diff --git a/apps/application/chat_pipeline/step/search_dataset_step/impl/base_search_dataset_step.py b/apps/application/chat_pipeline/step/search_dataset_step/impl/base_search_dataset_step.py index aacd36ed8..88c58cd04 100644 --- a/apps/application/chat_pipeline/step/search_dataset_step/impl/base_search_dataset_step.py +++ b/apps/application/chat_pipeline/step/search_dataset_step/impl/base_search_dataset_step.py @@ -37,12 +37,12 @@ def get_model_by_id(_id, user_id): def get_embedding_id(knowledge_id_list): knowledge_list = QuerySet(Knowledge).filter(id__in=knowledge_id_list) - if len(set([knowledge.embedding_mode_id for knowledge in knowledge_list])) > 1: + if len(set([knowledge.embedding_model_id for knowledge in knowledge_list])) > 1: raise Exception( _("The vector model of the associated knowledge base is inconsistent and the segmentation cannot be recalled.")) if len(knowledge_list) == 0: raise Exception(_("The knowledge base setting is wrong, please reset the knowledge base")) - return knowledge_list[0].embedding_mode_id + return knowledge_list[0].embedding_model_id class BaseSearchDatasetStep(ISearchDatasetStep): diff --git a/apps/knowledge/serializers/document.py b/apps/knowledge/serializers/document.py index 0ad13209f..f29aa17ea 100644 --- a/apps/knowledge/serializers/document.py +++ b/apps/knowledge/serializers/document.py @@ -298,7 +298,7 @@ class DocumentSerializers(serializers.Serializer): else: document_list.update(knowledge_id=target_knowledge_id) model_id = None - if knowledge.embedding_mode_id != target_knowledge.embedding_mode_id: + if knowledge.embedding_model_id != target_knowledge.embedding_model_id: model_id = get_embedding_model_id_by_knowledge_id(target_knowledge_id) pid_list = [paragraph.id for paragraph in paragraph_list] diff --git a/apps/knowledge/serializers/paragraph.py b/apps/knowledge/serializers/paragraph.py index 886403064..017b5f472 100644 --- a/apps/knowledge/serializers/paragraph.py +++ b/apps/knowledge/serializers/paragraph.py @@ -501,8 +501,8 @@ class ParagraphSerializers(serializers.Serializer): target_knowledge = QuerySet(Knowledge).filter(id=target_knowledge_id).first() knowledge = QuerySet(Knowledge).filter(id=knowledge_id).first() embedding_model_id = None - if target_knowledge.embedding_mode_id != knowledge.embedding_mode_id: - embedding_model_id = str(target_knowledge.embedding_mode_id) + if target_knowledge.embedding_model_id != knowledge.embedding_model_id: + embedding_model_id = str(target_knowledge.embedding_model_id) pid_list = [paragraph.id for paragraph in paragraph_list] # 修改段落信息 paragraph_list.update(knowledge_id=target_knowledge_id, document_id=target_document_id)