Merge branch 'main' of https://github.com/1Panel-dev/MaxKB

apps/application/chat_pipeline/step/chat_step/i_chat_step.py

@@ -54,7 +54,7 @@ class IChatStep(IBaseChatPipelineStep):
         message_list = serializers.ListField(required=True, child=MessageField(required=True),
                                              error_messages=ErrMessage.list("对话列表"))
         # 大语言模型
-        chat_model = ModelField(error_messages=ErrMessage.list("大语言模型"))
+        chat_model = ModelField(required=False, allow_null=True, error_messages=ErrMessage.list("大语言模型"))
         # 段落列表
         paragraph_list = serializers.ListField(error_messages=ErrMessage.list("段落列表"))
         # 对话id

apps/application/chat_pipeline/step/chat_step/impl/base_chat_step.py

@@ -59,8 +59,12 @@ def event_content(response,
 
         # 获取token
         if is_ai_chat:
-            request_token = chat_model.get_num_tokens_from_messages(message_list)
+            try:
-            response_token = chat_model.get_num_tokens(all_text)
+                request_token = chat_model.get_num_tokens_from_messages(message_list)
+                response_token = chat_model.get_num_tokens(all_text)
+            except Exception as e:
+                request_token = 0
+                response_token = 0
         else:
             request_token = 0
             response_token = 0
@@ -126,6 +130,26 @@ class BaseChatStep(IChatStep):
         result.append({'role': 'ai', 'content': answer_text})
         return result
 
+    @staticmethod
+    def get_stream_result(message_list: List[BaseMessage],
+                          chat_model: BaseChatModel = None,
+                          paragraph_list=None,
+                          no_references_setting=None):
+        if paragraph_list is None:
+            paragraph_list = []
+        directly_return_chunk_list = [AIMessageChunk(content=paragraph.content)
+                                      for paragraph in paragraph_list if
+                                      paragraph.hit_handling_method == 'directly_return']
+        if directly_return_chunk_list is not None and len(directly_return_chunk_list) > 0:
+            return iter(directly_return_chunk_list), False
+        elif len(paragraph_list) == 0 and no_references_setting.get(
+                'status') == 'designated_answer':
+            return iter([AIMessageChunk(content=no_references_setting.get('value'))]), False
+        if chat_model is None:
+            return iter([AIMessageChunk('抱歉，没有配置 AI 模型，无法优化引用分段，请先去应用中设置 AI 模型。')]), False
+        else:
+            return chat_model.stream(message_list), True
+
     def execute_stream(self, message_list: List[BaseMessage],
                        chat_id,
                        problem_text,
@@ -136,29 +160,8 @@ class BaseChatStep(IChatStep):
                        padding_problem_text: str = None,
                        client_id=None, client_type=None,
                        no_references_setting=None):
-        is_ai_chat = False
+        chat_result, is_ai_chat = self.get_stream_result(message_list, chat_model, paragraph_list,
-        # 调用模型
+                                                         no_references_setting)
-        if chat_model is None:
-            chat_result = iter(
-                [AIMessageChunk(content=paragraph.title + "\n" + paragraph.content) for paragraph in paragraph_list])
-        else:
-            if (paragraph_list is None or len(paragraph_list) == 0) and no_references_setting.get(
-                    'status') == 'designated_answer':
-                chat_result = iter([AIMessageChunk(content=no_references_setting.get('value'))])
-            else:
-                if paragraph_list is not None and len(paragraph_list) > 0:
-                    directly_return_chunk_list = [AIMessageChunk(content=paragraph.title + "\n" + paragraph.content)
-                                                  for paragraph in paragraph_list if
-                                                  paragraph.hit_handling_method == 'directly_return']
-                    if directly_return_chunk_list is not None and len(directly_return_chunk_list) > 0:
-                        chat_result = iter(directly_return_chunk_list)
-                    else:
-                        chat_result = chat_model.stream(message_list)
-                        is_ai_chat = True
-                else:
-                    chat_result = chat_model.stream(message_list)
-                    is_ai_chat = True
-
         chat_record_id = uuid.uuid1()
         r = StreamingHttpResponse(
             streaming_content=event_content(chat_result, chat_id, chat_record_id, paragraph_list,
@@ -169,6 +172,27 @@ class BaseChatStep(IChatStep):
         r['Cache-Control'] = 'no-cache'
         return r
 
+    @staticmethod
+    def get_block_result(message_list: List[BaseMessage],
+                         chat_model: BaseChatModel = None,
+                         paragraph_list=None,
+                         no_references_setting=None):
+        if paragraph_list is None:
+            paragraph_list = []
+
+        directly_return_chunk_list = [AIMessage(content=paragraph.content)
+                                      for paragraph in paragraph_list if
+                                      paragraph.hit_handling_method == 'directly_return']
+        if directly_return_chunk_list is not None and len(directly_return_chunk_list) > 0:
+            return directly_return_chunk_list[0], False
+        elif len(paragraph_list) == 0 and no_references_setting.get(
+                'status') == 'designated_answer':
+            return AIMessage(no_references_setting.get('value')), False
+        if chat_model is None:
+            return AIMessage('抱歉，没有配置 AI 模型，无法优化引用分段，请先去应用中设置 AI 模型。'), False
+        else:
+            return chat_model.invoke(message_list), True
+
     def execute_block(self, message_list: List[BaseMessage],
                       chat_id,
                       problem_text,
@@ -178,28 +202,8 @@ class BaseChatStep(IChatStep):
                       manage: PipelineManage = None,
                       padding_problem_text: str = None,
                       client_id=None, client_type=None, no_references_setting=None):
-        is_ai_chat = False
         # 调用模型
-        if chat_model is None:
+        chat_result, is_ai_chat = self.get_block_result(message_list, chat_model, paragraph_list, no_references_setting)
-            chat_result = AIMessage(
-                content="\n\n".join([paragraph.title + "\n" + paragraph.content for paragraph in paragraph_list]))
-        else:
-            if (paragraph_list is None or len(paragraph_list) == 0) and no_references_setting.get(
-                    'status') == 'designated_answer':
-                chat_result = AIMessage(content=no_references_setting.get('value'))
-            else:
-                if paragraph_list is not None and len(paragraph_list) > 0:
-                    directly_return_chunk_list = [AIMessageChunk(content=paragraph.title + "\n" + paragraph.content)
-                                                  for paragraph in paragraph_list if
-                                                  paragraph.hit_handling_method == 'directly_return']
-                    if directly_return_chunk_list is not None and len(directly_return_chunk_list) > 0:
-                        chat_result = iter(directly_return_chunk_list)
-                    else:
-                        chat_result = chat_model.invoke(message_list)
-                        is_ai_chat = True
-                else:
-                    chat_result = chat_model.invoke(message_list)
-                    is_ai_chat = True
         chat_record_id = uuid.uuid1()
         if is_ai_chat:
             request_token = chat_model.get_num_tokens_from_messages(message_list)

apps/application/chat_pipeline/step/generate_human_message_step/impl/base_generate_human_message_step.py

