95 lines
4.0 KiB
Python
95 lines
4.0 KiB
Python
import functools
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import time
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import json
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def create_trader(llm, memory):
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def trader_node(state, name):
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company_name = state["company_of_interest"]
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investment_plan = state["investment_plan"]
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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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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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if past_memories:
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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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else:
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past_memory_str = "No past memories found."
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market_regime = state.get("market_regime", "UNKNOWN")
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volatility_score = state.get("volatility_score", "UNKNOWN")
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context = {
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"role": "user",
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"content": f"Based on a comprehensive analysis by a team of analysts, here is an investment plan tailored for {company_name}. This plan incorporates insights from current technical market trends, macroeconomic indicators, and social media sentiment. Use this plan as a foundation for evaluating your next trading decision.\n\nProposed Investment Plan: {investment_plan}\nMARKET REGIME SIGNAL: {market_regime}\nVOLATILE METRICS: {volatility_score}\n\nLeverage these insights to make an informed and strategic decision.",
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}
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messages = [
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{
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"role": "system",
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"content": f"""You are the Portfolio Manager. You have final authority.
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Your goal is Alpha generation with SURVIVAL priority.
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CURRENT MARKET REGIME: {market_regime} (Read this carefully!)
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CRITICAL MENTAL MODELS FOR HYPERSCALE TECH ANALYSIS:
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1. CAPEX IS DEFENSE, NOT WASTE
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- For platform monopolies (Google, Amazon, MSFT), massive CapEx ($50B+) during paradigm shifts (AI) is a BULLISH signal of moat-widening.
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- DO NOT flag rising CapEx as "deteriorating free cash flow" unless ROIC is structurally collapsing < 15%.
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- FRAMING: "Strategic infrastructure investment to defend the terminal value of Search/Cloud."
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2. INVENTORY LOGIC DOES NOT APPLY
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- Ignore "inventory build" or "working capital" warnings. These are IP/Services companies.
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- Volatility in Operating Cash Flow (OCF) due to tax/SBC timing is normal, not a "quality of earnings" red flag.
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3. VALUATION PEERS
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- NEVER benchmark against the S&P 500 average P/E.
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- Benchmark against: Durability of the Monopoly, Net Cash Position, and Pricing Power.
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- A 30x P/E is "Cheap" for a monopoly growing 15% with 30% margins.
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4. REGULATORY OVERHANG
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- Treat antitrust risk as a "Chronic Condition" (manage position size) NOT a "Terminal Disease" (panic sell).
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- Historical Context: Microsoft (90s), Google (2010s) compounded through regulation.
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- DO NOT recommend a hard exit solely on regulatory news unless a breakup order is *signed* today.
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DECISION LOGIC:
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1. IF Regime == 'VOLATILE' OR 'TRENDING_DOWN':
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- You are in "FALLING KNIFE" mode.
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- Ignore Bullish "Growth" arguments unless they are overwhelming.
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- High probability action: HOLD or SELL.
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- Only BUY if: RSI < 30 AND Regime is reversing.
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2. IF Regime == 'TRENDING_UP':
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- You are in "MOMENTUM" mode.
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- Prioritize Bullish signals.
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- Buy dips.
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3. IF Regime == 'SIDEWAYS':
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- Buy Support, Sell Resistance.
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FINAL OUTPUT:
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End with 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**'. Do not forget to utilize lessons from past decisions to learn from your mistakes. Here is some reflections from similar situatiosn you traded in and the lessons learned: {past_memory_str}""",
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},
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context,
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]
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result = llm.invoke(messages)
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return {
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"messages": [result],
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"trader_investment_plan": result.content,
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"sender": name,
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}
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return functools.partial(trader_node, name="Trader")
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