Files
The-Ouroboros/docs/architecture.md
agentson 6b34367656
Some checks failed
Gitea CI / test (push) Failing after 3s
Gitea CI / test (pull_request) Failing after 3s
docs: v2/v3 구현 감사 문서 피드백 전체 반영 (#349)
11회 리뷰 사이클에서 남긴 [코멘트]를 모두 본문에 반영하고 블록을 제거한다.

변경 문서:
- docs/architecture.md: SmartScanner 동작 모드(both), 대시보드 10 API,
  DB 스키마(session_id/fx_pnl/mode), config 변수 갱신
- docs/commands.md: /api/pnl/history, /api/positions 엔드포인트 추가
- docs/testing.md: 테스트 수 고정값 제거, SmartScanner fallback 최신화,
  Dashboard 10 API routes 반영
- README.md: 고정 수치 제거, Gitea CI 명시, 파일별 수치 'CI 기준 변동' 표기
- CLAUDE.md: SmartScanner 섹션명 변경, 고정 수치 제거
- docs/requirements-log.md: #318~#331 구현 항목 추가
- docs/ouroboros/80_implementation_audit.md: ROOT-5/6/7 분리,
  REQ-V3-008 함수명 병기, v3 ~85% / 거버넌스 ~60%로 갱신
- docs/ouroboros/85_loss_recovery_action_plan.md: ACT-07 함수명 병기,
  테스트 수 갱신, 6.1/6.2 정확도 개선
- docs/ouroboros/60_repo_enforcement_checklist.md: CI job/step 구분 표 추가
- docs/ouroboros/README.md: 50_* 문서 (A)/(B) 보조 표기

Closes #349
2026-03-01 17:06:56 +09:00

756 lines
33 KiB
Markdown
Raw Permalink Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# System Architecture
## Overview
Self-evolving AI trading agent for global stock markets via KIS (Korea Investment & Securities) API. The main loop in `src/main.py` orchestrates components across multiple markets with two trading modes: daily (batch API calls) or realtime (per-stock decisions).
**v2 Proactive Playbook Architecture**: The system uses a "plan once, execute locally" approach. Pre-market, the AI generates a playbook of scenarios (one Gemini API call per market per day). During trading hours, a local scenario engine matches live market data against these pre-computed scenarios — no additional AI calls needed. This dramatically reduces API costs and latency.
## Trading Modes
The system supports two trading frequency modes controlled by the `TRADE_MODE` environment variable:
### Daily Mode (default)
Optimized for Gemini Free tier API limits (20 calls/day):
- **Batch decisions**: 1 API call per market per session
- **Fixed schedule**: 4 sessions per day at 6-hour intervals (configurable)
- **API efficiency**: Processes all stocks in a market simultaneously
- **Use case**: Free tier users, cost-conscious deployments
- **Configuration**:
```bash
TRADE_MODE=daily
DAILY_SESSIONS=4 # Sessions per day (1-10)
SESSION_INTERVAL_HOURS=6 # Hours between sessions (1-24)
```
**Example**: With 2 markets (US, KR) and 4 sessions/day = 8 API calls/day (within 20 call limit)
### Realtime Mode
High-frequency trading with individual stock analysis:
- **Per-stock decisions**: 1 API call per stock per cycle
- **60-second interval**: Continuous monitoring
- **Use case**: Production deployments with Gemini paid tier
- **Configuration**:
```bash
TRADE_MODE=realtime
```
**Note**: Realtime mode requires Gemini API subscription due to high call volume.
## Core Components
### 1. Broker (`src/broker/`)
**KISBroker** (`kis_api.py`) — Async KIS API client for domestic Korean market
- Automatic OAuth token refresh (valid for 24 hours)
- Leaky-bucket rate limiter (configurable RPS, default 2.0)
- POST body hash-key signing for order authentication
- Custom SSL context with disabled hostname verification for VTS (virtual trading) endpoint due to known certificate mismatch
- `fetch_market_rankings()` — Fetch volume surge rankings from KIS API
- `get_daily_prices()` — Fetch OHLCV history for technical analysis
**OverseasBroker** (`overseas.py`) — KIS overseas stock API wrapper
- Reuses KISBroker infrastructure (session, token, rate limiter) via composition
- Supports 9 global markets: US (NASDAQ/NYSE/AMEX), Japan, Hong Kong, China (Shanghai/Shenzhen), Vietnam (Hanoi/HCM)
- Different API endpoints for overseas price/balance/order operations
**Market Schedule** (`src/markets/schedule.py`) — Timezone-aware market management
- `MarketInfo` dataclass with timezone, trading hours, lunch breaks
- Automatic DST handling via `zoneinfo.ZoneInfo`
- `is_market_open()` checks weekends, trading hours, lunch breaks
- `get_open_markets()` returns currently active markets
- `get_next_market_open()` finds next market to open and when
- 10 global markets defined (KR, US_NASDAQ, US_NYSE, US_AMEX, JP, HK, CN_SHA, CN_SZA, VN_HNX, VN_HSX)
**Overseas Ranking API Methods** (added in v0.10.x):
- `fetch_overseas_rankings()` — Fetch overseas ranking universe (fluctuation / volume)
- Ranking endpoint paths and TR_IDs are configurable via environment variables
### 2. Analysis (`src/analysis/`)
**VolatilityAnalyzer** (`volatility.py`) — Technical indicator calculations
- ATR (Average True Range) for volatility measurement
- RSI (Relative Strength Index) using Wilder's smoothing method
- Price change percentages across multiple timeframes
- Volume surge ratios and price-volume divergence
- Momentum scoring (0-100 scale)
- Breakout/breakdown pattern detection
**TripleBarrierLabeler** (`triple_barrier.py`) — Financial time-series labeling (v2)
- Triple Barrier method: upper (take-profit), lower (stop-loss), time barrier
- First-touch labeling: labels confirmed by whichever barrier is breached first
- `max_holding_minutes` (calendar-minute) time barrier — session-aware, bar-period independent
- Tie-break mode: `"stop_first"` (conservative) or `"take_first"`
- Feature-label strict separation to prevent look-ahead bias
**BacktestPipeline** (`backtest_pipeline.py`) — End-to-end validation pipeline (v2)
- `run_v2_backtest_pipeline()`: cost guard → triple barrier labeling → walk-forward splits → fold scoring
- `BacktestPipelineResult`: artifact contract for reproducible output
- `fold_has_leakage()`: leakage detection utility
**WalkForwardSplit** (`walk_forward_split.py`) — Time-series validation (v2)
- Fold-based walk-forward splits (no random shuffling)
- Purge/Embargo: excludes N bars before/after fold boundaries to prevent data leakage
**BacktestExecutionModel** (`backtest_execution_model.py`) — Conservative fill simulation (v2/v3)
- Session-aware slippage: KRX_REG 5bps, NXT_AFTER 15bps, US_REG 3bps, US_PRE/DAY 30-50bps
- Order failure rate simulation per session
- Partial fill rate simulation with min/max ratio bounds
- Unfavorable-direction fill assumption (no simple close-price fill)
**BacktestCostGuard** (`backtest_cost_guard.py`) — Cost model validator (v2)
- `validate_backtest_cost_model()`: fail-fast check that session cost assumptions are present
