Fix: Fixed the issue where the operator added by clicking the plus sign in the data flow would overlap with the original section #9886 (#10458)

### What problem does this PR solve?

Fix: Fixed the issue where the operator added by clicking the plus sign
in the data flow would overlap with the original section #9886

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

admin/admin_client.py

@@ -1,3 +1,19 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
 import argparse
 import base64
 

admin/admin_server.py

@@ -1,3 +1,18 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
 
 import os
 import signal

admin/auth.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 import logging
 import uuid
 from functools import wraps

admin/config.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 import logging
 import threading
 from enum import Enum
@@ -35,7 +52,8 @@ class BaseConfig(BaseModel):
     detail_func_name: str
 
     def to_dict(self) -> dict[str, Any]:
-        return {'id': self.id, 'name': self.name, 'host': self.host, 'port': self.port, 'service_type': self.service_type}
+        return {'id': self.id, 'name': self.name, 'host': self.host, 'port': self.port,
+                'service_type': self.service_type}
 
 
 class MetaConfig(BaseConfig):

admin/models.py

@@ -0,0 +1,15 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#

admin/responses.py

@@ -1,15 +1,34 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 from flask import jsonify
 
-def success_response(data=None, message="Success", code = 0):
+
+def success_response(data=None, message="Success", code=0):
     return jsonify({
         "code": code,
         "message": message,
         "data": data
     }), 200
 
+
 def error_response(message="Error", code=-1, data=None):
     return jsonify({
         "code": code,
         "message": message,
         "data": data
-    }), 400
+    }), 400

admin/routes.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 from flask import Blueprint, request
 
 from auth import login_verify
@@ -42,7 +59,7 @@ def create_user():
         res = UserMgr.create_user(username, password, role)
         if res["success"]:
             user_info = res["user_info"]
-            user_info.pop("password") # do not return password
+            user_info.pop("password")  # do not return password
             return success_response(user_info, "User created successfully")
         else:
             return error_response("create user failed")
@@ -102,6 +119,7 @@ def alter_user_activate_status(username):
     except Exception as e:
         return error_response(str(e), 500)
 
+
 @admin_bp.route('/users/<username>', methods=['GET'])
 @login_verify
 def get_user_details(username):
@@ -114,6 +132,7 @@ def get_user_details(username):
     except Exception as e:
         return error_response(str(e), 500)
 
+
 @admin_bp.route('/users/<username>/datasets', methods=['GET'])
 @login_verify
 def get_user_datasets(username):

admin/services.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 import re
 from werkzeug.security import check_password_hash
 from api.db import ActiveEnum
@@ -12,13 +29,15 @@ from api.utils import health_utils
 from api.common.exceptions import AdminException, UserAlreadyExistsError, UserNotFoundError
 from config import SERVICE_CONFIGS
 
+
 class UserMgr:
     @staticmethod
     def get_all_users():
         users = UserService.get_all_users()
         result = []
         for user in users:
-            result.append({'email': user.email, 'nickname': user.nickname, 'create_date': user.create_date, 'is_active': user.is_active})
+            result.append({'email': user.email, 'nickname': user.nickname, 'create_date': user.create_date,
+                           'is_active': user.is_active})
         return result
 
     @staticmethod
@@ -112,6 +131,7 @@ class UserMgr:
         UserService.update_user(usr.id, {"is_active": target_status})
         return f"Turn {_activate_status} user activate status successfully!"
 
+
 class UserServiceMgr:
 
     @staticmethod
@@ -150,6 +170,7 @@ class UserServiceMgr:
             'canvas_category': r['canvas_category']
         } for r in res]
 
+
 class ServiceMgr:
 
     @staticmethod

agent/tools/retrieval.py

@@ -121,7 +121,7 @@ class Retrieval(ToolBase, ABC):
 
         if kbs:
             query = re.sub(r"^user[:：\s]*", "", query, flags=re.IGNORECASE)
-            kbinfos = settings.retrievaler.retrieval(
+            kbinfos = settings.retriever.retrieval(
                 query,
                 embd_mdl,
                 [kb.tenant_id for kb in kbs],
@@ -135,7 +135,7 @@ class Retrieval(ToolBase, ABC):
                 rank_feature=label_question(query, kbs),
             )
             if self._param.use_kg:
-                ck = settings.kg_retrievaler.retrieval(query,
+                ck = settings.kg_retriever.retrieval(query,
                                                        [kb.tenant_id for kb in kbs],
                                                        kb_ids,
                                                        embd_mdl,
@@ -146,7 +146,7 @@ class Retrieval(ToolBase, ABC):
             kbinfos = {"chunks": [], "doc_aggs": []}
 
         if self._param.use_kg and kbs:
-            ck = settings.kg_retrievaler.retrieval(query, [kb.tenant_id for kb in kbs], filtered_kb_ids, embd_mdl, LLMBundle(kbs[0].tenant_id, LLMType.CHAT))
+            ck = settings.kg_retriever.retrieval(query, [kb.tenant_id for kb in kbs], filtered_kb_ids, embd_mdl, LLMBundle(kbs[0].tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ck["content"] = ck["content_with_weight"]
                 del ck["content_with_weight"]

api/apps/api_app.py

@@ -536,7 +536,7 @@ def list_chunks():
             )
         kb_ids = KnowledgebaseService.get_kb_ids(tenant_id)
 
