59 lines
3.4 KiB
Python
Executable File
59 lines
3.4 KiB
Python
Executable File
from langchain_core.messages import AIMessage
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import time
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import json
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def create_safe_debator(llm):
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def safe_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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safe_history = risk_debate_state.get("safe_history", "")
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current_risky_response = risk_debate_state.get("current_risky_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"""As the Safe/Conservative Risk Analyst for SHORT-TERM trading (1-2 week horizon), your primary objective is to protect assets from short-term volatility and sudden market moves. You prioritize stability and risk mitigation, carefully assessing potential losses from near-term events, earnings surprises, and market volatility over the next 1-2 weeks. When evaluating the trader's position decision (LONG/SHORT/HOLD), critically examine high-risk elements for the short term, pointing out where the decision may expose the firm to undue near-term risk. Here is the trader's position decision:
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{trader_decision}
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Your task is to actively counter the arguments of the Risky and Neutral Analysts, highlighting where their views may overlook potential short-term threats or near-term downside risks. Respond directly to their points, drawing from the following data sources to build a convincing case for a cautious short-term approach:
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Market Research Report: {market_research_report}
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Social Media Sentiment Report: {sentiment_report}
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Latest World Affairs Report: {news_report}
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Company Fundamentals Report: {fundamentals_report}
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Here is the current conversation history: {history} Here is the last response from the risky analyst: {current_risky_response} Here is the last response from the neutral analyst: {current_neutral_response}. If there are no responses from the other viewpoints, do not halluncinate and just present your point.
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Engage by questioning their optimism and emphasizing the potential short-term downsides they may have overlooked. Address each of their counterpoints to showcase why a conservative stance is the safest path for the next 1-2 weeks. Focus on debating and critiquing their arguments to demonstrate the strength of a risk-aware strategy for short-term trading. Output conversationally as if you are speaking without any special formatting."""
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response = llm.invoke(prompt)
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argument = f"Safe Analyst: {response.content}"
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new_risk_debate_state = {
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"history": history + "\n" + argument,
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"risky_history": risk_debate_state.get("risky_history", ""),
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"safe_history": safe_history + "\n" + argument,
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"neutral_history": risk_debate_state.get("neutral_history", ""),
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"latest_speaker": "Safe",
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"current_risky_response": risk_debate_state.get(
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"current_risky_response", ""
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),
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"current_safe_response": argument,
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"current_neutral_response": risk_debate_state.get(
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"current_neutral_response", ""
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),
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"count": risk_debate_state["count"] + 1,
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}
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return {"risk_debate_state": new_risk_debate_state}
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return safe_node
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