refactor: replace get_embedding_model_default_params with get_model_default_params

apps/application/chat_pipeline/step/search_dataset_step/impl/base_search_dataset_step.py

@@ -22,10 +22,9 @@ from common.db.search import native_search
 from common.utils.common import get_file_content
 from knowledge.models import Paragraph, Knowledge
 from knowledge.models import SearchMode
-from knowledge.serializers.common import get_embedding_model_default_params
 from maxkb.conf import PROJECT_DIR
 from models_provider.models import Model
-from models_provider.tools import get_model, get_model_by_id
+from models_provider.tools import get_model, get_model_by_id, get_model_default_params
 
 
 def reset_meta(meta):
@@ -65,7 +64,7 @@ class BaseSearchDatasetStep(ISearchDatasetStep):
         if model.model_type != "EMBEDDING":
             raise Exception(_("Model does not exist"))
         self.context['model_name'] = model.name
-        default_params = get_embedding_model_default_params(model)
+        default_params = get_model_default_params(model)
         embedding_model = ModelManage.get_model(model_id, lambda _id: get_model(model, **{**default_params}))
         embedding_value = embedding_model.embed_query(exec_problem_text)
         vector = VectorStore.get_embedding_vector()

apps/knowledge/serializers/common.py

@@ -26,7 +26,7 @@ from common.utils.logger import maxkb_logger
 from knowledge.models import Document
 from knowledge.models import Paragraph, Problem, ProblemParagraphMapping, Knowledge, File
 from maxkb.conf import PROJECT_DIR
-from models_provider.tools import get_model
+from models_provider.tools import get_model, get_model_default_params
 
 
 class MetaSerializer(serializers.Serializer):
@@ -112,21 +112,6 @@ 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)
@@ -135,7 +120,7 @@ def get_embedding_model_by_knowledge_id_list(knowledge_id_list: List):
     if len(knowledge_list) == 0:
         raise Exception(_('Knowledge base setting error, please reset the knowledge base'))
 
-    default_params = get_embedding_model_default_params(knowledge_list[0].embedding_model)
+    default_params = get_model_default_params(knowledge_list[0].embedding_model)
 
     return ModelManage.get_model(
         str(knowledge_list[0].embedding_model_id),
@@ -146,14 +131,14 @@ def get_embedding_model_by_knowledge_id_list(knowledge_id_list: List):
 def get_embedding_model_by_knowledge_id(knowledge_id: str):
     knowledge = QuerySet(Knowledge).select_related('embedding_model').filter(id=knowledge_id).first()
 
-    default_params = get_embedding_model_default_params(knowledge.embedding_model)
+    default_params = get_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):
-    default_params = get_embedding_model_default_params(knowledge.embedding_model)
+    default_params = get_model_default_params(knowledge.embedding_model)
 
     return ModelManage.get_model(str(knowledge.embedding_model_id),
                                  lambda _id: get_model(knowledge.embedding_model, **{**default_params}))

apps/knowledge/task/embedding.py

@@ -12,9 +12,9 @@ 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, get_embedding_model_default_params
+from knowledge.serializers.common import drop_knowledge_index
 from models_provider.models import Model
-from models_provider.tools import get_model
+from models_provider.tools import get_model, get_model_default_params
 from ops import celery_app
 
 
@@ -26,7 +26,7 @@ def get_embedding_model(model_id, exception_handler=lambda e: maxkb_logger.error
     try:
         model = QuerySet(Model).filter(id=model_id).first()
 
-        default_params = get_embedding_model_default_params(model)
+        default_params = get_model_default_params(model)
 
         embedding_model = ModelManage.get_model(model_id, lambda _id: get_model(model, **{**default_params}))
     except Exception as e:

apps/models_provider/tools.py

@@ -115,6 +115,21 @@ def get_model_by_id(_id, workspace_id):
         raise Exception(_("Model does not exist"))
     return model
 
+def get_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_model_instance_by_model_workspace_id(model_id, workspace_id, **kwargs):
     """
@@ -124,5 +139,5 @@ def get_model_instance_by_model_workspace_id(model_id, workspace_id, **kwargs):
     @return:                模型实例
     """
     model = get_model_by_id(model_id, workspace_id)
-    s = {p.get('field'): p.get('default_value') for p in model.model_params_form if p.get('default_value') is not None}
+    s = get_model_default_params(model)
     return ModelManage.get_model(model_id, lambda _id: get_model(model, **{**s, **kwargs}))