main.py

import time

import pandas as pd

from agents import inventory_agent, ordering_agent, quoting_agent
from constants import DATA_FOLDER, RESULTS_FOLDER
from db import DB_ENGINE, init_database
from entities import QuoteRequestSample
from orchestrator import MultiAgentOrchestrator
from tools_functions import generate_financial_report


def run_test_scenarios():

    print("Initializing Database...")
    init_database(DB_ENGINE)
    try:
        quote_requests_sample = pd.read_csv(f"{DATA_FOLDER}/quote_requests_sample.csv")
        quote_requests_sample["request_date"] = pd.to_datetime(
            quote_requests_sample["request_date"], format="%m/%d/%y", errors="coerce"
        )
        quote_requests_sample.dropna(subset=["request_date"], inplace=True)
        quote_requests_sample = quote_requests_sample.sort_values("request_date")
    except Exception as e:
        print(f"FATAL: Error loading test data: {e}")
        return

    quote_requests_sample = pd.read_csv(f"{DATA_FOLDER}/quote_requests_sample.csv")

    # Sort by date
    quote_requests_sample["request_date"] = pd.to_datetime(
        quote_requests_sample["request_date"]
    )
    quote_requests_sample = quote_requests_sample.sort_values("request_date")

    # Get initial state
    initial_date = quote_requests_sample["request_date"].min().strftime("%Y-%m-%d")
    report = generate_financial_report(initial_date)
    current_cash = report["cash_balance"]
    current_inventory = report["inventory_value"]

    orchestrator = MultiAgentOrchestrator(
        inventory_agent=inventory_agent,
        quoting_agent=quoting_agent,
        ordering_agent=ordering_agent,
    )

    results = []
    for idx, row in quote_requests_sample.iterrows():
        request_date = row["request_date"].strftime("%Y-%m-%d")

        print(f"\n=== Request {idx+1} ===")
        print(f"Context: {row['job']} organizing {row['event']}")
        print(f"Request Date: {request_date}")
        print(f"Cash Balance: ${current_cash:.2f}")
        print(f"Inventory Value: ${current_inventory:.2f}")

        # Process request
        response = orchestrator.process_request(QuoteRequestSample(**row))

        # Update state
        report = generate_financial_report(request_date)
        current_cash = report["cash_balance"]
        current_inventory = report["inventory_value"]

        print(f"Response: {response}")
        print(f"Updated Cash: ${current_cash:.2f}")
        print(f"Updated Inventory: ${current_inventory:.2f}")

        results.append(
            {
                "request_id": idx + 1,
                "request_date": request_date,
                "cash_balance": current_cash,
                "inventory_value": current_inventory,
                "response": str(response),
            }
        )

        time.sleep(1)

    # Final report
    final_date = quote_requests_sample["request_date"].max().strftime("%Y-%m-%d")
    final_report = generate_financial_report(final_date)
    print("\n===== FINAL FINANCIAL REPORT =====")
    print(f"Final Cash: ${final_report['cash_balance']:.2f}")
    print(f"Final Inventory: ${final_report['inventory_value']:.2f}")

    # Save results
    pd.DataFrame(results).to_csv(f"{RESULTS_FOLDER}/test_results.csv", index=False)
    return results


if __name__ == "__main__":
    results = run_test_scenarios()
    print("\nTest scenarios completed.")