76 lines
2.9 KiB
Python
76 lines
2.9 KiB
Python
from tradingagents.agents.utils.agent_utils import build_instrument_context, get_language_instruction
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def create_portfolio_manager(llm, memory):
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def portfolio_manager_node(state) -> dict:
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instrument_context = build_instrument_context(state["company_of_interest"])
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history = state["risk_debate_state"]["history"]
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risk_debate_state = state["risk_debate_state"]
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market_research_report = state["market_report"]
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news_report = state["news_report"]
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fundamentals_report = state["fundamentals_report"]
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sentiment_report = state["sentiment_report"]
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trader_plan = state["investment_plan"]
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curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
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past_memories = memory.get_memories(curr_situation, n_matches=2)
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past_memory_str = ""
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for i, rec in enumerate(past_memories, 1):
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past_memory_str += rec["recommendation"] + "\n\n"
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prompt = f"""As the Portfolio Manager, synthesize the risk analysts' debate and deliver the final trading decision.
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{instrument_context}
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---
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**Rating Scale** (use exactly one):
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- **Buy**: Strong conviction to enter or add to position
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- **Overweight**: Favorable outlook, gradually increase exposure
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- **Hold**: Maintain current position, no action needed
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- **Underweight**: Reduce exposure, take partial profits
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- **Sell**: Exit position or avoid entry
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**Context:**
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- Trader's proposed plan: **{trader_plan}**
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- Lessons from past decisions: **{past_memory_str}**
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**Required Output Structure:**
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1. **Rating**: State one of Buy / Overweight / Hold / Underweight / Sell.
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2. **Executive Summary**: A concise action plan covering entry strategy, position sizing, key risk levels, and time horizon.
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3. **Investment Thesis**: Detailed reasoning anchored in the analysts' debate and past reflections.
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---
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**Risk Analysts Debate History:**
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{history}
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---
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Be decisive and ground every conclusion in specific evidence from the analysts.{get_language_instruction()}"""
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response = llm.invoke(prompt)
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new_risk_debate_state = {
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"judge_decision": response.content,
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"history": risk_debate_state["history"],
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"aggressive_history": risk_debate_state["aggressive_history"],
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"conservative_history": risk_debate_state["conservative_history"],
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"neutral_history": risk_debate_state["neutral_history"],
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"latest_speaker": "Judge",
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"current_aggressive_response": risk_debate_state["current_aggressive_response"],
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"current_conservative_response": risk_debate_state["current_conservative_response"],
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"current_neutral_response": risk_debate_state["current_neutral_response"],
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"count": risk_debate_state["count"],
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}
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return {
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"risk_debate_state": new_risk_debate_state,
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"final_trade_decision": response.content,
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}
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return portfolio_manager_node
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