Upload app.py

app.py

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+import os
+import subprocess
+
+# 🔹 Clear Hugging Face Pip Cache Before Installing
+subprocess.run("rm -rf /home/user/.cache/pip/*", shell=True)
+
+import streamlit as st
+import numpy as np
+
+import os
+os.system("pip install --no-cache-dir matplotlib")
+import matplotlib.pyplot as plt
+import pandas as pd
+
+
+import os
+os.system("pip install --no-cache-dir numpy==1.23.5 spacy==3.5.3 thinc==8.1.8 pydantic<2.0")
+import spacy
+
+
+def extract_equation_params(text):
+    """
+    Extracts demand and supply equation parameters from a structured natural language query.
+    """
+    doc = nlp(text.lower())
+    numbers = [float(token.text) for token in doc if token.like_num]
+
+    if len(numbers) < 14:
+        return None
+
+    demand_intercept_corn, demand_slope_corn, supply_intercept_corn, supply_slope_corn, \
+    supply_intercept_prod_pay, supply_slope_prod_pay, \
+    demand_intercept_cleaned, demand_slope_cleaned, supply_intercept_cleaned, supply_slope_cleaned, \
+    demand_intercept_no_loading, demand_slope_no_loading, supply_intercept_no_loading, supply_slope_no_loading = numbers[:14]
+
+    demand_slope_corn = -abs(demand_slope_corn)
+    demand_slope_cleaned = -abs(demand_slope_cleaned)
+    demand_slope_no_loading = -abs(demand_slope_no_loading)
+
+    return demand_intercept_corn, demand_slope_corn, supply_intercept_corn, supply_slope_corn, \
+           supply_intercept_prod_pay, supply_slope_prod_pay, \
+           demand_intercept_cleaned, demand_slope_cleaned, supply_intercept_cleaned, supply_slope_cleaned, \
+           demand_intercept_no_loading, demand_slope_no_loading, supply_intercept_no_loading, supply_slope_no_loading
+
+def calculate_equilibrium(demand_intercept, demand_slope, supply_intercept, supply_slope):
+    """
+    Computes Competitive Equilibrium: Quantity and Price.
+    Also calculates CS, PS, and SW for the competitive market.
+    """
+    quantity_eq = (demand_intercept - supply_intercept) / (supply_slope - demand_slope)
+    price_eq = demand_intercept + demand_slope * quantity_eq
+
+    cs_eq = (demand_intercept - price_eq) * quantity_eq / 2
+    ps_eq = (price_eq - supply_intercept) * quantity_eq / 2
+    sw_eq = cs_eq + ps_eq
+
+    return round(quantity_eq, 2), round(price_eq, 2), round(cs_eq, 2), round(ps_eq, 2), round(sw_eq, 2)
+
+def plot_market(demand_intercept, demand_slope, supply_intercept, supply_slope, quantity_eq, price_eq, market_name,
+                supply_intercept_alt=None, supply_slope_alt=None):
+    """
+    Plots the supply and demand curves for a given market.
+    """
+    q_range = np.linspace(0, quantity_eq * 1.5, 100)
+    demand_curve = demand_intercept + demand_slope * q_range
+    supply_curve_primary = supply_intercept + supply_slope * q_range
+    supply_curve_alt = supply_intercept_alt + supply_slope_alt * q_range if supply_intercept_alt is not None else None
+
+    plt.figure(figsize=(8, 6))
+    plt.plot(q_range, demand_curve, label="Demand Curve", color="blue")
+    plt.plot(q_range, supply_curve_primary, label="Supply Curve (Original)", color="green")
+    if supply_curve_alt is not None:
+        plt.plot(q_range, supply_curve_alt, label="Supply Curve (Alternative)", color="red", linestyle="dashed")
+
+    plt.xlabel("Quantity")
+    plt.ylabel("Price")
+    plt.title(f"Market Equilibrium: {market_name}")
+    plt.legend()
+    st.pyplot(plt)
+
+# Streamlit Interface
+st.title("Market Equilibrium Solver")
+
+st.write("Enter a question describing supply and demand equations for corn and water.")
+user_query = st.text_area(
+    "Type your question here:", 
+    value="Corn market demand: intercept 100, slope -2. Original Corn supply (water consumers pay): intercept 20, slope 3. Intervene Corn supply (corn producer pays): intercept 30, slope 3.\n"
+          "Original Sceanrio (water consumer pays): Water Demand has intercept 200, slope -4. Water Supply has intercept 64.38, slope 2.1.\n"
+          "Intervene Scenario (corn producer pays): Water demand has intercept 200, slope -4. Water supply has intercept 44.91, slope 2.1."
