Update app.py

app.py

@@ -1,74 +1,50 @@
 import gradio as gr
+import pandas as pd
 
-# Sample data
-laptops = {
-
-    "Dell": {
-        "Inspiron 15 3520": "i5 12th Gen, 8GB RAM, 512GB SSD",
-        "XPS 13 9315": "i7 12th Gen, 16GB RAM, 1TB SSD",
-        "G15 Gaming": "Ryzen 7, 16GB RAM, RTX 3050",
-        "Latitude 7440": "i7, 16GB RAM, 512GB SSD"
-    },
-
-    "HP": {
-        "Pavilion 15": "Ryzen 5, 8GB RAM, 512GB SSD",
-        "Envy x360": "i7, 16GB RAM, 1TB SSD",
-        "Victus Gaming": "i5, 16GB RAM, GTX 1650",
-        "Spectre x360": "i7, 16GB RAM, OLED"
-    },
-
-    "Lenovo": {
-        "IdeaPad Slim 3": "Ryzen 5, 8GB RAM, 512GB SSD",
-        "ThinkPad E14": "i5, 16GB RAM, 512GB SSD",
-        "Legion 5": "Ryzen 7, RTX 3060",
-        "Yoga 7i": "i7, 16GB RAM, 1TB SSD"
-    },
-
-    "ASUS": {
-        "VivoBook 15": "i5, 8GB RAM, 512GB SSD",
-        "ZenBook 14": "i7, 16GB RAM, 1TB SSD",
-        "ROG Strix G16": "i9, RTX 4060",
-        "TUF A15": "Ryzen 7, RTX 3050"
-    },
-
-    "Acer": {
-        "Aspire 5": "i5, 8GB RAM, 512GB SSD",
-        "Swift 3": "Ryzen 7, 16GB RAM",
-        "Predator Helios 300": "i7, RTX 3060",
-        "Nitro 5": "Ryzen 5, GTX 1650"
-    },
-
-    "Apple": {
-        "MacBook Air M1": "8GB RAM, 256GB SSD",
-        "MacBook Air M2": "8GB RAM, 512GB SSD",
-        "MacBook Pro 14": "M3, 16GB RAM",
-        "MacBook Pro 16": "M3 Max, 32GB RAM"
-    }
-}
+# Load dataset
+df = pd.read_csv("laptops_dataset.csv")
+
+# Get brands
+brands = df["Brand"].unique().tolist()
 
 # Functions
-def show_models(brand):
-    return gr.Dropdown(choices=list(laptops[brand].keys()))
+def get_models(brand):
+    models = df[df["Brand"] == brand]["Model"].tolist()
+    return gr.Dropdown(choices=models)
+
+def compare_laptops(brand, model1, model2):
+
+    lap1 = df[(df["Brand"] == brand) & (df["Model"] == model1)]
+    lap2 = df[(df["Brand"] == brand) & (df["Model"] == model2)]
+
+    if lap1.empty or lap2.empty:
+        return "Please select valid models."
 
-def show_specs(brand, model):
-    return laptops[brand][model]
+    comparison = pd.concat([lap1, lap2])
+    return comparison
 
-# UI using Blocks
+# UI
 with gr.Blocks() as app:
 
-    gr.Markdown("## 💻 Laptop Brand & Model Explorer")
+    gr.Markdown("## 💻 Laptop Comparison Tool")
 
-    brand_dd = gr.Dropdown(
-        choices=list(laptops.keys()),
-        label="Select Brand"
-    )
+    brand_dd = gr.Dropdown(brands, label="Select Brand")
+
+    model1_dd = gr.Dropdown(label="Select Model 1")
+    model2_dd = gr.Dropdown(label="Select Model 2")
 
-    model_dd = gr.Dropdown(label="Select Model")
+    compare_btn = gr.Button("Compare")
 
-    output = gr.Textbox(label="Specifications")
+    output = gr.Dataframe()
 
-    # Events MUST be inside Blocks
-    brand_dd.change(show_models, brand_dd, model_dd)
-    model_dd.change(show_specs, [brand_dd, model_dd], output)
+    # Events
+    brand_dd.change(get_models, brand_dd, model1_dd)
+    brand_dd.change(get_models, brand_dd, model2_dd)
+
+    compare_btn.click(
+        compare_laptops,
+        [brand_dd, model1_dd, model2_dd],
+        output
+    )
 
 app.launch()