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import gradio as gr
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from transformers import pipeline
import plotly.express as px
# Initialize the Hugging Face model for expense categorization (use zero-shot classification)
expense_classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
# Batch categorization function for efficiency
def categorize_transaction_batch(descriptions):
candidate_labels = ["Groceries", "Entertainment", "Rent", "Utilities", "Dining", "Transportation", "Shopping", "Others"]
return [expense_classifier(description, candidate_labels)["labels"][0] for description in descriptions]
# Function to process the uploaded CSV and generate visualizations
def process_expenses(file):
# Read CSV data
df = pd.read_csv(file.name)
# Check if required columns are present
if 'Date' not in df.columns or 'Description' not in df.columns or 'Amount' not in df.columns:
return "CSV file should contain 'Date', 'Description', and 'Amount' columns."
# Categorize the expenses (using batch processing to minimize model calls)
df['Category'] = categorize_transaction_batch(df['Description'].tolist())
# Create visualizations:
# 1. Pie chart for Category-wise spending
category_spending = df.groupby("Category")['Amount'].sum()
fig1 = px.pie(category_spending, names=category_spending.index, values=category_spending.values, title="Category-wise Spending")
# 2. Monthly spending trends (Line plot)
df['Date'] = pd.to_datetime(df['Date'])
df['Month'] = df['Date'].dt.to_period('M')
monthly_spending = df.groupby('Month')['Amount'].sum()
fig2 = px.line(monthly_spending, x=monthly_spending.index, y=monthly_spending.values, title="Monthly Spending Trends")
# 3. Budget vs Actual Spending (Bar chart)
category_list = df['Category'].unique()
budget_dict = {category: 500 for category in category_list} # Default budget is 500 for each category
budget_spending = {category: [budget_dict[category], category_spending.get(category, 0)] for category in category_list}
budget_df = pd.DataFrame(budget_spending, index=["Budget", "Actual"]).T
fig3 = px.bar(budget_df, x=budget_df.index, y=["Budget", "Actual"], title=
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