JOJO
3fd2214da0
深压缩从"建新对话+切过去"重构为标记当前对话历史前缀(deep_compacted)： 原文保留并照常显示，仅在 build_messages 构建请求时排除。conversation_id 不变，避免任务状态/目标模式/前端对话切换的大量适配带来的 bug。 - deep_compression.py: _mark_history_compacted 打标 + 重置 current_context_tokens 防自动续接死循环；总结请求传入正常 tools 以 100% 命中前缀缓存 - context.py build_messages: 跳过 deep_compacted 消息 - conversation.py /compress: 去掉切对话，按 compress_behavior 决定续接/等待 - 新增个性化设置 deep_compress_form(file/inject) 与 deep_compress_behavior(continue/wait，仅手动压缩生效) - 前端去掉强制切换对话，改为重载当前对话刷新展示 - AGENTS.md/CLAUDE.md: 补充默认中文交流约定等说明 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
726 lines
30 KiB
Python
726 lines
30 KiB
Python
"""Utilities for managing per-user personalization settings."""
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from __future__ import annotations
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import json
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from copy import deepcopy
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from pathlib import Path
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from typing import Any, Dict, Iterable, Optional, Union
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try:
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from config.limits import THINKING_FAST_INTERVAL
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except ImportError:
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THINKING_FAST_INTERVAL = 10
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from core.tool_config import TOOL_CATEGORIES
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from config.model_profiles import get_default_model_key, get_registered_model_keys
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ALLOWED_RUN_MODES = {"fast", "thinking", "deep"}
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ALLOWED_PERMISSION_MODES = {"readonly", "approval", "auto_approval", "unrestricted"}
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ALLOWED_THEMES = {"classic", "light", "dark"}
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ALLOWED_GOAL_REVIEW_MODES = {"readonly", "active"}
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ALLOWED_GOAL_END_CONDITIONS = {"max_turns", "max_tokens"}
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GOAL_MAX_TURNS_MIN = 1
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GOAL_MAX_TURNS_MAX = 100
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GOAL_MAX_TURNS_DEFAULT = 5
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GOAL_MAX_TOKENS_MIN = 1_000
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GOAL_MAX_TOKENS_MAX = 100_000_000
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PERSONALIZATION_FILENAME = "personalization.json"
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MAX_SHORT_FIELD_LENGTH = 20
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MAX_CONSIDERATION_LENGTH = 50
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MAX_CONSIDERATION_ITEMS = 10
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TONE_PRESETS = ["健谈", "幽默", "直言不讳", "鼓励性", "诗意", "企业商务", "打破常规", "同理心"]
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THINKING_INTERVAL_MIN = 1
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THINKING_INTERVAL_MAX = 50
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RECENT_CONVERSATIONS_PROMPT_LIMIT_MIN = 1
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RECENT_CONVERSATIONS_PROMPT_LIMIT_MAX = 30
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RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT = 10
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DEFAULT_SHALLOW_COMPRESS_TRIGGER_TOKENS = 80_000
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DEFAULT_SHALLOW_COMPRESS_KEEP_RECENT_TOOLS = 15
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DEFAULT_SHALLOW_COMPRESS_MAX_REPLACE_PER_ROUND = 10
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DEFAULT_SHALLOW_COMPRESS_TRIGGER_TOOL_CALLS_INTERVAL = 10
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DEFAULT_DEEP_COMPRESS_TRIGGER_TOKENS = 150_000
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MIN_COMPRESSION_TRIGGER_TOKENS = 1_000
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MAX_COMPRESSION_TRIGGER_TOKENS = 2_000_000
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MIN_SHALLOW_KEEP_RECENT_TOOLS = 0
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MAX_SHALLOW_KEEP_RECENT_TOOLS = 500
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MIN_SHALLOW_MAX_REPLACE_PER_ROUND = 1
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MAX_SHALLOW_MAX_REPLACE_PER_ROUND = 200
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MIN_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL = 1
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MAX_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL = 200
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MIN_SHALLOW_KEEP_USER_TURN_TOOLS = 0
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MAX_SHALLOW_KEEP_USER_TURN_TOOLS = 50
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DEFAULT_SHALLOW_KEEP_USER_TURN_TOOLS = 3
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DEFAULT_PERSONALIZATION_CONFIG: Dict[str, Any] = {
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"enabled": False,
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"communication_style": "default", # default / human_like
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"self_identify": "",
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"user_name": "",
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"use_custom_names": False,
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"profession": "",
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"tone": "",
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"considerations": [],
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"thinking_interval": None,
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"disabled_tool_categories": [],
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"enabled_skills": None,
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"skills_catalog_snapshot": None,
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"default_run_mode": None,
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"default_permission_mode": "unrestricted",
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"auto_generate_title": True,
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"recent_conversations_prompt_enabled": False,