- Enforces realistic cost assumptions before any backtest run proceeds
**SmartVolatilityScanner** (`smart_scanner.py`) — Python-first filtering pipeline
- **Domestic (KR)**:
- **Step 1**: Fetch domestic fluctuation ranking as primary universe
- **Step 2**: Fetch domestic volume ranking for liquidity bonus
- **Step 3**: Compute volatility-first score (max of daily change% and intraday range%)
- **Step 4**: Apply liquidity bonus and return top N candidates
- **Overseas (US/JP/HK/CN/VN)**:
- **Step 1**: Fetch overseas ranking universe (fluctuation rank + volume rank bonus)
- **Step 2**: Compute volatility-first score (max of daily change% and intraday range%)
- **Step 3**: Apply liquidity bonus from volume ranking
- **Step 4**: Return top N candidates (default 3)
- **Fallback (overseas only)**: If ranking API is unavailable, uses dynamic universe
from runtime active symbols + recent traded symbols + current holdings (no static watchlist)
- **Both modes**: Realtime 중심이지만 Daily 경로(`run_daily_session()`)에서도 후보 선별에 사용
**Benefits:**
- Reduces Gemini API calls from 20-30 stocks to 1-3 qualified candidates
- Fast Python-based filtering before expensive AI judgment
- Logs selection context (RSI-compatible proxy, volume_ratio, signal, score) for Evolution system
### 3. Brain (`src/brain/`)
**GeminiClient** (`gemini_client.py`) — AI decision engine powered by Google Gemini
- Constructs structured prompts from market data
- Parses JSON responses into `TradeDecision` objects (`action`, `confidence`, `rationale`)
- Forces HOLD when confidence < threshold (default 80)
- Falls back to safe HOLD on any parse/API error
- Handles markdown-wrapped JSON, malformed responses, invalid actions
**PromptOptimizer** (`prompt_optimizer.py`) — Token efficiency optimization
- Reduces prompt size while preserving decision quality
- Caches optimized prompts
**ContextSelector** (`context_selector.py`) — Relevant context selection for prompts
- Selects appropriate context layers for current market conditions
### 4. Risk Manager & Session Policy (`src/core/`)
**RiskManager** (`risk_manager.py`) — Safety circuit breaker and order validation
> **READ-ONLY by policy** (see [`docs/agents.md`](./agents.md))
- **Circuit Breaker**: Halts all trading via `SystemExit` when daily P&L drops below -3.0%
- Threshold may only be made stricter, never relaxed
- Calculated as `(total_eval - purchase_total) / purchase_total * 100`
- **Fat-Finger Protection**: Rejects orders exceeding 30% of available cash
- Must always be enforced, cannot be disabled
**OrderPolicy** (`order_policy.py`) — Session classification and order type enforcement (v3)
- `classify_session_id()`: Classifies current KR/US session from KST clock
- KR: `NXT_PRE` (08:00-08:50), `KRX_REG` (09:00-15:30), `NXT_AFTER` (15:30-20:00)
- US: `US_DAY` (10:00-18:00), `US_PRE` (18:00-23:30), `US_REG` (23:30-06:00), `US_AFTER` (06:00-07:00)
- Low-liquidity session detection: `NXT_AFTER`, `US_PRE`, `US_DAY`, `US_AFTER`
- Market order forbidden in low-liquidity sessions (`OrderPolicyRejected` raised)
- Limit/IOC/FOK orders always allowed
**KillSwitch** (`kill_switch.py`) — Emergency trading halt orchestration (v2)
- Fixed 5-step atomic sequence:
1. Block new orders (`new_orders_blocked = True`)
2. Cancel all unfilled orders
3. Refresh order state (query final status)
4. Reduce risk (force-close or reduce positions)
5. Snapshot state + send Telegram alert
- Async, injectable step callables — each step individually testable
- Highest priority: overrides overnight exception and all other rules