-        res = settings.retrievaler.chunk_list(doc_id, tenant_id, kb_ids)
+        res = settings.retriever.chunk_list(doc_id, tenant_id, kb_ids)
         res = [
             {
                 "content": res_item["content_with_weight"],
@@ -884,7 +884,7 @@ def retrieval():
         if req.get("keyword", False):
             chat_mdl = LLMBundle(kbs[0].tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
-        ranks = settings.retrievaler.retrieval(question, embd_mdl, kbs[0].tenant_id, kb_ids, page, size,
+        ranks = settings.retriever.retrieval(question, embd_mdl, kbs[0].tenant_id, kb_ids, page, size,
                                                similarity_threshold, vector_similarity_weight, top,
                                                doc_ids, rerank_mdl=rerank_mdl, highlight= highlight,
                                                rank_feature=label_question(question, kbs))

api/apps/chunk_app.py

@@ -60,7 +60,7 @@ def list_chunk():
         }
         if "available_int" in req:
             query["available_int"] = int(req["available_int"])
-        sres = settings.retrievaler.search(query, search.index_name(tenant_id), kb_ids, highlight=True)
+        sres = settings.retriever.search(query, search.index_name(tenant_id), kb_ids, highlight=True)
         res = {"total": sres.total, "chunks": [], "doc": doc.to_dict()}
         for id in sres.ids:
             d = {
@@ -346,7 +346,7 @@ def retrieval_test():
             question += keyword_extraction(chat_mdl, question)
 
         labels = label_question(question, [kb])
-        ranks = settings.retrievaler.retrieval(question, embd_mdl, tenant_ids, kb_ids, page, size,
+        ranks = settings.retriever.retrieval(question, embd_mdl, tenant_ids, kb_ids, page, size,
                                float(req.get("similarity_threshold", 0.0)),
                                float(req.get("vector_similarity_weight", 0.3)),
                                top,
@@ -354,7 +354,7 @@ def retrieval_test():
                                rank_feature=labels
                                )
         if use_kg:
-            ck = settings.kg_retrievaler.retrieval(question,
+            ck = settings.kg_retriever.retrieval(question,
                                                    tenant_ids,
                                                    kb_ids,
                                                    embd_mdl,
@@ -384,7 +384,7 @@ def knowledge_graph():
         "doc_ids": [doc_id],
         "knowledge_graph_kwd": ["graph", "mind_map"]
     }
-    sres = settings.retrievaler.search(req, search.index_name(tenant_id), kb_ids)
+    sres = settings.retriever.search(req, search.index_name(tenant_id), kb_ids)
     obj = {"graph": {}, "mind_map": {}}
     for id in sres.ids[:2]:
         ty = sres.field[id]["knowledge_graph_kwd"]

api/apps/kb_app.py

@@ -282,7 +282,7 @@ def list_tags(kb_id):
     tenants = UserTenantService.get_tenants_by_user_id(current_user.id)
     tags = []
     for tenant in tenants:
-        tags += settings.retrievaler.all_tags(tenant["tenant_id"], [kb_id])
+        tags += settings.retriever.all_tags(tenant["tenant_id"], [kb_id])
     return get_json_result(data=tags)
 
 
@@ -301,7 +301,7 @@ def list_tags_from_kbs():
     tenants = UserTenantService.get_tenants_by_user_id(current_user.id)
     tags = []
     for tenant in tenants:
-        tags += settings.retrievaler.all_tags(tenant["tenant_id"], kb_ids)
+        tags += settings.retriever.all_tags(tenant["tenant_id"], kb_ids)
     return get_json_result(data=tags)
 
 
@@ -362,7 +362,7 @@ def knowledge_graph(kb_id):
     obj = {"graph": {}, "mind_map": {}}
     if not settings.docStoreConn.indexExist(search.index_name(kb.tenant_id), kb_id):
         return get_json_result(data=obj)
-    sres = settings.retrievaler.search(req, search.index_name(kb.tenant_id), [kb_id])
+    sres = settings.retriever.search(req, search.index_name(kb.tenant_id), [kb_id])
     if not len(sres.ids):
         return get_json_result(data=obj)
 

api/apps/plugin_app.py

@@ -1,8 +1,26 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 from flask import Response
 from flask_login import login_required
 from api.utils.api_utils import get_json_result
 from plugin import GlobalPluginManager
 
+
 @manager.route('/llm_tools', methods=['GET'])  # noqa: F821
 @login_required
 def llm_tools() -> Response:

api/apps/sdk/agent.py

@@ -25,6 +25,7 @@ from api.utils.api_utils import get_data_error_result, get_error_data_result, ge
 from api.utils.api_utils import get_result
 from flask import request
 
+
 @manager.route('/agents', methods=['GET'])  # noqa: F821
 @token_required
 def list_agents(tenant_id):
@@ -41,7 +42,7 @@ def list_agents(tenant_id):
         desc = False
     else:
         desc = True
-    canvas = UserCanvasService.get_list(tenant_id,page_number,items_per_page,orderby,desc,id,title)
+    canvas = UserCanvasService.get_list(tenant_id, page_number, items_per_page, orderby, desc, id, title)
     return get_result(data=canvas)
 
 
@@ -93,7 +94,7 @@ def update_agent(tenant_id: str, agent_id: str):
             req["dsl"] = json.dumps(req["dsl"], ensure_ascii=False)
 
         req["dsl"] = json.loads(req["dsl"])
-    
+
     if req.get("title") is not None:
         req["title"] = req["title"].strip()
 

api/apps/sdk/dataset.py

@@ -215,7 +215,8 @@ def delete(tenant_id):
                     continue
                 kb_id_instance_pairs.append((kb_id, kb))
             if len(error_kb_ids) > 0:
-                return get_error_permission_result(message=f"""User '{tenant_id}' lacks permission for datasets: '{", ".join(error_kb_ids)}'""")
+                return get_error_permission_result(
+                    message=f"""User '{tenant_id}' lacks permission for datasets: '{", ".join(error_kb_ids)}'""")
 