+)
+
+
+if st.button("Solve"):
+    params = extract_equation_params(user_query)
+
+    if params:
+        demand_intercept_corn, demand_slope_corn, supply_intercept_corn, supply_slope_corn, \
+        supply_intercept_prod_pay, supply_slope_prod_pay, \
+        demand_intercept_cleaned, demand_slope_cleaned, supply_intercept_cleaned, supply_slope_cleaned, \
+        demand_intercept_no_loading, demand_slope_no_loading, supply_intercept_no_loading, supply_slope_no_loading = params
+
+        # Compute Equilibria for Corn
+        quantity_eq_corn, price_eq_corn, cs_eq_corn, ps_eq_corn, sw_eq_corn = \
+            calculate_equilibrium(demand_intercept_corn, demand_slope_corn, supply_intercept_corn, supply_slope_corn)
+
+        quantity_eq_corn_prod_pay, price_eq_corn_prod_pay, cs_eq_corn_prod_pay, ps_eq_corn_prod_pay, sw_eq_corn_prod_pay = \
+            calculate_equilibrium(demand_intercept_corn, demand_slope_corn, supply_intercept_prod_pay, supply_slope_prod_pay)
+
+        # Compute Equilibria for Water
+        quantity_eq_cleaned, price_eq_cleaned, cs_eq_cleaned, ps_eq_cleaned, sw_eq_cleaned = \
+            calculate_equilibrium(demand_intercept_cleaned, demand_slope_cleaned, supply_intercept_cleaned, supply_slope_cleaned)
+
+        quantity_eq_no_loading, price_eq_no_loading, cs_eq_no_loading, ps_eq_no_loading, sw_eq_no_loading = \
+            calculate_equilibrium(demand_intercept_no_loading, demand_slope_no_loading, supply_intercept_no_loading, supply_slope_no_loading)
+
+        # Display Equilibrium Prices and Quantities
+        st.write("\n**Equilibrium Prices and Quantities:**")
+        st.write(f"- **Corn Mkt(Original:Water Consumer Pay):** Price: ${price_eq_corn}, Quantity: {quantity_eq_corn} units")
+        st.write(f"- **Corn Mkt(Intervene:Corn Producer Pays):** Price: ${price_eq_corn_prod_pay}, Quantity: {quantity_eq_corn_prod_pay} units")
+        st.write(f"- **Water Market(Original:Water Consumer Pays):** Price: ${price_eq_cleaned}, Quantity: {quantity_eq_cleaned} units")
+        st.write(f"- **Water Mkt:(intervene:Corn Producer Pays):** Price: ${price_eq_no_loading}, Quantity: {quantity_eq_no_loading} units")
+
+        # Plot Graphs for Corn with both supply curves
+        plot_market(demand_intercept_corn, demand_slope_corn, supply_intercept_corn, supply_slope_corn,
+                    quantity_eq_corn, price_eq_corn, "Corn Market", supply_intercept_prod_pay, supply_slope_prod_pay)
+
+        # Plot Graphs for Water with both supply curves
+        plot_market(demand_intercept_cleaned, demand_slope_cleaned, supply_intercept_cleaned, supply_slope_cleaned,
+                    quantity_eq_cleaned, price_eq_cleaned, "Water Market", supply_intercept_no_loading, supply_slope_no_loading)
+
+        # Display Surplus Tables
+        st.write("\n**Surplus Tables:**")
+        st.table(pd.DataFrame({
+            "Scenario": ["Orig Corn Mkt:Water Cons Pay", "Intervene Corn Mkt:Corn Prod Pay)", "Difference"],
+            "Consumer Surplus": [cs_eq_corn, cs_eq_corn_prod_pay, cs_eq_corn_prod_pay - cs_eq_corn],
+            "Producer Surplus": [ps_eq_corn, ps_eq_corn_prod_pay, ps_eq_corn_prod_pay - ps_eq_corn],
+            "Total Social Welfare": [sw_eq_corn, sw_eq_corn_prod_pay, sw_eq_corn_prod_pay - sw_eq_corn]
+        }))
+
+        st.table(pd.DataFrame({
+            "Scenario": ["Orig Water Mkt:Water Cons Pay", "Intervene Water Mkt:Corn Prod Pay", "Difference"],
+            "Consumer Surplus": [cs_eq_cleaned, cs_eq_no_loading, cs_eq_no_loading - cs_eq_cleaned],
+            "Producer Surplus": [ps_eq_cleaned, ps_eq_no_loading, ps_eq_no_loading - ps_eq_cleaned],
+            "Total Social Welfare": [sw_eq_cleaned, sw_eq_no_loading, sw_eq_no_loading - sw_eq_cleaned]
+        }))