Added files

app.py

@@ -0,0 +1,58 @@
+import gradio as gr
+from joblib import load
+import os
+import pandas as pd
+
+# load the model
+def load_model(path=""):
+    if os.path.exists(path):
+        model_dict = load(path)
+        return model_dict
+    else:
+        print("Model not found")
+
+model_dict = load_model('diamond_price.joblib')
+# prediction function
+def diamond_price_regressor(caret, depth, table, x, y, z, cut, color, clarity):
+    model = model_dict['model']
+    target_converter = model_dict['quantile']
+    input_frame = pd.DataFrame({
+        'carat': [caret],
+        'cut': [cut],
+        'color': [color],
+        'clarity': [clarity],
+        'depth': [depth],
+        'table': [table],
+        'x': [x],
+        'y': [y],
+        'z': [z]
+    })
+    print(input_frame)
+    pred = model.predict(input_frame)
+    pred = target_converter.inverse_transform(pred.reshape(-1, 1))
+    print(pred)
+    return f'Approx price is ${pred[0][0]:.2f}'
+
+cut_choices = ['Ideal', 'Premium', 'Good', 'Very Good', 'Fair']
+color_choices = ['E', 'I', 'J', 'H', 'F', 'G', 'D']
+clarity_choices = ['SI2', 'SI1', 'VS1', 'VS2', 'VVS2', 'VVS1', 'I1', 'IF']
+
+# gradio interface
+ui = gr.Interface(
+    fn = diamond_price_regressor,
+    inputs = [
+        gr.Slider(minimum=0, maximum=10, step=.01, value=.7, label="Carat", info="1 carat = 0.2 grams"),
+        gr.Slider(minimum=0, maximum=100, step=.01, value=61, label="Depth", info="Total depth percentage"),
+        gr.Slider(minimum=0, maximum=100, step=.01, value=57, label="Table", info="Width of top of diamond relative to widest point"),
+        gr.Slider(minimum=0, maximum=100, step=.01, value=5, label="x", info="Length in mm"),
+        gr.Slider(minimum=0, maximum=100, step=.01, value=5, label="y", info="Width in mm"),
+        gr.Slider(minimum=0, maximum=100, step=.01, value=3.5, label="z", info="Height in mm"),
+        gr.Dropdown(cut_choices, label="Cut", value="Ideal", info="Cut quality"),
+        gr.Dropdown(color_choices, label="Color", value="E", info="Color grade"),
+        gr.Dropdown(clarity_choices, label="Clarity", value="SI2", info="Clarity grade")
+    ],
+    outputs = "text",
+)
+
+if __name__ == "__main__":
+    ui.launch()

diamond_price.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a317966b5e8d936934fd45dadca0f61c9959273ab1f1cf3d5db020ce2fd7428d
+size 12623306