         errors = []
         success_count = 0
@@ -232,7 +233,8 @@ def delete(tenant_id):
                     ]
                 )
                 File2DocumentService.delete_by_document_id(doc.id)
-            FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kb.name])
+            FileService.filter_delete(
+                [File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kb.name])
             if not KnowledgebaseService.delete_by_id(kb_id):
                 errors.append(f"Delete dataset error for {kb_id}")
                 continue
@@ -329,7 +331,8 @@ def update(tenant_id, dataset_id):
     try:
         kb = KnowledgebaseService.get_or_none(id=dataset_id, tenant_id=tenant_id)
         if kb is None:
-            return get_error_permission_result(message=f"User '{tenant_id}' lacks permission for dataset '{dataset_id}'")
+            return get_error_permission_result(
+                message=f"User '{tenant_id}' lacks permission for dataset '{dataset_id}'")
 
         if req.get("parser_config"):
             req["parser_config"] = deep_merge(kb.parser_config, req["parser_config"])
@@ -341,7 +344,8 @@ def update(tenant_id, dataset_id):
             del req["parser_config"]
 
         if "name" in req and req["name"].lower() != kb.name.lower():
-            exists = KnowledgebaseService.get_or_none(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value)
+            exists = KnowledgebaseService.get_or_none(name=req["name"], tenant_id=tenant_id,
+                                                      status=StatusEnum.VALID.value)
             if exists:
                 return get_error_data_result(message=f"Dataset name '{req['name']}' already exists")
 
@@ -349,7 +353,8 @@ def update(tenant_id, dataset_id):
             if not req["embd_id"]:
                 req["embd_id"] = kb.embd_id
             if kb.chunk_num != 0 and req["embd_id"] != kb.embd_id:
-                return get_error_data_result(message=f"When chunk_num ({kb.chunk_num}) > 0, embedding_model must remain {kb.embd_id}")
+                return get_error_data_result(
+                    message=f"When chunk_num ({kb.chunk_num}) > 0, embedding_model must remain {kb.embd_id}")
             ok, err = verify_embedding_availability(req["embd_id"], tenant_id)
             if not ok:
                 return err
@@ -359,10 +364,12 @@ def update(tenant_id, dataset_id):
                 return get_error_argument_result(message="'pagerank' can only be set when doc_engine is elasticsearch")
 
             if req["pagerank"] > 0:
-                settings.docStoreConn.update({"kb_id": kb.id}, {PAGERANK_FLD: req["pagerank"]}, search.index_name(kb.tenant_id), kb.id)
+                settings.docStoreConn.update({"kb_id": kb.id}, {PAGERANK_FLD: req["pagerank"]},
+                                             search.index_name(kb.tenant_id), kb.id)
             else:
                 # Elasticsearch requires PAGERANK_FLD be non-zero!
-                settings.docStoreConn.update({"exists": PAGERANK_FLD}, {"remove": PAGERANK_FLD}, search.index_name(kb.tenant_id), kb.id)
+                settings.docStoreConn.update({"exists": PAGERANK_FLD}, {"remove": PAGERANK_FLD},
+                                             search.index_name(kb.tenant_id), kb.id)
 
         if not KnowledgebaseService.update_by_id(kb.id, req):
             return get_error_data_result(message="Update dataset error.(Database error)")
@@ -454,7 +461,7 @@ def list_datasets(tenant_id):
                 return get_error_permission_result(message=f"User '{tenant_id}' lacks permission for dataset '{name}'")
 
         tenants = TenantService.get_joined_tenants_by_user_id(tenant_id)
-        kbs = KnowledgebaseService.get_list(
+        kbs, total = KnowledgebaseService.get_list(
             [m["tenant_id"] for m in tenants],
             tenant_id,
             args["page"],
@@ -468,14 +475,15 @@ def list_datasets(tenant_id):
         response_data_list = []
         for kb in kbs:
             response_data_list.append(remap_dictionary_keys(kb))
-        return get_result(data=response_data_list)
+        return get_result(data=response_data_list, total=total)
     except OperationalError as e:
         logging.exception(e)
         return get_error_data_result(message="Database operation failed")
 
+
 @manager.route('/datasets/<dataset_id>/knowledge_graph', methods=['GET'])  # noqa: F821
 @token_required
-def knowledge_graph(tenant_id,dataset_id):
+def knowledge_graph(tenant_id, dataset_id):
     if not KnowledgebaseService.accessible(dataset_id, tenant_id):
         return get_result(
             data=False,
@@ -491,7 +499,7 @@ def knowledge_graph(tenant_id,dataset_id):
     obj = {"graph": {}, "mind_map": {}}
     if not settings.docStoreConn.indexExist(search.index_name(kb.tenant_id), dataset_id):
         return get_result(data=obj)
-    sres = settings.retrievaler.search(req, search.index_name(kb.tenant_id), [dataset_id])
+    sres = settings.retriever.search(req, search.index_name(kb.tenant_id), [dataset_id])
     if not len(sres.ids):
         return get_result(data=obj)
 
@@ -507,14 +515,16 @@ def knowledge_graph(tenant_id,dataset_id):
     if "nodes" in obj["graph"]:
         obj["graph"]["nodes"] = sorted(obj["graph"]["nodes"], key=lambda x: x.get("pagerank", 0), reverse=True)[:256]
         if "edges" in obj["graph"]:
-            node_id_set = { o["id"] for o in obj["graph"]["nodes"] }
-            filtered_edges = [o for o in obj["graph"]["edges"] if o["source"] != o["target"] and o["source"] in node_id_set and o["target"] in node_id_set]
+            node_id_set = {o["id"] for o in obj["graph"]["nodes"]}
+            filtered_edges = [o for o in obj["graph"]["edges"] if
+                              o["source"] != o["target"] and o["source"] in node_id_set and o["target"] in node_id_set]
             obj["graph"]["edges"] = sorted(filtered_edges, key=lambda x: x.get("weight", 0), reverse=True)[:128]
     return get_result(data=obj)
 