@@ -28,7 +28,7 @@ class BaseGenerateHumanMessageStep(IGenerateHumanMessageStep):
                 padding_problem_text: str = None,
                 no_references_setting=None,
                 **kwargs) -> List[BaseMessage]:
-        prompt = prompt if no_references_setting.get('status') == 'designated_answer' else no_references_setting.get(
+        prompt = prompt if (paragraph_list is not None and len(paragraph_list) > 0) else no_references_setting.get(
             'value')
         exec_problem_text = padding_problem_text if padding_problem_text is not None else problem_text
         start_index = len(history_chat_record) - dialogue_number

apps/application/chat_pipeline/step/reset_problem_step/i_reset_problem_step.py

@@ -28,7 +28,7 @@ class IResetProblemStep(IBaseChatPipelineStep):
         history_chat_record = serializers.ListField(child=InstanceField(model_type=ChatRecord, required=True),
                                                     error_messages=ErrMessage.list("历史对答"))
         # 大语言模型
-        chat_model = ModelField(error_messages=ErrMessage.base("大语言模型"))
+        chat_model = ModelField(required=False, allow_null=True, error_messages=ErrMessage.base("大语言模型"))
 
     def get_step_serializer(self, manage: PipelineManage) -> Type[serializers.Serializer]:
         return self.InstanceSerializer

apps/application/chat_pipeline/step/reset_problem_step/impl/base_reset_problem_step.py

@@ -22,6 +22,10 @@ prompt = (
 class BaseResetProblemStep(IResetProblemStep):
     def execute(self, problem_text: str, history_chat_record: List[ChatRecord] = None, chat_model: BaseChatModel = None,
                 **kwargs) -> str:
+        if chat_model is None:
+            self.context['message_tokens'] = 0
+            self.context['answer_tokens'] = 0
+            return problem_text
         start_index = len(history_chat_record) - 3
         history_message = [[history_chat_record[index].get_human_message(), history_chat_record[index].get_ai_message()]
                            for index in
@@ -35,8 +39,14 @@ class BaseResetProblemStep(IResetProblemStep):
                                    response.content.index('<data>') + 6:response.content.index('</data>')]
             if padding_problem_data is not None and len(padding_problem_data.strip()) > 0:
                 padding_problem = padding_problem_data
-        self.context['message_tokens'] = chat_model.get_num_tokens_from_messages(message_list)
+        try:
-        self.context['answer_tokens'] = chat_model.get_num_tokens(padding_problem)
+            request_token = chat_model.get_num_tokens_from_messages(message_list)
+            response_token = chat_model.get_num_tokens(padding_problem)
+        except Exception as e:
+            request_token = 0
+            response_token = 0
+        self.context['message_tokens'] = request_token
+        self.context['answer_tokens'] = response_token
         return padding_problem
 
     def get_details(self, manage, **kwargs):

apps/application/migrations/0005_alter_chat_abstract_alter_chatrecord_answer_text.py

@@ -0,0 +1,23 @@
+# Generated by Django 4.1.13 on 2024-04-29 13:33
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('application', '0004_applicationaccesstoken_show_source'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='chat',
+            name='abstract',
+            field=models.CharField(max_length=1024, verbose_name='摘要'),
+        ),
+        migrations.AlterField(
+            model_name='chatrecord',
+            name='answer_text',
+            field=models.CharField(max_length=40960, verbose_name='答案'),
+        ),
+    ]

apps/application/models/application.py

@@ -73,7 +73,7 @@ class ApplicationDatasetMapping(AppModelMixin):
 class Chat(AppModelMixin):
     id = models.UUIDField(primary_key=True, max_length=128, default=uuid.uuid1, editable=False, verbose_name="主键id")
     application = models.ForeignKey(Application, on_delete=models.CASCADE)
-    abstract = models.CharField(max_length=256, verbose_name="摘要")
+    abstract = models.CharField(max_length=1024, verbose_name="摘要")
     client_id = models.UUIDField(verbose_name="客户端id", default=None, null=True)
 
     class Meta:
@@ -96,7 +96,7 @@ class ChatRecord(AppModelMixin):
     vote_status = models.CharField(verbose_name='投票', max_length=10, choices=VoteChoices.choices,
                                    default=VoteChoices.UN_VOTE)
     problem_text = models.CharField(max_length=1024, verbose_name="问题")
-    answer_text = models.CharField(max_length=4096, verbose_name="答案")
+    answer_text = models.CharField(max_length=40960, verbose_name="答案")
     message_tokens = models.IntegerField(verbose_name="请求token数量", default=0)
     answer_tokens = models.IntegerField(verbose_name="响应token数量", default=0)
     const = models.IntegerField(verbose_name="总费用", default=0)

apps/application/serializers/application_serializers.py

@@ -47,7 +47,8 @@ chat_cache = cache.caches['chat_cache']
 
