dennisthiessen
ebff19940b
A new /regime tab scoring how far the AI/Tech bull regime has deteriorated toward a re-rating as a single 0-100 index with per-signal breakdown and a 7/30-day trend. Intentionally decoupled: nothing reads its output to gate or score trades — the daily-pipeline membership is scheduling only. - regime_monitor_service: price sub-scores (P1-P6 via Alpaca, like market_regime), VIX + HY credit spreads via a small FRED helper, weighted aggregation over available signals (missing source -> n/a, dropped from the denominator), one snapshot row/day, and a ~90-day history backfill by replaying the already-fetched series as-of each past day. - F1/F3 fundamentals proposed by the configured grounded LLM (reuses sentiment_provider_service config resolution), with a manual override + lock. - regime_snapshots table (migration 011); endpoints on the existing market router; admin-editable weights/threshold; standalone /regime page. Data needs: prices via Alpaca, VIX/credit via FRED (optional key — signals show n/a without it). No LLM needed for history. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
95 lines
3.5 KiB
Python
95 lines
3.5 KiB
Python
from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")
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# Database
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database_url: str = "postgresql+asyncpg://stock_backend:changeme@localhost:5432/stock_data_backend"
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# Auth
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jwt_secret: str = "change-this-to-a-random-secret"
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jwt_expiry_minutes: int = 60
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# OHLCV Provider — Alpaca Markets
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alpaca_api_key: str = ""
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alpaca_api_secret: str = ""
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# Sentiment Provider — Gemini with Search Grounding (legacy)
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gemini_api_key: str = ""
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gemini_model: str = "gemini-2.0-flash"
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# Sentiment Provider — OpenAI
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openai_api_key: str = ""
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openai_model: str = "gpt-4o-mini"
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openai_sentiment_batch_size: int = 5
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# Sentiment Provider — DeepSeek / xAI (OpenAI-compatible; optional env fallback)
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deepseek_api_key: str = ""
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xai_api_key: str = ""
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# Fundamentals Provider — Financial Modeling Prep
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fmp_api_key: str = ""
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# Fundamentals Provider — Finnhub (optional fallback)
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finnhub_api_key: str = ""
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# Fundamentals Provider — Alpha Vantage (optional fallback)
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alpha_vantage_api_key: str = ""
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# Regime Monitor — FRED (VIX level + HY credit spreads). Optional: without it
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# the volatility (P5) and credit-spread (F2) signals are reported as n/a.
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fred_api_key: str = ""
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# Alerts — Telegram (optional env fallback; can also be set in Admin)
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telegram_bot_token: str = ""
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telegram_chat_id: str = ""
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# Scheduled Jobs
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data_collector_frequency: str = "daily"
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sentiment_poll_interval_minutes: int = 30
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# Sentiment search-budget controls (Gemini grounding free tier = 5000/month).
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# Only fetch sentiment for relevant tickers (watchlist + open trades + top-N by
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# composite), skip ones refreshed within fresh_hours, and cap per run.
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sentiment_fresh_hours: int = 72
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sentiment_max_per_run: int = 25
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sentiment_top_composite: int = 30
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fundamental_fetch_frequency: str = "weekly" # quarterly-ish data; weekly conserves API quota
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rr_scan_frequency: str = "daily"
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alerts_frequency: str = "hourly"
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fundamental_rate_limit_retries: int = 3
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fundamental_rate_limit_backoff_seconds: int = 15
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# Pause between tickers in the bulk fundamentals job. Free tiers throttle
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# hard (Finnhub ~60 calls/min, ~3 calls/ticker → ~3s/ticker); without
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# spacing the job bursts straight into 429s. 0 disables.
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fundamental_request_spacing_seconds: float = 3.0
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# Scoring Defaults
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default_watchlist_auto_size: int = 10
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default_rr_threshold: float = 1.5
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# Outcome evaluation: trading days before an undecided setup expires
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outcome_evaluation_max_bars: int = 30
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# OHLCV history depth to fetch. New tickers backfill this far; the manual
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# "data_backfill" job re-fetches the full window for everyone. ~5 years so
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# long-lookback factors (12-month momentum, 52-week high) and multi-regime
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# backtests become computable. ~252 trading days/year.
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ohlcv_history_days: int = 1825
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# Backtest parallelism: replay tickers across this many worker processes on
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# POSIX (forkserver), capped to cpu_count-1 so a core stays free for the web
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# server. 1 disables it (sequential). No effect on Windows / spawn-only
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# platforms — those fall back to a single worker thread.
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backtest_workers: int = 4
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# Database Pool
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db_pool_size: int = 5
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db_pool_timeout: int = 30
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# Logging
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log_level: str = "INFO"
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settings = Settings()
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