**BlackoutManager** (`blackout_manager.py`) — KIS maintenance window handling (v3)
- Configurable blackout windows (e.g., `23:30-00:10 KST`)
- `queue_order()`: Queues order intent during blackout, enforces max queue size
- `pop_recovery_batch()`: Returns queued intents after recovery
- Recovery revalidation path (in `src/main.py`):
- Stale BUY drop (position already exists)
- Stale SELL drop (position absent)
- `validate_order_policy()` rechecked
- Price drift check (>5% → drop, configurable via `BLACKOUT_RECOVERY_MAX_PRICE_DRIFT_PCT`)
### 5. Strategy (`src/strategy/`)
**PositionStateMachine** (`position_state_machine.py`) — 4-state sell state machine (v2)
- States: `HOLDING` → `BE_LOCK` → `ARMED` → `EXITED`
- `HOLDING`: Normal holding
- `BE_LOCK`: Profit ≥ `be_arm_pct` — stop-loss elevated to break-even
- `ARMED`: Profit ≥ `arm_pct` — peak-tracking trailing stop active
- `EXITED`: Position closed
- `promote_state()`: Immediately elevates to highest admissible state (handles gaps/skips)
- `evaluate_exit_first()`: EXITED conditions checked before state promotion
- Monotonic: states only move up, never down
**ExitRules** (`exit_rules.py`) — 4-layer composite exit logic (v2)
- **Hard Stop**: `unrealized <= hard_stop_pct` (always enforced, ATR-adaptive for KR)
- **Break-Even Lock**: Once in BE_LOCK/ARMED, exit if price falls to entry price
- **ATR Trailing Stop**: `trailing_stop_price = peak_price - (atr_multiplier_k × ATR)`
- **Model Signal**: Exit if `pred_down_prob >= model_prob_threshold AND liquidity_weak`
- `evaluate_exit()`: Returns `ExitEvaluation` with next state, exit flag, reason, trailing price
- `ExitRuleConfig`: Frozen dataclass with all tunable parameters
**Pre-Market Planner** (`pre_market_planner.py`) — AI playbook generation
- Runs before market open (configurable `PRE_MARKET_MINUTES`, default 30)
- Generates scenario-based playbooks via single Gemini API call per market
- Handles timeout (`PLANNER_TIMEOUT_SECONDS`, default 60) with defensive playbook fallback
- Persists playbooks to database for audit trail
**Scenario Engine** (`scenario_engine.py`) — Local scenario matching
- Matches live market data against pre-computed playbook scenarios
- No AI calls during trading hours — pure Python matching logic
- Returns matched scenarios with confidence scores
- Configurable `MAX_SCENARIOS_PER_STOCK` (default 5)
- Periodic rescan at `RESCAN_INTERVAL_SECONDS` (default 300)
**Playbook Store** (`playbook_store.py`) — Playbook persistence
- SQLite-backed storage for daily playbooks
- Date and market-based retrieval
- Status tracking (generated, active, expired)
**Models** (`models.py`) — Pydantic data models
- Scenario, Playbook, MatchResult, and related type definitions
### 6. Context System (`src/context/`)
**Context Store** (`store.py`) — L1-L7 hierarchical memory
- 7-layer context system (see [docs/context-tree.md](./context-tree.md)):
- L1: Tick-level (real-time price)
- L2: Intraday (session summary)
- L3: Daily (end-of-day)
- L4: Weekly (trend analysis)
- L5: Monthly (strategy review)
- L6: Daily Review (scorecard)
- L7: Evolution (long-term learning)
- Key-value storage with timeframe tagging
- SQLite persistence in `contexts` table
**Context Scheduler** (`scheduler.py`) — Periodic aggregation
- Scheduled summarization from lower to higher layers
- Configurable aggregation intervals
**Context Summarizer** (`summarizer.py`) — Layer summarization
- Aggregates lower-layer data into higher-layer summaries
### 7. Dashboard (`src/dashboard/`)
**FastAPI App** (`app.py`) — Read-only monitoring dashboard
- Runs as daemon thread when enabled (`--dashboard` CLI flag or `DASHBOARD_ENABLED=true`)
