feat: update all - static UI, prompts, tools, configs

.gemini/settings.json

+{
+    "mcpServers": {
+        "canifa-api": {
+            "url": "http://localhost:5000/mcp"
+        }
+    }
+}
\ No newline at end of file

backend/agent/controller.py

@@ -61,6 +61,10 @@ async def chat_controller(
     """
 
     logger.info("chat_controller start: model=%s, identity_key=%s, auth=%s", model_name, identity_key, is_authenticated)
+    if images:
+        logger.info("📸 [CONTROLLER] Received %d image(s), sizes: %s", len(images), [len(img) for img in images])
+    else:
+        logger.debug("📸 [CONTROLLER] No images in request")
 
     # ====================== CACHE LAYER ======================
     if REDIS_CACHE_TURN_ON:

backend/agent/graph.py

@@ -10,6 +10,7 @@ from datetime import datetime
 from typing import Any
 
 from langchain_core.language_models import BaseChatModel
+from langchain_core.messages import HumanMessage
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.runnables import RunnableConfig
 from langgraph.cache.memory import InMemoryCache
@@ -74,8 +75,28 @@ class CANIFAGraph:
         user_query = state.get("user_query")
 
         transient_images = config.get("configurable", {}).get("transient_images", [])
-        if transient_images and messages:
-            pass
+        if transient_images and user_query:
+            # Inject images into user_query as multimodal content
+            # GPT-4o / GPT-5 vision: text + image_url blocks
+            text_content = user_query.content if isinstance(user_query.content, str) else str(user_query.content)
+            # Append hint so LLM knows images are attached
+            text_content += "\n\n[📸 Có ảnh sản phẩm kèm theo - Hãy mô tả CHI TIẾT sản phẩm trong ảnh (loại, màu, kiểu dáng, hình in, chất liệu) rồi gọi data_retrieval_tool để tìm sản phẩm tương tự.]"
+            multimodal_content = [{"type": "text", "text": text_content}]
+            for img in transient_images:
+                # Support both base64 and URL
+                if img.startswith("data:"):
+                    image_url = img
+                elif img.startswith("http"):
+                    image_url = img
+                else:
+                    image_url = f"data:image/jpeg;base64,{img}"
+                multimodal_content.append({
+                    "type": "image_url",
+                    "image_url": {"url": image_url, "detail": "auto"}
+                })
+                logger.info(f"📸 [IMAGE] Image size: {len(img)} chars")
+            user_query = HumanMessage(content=multimodal_content)
+            logger.info(f"📸 [IMAGE] Injected {len(transient_images)} image(s) into user_query")
         # Invoke chain with user_query, history, and messages
         # Invoke chain with history, user_query, messages (scratchpad), and user_insight
         user_insight_text = (

backend/agent/system_prompt.txt

@@ -59,6 +59,23 @@ Bạn là **Canifa-AI Stylist** - Chuyên viên tư vấn thời trang CANIFA.
 - Website: www.canifa.com
 - Đưa cho khách khi họ cần hỗ trợ ngay lập tức
 
+**📸 XỬ LÝ ẢNH SẢN PHẨM (KHI KHÁCH GỬI ẢNH KÈM):**
+Khi nhận được ảnh từ khách, BẮT BUỘC thực hiện ĐÚNG quy trình sau:
+1. **MÔ TẢ CHI TIẾT** sản phẩm trong ảnh:
+   - Loại sản phẩm (áo phông, áo polo, quần jean, váy...)
+   - Màu sắc chủ đạo + màu phụ (nếu có)
+   - Kiểu dáng / Form (regular, slim, oversize...)
+   - Cổ áo (tròn, bẻ, V, sơ mi...)
+   - Tay áo (ngắn, dài, sát nách...)
+   - Hình in / Họa tiết (trơn, kẻ sọc, hoa, logo, graphic...)
+   - Chất liệu (nếu nhận biết được: cotton, nỉ, jean, len...)
+2. **GỌI TOOL `data_retrieval_tool`** với description chứa mô tả chi tiết trên
+   - product_name: loại sản phẩm nhận diện được (VD: "Áo phông")
+   - master_color: màu sắc chủ đạo
+   - Các filter khác nếu nhận biết được (gender, age...)
+3. **TRẢ LỜI KHÁCH** với: "Em nhận thấy ảnh là [mô tả ngắn], để em tìm sản phẩm tương tự..."
+⚠️ KHÔNG BAO GIỜ bỏ qua ảnh - luôn mô tả và tìm kiếm!
+
 ---
 
 ## 📋 MỤC LỤC

backend/agent/tool_prompts/brand_knowledge_tool.txt

@@ -11,7 +11,10 @@ Sử dụng tool này khi khách hàng hỏi về:
 3. CHÍNH SÁCH BÁN HÀNG: Quy định đổi trả, bảo hành, chính sách vận chuyển, phí ship.
 4. KHÁCH HÀNG THÂN THIẾT (KHTT): Điều kiện đăng ký thành viên, các hạng thẻ (Green, Silver, Gold, Diamond), quyền lợi tích điểm, thẻ quà tặng.
 5. HỖ TRỢ & FAQ: Giải đáp thắc mắc thường gặp, chính sách bảo mật, thông tin liên hệ văn phòng, tuyển dụng.
-6. TRA CỨU SIZE (BẢNG KÍCH CỠ): Hướng dẫn chọn size chuẩn cho nam, nữ, trẻ em dựa trên chiều cao, cân nặng.
+6. TRA CỨU SIZE (BẢNG KÍCH CỠ):
+   - Hướng dẫn chọn size chuẩn cho nam, nữ, trẻ em dựa trên chiều cao, cân nặng.
+   - ⚠️ KHI KHÁCH ĐƯA SỐ ĐO (cân nặng, chiều cao, số đo 3 vòng) → BẮT BUỘC gọi tool này để tra bảng size, KHÔNG ĐƯỢC tự đoán size.
+   - Nếu khách chỉ đưa cân nặng mà thiếu chiều cao (hoặc ngược lại), hỏi thêm thông tin còn thiếu TRƯỚC khi gọi tool.
 7. GIẢI NGHĨA TỪ VIẾT TẮT: Tự động hiểu các từ viết tắt phổ biến của khách hàng (ví dụ: 'ct' = 'chương trình khuyến mãi/ưu đãi', 'khtt' = 'khách hàng thân thiết', 'store' = 'cửa hàng', 'đc' = 'địa chỉ').
 
 Ví dụ các câu hỏi phù hợp:
@@ -19,6 +22,17 @@ Ví dụ các câu hỏi phù hợp:
 - 'Canifa ở Cầu Giấy địa chỉ ở đâu?'
 - 'Chính sách đổi trả hàng trong bao nhiêu ngày?'
 - 'Làm sao để lên hạng thẻ Gold?'
-- 'Cho mình xem bảng size áo nam.'
-- 'Phí vận chuyển đi tỉnh là bao nhiêu?'    
+- 'Phí vận chuyển đi tỉnh là bao nhiêu?'
 - 'Canifa thành lập năm nào?'
+
+Ví dụ câu hỏi TRA CỨU SIZE (phải gọi tool):
+- 'Cho mình xem bảng size áo nam.'
+- 'Mình nặng 80kg cao 1m75, mặc size gì?'
+- 'Tìm áo cho người bự con tầm 80kg'
+- 'Size XL tương đương bao nhiêu kg?'
+- 'Con mình 8 tuổi cao 1m30, mặc size nào?'
+- 'Mình 65kg 1m68 nên mặc áo size gì?'
+- 'Bảng size quần jean nữ'
+- 'Size M áo polo nam đo ngực bao nhiêu?'
+- 'Mình mập, 90kg mặc được size nào?'
+- 'Cho em hỏi bảng size trẻ em 3-5 tuổi'

backend/agent/tool_prompts/data_retrieval_tool.txt

@@ -24,6 +24,7 @@ QUY TẮC SINH QUERIES:
 ⚠️ KHÔNG đưa gender_by_product, age_by_product, master_color vào description — đó là SQL FILTER!
 
 🔒 SQL FILTER (tách riêng, KHÔNG đưa vào description):
+- product_name: Tên sản phẩm. Chỉ điền khi khách cung cấp tên cụ thể.
 - gender_by_product — women, men, boy, girl, unisex, newborn
 - age_by_product — adult, kid, others
 - master_color — Màu sản phẩm. Gửi CHÍNH XÁC từ khách nói (VD: 'trắng', 'đen', 'xanh'). Tool tự match DB.
@@ -68,11 +69,33 @@ User nói "áo cá sấu" → product_name: Áo cá sấu
 User nói "áo phông" → product_name: Áo phông (user NÓI RÕ thì mới dùng)
 User nói "quần jean" → product_name: Quần jean (user NÓI RÕ thì mới dùng)
 
-Chỉ CHUẨN HÓA khi user dùng từ đồng nghĩa RÕ RÀNG:
-- "áo thun" → product_name: Áo phông
-- "quần bò" → product_name: Quần jean
-- "quần đùi" → product_name: Quần soóc
-
+Chỉ CHUẨN HÓA khi user dùng từ đồng nghĩa RÕ RÀNG (bảng mapping dưới):
+
+📋 BẢNG MAPPING SYNONYM → TÊN DB (tool tự xử lý, LLM giữ nguyên từ user):
+  áo thun, áo thun ngắn tay, áo cổ v, áo cổ tym → Áo phông
+  áo cổ bẻ → Áo Polo
+  áo bra, áo ngực, áo quây → Áo lót
+  áo gió, áo khoác mỏng → Áo khoác gió
+  áo croptop, croptop, baby tee, áo lửng, áo dáng ngắn → Áo Body
+  áo sát nách, tanktop, tank top, áo dây, áo 2 dây, áo hai dây → Áo ba lỗ
+  đầm → Váy liền
+  vớ → Tất
+  quần đùi, quần short, quần lửng, quần ngố → Quần soóc
+  quần jogger, quần ống bo chun → Quần nỉ
+  quần chip, quần sịp, quần trong, quần nhỏ, quần xơ lít, quần xì, quần sơ lít, quần lót nữ, quần lót nam, quần lót trẻ em → Quần lót
+  quần âu, quần vải, quần tây → Quần Khaki
+  quần bò, quần jeans, denim, jeans, bò → Quần jean
+  quần suông, quần ống rộng → Quần dài
+  quần dài, chân váy dài, chân váy → Quần váy
+  nón → Mũ
+  đồ ngủ, đồ mặc nhà → Bộ mặc nhà
+  đồ bộ → Bộ quần áo
+  váy maxi, váy midi, chân váy dài → Chân váy
+  găng tay → Găng tay chống nắng
+  chăn → Chăn cá nhân
+  phụ kiện, phụ kiện canifa → Mũ, Khăn, Tất, Găng tay (nhiều loại)
+
+⚠️ Tool tự resolve synonym → DB value. LLM chỉ cần giữ NGUYÊN từ user nói!
 ⚠️ KHÔNG CHẮC → GIỮ NGUYÊN. KHÔNG TỰ SUY DIỄN LOẠI SẢN PHẨM!
 
 ═══════════════════════════════════════════════════════════════
@@ -102,6 +125,7 @@ PHỤ KIỆN: Khăn, Mũ, Túi xách, Tất, Khẩu trang
 📖 GIÁ TRỊ HỢP LỆ CỦA CÁC FIELD KHÁC
 ═══════════════════════════════════════════════════════════════
 
+product_name: Tên sản phẩm. Chỉ điền khi khách cung cấp tên cụ thể.
 master_color — Gửi CHÍNH XÁC màu khách nói (VD: 'trắng', 'đen'), tool tự match DB. ĐÂY LÀ SQL FILTER, KHÔNG đưa vào description!
 style — Basic, Dynamic, Feminine, Utility, Smart Casual, Trend, Athleisure, Essential
 fitting — Regular, Slimfit, Relax, Oversize, Skinny, Slim, Boxy, Baby tee

