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import streamlit as st
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import pandas as pd
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import logging
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from database import get_db, initialize_database, Product
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from inventory import (add_product, get_all_products, get_product_by_id, add_product_memory,
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update_product_memory, delete_product_memory, add_stock_memory,
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remove_stock_memory)
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from prediction import predict_stockout
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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logger = logging.getLogger(__name__)
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st.set_page_config(page_title="Inventory Dashboard", layout="wide")
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try:
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with open("styles.css") as f:
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st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
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except FileNotFoundError:
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logger.warning("styles.css not found")
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if "user_products" not in st.session_state:
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st.session_state.user_products = []
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if "user_transactions" not in st.session_state:
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st.session_state.user_transactions = []
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def initialize_example_products(db):
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"""Add electronics example products if database is empty."""
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try:
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if db.query(Product).count() == 0:
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examples = [
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("Smartphone", 50.0, 20.0, 7.0, 200.0, "A"),
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("Laptop", 30.0, 10.0, 5.0, 150.0, "A"),
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("Headphones", 100.0, 30.0, 3.0, 120.0, "B"),
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("Smartwatch", 80.0, 25.0, 4.0, 90.0, "C")
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]
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for name, stock, safety, lead, demand, cls in examples:
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add_product(db, name, stock, safety, lead, demand, cls)
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logger.info("Added example electronics products")
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except Exception as e:
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logger.error(f"Error adding example products: {str(e)}")
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raise
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try:
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initialize_database()
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with next(get_db()) as db:
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initialize_example_products(db)
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cached_products = get_all_products(db)
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except Exception as e:
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logger.error(f"Error initializing database or example products: {str(e)}")
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st.error(f"Error: {str(e)}")
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st.stop()
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st.sidebar.title("Navigation")
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page = st.sidebar.radio("Go to", ["Dashboard", "Product Management", "User Guide"])
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st.sidebar.markdown("**Note**: Changes are local to your session and reset on page refresh.")
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def display_footer():
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st.markdown("""
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<div class="footer">
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<p style="font-size: small; color: grey; text-align: center;">
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Developed By: Krishna Prakash
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<a href="https://www.linkedin.com/in/krishnaprakash-profile/" target="_blank">
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<img src="https://img.icons8.com/ios-filled/30/0077b5/linkedin.png" alt="LinkedIn" style="vertical-align: middle; margin: 0 10px;"/>
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</a>
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</p>
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</div>
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""", unsafe_allow_html=True)
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def validate_product_inputs(name, current_stock, safety_stock, lead_time, monthly_demand, product_class):
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if not name:
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return "Name is required."
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if any(x < 0 for x in [current_stock, safety_stock, lead_time, monthly_demand]):
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return "Negative values not allowed."
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if product_class not in ["A", "B", "C"]:
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return "Product class must be A, B, or C."
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return None
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if page == "Dashboard":
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st.title("Inventory Dashboard")
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try:
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session_products = st.session_state.user_products
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all_products = cached_products + [p for p in session_products]
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if not all_products:
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st.warning("No products found.")
