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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 subprocess | |
| # Ensure SpaCy is installed | |
| try: | |
| import spacy | |
| except ModuleNotFoundError: | |
| subprocess.run(["pip", "install", "spacy"]) | |
| import spacy | |
| # Ensure the model is installed | |
| try: | |
| nlp = spacy.load("en_core_web_sm") | |
| except OSError: | |
| subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"]) | |
| nlp = spacy.load("en_core_web_sm") | |
| 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] | |
| })) | |