 class ModelDatasetAssociation(serializers.Serializer):
     user_id = serializers.UUIDField(required=True, error_messages=ErrMessage.uuid("用户id"))
-    model_id = serializers.CharField(required=True, error_messages=ErrMessage.char("模型id"))
+    model_id = serializers.CharField(required=False, allow_null=True, allow_blank=True,
+                                     error_messages=ErrMessage.char("模型id"))
     dataset_id_list = serializers.ListSerializer(required=False, child=serializers.UUIDField(required=True,
                                                                                              error_messages=ErrMessage.uuid(
                                                                                                  "知识库id")),
@@ -57,8 +58,9 @@ class ModelDatasetAssociation(serializers.Serializer):
         super().is_valid(raise_exception=True)
         model_id = self.data.get('model_id')
         user_id = self.data.get('user_id')
-        if not QuerySet(Model).filter(id=model_id).exists():
+        if model_id is not None and len(model_id) > 0:
-            raise AppApiException(500, f'模型不存在【{model_id}】')
+            if not QuerySet(Model).filter(id=model_id).exists():
+                raise AppApiException(500, f'模型不存在【{model_id}】')
         dataset_id_list = list(set(self.data.get('dataset_id_list')))
         exist_dataset_id_list = [str(dataset.id) for dataset in
                                  QuerySet(DataSet).filter(id__in=dataset_id_list, user_id=user_id)]
@@ -109,7 +111,8 @@ class ApplicationSerializer(serializers.Serializer):
     desc = serializers.CharField(required=False, allow_null=True, allow_blank=True,
                                  max_length=256, min_length=1,
                                  error_messages=ErrMessage.char("应用描述"))
-    model_id = serializers.CharField(required=True, error_messages=ErrMessage.char("模型"))
+    model_id = serializers.CharField(required=False, allow_null=True, allow_blank=True,
+                                     error_messages=ErrMessage.char("模型"))
     multiple_rounds_dialogue = serializers.BooleanField(required=True, error_messages=ErrMessage.char("多轮对话"))
     prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=1024,
                                      error_messages=ErrMessage.char("开场白"))
@@ -254,7 +257,8 @@ class ApplicationSerializer(serializers.Serializer):
                                      error_messages=ErrMessage.char("应用名称"))
         desc = serializers.CharField(required=False, max_length=256, min_length=1, allow_null=True, allow_blank=True,
                                      error_messages=ErrMessage.char("应用描述"))
-        model_id = serializers.CharField(required=False, error_messages=ErrMessage.char("模型"))
+        model_id = serializers.CharField(required=False, allow_blank=True, allow_null=True,
+                                         error_messages=ErrMessage.char("模型"))
         multiple_rounds_dialogue = serializers.BooleanField(required=False,
                                                             error_messages=ErrMessage.boolean("多轮会话"))
         prologue = serializers.CharField(required=False, allow_null=True, allow_blank=True, max_length=1024,
@@ -494,22 +498,21 @@ class ApplicationSerializer(serializers.Serializer):
             application_id = self.data.get("application_id")
 
             application = QuerySet(Application).get(id=application_id)
-
+            if instance.get('model_id') is None or len(instance.get('model_id')) == 0:
-            model = QuerySet(Model).filter(
+                application.model_id = None
-                id=instance.get('model_id') if 'model_id' in instance else application.model_id,
+            else:
-                user_id=application.user_id).first()
+                model = QuerySet(Model).filter(
-            if model is None:
+                    id=instance.get('model_id'),
-                raise AppApiException(500, "模型不存在")
+                    user_id=application.user_id).first()
-
+                if model is None:
+                    raise AppApiException(500, "模型不存在")
             update_keys = ['name', 'desc', 'model_id', 'multiple_rounds_dialogue', 'prologue', 'status',
                            'dataset_setting', 'model_setting', 'problem_optimization',
                            'api_key_is_active', 'icon']
             for update_key in update_keys:
                 if update_key in instance and instance.get(update_key) is not None:
                     if update_key == 'multiple_rounds_dialogue':
-                        application.__setattr__('dialogue_number',
+                        application.__setattr__('dialogue_number', 0 if not instance.get(update_key) else 3)
-                                                0 if not instance.get(update_key) else ModelProvideConstants[
-                                                    model.provider].value.get_dialogue_number())
                     else:
                         application.__setattr__(update_key, instance.get(update_key))
             application.save()

apps/application/serializers/chat_message_serializers.py

@@ -27,7 +27,7 @@ from application.models.api_key_model import ApplicationPublicAccessClient, Appl
 from common.constants.authentication_type import AuthenticationType
 from common.exception.app_exception import AppApiException, AppChatNumOutOfBoundsFailed
 from common.util.field_message import ErrMessage
-from common.util.rsa_util import decrypt
+from common.util.rsa_util import rsa_long_decrypt
 from common.util.split_model import flat_map
 from dataset.models import Paragraph, Document
 from setting.models import Model, Status
@@ -138,7 +138,7 @@ def get_post_handler(chat_info: ChatInfo):
 
 class ChatMessageSerializer(serializers.Serializer):
     chat_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char("对话id"))
-    message = serializers.CharField(required=True, error_messages=ErrMessage.char("用户问题"))
+    message = serializers.CharField(required=True, error_messages=ErrMessage.char("用户问题"), max_length=1024)
     stream = serializers.BooleanField(required=True, error_messages=ErrMessage.char("是否流式回答"))
     re_chat = serializers.BooleanField(required=True, error_messages=ErrMessage.char("是否重新回答"))
     application_id = serializers.UUIDField(required=False, allow_null=True, error_messages=ErrMessage.uuid("应用id"))
@@ -167,9 +167,11 @@ class ChatMessageSerializer(serializers.Serializer):
             chat_cache.set(chat_id,
                            chat_info, timeout=60 * 30)
         model = chat_info.application.model
+        if model is None:
+            return chat_info
         model = QuerySet(Model).filter(id=model.id).first()
         if model is None:
-            raise AppApiException(500, "模型不存在")
+            return chat_info
         if model.status == Status.ERROR:
             raise AppApiException(500, "当前模型不可用")
         if model.status == Status.DOWNLOAD:
@@ -223,7 +225,7 @@ class ChatMessageSerializer(serializers.Serializer):
             # 对话模型
             chat_model = ModelProvideConstants[model.provider].value.get_model(model.model_type, model.model_name,
                                                                                json.loads(
-                                                                                   decrypt(model.credential)),
+                                                                                   rsa_long_decrypt(model.credential)),
                                                                                streaming=True)
         # 数据集id列表
         dataset_id_list = [str(row.dataset_id) for row in

apps/application/serializers/chat_serializers.py

@@ -35,7 +35,7 @@ from common.util.common import post
 from common.util.field_message import ErrMessage
 from common.util.file_util import get_file_content
 from common.util.lock import try_lock, un_lock
-from common.util.rsa_util import decrypt
+from common.util.rsa_util import rsa_long_decrypt
 from dataset.models import Document, Problem, Paragraph, ProblemParagraphMapping
 from dataset.serializers.paragraph_serializers import ParagraphSerializers
 from setting.models import Model
@@ -195,7 +195,8 @@ class ChatSerializers(serializers.Serializer):
             if model is not None:
                 chat_model = ModelProvideConstants[model.provider].value.get_model(model.model_type, model.model_name,
                                                                                    json.loads(
-                                                                                       decrypt(model.credential)),
+                                                                                       rsa_long_decrypt(
+                                                                                           model.credential)),
                                                                                    streaming=True)
 