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else:
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product_data = [{
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"ID": p.id if hasattr(p, "id") else p.get("id", "N/A"),
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"Name": p.name if hasattr(p, "name") else p.get("name", "Unknown"),
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"Stock": p.current_stock if hasattr(p, "current_stock") else p.get("current_stock", 0.0),
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"Safety Stock": p.safety_stock if hasattr(p, "safety_stock") else p.get("safety_stock", 0.0),
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"Lead Time (days)": p.lead_time if hasattr(p, "lead_time") else p.get("lead_time", 0.0),
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"Demand": p.monthly_demand if hasattr(p, "monthly_demand") else p.get("monthly_demand", 0.0),
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"Class": p.product_class if hasattr(p, "product_class") else p.get("product_class", "C"),
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"Source": "Example" if hasattr(p, "id") else "User"
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} for p in all_products]
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df = pd.DataFrame(product_data).reset_index(drop=True)
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st.subheader("Inventory")
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st.dataframe(df, use_container_width=True)
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st.subheader("Stockout Predictions")
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for p in all_products:
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with st.expander(f"{p.name if hasattr(p, 'name') else p.get('name', 'Unknown')} (ID: {p.id if hasattr(p, 'id') else p.get('id', 'N/A')})"):
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result = predict_stockout(
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p.monthly_demand if hasattr(p, "monthly_demand") else p.get("monthly_demand", 0.0),
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p.lead_time if hasattr(p, "lead_time") else p.get("lead_time", 0.0),
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p.current_stock if hasattr(p, "current_stock") else p.get("current_stock", 0.0),
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p.product_class if hasattr(p, "product_class") else p.get("product_class", "C")
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)
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st.markdown(result, unsafe_allow_html=True)
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st.subheader("Alerts")
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alerts = []
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for p in all_products:
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stock = p.current_stock if hasattr(p, "current_stock") else p.get("current_stock", 0.0)
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safety = p.safety_stock if hasattr(p, "safety_stock") else p.get("safety_stock", 0.0)
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name = p.name if hasattr(p, "name") else p.get("name", "Unknown")
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result = predict_stockout(
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p.monthly_demand if hasattr(p, "monthly_demand") else p.get("monthly_demand", 0.0),
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p.lead_time if hasattr(p, "lead_time") else p.get("lead_time", 0.0),
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stock,
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p.product_class if hasattr(p, "product_class") else p.get("product_class", "C")
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)
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risk_level = "Low Risk" if "Low Risk" in result else "Medium Risk" if "Medium Risk" in result else "High Risk"
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if "High Risk" in risk_level:
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alerts.append(f"High Risk Alert: {name} has {stock} units. Replenish inventory immediately.")
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elif "Medium Risk" in risk_level:
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alerts.append(f"Medium Risk Alert: {name} has {stock} units. Monitor closely.")
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elif "Low Risk" in risk_level and stock < safety:
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alerts.append(f"Low Risk Alert: {name} has {stock} units, below {safety}. No action needed yet.")
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if alerts:
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for alert in alerts:
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alert_class = "alert-high" if "High Risk" in alert else "alert-medium" if "Medium Risk" in alert else "alert"
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st.markdown(f"<div class='{alert_class}'>{alert}</div>", unsafe_allow_html=True)
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else:
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st.success("All products are above predicted safety thresholds.")
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except Exception as e:
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logger.error(f"Dashboard error: {str(e)}")
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st.error(f"Error: {str(e)}")
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elif page == "Product Management":
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st.title("Product Management")
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st.markdown("**Note**: Products and changes are local to your session and reset on page refresh.")
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try:
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st.subheader("Add Product")
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with st.form("add_form"):
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name = st.text_input("Name")
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current_stock = st.number_input("Stock", min_value=0.0, step=1.0)
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safety_stock = st.number_input("Safety Stock", min_value=0.0, step=1.0)
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lead_time = st.number_input("Lead Time (days)", min_value=0.0, max_value=90.0, step=1.0)
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monthly_demand = st.number_input("Monthly Demand", min_value=0.0, step=1.0)
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product_class = st.selectbox("Class", ["A", "B", "C"])
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if st.form_submit_button("Add"):
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error = validate_product_inputs(name, current_stock, safety_stock, lead_time, monthly_demand, product_class)
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if error:
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st.error(error)
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else:
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add_product_memory(st.session_state.user_products, name, current_stock, safety_stock, lead_time, monthly_demand, product_class)
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st.success(f"Added {name} (local to your session)")
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st.subheader("Manage Products")
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session_products = st.session_state.user_products
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if session_products:
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product_id = st.selectbox("Select Product", [p["id"] for p in session_products], format_func=lambda x: next(p["name"] for p in session_products if p["id"] == x))
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product = next(p for p in session_products if p["id"] == product_id)
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with st.form("edit_form"):
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edit_name = st.text_input("Name", value=product["name"])
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edit_current_stock = st.number_input("Stock", min_value=0.0, step=1.0, value=float(product["current_stock"]))
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edit_safety_stock = st.number_input("Safety Stock", min_value=0.0, step=1.0, value=float(product["safety_stock"]))
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edit_lead_time = st.number_input("Lead Time (days)", min_value=0.0, max_value=90.0, step=1.0, value=float(product["lead_time"]))
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edit_monthly_demand = st.number_input("Monthly Demand", min_value=0.0, step=1.0, value=float(product["monthly_demand"]))
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edit_product_class = st.selectbox("Class", ["A", "B", "C"], index=["A", "B", "C"].index(product["product_class"]))
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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if st.form_submit_button("Update"):
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error = validate_product_inputs(edit_name, edit_current_stock, edit_safety_stock, edit_lead_time, edit_monthly_demand, edit_product_class)
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if error:
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st.error(error)
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else:
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update_product_memory(st.session_state.user_products, product_id, edit_name, edit_current_stock, edit_safety_stock, edit_lead_time, edit_monthly_demand, edit_product_class)
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st.success(f"Updated {edit_name} (local)")
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with col2:
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if st.form_submit_button("Delete"):
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delete_product_memory(st.session_state.user_products, product_id)
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st.success(f"Deleted {product['name']} (local)")
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with col3:
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add_qty = st.number_input("Add Stock", min_value=0.0, step=1.0, key="add_qty")
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if st.form_submit_button("Add Stock"):
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if add_qty <= 0:
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st.error("Quantity must be positive.")
