Delete app.py

app.py

@@ -1,70 +0,0 @@
-# app.py
-
-import gradio as gr
-import pandas as pd
-import joblib
-import os
-from transformers import pipeline
-from sklearn.linear_model import LinearRegression
-
-# Helper function to train if model doesn't exist
-def train_models():
-    print("🔵 Training models because models/inventory_forecaster.pkl not found...")
-    data = pd.read_csv('data/sales_data_large.csv')
-    product_models = {}
-
-    for product_id, group in data.groupby('Product_ID'):
-        group = group.sort_values('Date')
-        X = group[['Units_Sold']].shift(1).fillna(0)
-        y = group['Units_Sold']
-        
-        model = LinearRegression()
-        model.fit(X, y)
-        
-        product_models[product_id] = model
-
-    os.makedirs('models', exist_ok=True)
-    joblib.dump(product_models, 'models/inventory_forecaster.pkl')
-    print("✅ Models trained and saved.")
-
-# Auto-train if model doesn't exist
-if not os.path.exists('models/inventory_forecaster.pkl'):
-    train_models()
-
-# Load all ML models
-product_models = joblib.load('models/inventory_forecaster.pkl')
-
-# Load LLM pipeline
-llm = pipeline("text2text-generation", model="google/flan-t5-base")
-
-# Inventory advisor function
-def inventory_advisor(product_id, current_inventory, last_day_sales):
-    if product_id not in product_models:
-        return f"❌ Error: Product ID {product_id} not found."
-
-    forecast_model = product_models[product_id]
-    future_sales = forecast_model.predict([[last_day_sales]])[0]
-
-    prompt = (f"Current inventory is {current_inventory} units. "
-              f"Predicted sales for next week is {int(future_sales)} units. "
-              f"Should restocking be done? Suggest a human-readable restocking advice.")
-
-    response = llm(prompt, max_length=100)[0]['generated_text']
-
-    return f"🔮 Predicted Sales Next Week: {int(future_sales)} units\n\n🛒 Advice:\n{response}"
-
-# Gradio UI
-iface = gr.Interface(
-    fn=inventory_advisor,
-    inputs=[
-        gr.Number(label="Product ID"),
-        gr.Number(label="Current Inventory"),
-        gr.Number(label="Units Sold Yesterday")
-    ],
-    outputs="text",
-    title="📦 Real-Time Inventory Management (Auto-Train)",
-    description="Enter product ID, current stock, and yesterday's sales. Get AI-based restocking advice!"
-)
-
-if __name__ == "__main__":
-    iface.launch()