from langchain_core.messages import AIMessage
import time
import json


def create_safe_debator(llm):
    def safe_node(state) -> dict:
        risk_debate_state = state["risk_debate_state"]
        history = risk_debate_state.get("history", "")
        safe_history = risk_debate_state.get("safe_history", "")

        current_risky_response = risk_debate_state.get("current_risky_response", "")
        current_neutral_response = risk_debate_state.get("current_neutral_response", "")

        market_research_report = state["market_report"]
        sentiment_report = state["sentiment_report"]
        news_report = state["news_report"]
        fundamentals_report = state["fundamentals_report"]

        trader_decision = state["trader_investment_plan"]

        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:

{trader_decision}

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:

Market Research Report: {market_research_report}
Social Media Sentiment Report: {sentiment_report}
Latest World Affairs Report: {news_report}
Company Fundamentals Report: {fundamentals_report}
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.

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."""

        response = llm.invoke(prompt)

        argument = f"Safe Analyst: {response.content}"

        new_risk_debate_state = {
            "history": history + "\n" + argument,
            "risky_history": risk_debate_state.get("risky_history", ""),
            "safe_history": safe_history + "\n" + argument,
            "neutral_history": risk_debate_state.get("neutral_history", ""),
            "latest_speaker": "Safe",
            "current_risky_response": risk_debate_state.get(
                "current_risky_response", ""
            ),
            "current_safe_response": argument,
            "current_neutral_response": risk_debate_state.get(
                "current_neutral_response", ""
            ),
            "count": risk_debate_state["count"] + 1,
        }

        return {"risk_debate_state": new_risk_debate_state}

    return safe_node