270 lines
8.9 KiB
Python
270 lines
8.9 KiB
Python
import json
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import os
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import re
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from pathlib import Path
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from typing import Final
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from urllib.parse import urlsplit, urlunsplit
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from dotenv import dotenv_values, load_dotenv
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BACKEND_ROOT: Final[Path] = Path(__file__).resolve().parents[1]
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PROJECT_ROOT: Final[Path] = BACKEND_ROOT.parent
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# Load env files used by this project.
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# Priority (high -> low):
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# 1) process environment
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# 2) project/.env.prod
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# 3) backend/.env
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#
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# We keep process-provided env untouched, while allowing .env.prod to override backend/.env.
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_process_env_keys = set(os.environ.keys())
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load_dotenv(BACKEND_ROOT / ".env", override=False)
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for _k, _v in dotenv_values(PROJECT_ROOT / ".env.prod").items():
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if _v is None:
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continue
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if _k in _process_env_keys:
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continue
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os.environ[_k] = str(_v)
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def _env_text(name: str, default: str) -> str:
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raw = os.getenv(name)
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if raw is None:
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return default
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return str(raw).replace("\\n", "\n")
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def _env_bool(name: str, default: bool) -> bool:
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raw = os.getenv(name)
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if raw is None:
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return default
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return str(raw).strip().lower() in {"1", "true", "yes", "on"}
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def _env_int(name: str, default: int, min_value: int, max_value: int) -> int:
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raw = os.getenv(name)
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if raw is None:
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return default
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try:
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value = int(str(raw).strip())
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except Exception:
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value = default
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return max(min_value, min(max_value, value))
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def _normalize_extension(raw: str) -> str:
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text = str(raw or "").strip().lower()
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if not text:
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return ""
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if text.startswith("*."):
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text = text[1:]
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if not text.startswith("."):
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text = f".{text}"
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if not re.fullmatch(r"\.[a-z0-9][a-z0-9._+-]{0,31}", text):
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return ""
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return text
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def _env_extensions(name: str, default: tuple[str, ...]) -> tuple[str, ...]:
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raw = os.getenv(name)
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if raw is None:
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source = list(default)
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else:
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source = re.split(r"[,;\s]+", str(raw))
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rows: list[str] = []
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for item in source:
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ext = _normalize_extension(item)
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if ext and ext not in rows:
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rows.append(ext)
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if raw is None:
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return tuple(rows or list(default))
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return tuple(rows)
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def _normalize_dir_path(path_value: str) -> str:
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raw = str(path_value or "").strip()
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if not raw:
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return raw
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raw = os.path.expandvars(os.path.expanduser(raw))
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p = Path(raw)
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if p.is_absolute():
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return str(p)
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return str((BACKEND_ROOT / p).resolve())
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def _load_json_object(path: Path) -> dict[str, object]:
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try:
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with open(path, "r", encoding="utf-8") as f:
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data = json.load(f)
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if isinstance(data, dict):
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return data
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except Exception:
