"""Runtime configuration — environment via Pydantic Settings + TOML-loaded data tables. Settings come from .env / process env. The TOML files (default.toml, portfolio.toml) define *what to track* — they're declarative content, not config knobs, so they stay separate from the settings model. """ from __future__ import annotations import tomllib from functools import lru_cache from pathlib import Path from typing import Any from pydantic import Field from pydantic_settings import BaseSettings, SettingsConfigDict CONFIG_DIR = Path(__file__).resolve().parent.parent / "config" class Settings(BaseSettings): """All runtime knobs. Read from process env, .env not needed in-container because compose injects vars directly; .env is supported for local dev.""" model_config = SettingsConfigDict( env_file=".env", env_file_encoding="utf-8", extra="ignore", ) # Database DATABASE_URL: str = "mysql+aiomysql://cassandra:changeme@db:3306/cassandra" # Redis: ephemeral pie storage during /api/analyze + batch buffer for # ticker_universe additions. No persistence — see compose service. REDIS_URL: str = "redis://redis:6379/0" # API keys (mirror prototype .env names) API_KEY: str = "" # Trading 212 key SECRET_KEY: str = "" # Trading 212 secret FRED_API_KEY: str = "" OPENROUTER_API_KEY: str = "" # App CASSANDRA_TOKEN: str = "" CASSANDRA_PORT: int = 8000 # Signing key for session cookies. Generate with: # python -c "import secrets; print(secrets.token_urlsafe(32))" # Falls back to CASSANDRA_TOKEN if unset (acceptable for single-host dev). CASSANDRA_SESSION_SECRET: str = "" # Set to false (or 0/no) to disable /signup after the first account is # created. Phase A leaves this open so the operator can self-onboard. CASSANDRA_SIGNUP_ENABLED: bool = True # SMTP for email OTP verification. If SMTP_SERVER is empty, OTP codes # are written to stdout instead of sent — convenient for local dev. SMTP_SERVER: str = "" SMTP_PORT: int = 587 SMTP_USER: str = "" SMTP_PASSWORD: str = "" SMTP_USE_TLS: bool = True SMTP_FROM: str = "" # Defaults to SMTP_USER if blank CASSANDRA_BASE_CURRENCY: str = "GBP" CASSANDRA_ANCHOR_DATE: str = "" CASSANDRA_MOCK: bool = False # Server-side pepper for the cloud-sync outer wrap. Generate with: # python -c "import secrets; print(secrets.token_urlsafe(32))" # When empty, the outer layer degrades to "salt by user_id only" — fine # for dev, but a prod DB leak would then suffice to brute-force PINs # offline. The startup log warns if this is empty on a non-sqlite DB. PORTFOLIO_SYNC_PEPPER: str = "" # AI log — provider abstraction with fallback chain. # `LLM_PROVIDER` is the primary; `LLM_FALLBACK` kicks in if the primary # raises (after its own internal retries). Set LLM_FALLBACK="" to # disable the fallback. LLM_PROVIDER: str = "deepseek" LLM_FALLBACK: str = "openrouter" # DeepSeek-direct (cheaper, primary). DEEPSEEK_API_KEY: str = "" DEEPSEEK_URL: str = "https://api.deepseek.com/chat/completions" DEEPSEEK_MODEL: str = "deepseek-v4-flash" # OpenRouter (fallback, also a valid primary). OPENROUTER_MODEL: str = "deepseek/deepseek-v4-flash" OPENROUTER_MONTHLY_CAP_USD: float = 20.0 # Tone axis. PRO was dropped in PROMPT_VERSION 6 (audience pivot to # young investors); legacy values are silently mapped to INTERMEDIATE # by app.services.openrouter._resolve_tone. CASSANDRA_TONE: str = "INTERMEDIATE" # NOVICE | INTERMEDIATE CASSANDRA_ANALYSIS: str = "SPECULATIVE" # DRY | SPECULATIVE BETA_MODE: bool = True # Shows a "BETA" pill in the app header. Flip to False at GA. # Config file locations (overridable for tests) BASELINE_TOML: Path = Field(default_factory=lambda: CONFIG_DIR / "default.toml") PORTFOLIO_TOML: Path = Field(default_factory=lambda: CONFIG_DIR / "portfolio.toml") @lru_cache def get_settings() -> Settings: return Settings() # --- TOML data tables -------------------------------------------------------- def _merge_toml(*paths: Path) -> dict[str, Any]: """Read TOML files in order; later ones override earlier at the top level (with shallow dict-merge for nested tables).""" out: dict[str, Any] = {} for path in paths: if not path.exists(): continue with path.open("rb") as f: data = tomllib.load(f) for k, v in data.items(): if isinstance(v, dict) and isinstance(out.get(k), dict): out[k].update(v) else: out[k] = v return out def load_groups(*paths: Path) -> dict[str, list[tuple[str, str, str]]]: """[(symbol, label, note), ...] per group name.""" data = _merge_toml(*paths) out: dict[str, list[tuple[str, str, str]]] = {} for name, items in (data.get("groups") or {}).items(): out[name] = [ (it["symbol"], it.get("label", it["symbol"]), it.get("note", "")) for it in items ] return out def load_feeds(*paths: Path) -> dict[str, list[tuple[str, str]]]: """[(name, url), ...] per category name.""" data = _merge_toml(*paths) out: dict[str, list[tuple[str, str]]] = {} for cat, items in (data.get("feeds") or {}).items(): out[cat] = [(it["name"], it["url"]) for it in items] return out def load_presets(*paths: Path) -> dict[str, list[str]]: """Keyword presets for news filtering.""" data = _merge_toml(*paths) presets = (data.get("news") or {}).get("presets") or {} return {name: list(kw) for name, kw in presets.items()} def load_all() -> tuple[dict, dict, dict]: """Shortcut: groups, feeds, presets using the configured TOML paths.""" s = get_settings() return ( load_groups(s.BASELINE_TOML, s.PORTFOLIO_TOML), load_feeds(s.BASELINE_TOML, s.PORTFOLIO_TOML), load_presets(s.BASELINE_TOML, s.PORTFOLIO_TOML), )