feat(bulk-ops): refactor AI search to use Gemini structured outputs and add Preview UI

backend/api/bulk_ops_route.py

+"""
+Bulk Operations API v2 — Search in clean_description + AI-powered bulk field editing.
+Integrates with Codex (Groq LLM) for context-aware content generation per product.
+"""
+
+import asyncio
+import json
+import logging
+import re
+from typing import Optional
+
+import httpx
+from fastapi import APIRouter, BackgroundTasks
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel, Field
+from langchain_core.messages import SystemMessage, HumanMessage
+from common.llm_factory import create_llm
+
+class AiSearchFilter(BaseModel):
+    keywords: list[str] = Field(default=[], description="Từ khóa tìm kiếm trong mô tả (VD: 'cotton', 'co giãn')")
+    product_line: str | None = Field(default=None, description="Dòng sản phẩm xuất hiện trong yêu cầu (VD: 'Áo phông', 'Quần jean')")
+    gender: str | None = Field(default=None, description="Giới tính: Nam, Nữ, Unisex, Bé trai, Bé gái")
+    age_group: str | None = Field(default=None, description="Độ tuổi: adult, kid")
+    color: str | None = Field(default=None, description="Màu sắc (VD: 'đỏ', 'xanh navy')")
+    season: str | None = Field(default=None, description="Mùa: Xuân, Hè, Thu, Đông")
+    occasion: str | None = Field(default=None, description="Dịp đặc biệt (VD: '2/9', 'đi biển')")
+    search_explain: str = Field(default="", description="Giải thích ngắn gọn cách AI hiểu query")
+
+from common.pool_wrapper import get_pooled_connection_compat
+from common.ultra_desc_db import UltraDescriptionDB
+
+logger = logging.getLogger(__name__)
+router = APIRouter(prefix="/api/bulk", tags=["Bulk Operations"])
+
+PG_TABLE = "dashboard_canifa.ultra_descriptions"
+
+# ═══ Groq Config — Reuse from product_desc_route ═══
+GROQ_API_KEYS = [
+    "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",
+    "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",
+    "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",
+    "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",
+    "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",
+    "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",
+]
+_groq_key_index = 0
+
+AI_MODEL = "openai/gpt-oss-120b"
+
+# ═══ Field Labels for dropdown ═══
+FIELD_OPTIONS = {
+    "dip_mac": "Dịp mặc",
+    "phoi_do": "Phối đồ",
+    "mo_ta_chinh": "Mô tả chính",
+    "phong_cach": "Phong cách",
+    "layer": "Gợi ý layering",
+    "cross_sell": "Cross-sell",
+    "ly_do_mua": "Lý do mua",
+    "luu_y_size": "Lưu ý size",
+    "hook_quang_cao": "Hook quảng cáo",
+    "tinh_nang_vai": "Tính năng vải",
+    "tags": "Tags",
+    "mua": "Mùa phù hợp",
+    "nguyen_tac_phoi_do": "Nguyên tắc phối đồ",
+    "tranh_phoi_cung": "Tránh phối cùng",
+    "loi_song": "Lối sống",
+    "tinh_cach": "Tính cách",
+    "tagline": "Tagline",
+    "faq_1_q": "FAQ 1 - Câu hỏi",
+    "faq_1_a": "FAQ 1 - Trả lời",
+    "faq_2_q": "FAQ 2 - Câu hỏi",
+    "faq_2_a": "FAQ 2 - Trả lời",
+    "faq_3_q": "FAQ 3 - Câu hỏi",
+    "faq_3_a": "FAQ 3 - Trả lời",
+}
+
+# ═══ Section grouping for re-rendering clean_description ═══
+_FIELD_LABELS = {
+    "ten_san_pham": "Tên sản phẩm", "tagline": "Tagline", "mo_ta_chinh": "Mô tả chính",
+    "chat_lieu": "Chất liệu", "tinh_nang_vai": "Tính năng vải",
+    "huong_dan_bao_quan": "Hướng dẫn bảo quản", "phong_cach": "Phong cách", "tags": "Tags",
+    "do_tuoi": "Độ tuổi", "gioi_tinh": "Giới tính", "loi_song": "Lối sống",
+    "tinh_cach": "Tính cách", "dip_mac": "Dịp mặc", "phoi_do": "Gợi ý phối đồ",
+    "nguyen_tac_phoi_do": "Nguyên tắc phối đồ", "tranh_phoi_cung": "Tránh phối cùng",
+    "layer": "Gợi ý layering", "mua": "Mùa phù hợp",
+    "faq_1_q": "FAQ 1 - Câu hỏi", "faq_1_a": "FAQ 1 - Trả lời",
+    "faq_2_q": "FAQ 2 - Câu hỏi", "faq_2_a": "FAQ 2 - Trả lời",
+    "faq_3_q": "FAQ 3 - Câu hỏi", "faq_3_a": "FAQ 3 - Trả lời",
+    "hook_quang_cao": "Hook quảng cáo", "cross_sell": "Cross-sell",
+    "ly_do_mua": "Lý do nên mua", "luu_y_size": "Lưu ý chọn size",
+}
+
+_SECTIONS = [
+    ("📦 THÔNG TIN CƠ BẢN", ["ten_san_pham", "tagline", "mo_ta_chinh", "phong_cach", "tags"]),
+    ("🧵 CHẤT LIỆU & BẢO QUẢN", ["chat_lieu", "tinh_nang_vai", "huong_dan_bao_quan"]),
+    ("🎯 ĐỐI TƯỢNG", ["do_tuoi", "gioi_tinh", "loi_song", "tinh_cach"]),
+    ("📅 DỊP MẶC & STYLING", ["dip_mac", "phoi_do", "nguyen_tac_phoi_do", "tranh_phoi_cung", "layer", "mua"]),
+    ("❓ FAQ", ["faq_1_q", "faq_1_a", "faq_2_q", "faq_2_a", "faq_3_q", "faq_3_a"]),
+    ("🛒 HỖ TRỢ BÁN HÀNG", ["hook_quang_cao", "cross_sell", "ly_do_mua", "luu_y_size"]),
+]
+
+
+# ═══ Batch AI Edit State ═══
+BULK_AI_STATE = {
+    "is_running": False,
+    "total": 0,
+    "done": 0,
+    "errors": 0,
+    "current_code": None,
+    "current_name": None,
+    "results": [],  # last results for display
+}
+
+
+# ═══════════════════════════════════════════════════════
+# HELPERS
+# ═══════════════════════════════════════════════════════
+
+def _next_groq_key() -> str:
+    global _groq_key_index
+    key = GROQ_API_KEYS[_groq_key_index % len(GROQ_API_KEYS)]
+    _groq_key_index += 1
+    return key
+
+
+async def _call_codex(messages: list, max_tokens: int = 1000, temperature: float = 0.7) -> str:
+    """Call Groq Codex with multi-key round-robin and model fallback."""
+    model_chain = [AI_MODEL, "openai/gpt-oss-20b", "qwen/qwen3-32b"]
+
+    for attempt_round in range(3):  # max 3 full rounds
+        for model in model_chain:
+            for _ in range(len(GROQ_API_KEYS)):
+                api_key = _next_groq_key()
+                try:
+                    async with httpx.AsyncClient(timeout=25) as client:
+                        resp = await client.post(
+                            "https://api.groq.com/openai/v1/chat/completions",
+                            headers={
+                                "Authorization": f"Bearer {api_key}",
+                                "Content-Type": "application/json",
+                            },
+                            json={
+                                "model": model,
+                                "max_tokens": max_tokens,
+                                "temperature": temperature,
+                                "messages": messages,
+                            },
+                        )
+                        if resp.status_code == 200:
+                            result = resp.json()
+                            if "error" not in result:
+                                return result["choices"][0]["message"]["content"]
+                        elif resp.status_code == 429:
+                            continue  # next key
+                        else:
+                            break  # next model
+                except Exception as e:
+                    logger.warning(f"Codex error: {e}")
+                    break
+
+        await asyncio.sleep(3)
+
+    raise Exception("Codex: tất cả model và key đều thất bại")
+
+
+def _render_description_text(data: dict, product_name: str = "") -> str:
+    """Re-render clean_description from description_data JSON."""
+    if not data:
+        data = {}
+    lines = []
+    title = data.get("ten_san_pham", product_name or "Sản phẩm")
+    lines.append(f"{'=' * 50}")
+    lines.append(f"  {title.upper()}")
+    lines.append(f"{'=' * 50}")
+    lines.append("")
+
+    for section_title, fields in _SECTIONS:
+        section_lines = []
+        for key in fields:
+            val = data.get(key, "")
+            if not val:
+                continue
+            label = _FIELD_LABELS.get(key, key)
+            if key.endswith("_q"):
+                section_lines.append(f"  💬 {val}")
+                continue
+            elif key.endswith("_a"):
+                section_lines.append(f"     → {val}")
+                continue
+            if key == "phoi_do" and "|" in str(val):
+                section_lines.append(f"  {label}:")
+                for combo in str(val).split("|"):
+                    section_lines.append(f"    • {combo.strip()}")
+                continue
+            if key == "ly_do_mua" and "|" in str(val):
+                section_lines.append(f"  {label}:")
+                for reason in str(val).split("|"):
+                    section_lines.append(f"    • {reason.strip()}")
+                continue
+            section_lines.append(f"  {label}: {val}")
+
+        if section_lines:
+            lines.append(f"── {section_title} ──")
+            lines.extend(section_lines)
+            lines.append("")
+        else:
+            lines.append(f"── {section_title} ──")
+            lines.append("  Chưa có dữ liệu.")
+            lines.append("")
+
+    return "\n".join(lines)
+
+
+# ═══════════════════════════════════════════════════════
+# 1. SEARCH — In clean_description (PostgreSQL)
+# ═══════════════════════════════════════════════════════
+
+class BulkSearchRequest(BaseModel):
+    keyword: str
+    limit: int = 100
+
+
+@router.post("/search", summary="Search products by keyword in clean_description")
+async def bulk_search(req: BulkSearchRequest):
+    """Search in clean_description using LIKE. Primary search for AI assistant."""
