app.py

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt

# App title
st.set_page_config(page_title="Dynamic Pricing AI", layout="centered")
st.title("💸 AI-Based Dynamic Pricing System")
st.write("""
This web app calculates *dynamic product prices* based on demand, supply, competition, and seasonal factors — just like real businesses do.
""")

# Sidebar Inputs
st.sidebar.header("Input Parameters")
base_price = st.sidebar.number_input("Base Product Price (₹)", min_value=50.0, value=100.0)
demand = st.sidebar.slider("Demand Level", 0.0, 1.0, 0.5)
supply = st.sidebar.slider("Supply Level", 0.0, 1.0, 0.5)
competition_price = st.sidebar.number_input("Competitor Average Price (₹)", min_value=50.0, value=100.0)
season_factor = st.sidebar.slider("Season Factor (Festive = 1.2, Off-season = 0.8)", 0.5, 1.5, 1.0)

# Dynamic Pricing Formula
dynamic_price = base_price * (1 + (demand - supply) * 0.4) * season_factor
dynamic_price = (dynamic_price + competition_price) / 2

# Show recommended price
st.subheader(f"💡 Recommended Dynamic Price: ₹{round(dynamic_price, 2)}")

# Visualization: Price vs Demand Curve
demand_values = np.linspace(0, 1, 10)
prices = base_price * (1 + (demand_values - supply) * 0.4) * season_factor
prices = (prices + competition_price) / 2

plt.figure(figsize=(6,4))
plt.plot(demand_values, prices, marker='o', color='blue', label='Price vs Demand')
plt.xlabel('Demand Level')
plt.ylabel('Price (₹)')
plt.title('Dynamic Pricing Curve')
plt.legend()
plt.grid(True)
st.pyplot(plt)

# Explanation
st.write("""
### 📈 How it Works
- *Higher demand* → price increases  
- *Higher supply* → price decreases  
- *Season factor* adjusts prices for festive/off-season  
- *Competitor price* ensures market competitiveness  

### 🎓 Business Concepts
- Demand-Supply Economics  
- Price Elasticity  
- Strategic Pricing  
- AI & Data-Driven Decision Making
""")

st.info("💬 Try adjusting sliders to see how the recommended price changes in real-time!")