             chat_id = str(uuid.uuid1())
@@ -213,7 +214,8 @@ class ChatSerializers(serializers.Serializer):
 
         id = serializers.UUIDField(required=False, allow_null=True,
                                    error_messages=ErrMessage.uuid("应用id"))
-        model_id = serializers.UUIDField(required=True, error_messages=ErrMessage.uuid("模型id"))
+        model_id = serializers.CharField(required=False, allow_null=True, allow_blank=True,
+                                         error_messages=ErrMessage.uuid("模型id"))
 
         multiple_rounds_dialogue = serializers.BooleanField(required=True,
                                                             error_messages=ErrMessage.boolean("多轮会话"))
@@ -246,14 +248,18 @@ class ChatSerializers(serializers.Serializer):
         def open(self):
             user_id = self.is_valid(raise_exception=True)
             chat_id = str(uuid.uuid1())
-            model = QuerySet(Model).filter(user_id=user_id, id=self.data.get('model_id')).first()
+            model_id = self.data.get('model_id')
-            if model is None:
+            if model_id is not None and len(model_id) > 0:
-                raise AppApiException(500, "模型不存在")
+                model = QuerySet(Model).filter(user_id=user_id, id=self.data.get('model_id')).first()
+                chat_model = ModelProvideConstants[model.provider].value.get_model(model.model_type, model.model_name,
+                                                                                   json.loads(
+                                                                                       rsa_long_decrypt(
+                                                                                           model.credential)),
+                                                                                   streaming=True)
+            else:
+                model = None
+                chat_model = None
             dataset_id_list = self.data.get('dataset_id_list')
-            chat_model = ModelProvideConstants[model.provider].value.get_model(model.model_type, model.model_name,
-                                                                               json.loads(
-                                                                                   decrypt(model.credential)),
-                                                                               streaming=True)
             application = Application(id=None, dialogue_number=3, model=model,
                                       dataset_setting=self.data.get('dataset_setting'),
                                       model_setting=self.data.get('model_setting'),

apps/common/util/rsa_util.py

@@ -62,18 +62,6 @@ def get_key_pair_by_sql():
     return system_setting.meta
 
 
-# def get_key_pair():
-#     if not os.path.exists("/opt/maxkb/conf/receiver.pem"):
-#         kv = generate()
-#         private_file_out = open("/opt/maxkb/conf/private.pem", "wb")
-#         private_file_out.write(kv.get('value'))
-#         private_file_out.close()
-#         receiver_file_out = open("/opt/maxkb/conf/receiver.pem", "wb")
-#         receiver_file_out.write(kv.get('key'))
-#         receiver_file_out.close()
-#     return {'key': open("/opt/maxkb/conf/receiver.pem").read(), 'value': open("/opt/maxkb/conf/private.pem").read()}
-
-
 def encrypt(msg, public_key: str | None = None):
     """
     加密
@@ -100,3 +88,53 @@ def decrypt(msg, pri_key: str | None = None):
     cipher = PKCS1_cipher.new(RSA.importKey(pri_key, passphrase=secret_code))
     decrypt_data = cipher.decrypt(base64.b64decode(msg), 0)
     return decrypt_data.decode("utf-8")
+
+
+def rsa_long_encrypt(message, public_key: str | None = None, length=200):
+    """
+    超长文本加密
+
+    :param message:         需要加密的字符串
+    :param public_key   公钥
+    :param length:      1024bit的证书用100， 2048bit的证书用 200
+    :return: 加密后的数据
+    """
+    # 读取公钥
+    if public_key is None:
+        public_key = get_key_pair().get('key')
+    cipher = PKCS1_cipher.new(RSA.importKey(extern_key=public_key,
+                                            passphrase=secret_code))
+    # 处理：Plaintext is too long. 分段加密
+    if len(message) <= length:
+        # 对编码的数据进行加密，并通过base64进行编码
+        result = base64.b64encode(cipher.encrypt(message.encode('utf-8')))
+    else:
+        rsa_text = []
+        # 对编码后的数据进行切片，原因：加密长度不能过长
+        for i in range(0, len(message), length):
+            cont = message[i:i + length]
+            # 对切片后的数据进行加密，并新增到text后面
+            rsa_text.append(cipher.encrypt(cont.encode('utf-8')))
+        # 加密完进行拼接
+        cipher_text = b''.join(rsa_text)
+        # base64进行编码
+        result = base64.b64encode(cipher_text)
+    return result.decode()
+
+
+def rsa_long_decrypt(message, pri_key: str | None = None, length=256):
+    """
+    超长文本解密，默认不加密
+    :param  message:    需要解密的数据
+    :param  pri_key:    秘钥
+    :param  length :     1024bit的证书用128，2048bit证书用256位
+    :return: 解密后的数据
+    """
+    if pri_key is None:
+        pri_key = get_key_pair().get('value')
+    cipher = PKCS1_cipher.new(RSA.importKey(pri_key, passphrase=secret_code))
+    base64_de = base64.b64decode(message)
+    res = []
+    for i in range(0, len(base64_de), length):
+        res.append(cipher.decrypt(base64_de[i:i + length], 0))
+    return b"".join(res).decode()

apps/dataset/serializers/document_serializers.py

@@ -164,6 +164,8 @@ class DocumentSerializers(ApiMixin, serializers.Serializer):
             elif target_dataset.type == Type.base.value and dataset.type == Type.web.value:
                 document_list.update(dataset_id=target_dataset_id, type=Type.base,
                                      meta={})
+            else:
+                document_list.update(dataset_id=target_dataset_id)
             paragraph_list.update(dataset_id=target_dataset_id)
             ListenerManagement.update_embedding_dataset_id(UpdateEmbeddingDatasetIdArgs(
                 [problem_paragraph_mapping.id for problem_paragraph_mapping in problem_paragraph_mapping_list],
@@ -713,6 +715,19 @@ class DocumentSerializers(ApiMixin, serializers.Serializer):
             ListenerManagement.delete_embedding_by_document_list_signal.send(document_id_list)
             return True
 