+    keyword = req.keyword.strip()
+    if not keyword or len(keyword) < 2:
+        return JSONResponse(
+            status_code=400,
+            content={"status": "error", "message": "Keyword phải có ít nhất 2 ký tự"}
+        )
+
+    conn = None
+    try:
+        conn = get_pooled_connection_compat()
+        cur = conn.cursor()
+        cur.execute(
+            f"""SELECT internal_ref_code, product_name, product_image_url, product_line,
+                       phase, status, 
+                       LEFT(clean_description, 300) AS description_preview
+                FROM {PG_TABLE}
+                WHERE LOWER(clean_description) LIKE %s
+                   OR LOWER(product_name) LIKE %s
+                ORDER BY updated_at DESC
+                LIMIT %s""",
+            (f"%{keyword.lower()}%", f"%{keyword.lower()}%", req.limit),
+        )
+        cols = [desc[0] for desc in cur.description]
+        results = [dict(zip(cols, row)) for row in cur.fetchall()]
+        cur.close()
+
+        return {
+            "status": "success",
+            "keyword": keyword,
+            "count": len(results),
+            "results": results,
+        }
+
+    except Exception as e:
+        logger.error(f"Bulk search error: {e}", exc_info=True)
+        return JSONResponse(status_code=500, content={"status": "error", "message": str(e)})
+    finally:
+        if conn:
+            conn.close()
+
+
+# ═══════════════════════════════════════════════════════
+# 1B. AI SEARCH — Agent-style intent parsing + smart SQL
+# ═══════════════════════════════════════════════════════
+
+# Canifa product lines for AI context (fallback static list)
+CANIFA_LINES = [
+    "Áo phông", "Quần soóc", "Áo nỉ", "Váy liền", "Quần nỉ", "Tất", "Áo len",
+    "Bộ mặc nhà", "Bộ quần áo", "Áo Polo", "Chân váy", "Áo nỉ có mũ", "Áo Sơ mi",
+    "Quần jean", "Quần dài", "Áo khoác chần bông", "Quần mặc nhà", "Áo Body",
+    "Quần Khaki", "Áo khoác gió", "Áo khoác dáng ngắn", "Áo kiểu", "Áo len gilet",
+    "Áo khoác gilet chần bông", "Áo giữ nhiệt", "Áo mặc nhà", "Quần lót", "Pyjama",
+    "Áo ba lỗ", "Cardigan", "Bộ thể thao", "Áo khoác chống nắng", "Quần váy",
+    "Blazer", "Áo khoác", "Áo khoác lông vũ", "Quần leggings", "Áo hai dây",
+]
+
+# Attempt to dynamically fetch product lines from DB to override the static list
+try:
+    _conn = get_pooled_connection_compat()
+    _cur = _conn.cursor()
+    _cur.execute(f"SELECT DISTINCT product_line FROM {PG_TABLE} WHERE product_line IS NOT NULL AND product_line != ''")
+    _db_lines = [r[0] for r in _cur.fetchall()]
+    _cur.close()
+    _conn.close()
+    if _db_lines:
+        CANIFA_LINES = _db_lines
+        logger.info(f"✅ Loaded {len(CANIFA_LINES)} product lines dynamically from DB")
+except Exception as e:
+    logger.warning(f"⚠️ Could not load product lines from DB, using fallback. Error: {e}")
+
+AI_SEARCH_SYSTEM = """Bạn là AI phân tích ý định tìm kiếm sản phẩm thời trang Canifa.
+
+Nhiệm vụ: Phân tích câu nhập của người dùng và trích xuất thành JSON filter.
+
+DANH SÁCH DÒNG SẢN PHẨM HỢP LỆ:
+""" + ", ".join(CANIFA_LINES) + """
+
+TRƯỜNG CÓ THỂ TRÍCH XUẤT:
+{
+  "keywords": ["từ khóa tìm trong mô tả"],     // VD: ["cotton", "co giãn"]
+  "product_line": "Dòng SP từ danh sách trên",  // VD: "Áo Polo" (chỉ chọn từ list)
+  "gender": "Nam|Nữ|Unisex|Bé trai|Bé gái",    // null nếu không rõ
+  "age_group": "adult|kid",                      // null nếu không rõ
+  "color": "màu sắc",                           // VD: "đỏ", "xanh navy"
+  "season": "Xuân|Hè|Thu|Đông",                 // null nếu không rõ
+  "occasion": "dịp mặc đặc biệt",              // VD: "2/9", "Tết", "đi làm" — dùng cho step bulk edit sau
+  "search_explain": "giải thích ngắn gọn cách hiểu câu query"
+}
+
+QUY TẮC:
+- Chỉ điền trường nào có thể suy ra từ câu nhập. Không bịa.
+- "bé trai" → gender: "Nam", age_group: "kid"
+- "bé gái" → gender: "Nữ", age_group: "kid"  
+- "trẻ em" → age_group: "kid"
+- "quần bò" → product_line: "Quần jean"
+- "sịp" → product_line: "Quần lót"
+- "áo đỏ" → color: "đỏ", keywords chứa product_line nếu nói rõ loại áo
+- Nếu người dùng nói "cotton", "kháng khuẩn" → đó là keywords tìm trong mô tả
+- Trả về ĐÚNG JSON, không text rác.
+"""
+
+
+class AiSearchRequest(BaseModel):
+    query: str
+    limit: int = 100
+
+
+def _build_ai_search_sql(filters: dict, limit: int, use_jsonb: bool = True) -> tuple[str, list, str]:
+    """
+    Build SQL from AI-parsed filters.
+    Supports 2 modes:
+      - JSONB mode (strict): queries description_data JSONB fields directly
+      - TEXT mode (relaxed): falls back to LIKE on clean_description
+    Returns: (sql_string, params_list, search_mode_label)
+    """
+    clauses = []
+    params = []
+
+    # ── Product line → always use dedicated columns ──
+    product_line = filters.get("product_line")
+    if product_line:
+        clauses.append("(LOWER(product_name) LIKE %s OR LOWER(product_line) LIKE %s)")
+        params.append(f"%{product_line.lower()}%")
+        params.append(f"%{product_line.lower()}%")
+
+    if use_jsonb:
+        # ═══ JSONB STRUCTURED FILTERS ═══
+        # Gender → description_data->>'gioi_tinh'
+        gender = filters.get("gender")
+        if gender:
+            gender_map = {
+                "nam": "Nam", "bé trai": "Nam", "men": "Nam", "boy": "Nam",
+                "nữ": "Nữ", "bé gái": "Nữ", "women": "Nữ", "girl": "Nữ",
+                "unisex": "Unisex",
+            }
+            mapped = gender_map.get(gender.lower(), gender)
+            if mapped in ("Nam", "Nữ"):
+                clauses.append(
+                    "(description_data->>'gioi_tinh' ILIKE %s OR description_data->>'gioi_tinh' ILIKE %s)"
+                )
+                params.extend([f"%{mapped}%", "%Unisex%"])
+            else:
+                clauses.append("description_data->>'gioi_tinh' ILIKE %s")
+                params.append(f"%{mapped}%")
+
+        # Age group → description_data->>'do_tuoi'
+        age_group = filters.get("age_group")
+        if age_group and age_group == "kid":
+            clauses.append(
+                "(description_data->>'do_tuoi' ILIKE %s OR description_data->>'do_tuoi' ILIKE %s "
+                "OR LOWER(product_line) LIKE %s)"
+            )
+            params.extend(["%trẻ%", "%bé%", "%bé%"])
+
+        # Color → LIKE in clean_description (color is spread across text, not a single JSONB field)
+        color = filters.get("color")
+        if color:
+            clauses.append("LOWER(clean_description) LIKE %s")
+            params.append(f"%{color.lower()}%")
+
+        # Season → description_data->>'mua'
+        season = filters.get("season")
+        if season:
+            clauses.append("description_data->>'mua' ILIKE %s")
+            params.append(f"%{season}%")
+
+        # Keywords → LIKE in clean_description (for material keywords like "cotton", "co giãn")
+        keywords = filters.get("keywords", [])
+        if keywords:
+            kw_parts = []
+            for kw in keywords[:5]:
+                kw_parts.append("LOWER(clean_description) LIKE %s")
+                params.append(f"%{kw.lower()}%")
+            clauses.append(f"({' AND '.join(kw_parts)})")
+
+        mode_label = "JSONB structured"
+    else:
+        # ═══ TEXT FALLBACK (relaxed) ═══
+        gender = filters.get("gender")
+        if gender:
+            gender_variants = set()
+            gl = gender.lower()
+            if gl in ("nam", "bé trai"):
+                gender_variants.update(["nam", "unisex"])
+            elif gl in ("nữ", "bé gái"):
+                gender_variants.update(["nữ", "unisex"])
+            else:
+                gender_variants.add(gl)
+            gparts = []
+            for g in gender_variants:
+                gparts.append("LOWER(clean_description) LIKE %s")
+                params.append(f"%{g}%")
+            if gparts:
+                clauses.append(f"({' OR '.join(gparts)})")
+
+        age_group = filters.get("age_group")
+        if age_group and age_group == "kid":
+            clauses.append(
+                "(LOWER(clean_description) LIKE %s OR LOWER(clean_description) LIKE %s)"
+            )
+            params.extend(["%trẻ em%", "%bé%"])
+
+        color = filters.get("color")
+        if color:
+            clauses.append("LOWER(clean_description) LIKE %s")
+            params.append(f"%{color.lower()}%")
+
+        season = filters.get("season")
+        if season:
+            clauses.append("LOWER(clean_description) LIKE %s")
+            params.append(f"%{season.lower()}%")
+
+        keywords = filters.get("keywords", [])
+        if keywords:
+            kw_parts = []
+            for kw in keywords[:5]:
+                kw_parts.append("LOWER(clean_description) LIKE %s")
+                params.append(f"%{kw.lower()}%")
+            clauses.append(f"({' AND '.join(kw_parts)})")
+
+        mode_label = "TEXT fallback"
+
+    where_str = " AND ".join(clauses) if clauses else "1=1"
+
+    sql = f"""SELECT internal_ref_code, product_name, product_image_url, product_line,
+                     phase, status,
+                     LEFT(clean_description, 300) AS description_preview
+              FROM {PG_TABLE}
+              WHERE {where_str}
+              ORDER BY updated_at DESC
+              LIMIT %s"""
+    params.append(limit)
+
+    return sql, params, mode_label
+
+
+@router.post("/ai-search", summary="AI-powered search: parse intent → smart SQL filters")
+async def ai_search(req: AiSearchRequest):
+    """
+    Agent-style search (v2 — JSONB structured filters):
+    1. Send user query to structured Gemini endpoint → extract filters
+    2. Build multi-condition SQL using JSONB operators on description_data
+    3. Progressive relaxation: if JSONB returns 0 → retry with TEXT fallback
+    4. Return matched products + explanation of how AI understood the query
+    """
+    query = req.query.strip()
+    if not query or len(query) < 2:
+        return JSONResponse(
+            status_code=400,
+            content={"status": "error", "message": "Query phải có ít nhất 2 ký tự"}
+        )
+
+    try:
+        # ── Step 1: AI Parse Intent (Structured) ──
+        logger.info(f"🧠 AI Search (Structured): parsing '{query}'...")
