Delete shelfy_purchase_rate_v2

shelfy_purchase_rate_v2/app.py

@@ -1,60 +0,0 @@
-import gradio as gr
-import pandas as pd
-import joblib
-
-# Load model
-model = joblib.load("shelfy_purchase_rate_v2.joblib")
-
-def predict_conversion(product_name, views, carts, unique_users, avg_price, carts_lag_1, carts_lag_3):
-    # Convert to float (Gradio passes strings)
-    views = float(views or 0)
-    carts = float(carts or 0) 
-    unique_users = float(unique_users or 0)
-    avg_price = float(avg_price or 0)
-    carts_lag_1 = float(carts_lag_1 or 0)
-    carts_lag_3 = float(carts_lag_3 or 0)
-    
-    # Calculate ratios (same as training)
-    cart_intent = carts / (views + 1)
-    user_intensity = unique_users / (views + 1)
-    
-    data = pd.DataFrame({
-        'views': [views],
-        'carts': [carts],
-        'unique_users': [unique_users],
-        'avg_price': [avg_price],
-        'carts_lag_1': [carts_lag_1],
-        'carts_lag_3': [carts_lag_3],
-        'cart_intent': [cart_intent],
-        'user_intensity': [user_intensity]
-    })
-    
-    future_rate = model.predict(data)[0]
-    
-    return (
-        f"{future_rate:.2%}", 
-        f"${future_rate * views * avg_price:.0f}",
-        "Good Demand" if future_rate >= 0.025 else "Medium Demand" if future_rate >= 0.015 else "Low Demand"
-    )
-
-demo = gr.Interface(
-    fn=predict_conversion,
-    inputs=[
-        gr.Textbox("iPhone Case", label="Product Name"),
-        gr.Number(1500, label="Views (Today)"), 
-        gr.Number(45, label="Carts (Today)"),
-        gr.Number(320, label="Unique Users"),
-        gr.Number(26, label="Avg Price $"),
-        gr.Number(40, label="Yesterday Carts"), 
-        gr.Number(35, label="3 Days Ago Carts")
-    ],
-    outputs=[
-        gr.Label(label="Predicted Conversion (Tomorrow)"),
-        gr.Label(label="Revenue Potential"), 
-        gr.Label(label="Demand")
-    ],
-    title="🛒 Shelfy: Tomorrow's Best Sellers",
-    description="Top 10% predictions captured 25.4% of sales!"
-)
-
-demo.launch()

shelfy_purchase_rate_v2/requirements.txt

@@ -1,5 +0,0 @@
-gradio==4.44.0
-xgboost
-pandas
-joblib
-scikit-learn

shelfy_purchase_rate_v2/shelfy_purchase_rate_v2.joblib

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9c69101767b9c73a12c57ceb042cd54d362f35475b87b8883cd2aec1c7884e24
-size 798259