56 lines
3.0 KiB
Python
Executable File
56 lines
3.0 KiB
Python
Executable File
import time
|
|
import json
|
|
|
|
|
|
def create_research_manager(llm, memory):
|
|
def research_manager_node(state) -> dict:
|
|
history = state["investment_debate_state"].get("history", "")
|
|
market_research_report = state["market_report"]
|
|
sentiment_report = state["sentiment_report"]
|
|
news_report = state["news_report"]
|
|
fundamentals_report = state["fundamentals_report"]
|
|
|
|
investment_debate_state = state["investment_debate_state"]
|
|
|
|
curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
|
|
past_memories = memory.get_memories(curr_situation, n_matches=2)
|
|
|
|
past_memory_str = ""
|
|
for i, rec in enumerate(past_memories, 1):
|
|
past_memory_str += rec["recommendation"] + "\n\n"
|
|
|
|
prompt = f"""As the portfolio manager and debate facilitator for SHORT-TERM trading (1-2 week horizon), your role is to critically evaluate this round of debate and make a definitive position decision: align with the bull analyst (LONG), the bear analyst (SHORT), or choose HOLD only if it is strongly justified based on the arguments presented.
|
|
|
|
Focus on SHORT-TERM factors: near-term catalysts, momentum, upcoming events, and what is likely to happen in the next 1-2 weeks. Summarize the key points from both sides concisely, focusing on the most compelling evidence for short-term price movement. Your position recommendation—LONG, SHORT, or HOLD—must be clear and actionable for a 1-2 week holding period. Avoid defaulting to HOLD simply because both sides have valid points; commit to a stance grounded in the debate's strongest short-term arguments.
|
|
|
|
Additionally, develop a detailed SHORT-TERM investment plan for the trader. This should include:
|
|
|
|
Your Position Recommendation: A decisive stance (LONG/SHORT/HOLD) for the next 1-2 weeks supported by the most convincing arguments.
|
|
Rationale: An explanation of why these arguments lead to your conclusion for the short-term.
|
|
Strategic Actions: Concrete steps for implementing the recommendation with a 1-2 week timeframe in mind.
|
|
Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting.
|
|
|
|
Here are your past reflections on mistakes:
|
|
\"{past_memory_str}\"
|
|
|
|
Here is the debate:
|
|
Debate History:
|
|
{history}"""
|
|
response = llm.invoke(prompt)
|
|
|
|
new_investment_debate_state = {
|
|
"judge_decision": response.content,
|
|
"history": investment_debate_state.get("history", ""),
|
|
"bear_history": investment_debate_state.get("bear_history", ""),
|
|
"bull_history": investment_debate_state.get("bull_history", ""),
|
|
"current_response": response.content,
|
|
"count": investment_debate_state["count"],
|
|
}
|
|
|
|
return {
|
|
"investment_debate_state": new_investment_debate_state,
|
|
"investment_plan": response.content,
|
|
}
|
|
|
|
return research_manager_node
|