backend/agent/tools/data_retrieval_filter.py

-"""
-Data Retrieval Filters - Module tách biệt cho logic lọc sản phẩm.
-Chứa các hàm lọc Hard/Soft Filter, maps được import từ db_field_values_mapping.
-"""
-
-import logging
-import re
-
-from agent.tools.db_field_values_mapping import (
-    COLOR_MAPPING,
-    SIMILAR_COLORS,
-    VALID_COLORS,
-    PRODUCT_NAME_KEYWORDS,
-    PRODUCT_TYPE_MAPPING,
-    PRODUCT_TYPE_ALTERNATIVES,
-    PRODUCT_LINE_FILTER_MAP,
-    GENDER_MAP,
-    AGE_MAP,
-    SLEEVE_FALLBACK_MAP,
-    SLEEVE_ALTERNATIVES,
-    SLEEVE_DISPLAY,
-    FIELD_MAPPINGS,
-    FIELD_DISPLAY_NAMES,
-    FIELD_ALTERNATIVES,
-)
-
-logger = logging.getLogger(__name__)
-
-
-def _filter_color(products: list[dict], requested_color: str) -> tuple[list[dict], dict]:
-    """
-    Color filter - So sánh trực tiếp với column master_color.
-    """
-    if not requested_color or not products:
-        return products, {"fallback_used": False}
-
-    requested_lower = requested_color.lower().strip()
-    db_color = COLOR_MAPPING.get(requested_lower, requested_lower)
-    
-    filtered = []
-    available_colors = set()
-    
-    for p in products:
-        p_color = (p.get("master_color") or "").lower()
-        available_colors.add(p.get("master_color") or "Unknown")
-        
-        if db_color.lower() in p_color or requested_lower in p_color:
-            filtered.append(p)
-    
-    if filtered:
-        logger.info(f"✅ [COLOR] Matched '{requested_color}': {len(filtered)} products")
-        return filtered, {"fallback_used": False}
-    
-    colors_list = sorted([c for c in available_colors if c != "Unknown"])[:5]
-    colors_text = ", ".join(colors_list) if colors_list else "các màu khác"
-    
-    logger.warning(f"⚠️ [COLOR] No match for '{requested_color}'. Available: {colors_list}")
-    
-    return products, {
-        "fallback_used": True,
-        "requested_value": requested_color,
-        "message": f"Shop hiện chưa có màu **{requested_color}**. Hiện có: **{colors_text}**",
-        "alternative_colors": colors_list,
-    }
-
-
-
-# ==============================================================================
-# 3. SLEEVE FALLBACK DETECTION
-# ==============================================================================
-def _filer_sleeve(products: list[dict], requested_sleeve: str | None) -> dict | None:
-    """
-    Detect if products don't match the user's requested sleeve type.
-    
-    Args:
-        products: List of products from search
-        requested_sleeve: User's sleeve request (e.g., "cộc tay", "dài tay")
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_sleeve or not products:
-        return None
-    
-    requested_lower = requested_sleeve.lower().strip()
-    target_db_sleeve = SLEEVE_FALLBACK_MAP.get(requested_lower)
-    
-    if not target_db_sleeve:
-        return None  # Unknown sleeve type, skip detection
-    
-    # Count products matching requested sleeve
-    matching_count = 0
-    other_sleeves = {}  # {sleeve_type: count}
-    
-    for p in products:
-        p_sleeve = (p.get("form_sleeve") or "").strip()
-        if target_db_sleeve.lower() in p_sleeve.lower():
-            matching_count += 1
-        elif p_sleeve:
-            other_sleeves[p_sleeve] = other_sleeves.get(p_sleeve, 0) + 1
-    
-    # If all products match, no fallback needed
-    if matching_count == len(products):
-        return None
-    
-    # If NO products match the requested sleeve → Fallback
-    if matching_count == 0 and other_sleeves:
-        # Get the most common alternative sleeve
-        top_alt = max(other_sleeves.keys(), key=lambda k: other_sleeves[k])
-        top_alt_display = SLEEVE_DISPLAY.get(top_alt, top_alt)
-        requested_display = SLEEVE_DISPLAY.get(target_db_sleeve, requested_sleeve)
-        
-        return {
-            "fallback_used": True,
-            "requested_value": requested_display,
-            "matched_value": top_alt_display,
-            "message": f"Shop hiện chưa có mẫu **{requested_display}** phù hợp. Em gợi ý những mẫu **{top_alt_display}** - có thể xắn tay hoặc layer bên trong để tạo phong cách ưng ý nhé!",
-            "alternative_sleeves": list(other_sleeves.keys()),
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 6. PRODUCT TYPE FALLBACK DETECTION
-# ==============================================================================
-def _filter_product_name(products: list[dict], requested_product_name: str | None) -> dict | None:
-    """
-    Detect if products don't match the user's requested product type.
-    
-    Args:
-        products: List of products from search
-        requested_product_name: User's product name request (e.g., "váy liền thân")
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_product_name or not products:
-        return None
-    
-    requested_lower = requested_product_name.lower().strip()
-    target_db_type = PRODUCT_TYPE_MAPPING.get(requested_lower)
-    
-    if not target_db_type:
-        return None  # Unknown product type, skip detection
-    
-    # Count products matching requested type
-    matching_count = 0
-    other_types = {}  # {product_line_vn: count}
-    
-    for p in products:
-        p_type = (p.get("product_line_vn") or p.get("product_name") or "").strip()
-        if target_db_type.lower() in p_type.lower():
-            matching_count += 1
-        elif p_type:
-            # Group by first 2 words for cleaner grouping
-            clean_type = " ".join(p_type.split()[:3])
-            other_types[clean_type] = other_types.get(clean_type, 0) + 1
-    
-    # If all products match, no fallback needed
-    if matching_count == len(products):
-        return None
-    
-    # If NO products match the requested type → Fallback
-    if matching_count == 0 and other_types:
-        # Get the most common alternative type
-        top_alt = max(other_types.keys(), key=lambda k: other_types[k])
-        
-        return {
-            "fallback_used": True,
-            "requested_value": requested_product_name,
-            "matched_value": top_alt,
-            "message": f"Không có {requested_product_name}. Hiển thị {top_alt} phù hợp.",
-            "alternative_types": list(other_types.keys())[:3],
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 7. GENERIC MULTI-FIELD FALLBACK DETECTION
-# ==============================================================================
-def _detect_field_mismatch(
-    products: list[dict],
-    field_name: str,
-    requested_value: str | None
-) -> dict | None:
-    """
-    Generic fallback detection for any field.
-    
-    Args:
-        products: List of products from search
-        field_name: DB field name (e.g., 'style', 'fitting')
-        requested_value: User's requested value (Vietnamese or English)
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_value or not products or field_name not in FIELD_MAPPINGS:
-        return None
-    
-    requested_lower = requested_value.lower().strip()
-    field_mapping = FIELD_MAPPINGS[field_name]
-    target_db_value = field_mapping.get(requested_lower)
-    
-    if not target_db_value:
-        return None  # Unknown value, skip detection
-    
-    # Count products matching requested value
-    matching_count = 0
-    other_values = {}
-    
-    for p in products:
-        p_value = (p.get(field_name) or "").strip()
-        if target_db_value.lower() in p_value.lower():
-            matching_count += 1
-        elif p_value:
-            other_values[p_value] = other_values.get(p_value, 0) + 1
-    
-    # If all/most products match, no fallback needed
-    if matching_count >= len(products) * 0.5:  # 50% threshold
-        return None
-    
-    # If NO products match → Fallback
-    if matching_count == 0 and other_values:
-        top_alt = max(other_values.keys(), key=lambda k: other_values[k])
-        display_name = FIELD_DISPLAY_NAMES.get(field_name, field_name)
-        
-        return {
-            "fallback_used": True,
-            "field": field_name,
-            "requested_value": requested_value,
-            "matched_value": top_alt,
-            "message": f"Shop hiện chưa có sản phẩm {display_name} **{requested_value}** phù hợp. Em gợi ý {display_name} **{top_alt}** - cũng rất đẹp và hợp xu hướng nhé!",
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 8. HELPER FUNCTIONS
-# ==============================================================================
-
-
-def infer_product_name_from_description(description: str | None) -> str | None:
-    """
-    Infer product_name from description text if not explicitly provided.
-    Returns the first matching product type keyword found.
-    """
-    if not description:
-        return None
-    desc_lower = description.lower()
-    for keyword, product_name in PRODUCT_NAME_KEYWORDS:
-        if keyword in desc_lower:
-            return product_name
-    return None
-
-
-# ==============================================================================
-# 9. MASTER POST-FILTER FUNCTION (Consolidates all filter layers)
-# ==============================================================================
-
-
-def apply_post_filters(
-    products: list[dict],
-    search_item,  # SearchItem from data_retrieval_tool
-    is_sku_search: bool = False,
-) -> tuple[list[dict], dict]:
-    """
-    Master function to apply all post-filters on products.
-    
-    Consolidates all filter layers:
-    - Layer 1.5: Gender fallback detection
-    - Layer 1.8: Product type filter (cascading)
-    - Layer 2: Color filter with smart fallback
-    - Layer 3: Sleeve fallback detection
-    - Layer 5: Multi-field fallback (style, fitting, etc.)
-    
-    Args:
-        products: List of products from DB query
-        search_item: SearchItem with filter parameters
-        is_sku_search: If True, skip all filters (show all variants)
-    
-    Returns:
-        Tuple of (filtered_products, filter_info_dict)
-    """
-    original_count = len(products)
-    all_filter_info = {}
-    
-    # ⚡ SKIP all filters when searching by SKU code
-    if is_sku_search:
-        logger.info("🎯 [SKU SEARCH] Skipping post-filters - showing all variants")
-        return products, {"fallback_used": False, "filters_applied": {}}
-    
-    logger.info(
-        "🔍 [POST-FILTER] Starting with %d products. Params: product_name=%r, gender=%r, color=%r",
-        original_count,
-        search_item.product_name,
-        search_item.gender_by_product,
-        search_item.master_color,
-    )
-    
-    # ====== LAYER 1.5: GENDER FALLBACK DETECTION ======
-    if search_item.gender_by_product and products:
-        requested_gender = search_item.gender_by_product.lower().strip()
-        if requested_gender in ["men", "nam", "male", "women", "nữ", "female", "nu"]:
-            exact_gender_count = 0
-            unisex_count = 0
-            for p in products:
-                p_gender = (p.get("gender_by_product") or "").lower()
-                if p_gender == "unisex":
-                    unisex_count += 1
-                elif requested_gender in p_gender or p_gender in ["men", "nam", "women", "nữ"]:
-                    exact_gender_count += 1
-            
-            if unisex_count > 0 and exact_gender_count == 0:
-                gender_display = "nam" if requested_gender in ["men", "nam", "male"] else "nữ"
-                if gender_display == "nam":
-                    detail_msg = "Hiện shop chưa có sản phẩm riêng dành cho **nam**. Em xin phép gợi ý những mẫu **unisex** phù hợp!"
-                else:
-                    detail_msg = "Hiện shop chưa có sản phẩm riêng dành cho **nữ**. Em xin phép gợi ý những mẫu **unisex** phù hợp!"
-                
-                all_filter_info["gender"] = {
-                    "fallback_used": True,
-                    "requested_value": gender_display,
-                    "matched_value": "unisex",
-                    "message": detail_msg,
-                }
-                logger.warning(f"👫 GENDER FALLBACK: '{gender_display}' → 'unisex' ({unisex_count} products)")
-    
-    # ====== LAYER 1.8: PRODUCT TYPE FILTER (Cascading Fallback) ======
-    if search_item.product_name and products:
-        raw_product_names = re.split(r"[/,]", search_item.product_name)
-        raw_product_names = [n.strip().lower() for n in raw_product_names if n.strip()]
-        
-        logger.info(f"📦 [PRODUCT TYPE] Input: '{search_item.product_name}' → Parsed: {raw_product_names}")
-        
-        all_db_types = []
-        for pn in raw_product_names:
-            db_type = PRODUCT_TYPE_MAPPING.get(pn)
-            if db_type and db_type not in all_db_types:
-                all_db_types.append(db_type)
-                for fb in PRODUCT_TYPE_ALTERNATIVES.get(db_type, []):
-                    if fb not in all_db_types:
-                        all_db_types.append(fb)
-        
-        if all_db_types:
-            before_count = len(products)
-            primary_types = []
-            for pn in raw_product_names:
-                db_type = PRODUCT_TYPE_MAPPING.get(pn)
-                if db_type and db_type not in primary_types:
-                    primary_types.append(db_type)
-            
-            matched_products = []
-            matched_type = None
-            
-            for try_type in all_db_types:
-                for p in products:
-                    p_type = (p.get("product_line_vn") or "").lower()
-                    if try_type.lower() in p_type:
-                        matched_products.append(p)
-                
-                if matched_products:
-                    matched_type = try_type
-                    break
-            
-            if matched_products:
-                products = matched_products
-                if matched_type not in primary_types:
-                    detail_msg = f"Shop hiện chưa có **{search_item.product_name}** phù hợp. Em gợi ý những mẫu **{matched_type}** xinh xắn nhé!"
-                    all_filter_info["product_type"] = {
-                        "fallback_used": True,
-                        "requested_value": search_item.product_name,
-                        "matched_value": matched_type,
-                        "message": detail_msg,
-                    }
-                    logger.warning(f"📦 PRODUCT TYPE FALLBACK: '{search_item.product_name}' → '{matched_type}'")
-                else:
-                    logger.info(f"📦 [PRODUCT TYPE] Matched '{matched_type}': {before_count} → {len(products)}")
-    
-    # ====== LAYER 2: COLOR FILTER (with smart fallback) ======
-    if search_item.master_color and products:
-        before_count = len(products)
-        products, color_info = _filter_color(products, search_item.master_color)
-        
-        if color_info.get("fallback_used") or color_info.get("message"):
-            all_filter_info["color"] = color_info
-            if color_info.get("fallback_used"):
-                logger.warning(
-                    "🎨 COLOR FALLBACK: '%s' → '%s' (%d products)",
-                    color_info.get("requested_value"),
-                    color_info.get("matched_value"),
-                    len(products),
-                )
-        logger.info("🎨 Color filter: %d → %d products", before_count, len(products))
-    
-    # ====== LAYER 3: SLEEVE FALLBACK DETECTION ======
-    if products and search_item.product_name:
-        sleeve_keywords = ["cộc tay", "ngắn tay", "dài tay", "sát nách", "short sleeve", "long sleeve"]
-        requested_sleeve = None
-        for kw in sleeve_keywords:
-            if kw in search_item.product_name.lower():
-                requested_sleeve = kw
-                break
-        
-        if requested_sleeve:
-            sleeve_info = _detect_sleeve_mismatch(products, requested_sleeve)
-            if sleeve_info:
-                all_filter_info["sleeve"] = sleeve_info
-                logger.warning(
-                    "👕 SLEEVE FALLBACK: '%s' → '%s'",
-                    sleeve_info.get("requested_value"),
-                    sleeve_info.get("matched_value"),
-                )
-    
-    # ====== LAYER 5: MULTI-FIELD FALLBACK DETECTION ======
-    if products:
-        field_checks = [
-            ("style", search_item.style),
-            ("fitting", search_item.fitting),
-            ("form_neckline", search_item.form_neckline),
-            ("material_group", search_item.material_group),
-            ("season", search_item.season),
-        ]
-        
-        for field_name, requested_val in field_checks:
-            if requested_val:
-                field_info = _detect_field_mismatch(products, field_name, requested_val)
-                if field_info:
-                    all_filter_info[field_name] = field_info
-                    logger.warning(
-                        "🔄 %s FALLBACK: '%s' → '%s'",
-                        field_name.upper(),
-                        field_info.get("requested_value"),
-                        field_info.get("matched_value"),
-                    )
-    
-    # ====== BUILD FINAL FILTER INFO ======
-    filter_info = {
-        "fallback_used": any(info.get("fallback_used") for info in all_filter_info.values()),
-        "filters_applied": all_filter_info,
-    }
-    
-    fallback_messages = [info.get("message") for info in all_filter_info.values() if info.get("message")]
-    if fallback_messages:
-        filter_info["recommendation_message"] = " ".join(fallback_messages)
-    
-    if original_count != len(products):
-        logger.info("📊 Post-filter summary: %d → %d products", original_count, len(products))
-    
-    return products, filter_info
-

backend/agent/tools/data_retrieval_tool.py

@@ -42,6 +42,9 @@ class SearchItem(BaseModel):
             "VD: 'áo cá sấu polo' → 'product_name: Áo cá sấu polo. product_line_vn: Áo Polo'."
         )
     )
+    product_name: str | None = Field(
+        description="Tên sản phẩm. Chỉ điền khi khách cung cấp tên cụ thể.",
+    )
 