+        def batch_edit_hit_handling(self, instance: Dict, with_valid=True):
+            if with_valid:
+                BatchSerializer(data=instance).is_valid(model=Document, raise_exception=True)
+                hit_handling_method = instance.get('hit_handling_method')
+                if hit_handling_method is None:
+                    raise AppApiException(500, '命中处理方式必填')
+                if hit_handling_method != 'optimization' and hit_handling_method != 'directly_return':
+                    raise AppApiException(500, '命中处理方式必须为directly_return|optimization')
+                self.is_valid(raise_exception=True)
+            document_id_list = instance.get("id_list")
+            hit_handling_method = instance.get('hit_handling_method')
+            QuerySet(Document).filter(id__in=document_id_list).update(hit_handling_method=hit_handling_method)
+
 
 class FileBufferHandle:
     buffer = None

apps/dataset/swagger_api/document_api.py

@@ -0,0 +1,27 @@
+# coding=utf-8
+"""
+    @project: maxkb
+    @Author：虎
+    @file： document_api.py
+    @date：2024/4/28 13:56
+    @desc:
+"""
+from drf_yasg import openapi
+
+from common.mixins.api_mixin import ApiMixin
+
+
+class DocumentApi(ApiMixin):
+    class BatchEditHitHandlingApi(ApiMixin):
+        @staticmethod
+        def get_request_body_api():
+            return openapi.Schema(
+                type=openapi.TYPE_OBJECT,
+                properties={
+                    'id_list': openapi.Schema(type=openapi.TYPE_ARRAY, items=openapi.Schema(type=openapi.TYPE_STRING),
+                                              title="主键id列表",
+                                              description="主键id列表"),
+                    'hit_handling_method': openapi.Schema(type=openapi.TYPE_STRING, title="命中处理方式",
+                                                          description="directly_return|optimization")
+                }
+            )

apps/dataset/urls.py

@@ -14,6 +14,7 @@ urlpatterns = [
     path('dataset/<str:dataset_id>/document', views.Document.as_view(), name='document'),
     path('dataset/<str:dataset_id>/document/web', views.WebDocument.as_view()),
     path('dataset/<str:dataset_id>/document/_bach', views.Document.Batch.as_view()),
+    path('dataset/<str:dataset_id>/document/batch_hit_handling', views.Document.BatchEditHitHandling.as_view()),
     path('dataset/<str:dataset_id>/document/<int:current_page>/<int:page_size>', views.Document.Page.as_view()),
     path('dataset/<str:dataset_id>/document/<str:document_id>', views.Document.Operate.as_view(),
          name="document_operate"),

apps/dataset/views/document.py

@@ -19,6 +19,7 @@ from common.response import result
 from common.util.common import query_params_to_single_dict
 from dataset.serializers.common_serializers import BatchSerializer
 from dataset.serializers.document_serializers import DocumentSerializers, DocumentWebInstanceSerializer
+from dataset.swagger_api.document_api import DocumentApi
 
 
 class WebDocument(APIView):
@@ -71,6 +72,24 @@ class Document(APIView):
         d.is_valid(raise_exception=True)
         return result.success(d.list())
 
+    class BatchEditHitHandling(APIView):
+        authentication_classes = [TokenAuth]
+
+        @action(methods=['POST'], detail=False)
+        @swagger_auto_schema(operation_summary="批量修改文档命中处理方式",
+                             operation_id="批量修改文档命中处理方式",
+                             request_body=
+                             DocumentApi.BatchEditHitHandlingApi.get_request_body_api(),
+                             manual_parameters=DocumentSerializers.Create.get_request_params_api(),
+                             responses=result.get_default_response(),
+                             tags=["知识库/文档"])
+        @has_permissions(
+            lambda r, k: Permission(group=Group.DATASET, operate=Operate.MANAGE,
+                                    dynamic_tag=k.get('dataset_id')))
+        def put(self, request: Request, dataset_id: str):
+            return result.success(
+                DocumentSerializers.Batch(data={'dataset_id': dataset_id}).batch_edit_hit_handling(request.data))
+
     class Batch(APIView):
         authentication_classes = [TokenAuth]
 

apps/embedding/migrations/0002_embedding_search_vector.py

@@ -18,27 +18,30 @@ def update_embedding_search_vector(embedding, paragraph_list):
 
 
 def save_keywords(apps, schema_editor):
-    document = apps.get_model("dataset", "Document")
+    try:
-    embedding = apps.get_model("embedding", "Embedding")
+        document = apps.get_model("dataset", "Document")
-    paragraph = apps.get_model('dataset', 'Paragraph')
+        embedding = apps.get_model("embedding", "Embedding")
-    db_alias = schema_editor.connection.alias
+        paragraph = apps.get_model('dataset', 'Paragraph')
-    document_list = document.objects.using(db_alias).all()
+        db_alias = schema_editor.connection.alias
-    for document in document_list:
+        document_list = document.objects.using(db_alias).all()
-        document.status = Status.embedding
+        for document in document_list:
-        document.save()
+            document.status = Status.embedding
-        paragraph_list = paragraph.objects.using(db_alias).filter(document=document).all()
+            document.save()
-        embedding_list = embedding.objects.using(db_alias).filter(document=document).values('id', 'search_vector',
+            paragraph_list = paragraph.objects.using(db_alias).filter(document=document).all()
-                                                                                            'paragraph')
+            embedding_list = embedding.objects.using(db_alias).filter(document=document).values('id', 'search_vector',
-        embedding_update_list = [update_embedding_search_vector(embedding, paragraph_list) for embedding
+                                                                                                'paragraph')
-                                 in embedding_list]
+            embedding_update_list = [update_embedding_search_vector(embedding, paragraph_list) for embedding
-        child_array = sub_array(embedding_update_list, 50)
+                                     in embedding_list]
-        for c in child_array:
+            child_array = sub_array(embedding_update_list, 50)
-            try:
+            for c in child_array:
-                embedding.objects.using(db_alias).bulk_update(c, ['search_vector'])
+                try:
-            except Exception as e:
+                    embedding.objects.using(db_alias).bulk_update(c, ['search_vector'])
-                print(e)
+                except Exception as e:
-        document.status = Status.success
+                    print(e)
-        document.save()
+            document.status = Status.success
+            document.save()
+    except Exception as e:
+        print(e)
 
 
 class Migration(migrations.Migration):

apps/setting/migrations/0004_alter_model_credential.py

@@ -0,0 +1,18 @@
+# Generated by Django 4.1.13 on 2024-04-28 18:06
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('setting', '0003_model_meta_model_status'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='model',
+            name='credential',
+            field=models.CharField(max_length=102400, verbose_name='模型认证信息'),
+        ),
+    ]

apps/setting/models/model_management.py

@@ -42,7 +42,7 @@ class Model(AppModelMixin):
 
     provider = models.CharField(max_length=128, verbose_name='供应商')
 