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pass
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return {}
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def _read_template_md(raw: object) -> str:
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if raw is None:
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return ""
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return str(raw).replace("\r\n", "\n").strip()
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DATA_ROOT: Final[str] = _normalize_dir_path(os.getenv("DATA_ROOT", str(PROJECT_ROOT / "data")))
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BOTS_WORKSPACE_ROOT: Final[str] = _normalize_dir_path(
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os.getenv("BOTS_WORKSPACE_ROOT", str(PROJECT_ROOT / "workspace" / "bots"))
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)
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def _normalize_database_url(url: str) -> str:
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raw = str(url or "").strip()
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prefix = "sqlite:///"
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if not raw.startswith(prefix):
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return raw
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path_part = raw[len(prefix) :]
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if not path_part or path_part.startswith("/"):
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return raw
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abs_path = (BACKEND_ROOT / path_part).resolve()
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return f"{prefix}{abs_path.as_posix()}"
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def _database_engine(url: str) -> str:
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raw = str(url or "").strip().lower()
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if raw.startswith("sqlite"):
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return "sqlite"
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if raw.startswith("postgresql"):
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return "postgresql"
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if raw.startswith("mysql"):
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return "mysql"
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if "+" in raw:
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return raw.split("+", 1)[0]
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if "://" in raw:
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return raw.split("://", 1)[0]
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return "unknown"
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def _mask_database_url(url: str) -> str:
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raw = str(url or "").strip()
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if not raw or raw.startswith("sqlite"):
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return raw
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try:
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parsed = urlsplit(raw)
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if parsed.password is None:
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return raw
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host = parsed.hostname or ""
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if parsed.port:
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host = f"{host}:{parsed.port}"
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auth = parsed.username or ""
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if auth:
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auth = f"{auth}:***@{host}"
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else:
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auth = host
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netloc = auth
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return urlunsplit((parsed.scheme, netloc, parsed.path, parsed.query, parsed.fragment))
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except Exception:
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return raw
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_db_env = str(os.getenv("DATABASE_URL") or "").strip()
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DATABASE_URL: Final[str] = _normalize_database_url(
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_db_env if _db_env else f"sqlite:///{Path(DATA_ROOT) / 'nanobot_dashboard.db'}"
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)
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DATABASE_ENGINE: Final[str] = _database_engine(DATABASE_URL)
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DATABASE_URL_DISPLAY: Final[str] = _mask_database_url(DATABASE_URL)
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DATABASE_ECHO: Final[bool] = _env_bool("DATABASE_ECHO", True)
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UPLOAD_MAX_MB: Final[int] = _env_int("UPLOAD_MAX_MB", 100, 1, 2048)
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WORKSPACE_DOWNLOAD_EXTENSIONS_DEFAULT: Final[tuple[str, ...]] = (
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".pdf",
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".doc",
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".docx",
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".xls",
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".xlsx",
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".xlsm",
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".ppt",
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".pptx",
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".odt",
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".ods",
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".odp",
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".wps",
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)
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WORKSPACE_DOWNLOAD_EXTENSIONS: Final[tuple[str, ...]] = _env_extensions(
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"WORKSPACE_DOWNLOAD_EXTENSIONS",
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WORKSPACE_DOWNLOAD_EXTENSIONS_DEFAULT,
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)
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STT_ENABLED: Final[bool] = _env_bool("STT_ENABLED", True)
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STT_MODEL: Final[str] = str(os.getenv("STT_MODEL") or "ggml-small-q8_0.bin").strip()
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_DEFAULT_STT_MODEL_DIR: Final[Path] = (Path(DATA_ROOT) / "model").resolve()
