统一 hash 函数

ruoyi-fastapi-backend/module_admin/controller/ragflow_controller.py

@@ -22,13 +22,7 @@ from module_admin.entity.vo.ragflow_vo import (
 )
 from utils.log_util import logger
 from utils.response_util import ResponseUtil
-from utils.semantic_cache_service import get_semantic_cache_service, lookup_question, store_qa_pair
+from utils.semantic_cache_service import get_semantic_cache_service, lookup_question, store_qa_pair, get_question_hash
-
-def _get_question_hash(question: str) -> str:
-    """计算问题的hash值"""
-    import hashlib
-    normalized = question.lower().strip()
-    return hashlib.md5(normalized.encode('utf-8')).hexdigest()[:16]
 from utils.static_qa_service import get_static_qa_service
 
 
@@ -36,7 +30,7 @@ async def _async_store_qa(chat_id: str, question: str, answer: str, redis) -> No
     """
     异步存储问答对到语义缓存
     """
-    store_hash = _get_question_hash(question)
+    store_hash = get_question_hash(question)
     logger.info(f"[SemanticCache] 存储QA | chat_id={chat_id} | question={question} | hash={store_hash} | answer_length={len(answer)}")
     try:
         await store_qa_pair(chat_id, question, answer, redis)
@@ -157,7 +151,7 @@ async def converse_with_chat_assistant(
     # ========== 2. RAG历史缓存查找 ==========
     logger.info(f'[SemanticCache] 准备执行RAG历史缓存查找 | redis={redis is not None} | chat_id={converse_params.chat_id}')
     if redis:
-        lookup_hash = _get_question_hash(converse_params.question)
+        lookup_hash = get_question_hash(converse_params.question)
         logger.info(f'[SemanticCache] 开始查找 | chat_id={converse_params.chat_id} | question={converse_params.question} | hash={lookup_hash} | threshold=0.60')
         cache_result = await lookup_question(
             converse_params.chat_id, 
@@ -202,7 +196,7 @@ async def converse_with_chat_assistant(
         result = RAGFlowService.converse_with_chat_assistant_services(converse_params)
         
         cache_question = cleaned_question if style_removed else converse_params.question
-        store_hash = _get_question_hash(cache_question)
+        store_hash = get_question_hash(cache_question)
         logger.info(f'[RAG_CACHE] 准备存储 | chat_id={converse_params.chat_id} | question={cache_question} | hash={store_hash}')
         
         async def make_cache_store(chat_id: str, question: str):

ruoyi-fastapi-backend/utils/semantic_cache_service.py

@@ -87,14 +87,6 @@ class SemanticCacheService:
         """构建缓存键"""
         return f"{self.CACHE_PREFIX}:{chat_id}:{question_hash}"
     
-    def _hash_question(self, question: str) -> str:
-        """对问题进行哈希，生成唯一标识"""
-        # 标准化问题文本（去除多余空格、统一标点）
-        normalized = self._normalize_question(question)
-        hash_value = hashlib.md5(normalized.encode('utf-8')).hexdigest()[:16]
-        logger.info(f"[SemanticCache] Hash计算 | 原始={question} | 标准化={normalized} | hash={hash_value}")
-        return hash_value
-    
     def _normalize_question(self, question: str) -> str:
         """标准化问题文本"""
         match_service = get_match_service()
@@ -134,7 +126,8 @@ class SemanticCacheService:
         
         try:
             # 1. 精确匹配
-            question_hash = self._hash_question(question)
+            normalized = question.lower().strip()
+            question_hash = hashlib.md5(normalized.encode('utf-8')).hexdigest()[:16]
             exact_key = self._build_cache_key(chat_id, question_hash)
             
             logger.info(f"[SemanticCache] 精确查找 | chat_id={chat_id} | question={question} | hash={question_hash} | key={exact_key}")
@@ -227,7 +220,8 @@ class SemanticCacheService:
                 return False
             
             # 构建缓存条目
-            question_hash = self._hash_question(question)
+            normalized = question.lower().strip()
+            question_hash = hashlib.md5(normalized.encode('utf-8')).hexdigest()[:16]
             cache_key = self._build_cache_key(chat_id, question_hash)
             
             logger.info(f"[SemanticCache] 存储缓存 | chat_id={chat_id} | question={question} | hash={question_hash} | key={cache_key}")
@@ -435,6 +429,12 @@ async def store_qa_pair(chat_id: str, question: str, answer: str, redis_client=N
     return await service.store(chat_id, question, answer, redis_client)
 
 
+def get_question_hash(question: str) -> str:
+    """计算问题的hash值（公共函数，确保存储和查找一致）"""
+    normalized = question.lower().strip()
+    return hashlib.md5(normalized.encode('utf-8')).hexdigest()[:16]
+
+
 async def clear_cache(chat_id: str = None, redis_client=None) -> bool:
     """清除缓存"""
     service = get_semantic_cache_service()