+        
+        # Use robust Gemini model with structured output
+        llm = create_llm("gemini-3.1-flash-lite-preview", streaming=False)
+        structured_llm = llm.with_structured_output(AiSearchFilter)
+        
+        messages = [
+            SystemMessage(content=AI_SEARCH_SYSTEM),
+            HumanMessage(content=f"Phân tích câu tìm kiếm: \"{query}\""),
+        ]
+
+        result: AiSearchFilter = await structured_llm.ainvoke(messages)
+        filters = result.model_dump(exclude_none=True)
+        
+        if "keywords" not in filters or filters["keywords"] is None:
+            filters["keywords"] = []
+
+        logger.info(f"🧠 AI Filters: {json.dumps(filters, ensure_ascii=False)}")
+
+        # ── Step 2+3: Build SQL → Execute with progressive relaxation ──
+        results = []
+        search_mode = "JSONB structured"
+
+        conn = None
+        try:
+            conn = get_pooled_connection_compat()
+            cur = conn.cursor()
+
+            # Tier 1: JSONB structured query (strict, precise)
+            sql, params, search_mode = _build_ai_search_sql(filters, req.limit, use_jsonb=True)
+            logger.info(f"🔍 Tier 1 ({search_mode}): {sql[:120]}...")
+            cur.execute(sql, tuple(params))
+            cols = [desc[0] for desc in cur.description]
+            results = [dict(zip(cols, row)) for row in cur.fetchall()]
+
+            # Tier 2: TEXT fallback if JSONB returned too few results
+            if len(results) < 3:
+                logger.info(f"⚠️ Tier 1 returned {len(results)} results, trying TEXT fallback...")
+                sql2, params2, search_mode = _build_ai_search_sql(filters, req.limit, use_jsonb=False)
+                cur.execute(sql2, tuple(params2))
+                cols2 = [desc[0] for desc in cur.description]
+                text_results = [dict(zip(cols2, row)) for row in cur.fetchall()]
+
+                # Merge: keep existing + add new unique results
+                existing_codes = {r["internal_ref_code"] for r in results}
+                for r in text_results:
+                    if r["internal_ref_code"] not in existing_codes:
+                        results.append(r)
+                        existing_codes.add(r["internal_ref_code"])
+                search_mode = "JSONB + TEXT merged"
+
+            cur.close()
+        finally:
+            if conn:
+                conn.close()
+
+        explain = filters.get("search_explain", "")
+        occasion = filters.get("occasion", "")
+
+        logger.info(
+            f"✅ AI Search done: query='{query}', mode={search_mode}, "
+            f"results={len(results)}, filters={json.dumps(filters, ensure_ascii=False)}"
+        )
+
+        return {
+            "status": "success",
+            "query": query,
+            "ai_filters": filters,
+            "explain": explain,
+            "occasion": occasion,
+            "search_mode": search_mode,
+            "count": len(results),
+            "results": results,
+        }
+
+    except Exception as e:
+        logger.error(f"AI Search error: {e}", exc_info=True)
+        return JSONResponse(status_code=500, content={"status": "error", "message": str(e)})
+
+
+# ═══════════════════════════════════════════════════════
+# 2. FIELD OPTIONS — For the widget dropdown
+# ═══════════════════════════════════════════════════════
+
+@router.get("/fields", summary="Get available fields for bulk AI editing")
+async def get_fields():
+    return {"status": "success", "fields": FIELD_OPTIONS}
+
+
+# ═══════════════════════════════════════════════════════
+# 3. AI EDIT — Codex-powered bulk field generation
+# ═══════════════════════════════════════════════════════
+
+class BulkAiEditRequest(BaseModel):
+    codes: list[str]
+    target_field: str          # which field in description_data to edit
+    instruction: str           # Vietnamese instruction for AI
+    mode: str = "append"       # append | overwrite
+
+
+@router.post("/ai-edit", summary="Bulk AI-powered field editing with Codex")
+async def bulk_ai_edit(req: BulkAiEditRequest, background_tasks: BackgroundTasks):
+    """
+    Use Codex to generate context-aware content for a specific field
+    across multiple products. Runs in background.
+    """
+    if not req.codes:
+        return JSONResponse(status_code=400, content={"status": "error", "message": "Trống codes"})
+    if req.target_field not in FIELD_OPTIONS and req.target_field not in _FIELD_LABELS:
+        return JSONResponse(status_code=400, content={
+            "status": "error",
+            "message": f"Trường '{req.target_field}' không hợp lệ. Chọn: {', '.join(FIELD_OPTIONS.keys())}"
+        })
+    if not req.instruction.strip():
+        return JSONResponse(status_code=400, content={"status": "error", "message": "Thiếu instruction"})
+    if BULK_AI_STATE["is_running"]:
+        return JSONResponse(status_code=409, content={
+            "status": "error", "message": "Đang có task AI chạy. Vui lòng đợi hoàn tất."
+        })
+
+    # Start background task
+    BULK_AI_STATE.update({
+        "is_running": True,
+        "total": len(req.codes),
+        "done": 0,
+        "errors": 0,
+        "current_code": None,
+        "current_name": None,
+        "results": [],
+    })
+
+    background_tasks.add_task(
+        _run_bulk_ai_edit, req.codes, req.target_field, req.instruction, req.mode
+    )
+
+    return {
+        "status": "success",
+        "message": f"Đã bắt đầu AI sinh nội dung cho {len(req.codes)} SP, trường '{FIELD_OPTIONS.get(req.target_field, req.target_field)}'. Chạy nền...",
+        "total": len(req.codes),
+    }
+
+
+@router.post("/ai-edit-preview", summary="Preview AI generated content for a single product")
+async def bulk_ai_edit_preview(req: BulkAiEditRequest):
+    """
+    Run Codex on ONE product and return the old and new text without saving to the DB.
+    Provides a quick UI preview before running the background bulk task.
+    """
+    if not req.codes:
+         return JSONResponse(status_code=400, content={"status": "error", "message": "Trống codes"})
+         
+    code = req.codes[0] # Just take the first one
+    target_field = req.target_field
+    instruction = req.instruction
+    mode = req.mode
+    
+    field_label = FIELD_OPTIONS.get(target_field, _FIELD_LABELS.get(target_field, target_field))
+    
+    conn = None
+    try:
+        conn = get_pooled_connection_compat()
+        cur = conn.cursor()
+        cur.execute(
+            f"SELECT internal_ref_code, product_name, product_line, description_data FROM {PG_TABLE} WHERE internal_ref_code = %s",
+            (code,)
+        )
+        cols = [desc[0] for desc in cur.description]
+        row = cur.fetchone()
+        cur.close()
+        
+        if not row:
+            return JSONResponse(status_code=404, content={"status": "error", "message": "Không tìm thấy sản phẩm"})
+            
+        product = dict(zip(cols, row))
+        desc_data = product.get("description_data", {})
+        if isinstance(desc_data, str):
+            try:
+                desc_data = json.loads(desc_data)
+            except Exception:
+                desc_data = {}
+                
+        current_value = desc_data.get(target_field, "")
+        
+        # Build context for AI
+        context_fields = {
+            "ten_san_pham": desc_data.get("ten_san_pham", product.get("product_name", "")),
+            "phong_cach": desc_data.get("phong_cach", ""),
+            "chat_lieu": desc_data.get("chat_lieu", ""),
+            "gioi_tinh": desc_data.get("gioi_tinh", ""),
+            "mua": desc_data.get("mua", ""),
+            "do_tuoi": desc_data.get("do_tuoi", ""),
+            "product_line": product.get("product_line", ""),
+        }
+        context_str = "\n".join(f"- {k}: {v}" for k, v in context_fields.items() if v)
+        
+        if mode == "append" and current_value:
+            prompt = f"""Bạn là Stylist thời trang Canifa. Dựa trên thông tin sản phẩm dưới đây, hãy BỔ SUNG thêm nội dung cho trường "{field_label}".
+
+THÔNG TIN SẢN KHẨM:
+{context_str}
+
+GIÁ TRỊ HIỆN TẠI của trường "{field_label}":
+{current_value}
+
+YÊU CẦU BỔ SUNG:
+{instruction}
+
+QUY TẮC:
+- GIỮ NGUYÊN nội dung cũ, CHỈ THÊM phần mới vào
+- Viết tự nhiên, phù hợp với sản phẩm cụ thể này
+- Dùng cùng format/style với nội dung cũ (nếu dùng dấu · thì thêm cũng dùng dấu ·)
+- Trả về TOÀN BỘ nội dung trường (cũ + mới), KHÔNG giải thích
+
+Trả về chỉ nội dung trường, không có gì khác."""
+        else:
+            prompt = f"""Bạn là Stylist thời trang Canifa. Dựa trên thông tin sản phẩm dưới đây, hãy VIẾT nội dung cho trường "{field_label}".
