import chainlit as cl
from langchain_openai import ChatOpenAI

from utils_data import get_company_data, get_opportunities
from utils_prompt import get_chat_prompt


async def prep_start(session_state):

    get_company_data(session_state)
    chat_prompt = get_chat_prompt()
    chat_model = ChatOpenAI(model=session_state.llm_model)
    simple_chain = chat_prompt | chat_model
    cl.user_session.set("chain", simple_chain)

    welcome_message = f"**Welcome to {session_state.company.name} SalesBuddy**\n*Home of {session_state.company.product}*"
    await cl.Message(content=welcome_message).send()
    await cl.Message(content=session_state.company.product_summary).send()

    scenarios = get_opportunities()
    cl.user_session.set("scenarios", scenarios)

async def prep_research(session_state):

    research_title = "**Customer Research**"
    await cl.Message(content=research_title).send()
    research_message = "Enter customer name to research"
    await cl.Message(content=research_message).send()


    
async def prep_sparring(session_state):
    scenarios = cl.user_session.get("scenarios", None)
    if scenarios is None:
        await cl.Message(content="No scenarios found.").send()
        return
    scenario_actions = []
    for idx, row in scenarios.iterrows():
        if row['Opportunity Description'] != "":
            scenario_action = cl.Action(
                name="Scenario",
                value=f"{idx}",  # Send the row index as value
                description=f"{row['Customer Name']}: {row['Opportunity Name']} ({row['Opportunity Stage']}) "
                            f"Value: {row['Opportunity Value']}. Meeting with {row['Customer Contact']} "
                            f"({row['Customer Contact Role']})"
            )
            scenario_actions.append(scenario_action)
    await cl.Message(content="Select a scenario (hover for details):", actions=scenario_actions).send()