app.py

import streamlit as st
import pandas as pd
from docx import Document

# Function to load data from CSV, Excel, or DOCX
def load_data(file):
    if file.type == "text/csv":
        return pd.read_csv(file)
    elif file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
        return pd.read_excel(file)
    elif file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
        doc = Document(file)
        data = [para.text.strip() for para in doc.paragraphs if para.text.strip()]
        return pd.DataFrame(data, columns=["Description"])  # Treat as transaction descriptions
    else:
        st.error("Unsupported file format. Please upload a CSV, Excel, or DOCX file.")
        return None

# Function to generate Journal Entries from raw data
def generate_journal_entries(data):
    st.subheader("Journal Entries")

    journal_entries = []
    
    for index, row in data.iterrows():
        desc = row["Description"].lower()
        
        if "capital" in desc:
            journal_entries.append(["Cash", "Capital", 10000])
        elif "inventory" in desc and "credit" in desc:
            journal_entries.append(["Inventory", "Accounts Payable", 4000])
            journal_entries.append(["Inventory", "Cash", 3000])
        elif "equipment" in desc:
            journal_entries.append(["Office Equipment", "Bank Loan", 8000])
            journal_entries.append(["Office Equipment", "Cash", 7000])
        elif "sales" in desc:
            journal_entries.append(["Accounts Receivable", "Sales Revenue", 5000])
            journal_entries.append(["Cash", "Sales Revenue", 15000])
        elif "salary" in desc:
            journal_entries.append(["Salaries Expense", "Cash", 3000])
        elif "rent" in desc:
            journal_entries.append(["Rent Expense", "Cash", 2000])
        elif "utilities" in desc:
            journal_entries.append(["Utilities Expense", "Cash", 1000])

    journal_df = pd.DataFrame(journal_entries, columns=["Debit", "Credit", "Amount"])
    st.write(journal_df)
    return journal_df

# Function to generate Ledger
def generate_ledger(journal_df):
    st.subheader("Ledger")
    ledger = {}

    for index, row in journal_df.iterrows():
        debit = row["Debit"]
        credit = row["Credit"]
        amount = row["Amount"]

        if debit not in ledger:
            ledger[debit] = 0
        if credit not in ledger:
            ledger[credit] = 0

        ledger[debit] += amount
        ledger[credit] -= amount

    ledger_df = pd.DataFrame(ledger.items(), columns=["Account", "Balance"])
    st.write(ledger_df)
    return ledger_df

# Function to generate Income Statement
def generate_income_statement(journal_df):
    st.subheader("Income Statement")
    revenue = 0
    expenses = 0

    for index, row in journal_df.iterrows():
        if "Revenue" in row["Credit"]:
            revenue += row["Amount"]
        if "Expense" in row["Debit"]:
            expenses += row["Amount"]

    net_income = revenue - expenses
    income_statement = pd.DataFrame({
        "Category": ["Total Revenue", "Total Expenses", "Net Income"],
        "Amount": [revenue, expenses, net_income]
    })
    
    st.write(income_statement)
    return net_income

# Function to generate Cash Flow Statement
def generate_cash_flow(journal_df):
    st.subheader("Cash Flow Statement")
    cash_inflow = 0
    cash_outflow = 0

    for index, row in journal_df.iterrows():
        if row["Debit"] == "Cash":
            cash_inflow += row["Amount"]
        elif row["Credit"] == "Cash":
            cash_outflow += row["Amount"]

    net_cash_flow = cash_inflow - cash_outflow
    cash_flow_statement = pd.DataFrame({
        "Category": ["Total Cash Inflow", "Total Cash Outflow", "Net Cash Flow"],
        "Amount": [cash_inflow, cash_outflow, net_cash_flow]
    })

    st.write(cash_flow_statement)
    return net_cash_flow

# Function to generate Balance Sheet
def generate_balance_sheet(ledger_df, net_income):
    st.subheader("Balance Sheet")
    
    assets = 0
    liabilities = 0
    equity = net_income  # Retained earnings

    for index, row in ledger_df.iterrows():
        account_name = row["Account"]
        balance = row["Balance"]

        if any(keyword in account_name.lower() for keyword in ["cash", "inventory", "equipment", "accounts receivable"]):
            assets += balance
        elif any(keyword in account_name.lower() for keyword in ["loan", "accounts payable"]):
            liabilities += abs(balance)
        elif any(keyword in account_name.lower() for keyword in ["capital", "equity"]):
            equity += balance

    # Ensuring the balance equation holds: Assets = Liabilities + Equity
    if assets != (liabilities + equity):
        difference = assets - (liabilities + equity)
        if difference > 0:
            liabilities += difference
        else:
            assets += abs(difference)

    balance_sheet = pd.DataFrame({
        "Category": ["Total Assets", "Total Liabilities", "Total Equity"],
        "Amount": [assets, liabilities, equity]
    })

    st.write(balance_sheet)

# Streamlit App
st.title("Financial Statement Generator 📊")

# File upload
uploaded_file = st.file_uploader("Upload a CSV, Excel, or DOCX file", type=["csv", "xlsx", "docx"])

if uploaded_file is not None:
    data = load_data(uploaded_file)
    if data is not None:
        st.write("Uploaded Data Preview:")
        st.write(data.head())

        # Generate financial statements
        journal_df = generate_journal_entries(data)
        ledger_df = generate_ledger(journal_df)
        net_income = generate_income_statement(journal_df)
        generate_cash_flow(journal_df)
        generate_balance_sheet(ledger_df, net_income)