from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
import time
import json
from tradingagents.agents.utils.agent_utils import (
    get_asset_news,
    get_global_news_unified as get_global_news,
)
from tradingagents.dataflows.config import get_config


def create_news_analyst(llm):
    def news_analyst_node(state):
        current_date = state["trade_date"]
        ticker = state["company_of_interest"]
        asset_class = state.get("asset_class", "equity")

        # Use unified tools for all asset classes
        tools = [get_asset_news, get_global_news]

        # Asset-specific messaging
        if asset_class == "commodity":
            system_message = (
                f"You are a news researcher tasked with analyzing recent news and trends for the commodity {ticker}. "
                "Please write a comprehensive report of relevant news over the past week that impacts this commodity's price. "
                f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for commodity-specific news, "
                "and get_global_news(curr_date, look_back_days) for broader macroeconomic context (do NOT specify limit). "
                f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. If get_asset_news returns limited results, make sure to use get_global_news to provide additional market context. "
                "Focus on supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends. "
                "Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
                + """ Make sure to append a Markdown table at the end of the report to organize key points."""
            )
        elif asset_class == "crypto":
            system_message = (
                f"You are a news researcher tasked with analyzing recent news and trends for the cryptocurrency {ticker}. "
                "Please write a comprehensive report of relevant news over the past week that impacts this cryptocurrency's price. "
                f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for crypto-specific blockchain news, "
                "and get_global_news(curr_date, look_back_days) for broader macroeconomic context (do NOT specify limit). "
                f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. If get_asset_news returns limited results, make sure to use get_global_news to provide additional market context. "
                "Focus on regulatory developments, adoption trends, technological updates, market sentiment, and macroeconomic factors affecting crypto. "
                "Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
                + """ Make sure to append a Markdown table at the end of the report to organize key points."""
            )
        else:  # equity
            system_message = (
                "You are a news researcher tasked with analyzing recent news and trends over the past week. "
                "Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. "
                f"Use the available tools: get_asset_news(symbol, start_date, end_date, asset_class=\"{asset_class}\") for company-specific or targeted news searches, "
                "and get_global_news(curr_date, look_back_days) for broader macroeconomic news (omit limit parameter). "
                f"IMPORTANT: Always pass asset_class=\"{asset_class}\" when calling get_asset_news. "
                "Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
                + """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
            )

        prompt = ChatPromptTemplate.from_messages(
            [
                (
                    "system",
                    "You are a helpful AI assistant, collaborating with other assistants."
                    " Use the provided tools to progress towards answering the question."
                    " If you are unable to fully answer, that's OK; another assistant with different tools"
                    " will help where you left off. Execute what you can to make progress."
                    " If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** or deliverable,"
                    " prefix your response with FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** so the team knows to stop."
                    " You have access to the following tools: {tool_names}.\n{system_message}"
                    "For your reference, the current date is {current_date}. We are looking at the company {ticker}",
                ),
                MessagesPlaceholder(variable_name="messages"),
            ]
        )

        prompt = prompt.partial(system_message=system_message)
        prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
        prompt = prompt.partial(current_date=current_date)
        prompt = prompt.partial(ticker=ticker)

        chain = prompt | llm.bind_tools(tools)
        result = chain.invoke(state["messages"])

        report = ""

        if len(result.tool_calls) == 0:
            report = result.content

        return {
            "messages": [result],
            "news_report": report,
        }

    return news_analyst_node