["visual_style"] = personality["visual_style"]
personality.pop("visual_style", None)
migrated_any = True
reasons.append("personality.visual_style_moved_to_visual.visual_style")
if visual is not None and "multimodal_planner" in chat:
if "multimodal_planner" not in visual and isinstance(chat["multimodal_planner"], bool):
visual["multimodal_planner"] = chat["multimodal_planner"]
if "multimodal_planner" in visual:
chat.pop("multimodal_planner", None)
migrated_any = True
reasons.append("chat.multimodal_planner_moved_to_visual.multimodal_planner")
if visual is not None and "replyer_generator_type" in chat:
multimodal_replyer = _parse_multimodal_replyer(chat["replyer_generator_type"])
if "multimodal_replyer" not in visual and multimodal_replyer is not None:
visual["multimodal_replyer"] = multimodal_replyer
if "multimodal_replyer" in visual:
chat.pop("replyer_generator_type", None)
migrated_any = True
reasons.append("chat.replyer_generator_type_moved_to_visual.multimodal_replyer")
maisaka = _as_dict(data.get("maisaka"))
mem = _as_dict(data.get("memory"))
if maisaka is not None:
moved_memory_keys = ("enable_memory_query_tool", "memory_query_default_limit")
if any(key in maisaka for key in moved_memory_keys) and mem is None:
mem = {}
data["memory"] = mem
if mem is not None:
for moved_key in moved_memory_keys:
if _move_section_key(maisaka, mem, moved_key):
migrated_any = True
reasons.append(f"maisaka.{moved_key}_moved_to_memory")
if mem is not None:
if _migrate_target_item_list(mem, "global_memory_blacklist"):
migrated_any = True
reasons.append("memory.global_memory_blacklist")
for removed_key in (
"agent_timeout_seconds",
"global_memory",
"global_memory_blacklist",
"max_agent_iterations",
):
if removed_key in mem:

177
src/config/official_configs.py
View File

@@ -113,15 +113,6 @@ class PersonalityConfig(ConfigBase):
)
"""每次构建回复时，从 multiple_reply_style 中随机替换 reply_style 的概率（0.0-1.0）"""
visual_style: str = Field(
default="请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多30字，请注意不要分点，就输出一段文本",
json_schema_extra={
"x-widget": "textarea",
"x-icon": "image",
},
)
"""_wrap_识图提示词，不建议修改"""
states: list[str] = Field(
default_factory=lambda: [
"是一个女大学生，喜欢上网聊天，会刷小红书。",
@@ -148,6 +139,40 @@ class PersonalityConfig(ConfigBase):
"""状态概率，每次构建人格时替换personality的概率"""
class VisualConfig(ConfigBase):
"""视觉配置类"""
__ui_label__ = "视觉"
__ui_icon__ = "image"
multimodal_planner: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "image",
},
)
"""是否直接输入图片"""
multimodal_replyer: bool = Field(
default=False,
json_schema_extra={
"x-widget": "switch",
"x-icon": "git-branch",
},
)
"""是否启用 Maisaka 多模态 replyer 生成器"""
visual_style: str = Field(
default="请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多30字，请注意不要分点，就输出一段文本",
json_schema_extra={
"x-widget": "textarea",
"x-icon": "image",
},
)
"""_wrap_识图提示词，不建议修改"""
class RelationshipConfig(ConfigBase):
"""关系配置类"""
@@ -253,24 +278,6 @@ class ChatConfig(ConfigBase):
},
)
multimodal_planner: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "image",
},
)
"""是否直接输入图片"""
replyer_generator_type: Literal["legacy", "multimodal"] = Field(
default="legacy",
json_schema_extra={