+
 @manager.route('/datasets/<dataset_id>/knowledge_graph', methods=['DELETE'])  # noqa: F821
 @token_required
-def delete_knowledge_graph(tenant_id,dataset_id):
+def delete_knowledge_graph(tenant_id, dataset_id):
     if not KnowledgebaseService.accessible(dataset_id, tenant_id):
         return get_result(
             data=False,
@@ -522,6 +532,7 @@ def delete_knowledge_graph(tenant_id,dataset_id):
             code=settings.RetCode.AUTHENTICATION_ERROR
         )
     _, kb = KnowledgebaseService.get_by_id(dataset_id)
-    settings.docStoreConn.delete({"knowledge_graph_kwd": ["graph", "subgraph", "entity", "relation"]}, search.index_name(kb.tenant_id), dataset_id)
+    settings.docStoreConn.delete({"knowledge_graph_kwd": ["graph", "subgraph", "entity", "relation"]},
+                                 search.index_name(kb.tenant_id), dataset_id)
 
     return get_result(data=True)

api/apps/sdk/dify_retrieval.py

@@ -1,4 +1,4 @@
-    #
+#
 #  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
@@ -38,9 +38,9 @@ def retrieval(tenant_id):
     retrieval_setting = req.get("retrieval_setting", {})
     similarity_threshold = float(retrieval_setting.get("score_threshold", 0.0))
     top = int(retrieval_setting.get("top_k", 1024))
-    metadata_condition = req.get("metadata_condition",{})
+    metadata_condition = req.get("metadata_condition", {})
     metas = DocumentService.get_meta_by_kbs([kb_id])
- 
+
     doc_ids = []
     try:
 
@@ -50,12 +50,12 @@ def retrieval(tenant_id):
 
         embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
         print(metadata_condition)
-        print("after",convert_conditions(metadata_condition))
+        # print("after", convert_conditions(metadata_condition))
         doc_ids.extend(meta_filter(metas, convert_conditions(metadata_condition)))
-        print("doc_ids",doc_ids)
+        # print("doc_ids", doc_ids)
         if not doc_ids and metadata_condition is not None:
             doc_ids = ['-999']
-        ranks = settings.retrievaler.retrieval(
+        ranks = settings.retriever.retrieval(
             question,
             embd_mdl,
             kb.tenant_id,
@@ -70,17 +70,17 @@ def retrieval(tenant_id):
         )
 
         if use_kg:
-            ck = settings.kg_retrievaler.retrieval(question,
-                                                   [tenant_id],
-                                                   [kb_id],
-                                                   embd_mdl,
-                                                   LLMBundle(kb.tenant_id, LLMType.CHAT))
+            ck = settings.kg_retriever.retrieval(question,
+                                                 [tenant_id],
+                                                 [kb_id],
+                                                 embd_mdl,
+                                                 LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
 
         records = []
         for c in ranks["chunks"]:
-            e, doc = DocumentService.get_by_id( c["doc_id"])
+            e, doc = DocumentService.get_by_id(c["doc_id"])
             c.pop("vector", None)
             meta = getattr(doc, 'meta_fields', {})
             meta["doc_id"] = c["doc_id"]
@@ -100,5 +100,3 @@ def retrieval(tenant_id):
             )
         logging.exception(e)
         return build_error_result(message=str(e), code=settings.RetCode.SERVER_ERROR)
-
-

api/apps/sdk/doc.py

@@ -982,7 +982,7 @@ def list_chunks(tenant_id, dataset_id, document_id):
         _ = Chunk(**final_chunk)
 
     elif settings.docStoreConn.indexExist(search.index_name(tenant_id), dataset_id):
-        sres = settings.retrievaler.search(query, search.index_name(tenant_id), [dataset_id], emb_mdl=None, highlight=True)
+        sres = settings.retriever.search(query, search.index_name(tenant_id), [dataset_id], emb_mdl=None, highlight=True)
         res["total"] = sres.total
         for id in sres.ids:
             d = {
@@ -1446,7 +1446,7 @@ def retrieval_test(tenant_id):
             chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
 
-        ranks = settings.retrievaler.retrieval(
+        ranks = settings.retriever.retrieval(
             question,
             embd_mdl,
             tenant_ids,
@@ -1462,7 +1462,7 @@ def retrieval_test(tenant_id):
             rank_feature=label_question(question, kbs),
         )
         if use_kg:
-            ck = settings.kg_retrievaler.retrieval(question, [k.tenant_id for k in kbs], kb_ids, embd_mdl, LLMBundle(kb.tenant_id, LLMType.CHAT))
+            ck = settings.kg_retriever.retrieval(question, [k.tenant_id for k in kbs], kb_ids, embd_mdl, LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
 

api/apps/sdk/files.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 import pathlib
 import re
 
@@ -17,7 +34,8 @@ from api.utils.api_utils import get_json_result
 from api.utils.file_utils import filename_type
 from rag.utils.storage_factory import STORAGE_IMPL
 
