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config.py

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+import os
+
+BASE_DIR = "data"
+ASSETS_DIR = "assets"
+DEFAULT_MAP = os.path.join(ASSETS_DIR, "default_map.jpg")
+PRODUCT_IMAGE_MAP = {
+    "shampoo": os.path.join(ASSETS_DIR, "shampoo_map.jpg"),
+    "curd": os.path.join(ASSETS_DIR, "curd_map.jpg"),
+    "ghee": os.path.join(ASSETS_DIR, "ghee_map.jpg")
+}

ui/layout.py

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+import gradio as gr
+from ui.navigator_tab import create_navigator_tab
+from ui.suggestions_tab import create_suggestions_tab
+
+def build_ui():
+    with gr.Blocks(title="RetailGenie") as demo:
+        gr.Markdown("# 🧞‍♂ RetailGenie – In-Store Smart Assistant")
+        with gr.Tabs():
+            create_navigator_tab()
+            create_suggestions_tab()
+    return demo

ui/suggestions_tab.py

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+import gradio as gr
+from utils.suggest_utils import suggest_items
+
+def create_suggestions_tab():
+    with gr.TabItem("🎁 Smart Suggestions"):
+        gr.Markdown("### 🤖 Ask RetailGenie for Recommendations")
+        suggestion_input = gr.Textbox(label="Ask something like:", placeholder="Gift items under 500", lines=1)
+        suggest_btn = gr.Button("💡 Get Suggestions")
+        suggestions_output = gr.Textbox(label="📝 Suggestions", lines=10)
+
+        suggest_btn.click(
+            suggest_items,
+            inputs=suggestion_input,
+            outputs=suggestions_output
+        )

utils/data_utils.py

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+import pandas as pd
+import gradio as gr
+
+def get_quantities_from_csv(path):
+    try:
+        df = pd.read_csv(path)
+        if df.empty or "Quantity" not in df.columns:
+            return gr.update(choices=[], visible=False), {}
+        return gr.update(choices=df["Quantity"].dropna().tolist(), visible=True), df.to_dict()
+    except Exception as e:
+        print(f"❌ Error loading CSV: {e}")
+        return gr.update(choices=[], visible=False), {}
+
+def display_quantity_info(quantity, data_dict):
+    try:
+        df = pd.DataFrame(data_dict)
+        row = df[df["Quantity"] == quantity].iloc[0]
+        if str(row["In Stock"]).strip().lower() == "yes":
+            msg = (
+                f"✅ {quantity} is available!\n"
+                f"• Floor: {row['Floor']}\n"
+                f"• Aisle: {row['Aisle']}\n"
+                f"• Price: ₹{row['Price']}"
+            )
+            if "Offer" in row and pd.notna(row["Offer"]) and row["Offer"].strip():
+                msg += f"\n• 🎉 Offer: {row['Offer']}"
+            return msg
+        else:
+            return f"❌ Sorry, {quantity} is currently not in stock."
+    except Exception as e:
+        return f"⚠ Error: {e}"

utils/file_utils.py

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+import os
+
+def get_subfolders(path):
+    try:
+        return sorted([f for f in os.listdir(path) if os.path.isdir(os.path.join(path, f))])
+    except Exception as e:
+        print(f"❌ Error reading subfolders from {path}: {e}")
+        return []
+
+def get_csv_files(path):
+    try:
+        return sorted([f[:-4] for f in os.listdir(path) if f.endswith(".csv")])
+    except Exception as e:
+        print(f"❌ Error reading CSVs from {path}: {e}")
+        return []

utils/suggest_utils.py

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+def suggest_items(query):
+    query = query.lower()
+    if "gift" in query and "500" in query:
+        return (
+            "🎁 Gift Suggestions under ₹500:\n"
+            "1. Bath & Body Gift Set - ₹499\n"
+            "2. Mini Perfume Pack - ₹349\n"
+            "3. Skin Care Hamper - ₹399\n"
+            "4. Chocolates Gift Box - ₹299"
+        )
+    if "shampoo" in query and "dry" in query:
+        return (
+            "🧴 Shampoos for Dry Hair:\n"
+            "1. Dove 500 ml - ₹325\n"
+            "2. Clinic Plus 500 ml - ₹680"
+        )
+    return "🤷 Sorry, no smart suggestions found. Try asking: 'Gift items under 500' or 'Shampoo for dry hair'"