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app.py

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+import gradio as gr
+import re
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Store equation values
+stored_equations = {}
+
+# Function to extract numbers from text
+def extract_numbers(phrase):
+    return [float(num) for num in re.findall(r'-?\d+\.?\d*', phrase)]
+
+# Function to calculate equilibrium
+def calculate_equilibrium(demand_intercept, slope_demand, supply_intercept, slope_supply):
+    Q_eq = (demand_intercept - supply_intercept) / (slope_supply - slope_demand)
+    P_eq = demand_intercept + slope_demand * Q_eq
+    return round(Q_eq, 2), round(P_eq, 2)
+
+def plot_equilibrium(demand_intercept, slope_demand, supply_intercept, slope_supply):
+    Q_range = np.linspace(0, 20, 100)
+    demand_curve = demand_intercept + (slope_demand * Q_range)
+    supply_curve = supply_intercept + (slope_supply * Q_range)
+
+    plt.figure(figsize=(6, 4))
+    plt.plot(Q_range, demand_curve, label="Demand Curve", color="blue")
+    plt.plot(Q_range, supply_curve, label="Supply Curve", color="green")
+
+    # Calculate equilibrium
+    Q_eq, P_eq = calculate_equilibrium(demand_intercept, slope_demand, supply_intercept, slope_supply)
+
+    # Calculate CS & PS
+    CS_top = demand_intercept  # Max price consumers would pay (demand intercept)
+    PS_bottom = supply_intercept  # Min price suppliers accept (supply intercept)
+
+    CS = 0.5 * (CS_top - P_eq) * Q_eq  # Triangle area for CS
+    PS = 0.5 * (P_eq - PS_bottom) * Q_eq  # Triangle area for PS
+
+    # ✅ Print CS & PS values
+    print(f"Consumer Surplus (CS): {CS:.2f}")
+    print(f"Producer Surplus (PS): {PS:.2f}")
+
+    # Highlight CS (shaded area above equilibrium price)
+    plt.fill_between([0, Q_eq], [CS_top, P_eq], P_eq, color="blue", alpha=0.3, label="Consumer Surplus")
+
+    # Highlight PS (shaded area below equilibrium price)
+    plt.fill_between([0, Q_eq], P_eq, [PS_bottom, P_eq], color="green", alpha=0.3, label="Producer Surplus")
+
+    # Mark equilibrium point
+    plt.scatter(Q_eq, P_eq, color="red", label=f"Equilibrium ({Q_eq}, {P_eq})")
+
+    plt.xlabel("Quantity")
+    plt.ylabel("Price")
+    plt.legend()
+    plt.title("Supply & Demand Equilibrium with CS & PS")
+    plt.grid()
+
+    plot_filename = "equilibrium_plot.png"
+    plt.savefig(plot_filename)
+    plt.close()
+    return plot_filename, CS, PS
+
+
+# Function to process user input
+def chatbot(user_input):
+    global stored_equations
+    user_input = user_input.strip().lower()
+
+    if not user_input:
+        return "Please enter a valid question.", None
+
+    # Step 1: Detect if user wants to find equilibrium
+    if "equilibrium" in user_input:
+        return "Enter demand and supply equations in this format: Demand: P = a - bQ, Supply: P = c + dQ.", None
+
+    # Step 2: Detect if user entered equations
+    if "p =" in user_input:
+        numbers = extract_numbers(user_input)
+        if len(numbers) == 4:
+            stored_equations = {
+                "demand_intercept": numbers[0],
+                "demand_slope": -abs(numbers[1]),  # Ensure demand slope is negative
+                "supply_intercept": numbers[2],
+                "supply_slope": abs(numbers[3])  # Ensure supply slope is positive
+            }
+            return (f"Stored values:\n"
+                    f"  Demand: P = {numbers[0]} - {abs(numbers[1])}Q\n"
+                    f"  Supply: P = {numbers[2]} + {numbers[3]}Q\n"
+                    f"Type 'solve' to calculate equilibrium."), None
+
+        else:
+            return "Invalid format. Please enter equations correctly.", None
+
+    # Step 3: Compute equilibrium when user types "solve"
+    if "solve" in user_input:
+        if not stored_equations:
+            return "Error: Missing equations. Please enter demand and supply equations first.", None
+
+        Q_eq, P_eq = calculate_equilibrium(
+            stored_equations["demand_intercept"],
+            stored_equations["demand_slope"],
+            stored_equations["supply_intercept"],
+            stored_equations["supply_slope"]
+        )
+        plot_path, CS, PS = plot_equilibrium(
+            stored_equations["demand_intercept"],
+            stored_equations["demand_slope"],
+            stored_equations["supply_intercept"],
+            stored_equations["supply_slope"]
+        )
+        return f"Equilibrium found at Quantity = {Q_eq}, Price = {P_eq}, CS = {CS}, PS = {PS}.", plot_path
+
+    return "I can help with equilibrium calculations. Try typing 'I want to find equilibrium.'", None
+
+# Launch Gradio chatbot
+#interface = gr.Interface(fn=chatbot, inputs="text", outputs=["text", "image"])
+
+# Launch Gradio chatbot
+interface = gr.Interface(
+    fn=chatbot,
+    inputs="text",
+    outputs=[
+        gr.Textbox(lines=4, interactive=False),  # Output box with flexible content, always 4 lines tall
+        gr.Image()
+    ],
+    title="AGEC 3503 HW Bot",
+    description="Hi, Welcome to the AGEC 3503 HW Bot! Enter your question to solve a problem like Competitive Equilibrium."
+)
+
+interface.launch(share=True)

requirements.txt

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+gradio
+numpy
+matplotlib