-@manager.route('/file/upload', methods=['POST']) # noqa: F821
+
+@manager.route('/file/upload', methods=['POST'])  # noqa: F821
 @token_required
 def upload(tenant_id):
     """
@@ -97,12 +115,14 @@ def upload(tenant_id):
                 e, file = FileService.get_by_id(file_id_list[len_id_list - 1])
                 if not e:
                     return get_json_result(data=False, message="Folder not found!", code=404)
-                last_folder = FileService.create_folder(file, file_id_list[len_id_list - 1], file_obj_names, len_id_list)
+                last_folder = FileService.create_folder(file, file_id_list[len_id_list - 1], file_obj_names,
+                                                        len_id_list)
             else:
                 e, file = FileService.get_by_id(file_id_list[len_id_list - 2])
                 if not e:
                     return get_json_result(data=False, message="Folder not found!", code=404)
-                last_folder = FileService.create_folder(file, file_id_list[len_id_list - 2], file_obj_names, len_id_list)
+                last_folder = FileService.create_folder(file, file_id_list[len_id_list - 2], file_obj_names,
+                                                        len_id_list)
 
             filetype = filename_type(file_obj_names[file_len - 1])
             location = file_obj_names[file_len - 1]
@@ -129,7 +149,7 @@ def upload(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/create', methods=['POST']) # noqa: F821
+@manager.route('/file/create', methods=['POST'])  # noqa: F821
 @token_required
 def create(tenant_id):
     """
@@ -207,7 +227,7 @@ def create(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/list', methods=['GET']) # noqa: F821
+@manager.route('/file/list', methods=['GET'])  # noqa: F821
 @token_required
 def list_files(tenant_id):
     """
@@ -299,7 +319,7 @@ def list_files(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/root_folder', methods=['GET']) # noqa: F821
+@manager.route('/file/root_folder', methods=['GET'])  # noqa: F821
 @token_required
 def get_root_folder(tenant_id):
     """
@@ -335,7 +355,7 @@ def get_root_folder(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/parent_folder', methods=['GET']) # noqa: F821
+@manager.route('/file/parent_folder', methods=['GET'])  # noqa: F821
 @token_required
 def get_parent_folder():
     """
@@ -380,7 +400,7 @@ def get_parent_folder():
         return server_error_response(e)
 
 
-@manager.route('/file/all_parent_folder', methods=['GET']) # noqa: F821
+@manager.route('/file/all_parent_folder', methods=['GET'])  # noqa: F821
 @token_required
 def get_all_parent_folders(tenant_id):
     """
@@ -428,7 +448,7 @@ def get_all_parent_folders(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/rm', methods=['POST']) # noqa: F821
+@manager.route('/file/rm', methods=['POST'])  # noqa: F821
 @token_required
 def rm(tenant_id):
     """
@@ -502,7 +522,7 @@ def rm(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/rename', methods=['POST']) # noqa: F821
+@manager.route('/file/rename', methods=['POST'])  # noqa: F821
 @token_required
 def rename(tenant_id):
     """
@@ -542,7 +562,8 @@ def rename(tenant_id):
         if not e:
             return get_json_result(message="File not found!", code=404)
 
-        if file.type != FileType.FOLDER.value and pathlib.Path(req["name"].lower()).suffix != pathlib.Path(file.name.lower()).suffix:
+        if file.type != FileType.FOLDER.value and pathlib.Path(req["name"].lower()).suffix != pathlib.Path(
+                file.name.lower()).suffix:
             return get_json_result(data=False, message="The extension of file can't be changed", code=400)
 
         for existing_file in FileService.query(name=req["name"], pf_id=file.parent_id):
@@ -562,9 +583,9 @@ def rename(tenant_id):
         return server_error_response(e)
 
 
-@manager.route('/file/get/<file_id>', methods=['GET']) # noqa: F821
+@manager.route('/file/get/<file_id>', methods=['GET'])  # noqa: F821
 @token_required
-def get(tenant_id,file_id):
+def get(tenant_id, file_id):
     """
     Download a file.
     ---
@@ -610,7 +631,7 @@ def get(tenant_id,file_id):
         return server_error_response(e)
 
 
-@manager.route('/file/mv', methods=['POST']) # noqa: F821
+@manager.route('/file/mv', methods=['POST'])  # noqa: F821
 @token_required
 def move(tenant_id):
     """
@@ -669,6 +690,7 @@ def move(tenant_id):
     except Exception as e:
         return server_error_response(e)
 
+
 @manager.route('/file/convert', methods=['POST'])  # noqa: F821
 @token_required
 def convert(tenant_id):
@@ -735,4 +757,4 @@ def convert(tenant_id):
                     file2documents.append(file2document.to_json())
         return get_json_result(data=file2documents)
     except Exception as e:
-        return server_error_response(e)
+        return server_error_response(e)

api/apps/sdk/session.py

@@ -36,7 +36,8 @@ from api.db.services.llm_service import LLMBundle
 from api.db.services.search_service import SearchService
 from api.db.services.user_service import UserTenantService
 from api.utils import get_uuid
-from api.utils.api_utils import check_duplicate_ids, get_data_openai, get_error_data_result, get_json_result, get_result, server_error_response, token_required, validate_request
+from api.utils.api_utils import check_duplicate_ids, get_data_openai, get_error_data_result, get_json_result, \
+    get_result, server_error_response, token_required, validate_request
 from rag.app.tag import label_question
 from rag.prompts.template import load_prompt
 from rag.prompts.generator import cross_languages, gen_meta_filter, keyword_extraction, chunks_format
@@ -88,7 +89,8 @@ def create_agent_session(tenant_id, agent_id):
     canvas.reset()
 