+
+THÔNG TIN SẢN PHẨM:
+{context_str}
+
+YÊU CẦU:
+{instruction}
+
+QUY TẮC:
+- Viết tự nhiên, phù hợp với sản phẩm cụ thể này
+- Phong cách giống Stylist thời trang cao cấp
+- Trả về chỉ nội dung trường, KHÔNG giải thích
+
+Trả về chỉ nội dung trường, không có gì khác."""
+            
+        messages = [
+            {"role": "system", "content": "Bạn là AI phụ trách nội dung sản phẩm thời trang Canifa. Trả lời ngắn gọn, chỉ trả về nội dung được yêu cầu."},
+            {"role": "user", "content": prompt},
+        ]
+
+        logger.info(f"👀 Preview for code: {code}")
+        ai_output = await _call_codex(messages, max_tokens=500, temperature=0.7)
+        new_value = ai_output.strip().strip('"').strip("'")
+        
+        return {
+            "status": "success",
+            "code": code,
+            "name": product.get("product_name", ""),
+            "old_value": current_value,
+            "new_value": new_value
+        }
+    except Exception as e:
+        logger.error(f"Preview error: {e}", exc_info=True)
+        return {"status": "error", "message": str(e)}
+    finally:
+        if conn:
+            conn.close()
+
+
+async def _run_bulk_ai_edit(codes: list[str], target_field: str, instruction: str, mode: str):
+    """Background worker: process each product with Codex."""
+    field_label = FIELD_OPTIONS.get(target_field, _FIELD_LABELS.get(target_field, target_field))
+
+    for code in codes:
+        BULK_AI_STATE["current_code"] = code
+        conn = None
+        try:
+            # 1. Fetch product data from PostgreSQL
+            conn = get_pooled_connection_compat()
+            cur = conn.cursor()
+            cur.execute(
+                f"SELECT internal_ref_code, product_name, product_line, description_data, clean_description FROM {PG_TABLE} WHERE internal_ref_code = %s",
+                (code,)
+            )
+            cols = [desc[0] for desc in cur.description]
+            row = cur.fetchone()
+            cur.close()
+
+            if not row:
+                BULK_AI_STATE["errors"] += 1
+                BULK_AI_STATE["results"].append({"code": code, "status": "not_found"})
+                continue
+
+            product = dict(zip(cols, row))
+            BULK_AI_STATE["current_name"] = product.get("product_name", "")
+
+            # 2. Parse description_data
+            desc_data = product.get("description_data", {})
+            if isinstance(desc_data, str):
+                try:
+                    desc_data = json.loads(desc_data)
+                except Exception:
+                    desc_data = {}
+
+            current_value = desc_data.get(target_field, "")
+
+            # 3. Build context for AI
+            context_fields = {
+                "ten_san_pham": desc_data.get("ten_san_pham", product.get("product_name", "")),
+                "phong_cach": desc_data.get("phong_cach", ""),
+                "chat_lieu": desc_data.get("chat_lieu", ""),
+                "gioi_tinh": desc_data.get("gioi_tinh", ""),
+                "mua": desc_data.get("mua", ""),
+                "do_tuoi": desc_data.get("do_tuoi", ""),
+                "product_line": product.get("product_line", ""),
+            }
+            context_str = "\n".join(f"- {k}: {v}" for k, v in context_fields.items() if v)
+
+            # 4. Call Codex
+            if mode == "append" and current_value:
+                prompt = f"""Bạn là Stylist thời trang Canifa. Dựa trên thông tin sản phẩm dưới đây, hãy BỔ SUNG thêm nội dung cho trường "{field_label}".
+
+THÔNG TIN SẢN PHẨM:
+{context_str}
+
+GIÁ TRỊ HIỆN TẠI của trường "{field_label}":
+{current_value}
+
+YÊU CẦU BỔ SUNG:
+{instruction}
+
+QUY TẮC:
+- GIỮ NGUYÊN nội dung cũ, CHỈ THÊM phần mới vào
+- Viết tự nhiên, phù hợp với sản phẩm cụ thể này
+- Dùng cùng format/style với nội dung cũ (nếu dùng dấu · thì thêm cũng dùng dấu ·)
+- Trả về TOÀN BỘ nội dung trường (cũ + mới), KHÔNG giải thích
+
+Trả về chỉ nội dung trường, không có gì khác."""
+            else:
+                prompt = f"""Bạn là Stylist thời trang Canifa. Dựa trên thông tin sản phẩm dưới đây, hãy VIẾT nội dung cho trường "{field_label}".
+
+THÔNG TIN SẢN PHẨM:
+{context_str}
+
+YÊU CẦU:
+{instruction}
+
+QUY TẮC:
+- Viết tự nhiên, phù hợp với sản phẩm cụ thể này
+- Phong cách giống Stylist thời trang cao cấp
+- Trả về chỉ nội dung trường, KHÔNG giải thích
+
+Trả về chỉ nội dung trường, không có gì khác."""
+
+            messages = [
+                {"role": "system", "content": "Bạn là AI phụ trách nội dung sản phẩm thời trang Canifa. Trả lời ngắn gọn, chỉ trả về nội dung được yêu cầu."},
+                {"role": "user", "content": prompt},
+            ]
+
+            ai_output = await _call_codex(messages, max_tokens=500, temperature=0.7)
+            new_value = ai_output.strip().strip('"').strip("'")
+
+            # 5. Update description_data
+            desc_data[target_field] = new_value
+
+            # 6. Re-render clean_description
+            new_clean = _render_description_text(desc_data, product.get("product_name", ""))
+
+            # 7. Save back to DB
+            conn2 = get_pooled_connection_compat()
+            cur2 = conn2.cursor()
+            cur2.execute(
+                f"UPDATE {PG_TABLE} SET description_data = %s::jsonb, clean_description = %s, updated_at = NOW() WHERE internal_ref_code = %s",
+                (json.dumps(desc_data, ensure_ascii=False), new_clean, code)
+            )
+            cur2.close()
+            conn2.close()
+
+            BULK_AI_STATE["done"] += 1
+            BULK_AI_STATE["results"].append({
+                "code": code,
+                "name": product.get("product_name", ""),
+                "status": "success",
+                "field": target_field,
+                "old_value": current_value[:100] if current_value else "",
+                "new_value": new_value[:150],
+            })
+
+            logger.info(f"✅ AI edit [{BULK_AI_STATE['done']}/{BULK_AI_STATE['total']}] {code} → {target_field}")
+
+        except Exception as e:
+            BULK_AI_STATE["errors"] += 1
+            BULK_AI_STATE["results"].append({"code": code, "status": "error", "error": str(e)})
+            logger.error(f"❌ AI edit error for {code}: {e}")
+
+        finally:
+            if conn:
+                try:
+                    conn.close()
+                except Exception:
+                    pass
+
+    # Done
+    BULK_AI_STATE["is_running"] = False
+    BULK_AI_STATE["current_code"] = None
+    BULK_AI_STATE["current_name"] = None
+    logger.info(f"🏁 Bulk AI edit completed: {BULK_AI_STATE['done']}/{BULK_AI_STATE['total']} (errors: {BULK_AI_STATE['errors']})")
+
+
+# ═══════════════════════════════════════════════════════
+# 4. AI EDIT STATUS — Poll progress
+# ═══════════════════════════════════════════════════════
+
+@router.get("/ai-edit-status", summary="Get progress of bulk AI edit")
+async def ai_edit_status():
+    return BULK_AI_STATE
+
+
+# ═══════════════════════════════════════════════════════
+# 5. SIMPLE BULK UPDATE — Static text (keep from v1)
+# ═══════════════════════════════════════════════════════
+
+class BulkUpdateRequest(BaseModel):
+    codes: list[str]
+    action: str       # append | prepend | replace | remove
+    text: str = ""
+    find: str = ""
+    replace_with: str = ""
+
+
+@router.post("/update", summary="Bulk update clean_description with static text")
+async def bulk_update(req: BulkUpdateRequest):
+    """Simple bulk text operations (non-AI). For quick static edits."""
