feat: add function to retrieve default parameters for embedding models

--bug=1063177 --user=刘瑞斌 【知识库】-知识库使用的模型更换维度参数值并重新向量化后，命中测试、检索报错 https://www.tapd.cn/62980211/s/1792117

apps/knowledge/serializers/common.py

@@ -112,6 +112,21 @@ class ProblemParagraphManage:
         ], problem_paragraph_mapping_list
         return result
 
+def get_embedding_model_default_params(model):
+    def convert_to_int(value):
+        if isinstance(value, str):
+            try:
+                return int(value)
+            except ValueError:
+                return value
+        return value
+
+    return {
+        p.get('field'): convert_to_int(p.get('default_value'))
+        for p in model.model_params_form
+        if p.get('default_value') is not None
+    }
+
 
 def get_embedding_model_by_knowledge_id_list(knowledge_id_list: List):
     knowledge_list = QuerySet(Knowledge).filter(id__in=knowledge_id_list)
@@ -119,17 +134,29 @@ def get_embedding_model_by_knowledge_id_list(knowledge_id_list: List):
         raise Exception(_('The knowledge base is inconsistent with the vector model'))
     if len(knowledge_list) == 0:
         raise Exception(_('Knowledge base setting error, please reset the knowledge base'))
-    return ModelManage.get_model(str(knowledge_list[0].embedding_model_id),
-                                 lambda _id: get_model(knowledge_list[0].embedding_model))
+
+    default_params = get_embedding_model_default_params(knowledge_list[0].embedding_model)
+
+    return ModelManage.get_model(
+        str(knowledge_list[0].embedding_model_id),
+        lambda _id: get_model(knowledge_list[0].embedding_model, **{**default_params})
+    )
 
 
 def get_embedding_model_by_knowledge_id(knowledge_id: str):
     knowledge = QuerySet(Knowledge).select_related('embedding_model').filter(id=knowledge_id).first()
-    return ModelManage.get_model(str(knowledge.embedding_model_id), lambda _id: get_model(knowledge.embedding_model))
+
+    default_params = get_embedding_model_default_params(knowledge.embedding_model)
+
+    return ModelManage.get_model(str(knowledge.embedding_model_id),
+                                 lambda _id: get_model(knowledge.embedding_model, **{**default_params}))
 
 
 def get_embedding_model_by_knowledge(knowledge):
-    return ModelManage.get_model(str(knowledge.embedding_model_id), lambda _id: get_model(knowledge.embedding_model))
+    default_params = get_embedding_model_default_params(knowledge.embedding_model)
+
+    return ModelManage.get_model(str(knowledge.embedding_model_id),
+                                 lambda _id: get_model(knowledge.embedding_model, **{**default_params}))
 
 
 def get_embedding_model_id_by_knowledge_id(knowledge_id):
@@ -241,7 +268,7 @@ def create_knowledge_index(knowledge_id=None, document_id=None):
         result = sql_execute(sql, [])
         if len(result) == 0:
             return
-        dims = result[0]['dims'] 
+        dims = result[0]['dims']
         sql = f"""CREATE INDEX "embedding_hnsw_idx_{k_id}" ON embedding USING hnsw ((embedding::vector({dims})) vector_cosine_ops) WHERE knowledge_id = '{k_id}'"""
         update_execute(sql, [])
         maxkb_logger.info(f'Created index for knowledge ID: {k_id}')

apps/knowledge/task/embedding.py

@@ -12,7 +12,7 @@ from common.event import ListenerManagement, UpdateProblemArgs, UpdateEmbeddingK
     UpdateEmbeddingDocumentIdArgs
 from common.utils.logger import maxkb_logger
 from knowledge.models import Document, TaskType, State
-from knowledge.serializers.common import drop_knowledge_index
+from knowledge.serializers.common import drop_knowledge_index, get_embedding_model_default_params
 from models_provider.models import Model
 from models_provider.tools import get_model
 from ops import celery_app
@@ -26,21 +26,9 @@ def get_embedding_model(model_id, exception_handler=lambda e: maxkb_logger.error
     try:
         model = QuerySet(Model).filter(id=model_id).first()
 
-        def convert_to_int(value):
-            if isinstance(value, str):
-                try:
-                    return int(value)
-                except ValueError:
-                    return value
-            return value
+        default_params = get_embedding_model_default_params(model)
 
-        s = {
-            p.get('field'): convert_to_int(p.get('default_value'))
-            for p in model.model_params_form
-            if p.get('default_value') is not None
-        }
-
-        embedding_model = ModelManage.get_model(model_id, lambda _id: get_model(model, **{**s}))
+        embedding_model = ModelManage.get_model(model_id, lambda _id: get_model(model, **{**default_params}))
     except Exception as e:
         exception_handler(e)
         raise e