import matplotlib.pyplot as plt
import pandas as pd
import os

def generate_report(df, spending_analysis, recommendations):
    # Create a directory for images if it doesn't exist
    images_dir = "images"
    if not os.path.exists(images_dir):
        os.makedirs(images_dir)

    report = f"""
    ## Invoice Reader & Budget Categorizer Report

    ### Categorized Transactions
    {df.groupby('category').apply(lambda x: x.to_markdown(index=False)).to_string()}

    ### Spending Insights
    {spending_analysis}

    ### Budget Recommendations
    {recommendations}

    ### Visualizations
    #### Category-wise Spending
    ![Category-wise Spending]({os.path.join(images_dir, 'category_spending.png')})

    #### Monthly Spending Trend
    ![Monthly Spending Trend]({os.path.join(images_dir, 'monthly_spending.png')})
    """
    
    if not df.empty:
        # Category-wise spending pie chart
        category_spending = df.groupby("category")["amount"].sum()
        plt.figure(figsize=(6, 6))
        plt.pie(category_spending, labels=category_spending.index, autopct="%1.1f%%")
        plt.title("Category-wise Spending")
        plt.savefig(os.path.join(images_dir, "category_spending.png"))
        plt.close()

        # Monthly spending trend with validation
        monthly_spending = df.groupby("month")["amount"].sum()
        if len(monthly_spending) > 1:  # Ensure multiple months
            plt.figure(figsize=(8, 4))
            monthly_spending.plot(kind="line", marker="o")
            plt.title("Monthly Spending Trend")
            plt.xlabel("Month")
            plt.ylabel("Amount")
            plt.savefig(os.path.join(images_dir, "monthly_spending.png"))
            plt.close()
        else:
            report += "\n#### Monthly Spending Trend\n(No trend available: insufficient data across multiple months)"

    return report