Add main project files

app.py

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+import gradio as gr
+import pandas as pd
+import pulp
+import numpy as np
+
+LANGUAGE = "en"
+
+# Define the quality tiers and names for the plants
+PLANTS_TIERS = {
+    "radiant": "金品质",
+    "flourishing": "紫品质",
+    "hardy": "蓝品质",
+    "feeble": "白品质",
+}
+
+PLANTS_I18N = {
+    "fanged_geranium": "毒牙天竺葵",
+    "gillyweed": "鳃囊草",
+    "rose": "玫瑰",
+    "puffapod": "泡泡豆荚",
+    "nifflers_fancy": "嗅幻草",
+    "ladys_mantle": "羽衣草",
+    "mandrake": "曼德拉草",
+    "chinese_chomping_cabbage": "中国咬人甘蓝",
+    "peony": "牡丹",
+    "begonia": "秋海棠",
+    "mayflower": "五月花",
+    "hydrangea": "绣球",
+    "daffodil": "水仙",
+}
+
+# Import and process plant data
+df = pd.read_csv("plants.csv")
+
+# Convert columns to Categorical type and remove rows with NaN in 'gold' column
+df["species"] = pd.Categorical(df["species"])
+df["tier"] = pd.Categorical(df["tier"])
+df = df.dropna(subset=["gold"])
+df = df.astype(
+    {
+        "gold": int,
+        "gems": int,
+    }
+)
+
+
+def calculator(*args):
+    """
+    Calculate the optimal solution of plant sales based on the given budget
+    and inventory constraints.
+
+    Args:
+        *args (tuple): A tuple where the first element is Gabby's gold budget,
+                       and the subsequent elements represent the stock levels of
+                       each plant type.
+
+    Returns:
+        str: A description of the optimal solution, including which plants to sell,
+             the total gold earned, and the remaining inventory.
+    """
+    budget = args[0]  # 葭碧预算
+    stocks = np.array(args[1:])  # 植物库存
+
+    # 植物名称列表
+    plants_en = [f"{row['tier']}_{row['species']}" for index, row in df.iterrows()]
+
+    gold = np.array(df["gold"])  # 植物单价
+
+    # 创建问题实例，目标是最大化存货数量
+    prob = pulp.LpProblem("Maximize_Sale", pulp.LpMaximize)
+
+    # 决策变量，售出每种植物的件数，必须是整数
+    x = pulp.LpVariable.dicts("x", range(len(stocks)), lowBound=0, cat="Integer")
+
+    # 遍历，设置决策变量的上界为库存量
+    for i in range(len(stocks)):
+        x[i].upBound = stocks[i]
+
+    # 目标函数：最大化总的存货数量
+    prob += pulp.lpSum([stocks[i] - x[i] for i in range(len(stocks))])
+
+    # 约束条件：每类产品售出数量乘以单价之和等于总价格
+    prob += pulp.lpSum([gold[i] * x[i] for i in range(len(stocks))]) == budget
+
+    # 求解问题
+    # CBC(Coin-or Branch and Cut)求解器使用分支定界算法来寻找整数规划问题的最优解
+    solver = pulp.getSolver("PULP_CBC_CMD")
+    prob.solve(solver=solver)
+
+    if pulp.LpStatus[prob.status] == "Optimal":
+
+        sold = 0
+        solution = []
+        for i, v in x.items():
+            if v.varValue:
+                if v.varValue > 0:
+                    solution.append(f"{plants_en[i]}: {int(v.varValue)}\n")
+                    sold += int(v.varValue) * gold[i]
+
+        return f"Optimal solution found:\n\n{''.join(solution)}\nTotal price: {sold}\nStock: {pulp.value(prob.objective)}"
+    else:
+        return "No solution found."
+
+
+# Create a Gradio interface with a column layout
+with gr.Blocks() as demo:
+    with gr.Column():
+        # Add a row for the budget input
+        with gr.Row():
+            budget = gr.Number(
+                label="Gold Budget", value=0, minimum=0, maximum=15000, step=100
+            )
+
+        # Add a row for the plant inventory inputs
+        with gr.Row():
+            inventory = {}
+            for index, row in df.iterrows():
+                inventory[f"{row['tier']}_{row['species']}"] = gr.Number(
+                    label=f"{row['tier']}_{row['species']}",
+                    value=0,
+                    minimum=0,
+                    maximum=500,
+                    step=10,
+                )
+
+        # Add a button to trigger the calculation
+        submit_btn = gr.Button(value="Calculate")
+
+        # Add a row for the result textbox
+        with gr.Row():
+            result = gr.Textbox()
+
+    # Set up the button click event to call the calculator function
+    submit_btn.click(
+        calculator,
+        inputs=[budget] + list(inventory.values()),
+        outputs=[result],
+        api_name=False,
+    )
+
+# Launch the Gradio application
+if __name__ == "__main__":
+    demo.launch(show_api=False)

plants.csv

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+gold,gems,species,tier,amount
+12,0,fanged_geranium,radiant,0
+9,0,fanged_geranium,flourishing,0
+8,0,fanged_geranium,hardy,0
+1,0,fanged_geranium,feeble,0
+6,0,gillyweed,radiant,0
+4,0,gillyweed,flourishing,0
+3,0,gillyweed,hardy,0
+1,0,gillyweed,feeble,0
+42,0,rose,radiant,0
+34,0,rose,flourishing,0
+30,0,rose,hardy,0
+,0,rose,feeble,0
+85,0,puffapod,radiant,0
+62,0,puffapod,flourishing,0
+55,0,puffapod,hardy,0
+,0,puffapod,feeble,0
+0,5,nifflers_fancy,radiant,0
+260,0,nifflers_fancy,flourishing,0
+234,0,nifflers_fancy,hardy,0
+1,0,nifflers_fancy,feeble,0
+105,0,ladys_mantle,radiant,0
+96,0,ladys_mantle,flourishing,0
+76,0,ladys_mantle,hardy,0
+,0,ladys_mantle,feeble,0
+24,0,mandrake,radiant,0
+22,0,mandrake,flourishing,0
+15,0,mandrake,hardy,0
+,0,mandrake,feeble,0
+57,0,chinese_chomping_cabbage,radiant,0
+40,0,chinese_chomping_cabbage,flourishing,0
+36,0,chinese_chomping_cabbage,hardy,0
+,0,chinese_chomping_cabbage,feeble,0
+0,2,peony,radiant,0
+58,0,peony,flourishing,0
+45,0,peony,hardy,0
+1,0,peony,feeble,0
+72,0,begonia,radiant,0
+58,0,begonia,flourishing,0
+,0,begonia,hardy,0
+,0,begonia,feeble,0
+186,0,mayflower,radiant,0
+,0,mayflower,flourishing,0
+,0,mayflower,hardy,0
+,0,mayflower,feeble,0
+215,0,hydrangea,radiant,0
+,0,hydrangea,flourishing,0
+,0,hydrangea,hardy,0
+,0,hydrangea,feeble,0
+0,2,daffodil,radiant,0
+,0,daffodil,flourishing,0
+,0,daffodil,hardy,0
+,0,daffodil,feeble,0