dennisthiessen
e5166ed668
Richer LLM output (same grounded call, ~no extra cost): - All providers now also return a recommendation (buy/hold/avoid) and a thorough reasoning paragraph; Gemini now actually captures reasoning + grounding citations (it was dropping them). Stored on sentiment_scores (migration 008), exposed in the API; display-only — NOT fed into the composite/EV. - Ticker Sentiment panel shows an "LLM view" badge and a "Full analysis & sources" expander with the complete reasoning + citations. Search-budget scoping (Gemini grounding free tier = 5000/mo): - collect_sentiment now targets only watchlist + open paper trades + top-N by composite, skips tickers refreshed within sentiment_fresh_hours (72h), and caps per run (sentiment_max_per_run). Once the relevant set is fresh, runs spend 0 searches until it ages out — bounding monthly usage well under the free tier. - Widened sentiment lookback to 7d (scoring + display) so sparser collection still feeds the dimension score. Deploy: alembic upgrade (sentiment_scores.recommendation). Switch provider to Gemini Flash in Admin for the cost win (grounded, cheapest). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
79 lines
2.6 KiB
Python
79 lines
2.6 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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# 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 = "daily"
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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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# 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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