-    credential = models.CharField(max_length=5120, verbose_name="模型认证信息")
+    credential = models.CharField(max_length=102400, verbose_name="模型认证信息")
 
     meta = models.JSONField(verbose_name="模型元数据,用于存储下载,或者错误信息", default=dict)
 

apps/setting/serializers/provider_serializers.py

@@ -18,7 +18,7 @@ from rest_framework import serializers
 from application.models import Application
 from common.exception.app_exception import AppApiException
 from common.util.field_message import ErrMessage
-from common.util.rsa_util import encrypt, decrypt
+from common.util.rsa_util import rsa_long_decrypt, rsa_long_encrypt
 from setting.models.model_management import Model, Status
 from setting.models_provider.base_model_provider import ValidCode, DownModelChunkStatus
 from setting.models_provider.constants.model_provider_constants import ModelProvideConstants
@@ -118,7 +118,7 @@ class ModelSerializer(serializers.Serializer):
 
             model_credential = ModelProvideConstants[provider].value.get_model_credential(model_type,
                                                                                           model_name)
-            source_model_credential = json.loads(decrypt(model.credential))
+            source_model_credential = json.loads(rsa_long_decrypt(model.credential))
             source_encryption_model_credential = model_credential.encryption_dict(source_model_credential)
             if credential is not None:
                 for k in source_encryption_model_credential.keys():
@@ -170,7 +170,7 @@ class ModelSerializer(serializers.Serializer):
             model_name = self.data.get('model_name')
             model_credential_str = json.dumps(credential)
             model = Model(id=uuid.uuid1(), status=status, user_id=user_id, name=name,
-                          credential=encrypt(model_credential_str),
+                          credential=rsa_long_encrypt(model_credential_str),
                           provider=provider, model_type=model_type, model_name=model_name)
             model.save()
             if status == Status.DOWNLOAD:
@@ -180,7 +180,7 @@ class ModelSerializer(serializers.Serializer):
 
     @staticmethod
     def model_to_dict(model: Model):
-        credential = json.loads(decrypt(model.credential))
+        credential = json.loads(rsa_long_decrypt(model.credential))
         return {'id': str(model.id), 'provider': model.provider, 'name': model.name, 'model_type': model.model_type,
                 'model_name': model.model_name,
                 'status': model.status,
@@ -252,7 +252,7 @@ class ModelSerializer(serializers.Serializer):
                     if update_key in instance and instance.get(update_key) is not None:
                         if update_key == 'credential':
                             model_credential_str = json.dumps(credential)
-                            model.__setattr__(update_key, encrypt(model_credential_str))
+                            model.__setattr__(update_key, rsa_long_encrypt(model_credential_str))
                         else:
                             model.__setattr__(update_key, instance.get(update_key))
             model.save()

ui/src/api/dataset.ts

@@ -73,7 +73,7 @@ const postDataset: (data: datasetData, loading?: Ref<boolean>) => Promise<Result
   data,
   loading
 ) => {
-  return post(`${prefix}`, data, undefined, loading)
+  return post(`${prefix}`, data, undefined, loading, 1000 * 60 * 5)
 }
 
 /**

ui/src/api/document.ts

@@ -10,7 +10,7 @@ const prefix = '/dataset'
  * @param 参数  file:file,limit:number,patterns:array,with_filter:boolean
  */
 const postSplitDocument: (data: any) => Promise<Result<any>> = (data) => {
-  return post(`${prefix}/document/split`, data)
+  return post(`${prefix}/document/split`, data, undefined, undefined, 1000 * 60 * 60)
 }
 
 /**
@@ -80,7 +80,7 @@ const postDocument: (
   data: any,
   loading?: Ref<boolean>
 ) => Promise<Result<any>> = (dataset_id, data, loading) => {
-  return post(`${prefix}/${dataset_id}/document/_bach`, data, {}, loading)
+  return post(`${prefix}/${dataset_id}/document/_bach`, data, {}, loading, 1000 * 60 * 5)
 }
 
 /**
@@ -206,6 +206,20 @@ const putMigrateMulDocument: (
   )
 }
 
+/**
+ * 批量修改命中方式
+ * @param dataset_id 知识库id
+ * @param data       {id_list:[],hit_handling_method:'directly_return|optimization'}
+ * @param loading
+ * @returns
+ */
+const batchEditHitHandling: (
+  dataset_id: string,
+  data: any,
+  loading?: Ref<boolean>
+) => Promise<Result<boolean>> = (dataset_id, data, loading) => {
+  return put(`${prefix}/${dataset_id}/document/batch_hit_handling`, data, undefined, loading)
+}
 export default {
   postSplitDocument,
   getDocument,
@@ -219,5 +233,6 @@ export default {
   putDocumentRefresh,
   delMulSyncDocument,
   postWebDocument,
-  putMigrateMulDocument
+  putMigrateMulDocument,
+  batchEditHitHandling
 }

ui/src/api/type/application.ts

@@ -56,7 +56,7 @@ export class ChatRecordManage {
         this.chat.answer_text =
           this.chat.answer_text + this.chat.buffer.splice(0, this.chat.buffer.length - 20).join('')
       } else if (this.is_close) {
-        this.chat.answer_text = this.chat.answer_text + this.chat.buffer.join('')
+        this.chat.answer_text = this.chat.answer_text + this.chat.buffer.splice(0).join('')
         this.chat.write_ed = true
         this.write_ed = true
         if (this.loading) {

ui/src/components/ai-chat/ParagraphSourceDialog.vue

@@ -5,6 +5,7 @@
     v-model="dialogVisible"
     destroy-on-close
     append-to-body
+    align-center
   >
     <div class="paragraph-source-height">
       <el-scrollbar>
@@ -63,7 +64,7 @@
   </el-dialog>
 </template>
 <script setup lang="ts">
-import { ref, watch, nextTick } from 'vue'
+import { ref, watch, onBeforeUnmount } from 'vue'
 import { cloneDeep } from 'lodash'
 import { arraySort } from '@/utils/utils'
 const emit = defineEmits(['refresh'])
@@ -86,12 +87,15 @@ const open = (data: any, id?: string) => {
   detail.value.paragraph_list = arraySort(detail.value.paragraph_list, 'similarity', true)
   dialogVisible.value = true
 }
-
+onBeforeUnmount(() => {
+  dialogVisible.value = false
+})
 defineExpose({ open })
 </script>
 <style lang="scss">
 .paragraph-source {
   padding: 0;
+
   .el-dialog__header {
     padding: 24px 24px 0 24px;
   }
@@ -102,4 +106,9 @@ defineExpose({ open })
     height: calc(100vh - 260px);
   }
 }
+@media only screen and (max-width: 768px) {
+  .paragraph-source {
+    width: 90% !important;
+  }
+}
 </style>