+    if not req.codes:
+        return JSONResponse(status_code=400, content={"status": "error", "message": "Trống codes"})
+
+    conn = None
+    updated = 0
+    errors = []
+
+    try:
+        conn = get_pooled_connection_compat()
+        cur = conn.cursor()
+
+        for code in req.codes:
+            try:
+                cur.execute(
+                    f"SELECT clean_description FROM {PG_TABLE} WHERE internal_ref_code = %s",
+                    (code,)
+                )
+                row = cur.fetchone()
+                if not row:
+                    errors.append({"code": code, "error": "Không tìm thấy"})
+                    continue
+
+                current_text = row[0] or ""
+
+                if req.action == "append":
+                    new_text = current_text + "\n" + req.text
+                elif req.action == "prepend":
+                    new_text = req.text + "\n" + current_text
+                elif req.action == "replace":
+                    new_text = current_text.replace(req.find, req.replace_with) if req.find else current_text
+                elif req.action == "remove":
+                    new_text = current_text.replace(req.text, "")
+                else:
+                    continue
+
+                cur.execute(
+                    f"UPDATE {PG_TABLE} SET clean_description = %s, updated_at = NOW() WHERE internal_ref_code = %s",
+                    (new_text.strip(), code)
+                )
+                updated += 1
+            except Exception as e:
+                errors.append({"code": code, "error": str(e)})
+
+        cur.close()
+        return {
+            "status": "success",
+            "message": f"Đã cập nhật {updated}/{len(req.codes)} sản phẩm",
+            "updated": updated,
+            "total": len(req.codes),
+            "errors": errors,
+        }
+    except Exception as e:
+        return JSONResponse(status_code=500, content={"status": "error", "message": str(e)})
+    finally:
+        if conn:
+            conn.close()

backend/static/css/ai-assistant.css

+/* ═══════════════════════════════════════════════════════════
+   AI Assistant — Floating Chat Widget
+   Premium glassmorphism design for Canifa Admin Console
+   ═══════════════════════════════════════════════════════════ */
+
+/* ── Bubble Button ── */
+.ai-bubble {
+    position: fixed;
+    bottom: 24px;
+    right: 24px;
+    width: 56px;
+    height: 56px;
+    border-radius: 50%;
+    background: linear-gradient(135deg, #3b5998 0%, #2d4a7a 100%);
+    color: #fff;
+    border: none;
+    cursor: pointer;
+    z-index: 9998;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-size: 24px;
+    box-shadow:
+        0 4px 16px rgba(59, 89, 152, 0.35),
+        0 2px 6px rgba(0, 0, 0, 0.12);
+    transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
+    animation: ai-bubble-pulse 3s ease-in-out infinite;
+}
+.ai-bubble:hover {
+    transform: scale(1.1);
+    box-shadow:
+        0 6px 24px rgba(59, 89, 152, 0.5),
+        0 3px 8px rgba(0, 0, 0, 0.15);
+}
+.ai-bubble:active {
+    transform: scale(0.95);
+}
+.ai-bubble.open {
+    animation: none;
+    transform: rotate(0deg);
+}
+.ai-bubble .bubble-icon { transition: transform 0.3s ease; }
+.ai-bubble.open .bubble-icon { transform: rotate(45deg); }
+
+@keyframes ai-bubble-pulse {
+    0%, 100% { box-shadow: 0 4px 16px rgba(59, 89, 152, 0.35), 0 2px 6px rgba(0, 0, 0, 0.12); }
+    50% { box-shadow: 0 4px 24px rgba(59, 89, 152, 0.55), 0 2px 8px rgba(0, 0, 0, 0.18), 0 0 0 8px rgba(59, 89, 152, 0.08); }
+}
+
+/* ── Notification dot ── */
+.ai-bubble-dot {
+    position: absolute;
+    top: 2px;
+    right: 2px;
+    width: 12px;
+    height: 12px;
+    background: #ef4444;
+    border-radius: 50%;
+    border: 2px solid #fff;
+    display: none;
+}
+
+/* ── Chat Panel ── */
+.ai-panel {
+    position: fixed;
+    bottom: 92px;
+    right: 24px;
+    width: 420px;
+    max-width: calc(100vw - 48px);
+    height: 580px;
+    max-height: calc(100vh - 120px);
+    background: #fff;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 16px;
+    box-shadow:
+        0 12px 48px rgba(0, 0, 0, 0.12),
+        0 4px 16px rgba(0, 0, 0, 0.06);
+    z-index: 9999;
+    display: flex;
+    flex-direction: column;
+    overflow: hidden;
+    opacity: 0;
+    transform: translateY(20px) scale(0.95);
+    pointer-events: none;
+    transition: all 0.35s cubic-bezier(0.4, 0, 0.2, 1);
+}
+.ai-panel.open {
+    opacity: 1;
+    transform: translateY(0) scale(1);
+    pointer-events: auto;
+}
+
+/* ── Panel Header ── */
+.ai-panel-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 14px 18px;
+    background: linear-gradient(135deg, #3b5998 0%, #2d4a7a 100%);
+    color: #fff;
+    flex-shrink: 0;
+}
+.ai-panel-header .header-left {
+    display: flex;
+    align-items: center;
+    gap: 10px;
+}
+.ai-panel-header .header-avatar {
+    width: 32px;
+    height: 32px;
+    border-radius: 50%;
+    background: rgba(255, 255, 255, 0.2);
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-size: 16px;
+}
+.ai-panel-header .header-info h3 {
+    margin: 0;
+    font-size: 14px;
+    font-weight: 700;
+}
+.ai-panel-header .header-info span {
+    font-size: 11px;
+    opacity: 0.8;
+}
+.ai-panel-header .header-actions {
+    display: flex;
+    gap: 6px;
+}
+.ai-panel-header .header-actions button {
+    background: rgba(255, 255, 255, 0.15);
+    border: none;
+    color: #fff;
+    width: 30px;
+    height: 30px;
+    border-radius: 8px;
+    cursor: pointer;
+    font-size: 13px;
+    transition: background 0.2s;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+}
+.ai-panel-header .header-actions button:hover {
+    background: rgba(255, 255, 255, 0.3);
+}
+
+/* ── Quick Actions Bar ── */
+.ai-quick-actions {
+    display: flex;
+    gap: 6px;
+    padding: 10px 14px;
+    background: #f8f7f4;
+    border-bottom: 1px solid var(--border, #e7e5e2);
+    flex-shrink: 0;
+    overflow-x: auto;
+}
+.ai-quick-actions::-webkit-scrollbar { height: 0; }
+.ai-quick-btn {
+    padding: 5px 12px;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 20px;
+    background: #fff;
+    font-size: 11px;
+    font-weight: 600;
+    cursor: pointer;
+    white-space: nowrap;
+    color: var(--secondary-fg, #57534e);
+    transition: all 0.2s;
+}
+.ai-quick-btn:hover {
+    background: var(--primary, #3b5998);
+    color: #fff;
+    border-color: var(--primary, #3b5998);
+}
+
+/* ── Messages Area ── */
+.ai-messages {
+    flex: 1;
+    overflow-y: auto;
+    padding: 16px;
+    display: flex;
+    flex-direction: column;
+    gap: 12px;
+    background: #faf9f7;
+    min-height: 0;
+}
+.ai-messages::-webkit-scrollbar { width: 4px; }
+.ai-messages::-webkit-scrollbar-thumb { background: #d6d3ce; border-radius: 4px; }
+
+/* ── Message Bubble ── */
+.ai-msg {
+    display: flex;
+    gap: 8px;
+    max-width: 92%;
+    animation: msg-in 0.3s ease;
+}
+@keyframes msg-in {
+    from { opacity: 0; transform: translateY(8px); }
+    to { opacity: 1; transform: translateY(0); }
+}
+.ai-msg.bot { align-self: flex-start; }
+.ai-msg.user { align-self: flex-end; flex-direction: row-reverse; }
+
+.ai-msg-avatar {
+    width: 28px;
+    height: 28px;
+    border-radius: 50%;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-size: 13px;
+    flex-shrink: 0;
+    margin-top: 2px;
+}
+.ai-msg.bot .ai-msg-avatar {
+    background: linear-gradient(135deg, #3b5998, #2d4a7a);
+    color: #fff;
+}
+.ai-msg.user .ai-msg-avatar {
+    background: var(--muted, #f0efec);
+    color: var(--muted-fg, #78716c);
+}
+
+.ai-msg-body {
+    padding: 10px 14px;
+    border-radius: 14px;
+    font-size: 13px;
+    line-height: 1.55;
+    word-break: break-word;
+}
+.ai-msg.bot .ai-msg-body {
+    background: #fff;
+    color: var(--foreground, #1c1917);
+    border: 1px solid var(--border, #e7e5e2);
+    border-top-left-radius: 4px;
+}
+.ai-msg.user .ai-msg-body {
+    background: var(--primary, #3b5998);
+    color: #fff;
+    border-top-right-radius: 4px;
+}
+
+/* ── Search Results inside chat ── */
+.ai-search-results {
+    margin-top: 8px;
+    max-height: 280px;
+    overflow-y: auto;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 10px;
+    background: #fff;
+}
+.ai-search-results::-webkit-scrollbar { width: 3px; }
+.ai-search-results::-webkit-scrollbar-thumb { background: #d6d3ce; border-radius: 3px; }
+
+.ai-result-item {
+    display: flex;
+    align-items: center;
+    gap: 10px;
+    padding: 8px 12px;
+    border-bottom: 1px solid #f0efec;
+    cursor: pointer;
+    transition: background 0.15s;
+}
+.ai-result-item:last-child { border-bottom: none; }
+.ai-result-item:hover { background: #f8f7f4; }
+
+.ai-result-item input[type="checkbox"] {
+    width: 16px;
+    height: 16px;
+    accent-color: var(--primary, #3b5998);
+    flex-shrink: 0;
+    cursor: pointer;
+}
+.ai-result-item img {
+    width: 36px;
+    height: 36px;
+    border-radius: 6px;
+    object-fit: cover;
+    flex-shrink: 0;
+    background: var(--muted, #f0efec);