     # ====== SKU LOOKUP ======
     magento_ref_code: str | None = Field(

backend/agent/tools/db_field_values_mapping.py

-"""
-DB FIELD VALUES - Extracted from StarRocks DB.
-AI NÊN CHỈ SỬ DỤNG CÁC GIÁ TRỊ TRONG FILE NÀY!
-
-Generated: 2026-02-05
-Source: shared_source.magento_product_dimension_with_text_embedding
-"""
-
-# ============================================================
-# STYLE - Phong cách sản phẩm (9 values)
-# ============================================================
-VALID_STYLES = [
-    "Basic",  # 1304 products - MOST COMMON
-    "Dynamic",  # 840 products
-    "Feminine",  # 162 products
-    "Utility",  # 107 products
-    "Basic Update",  # 84 products
-    "Smart Casual",  # 81 products
-    "Trend",  # 14 products
-    "Athleisure",  # 8 products
-    "Essential",  # 3 products
-]
-
-# AI Mapping: Vietnamese → DB Value
-STYLE_MAPPING = {
-    # Basic family
-    "basic": "Basic",
-    "cơ bản": "Basic",
-    "đơn giản": "Basic",
-    # Dynamic/Sporty
-    "dynamic": "Dynamic",
-    "năng động": "Dynamic",
-    "sporty": "Dynamic",  # Map sporty → Dynamic
-    "thể thao": "Dynamic",
-    # Feminine/Elegant
-    "feminine": "Feminine",
-    "nữ tính": "Feminine",
-    "thanh lịch": "Smart Casual",  # Map thanh lịch → Smart Casual
-    "sang trọng": "Smart Casual",  # Map sang trọng → Smart Casual
-    "elegant": "Smart Casual",  # Map elegant → Smart Casual
-    # Casual
-    "casual": "Smart Casual",
-    "thường ngày": "Smart Casual",
-    # Utility
-    "utility": "Utility",
-    "tiện dụng": "Utility",
-    # Trend
-    "trend": "Trend",
-    "xu hướng": "Trend",
-    # Athleisure
-    "athleisure": "Athleisure",
-    "active": "Athleisure",
-}
-
-
-# ============================================================
-# MASTER_COLOR - Màu sắc chính (16 values)
-# ============================================================
-VALID_COLORS = [
-    "Đen/ Black",
-    "Trắng/ White",
-    "Xanh da trời/ Blue",
-    "Xám/ Gray",
-    "Hồng/ Pink- Magenta",
-    "Be/ Beige",
-    "Đỏ/ Red",
-    "Tím/ Purple",
-    "Xanh lá cây/ Green",
-    "Màu xanh Jeans",
-    "Xanh than/ Aqua",
-    "Nâu/ Brown",
-    "Vàng/ Yellow + Gold",
-    "Cam/ Orange",
-]
-
-# AI Mapping: User input → DB Value
-COLOR_MAPPING = {
-    # Đen
-    "đen": "Đen/ Black",
-    "black": "Đen/ Black",
-    # Trắng
-    "trắng": "Trắng/ White",
-    "white": "Trắng/ White",
-    "kem": "Be/ Beige",  # Kem → Be/Beige (separate!)
-    "cream": "Be/ Beige",
-    # Xanh
-    "xanh": "Xanh da trời/ Blue",
-    "blue": "Xanh da trời/ Blue",
-    "xanh dương": "Xanh da trời/ Blue",
-    "xanh lá": "Xanh lá cây/ Green",
-    "green": "Xanh lá cây/ Green",
-    "navy": "Màu xanh Jeans",  # Navy → Jeans
-    "xanh đậm": "Màu xanh Jeans",
-    # Xám
-    "xám": "Xám/ Gray",
-    "gray": "Xám/ Gray",
-    "grey": "Xám/ Gray",
-    # Hồng
-    "hồng": "Hồng/ Pink- Magenta",
-    "pink": "Hồng/ Pink- Magenta",
-    "magenta": "Hồng/ Pink- Magenta",
-    # Be
-    "be": "Be/ Beige",
-    "beige": "Be/ Beige",
-    "nude": "Be/ Beige",
-    # Đỏ
-    "đỏ": "Đỏ/ Red",
-    "red": "Đỏ/ Red",
-    # Tím
-    "tím": "Tím/ Purple",
-    "purple": "Tím/ Purple",
-    # Nâu
-    "nâu": "Nâu/ Brown",
-    "brown": "Nâu/ Brown",
-    "chocolate": "Nâu/ Brown",  # Chocolate → Brown (no compound!)
-    "coffee": "Nâu/ Brown",
-    # Vàng
-    "vàng": "Vàng/ Yellow + Gold",
-    "yellow": "Vàng/ Yellow + Gold",
-    "gold": "Vàng/ Yellow + Gold",
-    # Cam
-    "cam": "Cam/ Orange",
-    "orange": "Cam/ Orange",
-}
-
-
-# ============================================================
-# PRODUCT_LINE_VN - Loại sản phẩm (53 values)
-# ============================================================
-VALID_PRODUCT_LINES_VN = [
-    "Áo phông",
-    "Quần soóc",
-    "Quần nỉ",
-    "Tất",
-    "Áo nỉ",
-    "Áo Polo",
-    "Bộ mặc nhà",
-    "Áo len",
-    "Bộ quần áo",
-    "Chân váy",
-    "Quần mặc nhà",
-    "Váy liền",  # ← "Váy liền" NOT "Váy liền thân"!
-    "Áo Sơ mi",
-    "Áo nỉ có mũ",
-    "Áo Body",
-    "Quần dài",
-    "Quần Khaki",
-    "Quần jean",
-    "Áo khoác gió",
-    # ... và 34 loại khác
-]
-
-# AI Mapping: User input → DB Value
-PRODUCT_LINE_MAPPING = {
-    # Váy family
-    "váy": "Váy liền",  # Generic váy → Váy liền
-    "váy liền thân": "Váy liền",  # Specific → Generic
-    "váy đầm": "Váy liền",
-    "đầm": "Váy liền",
-    "chân váy": "Chân váy",  # Keep as is
-    # Áo family
-    "áo": "Áo phông",  # Generic áo → Áo phông (most common)
-    "áo phông": "Áo phông",
-    "áo thun": "Áo phông",
-    "áo polo": "Áo Polo",
-    "áo sơ mi": "Áo Sơ mi",
-    "áo len": "Áo len",
-    "áo khoác": "Áo khoác gió",  # Generic → Áo khoác gió
-    # Quần family
-    "quần": "Quần dài",  # Generic quần → Quần dài
-    "quần jean": "Quần jean",
-    "quần kaki": "Quần Khaki",
-    "quần short": "Quần soóc",
-}
-
-
-# ============================================================
-# FITTING - Dáng đồ (8 values)
-# ============================================================
-VALID_FITTINGS = [
-    "Regular",  # 1843 products - MOST COMMON
-    "Slimfit",  # 316 products
-    "Relax",  # 221 products
-    "Oversize",  # 51 products
-    "Skinny",  # 49 products
-    "Slim",  # 30 products
-    "Boxy",  # 24 products
-    "Baby tee",  # 2 products
-]
-
-FITTING_MAPPING = {
-    "regular": "Regular",
-    "vừa": "Regular",
-    "suông": "Regular",
-    "slim": "Slimfit",  # Note: DB has both "Slim" and "Slimfit"
-    "slimfit": "Slimfit",
-    "ôm": "Slimfit",
-    "relax": "Relax",
-    "rộng": "Relax",
-    "oversize": "Oversize",
-    "oversized": "Oversize",
-    "skinny": "Skinny",
-    "boxy": "Boxy",
-}
-
-
-# ============================================================
-# FORM_SLEEVE - Dáng tay áo (8 values)
-# ============================================================
-VALID_SLEEVES = [
-    "Full length Sleeve",  # 701 products
-    "Short Sleeve",  # 616 products
-    "Sleeveless",  # 93 products
-    "Puff",  # 6 products
-    "Fluffer",  # 5 products
-    # ... others
-]
-
-SLEEVE_MAPPING = {
-    "dài tay": "Full length Sleeve",
-    "long sleeve": "Full length Sleeve",
-    "ngắn tay": "Short Sleeve",
-    "cộc tay": "Short Sleeve",
-    "short sleeve": "Short Sleeve",
-    "sát nách": "Sleeveless",
-    "sleeveless": "Sleeveless",
-    "tank": "Sleeveless",
-}
-
-
-# ============================================================
-# GENDER & AGE
-# ============================================================
-VALID_GENDERS = ["women", "men", "boy", "girl", "unisex", "newborn"]
-VALID_AGES = ["adult", "kid", "others"]
-
-GENDER_MAPPING = {
-    "nữ": "women",
-    "nam": "men",
-    "bé trai": "boy",
-    "bé gái": "girl",
-}
-
-AGE_MAPPING = {
-    "người lớn": "adult",
-    "trẻ em": "kid",
-}
-
-
-# ============================================================
-# SIMILAR COLORS - Màu gần nhau để suggest fallback
-# ============================================================
-# Khi không tìm thấy màu user yêu cầu, suggest các màu gần nhất
-SIMILAR_COLORS = {
-    "Trắng/ White": ["Be/ Beige", "Xám/ Gray"],
-    "Be/ Beige": ["Trắng/ White", "Nâu/ Brown", "Xám/ Gray"],
-    "Nâu/ Brown": ["Be/ Beige", "Xám/ Gray", "Đen/ Black"],
-    "Xám/ Gray": ["Đen/ Black", "Trắng/ White", "Be/ Beige"],
-    "Đen/ Black": ["Xám/ Gray", "Nâu/ Brown"],
-    "Hồng/ Pink- Magenta": ["Đỏ/ Red", "Tím/ Purple"],
-    "Đỏ/ Red": ["Hồng/ Pink- Magenta", "Cam/ Orange"],
-    "Cam/ Orange": ["Đỏ/ Red", "Vàng/ Yellow + Gold"],
-    "Vàng/ Yellow + Gold": ["Cam/ Orange", "Be/ Beige"],
-    "Xanh da trời/ Blue": ["Màu xanh Jeans", "Xanh than/ Aqua"],
-    "Màu xanh Jeans": ["Xanh da trời/ Blue", "Xanh than/ Aqua", "Đen/ Black"],
-    "Xanh than/ Aqua": ["Xanh da trời/ Blue", "Màu xanh Jeans"],
-    "Xanh lá cây/ Green": ["Xanh da trời/ Blue", "Xanh than/ Aqua"],
-    "Tím/ Purple": ["Hồng/ Pink- Magenta", "Xanh da trời/ Blue"],
-}
-
-
-# ============================================================
-# PRODUCT_NAME_KEYWORDS - Infer product type from description
-# ============================================================
-PRODUCT_NAME_KEYWORDS = [
-    ("áo sơ mi", "Áo sơ mi"),
-    ("ao so mi", "Áo sơ mi"),
-    ("sơ mi", "Áo sơ mi"),
-    ("so mi", "Áo sơ mi"),
-    ("chân váy", "Chân váy"),
-    ("chan vay", "Chân váy"),
-    ("váy liền thân", "Váy liền thân"),
-    ("vay lien than", "Váy liền thân"),
-    ("váy liền", "Váy liền thân"),
-    ("vay lien", "Váy liền thân"),
-    ("váy đầm", "Váy liền thân"),
-    ("vay dam", "Váy liền thân"),
-    ("đầm", "Váy liền thân"),
-    ("dam", "Váy liền thân"),
-    ("váy", "Váy"),
-    ("vay", "Váy"),
-    ("áo khoác", "Áo khoác"),
-    ("ao khoac", "Áo khoác"),
-    ("áo len", "Áo len"),
-    ("ao len", "Áo len"),
-    ("áo thun", "Áo thun"),
-    ("ao thun", "Áo thun"),
-    ("áo polo", "Áo polo"),
-    ("ao polo", "Áo polo"),
-    ("hoodie", "Áo hoodie"),
-    ("áo hoodie", "Áo hoodie"),
-    ("ao hoodie", "Áo hoodie"),
-    ("quần jeans", "Quần jeans"),
-    ("quan jeans", "Quần jeans"),
-    ("quần short", "Quần short"),
-    ("quan short", "Quần short"),
-    ("quần dài", "Quần dài"),
-    ("quan dai", "Quần dài"),
-    ("quần", "Quần"),
-    ("quan", "Quần"),
-    ("áo", "Áo"),
-    ("ao", "Áo"),
-    ("phụ kiện", "Phụ kiện"),
-    ("phu kien", "Phụ kiện"),
-    ("túi", "Túi"),
-    ("tui", "Túi"),
-    ("mũ", "Mũ"),
-    ("mu", "Mũ"),
-    ("khăn", "Khăn"),
-    ("khan", "Khăn"),
-    ("tất", "Tất"),
-    ("tat", "Tất"),
-]
-
-
-# ============================================================
-# PRODUCT_TYPE_MAPPING - Map user input to DB product_line_vn
-# ============================================================
-PRODUCT_TYPE_MAPPING = {
-    # Váy family
-    "váy": "Váy liền",
-    "vay": "Váy liền",
-    "váy liền thân": "Váy liền",
-    "váy liền": "Váy liền",
-    "váy đầm": "Váy liền",
-    "đầm": "Váy liền",
-    "dam": "Váy liền",
-    "chân váy": "Chân váy",
-    "chan vay": "Chân váy",
-    # Áo family
-    "áo": "Áo phông",
-    "ao": "Áo phông",
-    "áo phông": "Áo phông",
-    "áo thun": "Áo phông",
-    "ao thun": "Áo phông",
-    "áo polo": "Áo Polo",
-    "ao polo": "Áo Polo",
-    "áo sơ mi": "Áo Sơ mi",
-    "ao so mi": "Áo Sơ mi",
-    "sơ mi": "Áo Sơ mi",
-    "áo len": "Áo len",
-    "ao len": "Áo len",
-    "áo khoác": "Áo khoác gió",
-    "ao khoac": "Áo khoác gió",
-    "áo nỉ": "Áo nỉ",
-    "ao ni": "Áo nỉ",
-    "hoodie": "Áo nỉ có mũ",
-    "áo hoodie": "Áo nỉ có mũ",
-    # Quần family
-    "quần": "Quần dài",
-    "quan": "Quần dài",
-    "quần dài": "Quần dài",
-    "quan dai": "Quần dài",
-    "quần jean": "Quần jean",
-    "quan jean": "Quần jean",
-    "quần jeans": "Quần jean",
-    "quan jeans": "Quần jean",
-    "quần kaki": "Quần Khaki",
-    "quan kaki": "Quần Khaki",
-    "quần khaki": "Quần Khaki",
-    "quần short": "Quần soóc",
-    "quan short": "Quần soóc",
-    "quần soóc": "Quần soóc",