     cvs.dsl = json.loads(str(canvas))
-    conv = {"id": session_id, "dialog_id": cvs.id, "user_id": user_id, "message": [{"role": "assistant", "content": canvas.get_prologue()}], "source": "agent", "dsl": cvs.dsl}
+    conv = {"id": session_id, "dialog_id": cvs.id, "user_id": user_id,
+            "message": [{"role": "assistant", "content": canvas.get_prologue()}], "source": "agent", "dsl": cvs.dsl}
     API4ConversationService.save(**conv)
     conv["agent_id"] = conv.pop("dialog_id")
     return get_result(data=conv)
@@ -279,7 +281,7 @@ def chat_completion_openai_like(tenant_id, chat_id):
                     reasoning_match = re.search(r"<think>(.*?)</think>", answer, flags=re.DOTALL)
                     if reasoning_match:
                         reasoning_part = reasoning_match.group(1)
-                        content_part = answer[reasoning_match.end() :]
+                        content_part = answer[reasoning_match.end():]
                     else:
                         reasoning_part = ""
                         content_part = answer
@@ -324,7 +326,8 @@ def chat_completion_openai_like(tenant_id, chat_id):
             response["choices"][0]["delta"]["content"] = None
             response["choices"][0]["delta"]["reasoning_content"] = None
             response["choices"][0]["finish_reason"] = "stop"
-            response["usage"] = {"prompt_tokens": len(prompt), "completion_tokens": token_used, "total_tokens": len(prompt) + token_used}
+            response["usage"] = {"prompt_tokens": len(prompt), "completion_tokens": token_used,
+                                 "total_tokens": len(prompt) + token_used}
             if need_reference:
                 response["choices"][0]["delta"]["reference"] = chunks_format(last_ans.get("reference", []))
                 response["choices"][0]["delta"]["final_content"] = last_ans.get("answer", "")
@@ -559,7 +562,8 @@ def list_agent_session(tenant_id, agent_id):
         desc = True
     # dsl defaults to True in all cases except for False and false
     include_dsl = request.args.get("dsl") != "False" and request.args.get("dsl") != "false"
-    total, convs = API4ConversationService.get_list(agent_id, tenant_id, page_number, items_per_page, orderby, desc, id, user_id, include_dsl)
+    total, convs = API4ConversationService.get_list(agent_id, tenant_id, page_number, items_per_page, orderby, desc, id,
+                                                    user_id, include_dsl)
     if not convs:
         return get_result(data=[])
     for conv in convs:
@@ -581,7 +585,8 @@ def list_agent_session(tenant_id, agent_id):
                 if message_num != 0 and messages[message_num]["role"] != "user":
                     chunk_list = []
                     # Add boundary and type checks to prevent KeyError
-                    if chunk_num < len(conv["reference"]) and conv["reference"][chunk_num] is not None and isinstance(conv["reference"][chunk_num], dict) and "chunks" in conv["reference"][chunk_num]:
+                    if chunk_num < len(conv["reference"]) and conv["reference"][chunk_num] is not None and isinstance(
+                            conv["reference"][chunk_num], dict) and "chunks" in conv["reference"][chunk_num]:
                         chunks = conv["reference"][chunk_num]["chunks"]
                         for chunk in chunks:
                             # Ensure chunk is a dictionary before calling get method
@@ -639,13 +644,16 @@ def delete(tenant_id, chat_id):
 
     if errors:
         if success_count > 0:
-            return get_result(data={"success_count": success_count, "errors": errors}, message=f"Partially deleted {success_count} sessions with {len(errors)} errors")
+            return get_result(data={"success_count": success_count, "errors": errors},
+                              message=f"Partially deleted {success_count} sessions with {len(errors)} errors")
         else:
             return get_error_data_result(message="; ".join(errors))
 
     if duplicate_messages:
         if success_count > 0:
-            return get_result(message=f"Partially deleted {success_count} sessions with {len(duplicate_messages)} errors", data={"success_count": success_count, "errors": duplicate_messages})
+            return get_result(
+                message=f"Partially deleted {success_count} sessions with {len(duplicate_messages)} errors",
+                data={"success_count": success_count, "errors": duplicate_messages})
         else:
             return get_error_data_result(message=";".join(duplicate_messages))
 
@@ -691,13 +699,16 @@ def delete_agent_session(tenant_id, agent_id):
 
     if errors:
         if success_count > 0:
-            return get_result(data={"success_count": success_count, "errors": errors}, message=f"Partially deleted {success_count} sessions with {len(errors)} errors")
+            return get_result(data={"success_count": success_count, "errors": errors},
+                              message=f"Partially deleted {success_count} sessions with {len(errors)} errors")
         else:
             return get_error_data_result(message="; ".join(errors))
 
     if duplicate_messages:
         if success_count > 0:
-            return get_result(message=f"Partially deleted {success_count} sessions with {len(duplicate_messages)} errors", data={"success_count": success_count, "errors": duplicate_messages})
+            return get_result(
+                message=f"Partially deleted {success_count} sessions with {len(duplicate_messages)} errors",
+                data={"success_count": success_count, "errors": duplicate_messages})
         else:
             return get_error_data_result(message=";".join(duplicate_messages))
 
@@ -730,7 +741,9 @@ def ask_about(tenant_id):
             for ans in ask(req["question"], req["kb_ids"], uid):
                 yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
         except Exception as e:
-            yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps(
+                {"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
+                ensure_ascii=False) + "\n\n"
         yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
     resp = Response(stream(), mimetype="text/event-stream")
@@ -882,7 +895,9 @@ def begin_inputs(agent_id):
         return get_error_data_result(f"Can't find agent by ID: {agent_id}")
 
     canvas = Canvas(json.dumps(cvs.dsl), objs[0].tenant_id)
-    return get_result(data={"title": cvs.title, "avatar": cvs.avatar, "inputs": canvas.get_component_input_form("begin"), "prologue": canvas.get_prologue(), "mode": canvas.get_mode()})
+    return get_result(
+        data={"title": cvs.title, "avatar": cvs.avatar, "inputs": canvas.get_component_input_form("begin"),
+              "prologue": canvas.get_prologue(), "mode": canvas.get_mode()})
 
