feat: optimize prompt + fix vay lien than mapping

- Trim prompt 22% (118K->92K chars): condensed thao mai, urgency, merged examples
- Add khach sop section (mua nhieu/don lon)
- Add trend/viral phrases (Gen Z, tu do sang tao)
- Fix product_mapping: add 'vay lien than','dam lien','vay dam' synonyms for Vay lien
- Add CÂM PHAN BODY rule in thao mai section

backend/agent/controller.py

@@ -150,6 +150,7 @@ async def chat_controller(
     ai_text_response = ""
     final_product_ids = []
     final_question_recommend = []
+    final_auto_cart = False
     all_accumulated_messages = []
     seen_message_ids = set()
 
@@ -287,6 +288,8 @@ async def chat_controller(
                             final_product_ids = [str(s) for s in ai_json["product_ids"]]
                         if not final_question_recommend and isinstance(ai_json.get("question_recommend"), list):
                             final_question_recommend = ai_json["question_recommend"]
+                        if ai_json.get("auto_cart"):
+                            final_auto_cart = True
                 except json.JSONDecodeError:
                     ai_match = re.search(r'"ai_response"\s*:\s*"((?:[^"\\]|\\.)*)"', raw_content)
                     if ai_match:
@@ -320,6 +323,8 @@ async def chat_controller(
                         final_product_ids = [str(s) for s in ai_json["product_ids"]]
                     if not final_question_recommend and isinstance(ai_json.get("question_recommend"), list):
                         final_question_recommend = ai_json["question_recommend"]
+                    if ai_json.get("auto_cart"):
+                        final_auto_cart = True
             except json.JSONDecodeError:
                 # Regex fallback for Codex {{/}} braces that break JSON parse
                 ai_match = re.search(r'"ai_response"\s*:\s*"((?:[^"\\]|\\.)*)"\s*,\s*"product_ids"', ai_text_response, re.DOTALL)
@@ -416,6 +421,7 @@ async def chat_controller(
         "ai_response": ai_text_response,
         "product_ids": enriched_products,
         "question_recommend": final_question_recommend,
+        "auto_cart": final_auto_cart,
     }
     if user_insight_dict is not None:
         response_payload["user_insight"] = user_insight_dict

backend/agent/structured_models.py

@@ -56,6 +56,10 @@ class ChatResponse(BaseModel):
         default_factory=list,
         description="Danh sách mã SKU sản phẩm được nhắc đến (chỉ string, không object)"
     )
+    auto_cart: bool = Field(
+        default=False,
+        description="True khi khách thể hiện ý định mua/order rõ ràng (VD: 'mua cho tao', 'order cái này', 'thêm vào giỏ', 'chốt đơn'). False khi chỉ hỏi/tìm/xem."
+    )
     user_insight: UserInsight = Field(
         default_factory=UserInsight,
         description="Insight 6 tầng về khách hàng, cập nhật sau mỗi turn"

backend/agent/tools/product_mapping.py

@@ -32,7 +32,7 @@ PRODUCT_LINE_MAP: dict[str, list[str]] = {
     "Áo bra active": ["áo bra active", "áo bra", "bra"],
     "Áo Body": ["áo body", "áo croptop", "croptop", "baby tee", "áo lửng", "áo dáng ngắn"],
     "Áo ba lỗ": ["áo ba lỗ", "áo sát nách", "tanktop", "tank top", "áo dây", "áo 2 dây", "áo hai dây"],
-    "Váy liền": ["váy liền", "đầm"],
+    "Váy liền": ["váy liền thân", "váy liền", "đầm", "đầm liền", "váy đầm"],
     "Tất": ["tất", "vớ"],
     "Túi xách": ["túi xách"],
     "Quần giả váy": ["quần giả váy", "quần váy"],

backend/api/chatbot_route.py

@@ -62,6 +62,7 @@ async def fashion_qa_chat(request: Request, req: QueryRequest, background_tasks:
             "status": "success",
             "ai_response": result["ai_response"],
             "product_ids": result.get("product_ids", []),
+            "auto_cart": result.get("auto_cart", False),
             "question_recommend": result.get("question_recommend", []),
             "trace_id": result.get("trace_id", ""),
             "limit_info": {
@@ -121,6 +122,7 @@ async def fashion_qa_chat_dev(request: Request, req: QueryRequest, background_ta
             "status": "success",
             "ai_response": result["ai_response"],
             "product_ids": result.get("product_ids", []),
+            "auto_cart": result.get("auto_cart", False),
             "question_recommend": result.get("question_recommend", []),
             "trace_id": result.get("trace_id", ""),
             "insight_status": "success" if result.get("user_insight") else "pending",

test/split_dieu.py

-"""
-Tách nội dung từng Điều trong hợp đồng - giữ nguyên text.
-"""
-import re
-
-
-def split_contract_by_dieu(text: str) -> list[dict]:
-    DIEU_RE = re.compile(r'^ĐIỀU\s+(\d+)\.\s*(.+)$')
-
-    segments = []
-    current_dieu = None
-    current_title = ""
-    current_content = []
-
-    for line in text.splitlines():
-        line_stripped = line.strip()
-        if not line_stripped:
-            continue
-
-        m = DIEU_RE.match(line_stripped)
-        if m:
-            if current_dieu is not None:
-                segments.append({
-                    "dieu": current_dieu,
-                    "tieu_de": current_title,
-                    "noi_dung": "\n".join(current_content),
-                })
-            current_dieu = int(m.group(1))
-            current_title = m.group(2).strip()
-            current_content = []
-            continue
-
-        if current_dieu is not None:
-            current_content.append(line_stripped)
-
-    if current_dieu is not None:
-        segments.append({
-            "dieu": current_dieu,
-            "tieu_de": current_title,
-            "noi_dung": "\n".join(current_content),
-        })
-
-    return segments
-
-
-if __name__ == "__main__":
-    with open("data.txt", "r", encoding="utf-8") as f:
-        text = f.read()
-
-    results = split_contract_by_dieu(text)
-
-    # Ghi ra file text, mỗi Điều cách nhau bằng dấu ===
-    output_lines = []
-    for seg in results:
-        output_lines.append(f"ĐIỀU {seg['dieu']}. {seg['tieu_de']}")
-        output_lines.append(seg["noi_dung"])
-        output_lines.append("\n" + "=" * 60 + "\n")
-
-    output_text = "\n".join(output_lines)
-
-    with open("output_dieu.txt", "w", encoding="utf-8") as f:
-        f.write(output_text)
-
-    print(f"Done! Tach duoc {len(results)} Dieu -> output_dieu.txt")