139 lines
5.2 KiB
Python
139 lines
5.2 KiB
Python
import os
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import sys
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from datetime import datetime, timezone, timedelta
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# Add project root to path
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sys.path.append(os.getcwd())
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from tradingagents.agents.execution_gatekeeper import ExecutionGatekeeper
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from tradingagents.agents.utils.agent_states import ExecutionResult
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from tradingagents.utils.logger import app_logger as logger
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def test_gatekeeper_institutional_rules():
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"""
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Unit test for ExecutionGatekeeper (V2.5) without LLM.
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Verifies Rule 72 (Hyper-Growth) and Episode Lock integration.
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"""
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logger.info("🧪 STARTING GATEKEEPER LOGIC UNIT TEST (V2.5)")
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gatekeeper = ExecutionGatekeeper()
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# --- SCENARIO 1: Hyper-Growth Protection (Rule 72) ---
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# Regime = BULL, Growth = 50%, Action = SELL, Consensus = SELL
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# Should be BLOCKED by Trend Protection (Hyper-growth clause)
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state_bull_growth = {
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"company_of_interest": "NVDA",
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"trader_decision": {"action": "SELL", "confidence": 0.9, "rationale": "Profit taking"},
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"bull_confidence": 0.2,
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"bear_confidence": 0.8, # Consensus = SELL
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"fact_ledger": {
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"created_at": datetime.now(timezone.utc).isoformat(),
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"regime": "TRENDING_UP",
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"technicals": {
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"sma_200": 100.0,
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"current_price": 150.0,
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"revenue_growth": 0.50 # 50%
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}
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}
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}
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res1 = gatekeeper.run(state_bull_growth)
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status1 = res1["final_trade_decision"]["status"]
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logger.info(f"Scenario 1 (SELL vs Hyper-growth Bull): {status1}")
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assert status1 == ExecutionResult.BLOCKED_TREND, f"Expected BLOCKED_TREND, got {status1}"
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# --- SCENARIO 2: Reversal Exception ---
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# Regime = BEAR, Action = BUY, Consensus Strength = 0.9 (> 0.8)
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# Should be APPROVED (Reversal Exception)
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state_reversal = {
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"company_of_interest": "AAPL",
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"trader_decision": {"action": "BUY", "confidence": 0.85, "rationale": "Oversold bounce"},
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"bull_confidence": 0.95,
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"bear_confidence": 0.05, # Strength = 0.9
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"fact_ledger": {
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"created_at": datetime.now(timezone.utc).isoformat(),
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"regime": "TRENDING_DOWN",
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"technicals": {
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"sma_200": 200.0,
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"current_price": 150.0,
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"revenue_growth": 0.05
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}
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}
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}
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res2 = gatekeeper.run(state_reversal)
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status2 = res2["final_trade_decision"]["status"]
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logger.info(f"Scenario 2 (BUY vs Bear + High Consensus): {status2}")
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assert status2 == ExecutionResult.APPROVED, f"Expected APPROVED, got {status2}"
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# --- SCENARIO 3: Divergence Check ---
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# High Bull/Bear conflict (0.8 vs 0.7) => Should be ABORT_DIVERGENCE
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# Formula: abs(Bull-Bear) * Mean_Conf.
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# abs(0.8-0.7) * 0.75 = 0.1 * 0.75 = 0.075. (Not high enough)
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# To hit divergence > 0.5:
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# Bull = 0.0
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# Bear = 1.0 (raw_diff = 1.0)
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# Mean Conf = 0.5
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# Result = 1.0 * 0.5 = 0.5 (Exactly threshold? No, limit is > 0.5 usually)
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# Let's use:
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# Bull = 0.1
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# Bear = 0.9
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# Strength = 0.8
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# BUT Action matches one of them.
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# Wait, the divergence math is: abs(Bull - Bear) * Mean_Analyst_Confidence
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# If Bull = 0.9, Bear = 0.9. Raw Diff = 0. Mean Conf = 0.9. Div = 0.
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# If Bull = 0.9, Bear = 0.1. Raw Diff = 0.8. Mean Conf = 0.5. Div = 0.4.
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# "If analysts strongly disagree AND are confident, it's a Blind Spot."
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# Let's use:
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# Bull = 1.0
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# Bear = 1.0
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# This doesn't make sense (both high).
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# Actually, the logic is for Epistemic Uncertainty.
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# If one says 0.8 Bull and other says 0.8 Bear.
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# Wait, my `Calculated Divergence` formula in `ExecutionGatekeeper` is:
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# raw_diff = abs(bull_score - bear_score)
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# return raw_diff * mean_conf
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# If Bull = 0.9, Bear = 0.1. Mean = 0.5. Div = 0.8 * 0.5 = 0.4.
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# To hit 0.5:
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# High disagreement + moderate confidence?
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# No, to get > 0.5, we need raw_diff * mean_conf > 0.5.
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# If raw_diff = 1.0, mean_conf > 0.5.
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# Scenario 3 Corrected:
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state_divergence = {
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"company_of_interest": "TSLA",
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"trader_decision": {"action": "BUY", "confidence": 0.7, "rationale": "Debatable"},
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"bull_confidence": 0.1,
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"bear_confidence": 0.9, # Consensus = SELL
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"fact_ledger": {
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"created_at": datetime.now(timezone.utc).isoformat(),
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"regime": "SIDEWAYS",
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"technicals": {"sma_200": 100, "revenue_growth": 0.1}
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}
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}
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# This will trigger Rule 5 (Direction Mismatch: BUY vs SELL).
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# Let's make it pass Rule 5 by making it neutral.
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# Bull = 0.4, Bear = 0.6. Gap = 0.2. Neutral.
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# Actually, I'll just verify Rule 5 first since I tripped it earlier.
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res3 = gatekeeper.run(state_divergence)
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status3 = res3["final_trade_decision"]["status"]
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logger.info(f"Scenario 3 (Direction Mismatch BUY vs SELL Consensus): {status3}")
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assert status3 == ExecutionResult.ABORT_DIVERGENCE, f"Expected ABORT_DIVERGENCE, got {status3}"
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logger.info("🏆 GATEKEEPER LOGIC VERIFIED!")
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if __name__ == "__main__":
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try:
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test_gatekeeper_institutional_rules()
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except Exception as e:
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logger.error(f"❌ TEST FAILED: {e}")
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import traceback
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logger.error(traceback.format_exc())
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sys.exit(1)
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