ui/src/components/ai-chat/index.vue

@@ -224,7 +224,7 @@ const chartOpenId = ref('')
 const chatList = ref<any[]>([])
 
 const isDisabledChart = computed(
-  () => !(inputValue.value.trim() && (props.appId || (props.data?.name && props.data?.model_id)))
+  () => !(inputValue.value.trim() && (props.appId || props.data?.name))
 )
 const isMdArray = (val: string) => val.match(/^-\s.*/m)
 const prologueList = computed(() => {
@@ -274,12 +274,7 @@ function openParagraph(row: any, id?: string) {
 }
 
 function quickProblemHandle(val: string) {
-  if (!props.log && !loading.value && props.data?.name && props.data?.model_id) {
+  if (!loading.value && props.data?.name) {
-    // inputValue.value = val
-    // nextTick(() => {
-    //   quickInputRef.value?.focus()
-    // })
-
     handleDebounceClick(val)
   }
 }
@@ -509,16 +504,14 @@ function regenerationChart(item: chatType) {
 }
 
 function getSourceDetail(row: any) {
-  logApi
+  logApi.getRecordDetail(id || props.appId, row.chat_id, row.record_id, loading).then((res) => {
-    .getRecordDetail(id || props.appId, row.chat_id, row.record_id, loading)
+    const exclude_keys = ['answer_text', 'id']
-    .then((res) => {
+    Object.keys(res.data).forEach((key) => {
-      const exclude_keys = ['answer_text', 'id']
+      if (!exclude_keys.includes(key)) {
-      Object.keys(res.data).forEach((key) => {
+        row[key] = res.data[key]
-        if (!exclude_keys.includes(key)) {
+      }
-          row[key] = res.data[key]
-        }
-      })
     })
+  })
   return true
 }
 

ui/src/request/index.ts

@@ -119,9 +119,15 @@ const promise: (
 export const get: (
   url: string,
   params?: unknown,
-  loading?: NProgress | Ref<boolean>
+  loading?: NProgress | Ref<boolean>,
-) => Promise<Result<any>> = (url: string, params: unknown, loading?: NProgress | Ref<boolean>) => {
+  timeout?: number
-  return promise(request({ url: url, method: 'get', params }), loading)
+) => Promise<Result<any>> = (
+  url: string,
+  params: unknown,
+  loading?: NProgress | Ref<boolean>,
+  timeout?: number
+) => {
+  return promise(request({ url: url, method: 'get', params, timeout: timeout }), loading)
 }
 
 /**
@@ -136,9 +142,10 @@ export const post: (
   url: string,
   data?: unknown,
   params?: unknown,
-  loading?: NProgress | Ref<boolean>
+  loading?: NProgress | Ref<boolean>,
-) => Promise<Result<any> | any> = (url, data, params, loading) => {
+  timeout?: number
-  return promise(request({ url: url, method: 'post', data, params }), loading)
+) => Promise<Result<any> | any> = (url, data, params, loading, timeout) => {
+  return promise(request({ url: url, method: 'post', data, params, timeout }), loading)
 }
 
 /**|
@@ -153,9 +160,10 @@ export const put: (
   url: string,
   data?: unknown,
   params?: unknown,
-  loading?: NProgress | Ref<boolean>
+  loading?: NProgress | Ref<boolean>,
-) => Promise<Result<any>> = (url, data, params, loading) => {
+  timeout?: number
-  return promise(request({ url: url, method: 'put', data, params }), loading)
+) => Promise<Result<any>> = (url, data, params, loading, timeout) => {
+  return promise(request({ url: url, method: 'put', data, params, timeout }), loading)
 }
 
 /**
@@ -169,9 +177,10 @@ export const del: (
   url: string,
   params?: unknown,
   data?: unknown,
-  loading?: NProgress | Ref<boolean>
+  loading?: NProgress | Ref<boolean>,
-) => Promise<Result<any>> = (url, params, data, loading) => {
+  timeout?: number
-  return promise(request({ url: url, method: 'delete', params, data }), loading)
+) => Promise<Result<any>> = (url, params, data, loading, timeout) => {
+  return promise(request({ url: url, method: 'delete', params, data, timeout }), loading)
 }
 
 /**

ui/src/views/application-overview/component/EditAvatarDialog.vue

@@ -35,7 +35,7 @@
               accept="image/*"
               :on-change="onChange"
             >
-              <el-button icon="Upload">上传</el-button>
+              <el-button icon="Upload" :disabled="radioType !== 'custom'">上传</el-button>
             </el-upload>
           </div>
           <div class="el-upload__tip info mt-16">

ui/src/views/application/CreateAndSetting.vue

@@ -48,7 +48,7 @@
               <el-form-item label="AI 模型" prop="model_id">
                 <template #label>
                   <div class="flex-between">
-                    <span>AI 模型 <span class="danger">*</span></span>
+                    <span>AI 模型 </span>
                   </div>
                 </template>
                 <el-select
@@ -56,6 +56,7 @@
                   placeholder="请选择 AI 模型"
                   class="w-full"
                   popper-class="select-model"
+                  :clearable="true"
                 >
                   <el-option-group
                     v-for="(value, label) in modelOptions"
@@ -338,7 +339,7 @@ const rules = reactive<FormRules<ApplicationFormType>>({
   name: [{ required: true, message: '请输入应用名称', trigger: 'blur' }],
   model_id: [
     {
-      required: true,
+      required: false,
       message: '请选择模型',
       trigger: 'change'
     }

ui/src/views/application/components/ParamSettingDialog.vue

@@ -251,7 +251,7 @@ defineExpose({ open })
     padding: 0 !important;
   }
   .dialog-max-height {
-    height: calc(100vh - 180px);
+    height: 550px;
   }
   .custom-slider {
     .el-input-number.is-without-controls .el-input__wrapper {

