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Update app.py
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app.py
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import streamlit as st
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import numpy as np
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import matplotlib.pyplot as plt
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# App title
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st.set_page_config(page_title="Dynamic Pricing AI", layout="centered")
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st.title("💸 AI-Based Dynamic Pricing System")
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st.write("""
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This web app calculates *dynamic product prices* based on demand, supply, competition, and seasonal factors — just like real businesses do.
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""")
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# Sidebar Inputs
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st.sidebar.header("Input Parameters")
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base_price = st.sidebar.number_input("Base Product Price (₹)", min_value=50.0, value=100.0)
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demand = st.sidebar.slider("Demand Level", 0.0, 1.0, 0.5)
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supply = st.sidebar.slider("Supply Level", 0.0, 1.0, 0.5)
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competition_price = st.sidebar.number_input("Competitor Average Price (₹)", min_value=50.0, value=100.0)
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season_factor = st.sidebar.slider("Season Factor (Festive = 1.2, Off-season = 0.8)", 0.5, 1.5, 1.0)
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# Dynamic Pricing Formula
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dynamic_price = base_price * (1 + (demand - supply) * 0.4) * season_factor
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dynamic_price = (dynamic_price + competition_price) / 2
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# Show recommended price
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st.subheader(f"💡 Recommended Dynamic Price: ₹{round(dynamic_price, 2)}")
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# Visualization: Price vs Demand Curve
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demand_values = np.linspace(0, 1, 10)
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prices = base_price * (1 + (demand_values - supply) * 0.4) * season_factor
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prices = (prices + competition_price) / 2
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plt.figure(figsize=(6,4))
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plt.plot(demand_values, prices, marker='o', color='blue', label='Price vs Demand')
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plt.xlabel('Demand Level')
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plt.ylabel('Price (₹)')
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plt.title('Dynamic Pricing Curve')
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plt.legend()
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plt.grid(True)
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st.pyplot(plt)
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# Explanation
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st.write("""
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### 📈 How it Works
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- *Higher demand* → price increases
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- *Higher supply* → price decreases
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- *Season factor* adjusts prices for festive/off-season
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- *Competitor price* ensures market competitiveness
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### 🎓 Business Concepts
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- Demand-Supply Economics
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- Price Elasticity
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- Strategic Pricing
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- AI & Data-Driven Decision Making
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""")
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st.info("💬 Try adjusting sliders to see how the recommended price changes in real-time!")
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