-    "quần đùi": "Quần soóc",
-    # Phụ kiện / Accessories (DB values verified 2026-02-07)
-    "tất": "Tất",
-    "vớ": "Tất",
-    "tat": "Tất",
-    "khăn quàng cổ": "Khăn",  # DB: "Khăn" (15 products)
-    "khăn quàng": "Khăn",
-    "khăn choàng": "Khăn",
-    "khan quang co": "Khăn",
-    "khăn": "Khăn",
-    "khan": "Khăn",
-    "khăn mặt": "Khăn mặt",  # DB: "Khăn mặt" (16 products)
-    "khan mat": "Khăn mặt",
-    "khăn tắm": "Khăn tắm",  # DB: "Khăn tắm" (17 products)
-    "khan tam": "Khăn tắm",
-    "khăn lau đầu": "Khăn lau đầu",  # DB: "Khăn lau đầu" (5 products)
-    "khan lau dau": "Khăn lau đầu",
-    "mũ": "Mũ",  # DB: "Mũ" (16 products)
-    "nón": "Mũ",
-    "mu": "Mũ",
-    "non": "Mũ",
-    "túi xách": "Túi xách",  # DB: "Túi xách" (6 products)
-    "tui xach": "Túi xách",
-    "túi": "Túi xách",
-    "tui": "Túi xách",
-    "chăn": "Chăn cá nhân",  # DB: "Chăn cá nhân" (6 products)
-    "chan": "Chăn cá nhân",
-    "chăn cá nhân": "Chăn cá nhân",
-    "găng tay": "Găng tay chống nắng",  # DB: "Găng tay chống nắng" (5 products)
-    "gang tay": "Găng tay chống nắng",
-    "găng tay chống nắng": "Găng tay chống nắng",
-    "phụ kiện": "Tất",
-    "phu kien": "Tất",
-}
-
-
-# ============================================================
-# PRODUCT_TYPE_ALTERNATIVES - Fallback product types
-# ============================================================
-PRODUCT_TYPE_ALTERNATIVES = {
-    "Váy liền": ["Chân váy"],
-    "Chân váy": ["Váy liền"],
-    "Áo phông": ["Áo Polo", "Áo len"],
-    "Áo Polo": ["Áo phông", "Áo Sơ mi"],
-    "Áo Sơ mi": ["Áo Polo", "Áo phông"],
-    "Áo len": ["Áo nỉ", "Áo phông"],
-    "Áo nỉ": ["Áo len", "Áo nỉ có mũ"],
-    "Áo nỉ có mũ": ["Áo nỉ", "Áo khoác gió"],
-    "Áo khoác gió": ["Áo nỉ có mũ", "Áo nỉ"],
-    "Quần dài": ["Quần jean", "Quần Khaki"],
-    "Quần jean": ["Quần dài", "Quần Khaki"],
-    "Quần Khaki": ["Quần dài", "Quần jean"],
-    "Quần soóc": ["Quần dài"],
-    # Phụ kiện alternatives (DB values verified 2026-02-07)
-    "Tất": ["Khăn mặt"],
-    "Khăn": ["Khăn mặt", "Mũ"],
-    "Khăn mặt": ["Khăn tắm", "Khăn"],
-    "Khăn tắm": ["Khăn mặt", "Khăn lau đầu"],
-    "Khăn lau đầu": ["Khăn tắm", "Khăn mặt"],
-    "Mũ": ["Khăn", "Găng tay chống nắng"],
-    "Túi xách": ["Mũ"],
-    "Chăn cá nhân": ["Khăn tắm"],
-    "Găng tay chống nắng": ["Mũ"],
-}
-
-
-# ============================================================
-# LEGACY MAPS - For backward compatibility with filter logic
-# ============================================================
-
-# Gender alternatives map (still used by apply_post_filters)
-GENDER_MAP = {
-    "men": ["men", "nam", "male", "boy"],
-    "nam": ["men", "nam", "male"],
-    "women": ["women", "nữ", "female", "nu"],
-    "nữ": ["women", "nữ", "female", "nu"],
-    "boy": ["boy", "bé trai", "be trai"],
-    "bé trai": ["boy", "bé trai", "be trai"],
-    "girl": ["girl", "bé gái", "be gai"],
-    "bé gái": ["girl", "bé gái", "be gai"],
-    "unisex": ["unisex"],
-}
-
-# Age alternatives map (still used by apply_post_filters)
-AGE_MAP = {
-    "adult": ["adult", "người lớn", "nguoi lon"],
-    "người lớn": ["adult", "người lớn", "nguoi lon"],
-    "kid": ["kid", "trẻ em", "tre em", "kids", "child", "children"],
-    "trẻ em": ["kid", "trẻ em", "tre em", "kids"],
-}
-
-
-# ============================================================
-# PRODUCT_LINE_FILTER_MAP - For post-filter product line matching
-# Maps user search term -> acceptable product_line values
-# ============================================================
-PRODUCT_LINE_FILTER_MAP = {
-    # Chân váy / Skirt
-    "chân váy": ["skirt", "chân váy", "chan vay"],
-    "chan vay": ["skirt", "chân váy", "chan vay"],
-    "skirt": ["skirt", "chân váy"],
-    # Váy / Dress
-    "váy": ["dress", "váy", "vay", "đầm", "dam"],
-    "vay": ["dress", "váy", "vay"],
-    "dress": ["dress", "váy", "đầm"],
-    "đầm": ["dress", "đầm", "dam", "váy"],
-    "dam": ["dress", "đầm", "dam"],
-    "váy liền thân": ["dress", "váy", "vay", "đầm", "dam"],
-    "vay lien than": ["dress", "váy", "vay", "đầm", "dam"],
-    "đầm liền thân": ["dress", "váy", "vay", "đầm", "dam"],
-    "dam lien than": ["dress", "váy", "vay", "đầm", "dam"],
-    "váy liền": ["dress", "váy", "vay", "đầm", "dam"],
-    "vay lien": ["dress", "váy", "vay", "đầm", "dam"],
-    "váy đầm": ["dress", "váy", "vay", "đầm", "dam"],
-    "vay dam": ["dress", "váy", "vay", "đầm", "dam"],
-    "váy bé gái": ["dress", "váy", "vay", "đầm", "dam"],
-    "vay be gai": ["dress", "váy", "vay", "đầm", "dam"],
-    "chân váy bé gái": ["skirt", "chân váy", "chan vay"],
-    "chan vay be gai": ["skirt", "chân váy", "chan vay"],
-    # Áo / Shirt / Top
-    "áo": ["shirt", "top", "polo", "t-shirt", "blouse", "áo", "ao"],
-    "ao": ["shirt", "top", "áo", "ao"],
-    "áo sơ mi": ["shirt", "áo sơ mi", "ao so mi"],
-    "ao so mi": ["shirt", "áo sơ mi"],
-    "áo thun": ["t-shirt", "tee", "áo thun", "ao thun"],
-    "ao thun": ["t-shirt", "áo thun"],
-    "áo polo": ["polo", "áo polo", "ao polo"],
-    "ao polo": ["polo", "áo polo"],
-    "áo khoác": ["jacket", "coat", "áo khoác", "ao khoac", "outerwear"],
-    "ao khoac": ["jacket", "coat", "áo khoác"],
-    "áo len": ["sweater", "knit", "knitwear", "áo len", "ao len"],
-    "ao len": ["sweater", "knit", "áo len"],
-    "áo hoodie": ["hoodie", "áo hoodie"],
-    "hoodie": ["hoodie", "áo hoodie"],
-    "shirt": ["shirt", "áo", "ao"],
-    "t-shirt": ["t-shirt", "tee", "áo thun"],
-    "top": ["top", "áo", "blouse"],
-    # Quần / Pants
-    "quần": ["pants", "trousers", "shorts", "jeans", "quần", "quan"],
-    "quan": ["pants", "trousers", "quần", "quan"],
-    "quần jeans": ["jeans", "denim", "quần jeans", "quan jeans"],
-    "quan jeans": ["jeans", "quần jeans"],
-    "jeans": ["jeans", "denim", "quần jeans"],
-    "quần short": ["shorts", "quần short", "quan short"],
-    "quan short": ["shorts", "quần short"],
-    "shorts": ["shorts", "quần short"],
-    "quần dài": ["pants", "trousers", "quần dài", "quan dai"],
-    "quan dai": ["pants", "trousers", "quần dài"],
-    "pants": ["pants", "trousers", "quần"],
-    "trousers": ["pants", "trousers", "quần"],
-    # Bộ / Set
-    "bộ": ["set", "bộ", "bo", "bộ quần áo"],
-    "bo": ["set", "bộ", "bo"],
-    "bộ quần áo": ["set", "bộ quần áo", "bo quan ao"],
-    "bo quan ao": ["set", "bộ quần áo"],
-    "set": ["set", "bộ"],
-    # Phụ kiện / Accessories
-    "phụ kiện": ["accessory", "accessories", "phụ kiện", "phu kien"],
-    "phu kien": ["accessory", "phụ kiện"],
-    "accessory": ["accessory", "accessories", "phụ kiện"],
-    "túi": ["bag", "túi", "tui"],
-    "tui": ["bag", "túi"],
-    "bag": ["bag", "túi"],
-    "mũ": ["hat", "cap", "mũ", "mu", "nón"],
-    "mu": ["hat", "cap", "mũ"],
-    "hat": ["hat", "cap", "mũ"],
-    "cap": ["cap", "hat", "mũ"],
-    "khăn": ["scarf", "khăn", "khan"],
-    "khan": ["scarf", "khăn"],
-    "scarf": ["scarf", "khăn"],
-    # Tất / Socks
-    "tất": ["socks", "tất", "tat"],
-    "tat": ["socks", "tất"],
-    "socks": ["socks", "tất"],
-}
-
-
-# ============================================================
-# SLEEVE MAPPINGS - For post-filter sleeve matching
-# ============================================================
-
-# Mapping user input → DB form_sleeve value
-SLEEVE_FALLBACK_MAP = {
-    "cộc tay": "Short Sleeve",
-    "ngắn tay": "Short Sleeve",
-    "short sleeve": "Short Sleeve",
-    "dài tay": "Full length Sleeve",
-    "long sleeve": "Full length Sleeve",
-    "sát nách": "Sleeveless",
-    "sleeveless": "Sleeveless",
-    "tank": "Sleeveless",
-}
-
-# Opposite sleeve for fallback suggestion
-SLEEVE_ALTERNATIVES = {
-    "Short Sleeve": ["Full length Sleeve", "Sleeveless"],
-    "Full length Sleeve": ["Short Sleeve"],
-    "Sleeveless": ["Short Sleeve"],
-}
-
-# Display names for user messages
-SLEEVE_DISPLAY = {
-    "Short Sleeve": "cộc tay",
-    "Full length Sleeve": "dài tay",
-    "Sleeveless": "sát nách",
-}
-
-
-# ============================================================
-# FIELD MAPPINGS - For generic multi-field fallback detection
-# ============================================================
-
-FIELD_MAPPINGS = {
-    "style": {
-        "basic": "Basic",
-        "cơ bản": "Basic",
-        "dynamic": "Dynamic",
-        "năng động": "Dynamic",
-        "sporty": "Dynamic",
-        "thể thao": "Dynamic",
-        "feminine": "Feminine",
-        "nữ tính": "Feminine",
-        "smart casual": "Smart Casual",
-        "thanh lịch": "Smart Casual",
-        "casual": "Smart Casual",
-    },
-    "fitting": {
-        "regular": "Regular",
-        "vừa": "Regular",
-        "suông": "Regular",
-        "slimfit": "Slimfit",
-        "slim": "Slimfit",
-        "ôm": "Slimfit",
-        "relax": "Relax",
-        "rộng": "Relax",
-        "oversize": "Oversize",
-        "skinny": "Skinny",
-        "boxy": "Boxy",
-    },
-    "form_neckline": {
-        "cổ tròn": "Crew Neck",
-        "crew neck": "Crew Neck",
-        "cổ chữ v": "V-neck",
-        "v-neck": "V-neck",
-        "cổ bẻ": "Classic Collar",
-        "cổ đức": "Mock Neck/ High neck",
-        "cổ cao": "Mock Neck/ High neck",
-        "có mũ": "Hooded collar",
-        "hoodie": "Hooded collar",
-    },
-    "material_group": {
-        "dệt kim": "Knit - Dệt Kim",
-        "knit": "Knit - Dệt Kim",
-        "dệt thoi": "Woven - Dệt Thoi",
-        "woven": "Woven - Dệt Thoi",
-        "len": "Yarn - Sợi",
-        "sợi": "Yarn - Sợi",
-    },
-    "season": {
-        "thu đông": "Fall Winter",
-        "mùa đông": "Fall Winter",
-        "fall winter": "Fall Winter",
-        "xuân hè": "Spring Summer",
-        "mùa hè": "Spring Summer",
-        "spring summer": "Spring Summer",
-        "4 mùa": "Year",
-        "quanh năm": "Year",
-    },
-    "form_length": {
-        "dài": "Long",
-        "long": "Long",
-        "ngắn": "Short",
-        "short": "Short",
-        "midi": "Midi",
-        "mini": "Mini",
-        "maxi": "Maxi",
-    },
-}
-
-# Display names for user-friendly messages
-FIELD_DISPLAY_NAMES = {
-    "style": "phong cách",
-    "fitting": "dáng",
-    "form_neckline": "kiểu cổ",
-    "material_group": "chất liệu",
-    "season": "mùa",
-    "form_length": "độ dài",
-}
-
-# Alternative values for fallback suggestions
-FIELD_ALTERNATIVES = {
-    "style": {
-        "Basic": ["Dynamic", "Smart Casual"],
-        "Dynamic": ["Basic", "Athleisure"],
-        "Feminine": ["Smart Casual", "Trend"],
-        "Smart Casual": ["Basic", "Feminine"],
-    },
-    "fitting": {
-        "Slimfit": ["Slim", "Regular"],
-        "Slim": ["Slimfit", "Regular"],
-        "Regular": ["Relax", "Slimfit"],
-        "Oversize": ["Relax", "Boxy"],
-        "Relax": ["Regular", "Oversize"],
-    },
-    "season": {
-        "Fall Winter": ["Year"],
-        "Spring Summer": ["Year"],
-        "Year": ["Fall Winter", "Spring Summer"],
-    },
-}