 
 @manager.route("/searchbots/ask", methods=["POST"])  # noqa: F821
@@ -911,7 +926,9 @@ def ask_about_embedded():
             for ans in ask(req["question"], req["kb_ids"], uid, search_config=search_config):
                 yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
         except Exception as e:
-            yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps(
+                {"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
+                ensure_ascii=False) + "\n\n"
         yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
     resp = Response(stream(), mimetype="text/event-stream")
@@ -978,7 +995,8 @@ def retrieval_test_embedded():
                     tenant_ids.append(tenant.tenant_id)
                     break
             else:
-                return get_json_result(data=False, message="Only owner of knowledgebase authorized for this operation.", code=settings.RetCode.OPERATING_ERROR)
+                return get_json_result(data=False, message="Only owner of knowledgebase authorized for this operation.",
+                                       code=settings.RetCode.OPERATING_ERROR)
 
         e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
         if not e:
@@ -998,11 +1016,13 @@ def retrieval_test_embedded():
             question += keyword_extraction(chat_mdl, question)
 
         labels = label_question(question, [kb])
-        ranks = settings.retrievaler.retrieval(
-            question, embd_mdl, tenant_ids, kb_ids, page, size, similarity_threshold, vector_similarity_weight, top, doc_ids, rerank_mdl=rerank_mdl, highlight=req.get("highlight"), rank_feature=labels
+        ranks = settings.retriever.retrieval(
+            question, embd_mdl, tenant_ids, kb_ids, page, size, similarity_threshold, vector_similarity_weight, top,
+            doc_ids, rerank_mdl=rerank_mdl, highlight=req.get("highlight"), rank_feature=labels
         )
         if use_kg:
-            ck = settings.kg_retrievaler.retrieval(question, tenant_ids, kb_ids, embd_mdl, LLMBundle(kb.tenant_id, LLMType.CHAT))
+            ck = settings.kg_retriever.retrieval(question, tenant_ids, kb_ids, embd_mdl,
+                                                 LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
 
@@ -1013,7 +1033,8 @@ def retrieval_test_embedded():
         return get_json_result(data=ranks)
     except Exception as e:
         if str(e).find("not_found") > 0:
-            return get_json_result(data=False, message="No chunk found! Check the chunk status please!", code=settings.RetCode.DATA_ERROR)
+            return get_json_result(data=False, message="No chunk found! Check the chunk status please!",
+                                   code=settings.RetCode.DATA_ERROR)
         return server_error_response(e)
 
 
@@ -1082,7 +1103,8 @@ def detail_share_embedded():
             if SearchService.query(tenant_id=tenant.tenant_id, id=search_id):
                 break
         else:
-            return get_json_result(data=False, message="Has no permission for this operation.", code=settings.RetCode.OPERATING_ERROR)
+            return get_json_result(data=False, message="Has no permission for this operation.",
+                                   code=settings.RetCode.OPERATING_ERROR)
 
         search = SearchService.get_detail(search_id)
         if not search:

api/apps/system_app.py

@@ -39,6 +39,7 @@ from rag.utils.redis_conn import REDIS_CONN
 from flask import jsonify
 from api.utils.health_utils import run_health_checks
 
+
 @manager.route("/version", methods=["GET"])  # noqa: F821
 @login_required
 def version():
@@ -161,7 +162,7 @@ def status():
         task_executors = REDIS_CONN.smembers("TASKEXE")
         now = datetime.now().timestamp()
         for task_executor_id in task_executors:
-            heartbeats = REDIS_CONN.zrangebyscore(task_executor_id, now - 60*30, now)
+            heartbeats = REDIS_CONN.zrangebyscore(task_executor_id, now - 60 * 30, now)
             heartbeats = [json.loads(heartbeat) for heartbeat in heartbeats]
             task_executor_heartbeats[task_executor_id] = heartbeats
     except Exception:
@@ -273,7 +274,8 @@ def token_list():
         objs = [o.to_dict() for o in objs]
         for o in objs:
             if not o["beta"]:
-                o["beta"] = generate_confirmation_token(generate_confirmation_token(tenants[0].tenant_id)).replace("ragflow-", "")[:32]
+                o["beta"] = generate_confirmation_token(generate_confirmation_token(tenants[0].tenant_id)).replace(
+                    "ragflow-", "")[:32]
                 APITokenService.filter_update([APIToken.tenant_id == tenant_id, APIToken.token == o["token"]], o)
         return get_json_result(data=objs)
     except Exception as e:

api/apps/tenant_app.py

@@ -70,7 +70,8 @@ def create(tenant_id):
             return get_data_error_result(message=f"{invite_user_email} is already in the team.")
         if user_tenant_role == UserTenantRole.OWNER:
             return get_data_error_result(message=f"{invite_user_email} is the owner of the team.")
-        return get_data_error_result(message=f"{invite_user_email} is in the team, but the role: {user_tenant_role} is invalid.")
+        return get_data_error_result(
+            message=f"{invite_user_email} is in the team, but the role: {user_tenant_role} is invalid.")
 
     UserTenantService.save(
         id=get_uuid(),
@@ -132,7 +133,8 @@ def tenant_list():
 @login_required
 def agree(tenant_id):
     try:
-        UserTenantService.filter_update([UserTenant.tenant_id == tenant_id, UserTenant.user_id == current_user.id], {"role": UserTenantRole.NORMAL})
+        UserTenantService.filter_update([UserTenant.tenant_id == tenant_id, UserTenant.user_id == current_user.id],
+                                        {"role": UserTenantRole.NORMAL})
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)

api/common/exceptions.py

@@ -1,3 +1,20 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
 class AdminException(Exception):
     def __init__(self, message, code=400):
         super().__init__(message)
@@ -18,4 +35,4 @@ class UserAlreadyExistsError(AdminException):
 
 class CannotDeleteAdminError(AdminException):
     def __init__(self):
-        super().__init__("Cannot delete admin account", 403)
+        super().__init__("Cannot delete admin account", 403)

api/db/services/dialog_service.py

@@ -370,7 +370,7 @@ def chat(dialog, messages, stream=True, **kwargs):
         chat_mdl.bind_tools(toolcall_session, tools)
     bind_models_ts = timer()
 