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"recent_conversations_prompt_limit": RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT,
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"tool_intent_enabled": True,
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"skill_hints_enabled": False, # Skill 提示系统开关（默认关闭）
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"skill_strict_terminal_enabled": False, # 强约束：terminal 系列工具需先阅读 terminal-guide
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"skill_strict_sub_agent_enabled": False, # 强约束：子智能体系列工具需先阅读 sub-agent-guide
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"skill_strict_run_command_foreground_enabled": False, # 强约束：run_command 前台模式需先阅读 run-command-guide
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"skill_strict_run_command_background_enabled": False, # 强约束：run_command 后台模式需先阅读 run-command-guide
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"default_model": None,
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"image_compression": "original", # original / 1080p / 720p / 540p
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"auto_shallow_compress_enabled": False,
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"auto_deep_compress_enabled": False,
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"shallow_compress_trigger_tokens": None,
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"shallow_compress_keep_recent_tools": None,
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"shallow_compress_max_replace_per_round": None,
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"shallow_compress_trigger_tool_calls_interval": None,
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"shallow_compress_keep_user_turn_tools": None, # 保留最近N次用户输入后的工具不压缩（默认3）
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"deep_compress_trigger_tokens": None,
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"deep_compress_form": "file", # 深压缩形式：file-生成文件 / inject-直接注入文件全文
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"deep_compress_behavior": "continue", # 手动压缩行为：continue-注入并触发请求 / wait-仅插入等待用户
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"silent_tool_disable": True, # 禁用工具时不向模型插入提示（默认开启）
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"enhanced_tool_display": True, # 增强工具显示
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"versioning_restore_mode": "overwrite", # 版本回溯模式固定为 overwrite
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"agents_md_auto_inject": False, # AGENTS.md 自动注入开关
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"allow_root_file_creation": False, # 允许在根目录创建文件开关
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"theme": "classic", # 主题配色: classic-经典/light-明亮/dark-暗黑
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# 目标模式（Goal Mode）
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"goal_review_mode": "readonly", # readonly-仅读对话判断 / active-允许审核智能体跑只读命令取证
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"goal_end_conditions": ["max_turns"], # 结束方式，可多选：max_turns / max_tokens
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"goal_max_turns": GOAL_MAX_TURNS_DEFAULT, # 最多自动续命轮数
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"goal_max_tokens": None, # 累计(输入+输出)token 上限；None 表示不启用
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}
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__all__ = [
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"PERSONALIZATION_FILENAME",
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"DEFAULT_PERSONALIZATION_CONFIG",
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"TONE_PRESETS",
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"MAX_CONSIDERATION_ITEMS",
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"RECENT_CONVERSATIONS_PROMPT_LIMIT_MIN",
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"RECENT_CONVERSATIONS_PROMPT_LIMIT_MAX",
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"RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT",
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"load_personalization_config",
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"save_personalization_config",
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"ensure_personalization_config",
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"build_personalization_prompt",
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"sanitize_personalization_payload",
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"resolve_context_compression_settings",
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"validate_context_compression_settings",
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"ALLOWED_PERMISSION_MODES",
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]
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PathLike = Union[str, Path]
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def _ensure_parent(path: Path) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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def _to_path(base: PathLike) -> Path:
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base_path = Path(base).expanduser()
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if base_path.is_dir():
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return base_path / PERSONALIZATION_FILENAME
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return base_path
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def ensure_personalization_config(base_dir: PathLike) -> Dict[str, Any]:
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"""Ensure the personalization file exists and return its content."""
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path = _to_path(base_dir)
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_ensure_parent(path)
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if not path.exists():
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with open(path, "w", encoding="utf-8") as f:
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json.dump(DEFAULT_PERSONALIZATION_CONFIG, f, ensure_ascii=False, indent=2)
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return deepcopy(DEFAULT_PERSONALIZATION_CONFIG)
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return load_personalization_config(base_dir)
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def load_personalization_config(base_dir: PathLike) -> Dict[str, Any]:
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"""Load personalization config; fall back to defaults on errors."""
