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d721393 023cd07 833892f d721393 e55017c d721393 833892f d721393 985dc48 18acca1 985dc48 18acca1 985dc48 18acca1 985dc48 d721393 833892f d721393 833892f d721393 833892f d721393 833892f e55017c 18acca1 d721393 11b8701 184a732 11b8701 d721393 6447e24 d721393 50654b2 d721393 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 | import gradio as gr
import pandas as pd
import matplotlib.pyplot as plt
from openpyxl import Workbook
from io import BytesIO
import base64
import re
def parse_assumptions(assumptions_text):
# Default values
gr.Markdown("# Projections for Tea Production Machine Replacement")
params = {
'initial_investment': 1000000000, # Rp 1M
'annual_revenue': 500000000, # Rp 500jt/tahun
'revenue_growth': 0.05, # 5% per tahun
'operating_cost': 300000000, # Rp 300jt/tahun
'cost_growth': 0.03, # 3% per tahun
'depreciation_years': 7, # Umur ekonomis mesin
'tax_rate': 0.25, # Pajak 25%
'working_capital': 50000000 # Modal kerja Rp 50jt
}
# Parsing assumptions from text
patterns = {
'initial_investment': r'Initial Investment[\s:]*Rp\s*([\d,.]+)',
'annual_revenue': r'Annual Revenue[\s:]*Rp\s*([\d,.]+)',
'revenue_growth': r'Revenue Growth[\s:]*([\d.]+)\%',
'operating_cost': r'Operating Cost[\s:]*Rp\s*([\d,.]+)',
'cost_growth': r'Cost Growth[\s:]*([\d.]+)\%',
'depreciation_years': r'Depreciation Years[\s:]*(\d+)',
'tax_rate': r'Tax Rate[\s:]*([\d.]+)\%',
'working_capital': r'Working Capital[\s:]*Rp\s*([\d,.]+)'
}
for key, pattern in patterns.items():
match = re.search(pattern, assumptions_text, re.IGNORECASE)
if match:
value = match.group(1)
if key in ['initial_investment', 'annual_revenue', 'operating_cost', 'working_capital']:
value = float(value.replace(',', '').replace('.', ''))
elif key in ['revenue_growth', 'cost_growth', 'tax_rate']:
value = float(value) / 100
else:
value = float(value)
params[key] = value
return params
def generate_charts(pl_df, cf_df):
# Create Profit Loss chart
plt.figure(figsize=(10, 6))
plt.plot(pl_df['Year'], pl_df['Revenue'], label='Revenue', marker='o')
plt.plot(pl_df['Year'], pl_df['Net Income'], label='Net Income', marker='s')
plt.title('Profit and Loss Trend')
plt.xlabel('Year')
plt.ylabel('Amount (Rp)')
plt.grid(True)
plt.legend()
plt.tight_layout()
# Save PL chart to BytesIO
pl_chart_io = BytesIO()
plt.savefig(pl_chart_io, format='png')
plt.savefig('pl_chart_base64.png') # Save the image
plt.close()
pl_chart_io.seek(0)
pl_chart_base64 = base64.b64encode(pl_chart_io.read()).decode('utf-8')
# Create Cashflow chart
plt.figure(figsize=(10, 6))
plt.plot(cf_df['Year'], cf_df['Net Cashflow'], label='Net Cashflow', marker='o', color='green')
plt.title('Cashflow Trend')
plt.xlabel('Year')
plt.ylabel('Amount (Rp)')
plt.grid(True)
plt.legend()
plt.tight_layout()
# Save CF chart to BytesIO
cf_chart_io = BytesIO()
plt.savefig(cf_chart_io, format='png')
plt.savefig('cf_chart_base64.png') # Save the image
plt.close()
cf_chart_io.seek(0)
cf_chart_base64 = base64.b64encode(cf_chart_io.read()).decode('utf-8')
return pl_chart_base64, cf_chart_base64
def generate_financials(assumptions_text):
params = parse_assumptions(assumptions_text)
print("halo mulai", params)
years = range(1, 8)
# Initialize data structures
profit_loss = []
cashflow = []
# Calculate financials
initial_investment = params['initial_investment']
working_capital = params['working_capital']
depreciation = initial_investment / params['depreciation_years']
print("depreciation:", depreciation)
revenue = params['annual_revenue']
operating_cost = params['operating_cost']
for year in years:
# Profit Loss
revenue *= (1 + params['revenue_growth'])
operating_cost *= (1 + params['cost_growth'])
ebitda = revenue - operating_cost
ebit = ebitda - depreciation
tax = max(ebit * params['tax_rate'], 0)
net_income = ebit - tax
profit_loss.append({
'Year': year,
'Revenue': revenue,
'Operating Cost': operating_cost,
'EBITDA': ebitda,
'Depreciation': depreciation,
'EBIT': ebit,
'Tax': tax,
'Net Income': net_income
})
# Cashflow
cash_in = revenue
cash_out = operating_cost + tax
if year == 1:
cash_out += initial_investment + working_capital
if year == 7:
cash_in += working_capital # Recovery of working capital
net_cashflow = cash_in - cash_out
cashflow.append({
'Year': year,
'Cash In': cash_in,
'Cash Out': cash_out,
'Net Cashflow': net_cashflow
})
# Create DataFrames
print("proses:", profit_loss, cashflow)
pl_df = pd.DataFrame(profit_loss)
cf_df = pd.DataFrame(cashflow)
# Create an Excel writer object
with pd.ExcelWriter('financial_projections.xlsx') as writer:
# Write the first DataFrame to the first sheet
pl_df.to_excel(writer, sheet_name='Sheet1', index=False)
# Write the second DataFrame to the second sheet
cf_df.to_excel(writer, sheet_name='Sheet2', index=False)
print("Excel file 'output.xlsx' created with two sheets.")
# Generate charts
pl_chart_base64, cf_chart_base64 = generate_charts(pl_df, cf_df)
#return 'financial_projections.xlsx', f"data:image/png;base64,{pl_chart_base64}", f"data:image/png;base64,{cf_chart_base64}"
return 'financial_projections.xlsx','pl_chart_base64.png','cf_chart_base64.png'
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Financial Projections for Tea Production Machine Replacement")
assumptions = gr.Textbox(
label="Input Assumptions",
placeholder="""Example format:
Initial Investment: Rp 1,000,000,000
Annual Revenue: Rp 500,000,000
Revenue Growth: 5%
Operating Cost: Rp 300,000,000
Cost Growth: 3%
Depreciation Years: 7
Tax Rate: 25%
Working Capital: Rp 50,000,000""",
lines=10,
value= """Initial Investment: Rp 1,000,000,000
Annual Revenue: Rp 500,000,000
Revenue Growth: 5%
Operating Cost: Rp 300,000,000
Cost Growth: 3%
Depreciation Years: 7
Tax Rate: 25%
Working Capital: Rp 50,000,000"""
)
generate_button = gr.Button("Generate Financials")
output_file = gr.File(label="Download Excel File")
pl_chart = gr.Image(label="Profit and Loss Chart")
cf_chart = gr.Image(label="Cashflow Chart")
generate_button.click(
fn=generate_financials,
inputs=assumptions,
outputs=[output_file, pl_chart, cf_chart]
)
demo.launch() |