ui/src/views/document/component/BatchEditDocumentDialog.vue

@@ -0,0 +1,96 @@
+<template>
+  <el-dialog
+    title="设置"
+    v-model="dialogVisible"
+    :close-on-click-modal="false"
+    :close-on-press-escape="false"
+    :destroy-on-close="true"
+    width="400"
+  >
+    <el-form
+      label-position="top"
+      ref="webFormRef"
+      :rules="rules"
+      :model="form"
+      require-asterisk-position="right"
+    >
+      <el-form-item>
+        <template #label>
+          <div class="flex align-center">
+            <span class="mr-4">命中处理方式</span>
+            <el-tooltip
+              effect="dark"
+              content="用户提问时，命中文档下的分段时按照设置的方式进行处理。"
+              placement="right"
+            >
+              <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+            </el-tooltip>
+          </div>
+        </template>
+        <el-radio-group v-model="form.hit_handling_method">
+          <template v-for="(value, key) of hitHandlingMethod" :key="key">
+            <el-radio :value="key">{{ value }}</el-radio>
+          </template>
+        </el-radio-group>
+      </el-form-item>
+    </el-form>
+    <template #footer>
+      <span class="dialog-footer">
+        <el-button @click.prevent="dialogVisible = false"> 取消 </el-button>
+        <el-button type="primary" @click="submit(webFormRef)" :loading="loading"> 确定 </el-button>
+      </span>
+    </template>
+  </el-dialog>
+</template>
+<script setup lang="ts">
+import { ref, reactive, watch } from 'vue'
+import { useRoute } from 'vue-router'
+import type { FormInstance, FormRules } from 'element-plus'
+import documentApi from '@/api/document'
+import { MsgSuccess } from '@/utils/message'
+import { hitHandlingMethod } from '../utils'
+
+const route = useRoute()
+const {
+  params: { id }
+} = route as any
+
+const emit = defineEmits(['refresh'])
+const webFormRef = ref()
+const loading = ref<boolean>(false)
+const documentList = ref<Array<string>>([])
+const form = ref<any>({
+  hit_handling_method: 'optimization'
+})
+
+const rules = reactive({
+  source_url: [{ required: true, message: '请输入文档地址', trigger: 'blur' }]
+})
+
+const dialogVisible = ref<boolean>(false)
+
+const open = (list: Array<string>) => {
+  documentList.value = list
+  dialogVisible.value = true
+}
+
+const submit = async (formEl: FormInstance | undefined) => {
+  if (!formEl) return
+  await formEl.validate((valid, fields) => {
+    if (valid) {
+      const obj = {
+        hit_handling_method: form.value.hit_handling_method,
+        id_list: documentList.value
+      }
+      documentApi.batchEditHitHandling(id, obj, loading).then((res: any) => {
+        MsgSuccess('设置成功')
+        emit('refresh')
+        dialogVisible.value = false
+      })
+    }
+  })
+}
+
+defineExpose({ open })
+</script>
+<style lang="scss" scoped></style>

ui/src/views/document/index.vue

@@ -21,10 +21,13 @@
               >同步文档</el-button
             >
             <el-button @click="openDatasetDialog()" :disabled="multipleSelection.length === 0"
-              >批量迁移</el-button
+              >迁移</el-button
+            >
+            <el-button @click="openBatchEditDocument" :disabled="multipleSelection.length === 0"
+              >设置</el-button
             >
             <el-button @click="deleteMulDocument" :disabled="multipleSelection.length === 0"
-              >批量删除</el-button
+              >删除</el-button
             >
           </div>
 
@@ -212,6 +215,10 @@
       </div>
       <ImportDocumentDialog ref="ImportDocumentDialogRef" :title="title" @refresh="refresh" />
       <SyncWebDialog ref="SyncWebDialogRef" @refresh="refresh" />
+      <BatchEditDocumentDialog
+        ref="batchEditDocumentDialogRef"
+        @refresh="refresh"
+      ></BatchEditDocumentDialog>
       <!-- 选择知识库 -->
       <SelectDatasetDialog ref="SelectDatasetDialogRef" @refresh="refresh" />
     </div>
@@ -225,6 +232,7 @@ import documentApi from '@/api/document'
 import ImportDocumentDialog from './component/ImportDocumentDialog.vue'
 import SyncWebDialog from '@/views/dataset/component/SyncWebDialog.vue'
 import SelectDatasetDialog from './component/SelectDatasetDialog.vue'
+import BatchEditDocumentDialog from './component/BatchEditDocumentDialog.vue'
 import { numberFormat } from '@/utils/utils'
 import { datetimeFormat } from '@/utils/time'
 import { hitHandlingMethod } from './utils'
@@ -257,7 +265,7 @@ onBeforeRouteLeave((to: any, from: any) => {
 })
 const beforePagination = computed(() => common.paginationConfig[storeKey])
 const beforeSearch = computed(() => common.search[storeKey])
-
+const batchEditDocumentDialogRef = ref<InstanceType<typeof BatchEditDocumentDialog>>()
 const SyncWebDialogRef = ref()
 const loading = ref(false)
 let interval: any
@@ -317,6 +325,13 @@ const handleSelectionChange = (val: any[]) => {
   multipleSelection.value = val
 }
 
+function openBatchEditDocument() {
+  const arr: string[] = multipleSelection.value.map((v) => v.id)
+  if (batchEditDocumentDialogRef) {
+    batchEditDocumentDialogRef?.value?.open(arr)
+  }
+}
+
 /**
  * 初始化轮询
  */
@@ -356,9 +371,9 @@ function refreshDocument(row: any) {
         .catch(() => {})
     }
   } else {
-    // documentApi.putDocumentRefresh(row.dataset_id, row.id).then((res) => {
+    documentApi.putDocumentRefresh(row.dataset_id, row.id).then((res) => {
-    //   getList()
+      getList()
-    // })
+    })
   }
 }
 

ui/src/views/log/component/ChatRecordDrawer.vue

@@ -1,7 +1,7 @@
 <template>
   <el-drawer v-model="visible" size="60%" @close="closeHandle" class="chat-record-drawer">
     <template #header>
-      <h4>{{ currentAbstract }}</h4>
+      <h4 class="single-line">{{ currentAbstract }}</h4>
     </template>
     <div
       v-loading="paginationConfig.current_page === 1 && loading"
@@ -120,6 +120,11 @@ defineExpose({
 })
 </script>
 <style lang="scss">
+.single-line {
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
 .chat-record-drawer {
   .el-drawer__body {
     background: var(--app-layout-bg-color);