修改铭感词匹配规则

dbgpt/app/apps/utils/filter.py

@@ -123,6 +123,8 @@ class DFAFilter():
         for keyword in datas:
             self.add(keyword.word_name)
 
+
+    #最长匹配模式，确保敏感词过滤器优先匹配和替换较长的敏感词
     def filter(self, message, repl="*"):
         is_sensitive = False
         if not isinstance(message, str):
@@ -130,30 +132,37 @@ class DFAFilter():
         message = message.lower()
         ret = []
         start = 0
-        matched_sensitives = []  # List to store matched sensitive words
+        matched_sensitives = []  # 用来存储匹配的敏感词
+
         while start < len(message):
             level = self.keyword_chains
+            longest_match_len = 0  # 记录最长匹配长度
+            longest_match_word = None  # 记录最长匹配的敏感词
             step_ins = 0
-            for char in message[start:]:
+
+            for i, char in enumerate(message[start:], start=1):
                 if char in level:
+                    level = level[char]
                     step_ins += 1
-                    if self.delimit not in level[char]:
-                        level = level[char]
-                    else:
-                        # Store the matched sensitive word
-                        matched_sensitives.append(message[start:start + step_ins])
-                        ret.append(repl * step_ins)
-                        start += step_ins - 1
-                        is_sensitive = True
-                        break
+                    if self.delimit in level:
+                        # 找到一个完整的敏感词
+                        longest_match_len = step_ins
+                        longest_match_word = message[start:start + step_ins]
                 else:
-                    ret.append(message[start])
                     break
+
+            if longest_match_len > 0:
+                # 进行最长匹配替换
+                matched_sensitives.append(longest_match_word)
+                ret.append(repl * longest_match_len)
+                start += longest_match_len
+                is_sensitive = True
             else:
+                # 无匹配，直接保留原字符
                 ret.append(message[start])
-            start += 1
+                start += 1
 
-        # return 返回三个参数
+        # 返回三个参数
         return ''.join(ret), is_sensitive, matched_sensitives
 
 #初始化全局对象

dbgpt/app/apps/vadmin/keywordsviews.py

@@ -35,6 +35,15 @@ from sqlalchemy import BinaryExpression
 
 router = APIRouter()
 
+#提问次数
+question_count = 0
+
+#关键词匹配到的类型
+MEDIA_TYPE1 = 1 #图片
+MEDIA_TYPE2 = 2 #视频
+MEDIA_TYPE3 = 3 #铭感词
+MEDIA_TYPE4 = 4 #问答对
+MEDIA_TYPE5 = 5 #统计次数3->留下联系电话
 
 def get_key_words(user_input: str) -> list:
     """
@@ -97,7 +106,7 @@ async def get_media_datas_by(conv_uid: str, words: str, db: AsyncSession, knownl
             print(f"-----查询到的图片为:---->:{images_datas}")
 
             for data in images_datas:
-                json_image = {'type': 1, 'file_name': data.get('file_name'), 'key_word': data.get('key_word'),
+                json_image = {'type': MEDIA_TYPE1, 'file_name': data.get('file_name'), 'key_word': data.get('key_word'),
                               'local_path': data.get('local_path'), 'remote_path': data.get('remote_path')}
                 result.append(json_image)
 
@@ -113,7 +122,7 @@ async def get_media_datas_by(conv_uid: str, words: str, db: AsyncSession, knownl
             video_datas, count = await MediaDal(db).get_datas(**video_dic, v_return_count=True)
             print(f"-----查询到的视频为:---->:{video_datas}")
             for videodata in video_datas:
-                json_video = {'type': 2, 'file_name': videodata.get('file_name'),
+                json_video = {'type': MEDIA_TYPE2, 'file_name': videodata.get('file_name'),
                               'key_word': videodata.get('key_word'),
                               'local_path': videodata.get('local_path'),
                               'remote_path': videodata.get('remote_path')}
@@ -130,7 +139,7 @@ async def get_media_datas_by(conv_uid: str, words: str, db: AsyncSession, knownl
             question_datas, count = await QuestionDal(db).get_datas(**question_dic, v_return_count=True)
             print(f"-----查询到的问答对为:---->:{question_datas}")
             for questiondata in question_datas:
-                json_question = {'type': 4, 'title': questiondata.get('title'),
+                json_question = {'type': MEDIA_TYPE4, 'title': questiondata.get('title'),
                                  'key_word': questiondata.get('key_word'),
                                  'answer': questiondata.get('answer')}
                 result.append(json_question)
@@ -161,7 +170,7 @@ async def get_media_datas(conv_uid: str, words: str, db: AsyncSession) -> list:
     print(f"-----查询到的图片为:---->:{images_datas}")
     result = []
     for data in images_datas:
-        json_image = {'type': 1, 'file_name': data.get('file_name'), 'key_word': data.get('key_word'),
+        json_image = {'type': MEDIA_TYPE1, 'file_name': data.get('file_name'), 'key_word': data.get('key_word'),
                       'local_path': data.get('local_path'), 'remote_path': data.get('remote_path')}
         result.append(json_image)
 