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path = _to_path(base_dir)
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_ensure_parent(path)
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if not path.exists():
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return ensure_personalization_config(base_dir)
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try:
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with open(path, "r", encoding="utf-8") as f:
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raw = json.load(f)
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sanitized = sanitize_personalization_payload(raw)
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# 若发现缺失字段（如默认模型）或数据被规范化，主动写回文件，避免下一次读取仍为旧格式
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if sanitized != raw:
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with open(path, "w", encoding="utf-8") as wf:
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json.dump(sanitized, wf, ensure_ascii=False, indent=2)
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return sanitized
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except (json.JSONDecodeError, OSError):
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# 重置为默认配置，避免错误阻塞
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with open(path, "w", encoding="utf-8") as f:
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json.dump(DEFAULT_PERSONALIZATION_CONFIG, f, ensure_ascii=False, indent=2)
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return deepcopy(DEFAULT_PERSONALIZATION_CONFIG)
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def sanitize_personalization_payload(
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payload: Optional[Dict[str, Any]],
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fallback: Optional[Dict[str, Any]] = None
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) -> Dict[str, Any]:
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"""Normalize payload structure and clamp field lengths."""
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base = deepcopy(DEFAULT_PERSONALIZATION_CONFIG)
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if fallback:
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base.update(fallback)
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data = payload or {}
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allowed_tool_categories = set(TOOL_CATEGORIES.keys())
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allowed_models = set(get_registered_model_keys(visible_only=True))
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allowed_image_modes = {"original", "1080p", "720p", "540p"}
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def _resolve_short_field(key: str) -> str:
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if key in data:
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return _sanitize_short_field(data.get(key))
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return _sanitize_short_field(base.get(key))
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base["enabled"] = bool(data.get("enabled", base["enabled"]))
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# 交流风格: default / human_like
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_comm_style = data.get("communication_style", base.get("communication_style", "default"))
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base["communication_style"] = "human_like" if _comm_style == "human_like" else "default"
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base["auto_generate_title"] = bool(data.get("auto_generate_title", base["auto_generate_title"]))
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base["recent_conversations_prompt_enabled"] = bool(
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data.get("recent_conversations_prompt_enabled", base.get("recent_conversations_prompt_enabled", False))
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)
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base["recent_conversations_prompt_limit"] = (
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_sanitize_optional_int(
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data.get("recent_conversations_prompt_limit", base.get("recent_conversations_prompt_limit")),
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min_value=RECENT_CONVERSATIONS_PROMPT_LIMIT_MIN,
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max_value=RECENT_CONVERSATIONS_PROMPT_LIMIT_MAX,
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)
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or RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT
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)
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base["self_identify"] = _resolve_short_field("self_identify")
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base["user_name"] = _resolve_short_field("user_name")
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base["profession"] = _resolve_short_field("profession")
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base["tone"] = _resolve_short_field("tone")
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if "considerations" in data:
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base["considerations"] = _sanitize_considerations(data.get("considerations"))
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else:
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base["considerations"] = _sanitize_considerations(base.get("considerations", []))
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if "thinking_interval" in data:
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base["thinking_interval"] = _sanitize_thinking_interval(data.get("thinking_interval"))
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else:
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base["thinking_interval"] = _sanitize_thinking_interval(base.get("thinking_interval"))
