Merge 0624bf4564 into fa4d01c23a
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Ashim Nandi
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"""
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System R Risk Intelligence Integration for TradingAgents
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=========================================================
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This example shows how to add System R (https://systemr.ai) as an external
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risk-validation layer on top of TradingAgents' built-in risk debate.
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How it works:
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1. TradingAgents runs its normal analyst -> trader -> risk-debate pipeline.
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2. Before the final decision is acted on, this wrapper calls System R's
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pre-trade-gate API to get an independent risk assessment.
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3. If System R vetoes the trade (gate="FAIL"), the decision is downgraded
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to HOLD regardless of what the internal agents decided.
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The pre-trade gate evaluates position sizing, drawdown limits, correlation
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risk, and concentration against the portfolio equity you supply.
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Prerequisites:
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pip install requests tradingagents
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Environment variables:
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SYSTEMR_API_KEY - your System R API key (get one at https://systemr.ai)
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For a full standalone trading agent with System R risk management, see:
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https://github.com/System-R-AI/demo-trading-agent
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"""
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import os
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import re
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import requests
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from typing import Tuple, Optional
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from dotenv import load_dotenv
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from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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load_dotenv()
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# ---------------------------------------------------------------------------
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# System R pre-trade gate
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# ---------------------------------------------------------------------------
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SYSTEMR_PRE_TRADE_GATE_URL = "https://agents.systemr.ai/v1/compound/pre-trade-gate"
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def call_systemr_pre_trade_gate(
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symbol: str,
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direction: str,
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entry_price: float,
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stop_price: float,
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equity: float,
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api_key: Optional[str] = None,
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) -> dict:
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"""Call System R's pre-trade-gate API for independent risk validation.
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The gate checks position sizing, drawdown limits, correlation risk, and
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portfolio concentration before a trade is executed.
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Args:
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symbol: Ticker symbol, e.g. "NVDA".
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direction: "LONG" or "SHORT".
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entry_price: Planned entry price.
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stop_price: Planned stop-loss price.
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equity: Total portfolio equity in USD.
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api_key: System R API key (falls back to SYSTEMR_API_KEY env var).
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Returns:
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API response dict. Key fields:
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- gate: "PASS" or "FAIL"
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- checks: list of individual risk checks and their results
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- summary: human-readable explanation
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Raises:
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requests.HTTPError on non-2xx responses.
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"""
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key = api_key or os.getenv("SYSTEMR_API_KEY", "")
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headers = {
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"Content-Type": "application/json",
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}
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if key:
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headers["X-API-Key"] = key
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payload = {
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"symbol": symbol,
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"direction": direction,
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"entry_price": entry_price,
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"stop_price": stop_price,
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"equity": equity,
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}
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resp = requests.post(
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SYSTEMR_PRE_TRADE_GATE_URL,
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json=payload,
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headers=headers,
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timeout=15,
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)
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resp.raise_for_status()
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return resp.json()
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# ---------------------------------------------------------------------------
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# Wrapper that adds System R validation to TradingAgentsGraph
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# ---------------------------------------------------------------------------
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def extract_decision(signal_text: str) -> str:
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"""Pull BUY / SELL / HOLD from the final signal text."""
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match = re.search(r"\b(BUY|SELL|HOLD)\b", signal_text.upper())
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return match.group(1) if match else "HOLD"
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def run_with_systemr_risk_gate(
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ticker: str,
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trade_date: str,
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equity: float = 100_000.0,
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entry_price: Optional[float] = None,
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stop_price: Optional[float] = None,
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config: Optional[dict] = None,
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) -> Tuple[str, dict, dict]:
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"""Run TradingAgents and validate the result through System R.
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Args:
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ticker: Stock ticker symbol (e.g. "NVDA").
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trade_date: Date string (e.g. "2024-05-10").
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equity: Portfolio equity for risk sizing (default $100k).
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entry_price: Planned entry price. If None, a placeholder is used.
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stop_price: Planned stop-loss price. If None, defaults to 2% below
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entry for BUY, 2% above entry for SELL.
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config: Optional TradingAgents config dict override.
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Returns:
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Tuple of (final_decision, full_signal, systemr_response).
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"""
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# 1. Run the standard TradingAgents pipeline
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cfg = {**DEFAULT_CONFIG, **(config or {})}
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ta = TradingAgentsGraph(debug=False, config=cfg)
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full_signal, decision = ta.propagate(ticker, trade_date)
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internal_decision = extract_decision(decision)
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print(f"[TradingAgents] Internal decision: {internal_decision}")
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# Nothing to gate if the agents already say HOLD
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if internal_decision == "HOLD":
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print("[System R] Skipping gate -- internal decision is HOLD.")
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return internal_decision, full_signal, {}
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# 2. Determine direction and prices for the gate
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direction = "LONG" if internal_decision == "BUY" else "SHORT"
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# Use provided prices or sensible defaults
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_entry = entry_price or 100.0 # placeholder when price is unknown
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if stop_price is None:
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# Default: 2% adverse move
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_stop = _entry * 0.98 if direction == "LONG" else _entry * 1.02
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else:
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_stop = stop_price
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# 3. Call System R pre-trade gate
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print(f"[System R] Calling pre-trade gate for {ticker} {direction} ...")
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try:
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gate_result = call_systemr_pre_trade_gate(
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symbol=ticker,
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direction=direction,
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entry_price=_entry,
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stop_price=_stop,
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equity=equity,
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)
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except requests.RequestException as exc:
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# If the external service is unreachable, log and fall through to
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# the internal decision (fail-open). Change to fail-closed if you
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# prefer safety over availability.
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print(f"[System R] Gate unavailable ({exc}); using internal decision.")
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return internal_decision, full_signal, {}
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gate_verdict = gate_result.get("gate", "UNKNOWN")
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print(f"[System R] Gate verdict: {gate_verdict}")
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if gate_result.get("summary"):
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print(f"[System R] Summary: {gate_result['summary']}")
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# 4. Apply the gate
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if gate_verdict == "PASS":
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final_decision = internal_decision
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print(f"[Final] Trade APPROVED -- executing {final_decision}.")
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else:
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final_decision = "HOLD"
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print("[Final] Trade BLOCKED by System R risk gate -- downgrading to HOLD.")
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return final_decision, full_signal, gate_result
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# ---------------------------------------------------------------------------
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# Main
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# ---------------------------------------------------------------------------
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if __name__ == "__main__":
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# Configure TradingAgents (adjust models to your preference)
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config = DEFAULT_CONFIG.copy()
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config["deep_think_llm"] = "gpt-4o"
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config["quick_think_llm"] = "gpt-4o-mini"
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config["max_debate_rounds"] = 1
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# Run with System R gate
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final, signal, gate = run_with_systemr_risk_gate(
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ticker="NVDA",
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trade_date="2024-05-10",
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equity=100_000,
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config=config,
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)
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print("\n" + "=" * 60)
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print(f"FINAL DECISION: {final}")
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if gate:
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print(f"RISK GATE: {gate.get('gate', 'N/A')}")
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print("=" * 60)
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