- Configurable host/port (`DASHBOARD_HOST`, `DASHBOARD_PORT`, default `127.0.0.1:8080`)
- Serves static HTML frontend
**10 API Endpoints:**
| Endpoint | Method | Description |
|----------|--------|-------------|
| `/` | GET | Static HTML dashboard |
| `/api/status` | GET | Daily trading status by market |
| `/api/playbook/{date}` | GET | Playbook for specific date and market |
| `/api/scorecard/{date}` | GET | Daily scorecard from L6_DAILY context |
| `/api/performance` | GET | Trading performance metrics (by market + combined) |
| `/api/context/{layer}` | GET | Query context by layer (L1-L7) |
| `/api/decisions` | GET | Decision log entries with outcomes |
| `/api/scenarios/active` | GET | Today's matched scenarios |
| `/api/pnl/history` | GET | P&L history time series |
| `/api/positions` | GET | Current open positions |
### 8. Notifications (`src/notifications/telegram_client.py`)
**TelegramClient** — Real-time event notifications via Telegram Bot API
- Sends alerts for trades, circuit breakers, fat-finger rejections, system events
- Non-blocking: failures are logged but never crash trading
- Rate-limited: 1 message/second default to respect Telegram API limits
- Auto-disabled when credentials missing
**TelegramCommandHandler** — Bidirectional command interface
- Long polling from Telegram API (configurable `TELEGRAM_POLLING_INTERVAL`)
- 9 interactive commands: `/help`, `/status`, `/positions`, `/report`, `/scenarios`, `/review`, `/dashboard`, `/stop`, `/resume`
- Authorization filtering by `TELEGRAM_CHAT_ID`
- Enable/disable via `TELEGRAM_COMMANDS_ENABLED` (default: true)
**Notification Types:**
- Trade execution (BUY/SELL with confidence)
- Circuit breaker trips (critical alert)
- Fat-finger protection triggers (order rejection)
- Market open/close events
- System startup/shutdown status
- Playbook generation results
- Stop-loss monitoring alerts
### 9. Evolution (`src/evolution/`)
**StrategyOptimizer** (`optimizer.py`) — Self-improvement loop
- Analyzes high-confidence losing trades from SQLite
- Asks Gemini to generate new `BaseStrategy` subclasses
- Validates generated strategies by running full pytest suite
- Simulates PR creation for human review
- Only activates strategies that pass all tests
**DailyReview** (`daily_review.py`) — End-of-day review
- Generates comprehensive trade performance summary
- Stores results in L6_DAILY context layer
- Tracks win rate, P&L, confidence accuracy
**DailyScorecard** (`scorecard.py`) — Performance scoring
- Calculates daily metrics (trades, P&L, win rate, avg confidence)
- Enables trend tracking across days
**Stop-Loss Monitoring** — Real-time position protection
- Monitors positions against stop-loss levels from playbook scenarios
- Sends Telegram alerts when thresholds approached or breached
### 10. Decision Logger (`src/logging/decision_logger.py`)
**DecisionLogger** — Comprehensive audit trail
- Logs every trading decision with full context snapshot
- Captures input data, rationale, confidence, and outcomes
- Supports outcome tracking (P&L, accuracy) for post-analysis
- Stored in `decision_logs` table with indexed queries
- Review workflow support (reviewed flag, review notes)
### 11. Data Integration (`src/data/`)
**External Data Sources** (optional):
- `news_api.py` — News sentiment data
- `market_data.py` — Extended market data
- `economic_calendar.py` — Economic event calendar
### 12. Backup (`src/backup/`)
**Disaster Recovery** (see [docs/disaster_recovery.md](./disaster_recovery.md)):
- `scheduler.py` — Automated backup scheduling