+    border: 1px solid var(--border, #e7e5e2);
+}
+.ai-result-info {
+    flex: 1;
+    min-width: 0;
+}
+.ai-result-name {
+    font-size: 12px;
+    font-weight: 600;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.ai-result-code {
+    font-size: 10px;
+    color: var(--muted-fg, #78716c);
+    font-family: var(--font-mono, monospace);
+}
+.ai-result-status {
+    font-size: 10px;
+    font-weight: 600;
+    padding: 2px 8px;
+    border-radius: 12px;
+    flex-shrink: 0;
+}
+.ai-result-status.done { background: #ecfdf5; color: #16a34a; }
+.ai-result-status.pending { background: #fff3cd; color: #856404; }
+.ai-result-status.missing { background: #fef2f2; color: #dc2626; }
+
+/* ── Bulk Action Bar (appears after search) ── */
+.ai-bulk-bar {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 12px;
+    background: #eef1f8;
+    border-top: 1px solid var(--border, #e7e5e2);
+    font-size: 12px;
+    flex-shrink: 0;
+}
+.ai-bulk-bar .bulk-count {
+    font-weight: 700;
+    color: var(--primary, #3b5998);
+}
+.ai-bulk-bar select {
+    flex: 1;
+    padding: 6px 8px;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 6px;
+    font-size: 12px;
+    background: #fff;
+    outline: none;
+}
+.ai-bulk-bar button {
+    padding: 6px 14px;
+    border: none;
+    border-radius: 6px;
+    background: var(--primary, #3b5998);
+    color: #fff;
+    font-size: 12px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: background 0.2s;
+    white-space: nowrap;
+}
+.ai-bulk-bar button:hover { background: var(--primary-hover, #2d4a7a); }
+
+/* ── Input Area ── */
+.ai-input-area {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 12px 14px;
+    border-top: 1px solid var(--border, #e7e5e2);
+    background: #fff;
+    flex-shrink: 0;
+}
+.ai-input-area input {
+    flex: 1;
+    padding: 10px 14px;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 10px;
+    font: inherit;
+    font-size: 13px;
+    outline: none;
+    transition: border-color 0.2s, box-shadow 0.2s;
+    background: #faf9f7;
+}
+.ai-input-area input:focus {
+    border-color: var(--primary, #3b5998);
+    box-shadow: 0 0 0 3px rgba(59, 89, 152, 0.08);
+    background: #fff;
+}
+.ai-input-area input::placeholder { color: #a8a29e; }
+.ai-send-btn {
+    width: 40px;
+    height: 40px;
+    border-radius: 10px;
+    border: none;
+    background: var(--primary, #3b5998);
+    color: #fff;
+    cursor: pointer;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-size: 16px;
+    transition: all 0.2s;
+    flex-shrink: 0;
+}
+.ai-send-btn:hover { background: var(--primary-hover, #2d4a7a); transform: scale(1.05); }
+.ai-send-btn:disabled { opacity: 0.5; cursor: not-allowed; transform: none; }
+
+/* ── Typing indicator ── */
+.ai-typing {
+    display: flex;
+    gap: 4px;
+    padding: 12px 14px;
+    align-self: flex-start;
+}
+.ai-typing-dot {
+    width: 7px;
+    height: 7px;
+    background: #a8a29e;
+    border-radius: 50%;
+    animation: typing-bounce 1.4s infinite ease-in-out;
+}
+.ai-typing-dot:nth-child(2) { animation-delay: 0.2s; }
+.ai-typing-dot:nth-child(3) { animation-delay: 0.4s; }
+@keyframes typing-bounce {
+    0%, 80%, 100% { transform: translateY(0); }
+    40% { transform: translateY(-6px); }
+}
+
+/* ── Bulk Edit Modal (inside chat) ── */
+.ai-edit-modal {
+    margin-top: 8px;
+    padding: 12px;
+    background: #fff;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 10px;
+}
+.ai-edit-modal label {
+    display: block;
+    font-size: 11px;
+    font-weight: 700;
+    color: var(--muted-fg, #78716c);
+    margin-bottom: 4px;
+    text-transform: uppercase;
+    letter-spacing: 0.03em;
+}
+.ai-edit-modal select,
+.ai-edit-modal input,
+.ai-edit-modal textarea {
+    width: 100%;
+    padding: 8px 10px;
+    border: 1px solid var(--border, #e7e5e2);
+    border-radius: 8px;
+    font: inherit;
+    font-size: 12px;
+    outline: none;
+    margin-bottom: 8px;
+    resize: vertical;
+}
+.ai-edit-modal textarea { min-height: 60px; }
+.ai-edit-modal select:focus,
+.ai-edit-modal input:focus,
+.ai-edit-modal textarea:focus {
+    border-color: var(--primary, #3b5998);
+}
+.ai-edit-actions {
+    display: flex;
+    gap: 6px;
+    justify-content: flex-end;
+}
+.ai-edit-actions button {
+    padding: 6px 16px;
+    border: none;
+    border-radius: 6px;
+    font-size: 12px;
+    font-weight: 600;
+    cursor: pointer;
+    transition: background 0.2s;
+}
+.ai-edit-actions .btn-preview {
+    background: #f0efec;
+    color: #57534e;
+}
+.ai-edit-actions .btn-preview:hover { background: #e7e5e2; }
+.ai-edit-actions .btn-apply {
+    background: #16a34a;
+    color: #fff;
+}
+.ai-edit-actions .btn-apply:hover { background: #15803d; }
+
+/* ── Responsive ── */
+@media (max-width: 480px) {
+    .ai-panel {
+        width: calc(100vw - 16px);
+        right: 8px;
+        bottom: 80px;
+        height: calc(100vh - 100px);
+        border-radius: 12px;
+    }
+    .ai-bubble {
+        right: 16px;
+        bottom: 16px;
+        width: 50px;
+        height: 50px;
+    }
+}
+
+/* ── Progress Bar ── */
+.ai-progress-bar {
+    padding: 10px 14px;
+    background: #eef1f8;
+    border-top: 1px solid var(--border, #e7e5e2);
+    flex-shrink: 0;
+}
+.ai-progress-bar .progress-info {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    font-size: 11px;
+    margin-bottom: 6px;
+    color: var(--foreground, #1c1917);
+}
+.ai-progress-bar .progress-name {
+    font-size: 10px;
+    color: var(--muted-fg, #78716c);
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    max-width: 180px;
+}
+.ai-progress-bar .progress-track {
+    width: 100%;
+    height: 6px;
+    background: #e7e5e2;
+    border-radius: 3px;
+    overflow: hidden;
+}
+.ai-progress-bar .progress-fill {
+    height: 100%;
+    background: linear-gradient(90deg, #3b5998, #16a34a);
+    border-radius: 3px;
+    width: 0%;
+    transition: width 0.5s ease;
+}
+
+/* ── AI Sinh Button (accent green) ── */
+.bulk-ai-btn {
+    background: #16a34a !important;
+    font-weight: 700 !important;
+}
+.bulk-ai-btn:hover {
+    background: #15803d !important;
+}
+
+/* ── AI Filter Tags (Agent search results) ── */
+.ai-filter-tags {
+    padding: 8px 10px;
+    background: #f8fafc;
+    border-radius: 8px;
+    border: 1px solid #e2e8f0;
+    margin-bottom: 8px;
+}
+.ai-filter-explain {
+    font-size: 11px;
+    color: #64748b;
+    font-style: italic;
+}
+.ai-tag {
+    display: inline-flex;
+    align-items: center;
+    gap: 2px;
+    padding: 2px 8px;
+    border-radius: 12px;
+    font-size: 11px;
+    font-weight: 600;
+    white-space: nowrap;
+}
+.ai-tag.product { background: #dbeafe; color: #1d4ed8; }
+.ai-tag.color   { background: #fce7f3; color: #be185d; }
+.ai-tag.gender  { background: #f3e8ff; color: #7c3aed; }
+.ai-tag.age     { background: #fef3c7; color: #b45309; }
+.ai-tag.season  { background: #d1fae5; color: #047857; }
+.ai-tag.occasion{ background: #fee2e2; color: #dc2626; }
+.ai-tag.keyword { background: #e0e7ff; color: #4338ca; }

backend/static/js/ai-assistant.js

+/**
+ * AI Assistant v3 — Agent-Style Search + Codex Bulk Edit
+ * Features: AI intent parsing → smart SQL filters, bulk field editing
+ */
+
+(function () {
+    'use strict';
+
+    // ═══ STATE ═══
+    let panelOpen = false;
+    let searchResults = [];
+    let selectedCodes = new Set();
+    let currentMode = 'idle'; // idle | searching | searched | ai_running
+    let pollTimer = null;
+    let fieldOptions = {};
+    let lastAiFilters = null;
+    let lastOccasion = '';
+
+    // ═══ DOM CREATION ═══
+    function createWidget() {
+        // ── Bubble ──
+        const bubble = document.createElement('button');
+        bubble.className = 'ai-bubble';
+        bubble.id = 'aiBubble';
+        bubble.title = 'AI Assistant — Tìm & Sinh Mô Tả Hàng Loạt';
+        bubble.innerHTML = '<span class="bubble-icon">✦</span><span class="ai-bubble-dot" id="aiBubbleDot"></span>';
+        bubble.onclick = togglePanel;
+
+        // ── Panel ──
+        const panel = document.createElement('div');
+        panel.className = 'ai-panel';
+        panel.id = 'aiPanel';
+        panel.innerHTML = `
+            <div class="ai-panel-header">
+                <div class="header-left">
+                    <div class="header-avatar">✦</div>
+                    <div class="header-info">
+                        <h3>Canifa AI</h3>
+                        <span>Agent Search + Sinh mô tả</span>
+                    </div>
+                </div>
+                <div class="header-actions">
+                    <button onclick="window._ai.clearChat()" title="Xóa chat">🗑</button>
+                    <button onclick="window._ai.togglePanel()" title="Đóng">✕</button>
+                </div>
+            </div>
+
+            <div class="ai-quick-actions" id="aiQuickActions">
+                <button class="ai-quick-btn" onclick="window._ai.qSearch('áo màu đỏ cho bé trai')">🔴 Áo đỏ bé trai</button>
+                <button class="ai-quick-btn" onclick="window._ai.qSearch('váy cotton bé gái mùa hè')">👗 Váy bé gái</button>