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else:
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add_stock_memory(st.session_state.user_products, st.session_state.user_transactions, product_id, add_qty)
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st.success(f"Added {add_qty} to {product['name']} (local)")
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with col4:
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remove_qty = st.number_input("Remove Stock", min_value=0.0, step=1.0, key="remove_qty")
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if st.form_submit_button("Remove Stock"):
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if remove_qty <= 0:
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st.error("Quantity must be positive.")
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else:
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remove_stock_memory(st.session_state.user_products, st.session_state.user_transactions, product_id, remove_qty)
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st.success(f"Removed {remove_qty} from {product['name']} (local)")
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else:
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st.warning("No user-added products in your session.")
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except Exception as e:
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logger.error(f"Product management error: {str(e)}")
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st.error(f"Error: {str(e)}")
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elif page == "User Guide":
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st.title("User Guide")
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st.markdown("""
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Welcome to the **Inventory Dashboard**! This guide explains how to use the system, the meaning of risk levels, and inventory management concepts.
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""")
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with st.expander("What is the Inventory Dashboard?"):
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st.markdown("""
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The Inventory Dashboard helps you track and manage stock levels for electronics products. It predicts stockout risks and provides alerts to ensure availability.
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""")
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with st.expander("ABC Classification"):
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st.markdown("""
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<b>ABC Classification</b> categorizes inventory based on value and quantity to prioritize management efforts:<br>
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- <b>Class A</b>: High-value, low-quantity items (e.g., Smartphones, Laptops) requiring tight control.<br>
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- <b>Class B</b>: Medium-value, medium-quantity items (e.g., Headphones) needing balanced oversight.<br>
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- <b>Class C</b>: Low-value, high-quantity items (e.g., Smartwatches) requiring minimal attention.<br>
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<b>Example</b>: A store might prioritize restocking Smartphones (Class A) over Smartwatches (Class C) due to higher value and demand variability.
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""", unsafe_allow_html=True)
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with st.expander("Risk Levels"):
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st.markdown("""
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- <b>Low Risk</b>: Risk below 15%. Indicates the current stock is sufficient with no immediate action needed.<br>
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- <b>Medium Risk</b>: Risk between 15% and 40%. Suggests monitoring the product closely to avoid potential stockouts.<br>
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- <b>High Risk</b>: Risk above 40%. Indicates a need to replenish inventory immediately to prevent stockouts.
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""", unsafe_allow_html=True)
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with st.expander("Inventory Levels"):
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st.markdown("""
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- <b>Optimal Inventory Level</b>: Stock is well above safety stock, ensuring availability without excess.<br>
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- <b>Monitor Closely</b>: Stock is nearing safety stock; keep an eye on demand and supply.<br>
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- <b>Replenish Inventory</b>: Stock is below safety stock; urgent action is required to restock.
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""", unsafe_allow_html=True)
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with st.expander("Benefits and Use Cases"):
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st.markdown("""
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<b>Benefits include:</b><br>
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- Cost Savings: Reduces excess inventory and storage costs.<br>
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- Efficiency: Automates tracking, saving time.<br>
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- Customer Satisfaction: Prevents stockouts, ensuring product availability.<br>
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<b>Use Cases:</b><br>
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- Retail: Manage stock in electronics stores or e-commerce.<br>
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- Manufacturing: Track electronic components and finished goods.<br>
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- Healthcare: Ensure availability of medical electronics.
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""", unsafe_allow_html=True)
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display_footer() |