- `exporter.py` — Data export to various formats
- `cloud_storage.py` — S3-compatible cloud backup
- `health_monitor.py` — Backup integrity verification
## Data Flow
### Playbook Mode (Daily — Primary v2 Flow)
```
┌─────────────────────────────────────────────────────────────┐
│ Pre-Market Phase (before market open) │
└─────────────────────────────────────────────────────────────┘
┌──────────────────────────────────┐
│ Pre-Market Planner │
│ - 1 Gemini API call per market │
│ - Generate scenario playbook │
│ - Store in playbooks table │
└──────────────────┬───────────────┘
┌─────────────────────────────────────────────────────────────┐
│ Trading Hours (market open → close) │
└─────────────────────────────────────────────────────────────┘
┌──────────────────────────────────┐
│ Market Schedule Check │
│ - Get open markets │
│ - Filter by enabled markets │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Scenario Engine (local) │
│ - Match live data vs playbook │
│ - No AI calls needed │
│ - Return matched scenarios │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Risk Manager: Validate Order │
│ - Check circuit breaker │
│ - Check fat-finger limit │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Broker: Execute Order │
│ - Domestic: send_order() │
│ - Overseas: send_overseas_order()│
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Decision Logger + DB │
│ - Full audit trail │
│ - Context snapshot │
│ - Telegram notification │
└──────────────────┬───────────────┘
┌─────────────────────────────────────────────────────────────┐
│ Post-Market Phase │
└─────────────────────────────────────────────────────────────┘
┌──────────────────────────────────┐
│ Daily Review + Scorecard │
│ - Performance summary │
│ - Store in L6_DAILY context │
│ - Evolution learning │
└──────────────────────────────────┘
```
### Realtime Mode (with Smart Scanner)
```
┌─────────────────────────────────────────────────────────────┐
│ Main Loop (60s cycle per market) │
└─────────────────────────────────────────────────────────────┘
┌──────────────────────────────────┐
│ Market Schedule Check │
│ - Get open markets │
│ - Filter by enabled markets │
│ - Wait if all closed │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Smart Scanner (Python-first) │
│ - Domestic: fluctuation rank │
│ + volume rank bonus │
│ + volatility-first scoring │
│ - Overseas: ranking universe │
│ + volatility-first scoring │
│ - Fallback: dynamic universe │
│ - Return top 3 qualified stocks │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ For Each Qualified Candidate │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Broker: Fetch Market Data │
│ - Domestic: orderbook + balance │
│ - Overseas: price + balance │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Brain: Get Decision (AI) │
│ - Build prompt with market data │
│ - Call Gemini API │
│ - Parse JSON response │
│ - Return TradeDecision │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Risk Manager: Validate Order │
│ - Check circuit breaker │
│ - Check fat-finger limit │
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Broker: Execute Order │
│ - Domestic: send_order() │
│ - Overseas: send_overseas_order()│
└──────────────────┬───────────────┘
┌──────────────────────────────────┐
│ Decision Logger + Notifications │
│ - Log trade to SQLite │
│ - selection_context (JSON) │
│ - Telegram notification │
└──────────────────────────────────┘
```
## Database Schema
**SQLite** (`src/db.py`) — Database: `data/trades.db`
### trades
```sql
CREATE TABLE trades (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
