import functools

from tradingagents.agents.utils.agent_utils import build_instrument_context


def create_trader(llm):
    def trader_node(state, name):
        company_name = state["company_of_interest"]
        instrument_context = build_instrument_context(company_name)
        investment_plan = state["investment_plan"]

        context = {
            "role": "user",
            "content": f"Based on a comprehensive analysis by a team of analysts, here is an investment plan tailored for {company_name}. {instrument_context} 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}\n\nLeverage these insights to make an informed and strategic decision.",
        }

        messages = [
            {
                "role": "system",
                "content": "You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide a specific recommendation to buy, sell, or hold. End with a firm decision and always conclude your response with 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**' to confirm your recommendation.",
            },
            context,
        ]

        result = llm.invoke(messages)

        return {
            "messages": [result],
            "trader_investment_plan": result.content,
            "sender": name,
        }

    return functools.partial(trader_node, name="Trader")