feat: AI analysis engine refactor, dark theme polish & virtual position management

Core changes:
- Refactor FastAnalysisService: single LLM multi-factor analysis replaces
  7-agent pipeline; add multi-timeframe consensus, threshold calibration,
  confidence calibration, multi-model ensemble voting
- Add RAG memory injection and reflection validation (analysis_memory +
  reflection worker)
- Simplify billing config: remove unused strategy_run/backtest/portfolio_monitor,
  add ai_code_gen separate billing (different token consumption scale)
- Settings hot-reload after save, no backend restart needed

Frontend:
- Global dark theme overhaul: pure black palette replacing blue-tinted colors
  across sidebar/header/dashboard/analysis/K-line/user-manage/profile/settings/billing
- Fix USDT payment modal dark theme (portal rendering broke CSS selectors)
- Refactor position modal: direction + quantity + entry price, remove add/reduce
  logic, show raw DB values on re-open, save exactly what user inputs
- Fix Polymarket prediction market dark text
- i18n for position modal title

Backend:
- Position management: one record per symbol (DELETE+INSERT replacing
  ON CONFLICT with side), fixes PnL showing 0 when switching long/short
- MarketDataCollector data fetching optimization
- portfolio_monitor scheduled monitoring improvements
- env.example reorganized: common config first, advanced config last

Documentation:
- README architecture diagram updated to FastAnalysisService flow
- Add virtual position, AI tuning config, billing items documentation
- Add INDICATOR_DEFINITIONS_CN.md, FRONTEND_FAST_ANALYSIS.md

Made-with: Cursor

backend_api_python/README.md

@@ -177,20 +177,19 @@ POST /api/users/change-password - Change own password
 ```text
 GET  /api/health
 GET  /api/indicator/kline
-POST /api/analysis/multi
+POST /api/fast-analysis/analyze    - Fast AI analysis (main entry)
+GET  /api/fast-analysis/history    - Analysis history
+GET  /api/fast-analysis/similar-patterns - RAG similar patterns
+POST /api/fast-analysis/feedback   - User feedback on analysis
 ```
 
-## AI memory augmentation
+## AI analysis & memory
 
-This backend includes a lightweight, privacy-first **memory-augmented multi-agent** system:
+Uses **FastAnalysisService** (single LLM call, multi-factor):
 
-- Memory DBs stored in PostgreSQL
-- API hooks:
-  - `POST /api/analysis/multi` (main entry)
-  - `POST /api/analysis/reflect` (manual learn from post-trade outcomes)
-- Controls in `.env`:
-  - `ENABLE_AGENT_MEMORY`, `AGENT_MEMORY_*`
-  - `ENABLE_REFLECTION_WORKER`, `REFLECTION_WORKER_INTERVAL_SEC`
+- Memory: `qd_analysis_memory` in PostgreSQL
+- API: `POST /api/fast-analysis/analyze` (main), `/history`, `/similar-patterns`, `/feedback`
+- Calibration: `AICalibrationService` tunes BUY/SELL thresholds from validated outcomes
 
 ## Frontend integration