stock_code TEXT NOT NULL,
action TEXT NOT NULL, -- BUY | SELL | HOLD
confidence INTEGER NOT NULL, -- 0-100
rationale TEXT,
quantity INTEGER,
price REAL,
pnl REAL DEFAULT 0.0,
market TEXT DEFAULT 'KR',
exchange_code TEXT DEFAULT 'KRX',
session_id TEXT DEFAULT 'UNKNOWN', -- v3: KRX_REG | NXT_AFTER | US_REG | US_PRE | ...
selection_context TEXT, -- JSON: {rsi, volume_ratio, signal, score}
decision_id TEXT, -- Links to decision_logs
strategy_pnl REAL, -- v3: Core strategy P&L (separated from FX)
fx_pnl REAL DEFAULT 0.0, -- v3: FX gain/loss for USD trades (schema ready, activation pending)
mode TEXT -- paper | live
);
```
### contexts
```sql
CREATE TABLE contexts (
id INTEGER PRIMARY KEY AUTOINCREMENT,
layer TEXT NOT NULL, -- L1 through L7
timeframe TEXT,
key TEXT NOT NULL,
value TEXT NOT NULL, -- JSON data
created_at TEXT NOT NULL,
updated_at TEXT NOT NULL
);
-- Indices: idx_contexts_layer, idx_contexts_timeframe, idx_contexts_updated
```
### decision_logs
```sql
CREATE TABLE decision_logs (
decision_id TEXT PRIMARY KEY,
timestamp TEXT NOT NULL,
stock_code TEXT,
market TEXT,
exchange_code TEXT,
session_id TEXT DEFAULT 'UNKNOWN', -- v3: session when decision was made
action TEXT,
confidence INTEGER,
rationale TEXT,
context_snapshot TEXT, -- JSON: full context at decision time
input_data TEXT, -- JSON: market data used
outcome_pnl REAL,
outcome_accuracy INTEGER,
reviewed INTEGER DEFAULT 0,
review_notes TEXT
);
-- Indices: idx_decision_logs_timestamp, idx_decision_logs_reviewed, idx_decision_logs_confidence
```
### playbooks
```sql
CREATE TABLE playbooks (
id INTEGER PRIMARY KEY AUTOINCREMENT,
date TEXT NOT NULL,
market TEXT NOT NULL,
status TEXT NOT NULL DEFAULT 'pending', -- pending → generated → active → expired
playbook_json TEXT NOT NULL, -- Full playbook with scenarios
generated_at TEXT NOT NULL,
token_count INTEGER,
scenario_count INTEGER,
match_count INTEGER DEFAULT 0
);
-- Indices: idx_playbooks_date, idx_playbooks_market
```
### context_metadata
```sql
CREATE TABLE context_metadata (
layer TEXT PRIMARY KEY,
description TEXT,
retention_days INTEGER,
aggregation_source TEXT
);
```
## Configuration
**Pydantic Settings** (`src/config.py`)
Loaded from `.env` file:
```bash
# Required
KIS_APP_KEY=your_app_key
KIS_APP_SECRET=your_app_secret
KIS_ACCOUNT_NO=XXXXXXXX-XX
GEMINI_API_KEY=your_gemini_key
# Optional — Trading Mode
MODE=paper # paper | live
TRADE_MODE=daily # daily | realtime
DAILY_SESSIONS=4 # Sessions per day (daily mode only)
SESSION_INTERVAL_HOURS=6 # Hours between sessions (daily mode only)
# Optional — Database
DB_PATH=data/trades.db
# Optional — Risk
CONFIDENCE_THRESHOLD=80
MAX_LOSS_PCT=3.0
MAX_ORDER_PCT=30.0
# Optional — Markets
ENABLED_MARKETS=KR,US # Comma-separated market codes
RATE_LIMIT_RPS=2.0 # KIS API requests per second
# Optional — Pre-Market Planner (v2)
PRE_MARKET_MINUTES=30 # Minutes before market open to generate playbook
MAX_SCENARIOS_PER_STOCK=5 # Max scenarios per stock in playbook
PLANNER_TIMEOUT_SECONDS=60 # Timeout for playbook generation
DEFENSIVE_PLAYBOOK_ON_FAILURE=true # Fallback on AI failure
RESCAN_INTERVAL_SECONDS=300 # Scenario rescan interval during trading
# Optional — v2 Exit Rules (State Machine)
STAGED_EXIT_BE_ARM_PCT=1.2 # Break-even lock threshold (%)
STAGED_EXIT_ARM_PCT=3.0 # Armed state threshold (%)
KR_ATR_STOP_MULTIPLIER_K=2.0 # ATR multiplier for KR dynamic hard stop
KR_ATR_STOP_MIN_PCT=-2.0 # KR hard stop floor (must tighten, negative)
KR_ATR_STOP_MAX_PCT=-7.0 # KR hard stop ceiling (loosest, negative)
# Optional — v2 Trade Filters
STOP_LOSS_COOLDOWN_MINUTES=120 # Cooldown after stop-loss before re-entry (same ticker)