backend/agent/tools/filter.py

-"""
-Data Retrieval Filters - Module tách biệt cho logic lọc sản phẩm.
-Chứa các hàm lọc Hard/Soft Filter, maps được import từ db_field_values_mapping.
-"""
-
-import logging
-import re
-
-from agent.tools.db_field_values_mapping import (
-    COLOR_MAPPING,
-    SIMILAR_COLORS,
-    VALID_COLORS,
-    PRODUCT_NAME_KEYWORDS,
-    PRODUCT_TYPE_MAPPING,
-    PRODUCT_TYPE_ALTERNATIVES,
-    PRODUCT_LINE_FILTER_MAP,
-    GENDER_MAP,
-    AGE_MAP,
-    SLEEVE_FALLBACK_MAP,
-    SLEEVE_ALTERNATIVES,
-    SLEEVE_DISPLAY,
-    FIELD_MAPPINGS,
-    FIELD_DISPLAY_NAMES,
-    FIELD_ALTERNATIVES,
-)
-
-logger = logging.getLogger(__name__)
-
-
-def _filter_color(products: list[dict], requested_color: str) -> tuple[list[dict], dict]:
-    """
-    Color filter - So sánh trực tiếp với column master_color.
-    """
-    if not requested_color or not products:
-        return products, {"fallback_used": False}
-
-    requested_lower = requested_color.lower().strip()
-    db_color = COLOR_MAPPING.get(requested_lower, requested_lower)
-    
-    filtered = []
-    available_colors = set()
-    
-    for p in products:
-        p_color = (p.get("master_color") or "").lower()
-        available_colors.add(p.get("master_color") or "Unknown")
-        
-        if db_color.lower() in p_color or requested_lower in p_color:
-            filtered.append(p)
-    
-    if filtered:
-        logger.info(f"✅ [COLOR] Matched '{requested_color}': {len(filtered)} products")
-        return filtered, {"fallback_used": False}
-    
-    colors_list = sorted([c for c in available_colors if c != "Unknown"])[:5]
-    colors_text = ", ".join(colors_list) if colors_list else "các màu khác"
-    
-    logger.warning(f"⚠️ [COLOR] No match for '{requested_color}'. Available: {colors_list}")
-    
-    return products, {
-        "fallback_used": True,
-        "requested_value": requested_color,
-        "message": f"Shop hiện chưa có màu **{requested_color}**. Hiện có: **{colors_text}**",
-        "alternative_colors": colors_list,
-    }
-
-
-
-# ==============================================================================
-# 3. SLEEVE FALLBACK DETECTION
-# ==============================================================================
-def _detect_sleeve_mismatch(products: list[dict], requested_sleeve: str | None) -> dict | None:
-    """
-    Detect if products don't match the user's requested sleeve type.
-    
-    Args:
-        products: List of products from search
-        requested_sleeve: User's sleeve request (e.g., "cộc tay", "dài tay")
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_sleeve or not products:
-        return None
-    
-    requested_lower = requested_sleeve.lower().strip()
-    target_db_sleeve = SLEEVE_FALLBACK_MAP.get(requested_lower)
-    
-    if not target_db_sleeve:
-        return None  # Unknown sleeve type, skip detection
-    
-    # Count products matching requested sleeve
-    matching_count = 0
-    other_sleeves = {}  # {sleeve_type: count}
-    
-    for p in products:
-        p_sleeve = (p.get("form_sleeve") or "").strip()
-        if target_db_sleeve.lower() in p_sleeve.lower():
-            matching_count += 1
-        elif p_sleeve:
-            other_sleeves[p_sleeve] = other_sleeves.get(p_sleeve, 0) + 1
-    
-    # If all products match, no fallback needed
-    if matching_count == len(products):
-        return None
-    
-    # If NO products match the requested sleeve → Fallback
-    if matching_count == 0 and other_sleeves:
-        # Get the most common alternative sleeve
-        top_alt = max(other_sleeves.keys(), key=lambda k: other_sleeves[k])
-        top_alt_display = SLEEVE_DISPLAY.get(top_alt, top_alt)
-        requested_display = SLEEVE_DISPLAY.get(target_db_sleeve, requested_sleeve)
-        
-        return {
-            "fallback_used": True,
-            "requested_value": requested_display,
-            "matched_value": top_alt_display,
-            "message": f"Shop hiện chưa có mẫu **{requested_display}** phù hợp. Em gợi ý những mẫu **{top_alt_display}** - có thể xắn tay hoặc layer bên trong để tạo phong cách ưng ý nhé!",
-            "alternative_sleeves": list(other_sleeves.keys()),
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 6. PRODUCT TYPE FALLBACK DETECTION
-# ==============================================================================
-
-
-
-def _detect_product_type_mismatch(products: list[dict], requested_product_name: str | None) -> dict | None:
-    """
-    Detect if products don't match the user's requested product type.
-    
-    Args:
-        products: List of products from search
-        requested_product_name: User's product name request (e.g., "váy liền thân")
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_product_name or not products:
-        return None
-    
-    requested_lower = requested_product_name.lower().strip()
-    target_db_type = PRODUCT_TYPE_MAPPING.get(requested_lower)
-    
-    if not target_db_type:
-        return None  # Unknown product type, skip detection
-    
-    # Count products matching requested type
-    matching_count = 0
-    other_types = {}  # {product_line_vn: count}
-    
-    for p in products:
-        p_type = (p.get("product_line_vn") or p.get("product_name") or "").strip()
-        if target_db_type.lower() in p_type.lower():
-            matching_count += 1
-        elif p_type:
-            # Group by first 2 words for cleaner grouping
-            clean_type = " ".join(p_type.split()[:3])
-            other_types[clean_type] = other_types.get(clean_type, 0) + 1
-    
-    # If all products match, no fallback needed
-    if matching_count == len(products):
-        return None
-    
-    # If NO products match the requested type → Fallback
-    if matching_count == 0 and other_types:
-        # Get the most common alternative type
-        top_alt = max(other_types.keys(), key=lambda k: other_types[k])
-        
-        return {
-            "fallback_used": True,
-            "requested_value": requested_product_name,
-            "matched_value": top_alt,
-            "message": f"Không có {requested_product_name}. Hiển thị {top_alt} phù hợp.",
-            "alternative_types": list(other_types.keys())[:3],
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 7. GENERIC MULTI-FIELD FALLBACK DETECTION
-# ==============================================================================
-
-
-
-def _detect_field_mismatch(
-    products: list[dict],
-    field_name: str,
-    requested_value: str | None
-) -> dict | None:
-    """
-    Generic fallback detection for any field.
-    
-    Args:
-        products: List of products from search
-        field_name: DB field name (e.g., 'style', 'fitting')
-        requested_value: User's requested value (Vietnamese or English)
-    
-    Returns:
-        dict with fallback info if mismatch detected, None otherwise
-    """
-    if not requested_value or not products or field_name not in FIELD_MAPPINGS:
-        return None
-    
-    requested_lower = requested_value.lower().strip()
-    field_mapping = FIELD_MAPPINGS[field_name]
-    target_db_value = field_mapping.get(requested_lower)
-    
-    if not target_db_value:
-        return None  # Unknown value, skip detection
-    
-    # Count products matching requested value
-    matching_count = 0
-    other_values = {}
-    
-    for p in products:
-        p_value = (p.get(field_name) or "").strip()
-        if target_db_value.lower() in p_value.lower():
-            matching_count += 1
-        elif p_value:
-            other_values[p_value] = other_values.get(p_value, 0) + 1
-    
-    # If all/most products match, no fallback needed
-    if matching_count >= len(products) * 0.5:  # 50% threshold
-        return None
-    
-    # If NO products match → Fallback
-    if matching_count == 0 and other_values:
-        top_alt = max(other_values.keys(), key=lambda k: other_values[k])
-        display_name = FIELD_DISPLAY_NAMES.get(field_name, field_name)
-        
-        return {
-            "fallback_used": True,
-            "field": field_name,
-            "requested_value": requested_value,
-            "matched_value": top_alt,
-            "message": f"Shop hiện chưa có sản phẩm {display_name} **{requested_value}** phù hợp. Em gợi ý {display_name} **{top_alt}** - cũng rất đẹp và hợp xu hướng nhé!",
-        }
-    
-    return None
-
-
-# ==============================================================================
-# 8. HELPER FUNCTIONS
-# ==============================================================================
-
-
-def infer_product_name_from_description(description: str | None) -> str | None:
-    """
-    Infer product_name from description text if not explicitly provided.
-    Returns the first matching product type keyword found.
-    """
-    if not description:
-        return None
-    desc_lower = description.lower()
-    for keyword, product_name in PRODUCT_NAME_KEYWORDS:
-        if keyword in desc_lower:
-            return product_name
-    return None
-
-
-# ==============================================================================
-# 9. MASTER POST-FILTER FUNCTION (Consolidates all filter layers)
-# ==============================================================================
-
-
-def apply_post_filters(
-    products: list[dict],
-    search_item,  # SearchItem from data_retrieval_tool
-    is_sku_search: bool = False,
-) -> tuple[list[dict], dict]:
-    """
-    Master function to apply all post-filters on products.
-    
-    Consolidates all filter layers:
-    - Layer 1.5: Gender fallback detection
-    - Layer 1.8: Product type filter (cascading)
-    - Layer 2: Color filter with smart fallback
-    - Layer 3: Sleeve fallback detection
-    - Layer 5: Multi-field fallback (style, fitting, etc.)
-    
-    Args:
-        products: List of products from DB query
-        search_item: SearchItem with filter parameters
-        is_sku_search: If True, skip all filters (show all variants)
-    
-    Returns:
-        Tuple of (filtered_products, filter_info_dict)
-    """
-    original_count = len(products)
-    all_filter_info = {}
-    
-    # ⚡ SKIP all filters when searching by SKU code
-    if is_sku_search:
-        logger.info("🎯 [SKU SEARCH] Skipping post-filters - showing all variants")
-        return products, {"fallback_used": False, "filters_applied": {}}
-    
-    logger.info(
-        "🔍 [POST-FILTER] Starting with %d products. Params: product_name=%r, gender=%r, color=%r",
-        original_count,
-        search_item.product_name,
-        search_item.gender_by_product,
-        search_item.master_color,
-    )
-    
-    # ====== LAYER 1.5: GENDER FALLBACK DETECTION ======
-    if search_item.gender_by_product and products:
-        requested_gender = search_item.gender_by_product.lower().strip()
-        if requested_gender in ["men", "nam", "male", "women", "nữ", "female", "nu"]:
-            exact_gender_count = 0
-            unisex_count = 0
-            for p in products:
-                p_gender = (p.get("gender_by_product") or "").lower()
-                if p_gender == "unisex":
-                    unisex_count += 1
-                elif requested_gender in p_gender or p_gender in ["men", "nam", "women", "nữ"]:
-                    exact_gender_count += 1
-            
-            if unisex_count > 0 and exact_gender_count == 0:
-                gender_display = "nam" if requested_gender in ["men", "nam", "male"] else "nữ"
-                if gender_display == "nam":
-                    detail_msg = "Hiện shop chưa có sản phẩm riêng dành cho **nam**. Em xin phép gợi ý những mẫu **unisex** phù hợp!"
-                else:
-                    detail_msg = "Hiện shop chưa có sản phẩm riêng dành cho **nữ**. Em xin phép gợi ý những mẫu **unisex** phù hợp!"
-                
-                all_filter_info["gender"] = {
-                    "fallback_used": True,
-                    "requested_value": gender_display,
-                    "matched_value": "unisex",
-                    "message": detail_msg,
-                }
-                logger.warning(f"👫 GENDER FALLBACK: '{gender_display}' → 'unisex' ({unisex_count} products)")
-    
-    # ====== LAYER 1.8: PRODUCT TYPE FILTER (Cascading Fallback) ======
-    if search_item.product_name and products:
-        raw_product_names = re.split(r"[/,]", search_item.product_name)
-        raw_product_names = [n.strip().lower() for n in raw_product_names if n.strip()]
-        
-        logger.info(f"📦 [PRODUCT TYPE] Input: '{search_item.product_name}' → Parsed: {raw_product_names}")
-        
-        all_db_types = []
-        for pn in raw_product_names:
-            db_type = PRODUCT_TYPE_MAPPING.get(pn)
-            if db_type and db_type not in all_db_types:
-                all_db_types.append(db_type)
-                for fb in PRODUCT_TYPE_ALTERNATIVES.get(db_type, []):
-                    if fb not in all_db_types:
-                        all_db_types.append(fb)
-        
-        if all_db_types:
-            before_count = len(products)
-            primary_types = []
-            for pn in raw_product_names:
-                db_type = PRODUCT_TYPE_MAPPING.get(pn)
-                if db_type and db_type not in primary_types:
-                    primary_types.append(db_type)
-            
-            matched_products = []
-            matched_type = None
-            
-            for try_type in all_db_types:
-                for p in products:
-                    p_type = (p.get("product_line_vn") or "").lower()
-                    if try_type.lower() in p_type:
-                        matched_products.append(p)
-                
-                if matched_products:
-                    matched_type = try_type
-                    break
-            
-            if matched_products:
-                products = matched_products
-                if matched_type not in primary_types:
-                    detail_msg = f"Shop hiện chưa có **{search_item.product_name}** phù hợp. Em gợi ý những mẫu **{matched_type}** xinh xắn nhé!"
-                    all_filter_info["product_type"] = {
-                        "fallback_used": True,
-                        "requested_value": search_item.product_name,
-                        "matched_value": matched_type,
-                        "message": detail_msg,
-                    }
-                    logger.warning(f"📦 PRODUCT TYPE FALLBACK: '{search_item.product_name}' → '{matched_type}'")
-                else:
-                    logger.info(f"📦 [PRODUCT TYPE] Matched '{matched_type}': {before_count} → {len(products)}")
-    
-    # ====== LAYER 2: COLOR FILTER (with smart fallback) ======
-    if search_item.master_color and products:
-        before_count = len(products)
-        products, color_info = _filter_color(products, search_item.master_color)
-        
-        if color_info.get("fallback_used") or color_info.get("message"):
-            all_filter_info["color"] = color_info
-            if color_info.get("fallback_used"):
-                logger.warning(
-                    "🎨 COLOR FALLBACK: '%s' → '%s' (%d products)",
-                    color_info.get("requested_value"),
-                    color_info.get("matched_value"),
-                    len(products),
-                )
-        logger.info("🎨 Color filter: %d → %d products", before_count, len(products))
-    
-    # ====== LAYER 3: SLEEVE FALLBACK DETECTION ======
-    if products and search_item.product_name:
-        sleeve_keywords = ["cộc tay", "ngắn tay", "dài tay", "sát nách", "short sleeve", "long sleeve"]
-        requested_sleeve = None
-        for kw in sleeve_keywords:
-            if kw in search_item.product_name.lower():
-                requested_sleeve = kw
-                break
-        
-        if requested_sleeve:
-            sleeve_info = _detect_sleeve_mismatch(products, requested_sleeve)
-            if sleeve_info:
-                all_filter_info["sleeve"] = sleeve_info
-                logger.warning(
-                    "👕 SLEEVE FALLBACK: '%s' → '%s'",
-                    sleeve_info.get("requested_value"),
-                    sleeve_info.get("matched_value"),
-                )
-    
-    # ====== LAYER 5: MULTI-FIELD FALLBACK DETECTION ======
-    if products:
-        field_checks = [
-            ("style", search_item.style),
-            ("fitting", search_item.fitting),
-            ("form_neckline", search_item.form_neckline),
-            ("material_group", search_item.material_group),
-            ("season", search_item.season),
-        ]
-        
-        for field_name, requested_val in field_checks:
-            if requested_val:
-                field_info = _detect_field_mismatch(products, field_name, requested_val)
-                if field_info:
-                    all_filter_info[field_name] = field_info
-                    logger.warning(
-                        "🔄 %s FALLBACK: '%s' → '%s'",
-                        field_name.upper(),
-                        field_info.get("requested_value"),
-                        field_info.get("matched_value"),
-                    )
-    
-    # ====== BUILD FINAL FILTER INFO ======
-    filter_info = {
-        "fallback_used": any(info.get("fallback_used") for info in all_filter_info.values()),
-        "filters_applied": all_filter_info,
-    }
-    
-    fallback_messages = [info.get("message") for info in all_filter_info.values() if info.get("message")]
-    if fallback_messages:
-        filter_info["recommendation_message"] = " ".join(fallback_messages)
-    
-    if original_count != len(products):
-        logger.info("📊 Post-filter summary: %d → %d products", original_count, len(products))
-    
-    return products, filter_info
-

backend/agent/tools/flow.txt

-Step 1: User hỏi "váy màu trắng kem"
-        ↓
-Step 2: LLM gọi tool với: master_color="trắng kem" (raw từ user)
-        ↓
-Step 3: Tool chạy SEMANTIC SEARCH (vector DB)
-        - Dùng description để embed và tìm trong DB
-        - Trả về ~50 products (CHƯA LỌC MÀU)
-        ↓
-Step 4: Tool chạy COLOR FILTER (post-filter)
-        - Nhận 50 products từ Step 3
-        - Check: "trắng kem" có trong các products không? → KHÔNG
-        - Tách token: ["trắng", "kem"]
-        - Tìm products có màu chứa "trắng" → "Trắng/ White"
-        - Tìm products có màu chứa "kem" → "Be/ Beige" (vì Be trong DB)
-        - Gộp lại → trả về products 2 màu + MESSAGE
-        ↓
-Step 5: Tool trả về:
-        {
-          "results": [products màu Trắng + Be],
-          "filter_info": {
-            "message": "Shop không có màu 'trắng kem'. Chỉ có màu 'Trắng/ White' hoặc 'Be/ Beige'."
-          }
-        }
-        ↓
-Step 6: Agent nhận message → báo khách
-
-
-┌─────────────────────────────────────────────────────────────────────┐
-│  LAYER 1: SQL QUERY (Hard Filters - Nếu fail = 0 products)         │
-│  ─────────────────────────────────────────────────────────────────  │
-│  • gender_by_product (men/women/boy/girl)                          │
-│  • age_by_product (adult/kid)                                      │
-│  • price_min / price_max                                           │
-│  • discount_percent                                                 │
-│  → KHÔNG CÓ FALLBACK. Lọc cứng trong SQL.                         │
-└─────────────────────────────────────────────────────────────────────┘
-                              │
-                              ▼
-┌─────────────────────────────────────────────────────────────────────┐
-│  LAYER 2: PYTHON FILTER - COLOR ONLY (Soft Filter + Smart Fallback)│
-│  ─────────────────────────────────────────────────────────────────  │
-│  Function: filter_color_with_smart_fallback()                      │
-│                                                                     │
-│  Step 1: Exact Match                                               │
-│     User: "Nâu" → Tìm products có master_color chứa "Nâu"          │
-│     ✅ Found? → Return ngay (fallback_used = False)                │
-│                                                                     │
-│  Step 2: Token Split + COLOR_MAPPING                               │
-│     User: "Trắng kem" → tokens ["Trắng", "kem"]                    │
-│     Map tokens → DB colors: {"Trắng", "Kem"}                       │
-│     ✅ Found? → Return products + recommendation_message           │
-│                                                                     │
-│  Step 3: NO MATCH → Return ALL products + Show Available Colors    │
-│     "Không tìm thấy màu 'Nâu'. Có các màu: Hồng, Cam, Xanh..."    │
-│     → fallback_used = True                                         │
-│     → alternative_colors = ["Hồng", "Cam", "Xanh", ...]           │
-└─────────────────────────────────────────────────────────────────────┘
-                              │
-                              ▼
-┌─────────────────────────────────────────────────────────────────────┐
-│  OUTPUT: filter_info Object                                         │
-│  ─────────────────────────────────────────────────────────────────  │
-│  {                                                                  │
-│    "fallback_used": true/false,                                    │
-│    "requested_value": "Nâu",                                       │
-│    "matched_value": "Brown" or null,                               │
-│    "message": "Không tìm thấy màu 'Nâu'. Có các màu: Hồng, Cam",  │
-│    "alternative_colors": ["Hồng", "Cam", "Xanh"]                   │
-│  }                                                                  │
-│                                                                     │
-│  → recommendation_message được truyền lên cho LLM để nói với user  │
-└─────────────────────────────────────────────────────────────────────┘
-
-
-┌─────────────────────────────────────────────────────────────────────┐
-│  SEMANTIC SEARCH + SQL HARD FILTERS (1 query duy nhất)             │
-│  ────────────────────────────────────────────────────────────────   │
-│                                                                     │
-│  SELECT * FROM products                                             │
-│  WHERE approx_cosine_similarity(embedding, ?) > 0.5                │
-│    AND gender_by_product = 'men'      ← HARD FILTER (trong SQL)    │
-│    AND sale_price <= 100000           ← HARD FILTER (trong SQL)    │
-│    AND discount_percent >= 20         ← HARD FILTER (trong SQL)    │
-│                                                                     │
-│  → Nếu 0 kết quả = CHẾT, không có fallback!                        │
-└─────────────────────────────────────────────────────────────────────┘
-                              │
-                              ▼
-┌─────────────────────────────────────────────────────────────────────┐
-│  PYTHON POST-FILTER (Chỉ có COLOR có fallback)                     │
-│  ────────────────────────────────────────────────────────────────   │
-│                                                                     │
-│  filter_color_with_smart_fallback(products, "nâu")                 │
-│  → Lọc màu + fallback nếu không có                                 │
-│                                                                     │
-│  → Color fallback có thể vì COLOR KHÔNG trong SQL query!           │
-└─────────────────────────────────────────────────────────────────────┘
-
-Bro ơi, tao đã bỏ sạch product_line_vn khỏi SQL rồi!
-
-Kiến trúc bây giờ:
-Tầng	Filter	Mục đích
-SQL (product_search_helpers.py)	gender + age ONLY	Giữ HNSW index nguyên vẹn
-Python (data_retrieval_filter.py)	PRODUCT_TYPE_MAPPING → exact match product_line_vn	Lọc đúng loại sản phẩm
-Flow cho "quần đùi bé trai":
-SQL: Vector search "Quần soóc bé trai" → top 100 (HNSW intact ✅)
-SQL: filtered_matches chỉ filter gender=boy, age=kid → ~80 results
-Python: PRODUCT_TYPE_MAPPING["quần soóc"] = "Quần soóc" → exact match product_line_vn ✅
-Nếu 0 match → reject all + message "Shop chưa có..."
-Server đang reload. Test lại đi bro! 🚀
-