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# 工具意图提示开关
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if "tool_intent_enabled" in data:
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base["tool_intent_enabled"] = bool(data.get("tool_intent_enabled"))
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else:
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base["tool_intent_enabled"] = bool(base.get("tool_intent_enabled"))
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# Skill 提示系统开关
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if "skill_hints_enabled" in data:
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base["skill_hints_enabled"] = bool(data.get("skill_hints_enabled"))
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else:
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base["skill_hints_enabled"] = bool(base.get("skill_hints_enabled"))
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# Skill 强约束开关（仅针对已启用的 skill 生效）
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if "skill_strict_terminal_enabled" in data:
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base["skill_strict_terminal_enabled"] = bool(data.get("skill_strict_terminal_enabled"))
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else:
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base["skill_strict_terminal_enabled"] = bool(base.get("skill_strict_terminal_enabled", False))
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if "skill_strict_sub_agent_enabled" in data:
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base["skill_strict_sub_agent_enabled"] = bool(data.get("skill_strict_sub_agent_enabled"))
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else:
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base["skill_strict_sub_agent_enabled"] = bool(base.get("skill_strict_sub_agent_enabled", False))
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if "skill_strict_run_command_foreground_enabled" in data:
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base["skill_strict_run_command_foreground_enabled"] = bool(data.get("skill_strict_run_command_foreground_enabled"))
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else:
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base["skill_strict_run_command_foreground_enabled"] = bool(
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base.get("skill_strict_run_command_foreground_enabled", False)
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)
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if "skill_strict_run_command_background_enabled" in data:
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base["skill_strict_run_command_background_enabled"] = bool(data.get("skill_strict_run_command_background_enabled"))
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else:
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base["skill_strict_run_command_background_enabled"] = bool(
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base.get("skill_strict_run_command_background_enabled", False)
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)
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if "disabled_tool_categories" in data:
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base["disabled_tool_categories"] = _sanitize_tool_categories(data.get("disabled_tool_categories"), allowed_tool_categories)
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else:
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base["disabled_tool_categories"] = _sanitize_tool_categories(base.get("disabled_tool_categories"), allowed_tool_categories)
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if "enabled_skills" in data:
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base["enabled_skills"] = _sanitize_skills(data.get("enabled_skills"))
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else:
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base["enabled_skills"] = _sanitize_skills(base.get("enabled_skills"))
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if "skills_catalog_snapshot" in data:
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base["skills_catalog_snapshot"] = _sanitize_skills(data.get("skills_catalog_snapshot"))
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else:
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base["skills_catalog_snapshot"] = _sanitize_skills(base.get("skills_catalog_snapshot"))
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if "default_run_mode" in data:
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base["default_run_mode"] = _sanitize_run_mode(data.get("default_run_mode"))
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else:
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base["default_run_mode"] = _sanitize_run_mode(base.get("default_run_mode"))
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permission_mode = data.get("default_permission_mode", base.get("default_permission_mode"))
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if isinstance(permission_mode, str) and permission_mode in ALLOWED_PERMISSION_MODES:
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base["default_permission_mode"] = permission_mode
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elif base.get("default_permission_mode") not in ALLOWED_PERMISSION_MODES:
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base["default_permission_mode"] = "unrestricted"
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base["versioning_restore_mode"] = "overwrite"
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# 默认模型
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chosen_model = data.get("default_model", base.get("default_model"))
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if isinstance(chosen_model, str) and chosen_model in allowed_models:
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base["default_model"] = chosen_model
