from datetime import datetime, timedelta

from langchain_core.messages import HumanMessage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

from tradingagents.agents.utils.agent_utils import (
    build_instrument_context,
    get_global_news,
    get_news,
    prefetch_tool_data,
    supports_tool_calling,
)
from tradingagents.dataflows.config import get_config


def create_news_analyst(llm):
    def news_analyst_node(state):
        current_date = state["trade_date"]
        instrument_context = build_instrument_context(state["company_of_interest"])

        tools = [
            get_news,
            get_global_news,
        ]

        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. Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Provide specific, actionable insights with supporting evidence to help traders make informed 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}. {instrument_context}",
                ),
                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(instrument_context=instrument_context)

        if supports_tool_calling():
            chain = prompt | llm.bind_tools(tools)
            result = chain.invoke(state["messages"])
        else:
            ticker = state["company_of_interest"]
            start_date = (datetime.strptime(current_date, "%Y-%m-%d") - timedelta(days=7)).strftime("%Y-%m-%d")
            tool_data = prefetch_tool_data(tools, [
                {"ticker": ticker, "start_date": start_date, "end_date": current_date},
                {"curr_date": current_date, "look_back_days": 7, "limit": 5},
            ])
            result = (prompt | llm).invoke([
                HumanMessage(content=f"Analyze {ticker}.\n\nHere is the pre-fetched news data:\n\n{tool_data}\n\nWrite your comprehensive report.")
            ])

        report = ""

        if not getattr(result, "tool_calls", None):
            report = result.content

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

    return news_analyst_node