@@ -172,7 +181,7 @@ async def get_media_datas(conv_uid: str, words: str, db: AsyncSession) -> list:
     video_datas, count = await MediaDal(db).get_datas(**video_dic, v_return_count=True)
     print(f"-----查询到的视频为:---->:{video_datas}")
     for videodata in video_datas:
-        json_video = {'type': 2, 'file_name': videodata.get('file_name'), 'key_word': videodata.get('key_word'),
+        json_video = {'type': MEDIA_TYPE2, 'file_name': videodata.get('file_name'), 'key_word': videodata.get('key_word'),
                       'local_path': videodata.get('local_path'), 'remote_path': videodata.get('remote_path')}
         result.append(json_video)
 
@@ -181,7 +190,7 @@ async def get_media_datas(conv_uid: str, words: str, db: AsyncSession) -> list:
     question_datas, count = await QuestionDal(db).get_datas(**question_dic, v_return_count=True)
     print(f"-----查询到的问答对为:---->:{question_datas}")
     for questiondata in question_datas:
-        json_question = {'type': 4, 'title': questiondata.get('title'), 'key_word': questiondata.get('key_word'),
+        json_question = {'type': MEDIA_TYPE4, 'title': questiondata.get('title'), 'key_word': questiondata.get('key_word'),
                          'answer': questiondata.get('answer')}
         result.append(json_question)
 
@@ -208,7 +217,7 @@ async def get_media_datas_all(conv_uid: str, default_model: str, db: AsyncSessio
                    'message_medias': ('like', None)}
     datas, count = await ChatHistoryDal(db).get_datas(**history_dic, v_return_count=True)
 
-    json_data = [{"type": 1, "file_name": "723629348SJfHgjzD.png"}]  # 传入列表
+    json_data = [{"type": MEDIA_TYPE1, "file_name": "723629348SJfHgjzD.png"}]  # 传入列表
     if count > 0:
         history_datas = datas[0].get('message_medias')
         json_data = json.loads(history_datas)
@@ -234,6 +243,19 @@ async def get_spacy_keywords(dialogue: ConversationVo = Body(), auth: Auth = Dep
     print(f"用户输入的问题：{dialogue.user_input} -- 选择的知识库为:{dialogue.select_param}")
     print('----------------begin---------------->')
 
+    #统计提问次数
+    """
+    global question_count
+    question_count += 1
+    print(f"=====>question_count:{question_count}")
+    if question_count >= 3:
+        print('=====触发留下联系方式=====')
+        result = {'code': 200, 'message': 'success',
+                  'data': [{'type': MEDIA_TYPE5, 'answer': "请留下您的联系方式,后续给您安排技术人员给您详细讲解一下:"}]}
+        question_count = 0
+        return SuccessResponse(result)  # 返回type=5
+    """
+
     #先判断敏感词
     dfa_result, is_sensitive, matched_sensitives = mydfafiter.filter(dialogue.user_input, "*")
     print(dfa_result)
@@ -241,7 +263,7 @@ async def get_spacy_keywords(dialogue: ConversationVo = Body(), auth: Auth = Dep
     if is_sensitive:
         print('用户输入有敏感词')
         result = {'code': 200, 'message': 'success',
-                  'data': [{'type': 3, 'word_name': matched_sensitives, 'is_sensitive': 1, 'user_input': dfa_result}]}
+                  'data': [{'type': MEDIA_TYPE3, 'word_name': matched_sensitives, 'is_sensitive': 1, 'user_input': dfa_result}]}
         return SuccessResponse(result)  #返回type=3
 
     #没有敏感词的时候,查找是否有相关图片 或者 视频

dbgpt/app/openapi/api_v1/api_v1.py

@@ -544,6 +544,7 @@ async def stream_generator(chat, incremental: bool, model_name: str):
                 json_chunk = model_to_json(
                     chunk, exclude_unset=True, ensure_ascii=False
                 )
+                #把\\n --> 转换为 \n
                 json_chunk = json_chunk.replace("\\n", "n")
                 #print(f"===>:{json_chunk}")
                 yield f"data: {json_chunk}\n\n"