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elif allowed_models and base.get("default_model") not in allowed_models:
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try:
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base["default_model"] = get_default_model_key(visible_only=True)
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except Exception:
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base["default_model"] = None
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# 图片压缩模式
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img_mode = data.get("image_compression", base.get("image_compression"))
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if isinstance(img_mode, str) and img_mode in allowed_image_modes:
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base["image_compression"] = img_mode
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elif base.get("image_compression") not in allowed_image_modes:
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base["image_compression"] = "original"
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if "auto_shallow_compress_enabled" in data:
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base["auto_shallow_compress_enabled"] = bool(data.get("auto_shallow_compress_enabled"))
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else:
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base["auto_shallow_compress_enabled"] = bool(base.get("auto_shallow_compress_enabled", False))
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if "auto_deep_compress_enabled" in data:
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base["auto_deep_compress_enabled"] = bool(data.get("auto_deep_compress_enabled"))
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else:
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base["auto_deep_compress_enabled"] = bool(base.get("auto_deep_compress_enabled", False))
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if "shallow_compress_trigger_tokens" in data:
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base["shallow_compress_trigger_tokens"] = _sanitize_optional_int(
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data.get("shallow_compress_trigger_tokens"),
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min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
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max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
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)
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else:
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base["shallow_compress_trigger_tokens"] = _sanitize_optional_int(
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base.get("shallow_compress_trigger_tokens"),
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min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
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max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
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)
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if "shallow_compress_keep_recent_tools" in data:
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base["shallow_compress_keep_recent_tools"] = _sanitize_optional_int(
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data.get("shallow_compress_keep_recent_tools"),
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min_value=MIN_SHALLOW_KEEP_RECENT_TOOLS,
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max_value=MAX_SHALLOW_KEEP_RECENT_TOOLS,
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)
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else:
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base["shallow_compress_keep_recent_tools"] = _sanitize_optional_int(
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base.get("shallow_compress_keep_recent_tools"),
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min_value=MIN_SHALLOW_KEEP_RECENT_TOOLS,
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max_value=MAX_SHALLOW_KEEP_RECENT_TOOLS,
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)
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if "shallow_compress_keep_user_turn_tools" in data:
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base["shallow_compress_keep_user_turn_tools"] = _sanitize_optional_int(
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data.get("shallow_compress_keep_user_turn_tools"),
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min_value=MIN_SHALLOW_KEEP_USER_TURN_TOOLS,
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max_value=MAX_SHALLOW_KEEP_USER_TURN_TOOLS,
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)
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else:
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base["shallow_compress_keep_user_turn_tools"] = _sanitize_optional_int(
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base.get("shallow_compress_keep_user_turn_tools"),
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min_value=MIN_SHALLOW_KEEP_USER_TURN_TOOLS,
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max_value=MAX_SHALLOW_KEEP_USER_TURN_TOOLS,
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)
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if "shallow_compress_max_replace_per_round" in data:
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base["shallow_compress_max_replace_per_round"] = _sanitize_optional_int(
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data.get("shallow_compress_max_replace_per_round"),
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min_value=MIN_SHALLOW_MAX_REPLACE_PER_ROUND,
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max_value=MAX_SHALLOW_MAX_REPLACE_PER_ROUND,
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)
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else:
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base["shallow_compress_max_replace_per_round"] = _sanitize_optional_int(
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base.get("shallow_compress_max_replace_per_round"),
|
||
min_value=MIN_SHALLOW_MAX_REPLACE_PER_ROUND,
|
||
max_value=MAX_SHALLOW_MAX_REPLACE_PER_ROUND,
|
||
)
|
||
|
||
if "deep_compress_trigger_tokens" in data:
|
||
base["deep_compress_trigger_tokens"] = _sanitize_optional_int(
|
||
data.get("deep_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
)
|
||
else:
|
||
base["deep_compress_trigger_tokens"] = _sanitize_optional_int(
|
||
base.get("deep_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
)
|
||
|
||
# 深压缩形式：file（生成文件，引导语提示位置）/ inject（直接注入文件全文）
|
||
deep_form = data.get("deep_compress_form", base.get("deep_compress_form"))
|
||
if isinstance(deep_form, str) and deep_form.strip().lower() in ("file", "inject"):
|
||
base["deep_compress_form"] = deep_form.strip().lower()
|
||
else:
|
||
base["deep_compress_form"] = "file"
|
||
|
||
# 手动压缩行为：continue（注入并触发请求）/ wait（仅插入等待用户）
|
||
deep_behavior = data.get("deep_compress_behavior", base.get("deep_compress_behavior"))
|
||
if isinstance(deep_behavior, str) and deep_behavior.strip().lower() in ("continue", "wait"):
|
||
base["deep_compress_behavior"] = deep_behavior.strip().lower()
|
||
else:
|
||
base["deep_compress_behavior"] = "continue"
|
||
|
||
if "shallow_compress_trigger_tool_calls_interval" in data:
|
||
base["shallow_compress_trigger_tool_calls_interval"] = _sanitize_optional_int(
|
||
data.get("shallow_compress_trigger_tool_calls_interval"),
|
||
min_value=MIN_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
max_value=MAX_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
)
|
||
else:
|
||
base["shallow_compress_trigger_tool_calls_interval"] = _sanitize_optional_int(
|
||
base.get("shallow_compress_trigger_tool_calls_interval"),
|
||
min_value=MIN_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
max_value=MAX_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
)
|
||
|
||
# 静默禁用工具提示
|
||
if "silent_tool_disable" in data:
|
||
base["silent_tool_disable"] = bool(data.get("silent_tool_disable"))
|
||
else:
|
||
base["silent_tool_disable"] = bool(base.get("silent_tool_disable"))
|
||
|
||
# 增强工具显示
|
||
if "enhanced_tool_display" in data:
|
||
base["enhanced_tool_display"] = bool(data.get("enhanced_tool_display"))
|
||
else:
|
||
base["enhanced_tool_display"] = bool(base.get("enhanced_tool_display", True))
|
||
|
||
# 使用自定义称呼
|
||
if "use_custom_names" in data:
|
||
base["use_custom_names"] = bool(data.get("use_custom_names"))
|
||
else:
|
||
base["use_custom_names"] = bool(base.get("use_custom_names"))
|
||
|
||
# AGENTS.md 自动注入开关
|
||
if "agents_md_auto_inject" in data:
|
||
base["agents_md_auto_inject"] = bool(data.get("agents_md_auto_inject"))
|
||
else:
|
||
base["agents_md_auto_inject"] = bool(base.get("agents_md_auto_inject", False))
|
||
|
||
# 允许根目录创建文件开关
|
||
if "allow_root_file_creation" in data:
|
||
base["allow_root_file_creation"] = bool(data.get("allow_root_file_creation"))
|
||
else:
|
||
base["allow_root_file_creation"] = bool(base.get("allow_root_file_creation", False))
|
||
|
||
# 主题配色
|
||
theme_value = data.get("theme", base.get("theme"))
|
||
if isinstance(theme_value, str) and theme_value in ALLOWED_THEMES:
|
||
base["theme"] = theme_value
|
||
elif base.get("theme") not in ALLOWED_THEMES:
|
||
base["theme"] = "classic"
|
||
|
||
# 目标模式：审核模式
|
||
goal_review_mode = data.get("goal_review_mode", base.get("goal_review_mode"))
|
||
if isinstance(goal_review_mode, str) and goal_review_mode in ALLOWED_GOAL_REVIEW_MODES:
|
||
base["goal_review_mode"] = goal_review_mode
|
||
elif base.get("goal_review_mode") not in ALLOWED_GOAL_REVIEW_MODES:
|
||
base["goal_review_mode"] = "readonly"
|
||
|
||
# 目标模式：结束方式（多选）
|
||
if "goal_end_conditions" in data:
|
||
base["goal_end_conditions"] = _sanitize_goal_end_conditions(data.get("goal_end_conditions"))
|
||
else:
|
||
base["goal_end_conditions"] = _sanitize_goal_end_conditions(base.get("goal_end_conditions"))
|
||
|
||
# 目标模式：最大轮数
|
||
if "goal_max_turns" in data:
|
||
base["goal_max_turns"] = _sanitize_optional_int(
|
||
data.get("goal_max_turns"), min_value=GOAL_MAX_TURNS_MIN, max_value=GOAL_MAX_TURNS_MAX
|
||
) or GOAL_MAX_TURNS_DEFAULT
|
||
else:
|
||
base["goal_max_turns"] = _sanitize_optional_int(
|
||
base.get("goal_max_turns"), min_value=GOAL_MAX_TURNS_MIN, max_value=GOAL_MAX_TURNS_MAX
|
||
) or GOAL_MAX_TURNS_DEFAULT
|
||
|
||
# 目标模式：累计 token 上限（可空）
|
||
if "goal_max_tokens" in data:
|
||
base["goal_max_tokens"] = _sanitize_optional_int(
|
||
data.get("goal_max_tokens"), min_value=GOAL_MAX_TOKENS_MIN, max_value=GOAL_MAX_TOKENS_MAX
|
||
)
|
||
else:
|
||
base["goal_max_tokens"] = _sanitize_optional_int(
|
||
base.get("goal_max_tokens"), min_value=GOAL_MAX_TOKENS_MIN, max_value=GOAL_MAX_TOKENS_MAX
|
||
)
|
||
|
||
return base
|
||
|
||
|
||
def _sanitize_goal_end_conditions(value: Any) -> list:
|
||
"""清洗目标模式结束方式列表，保证至少包含 max_turns。"""
|
||
cleaned: list = []
|
||
if isinstance(value, list):
|
||
for item in value:
|
||
if isinstance(item, str) and item in ALLOWED_GOAL_END_CONDITIONS and item not in cleaned:
|
||
cleaned.append(item)
|
||
if "max_turns" not in cleaned:
|
||
cleaned.insert(0, "max_turns")
|
||
return cleaned
|
||
|
||
|
||
def _sanitize_skills(value: Any) -> Optional[list]:
|
||
"""Sanitize enabled skills list / 清洗启用技能列表。"""
|
||
if value is None:
|
||
return None
|
||
if not isinstance(value, list):
|
||
return []
|
||
cleaned: list = []
|
||
seen = set()
|
||
for item in value:
|
||
if not isinstance(item, str):
|
||
continue
|
||
skill_id = item.strip()
|
||
if not skill_id or skill_id in seen:
|
||
continue
|
||
cleaned.append(skill_id)
|
||
seen.add(skill_id)
|
||
return cleaned
|
||
|
||
|
||
def save_personalization_config(base_dir: PathLike, payload: Dict[str, Any]) -> Dict[str, Any]:
|
||
"""Persist sanitized personalization config and return it."""
