Update app.py

app.py

@@ -2,12 +2,6 @@ import pandas as pd
 import numpy as np
 import gradio as gr
 import matplotlib.pyplot as plt
-import requests
-import os
-from transformers import pipeline
-
-# Initialize Summarizer
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
 # Simple DCF Calculator Setup
 def discounted_cash_flow(fcf, growth_rate, discount_rate, terminal_growth_rate, forecast_years=5):
@@ -30,64 +24,17 @@ def discounted_cash_flow(fcf, growth_rate, discount_rate, terminal_growth_rate,
 
     return fcf_forecast, present_values, terminal_value, terminal_value_pv, total_value
 
-def get_company_fcf(symbol):
-    api_key = os.getenv("POLYGON_API_KEY")
-    url = f"https://api.polygon.io/vX/reference/financials?ticker={symbol}&apiKey={api_key}"
-    try:
-        response = requests.get(url)
-        response.raise_for_status()
-        data = response.json()
-        fcf = data['results'][0]['financials']['cash_flow_statement']['free_cash_flow']['value']
-        return float(fcf)
-    except Exception as e:
-        print(f"DEBUG: Error fetching FCF for {symbol}: {e}")
-        return None
-
-def get_current_stock_price(symbol):
-    api_key = os.getenv("POLYGON_API_KEY")
-    url = f"https://api.polygon.io/v2/aggs/ticker/{symbol}/prev?adjusted=true&apiKey={api_key}"
-    try:
-        response = requests.get(url)
-        response.raise_for_status()
-        data = response.json()
-        price = data['results'][0]['c']  # 'c' = close price
-        return float(price)
-    except Exception as e:
-        print(f"DEBUG: Error fetching current price for {symbol}: {e}")
-        return None
-
-def generate_summary(symbol, intrinsic_value, market_price):
-    verdict = "undervalued ✅" if intrinsic_value > market_price else "overvalued ⚠️"
-    text = (
-        f"Based on a DCF analysis, the intrinsic value of {symbol} is estimated to be "
-        f"${intrinsic_value:,.2f} compared to its current market price of ${market_price:,.2f}. "
-        f"The stock appears {verdict}."
-    )
-    summary = summarizer(text, max_length=100, min_length=30, do_sample=False)[0]['summary_text']
-    return summary
-
-def dcf_interface(symbol, growth_rate, discount_rate, terminal_growth_rate, forecast_years):
-    fcf = get_company_fcf(symbol)
-    if fcf is None:
-        empty_df = pd.DataFrame({"Error": ["Invalid symbol or no data available"]})
-
-        fig, ax = plt.subplots()
-        ax.text(0.5, 0.5, 'Error: Invalid Symbol', fontsize=12, ha='center')
-        ax.axis('off')
-
-        error_message = "⚠️ Error fetching financial data. Please check the symbol or try another company."
-        return empty_df, fig, error_message
-
+def dcf_interface(fcf, growth_rate, discount_rate, terminal_growth_rate, forecast_years):
     fcf_forecast, present_values, terminal_value, terminal_value_pv, total_intrinsic_value = discounted_cash_flow(
         fcf, growth_rate, discount_rate, terminal_growth_rate, forecast_years
     )
-
     df = pd.DataFrame({
         'Year': list(range(1, forecast_years + 1)),
         'Forecasted FCF ($)': fcf_forecast,
         'Present Value of FCF ($)': present_values
     })
 
+    # Plot FCF
     fig, ax = plt.subplots()
     ax.plot(df['Year'], df['Forecasted FCF ($)'], marker='o')
     ax.set_title('Forecasted Free Cash Flow Over Time')
@@ -95,17 +42,17 @@ def dcf_interface(symbol, growth_rate, discount_rate, terminal_growth_rate, fore
     ax.set_ylabel('Free Cash Flow ($)')
     ax.grid(True)
 
-    market_price = get_current_stock_price(symbol)
-    if market_price is None:
-        market_price = 0  # fallback
-
-    summary = generate_summary(symbol, total_intrinsic_value, market_price)
+    summary = f"""
+🏦 Total Intrinsic Value Estimate: ${total_intrinsic_value:,.2f}
+Terminal Value (undiscounted): ${terminal_value:,.2f}
+Present Value of Terminal Value: ${terminal_value_pv:,.2f}
+"""
     return df, fig, summary
 
 iface = gr.Interface(
     fn=dcf_interface,
     inputs=[
-        gr.Textbox(label="Stock Symbol (e.g., AAPL)"),
+        gr.Number(label="Initial Free Cash Flow ($)"),
         gr.Number(label="Annual Growth Rate (e.g., 0.06 for 6%)"),
         gr.Number(label="Discount Rate (e.g., 0.08 for 8%)"),
         gr.Number(label="Terminal Growth Rate (e.g., 0.025 for 2.5%)"),
@@ -114,13 +61,13 @@ iface = gr.Interface(
     outputs=[
         gr.Dataframe(label="DCF Forecast Table"),
         gr.Plot(label="Free Cash Flow Forecast Chart"),
-        gr.Textbox(label="AI Summary")
+        gr.Textbox(label="Summary")
     ],
     examples=[
-        ["AAPL", 0.06, 0.08, 0.025, 5]
+        [100_560_000_000, 0.06, 0.08, 0.025, 5]  # Example: Apple
     ],
-    title="AI-Powered DCF Valuation Calculator",
-    description="Enter a stock symbol and your assumptions. The app pulls live data from Polygon.io, runs a DCF, compares to the market price, and generates a research summary."
+    title="DCF Valuation Calculator",
+    description="Estimate a company's intrinsic value using Discounted Cash Flow (DCF) analysis. Adjust inputs or run a preset example."
 )
 
 if __name__ == "__main__":