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_configured_stt_model_dir = _normalize_dir_path(os.getenv("STT_MODEL_DIR", str(_DEFAULT_STT_MODEL_DIR)))
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if _configured_stt_model_dir and not Path(_configured_stt_model_dir).exists() and _DEFAULT_STT_MODEL_DIR.exists():
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STT_MODEL_DIR: Final[str] = str(_DEFAULT_STT_MODEL_DIR)
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else:
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STT_MODEL_DIR: Final[str] = _configured_stt_model_dir
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STT_DEVICE: Final[str] = str(os.getenv("STT_DEVICE") or "cpu").strip().lower() or "cpu"
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STT_MAX_AUDIO_SECONDS: Final[int] = _env_int("STT_MAX_AUDIO_SECONDS", 20, 5, 600)
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STT_DEFAULT_LANGUAGE: Final[str] = str(os.getenv("STT_DEFAULT_LANGUAGE") or "zh").strip().lower() or "zh"
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STT_FORCE_SIMPLIFIED: Final[bool] = _env_bool("STT_FORCE_SIMPLIFIED", True)
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STT_AUDIO_PREPROCESS: Final[bool] = _env_bool("STT_AUDIO_PREPROCESS", True)
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STT_AUDIO_FILTER: Final[str] = str(
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os.getenv("STT_AUDIO_FILTER") or "highpass=f=120,lowpass=f=7600,afftdn=nf=-20"
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).strip()
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STT_INITIAL_PROMPT: Final[str] = str(
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os.getenv("STT_INITIAL_PROMPT")
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or "以下内容可能包含简体中文和英文术语。请优先输出简体中文，英文单词、缩写、品牌名和数字保持原文，不要翻译。"
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).strip()
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REDIS_ENABLED: Final[bool] = _env_bool("REDIS_ENABLED", False)
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REDIS_URL: Final[str] = str(os.getenv("REDIS_URL") or "").strip()
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REDIS_PREFIX: Final[str] = str(os.getenv("REDIS_PREFIX") or "dashboard_nanobot").strip() or "dashboard_nanobot"
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REDIS_DEFAULT_TTL: Final[int] = _env_int("REDIS_DEFAULT_TTL", 60, 1, 86400)
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PANEL_ACCESS_PASSWORD: Final[str] = str(os.getenv("PANEL_ACCESS_PASSWORD") or "").strip()
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TOPIC_MCP_INTERNAL_URL: Final[str] = str(
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os.getenv("TOPIC_MCP_INTERNAL_URL") or "http://host.docker.internal:8000/api/mcp/topic"
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).strip()
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TEMPLATE_ROOT: Final[Path] = (BACKEND_ROOT / "templates").resolve()
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AGENT_MD_TEMPLATES_FILE: Final[Path] = TEMPLATE_ROOT / "agent_md_templates.json"
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TOPIC_PRESETS_TEMPLATES_FILE: Final[Path] = TEMPLATE_ROOT / "topic_presets.json"
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_agent_md_templates_raw = _load_json_object(AGENT_MD_TEMPLATES_FILE)
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DEFAULT_AGENTS_MD: Final[str] = _env_text(
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"DEFAULT_AGENTS_MD",
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_read_template_md(_agent_md_templates_raw.get("agents_md")),
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).strip()
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DEFAULT_SOUL_MD: Final[str] = _env_text(
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"DEFAULT_SOUL_MD",
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_read_template_md(_agent_md_templates_raw.get("soul_md")),
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).strip()
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DEFAULT_USER_MD: Final[str] = _env_text(
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"DEFAULT_USER_MD",
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_read_template_md(_agent_md_templates_raw.get("user_md")),
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).strip()
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DEFAULT_TOOLS_MD: Final[str] = _env_text(
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"DEFAULT_TOOLS_MD",
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_read_template_md(_agent_md_templates_raw.get("tools_md")),
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).strip()
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DEFAULT_IDENTITY_MD: Final[str] = _env_text(
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"DEFAULT_IDENTITY_MD",
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_read_template_md(_agent_md_templates_raw.get("identity_md")),
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).strip()
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_topic_presets_raw = _load_json_object(TOPIC_PRESETS_TEMPLATES_FILE)
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_topic_presets_list = _topic_presets_raw.get("presets")
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TOPIC_PRESET_TEMPLATES: Final[list[dict[str, object]]] = [
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dict(row) for row in (_topic_presets_list if isinstance(_topic_presets_list, list) else []) if isinstance(row, dict)
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]
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def load_agent_md_templates() -> dict[str, str]:
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raw = _load_json_object(AGENT_MD_TEMPLATES_FILE)
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rows: dict[str, str] = {}
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for key in ("agents_md", "soul_md", "user_md", "tools_md", "identity_md"):
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rows[key] = _read_template_md(raw.get(key))
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return rows
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def load_topic_presets_template() -> dict[str, object]:
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raw = _load_json_object(TOPIC_PRESETS_TEMPLATES_FILE)
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presets = raw.get("presets")
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if not isinstance(presets, list):
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return {"presets": []}
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return {"presets": [dict(row) for row in presets if isinstance(row, dict)]}
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