US_MIN_PRICE=5.0 # Minimum US stock price for BUY ($)
# Optional — v3 Session Risk Management
SESSION_RISK_RELOAD_ENABLED=true # Reload risk params at session boundaries
SESSION_RISK_PROFILES_JSON="{}" # Per-session overrides JSON: {"KRX_REG": {"be_arm_pct": 1.0}}
OVERNIGHT_EXCEPTION_ENABLED=true # Allow holding through session close (conditions apply)
# Optional — v3 Blackout (KIS maintenance windows)
ORDER_BLACKOUT_ENABLED=true
ORDER_BLACKOUT_WINDOWS_KST=23:30-00:10 # Comma-separated: "HH:MM-HH:MM"
ORDER_BLACKOUT_QUEUE_MAX=500 # Max queued orders during blackout
BLACKOUT_RECOVERY_PRICE_REVALIDATION_ENABLED=true
BLACKOUT_RECOVERY_MAX_PRICE_DRIFT_PCT=5.0 # Drop recovery order if price drifted >5%
# Optional — Smart Scanner (realtime mode only)
RSI_OVERSOLD_THRESHOLD=30 # 0-50, oversold threshold
RSI_MOMENTUM_THRESHOLD=70 # 50-100, momentum threshold
VOL_MULTIPLIER=2.0 # Minimum volume ratio (2.0 = 200%)
SCANNER_TOP_N=3 # Max qualified candidates per scan
# Optional — Dashboard
DASHBOARD_ENABLED=false # Enable FastAPI dashboard
DASHBOARD_HOST=127.0.0.1 # Dashboard bind address
DASHBOARD_PORT=8080 # Dashboard port (1-65535)
# Optional — Telegram
TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
TELEGRAM_CHAT_ID=123456789
TELEGRAM_ENABLED=true
TELEGRAM_COMMANDS_ENABLED=true # Enable bidirectional commands
TELEGRAM_POLLING_INTERVAL=1.0 # Command polling interval (seconds)
# Optional — Backup
BACKUP_ENABLED=false
BACKUP_DIR=data/backups
S3_ENDPOINT_URL=...
S3_ACCESS_KEY=...
S3_SECRET_KEY=...
S3_BUCKET_NAME=...
S3_REGION=...
# Optional — External Data
NEWS_API_KEY=...
NEWS_API_PROVIDER=...
MARKET_DATA_API_KEY=...
# Position Sizing (optional)
POSITION_SIZING_ENABLED=true
POSITION_BASE_ALLOCATION_PCT=5.0
POSITION_MIN_ALLOCATION_PCT=1.0
POSITION_MAX_ALLOCATION_PCT=10.0
POSITION_VOLATILITY_TARGET_SCORE=50.0
# Legacy/compat scanner thresholds (kept for backward compatibility)
RSI_OVERSOLD_THRESHOLD=30
RSI_MOMENTUM_THRESHOLD=70
VOL_MULTIPLIER=2.0
# Overseas Ranking API (optional override; account-dependent)
OVERSEAS_RANKING_ENABLED=true
OVERSEAS_RANKING_FLUCT_TR_ID=HHDFS76200100
OVERSEAS_RANKING_VOLUME_TR_ID=HHDFS76200200
OVERSEAS_RANKING_FLUCT_PATH=/uapi/overseas-price/v1/quotations/inquire-updown-rank
OVERSEAS_RANKING_VOLUME_PATH=/uapi/overseas-price/v1/quotations/inquire-volume-rank
```
Tests use in-memory SQLite (`DB_PATH=":memory:"`) and dummy credentials via `tests/conftest.py`.
## Error Handling
### Connection Errors (Broker API)
- Retry with exponential backoff (2^attempt seconds)
- Max 3 retries per stock
- After exhaustion, skip stock and continue with next
### API Quota Errors (Gemini)
- Return safe HOLD decision with confidence=0
- Log error but don't crash
- Agent continues trading on next cycle
### Circuit Breaker Tripped
- Immediately halt via `SystemExit`
- Log critical message
- Requires manual intervention to restart
### Market Closed
- Wait until next market opens
- Use `get_next_market_open()` to calculate wait time
- Sleep until market open time
### Telegram API Errors
- Log warning but continue trading
- Missing credentials → auto-disable notifications
- Network timeout → skip notification, no retry
- Invalid token → log error, trading unaffected
- Rate limit exceeded → queued via rate limiter
### Playbook Generation Failure
- Timeout → fall back to defensive playbook (`DEFENSIVE_PLAYBOOK_ON_FAILURE`)
- API error → use previous day's playbook if available
- No playbook → skip pre-market phase, fall back to direct AI calls
**Guarantee**: Notification and dashboard failures never interrupt trading operations.