Create app.py

app.py

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+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Data: Nutritional Information for the healthiest dishes
+nutritional_data = {
+    "Idli with Vegetable Sambar": {
+        "Energy (kcal)": 100, "Protein (g)": 5.5, "Fat (g)": 1.5, "Carbohydrate (g)": 17.0, "Fiber (g)": 3.0, "Calcium (mg)": 35, "Iron (mg)": 1.0, "Vitamin C (mg)": 8.0
+    },
+    "Khichdi": {
+        "Energy (kcal)": 120, "Protein (g)": 4.0, "Fat (g)": 2.5, "Carbohydrate (g)": 20.0, "Fiber (g)": 2.5, "Calcium (mg)": 40, "Iron (mg)": 1.0, "Vitamin C (mg)": 5.0
+    },
+    "Tandoori Chicken": {
+        "Energy (kcal)": 150, "Protein (g)": 18.0, "Fat (g)": 7.0, "Carbohydrate (g)": 3.0, "Fiber (g)": 0.5, "Calcium (mg)": 15, "Iron (mg)": 1.2, "Vitamin C (mg)": 1.5
+    },
+    "Palak Paneer": {
+        "Energy (kcal)": 140, "Protein (g)": 7.5, "Fat (g)": 10.0, "Carbohydrate (g)": 6.0, "Fiber (g)": 3.0, "Calcium (mg)": 200, "Iron (mg)": 3.0, "Vitamin C (mg)": 15.0
+    },
+    "Raita": {
+        "Energy (kcal)": 60, "Protein (g)": 3.5, "Fat (g)": 2.0, "Carbohydrate (g)": 6.5, "Fiber (g)": 0.5, "Calcium (mg)": 100, "Iron (mg)": 0.5, "Vitamin C (mg)": 2.0
+    },
+    "Rajma": {
+        "Energy (kcal)": 140, "Protein (g)": 7.5, "Fat (g)": 5.0, "Carbohydrate (g)": 20.0, "Fiber (g)": 6.0, "Calcium (mg)": 50, "Iron (mg)": 3.5, "Vitamin C (mg)": 4.0
+    },
+    "Baingan Bharta": {
+        "Energy (kcal)": 70, "Protein (g)": 2.5, "Fat (g)": 3.0, "Carbohydrate (g)": 10.0, "Fiber (g)": 4.0, "Calcium (mg)": 30, "Iron (mg)": 0.7, "Vitamin C (mg)": 6.0
+    },
+    "Besan Chilla": {
+        "Energy (kcal)": 180, "Protein (g)": 8.0, "Fat (g)": 7.0, "Carbohydrate (g)": 20.0, "Fiber (g)": 5.0, "Calcium (mg)": 30, "Iron (mg)": 2.5, "Vitamin C (mg)": 1.0
+    },
+    "Masoor Dal": {
+        "Energy (kcal)": 110, "Protein (g)": 7.5, "Fat (g)": 2.0, "Carbohydrate (g)": 16.0, "Fiber (g)": 5.5, "Calcium (mg)": 25, "Iron (mg)": 3.0, "Vitamin C (mg)": 4.0
+    },
+    "Upma": {
+        "Energy (kcal)": 150, "Protein (g)": 4.0, "Fat (g)": 6.0, "Carbohydrate (g)": 25.0, "Fiber (g)": 3.0, "Calcium (mg)": 30, "Iron (mg)": 1.0, "Vitamin C (mg)": 3.0
+    }
+}
+
+def plot_nutritional_comparison(dish):
+    """Plots a radar chart comparing the nutritional values of the selected dish."""
+    labels = list(nutritional_data[dish].keys())
+    values = list(nutritional_data[dish].values())
+    
+    # Normalize values for better comparison on the radar chart
+    max_values = [max(nutritional_data[d][label] for d in nutritional_data) for label in labels]
+    normalized_values = [value / max_val if max_val > 0 else 0 for value, max_val in zip(values, max_values)]
+    
+    # Setup the radar chart
+    angles = np.linspace(0, 2 * np.pi, len(labels), endpoint=False).tolist()
+    values += values[:1]  # repeat the first value to close the circle
+    normalized_values += normalized_values[:1]
+    angles += angles[:1]
+    
+    fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))
+    ax.fill(angles, normalized_values, color='blue', alpha=0.25)
+    ax.plot(angles, normalized_values, color='blue', linewidth=2)
+    ax.set_yticklabels([])
+    ax.set_xticks(angles[:-1])
+    ax.set_xticklabels(labels)
+    ax.set_title(f'Nutritional Profile for {dish}', size=15, color='blue', y=1.1)
+    
+    return fig
+
+# Gradio Interface
+def create_interface():
+    dishes = list(nutritional_data.keys())
+    
+    with gr.Blocks() as demo:
+        gr.Markdown("# Nutritional Comparison of Healthiest Dishes")
+        dish_selector = gr.Dropdown(choices=dishes, label="Select a Dish", value=dishes[0])
+        nutritional_comparison_output = gr.Plot(label="Nutritional Comparison")
+        
+        # Update the plot based on the selected dish
+        def update_nutritional_comparison(dish):
+            return plot_nutritional_comparison(dish)
+        
+        dish_selector.change(fn=update_nutritional_comparison, inputs=dish_selector, outputs=nutritional_comparison_output)
+        
+        gr.Row(dish_selector, nutritional_comparison_output)
+    
+    return demo
+
+# Launch the interface
+demo = create_interface()
+demo.launch(share=True)