"x-widget": "select",
"x-icon": "git-branch",
},
)
"""Maisaka replyer 生成器类型：legacy（旧版单 prompt）/ multimodal（多模态版，适合主循环直接展示图片）"""
enable_talk_value_rules: bool = Field(
default=True,
json_schema_extra={
@@ -373,24 +380,6 @@ class MemoryConfig(ConfigBase):
__ui_parent__ = "emoji"
max_agent_iterations: int = Field(
default=5,
ge=1,
json_schema_extra={
"x-widget": "input",
"x-icon": "layers",
},
)
"""记忆思考深度（最低为1）"""
agent_timeout_seconds: float = Field(
default=120.0,
json_schema_extra={
"x-widget": "input",
"x-icon": "clock",
},
)
"""最长回忆时间（秒）"""
global_memory: bool = Field(
default=False,
@@ -410,6 +399,26 @@ class MemoryConfig(ConfigBase):
)
"""_wrap_全局记忆黑名单，当启用全局记忆时，不将特定聊天流纳入检索"""
enable_memory_query_tool: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "database",
},
)
"""是否启用 Maisaka 内置长期记忆检索工具 query_memory"""
memory_query_default_limit: int = Field(
default=5,
ge=1,
le=20,
json_schema_extra={
"x-widget": "input",
"x-icon": "hash",
},
)
"""Maisaka 内置长期记忆检索工具 query_memory 的默认返回条数"""
long_term_auto_summary_enabled: bool = Field(
default=True,
json_schema_extra={
@@ -657,16 +666,6 @@ class ExpressionConfig(ConfigBase):
)
"""是否开启全局黑话模式，注意，此功能关闭后，已经记录的全局黑话不会改变，需要手动删除"""
enable_jargon_explanation: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "info",
},
)
"""是否在回复前尝试对上下文中的黑话进行解释（关闭可减少一次LLM调用，仅影响回复前的黑话匹配与解释，不影响黑话学习）"""
class VoiceConfig(ConfigBase):
"""语音识别配置类"""
@@ -700,7 +699,7 @@ class EmojiConfig(ConfigBase):
"""一次从多少个表情包中选择发送，最大为 64"""
max_reg_num: int = Field(
default=100,
default=64,
json_schema_extra={
"x-widget": "input",
"x-icon": "hash",
@@ -988,23 +987,6 @@ class DebugConfig(ConfigBase):
)
"""是否显示prompt"""
show_replyer_prompt: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "message-square",
},
)
"""是否显示回复器prompt"""
show_replyer_reasoning: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "brain",
},
)
show_maisaka_thinking: bool = Field(
default=True,
json_schema_extra={
@@ -1041,25 +1023,6 @@ class DebugConfig(ConfigBase):
)
"""是否显示记忆检索相关prompt"""
show_planner_prompt: bool = Field(
default=False,
json_schema_extra={
"x-widget": "switch",
"x-icon": "map",
},
)
"""是否显示planner的prompt和原始返回结果"""
show_lpmm_paragraph: bool = Field(
default=False,
json_schema_extra={
"x-widget": "switch",
"x-icon": "file-text",
},
)
"""是否显示lpmm找到的相关文段日志"""
class ExtraPromptItem(ConfigBase):
platform: str = Field(
default="",
@@ -1511,16 +1474,6 @@ class MaiSakaConfig(ConfigBase):
)
"""MaiSaka 使用的用户名称"""
max_internal_rounds: int = Field(
default=6,
ge=1,
json_schema_extra={
"x-widget": "input",
"x-icon": "repeat",
},
)
"""每个入站消息的最大内部规划轮数"""
planner_interrupt_max_consecutive_count: int = Field(
default=2,
ge=0,
@@ -1531,26 +1484,6 @@ class MaiSakaConfig(ConfigBase):
)
"""Planner 连续被新消息打断的最大次数，0 表示不启用打断"""
enable_memory_query_tool: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "database",
},
)
"""是否启用 Maisaka 内置长期记忆检索工具 query_memory"""
memory_query_default_limit: int = Field(
default=5,
ge=1,
le=20,
json_schema_extra={
"x-widget": "input",
"x-icon": "hash",
},
)
"""Maisaka 内置长期记忆检索工具 query_memory 的默认返回条数"""
tool_filter_task_name: str = Field(
default="utils",
json_schema_extra={