backend/agent/tools/note/query.txt

+-- [HYDE SEARCH] Full Executable Query
+-- Original Params: ['women', 'unisex', 'adult', '%tím%', '%tím%', '%liền%']
+
+    WITH vector_matches AS (
+        SELECT /*+ SET_VAR(ann_params='{"ef_search":256}') */
+            internal_ref_code,
+            magento_ref_code,
+            product_color_code,
+            product_name,
+            master_color,
+            product_color_name,
+            product_image_url_thumbnail,
+            product_web_url,
+            sale_price,
+            original_price,
+            discount_amount,
+            ROUND(((original_price - sale_price) / original_price * 100), 0) as discount_percent,
+            age_by_product,
+            gender_by_product,
+            product_line_vn,
+            product_line_en,
+            description_text_full,
+            quantity_sold,
+            is_new_product,
+            approx_cosine_similarity(vector, [0.041171539574861526,0.03616797924041748,-0.04494577646255493,-0.028166595846414566,0.03670715540647507,-0.004836415871977806,0.005936336703598499,0.04503204673528671,0.06521882861852646,-0.014870496466755867,-0.050294410437345505,0.028080327436327934,-0.013997029513120651,-0.03474455326795578,0.02368064410984516,0.04800830036401749,-0.0194642823189497,0.002722842851653695,-0.030862480401992798,0.030129199847579002,0.013889194466173649,0.015280270017683506,0.012573602609336376,0.011214877478778362,0.018288876861333847,0.058317363262176514,0.03536999970674515,0.004480559378862381,0.02178274281322956,-0.03431321308016777,0.03142322227358818,-0.034528881311416626,0.024478627368807793,-0.05723900720477104,0.04498891159892082,0.021351400762796402,0.05051008239388466,0.01314513012766838,0.01698406971991062,-0.01670369692146778,0.025406010448932648,-0.00490111717954278,0.042249895632267,-0.009322366677224636,0.031078150495886803,0.029395919293165207,-0.0014369061682373285,0.0006557737942785025,0.021189648658037186,-0.003307849634438753,0.00994781218469143,-0.039942216128110886,-0.011171743273735046,0.043694887310266495,-0.02016521245241165,-0.00941941887140274,0.004868766292929649,0.011948158033192158,0.03028016909956932,-0.01120409369468689,0.007839630357921124,-0.04921605810523033,-0.027519583702087402,-0.0007036257302388549,-0.02976255863904953,-0.010810494422912598,-0.027929358184337616,-0.023184603080153465,0.0034857778809964657,-0.01089137140661478,0.04736128821969032,0.018051639199256897,-0.03317015618085861,0.02249445579946041,-0.006081914063543081,0.05473722890019417,-0.04268123582005501,-0.02639809623360634,-0.01051394734531641,-0.04076176509261131,-0.043177276849746704,0.030689943581819534,0.005345937795937061,0.03916580229997635,-0.03914423659443855,-0.02956845611333847,-0.027929358184337616,0.06478748470544815,0.014158782549202442,0.021394535899162292,0.0067612770944833755,-0.006513255648314953,0.04498891159892082,-0.005383680108934641,0.025406010448932648,-0.02506093680858612,0.0016364016337320209,-0.040222588926553726,-0.026354961097240448,0.043543919920921326,0.042789071798324585,-0.005688315257430077,0.035671938210725784,-0.013802926056087017,0.023249303922057152,-0.037720806896686554,0.013986245729029179,-0.020229913294315338,-0.05374514311552048,0.002678360790014267,-0.058878105133771896,-0.00401147548109293,-0.01755559630692005,0.042508698999881744,0.019496632739901543,0.025837352499365807,0.04268123582005501,0.03317015618085861,-0.023853180930018425,-0.03090561367571354,-0.012454983778297901,-0.005132962949573994,0.02288266271352768,-0.06056033819913864,-0.0351111926138401,0.04138721153140068,-0.011430548503994942,0.026031455025076866,-0.003046348923817277,-0.03493865579366684,-0.013846060261130333,0.04524771496653557,0.005273148883134127,-0.00780727993696928,0.010066431015729904,-0.017361493781208992,-0.051329631358385086,0.08014323562383652,-0.04593786224722862,0.008341064676642418,0.06780687719583511,-0.011053124442696571,0.05490976572036743,0.029870394617319107,0.011549167335033417,0.04503204673528671,-0.0019059899495914578,0.020801441743969917,-0.024953102692961693,0.05158843472599983,-0.0012994160642847419,0.004903812892735004,0.0035477832425385714,0.01065952517092228,-0.04106370359659195,-0.019755437970161438,-0.009139047004282475,0.0066642253659665585,-0.04641233757138252,0.018968239426612854,0.01618608832359314,-0.023723779246211052,0.011635434813797474,-0.027519583702087402,-0.032307472079992294,-0.0021391839254647493,0.018482981249690056,-0.014083297923207283,-0.05046694725751877,0.014514639042317867,0.005855460185557604,-0.011754054576158524,-0.008006775751709938,0.016779182478785515,-0.0002788554993458092,-0.03478768840432167,0.020758306607604027,0.015366538427770138,-0.0327603816986084,0.057454679161310196,0.04671427607536316,0.02197684533894062,-0.0028792039956897497,-0.06327778846025467,-0.08199800550937653,-0.0022483672946691513,-0.03972654789686203,0.01618608832359314,0.029439052566885948,-0.02368064410984516,-0.022580724209547043,0.010233575478196144,0.037569839507341385,-0.030107632279396057,0.025664815679192543,-0.05258052051067352,-0.012929460033774376,0.004774410743266344,0.030776211991906166,-0.011322712525725365,0.008702313527464867,-0.003612484550103545,-0.013899978250265121,-0.029201814904808998,0.021577855572104454,-0.03155262768268585,-0.06715986132621765,0.012627520598471165,0.05710960552096367,-0.02368064410984516,0.053615741431713104,0.005893202498555183,-0.001353333704173565,-0.02007894404232502,0.034485746175050735,-0.02700197324156761,0.04878471791744232,-0.004936163779348135,0.00414087763056159,0.02378848008811474,0.000368662120308727,0.009095912799239159,0.03066837601363659,0.029503753408789635,-0.01618608832359314,-0.003448035567998886,0.06392480432987213,-0.000943559396546334,-0.06940283626317978,-0.03470141813158989,-0.00039932780782692134,0.03834625333547592,0.017641864717006683,-0.028792040422558784,-0.021707257255911827,-0.018526114523410797,-0.019237827509641647,-0.006858328823000193,0.046110399067401886,0.05288245901465416,-0.027541151270270348,-0.0313153900206089,-0.011355062946677208,0.012012858875095844,0.0057584079913794994,-0.00911747943609953,-0.019518200308084488,-0.022300351411104202,0.03217807039618492,0.01614295318722725,0.062156300991773605,0.0035531751345843077,-0.06728926301002502,-0.021858226507902145,-0.020909275859594345,0.0073004537262022495,-0.04900038614869118,-0.006459338124841452,0.013943111523985863,-0.01452542282640934,0.04598099738359451,0.004445512779057026,-0.01018504984676838,-0.006200533360242844,0.00959195476025343,-0.016789965331554413,0.02790779061615467,0.07246536016464233,0.01089137140661478,0.04688681289553642,-0.0189898069947958,-0.026743169873952866,0.011635434813797474,0.04912979155778885,-0.01822417601943016,-0.012724572792649269,-0.010093390010297298,0.008572910912334919,0.039899084717035294,0.05370200797915459,-0.03858349099755287,-0.02169647440314293,0.043414514511823654,-0.031164418905973434,0.05288245901465416,0.04619666934013367,0.025190340355038643,-0.019572118297219276,0.0057314494624733925,-0.021610205993056297,-0.011829539202153683,0.02478056587278843,-0.04380272328853607,-0.03248000890016556,0.025039371103048325,0.007758754305541515,-0.026807870715856552,-0.011096258647739887,0.0034965614322572947,0.010400720871984959,0.038756027817726135,0.042228326201438904,0.003795804688706994,-0.007650918792933226,0.009759100154042244,0.0030409570317715406,0.0215994231402874,-0.049302324652671814,0.025880485773086548,-0.011754054576158524,0.02060733735561371,0.018957456573843956,-0.019345663487911224,-0.04498891159892082,-0.03157419338822365,-0.004636920522898436,-0.08324889838695526,0.01746932789683342,0.030409570783376694,0.003229669062420726,0.02577265165746212,0.023184603080153465,0.0598270557820797,0.005882418714463711,0.03198396787047386,0.007456814870238304,0.03213493525981903,-0.006577956955879927,0.03873446211218834,-0.032156504690647125,-0.06866955757141113,-0.025082504376769066,-0.011958940885961056,0.011452115140855312,0.011754054576158524,-0.015150868333876133,0.025902053341269493,0.010282101109623909,0.025147205218672752,0.040459826588630676,0.031725164502859116,-0.05184724181890488,-0.049302324652671814,0.007133308798074722,0.024241389706730843,0.010071822442114353,0.04043826088309288,-0.027994059026241302,-0.036858126521110535,0.02790779061615467,0.0030301737133413553,-0.0028899875469505787,-0.017027202993631363,0.030603675171732903,-0.01575474627315998,-0.03317015618085861,0.0654776319861412,-0.004844503477215767,-0.07759832590818405,0.05279619246721268,-0.016811532899737358,-0.07130073755979538,0.012023642659187317,-0.008966510184109211,-0.01065413374453783,-0.01978778839111328,0.05685080215334892,0.020855357870459557,0.010050255805253983,0.011408980935811996,0.018429063260555267,0.05736841261386871,0.008195486851036549,0.012454983778297901,-0.006815194617956877,0.060258399695158005,0.023982584476470947,-0.008669963106513023,0.02572951652109623,-0.0417754165828228,0.018148690462112427,-0.023055199533700943,-0.026139291003346443,0.018450630828738213,-0.0024856049567461014,-0.0013620953541249037,-0.003156880149617791,0.00020505567954387516,0.07440640032291412,-0.002927730092778802,-0.012994160875678062,-0.05046694725751877,0.029740992933511734,0.041840121150016785,-0.015431240200996399,-0.022904230281710625,0.09946733713150024,0.01288632582873106,-0.024047285318374634,-0.02991352789103985,0.024694297462701797,0.02183666080236435,-0.019280962646007538,0.010486988350749016,0.02948218770325184,0.012142261490225792,0.016595860943198204,-0.007931291125714779,0.012476551346480846,0.024435492232441902,0.0023575504310429096,-0.006081914063543081,0.037612974643707275,0.00975370779633522,0.022429754957556725,-0.021092595532536507,0.03554253280162811,0.0011949505424126983,-0.02098476141691208,0.009683615528047085,-0.013716657646000385,-0.01812712475657463,-0.0185153316706419,-0.011807971633970737,0.04050296172499657,0.03711692988872528,0.025406010448932648,-0.0016431412659585476,0.008540560491383076,-0.05870556831359863,0.0038443305529654026,-0.06797941029071808,0.04671427607536316,-0.017598731443285942,0.01267065480351448,-0.036771856248378754,-0.0002589733630884439,0.08005697280168533,0.0313153900206089,0.010983031243085861,0.02473743073642254,0.01072961837053299,-0.01497833151370287,-0.00010160113015444949,0.04102057218551636,0.00812000222504139,0.044730108231306076,-0.0051410505548119545,-0.03498179093003273,0.011667786166071892,-0.02462959662079811,-0.010336019098758698,-0.016811532899737358,-0.03459358215332031,0.012002075091004372,0.051286496222019196,-0.013511770404875278,-0.04086960107088089,-0.01836436241865158,-0.01338236778974533,0.058878105133771896,-0.007893548347055912,0.0313369557261467,0.010481596924364567,0.013511770404875278,0.0021728824358433485,-0.01841827854514122,-0.03976967930793762,0.025233473628759384,0.01359803881496191,-0.02277482859790325,-0.018774136900901794,0.03910110145807266,-0.012476551346480846,0.0038982483092695475,0.038518790155649185,0.043738022446632385,0.02387474849820137,-0.02331400476396084,-0.019539767876267433,-0.010848237201571465,0.03976967930793762,-0.022106248885393143,-0.034722987562417984,0.02007894404232502,0.0773826539516449,0.05542737618088722,0.028360700234770775,-0.04268123582005501,0.03437791392207146,-0.007456814870238304,0.015398888848721981,-0.005370201077312231,-0.008146961219608784,0.004822936374694109,-0.002352158771827817,0.01089137140661478,-0.0013000901089981198,0.005343242082744837,-0.050337545573711395,-0.006119656842201948,-0.033385828137397766,0.034572016447782516,-0.07863354682922363,0.03981281444430351,0.003000518772751093,0.03953244164586067,0.04869844764471054,0.019000589847564697,-0.002482909243553877,-0.026700034737586975,0.0006197163020260632,0.01695171929895878,0.0001299921568715945,-0.011473681777715683,0.007214185316115618,-0.018299659714102745,0.014007813297212124,-0.02311990037560463,0.003488473827019334,-0.008993469178676605,0.02122199907898903,0.024198254570364952,0.011355062946677208,-0.02344340644776821,-0.06349346041679382,0.006453946232795715,-0.025945186614990234,-0.0024883009027689695,-0.014396020211279392,-0.020531851798295975,0.004386203363537788,-0.026419663801789284,0.0022928493563085794,-0.0075808255933225155,0.009538037702441216,0.004092351999133825,-0.0005951164057478309,0.013608822599053383,-0.0019828227814286947,-0.002198493340983987,0.012476551346480846,-0.0012286491692066193,-0.01622922159731388,-0.03256627917289734,0.013878410682082176,-0.00048525910824537277,-0.0051140920259058475,-0.01695171929895878,0.012897108681499958,0.02885674126446247,-0.020855357870459557,-0.03834625333547592,-0.03603857755661011,-0.013749008066952229,0.002135140122845769,0.0005799520295113325,-0.029546888545155525,-0.014924413524568081,-0.030452705919742584,0.003933294676244259,0.015312621369957924,0.0058500682935118675,0.019162343814969063,-0.0016242701094597578,0.018310444429516792,-1.248952503374312e-05,0.043975260108709335,-0.016293922439217567,-0.03138009086251259,-0.029266515746712685,0.02249445579946041,0.007348979823291302,-0.04740442335605621,0.008109219372272491,-0.027735253795981407,0.023961016908288002,-0.00865917932242155,-0.0055966549552977085,-0.02743331529200077,-0.02805875986814499,-0.0065294308587908745,0.00671814288944006,-0.022839529439806938,-0.03431321308016777,0.014180350117385387,0.0379580482840538,-0.03364463150501251,-0.041840121150016785,0.012314798310399055,0.006825978402048349,-0.02093084342777729,0.00037472788244485855,0.03155262768268585,0.02572951652109623,-0.013878410682082176,-0.028468534350395203,-0.013447069562971592,-0.016488026827573776,-0.060646604746580124,0.02639809623360634,-0.01723209023475647,-0.03437791392207146,-0.00028357328847050667,-0.004653095733374357,0.008707704953849316,0.0015703524695709348,-0.007408289238810539,-0.00582850119099021,-0.020542636513710022,0.011026165448129177,0.04395369067788124,0.01674683205783367,-0.007316628936678171,0.01444993820041418,-0.0028145029209554195,-0.03301918879151344,0.03651305288076401,-0.02383161522448063,-0.02639809623360634,-0.029827259480953217,-0.00996398739516735,-0.012616736814379692,-0.021049462258815765,-0.0031946224626153708,0.02620399184525013,-0.01689780130982399,-0.06474435329437256,-0.016919367015361786,-0.023098334670066833,0.0072034019976854324,-0.030625242739915848,0.03478768840432167,-0.00797442439943552,0.01751246303319931,-0.015291053801774979,-0.022753261029720306,-0.035585667937994,0.024564895778894424,0.00011617575364653021,-0.012487334199249744,0.002071786904707551,0.04542025178670883,-0.018731001764535904,0.03575820475816727,0.011117825284600258,-0.026743169873952866,-0.01521556917577982,-0.01585179753601551,0.024133553728461266,0.029266515746712685,0.0010271318024024367,0.03435634449124336,0.018677083775401115,0.020855357870459557,0.025902053341269493,-0.04727502167224884,-0.0074190725572407246,-0.030172333121299744,0.015938065946102142,-0.027562716975808144,0.018687868490815163,0.01274613942950964,-0.025751084089279175,0.004275672137737274,0.01314513012766838,0.013964679092168808,0.018008505925536156,-0.020639687776565552,-0.013986245729029179,0.0021715345792472363,0.041602883487939835,0.023141467943787575,0.0006648724083788693,-0.025362877175211906,-0.007753362413495779,-0.00966204795986414,0.01894667185842991,0.034334778785705566,-0.017728133127093315,-0.008928767405450344,0.0189790241420269,0.022278785705566406,0.011258011683821678,0.030409570783376694,-0.006464730016887188,-0.005122179631143808,0.04039512574672699,-0.03295448422431946,0.010508555918931961,0.008389591239392757,0.004661183338612318,0.012066776864230633,0.010524731129407883,0.03390343859791756,-0.006653441581875086,0.009451769292354584,0.04524771496653557,0.002025956753641367,-0.003728407435119152,-0.029935095459222794,0.004857982974499464,-0.030452705919742584,-0.021707257255911827,-0.04265966638922691,0.009796842001378536,-0.03241530805826187,-0.03301918879151344,0.0006914942641742527,-0.0037877170834690332,0.001671448117122054,-0.016434108838438988,-0.01203442644327879,0.02605302259325981,0.017124254256486893,0.0061088730581104755,-0.012713789008557796,-0.017210522666573524,-0.012853974476456642,0.009101304225623608,-0.018332011997699738,0.005521170329302549,-0.029697857797145844,-0.0008593130041845143,-0.05680766701698303,0.035434700548648834,0.04818083718419075,0.019960325211286545,-0.0023723780177533627,0.003121833549812436,0.020618120208382607,0.028511669486761093,-0.017005635425448418,0.026980407536029816,-0.023723779246211052,-0.026096157729625702,-0.006896071135997772,0.02620399184525013,-0.00048290021368302405,-0.017771266400814056,0.003919815178960562,-0.003499257378280163,0.03420537710189819,0.0057584079913794994,-0.0204132329672575,0.043177276849746704,-0.013759791851043701,-0.00582850119099021,-0.007920507341623306,0.02292579784989357,0.01808398962020874,0.004779802169650793,-0.04718875139951706,0.035715069621801376,0.008767014369368553,-0.0018925105687230825,0.009414026513695717,0.013544120825827122,0.06828135251998901,-0.0006187053513713181,-0.02084457501769066,0.039230503141880035,-0.004671967122703791,-0.009079737588763237,-0.035585667937994,0.010869803838431835,-0.02648436464369297,0.007478381972759962,-0.05715274065732956,-0.0011700136819854379,0.021944494917988777,-0.009980162605643272,-0.03161732852458954,0.004162444733083248,-0.014406803995370865,-0.0007177790976129472,-0.03981281444430351,-0.0028360700234770775,0.015743961557745934,0.015571425668895245,0.0074406396597623825,0.0056182220578193665,-0.0075376913882792,-0.025082504376769066,0.02795092575252056,-0.03345052897930145,0.007214185316115618,0.008702313527464867,0.004