75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
from tradingagents.agents.utils.agent_utils import update_risk_debate_state
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from tradingagents.agents.utils.llm_utils import parse_llm_response
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def create_risky_debator(llm):
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def risky_node(state) -> dict:
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risk_debate_state = state["risk_debate_state"]
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history = risk_debate_state.get("history", "")
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current_safe_response = risk_debate_state.get("current_safe_response", "")
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current_neutral_response = risk_debate_state.get("current_neutral_response", "")
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market_research_report = state["market_report"]
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sentiment_report = state["sentiment_report"]
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news_report = state["news_report"]
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fundamentals_report = state["fundamentals_report"]
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trader_decision = state["trader_investment_plan"]
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prompt = f"""You are the Aggressive Trade Reviewer. Your job is to push for taking the trade if there is a short-term edge (5-14 days).
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## CORE RULES (CRITICAL)
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- Evaluate this ticker IN ISOLATION (no portfolio sizing, no portfolio impact).
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- Use ONLY the provided reports and the trader plan as evidence.
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- Focus on the upside path: what must happen for this to work, and how to structure the trade to capture it.
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## OUTPUT STRUCTURE (MANDATORY)
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### Stance
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State whether you agree with the Trader's direction (BUY/SELL) or flip it (no HOLD).
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### Best-Case Setup
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- Entry: [price/condition]
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- Stop: [price] ([%] risk)
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- Target: [price] ([%] reward)
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- Risk/Reward: [ratio]
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### Why This Can Work Soon
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- [3 bullets max: catalyst + technical + sentiment/news/fundamentals, all from provided data]
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### Counters (Brief)
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- Respond to the Safe and Neutral critiques with 1-2 data-backed points each.
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---
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**TRADER'S PLAN:**
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{trader_decision}
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**YOUR TASK:** Argue why this plan should be executed with conviction and clear triggers.
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**MARKET DATA:**
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- Technical: {market_research_report}
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- Sentiment: {sentiment_report}
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- News: {news_report}
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- Fundamentals: {fundamentals_report}
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**DEBATE HISTORY:**
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{history}
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**CONSERVATIVE ARGUMENT:**
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{current_safe_response}
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**NEUTRAL ARGUMENT:**
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{current_neutral_response}
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**If no other arguments yet:** Present your strongest case for why this trade can work soon, using only the provided data."""
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response = llm.invoke(prompt)
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response_text = parse_llm_response(response.content)
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argument = f"Risky Analyst: {response_text}"
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return {"risk_debate_state": update_risk_debate_state(risk_debate_state, argument, "Risky")}
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return risky_node
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