+                <button class="ai-quick-btn" onclick="window._ai.qSearch('polo nam đi làm')">👔 Polo nam</button>
+                <button class="ai-quick-btn" onclick="window._ai.qSearch('áo khoác mùa đông')">🧥 Khoác đông</button>
+                <button class="ai-quick-btn" onclick="window._ai.showHelp()">❓ Help</button>
+            </div>
+
+            <div class="ai-messages" id="aiMessages">
+                <div class="ai-msg bot">
+                    <div class="ai-msg-avatar">✦</div>
+                    <div class="ai-msg-body">
+                        <strong>Chào bro!</strong> 🤖<br><br>
+                        Tao là AI Assistant tích hợp <strong>Codex Agent</strong>.<br>
+                        Gõ <strong>câu tự nhiên</strong> — AI sẽ hiểu ý và tìm SP thông minh:<br><br>
+                        VD: <em>"tìm áo đỏ cho bé trai phù hợp 2/9"</em><br>
+                        → AI hiểu: <strong>Áo + đỏ + bé trai + trẻ em</strong><br>
+                        → Tìm đúng SP, rồi cho AI sinh nội dung hàng loạt 🔥
+                    </div>
+                </div>
+            </div>
+
+            <div class="ai-bulk-bar" id="aiBulkBar" style="display:none;">
+                <span>Đã chọn: <strong class="bulk-count" id="aiBulkCount">0</strong></span>
+                <button onclick="window._ai.selectAll()">✅ All</button>
+                <button onclick="window._ai.deselectAll()">◻️ None</button>
+                <button class="bulk-ai-btn" onclick="window._ai.showAiForm()">🤖 AI Sinh</button>
+            </div>
+
+            <div class="ai-progress-bar" id="aiProgressBar" style="display:none;">
+                <div class="progress-info">
+                    <span>🤖 AI đang sinh:</span>
+                    <strong id="aiProgressText">0/0</strong>
+                    <span id="aiProgressName" class="progress-name"></span>
+                </div>
+                <div class="progress-track"><div class="progress-fill" id="aiProgressFill"></div></div>
+            </div>
+
+            <div class="ai-input-area">
+                <input type="text" id="aiInput" placeholder="Gõ tiếng Việt tự nhiên... VD: áo cotton bé gái" autocomplete="off">
+                <button class="ai-send-btn" id="aiSendBtn" onclick="window._ai.send()">➤</button>
+            </div>
+        `;
+
+        document.body.appendChild(bubble);
+        document.body.appendChild(panel);
+
+        document.getElementById('aiInput').addEventListener('keydown', e => {
+            if (e.key === 'Enter') window._ai.send();
+        });
+
+        // Load field options
+        fetch('/api/bulk/fields').then(r => r.json()).then(d => {
+            if (d.status === 'success') fieldOptions = d.fields;
+        }).catch(() => {});
+    }
+
+    // ═══ PANEL ═══
+    function togglePanel() {
+        panelOpen = !panelOpen;
+        document.getElementById('aiPanel').classList.toggle('open', panelOpen);
+        document.getElementById('aiBubble').classList.toggle('open', panelOpen);
+        if (panelOpen) setTimeout(() => document.getElementById('aiInput').focus(), 350);
+    }
+
+    // ═══ MESSAGES ═══
+    function msg(content, type = 'bot') {
+        const c = document.getElementById('aiMessages');
+        const avatar = type === 'bot' ? '✦' : '👤';
+        const el = document.createElement('div');
+        el.className = `ai-msg ${type}`;
+        el.innerHTML = `<div class="ai-msg-avatar">${avatar}</div><div class="ai-msg-body">${content}</div>`;
+        c.appendChild(el);
+        c.scrollTop = c.scrollHeight;
+        return el;
+    }
+
+    function typing(show) {
+        const existing = document.getElementById('aiTyping');
+        if (existing) existing.remove();
+        if (!show) return;
+        const c = document.getElementById('aiMessages');
+        const el = document.createElement('div');
+        el.className = 'ai-typing'; el.id = 'aiTyping';
+        el.innerHTML = '<div class="ai-typing-dot"></div><div class="ai-typing-dot"></div><div class="ai-typing-dot"></div>';
+        c.appendChild(el);
+        c.scrollTop = c.scrollHeight;
+    }
+
+    // ═══ SEND ═══
+    function send() {
+        const inp = document.getElementById('aiInput');
+        const text = inp.value.trim();
+        if (!text) return;
+        inp.value = '';
+        msg(text, 'user');
+        doAiSearch(text);
+    }
+
+    function qSearch(kw) {
+        document.getElementById('aiInput').value = kw;
+        send();
+    }
+
+    // ═══ AI SEARCH (Agent-Style) ═══
+    async function doAiSearch(query) {
+        typing(true);
+        currentMode = 'searching';
+
+        // Show "AI đang phân tích..." message
+        const thinkMsg = msg('🧠 AI đang phân tích ý định tìm kiếm...');
+
+        try {
+            const resp = await fetch('/api/bulk/ai-search', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ query, limit: 100 }),
+            });
+            const data = await resp.json();
+            typing(false);
+
+            // Remove thinking message
+            if (thinkMsg) thinkMsg.remove();
+
+            if (data.status !== 'success') {
+                msg(`❌ ${data.message || 'Lỗi tìm kiếm'}`);
+                return;
+            }
+
+            lastAiFilters = data.ai_filters || {};
+            lastOccasion = data.occasion || '';
+
+            // Show AI understanding
+            let filterHtml = '<div class="ai-filter-tags">';
+            filterHtml += '<strong style="font-size:11px;color:#6b7280;">🧠 AI hiểu:</strong> ';
+            if (data.explain) {
+                filterHtml += `<span class="ai-filter-explain">${esc(data.explain)}</span><br>`;
+            }
+            filterHtml += '<div style="display:flex;flex-wrap:wrap;gap:4px;margin-top:4px;">';
+
+            const f = data.ai_filters || {};
+            if (f.product_line) filterHtml += `<span class="ai-tag product">${esc(f.product_line)}</span>`;
+            if (f.color) filterHtml += `<span class="ai-tag color">🎨 ${esc(f.color)}</span>`;
+            if (f.gender) filterHtml += `<span class="ai-tag gender">👤 ${esc(f.gender)}</span>`;
+            if (f.age_group) filterHtml += `<span class="ai-tag age">${f.age_group === 'kid' ? '👶 Trẻ em' : '🧑 Người lớn'}</span>`;
+            if (f.season) filterHtml += `<span class="ai-tag season">🌤 ${esc(f.season)}</span>`;
+            if (f.occasion) filterHtml += `<span class="ai-tag occasion">📅 ${esc(f.occasion)}</span>`;
+            if (f.keywords && f.keywords.length > 0) {
+                f.keywords.forEach(kw => {
+                    filterHtml += `<span class="ai-tag keyword">🔍 ${esc(kw)}</span>`;
+                });
+            }
+
+            filterHtml += '</div></div>';
+
+            if (!data.results || !data.results.length) {
+                msg(`${filterHtml}<br>Không tìm thấy SP nào phù hợp. Thử câu khác?`);
+                return;
+            }
+
+            searchResults = data.results;
+            selectedCodes = new Set(data.results.map(r => r.internal_ref_code));
+            currentMode = 'searched';
+
+            let html = `${filterHtml}<br>Tìm được <strong>${data.count}</strong> SP:`;
+            html += '<div class="ai-search-results">';
+            data.results.forEach((r, i) => {
+                const st = r.status === 1 ? 'done' : (r.status === 0 ? 'pending' : 'missing');
+                const stText = r.status === 1 ? '✅' : (r.status === 0 ? '⏳' : '✕');
+                const img = r.product_image_url
+                    ? `<img src="${esc(r.product_image_url)}" alt="" onerror="this.style.display='none'">`
+                    : '<div style="width:36px;height:36px;border-radius:6px;background:#f0efec;display:flex;align-items:center;justify-content:center;font-size:14px;flex-shrink:0;">📦</div>';
+                html += `
+                    <div class="ai-result-item" onclick="window._ai.toggle('${esc(r.internal_ref_code)}',${i})">
+                        <input type="checkbox" id="aiChk_${i}" ${selectedCodes.has(r.internal_ref_code) ? 'checked' : ''} onclick="event.stopPropagation();window._ai.toggle('${esc(r.internal_ref_code)}',${i})">
+                        ${img}
+                        <div class="ai-result-info">
+                            <div class="ai-result-name">${esc(r.product_name || '—')}</div>
+                            <div class="ai-result-code">${esc(r.internal_ref_code)}</div>
+                        </div>
+                        <span class="ai-result-status ${st}">${stText}</span>
+                    </div>`;
+            });
+            html += '</div>';
+            msg(html);
+            updateBar();
+
+            // Auto-suggest if occasion detected
+            if (lastOccasion) {
+                msg(`
+                    💡 <strong>Gợi ý:</strong> AI phát hiện dịp <strong>"${esc(lastOccasion)}"</strong>.<br>
+                    Bấm <strong>🤖 AI Sinh</strong> → chọn trường <strong>"Dịp mặc"</strong> → AI sẽ tự động thêm dịp này cho ${data.count} SP!
