dennisthiessen
5d41ccac1c
Closes the action loop — instead of polling the dashboard, the platform pushes actionable signals to Telegram. New hourly 'alerts' job dispatches four toggleable triggers, deduped via a new alert_log table (cooldown-based for qualified/S-R/digest, watermark-based for score deterioration). Admin → Settings gains a Telegram panel (write-only bot token, chat ID, per-trigger toggles, Send Test). Credentials follow DB > env precedence (TELEGRAM_BOT_TOKEN / _CHAT_ID). Backend: alert_service + AlertLog model + migration 005, scheduler job, admin endpoints/schema. Frontend: AlertSettings panel, hooks, api, types. Deploy: run alembic upgrade (new alert_log table). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
28 lines
773 B
Python
28 lines
773 B
Python
from app.models.ticker import Ticker
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from app.models.ohlcv import OHLCVRecord
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from app.models.user import User
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from app.models.sentiment import SentimentScore
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from app.models.fundamental import FundamentalData
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from app.models.score import DimensionScore, CompositeScore
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from app.models.sr_level import SRLevel
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from app.models.trade_setup import TradeSetup
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from app.models.watchlist import WatchlistEntry
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from app.models.settings import SystemSetting, IngestionProgress
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from app.models.alert import AlertLog
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__all__ = [
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"Ticker",
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"OHLCVRecord",
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"User",
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"SentimentScore",
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"FundamentalData",
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"DimensionScore",
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"CompositeScore",
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"SRLevel",
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"TradeSetup",
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"WatchlistEntry",
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"SystemSetting",
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"IngestionProgress",
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"AlertLog",
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]
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