Fetching metadata from the HF Docker repository...
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feat(ai): add bilingual account and chart labels
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feat(ai): add causal holding research and price replay dashboards
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fix(ui): restore full-day charts and remove synthetic metrics
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feat(ai): restore classic dashboards and independent account funds display
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fix(ai): distinguish proxy wave history from genuine L1 snapshots
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feat(ai): sync trade logs datasets and daily reflections
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feat(ai): restructure repository layout into clean docs and scripts directories
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feat(lob): embed today live data and fix date selector fallback
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feat(lob): support real-time intraday order book wave tracking
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feat(ai): clean date dropdown label display in saggese wave terminal
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feat(ai): support hybrid historical multi-day navigation with lazy api cache
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feat(ai): fix markpoint variable reference in saggese wave terminal
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feat(ai): bundle local echarts and add robust multi-cdn fallback with no-cache endpoint
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feat(ai): configure dashboard for ultra-fast single-day real-time execution
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feat(ai): optimize terminal asset payload and font loading for fast page rendering
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feat(ai): fix microprice drift and queue imbalance calculation with dynamic bps waves
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feat(ai): rename microstructure wave dashboard to institutional LOB terminal
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feat(ai): enhance saggese wave visual dashboard with multi-day navigation and debounced clean markers
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feat(ai): add saggese microstructure wave interactive visual dashboard
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feat(ai): support intraday historical date review and enable shorting execution
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feat(ai): isolate per-ticker ml models and add early pullback anti-trap logic
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feat(ai): implement robinhood style ml prediction trajectory and multi horizon ensemble
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feat(ai): integrate per-ticker ml models and replace hardcoded exit with dynamic trailing stop
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feat(ai): import HTMLResponse and track dashboard html files
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feat(ml): upgrade 2-week multi-asset probability engine and institutional ofi exits
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feat(ai): clean up temporary test scripts and streamline project data files
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feat(ai): integrate two stage ML architecture and human readable situation dashboard
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feat(ai): fix currentDate fallback to available dates in trade comparison dashboard
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feat(ai): fix empty chart fallback logic and fstring formatting in trade comparison dashboard
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feat(ai): add interactive buy short exit trade markers and tooltips directly on intraday kline chart
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feat(ai): add progressive single ticker kline lazy loading endpoint and refine watchlist
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feat(ai): optimize chart loading performance with simd vectorization and async zero-copy caching
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feat(ai): unify dynamic simulation engine and retrospective chart into synchronized master dashboard
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feat(ai): add interactive dynamic ml simulation replay engine and mockup visual
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feat(ai): fix template literal syntax escaping in retrospective report script
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feat(ai): upgrade retrospective chart to tradingview pro dark theme and fix api endpoints
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feat(ai): configure gitattributes to ignore generated html from language stats
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feat(ai): sync live trade markers and enable today date in retrospective dashboard
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feat(ai): purge c++ dependencies and enforce 100 percent pure python native architecture
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feat(ai): fix fast pnl fetcher parameters and accelerate live pnl polling
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feat(ai): fix multi date chart stitching and purge mu from frontend watchlist
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feat(ai): replace hardcoded time slots with dynamic feature driven ML regime modeling
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feat(ai): add intraday multi wave regime predictor and strictly enforce watchlist scope
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feat(ai): restore beautiful real intraday kline dashboard and fix JS filtering
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feat(ai): add historical date switcher and dual mode trade replay
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feat(ai): fix grouping method and enhance prompt
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feat(ai): fix grouping method and enhance prompt
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feat(ai): fix grouping method and enhance prompt
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feat(ai): fix grouping method and enhance prompt
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feat(ai): fix grouping method and enhance prompt