+                `);
+            } else {
+                msg(`
+                    Chọn SP rồi bấm <strong>🤖 AI Sinh</strong> ở thanh dưới để:<br>
+                    • Chọn <strong>trường</strong> cần sửa (dịp mặc, phối đồ...)<br>
+                    • Gõ <strong>yêu cầu</strong> bằng tiếng Việt<br>
+                    • AI Codex sinh nội dung <strong>riêng cho từng SP</strong> 🔥
+                `);
+            }
+
+        } catch (e) {
+            typing(false);
+            msg(`❌ Lỗi: ${e.message}`);
+        }
+    }
+
+    // ═══ SELECT ═══
+    function toggle(code, idx) {
+        selectedCodes.has(code) ? selectedCodes.delete(code) : selectedCodes.add(code);
+        const chk = document.getElementById(`aiChk_${idx}`);
+        if (chk) chk.checked = selectedCodes.has(code);
+        updateBar();
+    }
+    function selectAll() {
+        searchResults.forEach((r, i) => { selectedCodes.add(r.internal_ref_code); const c = document.getElementById(`aiChk_${i}`); if (c) c.checked = true; });
+        updateBar();
+    }
+    function deselectAll() {
+        selectedCodes.clear();
+        searchResults.forEach((_, i) => { const c = document.getElementById(`aiChk_${i}`); if (c) c.checked = false; });
+        updateBar();
+    }
+    function updateBar() {
+        const bar = document.getElementById('aiBulkBar');
+        document.getElementById('aiBulkCount').textContent = selectedCodes.size;
+        bar.style.display = (currentMode === 'searched' && searchResults.length > 0) ? 'flex' : 'none';
+    }
+
+    // ═══ AI EDIT FORM ═══
+    function showAiForm() {
+        if (selectedCodes.size === 0) { msg('⚠️ Chưa chọn SP nào!'); return; }
+
+        // Build field dropdown
+        let opts = '';
+        for (const [key, label] of Object.entries(fieldOptions)) {
+            const sel = key === 'dip_mac' ? ' selected' : '';
+            opts += `<option value="${key}"${sel}>${label}</option>`;
+        }
+        if (!opts) {
+            opts = `
+                <option value="dip_mac" selected>Dịp mặc</option>
+                <option value="phoi_do">Phối đồ</option>
+                <option value="mo_ta_chinh">Mô tả chính</option>
+                <option value="phong_cach">Phong cách</option>
+                <option value="hook_quang_cao">Hook quảng cáo</option>
+                <option value="cross_sell">Cross-sell</option>
+                <option value="ly_do_mua">Lý do mua</option>
+                <option value="tags">Tags</option>
+                <option value="mua">Mùa phù hợp</option>
+                <option value="layer">Gợi ý layering</option>
+                <option value="luu_y_size">Lưu ý size</option>
+                <option value="tagline">Tagline</option>
+            `;
+        }
+
+        // Pre-fill instruction if occasion detected
+        const defaultInstruction = lastOccasion
+            ? `Thêm rằng sản phẩm này phù hợp mặc dịp ${lastOccasion}`
+            : '';
+
+        msg(`
+            <strong>🤖 AI Sinh Nội Dung — ${selectedCodes.size} sản phẩm</strong>
+            <div class="ai-edit-modal">
+                <label>Trường cần sửa</label>
+                <select id="aiFieldSelect">${opts}</select>
+
+                <label>Chế độ</label>
+                <select id="aiModeSelect">
+                    <option value="append">➕ Bổ sung thêm (giữ cái cũ)</option>
+                    <option value="overwrite">🔄 Viết lại hoàn toàn</option>
+                </select>
+
+                <label>Yêu cầu cho AI (tiếng Việt)</label>
+                <textarea id="aiInstruction" placeholder="VD: Thêm rằng áo này phù hợp mặc dịp Quốc Khánh 2/9 vì có gam đỏ cờ Tổ quốc...">${esc(defaultInstruction)}</textarea>
+
+                <div class="ai-edit-actions" style="margin-top:12px; display:flex; gap:8px;">
+                    <button class="btn-secondary" onclick="window._ai.previewAiEdit()">👀 Thử nghiệm (1 SP)</button>
+                    <button class="btn-apply" onclick="window._ai.startAiEdit()">🚀 Bắt đầu chạy HÀNG LOẠT</button>
+                </div>
+                <div id="aiPreviewBox" style="display:none; margin-top:12px; background:rgba(0,0,0,0.2); padding:10px; border-radius:8px; font-size:12px; border:1px solid rgba(255,255,255,0.1);">
+                </div>
+            </div>
+        `);
+    }
+
+    // ═══ PREVIEW AI EDIT ═══
+    async function previewAiEdit() {
+        const field = document.getElementById('aiFieldSelect').value;
+        const mode = document.getElementById('aiModeSelect').value;
+        const instruction = document.getElementById('aiInstruction').value.trim();
+
+        if (!instruction) { msg('⚠️ Nhập yêu cầu cho AI!'); return; }
+
+        // Mặc định lấy sản phẩm ĐẦU TIÊN trong list được chọn để preview
+        const codes = Array.from(selectedCodes);
+        if (codes.length === 0) return;
+        const previewCode = [codes[0]];
+
+        const box = document.getElementById('aiPreviewBox');
+        box.style.display = 'block';
+        box.innerHTML = `<em>Đang sinh thử nội dung cho SP <strong>${previewCode[0]}</strong>...</em> <span class="ai-spinner"></span>`;
+
+        try {
+            const resp = await fetch('/api/bulk/ai-edit-preview', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ codes: previewCode, target_field: field, instruction, mode }),
+            });
+            const data = await resp.json();
+
+            if (data.status === 'success') {
+                box.innerHTML = `
+                    <div style="color:#d6d3d1; margin-bottom:4px;"><strong>Kết quả thử nghiệm (${esc(data.code)}):</strong></div>
+                    <div style="color:#dc2626; margin-bottom:4px; text-decoration:line-through;">${data.old_value ? esc(data.old_value) : '<em>(trống)</em>'}</div>
+                    <div style="color:#22c55e;">${esc(data.new_value)}</div>
+                    <div style="margin-top:6px; font-size:11px; color:#a8a29e;">Review ổn thì bấm Bắt đầu chạy hàng loạt nhé 👇</div>
+                `;
+            } else {
+                box.innerHTML = `<div style="color:#dc2626;">❌ ${esc(data.message)}</div>`;
+            }
+        } catch (e) {
+            box.innerHTML = `<div style="color:#dc2626;">❌ Lỗi: ${e.message}</div>`;
+        }
+    }
+
+    // ═══ START AI EDIT ═══
+    async function startAiEdit() {
+        const field = document.getElementById('aiFieldSelect').value;
+        const mode = document.getElementById('aiModeSelect').value;
+        const instruction = document.getElementById('aiInstruction').value.trim();
+
+        if (!instruction) { msg('⚠️ Nhập yêu cầu cho AI!'); return; }
+
+        const codes = Array.from(selectedCodes);
+        const fieldLabel = fieldOptions[field] || field;
+
+        msg(`🚀 Đang gửi yêu cầu cho AI Codex...<br>
+             Trường: <strong>${fieldLabel}</strong><br>
+             Chế độ: <strong>${mode === 'append' ? 'Bổ sung' : 'Viết lại'}</strong><br>
+             SP: <strong>${codes.length}</strong><br>
+             Yêu cầu: <em>"${esc(instruction)}"</em>`);
+
+        typing(true);
+
+        try {
+            const resp = await fetch('/api/bulk/ai-edit', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ codes, target_field: field, instruction, mode }),
+            });
+            const data = await resp.json();
+            typing(false);
+
+            if (data.status === 'success') {
+                msg(`✅ ${data.message}`);
+                currentMode = 'ai_running';
+                showProgress();
+                startPolling();
+            } else {
+                msg(`❌ ${data.message}`);
+            }
+        } catch (e) {
+            typing(false);
+            msg(`❌ Lỗi: ${e.message}`);
+        }
+    }
+
+    // ═══ PROGRESS TRACKING ═══
+    function showProgress() {
+        document.getElementById('aiProgressBar').style.display = 'block';
+    }
+    function hideProgress() {
+        document.getElementById('aiProgressBar').style.display = 'none';
+    }
+
+    function startPolling() {
+        if (pollTimer) clearInterval(pollTimer);
+        pollTimer = setInterval(pollStatus, 2000);
+    }
+
+    async function pollStatus() {
+        try {
+            const resp = await fetch('/api/bulk/ai-edit-status');
+            const s = await resp.json();
+
+            const pct = s.total > 0 ? Math.round((s.done / s.total) * 100) : 0;
+            document.getElementById('aiProgressText').textContent = `${s.done}/${s.total}`;
+            document.getElementById('aiProgressFill').style.width = pct + '%';
+            document.getElementById('aiProgressName').textContent = s.current_name ? `→ ${s.current_name}` : '';
+
+            if (!s.is_running) {
+                clearInterval(pollTimer);
+                pollTimer = null;
+                hideProgress();
+                currentMode = 'searched';
+
+                // Show completion + results
+                let html = `🏁 <strong>AI hoàn tất!</strong> ${s.done}/${s.total} SP (${s.errors} lỗi)<br><br>`;
+
+                if (s.results && s.results.length > 0) {
+                    html += '<div class="ai-search-results" style="max-height:220px;">';
+                    s.results.forEach(r => {
+                        if (r.status === 'success') {
+                            html += `
+                                <div class="ai-result-item" style="flex-direction:column;align-items:flex-start;gap:4px;cursor:default;">
+                                    <div style="display:flex;align-items:center;gap:6px;width:100%;">
+                                        <span class="ai-result-status done">✅</span>
+                                        <strong style="font-size:11px;">${esc(r.code)}</strong>
+                                        <span style="font-size:11px;color:#78716c;">${esc(r.name || '')}</span>
+                                    </div>
+                                    <div style="font-size:11px;width:100%;">
+                                        <div style="color:#dc2626;">- ${esc(r.old_value || '(trống)')}</div>
+                                        <div style="color:#16a34a;">+ ${esc(r.new_value || '')}</div>
+                                    </div>
+                                </div>`;
+                        } else {
+                            html += `
+                                <div class="ai-result-item" style="cursor:default;">
+                                    <span class="ai-result-status missing">❌</span>
+                                    <span style="font-size:11px;">${esc(r.code)} — ${esc(r.error || r.status)}</span>
+                                </div>`;
+                        }
+                    });
+                    html += '</div>';
+                }
+
+                msg(html);
+            }
+        } catch (e) {
+            console.warn('Poll error:', e);
+        }
+    }
+
+    // ═══ HELP ═══
+    function showHelp() {
+        msg(`
+            <strong>📖 Hướng dẫn sử dụng — AI Agent v3</strong><br><br>
+            <strong>1️⃣ Tìm kiếm thông minh:</strong><br>
+            Gõ <strong>câu tự nhiên</strong> — AI hiểu ý và tìm SP:<br>
+            • <em>"áo đỏ cho bé trai"</em> → lọc: Áo + đỏ + Nam + trẻ em<br>
+            • <em>"polo nam đi làm"</em> → lọc: Áo Polo + Nam<br>
+            • <em>"váy cotton mùa hè"</em> → lọc: Váy + cotton + Hè<br><br>
+            <strong>2️⃣ Chọn SP:</strong><br>
+            Tick checkbox chọn SP cần sửa (mặc định chọn hết)<br><br>
+            <strong>3️⃣ AI Sinh nội dung:</strong><br>
+            Bấm <strong>🤖 AI Sinh</strong> → chọn trường + gõ yêu cầu<br>
+            AI Codex sinh nội dung <strong>riêng cho từng SP</strong> 🔥<br><br>
+            <strong>💡 Tips:</strong> Nếu bạn nói dịp đặc biệt ("2/9", "Tết"), AI sẽ tự gợi ý instruction!
+        `);
+    }
+
+    // ═══ CLEAR ═══
+    function clearChat() {
+        document.getElementById('aiMessages').innerHTML = '';
+        searchResults = []; selectedCodes.clear(); currentMode = 'idle';
+        lastAiFilters = null; lastOccasion = '';
+        updateBar(); hideProgress();
+        if (pollTimer) { clearInterval(pollTimer); pollTimer = null; }
+        msg('🧹 Đã xóa. Gõ câu tự nhiên để AI tìm SP thông minh!');
+    }
+
+    // ═══ UTILS ═══
+    function esc(s) {
+        if (!s) return '';
+        const d = document.createElement('div');
+        d.textContent = s;
+        return d.innerHTML;
+    }
+
+    // ═══ INIT ═══
+    if (document.readyState === 'loading') document.addEventListener('DOMContentLoaded', createWidget);
+    else createWidget();
+
+    // ═══ PUBLIC API ═══
+    window._ai = {
+        togglePanel, send, qSearch, toggle, selectAll, deselectAll,
+        showAiForm, previewAiEdit, startAiEdit, showHelp, clearChat, updateBar
+    };
+})();