|
||
existing = load_personalization_config(base_dir)
|
||
config = sanitize_personalization_payload(payload, fallback=existing)
|
||
validate_context_compression_settings(config)
|
||
path = _to_path(base_dir)
|
||
_ensure_parent(path)
|
||
with open(path, "w", encoding="utf-8") as f:
|
||
json.dump(config, f, ensure_ascii=False, indent=2)
|
||
return config
|
||
|
||
|
||
def _sanitize_optional_int(value: Any, *, min_value: int, max_value: int) -> Optional[int]:
|
||
if value is None or value == "":
|
||
return None
|
||
if isinstance(value, bool):
|
||
return None
|
||
try:
|
||
parsed = int(value)
|
||
except (TypeError, ValueError):
|
||
return None
|
||
if parsed < min_value:
|
||
return min_value
|
||
if parsed > max_value:
|
||
return max_value
|
||
return parsed
|
||
|
||
|
||
def resolve_context_compression_settings(config: Optional[Dict[str, Any]]) -> Dict[str, int]:
|
||
data = config or {}
|
||
shallow_trigger = _sanitize_optional_int(
|
||
data.get("shallow_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
) or DEFAULT_SHALLOW_COMPRESS_TRIGGER_TOKENS
|
||
shallow_keep_recent = _sanitize_optional_int(
|
||
data.get("shallow_compress_keep_recent_tools"),
|
||
min_value=MIN_SHALLOW_KEEP_RECENT_TOOLS,
|
||
max_value=MAX_SHALLOW_KEEP_RECENT_TOOLS,
|
||
)
|
||
if shallow_keep_recent is None:
|
||
shallow_keep_recent = DEFAULT_SHALLOW_COMPRESS_KEEP_RECENT_TOOLS
|
||
shallow_keep_user_turn = _sanitize_optional_int(
|
||
data.get("shallow_compress_keep_user_turn_tools"),
|
||
min_value=MIN_SHALLOW_KEEP_USER_TURN_TOOLS,
|
||
max_value=MAX_SHALLOW_KEEP_USER_TURN_TOOLS,
|
||
)
|
||
if shallow_keep_user_turn is None:
|
||
shallow_keep_user_turn = DEFAULT_SHALLOW_KEEP_USER_TURN_TOOLS
|
||
shallow_max_replace = _sanitize_optional_int(
|
||
data.get("shallow_compress_max_replace_per_round"),
|
||
min_value=MIN_SHALLOW_MAX_REPLACE_PER_ROUND,
|
||
max_value=MAX_SHALLOW_MAX_REPLACE_PER_ROUND,
|
||
) or DEFAULT_SHALLOW_COMPRESS_MAX_REPLACE_PER_ROUND
|
||
shallow_trigger_interval = _sanitize_optional_int(
|
||
data.get("shallow_compress_trigger_tool_calls_interval"),
|
||
min_value=MIN_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
max_value=MAX_SHALLOW_TRIGGER_TOOL_CALLS_INTERVAL,
|
||
) or DEFAULT_SHALLOW_COMPRESS_TRIGGER_TOOL_CALLS_INTERVAL
|
||
deep_trigger = _sanitize_optional_int(
|
||
data.get("deep_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
) or DEFAULT_DEEP_COMPRESS_TRIGGER_TOKENS
|
||
if deep_trigger <= shallow_trigger:
|
||
deep_trigger = shallow_trigger + 1
|
||
return {
|
||
"shallow_trigger_tokens": shallow_trigger,
|
||
"shallow_keep_recent_tools": shallow_keep_recent,
|
||
"shallow_keep_user_turn_tools": shallow_keep_user_turn,
|
||
"shallow_max_replace_per_round": shallow_max_replace,
|
||
"shallow_trigger_tool_calls_interval": shallow_trigger_interval,
|
||
"deep_trigger_tokens": deep_trigger,
|
||
}
|
||
|
||
|
||
def validate_context_compression_settings(config: Optional[Dict[str, Any]]) -> None:
|
||
data = config or {}
|
||
shallow_trigger = _sanitize_optional_int(
|
||
data.get("shallow_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
) or DEFAULT_SHALLOW_COMPRESS_TRIGGER_TOKENS
|
||
deep_trigger = _sanitize_optional_int(
|
||
data.get("deep_compress_trigger_tokens"),
|
||
min_value=MIN_COMPRESSION_TRIGGER_TOKENS,
|
||
max_value=MAX_COMPRESSION_TRIGGER_TOKENS,
|
||
) or DEFAULT_DEEP_COMPRESS_TRIGGER_TOKENS
|
||
if deep_trigger <= shallow_trigger:
|
||
raise ValueError("深压缩触发上下文必须大于浅压缩触发上下文")
|
||
|
||
|
||
def _load_human_like_prompt() -> str:
|
||
"""加载拟人化风格提示词文件。"""
|
||
from config.paths import PROMPTS_DIR
|
||
try:
|
||
prompt_path = Path(PROMPTS_DIR) / "human_like_style.txt"
|
||
if prompt_path.exists():
|
||
return prompt_path.read_text(encoding="utf-8").strip()
|
||
except Exception:
|
||
pass
|
||
# 默认提示词
|
||
return (
|
||
"不要「像AI一样说话」，而是尽可能的模仿真人的说话方式或是模仿用户输入的说话方式。\n"
|
||
"尽可能不要用markdown格式，尤其是：\n"
|
||
"- ###、##、#等一二三级标题\n"
|
||
"- 等列表形式\n"
|
||
"- 不必要的** **加粗\n"
|
||
"- 刻意的分点分层次的回答\n"
|
||
"用户如果不输入emoji，就不要使用emoji回答。"
|
||
)
|
||
|
||
|
||
def build_personalization_prompt(
|
||
config: Optional[Dict[str, Any]],
|
||
include_header: bool = True
|
||
) -> Optional[str]:
|
||
"""Generate the personalization prompt text based on config."""