429337568581104,-0.027692120522260666,0.014352886006236076,0.011559950187802315,0.016078252345323563,-0.03271724656224251,0.0389285646378994,0.009888502769172192,-0.012347148731350899,-0.008405766449868679,0.009300800040364265,-0.04636920616030693,-0.026549065485596657,0.016919367015361786,-0.05111395940184593,0.01709190383553505,0.02572951652109623,0.008319498039782047,-0.019830921664834023,0.04332824796438217,0.025362877175211906,-0.03301918879151344,-0.011430548503994942,0.005348633974790573,-0.0043996828608214855,0.03155262768268585,0.05715274065732956,0.002981647616252303,0.011710920371115208,-0.014352886006236076,-0.02833913266658783,0.012832407839596272,0.07293983548879623,-0.006626483052968979,-0.012314798310399055,0.017307575792074203,-0.009570388123393059,0.013350017368793488,0.04076176509261131,0.02296893112361431,0.014277401380240917,-0.0061088730581104755,-0.029978230595588684,0.016078252345323563,0.004092351999133825,-0.036901261657476425,-0.04054609686136246,0.0011774273589253426,-0.00262309517711401,-0.02083379216492176,-0.005227318964898586,0.011710920371115208,0.040373560041189194,0.01737227663397789,0.00539985578507185,-0.023896316066384315,-0.015129300765693188,0.016638996079564095,0.012109911069273949,-0.017695782706141472,0.009338541887700558,0.06099167838692665,-0.002104137558490038,0.002100093523040414,0.014115648344159126,0.01798693835735321,-0.04283220320940018,0.010848237201571465,0.011969724670052528,0.0168546661734581,0.02192292921245098,0.014126432128250599,-0.02482369914650917,0.010389937087893486,-0.023098334670066833,0.01717817224562168,-0.007198010105639696,-0.035866040736436844,0.003383334493264556,0.02093084342777729,-0.005488819908350706,0.061207350343465805,-0.01671447977423668,0.00505478261038661,0.0024977365974336863,0.014697959646582603,0.01646645925939083,0.026937272399663925,-0.018526114523410797,0.050294410437345505,0.013242182321846485,0.036901261657476425,0.03390343859791756,0.01870943419635296,0.025880485773086548,0.013943111523985863,-0.014622475020587444,0.0013951199362054467,-0.01430975180119276,0.0379796139895916,-0.02596675418317318,0.013781358487904072,0.009775275364518166,0.006103481166064739,0.007985208183526993,0.014945981092751026,0.00431880634278059,0.010546297766268253,0.008179311640560627,0.005882418714463711,0.020909275859594345,-0.02877047471702099,0.008163136430084705,0.030970314517617226,-0.0051572262309491634,0.006394636817276478,-0.013468636199831963,0.042551834136247635,0.011408980935811996,0.01998189277946949,-0.013759791851043701,0.018332011997699738,0.007478381972759962,-0.00366640230640769,-0.014719526283442974,-0.026980407536029816,0.008864066563546658,0.02013286203145981,0.02378848008811474,-0.025147205218672752,0.05025127902626991,-0.04291847348213196,0.02810189500451088,-0.00935471709817648,-0.02672160230576992,-0.030258601531386375,-0.028037194162607193,-0.035003356635570526,0.0038793771527707577,-0.02710980921983719,0.015463590621948242,-0.0017536724917590618,-0.02136218547821045,0.020014243200421333,-0.021146513521671295,0.013716657646000385,0.0005428836448118091,-0.0050574783235788345,0.011958940885961056,-0.00041482914821244776,0.002569177420809865,-0.034291643649339676,-0.01322061475366354,-0.004844503477215767,-0.037763942033052444,0.0035396956373006105,0.015733178704977036,0.041753850877285004,0.013943111523985863,-0.01970151998102665,0.02203076332807541,0.00412739859893918,0.010567865334451199,-0.00925766583532095,0.022666992619633675,0.0031056583393365145,-0.01780361868441105,0.0016215741634368896,0.012476551346480846,-0.013608822599053383,-0.008486642502248287,-0.0029223382007330656,0.0074136811308562756,0.012066776864230633,0.0018399407854303718,-0.008777798153460026,0.030452705919742584,-0.017242873087525368,0.030258601531386375,-0.03698752820491791,0.06634031236171722,0.02572951652109623,-0.017922237515449524,0.025556979700922966,0.00579075887799263,0.01812712475657463,0.0035181285347789526,0.03483081981539726,0.038712892681360245,-0.007990600541234016,-0.0069014630280435085,-0.05158843472599983,0.03534843027591705,0.05193350836634636,0.05063948407769203,0.022516023367643356,-0.009640481323003769,0.009219923056662083,-0.007009298540651798,-0.008400374092161655,0.05197664350271225,0.009500294923782349,-0.041559748351573944,0.011026165448129177,-0.0005910725449211895,0.011171743273735046,-0.010540906339883804,0.00828175526112318,-0.0033779426012188196,0.03813058137893677,-0.016293922439217567,0.02616085857152939,0.006276017986238003,-0.029223382472991943,0.00487685389816761,0.025082504376769066,-0.032587844878435135,0.03886386379599571,0.03584447503089905,0.009365500882267952,0.0038497222121804953,-0.021998412907123566,-0.019011374562978745,-0.03127225488424301,0.01203442644327879,0.028317565098404884,0.0033860302064567804,0.02065047062933445,-0.01474109385162592,0.03248000890016556,0.04675741121172905,-0.0006823956500738859,-0.0194642823189497,0.012282447889447212,0.03327799215912819,-0.013554904609918594,0.00575301656499505,0.03817371651530266,0.030862480401992798,-0.013684307225048542,-0.03502492606639862,0.008998860605061054,0.009505687281489372,-0.0012926763156428933,-0.05301186442375183,0.0018803790444508195,-0.0225375909358263,0.011214877478778362,-0.0036017009988427162,0.02084457501769066,-0.003798500634729862,0.00965665653347969,-0.006631874479353428,-0.009333150461316109,0.01614295318722725,-0.003022085875272751,-0.018968239426612854,-0.023184603080153465,-0.005256973672658205,0.00787737313657999,0.0025085201486945152,0.0010365673806518316,-0.02842540107667446,-0.005947120022028685,-0.0021068332716822624,0.03360149636864662,-0.00644316291436553,0.00715487590059638,0.018332011997699738,-0.017296791076660156,0.031444791704416275,0.0004724536556750536,-0.01580866426229477,-0.015603776089847088,0.011430548503994942,0.03573663905262947,-0.0004936837358400226,0.019809355959296227,-0.006755885202437639,0.02782152220606804,-0.016358623281121254,-0.01884962059557438,0.022063113749027252,-0.009311582893133163,0.0006699271616525948,0.012800057418644428,0.036081712692976,-0.016822315752506256,-0.015970416367053986,-0.013662739656865597,-0.0012171915732324123,0.03498179093003273,-0.027282346040010452,0.004281063564121723,0.019712302833795547,0.005065565928816795,-0.015409672632813454,-0.01336080115288496,0.010012513026595116,-0.01652037724852562,0.010632566176354885,-0.010907546617090702,-0.011937374249100685,-0.007516124751418829,0.008195486851036549,0.0185153316706419,0.021815093234181404,-0.03841095417737961,0.02335713803768158,0.028943009674549103,0.03854035586118698,0.01790066994726658,0.0031811431981623173,0.010610999539494514,-0.012810840271413326,0.017879102379083633,-0.047533825039863586,0.011376630514860153,-0.02695883996784687,0.019302530214190483,-0.029978230595588684,0.03118598647415638,0.019669169560074806,0.014568557031452656,-0.0088964169844985,-0.0003381649439688772,0.0027794563211500645,0.0107997115701437,0.019572118297219276,0.018105557188391685,0.012552035972476006,0.010411503724753857,-0.026570633053779602,-0.003925207071006298,-0.0159057155251503,-0.0016296618850901723,-0.014191132970154285,0.0029412093572318554,-0.026225559413433075,-0.017480112612247467,0.0033132415264844894,-0.012649087235331535,0.019162343814969063,0.012422633357346058,-0.02430609054863453,0.02340027317404747,-0.028209729120135307,-0.004105831496417522,0.002765977056697011,-0.022192517295479774,-0.015398888848721981,-0.017102688550949097,0.04710248485207558,-0.0044050742872059345,0.018569249659776688,-0.021966062486171722,-5.214850534684956e-05,-0.005580479744821787,0.037483569234609604,0.06478748470544815,-0.027605852112174034,-0.006707359571009874,-0.008643004111945629,-0.013705873861908913,0.0038658976554870605,-0.02073673903942108,0.017825184389948845,0.007122525479644537,0.009300800040364265,0.009791450574994087,0.017027202993631363,0.005774583667516708,0.032156504690647125,0.007149484474211931,-0.010837453417479992,-0.008324889466166496,-0.02581578493118286,-0.0019545159302651882,-0.014967547729611397,-0.005526562221348286,0.004604569636285305,-0.007942073978483677,-0.04774949699640274,0.012897108681499958,-0.031099718064069748,-0.001965299481526017,0.006993122864514589,0.03640521690249443,0.044730108231306076,0.017534028738737106,0.03838938847184181,-0.018116340041160583,-0.027260778471827507,-0.013964679092168808,-0.04104213789105415,0.01989562436938286,-0.030862480401992798,0.02510407194495201,-0.017124254256486893,-0.005877027288079262,-0.008443508297204971,0.022429754957556725,-0.0014085994334891438,0.015927283093333244,-0.003814675845205784,-0.013608822599053383,-0.02340027317404747,0.060172129422426224,0.0010985727421939373,-0.021825876086950302,0.013274532742798328,-0.002113573020324111,-0.010481596924364567,0.00987232755869627,0.01823495887219906,0.01879570260643959,0.0032269731163978577,-0.032674115151166916,0.01072961837053299,0.016035117208957672,-0.03439947962760925,0.018051639199256897,0.004097743425518274,-0.004423945676535368,0.012853974476456642,0.006567173171788454,0.055944982916116714,-0.005027823615819216,0.0012488682987168431,0.016908584162592888,0.00286033283919096,0.006939205341041088,-0.022278785705566406,0.00435654865577817,-0.017738915979862213,0.02021913044154644,-0.02629026025533676,-0.015787096694111824,-0.037009093910455704,-0.02596675418317318,0.00828175526112318,0.012703005224466324,0.011937374249100685,-0.018159475177526474,-0.04969053342938423,-0.028684206306934357,0.016692914068698883,-0.03603857755661011,-0.013069645501673222,-0.0009368197061121464,0.0065240394324064255,-0.0026689250953495502,-0.0102012250572443,-0.02268856018781662,-0.012713789008557796,-0.03877759352326393,0.02790779061615467,-0.020801441743969917,0.0002916609519161284,-0.0022133206948637962,0.025902053341269493,-0.006971555761992931,0.01989562436938286,0.007068607956171036,-0.014546990394592285,-0.00897190161049366,0.008545951917767525,-0.00524619035422802,-0.03698752820491791,-0.006626483052968979,0.02288266271352768,0.011408980935811996,-0.021588638424873352,-0.028554802760481834,0.0012016902910545468,-0.027778388932347298,-0.024758998304605484,-0.01322061475366354,-0.03722476586699486,0.025751084089279175,-0.05434902012348175,-0.0017078424571081996,0.023723779246211052,-0.0389069989323616,0.01298337709158659,0.016304707154631615,0.05201977863907814,0.015096950344741344,-0.011732487007975578,-0.0022483672946691513,-0.021135730668902397,-0.008324889466166496,-0.00503051932901144,0.01927017793059349,-0.00012813873763661832,-0.008885633200407028,-0.038475655019283295,-0.016358623281121254,-0.00233867927454412,0.0055912635289132595,0.011333496309816837,0.019863273948431015,0.012023642659187317,0.0016903192736208439,0.011872673407196999,0.004577611107379198,0.01559299323707819,-0.007920507341623306,-0.020639687776565552,0.04593786224722862,-0.006114264950156212,0.02976255863904953,-0.01932409591972828,0.031358521431684494,0.003663706360384822,0.0035693503450602293,-0.011710920371115208,0.024478627368807793,0.00249234470538795,0.011667786166071892,0.004283759742975235,-0.01545280683785677,-0.004014171194285154,0.015743961557745934,0.012595170177519321,-0.015043032355606556,0.022365054115653038,-0.027303913608193398,-0.0230120662599802,-0.02838226594030857,-0.0032242771703749895,0.016531160101294518,0.02458646148443222,0.006141223944723606,0.020909275859594345,-0.006847545504570007,0.004990081302821636,0.004874158184975386,-0.0025840047746896744,-0.008767014369368553,0.0005068262107670307,-0.013403935357928276,-0.03090561367571354,-0.02833913266658783,-0.02877047471702099,0.0023265478666871786,-0.017544813454151154,0.028209729120135307,0.022710125893354416,0.03297605365514755,0.009721357375383377,0.004787889774888754,0.005558912642300129,0.016887016594409943,0.02486683428287506,0.005893202498555183,0.007176443003118038,0.006825978402048349,0.026311827823519707,-0.011764837428927422,-0.0067828441970050335,0.037052229046821594,0.02193371206521988,0.010168874636292458,-0.011829539202153683,0.013608822599053383,0.005205751862376928,-0.012767706997692585,-0.017868319526314735,0.003067916026338935,-0.009300800040364265,-0.0026621853467077017,-0.02277482859790325,-0.04580846056342125,0.01955055072903633,0.043457649648189545,0.030625242739915848,-0.042228326201438904,-0.011225661262869835,0.004585698712617159,0.028921443969011307,-0.02771368809044361,-0.0026635334361344576,-0.025600114837288857,0.02060733735561371,-0.009333150461316109,-0.04774949699640274,0.023745346814393997,-0.036534618586301804,-0.01476266048848629,0.05676453188061714,0.02122199907898903,0.02140531875193119,-0.03166045993566513,-0.0037796292454004288,-0.0020731347613036633,0.009705182164907455,-0.001767151989042759,-0.04229302704334259,0.0016390974633395672,-0.026851003989577293,-0.04662800952792168,0.058834973722696304,-0.04550652205944061,-0.02767055295407772,-0.010077213868498802,-0.008179311640560627,-0.006400028709322214,0.028403833508491516,0.015830229967832565,0.012325581163167953,0.0332132913172245,0.0010129783768206835,-0.021901361644268036,-0.00733280461281538,0.004388899076730013,-0.022278785705566406,0.01652037724852562,-0.006739709991961718,-0.010411503724753857,0.00041988393059000373,0.026937272399663925,0.013468636199831963,0.019755437970161438,0.009624306112527847,-0.03118598647415638,-0.024931535124778748,0.05443529039621353,0.01112860906869173,0.02596675418317318,0.004693534225225449,-0.01414799876511097,0.004510214086622,-0.02980569377541542,0.03138009086251259,-0.005480732303112745,-0.006044171750545502,0.027692120522260666,-0.00828175526112318,-0.0389285646378994,0.04947486147284508,-0.0025745693128556013,0.0031838389113545418,-0.0008660527528263628,-0.024715865030884743,-0.0014180350117385387,0.03312702104449272,-0.008783189579844475,-0.002701275749132037,-0.02311990037560463,0.006281409878283739,-0.0008903156849555671,-0.010179657489061356,0.028986144810914993,0.056548863649368286,-0.0168546661734581,-0.01267065480351448,-0.032587844878435135,-0.016488026827573776,0.018644733354449272,0.022947363555431366,4.0480383177055046e-05,0.024457059800624847,-0.00942481029778719,0.03198396787047386,0.028446968644857407,-0.0021863619331270456,0.011861889623105526,0.02292579784989357,0.0008384199463762343,0.027303913608193398,0.014342103153467178,0.0002136488037649542,-0.01312356349080801,-0.00334020028822124,0.012541252188384533,0.026807870715856552,0.0038416346069425344,-0.0045668273232877254,0.023227736353874207,-0.0006729600136168301,0.026786303147673607,-0.010260534472763538,-0.03222120553255081,0.003162271808832884,-0.021114163100719452,0.010621783323585987,0.008944942615926266,0.002895379438996315,0.002255107043311,0.02592362090945244,-0.02913711406290531,-0.0037769335322082043,0.0015784400748088956,-0.025039371103048325,0.009144438430666924,0.004000691697001457,0.017404627054929733,-0.022861097007989883,0.006324543617665768,0.028490101918578148,0.031207552179694176,0.026570633053779602,0.011355062946677208,-0.004928075708448887,0.00788276456296444,-0.009478728286921978,-0.02691570483148098,0.0006527408841066062,-0.011171743273735046,0.015398888848721981,-0.024845266714692116,0.019097642973065376,0.049345459789037704,0.014881279319524765,0.03944617509841919,-0.008928767405450344,-0.03979124873876572,-0.009505687281489372,-0.012217746116220951,0.02434922382235527,0.021631773561239243,0.0075754341669380665,0.037375736981630325,0.0027605851646512747,-0.0024357312358915806,0.025643248111009598,0.008292539045214653,0.0159057155251503,-0.023270869627594948,-0.051329631358385086,0.02700197324156761,-0.03379560261964798,0.017264440655708313,0.01812712475657463,0.005418726708739996,-0.025664815679192543,0.002643314190208912,0.013403935357928276,-0.022796394303441048,-0.02534130960702896,0.010265925899147987,-0.008578303270041943,0.011926590465009212,0.012314798310399055,0.0019113817252218723,0.016337057575583458,-0.026570633053779602]) as similarity_score
+        FROM shared_source.magento_product_dimension_with_text_embedding
+        ORDER BY similarity_score DESC
+        LIMIT 200
+    ),
+    filtered_matches AS (
+        SELECT * FROM vector_matches
+         WHERE gender_by_product IN ('women', 'unisex') AND age_by_product = 'adult' AND (LOWER(master_color) LIKE '%tím%' OR LOWER(product_color_name) LIKE '%tím%') AND LOWER(product_name) LIKE '%liền%'
+        ORDER BY similarity_score DESC
+        LIMIT 150
+    )
+    SELECT 
+        internal_ref_code,
+        MAX_BY(magento_ref_code, similarity_score) as magento_ref_code,
+        product_color_code,
+        MAX_BY(product_name, similarity_score) as product_name,
+        MAX_BY(master_color, similarity_score) as master_color,
+        MAX_BY(product_image_url_thumbnail, similarity_score) as product_image_url_thumbnail,
+        MAX_BY(product_web_url, similarity_score) as product_web_url,
+        MAX_BY(sale_price, similarity_score) as sale_price,
+        MAX_BY(original_price, similarity_score) as original_price,
+        MAX_BY(discount_amount, similarity_score) as discount_amount,
+        MAX_BY(discount_percent, similarity_score) as discount_percent,
+        MAX_BY(description_text_full, similarity_score) as description_text_full,
+        MAX_BY(gender_by_product, similarity_score) as gender_by_product,
+        MAX_BY(age_by_product, similarity_score) as age_by_product,
+        MAX_BY(product_line_vn, similarity_score) as product_line_vn,
+        MAX_BY(quantity_sold, similarity_score) as quantity_sold,
+        MAX(similarity_score) as max_score
+    FROM filtered_matches
+    GROUP BY product_color_code, internal_ref_code
+    ORDER BY max_score DESC
+    LIMIT 80
+    
\ No newline at end of file

