import re
import os
import gspread
import gradio as gr
import datetime
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from LLM_openai import client, expense_classifier
from utils import create_plot, create_barplot
from dataframe_processing import dataframe_process
from vision_api_call import process_image

#connect to the service account
gc = gspread.service_account(filename="credentials.json")
#connect to your sheet (between "" = the name of your G Sheet, keep it short)
spreadsheet = gc.open("Snackers_spreadsheet").sheet1

def update_spend_from_image(img):
    ##This processes the image
    extracted_dictionay_from_image=process_image(img)
    total_from_receipt=extracted_dictionay_from_image['total']
    concept_from_receipt=extracted_dictionay_from_image['purchase_summary']
    shop_type=extracted_dictionay_from_image['store_type']
    shop_name=extracted_dictionay_from_image['store']
    receipt_items=str(extracted_dictionay_from_image['items'])

    concept_and_shop=concept_from_receipt+" from "+shop_type+f" ({shop_name})"
    
    ##The function update_spend in the line below only takes a string and float
    category, day_month, todays_amount, current_week_amount , fig, fig2, fig3=update_spend(concept_and_shop, total_from_receipt, receipt_items)

    return category, day_month, todays_amount, current_week_amount , fig, fig2, fig3



def update_spend(concept, amount, items_from_receipt=None):
    category=expense_classifier(concept)
    today = datetime.date.today()
    
    # Append a new row
    spreadsheet.append_row([str(today), concept,float(amount),category, items_from_receipt ])
    
    day_month, todays_amount, current_week_amount , fig, fig2, fig3=dataframe_process(spreadsheet)
    return category, day_month, todays_amount, current_week_amount , fig, fig2, fig3

def show_plots():
    category='N/A'
    today = 'N/A'
    
    # Append a new row
    # spreadsheet.append_row([str(today), concept,float(amount),category, items_from_receipt ])
    
    day_month, todays_amount, current_week_amount , fig, fig2, fig3=dataframe_process(spreadsheet)
    return category, day_month, todays_amount, current_week_amount , fig, fig2, fig3




with gr.Blocks() as demo:
    gr.Markdown("Expense tracker")
    
    with gr.Tab("Manual input"):
        with gr.Row():
            concept = gr.Textbox(label="concept")
        with gr.Row():
            amount= gr.Textbox(label="amount")
        btn_manual = gr.Button("Submit expense")

    with gr.Tab("Upload receipt"):
        with gr.Row():
            input_image = gr.Image( type="pil")
        btn_image = gr.Button("Submit expense")
        
        
        
    
    
    with gr.Row():
        btn_show = gr.Button("Show plots")

    with gr.Row():
        expense_class= gr.Textbox(label='expense class')
        ui_date=gr.Textbox(label='date')
        expenses_today= gr.Textbox(label='expenses today')
        expenses_this_week= gr.Textbox(label='expenses this week')
    with gr.Row():
        daily_plot=gr.Plot(label=None)
        week_plot=gr.Plot()
        category_plot=gr.Plot()


    btn_manual.click(fn=update_spend, inputs=[concept, amount], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                  daily_plot,week_plot,category_plot])
    btn_image.click(fn=update_spend_from_image, inputs=[input_image], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                  daily_plot,week_plot,category_plot])
    btn_show.click(fn=show_plots, inputs=[], outputs=[expense_class,ui_date, expenses_today,expenses_this_week,
                                                                  daily_plot,week_plot,category_plot])


demo.launch()