|
||
if not config or not config.get("enabled"):
|
||
return None
|
||
|
||
lines = []
|
||
if include_header:
|
||
lines.append("用户的个性化数据，请回答时务必参照这些信息")
|
||
|
||
if config.get("self_identify"):
|
||
lines.append(f"用户希望你自称：{config['self_identify']}")
|
||
if config.get("user_name"):
|
||
lines.append(f"用户希望你称呼为：{config['user_name']}")
|
||
if config.get("profession"):
|
||
lines.append(f"用户的职业是：{config['profession']}")
|
||
if config.get("tone"):
|
||
lines.append(f"用户希望你使用 {config['tone']} 的语气与TA交流")
|
||
|
||
considerations: Iterable[str] = config.get("considerations") or []
|
||
considerations = [item for item in considerations if item]
|
||
if considerations:
|
||
lines.append("用户希望你在回答问题时必须考虑的信息是：")
|
||
for idx, item in enumerate(considerations, 1):
|
||
lines.append(f"{idx}. {item}")
|
||
|
||
# 拟人化交流风格
|
||
if config.get("communication_style") == "human_like":
|
||
human_like_prompt = _load_human_like_prompt()
|
||
if human_like_prompt:
|
||
lines.append("\n【交流风格要求】")
|
||
lines.append(human_like_prompt)
|
||
|
||
if len(lines) == (1 if include_header else 0):
|
||
# 没有任何有效内容时不注入
|
||
return None
|
||
return "\n".join(lines)
|
||
|
||
|
||
def _sanitize_short_field(value: Optional[str]) -> str:
|
||
if not value:
|
||
return ""
|
||
text = str(value).strip()
|
||
if not text:
|
||
return ""
|
||
return text[:MAX_SHORT_FIELD_LENGTH]
|
||
|
||
|
||
def _sanitize_considerations(value: Any) -> list:
|
||
if not isinstance(value, list):
|
||
return []
|
||
cleaned = []
|
||
for item in value:
|
||
if not isinstance(item, str):
|
||
continue
|
||
text = item.strip()
|
||
if not text:
|
||
continue
|
||
cleaned.append(text[:MAX_CONSIDERATION_LENGTH])
|
||
if len(cleaned) >= MAX_CONSIDERATION_ITEMS:
|
||
break
|
||
return cleaned
|
||
|
||
|
||
def _sanitize_thinking_interval(value: Any) -> Optional[int]:
|
||
if value is None or value == "":
|
||
return None
|
||
try:
|
||
interval = int(value)
|
||
except (TypeError, ValueError):
|
||
return None
|
||
interval = max(THINKING_INTERVAL_MIN, min(THINKING_INTERVAL_MAX, interval))
|
||
if interval == THINKING_FAST_INTERVAL:
|
||
return None
|
||
return interval
|
||
|
||
|
||
def _sanitize_tool_categories(value: Any, allowed: set) -> list:
|
||
if not isinstance(value, list):
|
||
return []
|
||
result = []
|
||
dynamic_prefixes = ("mcp_server__",)
|
||
for item in value:
|
||
if not isinstance(item, str):
|
||
continue
|
||
candidate = item.strip()
|
||
if not candidate:
|
||
continue
|
||
dynamic_ok = candidate == "custom" or any(candidate.startswith(prefix) for prefix in dynamic_prefixes)
|
||
if candidate not in allowed and not dynamic_ok:
|
||
continue
|
||
if candidate not in result:
|
||
result.append(candidate)
|
||
return result
|
||
|
||
|
||
def _sanitize_run_mode(value: Any) -> Optional[str]:
|
||
if value is None:
|
||
return None
|
||
if isinstance(value, str):
|
||
candidate = value.strip().lower()
|
||
if candidate in ALLOWED_RUN_MODES:
|
||
return candidate
|
||
return None
|