backend/static/index.html

@@ -735,7 +735,19 @@
                         <span style="font-style: normal;">🤖</span> AI is thinking...
                     </div>
 
+                    <!-- Image Preview Strip -->
+                    <div id="imagePreviewStrip"
+                        style="display: none; padding: 8px 0; gap: 8px; overflow-x: auto; white-space: nowrap;">
+                    </div>
+
                     <div class="input-area">
+                        <input type="file" id="imageFileInput" accept="image/*" style="display: none;"
+                            onchange="handleImageSelect(event)">
+                        <button onclick="document.getElementById('imageFileInput').click()" id="imgBtn"
+                            title="Upload Image (Experimental 📸)"
+                            style="background: #4a4a4a; color: #ccc; padding: 0 14px; border: 1px dashed #666; border-radius: 8px; font-size: 1.2em; cursor: pointer; transition: all 0.2s;"
+                            onmouseover="this.style.background='#5a5a5a'; this.style.borderColor='#667eea'; this.style.color='#667eea'"
+                            onmouseout="this.style.background='#4a4a4a'; this.style.borderColor='#666'; this.style.color='#ccc'">📷</button>
                         <input type="text" id="userInput" placeholder="Type your message..."
                             onkeypress="handleKeyPress(event)" autocomplete="off">
                         <button onclick="sendMessage()" id="sendBtn">➤ Send</button>
@@ -800,7 +812,72 @@
             let isPromptPanelOpen = false;
             let currentPromptTab = 'system';
             let selectedToolPrompt = '';
+            let pendingImages = []; // 📸 Experimental: images to send with next message
+
+            // ==================== IMAGE HANDLING (Experimental) ====================
+            function handleImageSelect(event) {
+                const file = event.target.files[0];
+                if (!file) return;
+                if (file.size > 5 * 1024 * 1024) {
+                    alert('⚠️ Image too large (max 5MB)');
+                    return;
+                }
+                const reader = new FileReader();
+                reader.onload = function (e) {
+                    pendingImages.push(e.target.result); // data:image/...;base64,...
+                    renderImagePreview();
+                };
+                reader.readAsDataURL(file);
+                event.target.value = ''; // Reset so same file can be re-selected
+            }
+
+            function renderImagePreview() {
+                const strip = document.getElementById('imagePreviewStrip');
+                if (pendingImages.length === 0) {
+                    strip.style.display = 'none';
+                    strip.innerHTML = '';
+                    return;
+                }
+                strip.style.display = 'flex';
+                strip.innerHTML = pendingImages.map((img, i) => `
+                    <div style="position: relative; display: inline-block; flex-shrink: 0;">
+                        <img src="${img}" style="height: 60px; border-radius: 8px; border: 1px solid #555; object-fit: cover;">
+                        <button onclick="removePendingImage(${i})" style="position: absolute; top: -5px; right: -5px; background: #d32f2f; color: white; border: none; border-radius: 50%; width: 18px; height: 18px; font-size: 10px; cursor: pointer; line-height: 1;">✕</button>
+                    </div>
+                `).join('') + `<button onclick="clearPendingImages()" style="background: #555; color: #ccc; border: none; border-radius: 6px; padding: 4px 10px; font-size: 0.75em; cursor: pointer; align-self: center;">Clear all</button>`;
+            }
 
+            function removePendingImage(index) {
+                pendingImages.splice(index, 1);
+                renderImagePreview();
+            }
+
+            function clearPendingImages() {
+                pendingImages = [];
+                renderImagePreview();
+            }
+
+            // 📋 Clipboard Paste — Ctrl+V ảnh vào ô chat
+            document.getElementById('userInput').addEventListener('paste', function (e) {
+                const items = (e.clipboardData || e.originalEvent.clipboardData).items;
+                for (const item of items) {
+                    if (item.type.startsWith('image/')) {
+                        e.preventDefault();
+                        const blob = item.getAsFile();
+                        if (blob.size > 5 * 1024 * 1024) {
+                            alert('⚠️ Image too large (max 5MB)');
+                            return;
+                        }
+                        const reader = new FileReader();
+                        reader.onload = function (ev) {
+                            pendingImages.push(ev.target.result);
+                            renderImagePreview();
+                        };
+                        reader.readAsDataURL(blob);
+                        break;
+                    }
+                }
+            });
             async function resetChat() {
                 if (!confirm('Bạn có chắc muốn làm mới cuộc trò chuyện? Lịch sử cũ sẽ được lưu trữ.')) return;
 
@@ -1177,8 +1254,21 @@
                 const messageId = 'hist-' + (msg.id || Date.now() + Math.random());
 
                 if (msg.is_human) {
-                    // User message: simple text
-                    div.innerText = msg.message;
+                    // User message: show images (if any) + text
+                    if (msg.images && msg.images.length > 0) {
+                        const imgStrip = document.createElement('div');
+                        imgStrip.style.cssText = 'display: flex; gap: 6px; margin-bottom: 8px; flex-wrap: wrap;';
+                        msg.images.forEach(src => {
+                            const img = document.createElement('img');
+                            img.src = src;
+                            img.style.cssText = 'max-height: 120px; max-width: 180px; border-radius: 8px; object-fit: cover; border: 1px solid rgba(255,255,255,0.2);';
+                            imgStrip.appendChild(img);
+                        });
+                        div.appendChild(imgStrip);
+                    }
+                    const textSpan = document.createElement('span');
+                    textSpan.innerText = msg.message;
+                    div.appendChild(textSpan);
                 } else {
                     // Bot message: add Widget/Raw JSON toggle
 
@@ -1268,14 +1358,19 @@
                 sendBtn.disabled = true;
                 typingIndicator.style.display = 'block';
 
-                // Add user message immediately
+                // Capture images before clearing
+                const imagesToSend = [...pendingImages];
+
+                // Add user message immediately (with image previews)
                 appendMessage({
                     message: text,
                     is_human: true,
                     timestamp: new Date().toISOString(),
-                    id: 'pending'
+                    id: 'pending',
+                    images: imagesToSend.length > 0 ? imagesToSend : undefined
                 });
                 input.value = '';
+                clearPendingImages(); // Clear image previews after send
                 chatBox.scrollTop = chatBox.scrollHeight;
 
                 // Save config to localStorage
@@ -1301,7 +1396,8 @@
                         headers: headers,
                         body: JSON.stringify({
                             user_query: text,
-                            device_id: deviceId
+                            device_id: deviceId,
+                            ...(imagesToSend.length > 0 && { images: imagesToSend })
                         })
                     });
 
@@ -1573,7 +1669,7 @@
                             limitDiv.style.background = 'rgba(255, 255, 255, 0.05)';
                             limitDiv.style.borderRadius = '6px';
                             limitDiv.style.borderLeft = '3px solid #667eea';
-                            
+
                             const limitText = `📊 Message Limit: ${data.limit_info.used}/${data.limit_info.limit} (Còn ${data.limit_info.remaining} tin nhắn)`;
                             limitDiv.innerText = limitText;
                             botMsgDiv1.appendChild(limitDiv);