-    retriever = settings.retrievaler
+    retriever = settings.retriever
     questions = [m["content"] for m in messages if m["role"] == "user"][-3:]
     attachments = kwargs["doc_ids"].split(",") if "doc_ids" in kwargs else []
     if "doc_ids" in messages[-1]:
@@ -472,7 +472,7 @@ def chat(dialog, messages, stream=True, **kwargs):
                 kbinfos["chunks"].extend(tav_res["chunks"])
                 kbinfos["doc_aggs"].extend(tav_res["doc_aggs"])
             if prompt_config.get("use_kg"):
-                ck = settings.kg_retrievaler.retrieval(" ".join(questions), tenant_ids, dialog.kb_ids, embd_mdl,
+                ck = settings.kg_retriever.retrieval(" ".join(questions), tenant_ids, dialog.kb_ids, embd_mdl,
                                                        LLMBundle(dialog.tenant_id, LLMType.CHAT))
                 if ck["content_with_weight"]:
                     kbinfos["chunks"].insert(0, ck)
@@ -658,7 +658,7 @@ Please write the SQL, only SQL, without any other explanations or text.
 
         logging.debug(f"{question} get SQL(refined): {sql}")
         tried_times += 1
-        return settings.retrievaler.sql_retrieval(sql, format="json"), sql
+        return settings.retriever.sql_retrieval(sql, format="json"), sql
 
     tbl, sql = get_table()
     if tbl is None:
@@ -752,7 +752,7 @@ def ask(question, kb_ids, tenant_id, chat_llm_name=None, search_config={}):
     embedding_list = list(set([kb.embd_id for kb in kbs]))
 
     is_knowledge_graph = all([kb.parser_id == ParserType.KG for kb in kbs])
-    retriever = settings.retrievaler if not is_knowledge_graph else settings.kg_retrievaler
+    retriever = settings.retriever if not is_knowledge_graph else settings.kg_retriever
 
     embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING, embedding_list[0])
     chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, chat_llm_name)
@@ -848,7 +848,7 @@ def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
             if not doc_ids:
                 doc_ids = None
 
-    ranks = settings.retrievaler.retrieval(
+    ranks = settings.retriever.retrieval(
         question=question,
         embd_mdl=embd_mdl,
         tenant_ids=tenant_ids,

api/db/services/knowledgebase_service.py

@@ -379,6 +379,7 @@ class KnowledgebaseService(CommonService):
         #     name: Optional name filter
         # Returns:
         #     List of knowledge bases
+        #     Total count of knowledge bases
         kbs = cls.model.select()
         if id:
             kbs = kbs.where(cls.model.id == id)
@@ -390,6 +391,7 @@ class KnowledgebaseService(CommonService):
                 cls.model.tenant_id == user_id))
             & (cls.model.status == StatusEnum.VALID.value)
         )
+
         if desc:
             kbs = kbs.order_by(cls.model.getter_by(orderby).desc())
         else:
@@ -397,7 +399,7 @@ class KnowledgebaseService(CommonService):
 
         kbs = kbs.paginate(page_number, items_per_page)
 
-        return list(kbs.dicts())
+        return list(kbs.dicts()), kbs.count()
 
     @classmethod
     @DB.connection_context()

api/db/services/mcp_server_service.py

@@ -33,7 +33,8 @@ class MCPServerService(CommonService):
 
     @classmethod
     @DB.connection_context()
-    def get_servers(cls, tenant_id: str, id_list: list[str] | None, page_number, items_per_page, orderby, desc, keywords):
+    def get_servers(cls, tenant_id: str, id_list: list[str] | None, page_number, items_per_page, orderby, desc,
+                    keywords):
         """Retrieve all MCP servers associated with a tenant.
 
         This method fetches all MCP servers for a given tenant, ordered by creation time.

api/db/services/search_service.py

@@ -94,7 +94,8 @@ class SearchService(CommonService):
         query = (
             cls.model.select(*fields)
             .join(User, on=(cls.model.tenant_id == User.id))
-            .where(((cls.model.tenant_id.in_(joined_tenant_ids)) | (cls.model.tenant_id == user_id)) & (cls.model.status == StatusEnum.VALID.value))
+            .where(((cls.model.tenant_id.in_(joined_tenant_ids)) | (cls.model.tenant_id == user_id)) & (
+                        cls.model.status == StatusEnum.VALID.value))
         )
 
         if keywords:

api/db/services/task_service.py

@@ -165,7 +165,7 @@ class TaskService(CommonService):
         ]
         tasks = (
             cls.model.select(*fields).order_by(cls.model.from_page.asc(), cls.model.create_time.desc())
-                .where(cls.model.doc_id == doc_id)
+            .where(cls.model.doc_id == doc_id)
         )
         tasks = list(tasks.dicts())
         if not tasks:
@@ -205,18 +205,18 @@ class TaskService(CommonService):
                 cls.model.select(
                     *[Document.id, Document.kb_id, Document.location, File.parent_id]
                 )
-                    .join(Document, on=(cls.model.doc_id == Document.id))
-                    .join(
+                .join(Document, on=(cls.model.doc_id == Document.id))
+                .join(
                     File2Document,
                     on=(File2Document.document_id == Document.id),
                     join_type=JOIN.LEFT_OUTER,
                 )
-                    .join(
+                .join(
                     File,
                     on=(File2Document.file_id == File.id),
                     join_type=JOIN.LEFT_OUTER,
                 )
-                    .where(
+                .where(
                     Document.status == StatusEnum.VALID.value,
                     Document.run == TaskStatus.RUNNING.value,
                     ~(Document.type == FileType.VIRTUAL.value),
@@ -294,8 +294,8 @@ class TaskService(CommonService):
                 cls.model.update(progress=prog).where(
                     (cls.model.id == id) &
                     (
-                        (cls.model.progress != -1) &
-                        ((prog == -1) | (prog > cls.model.progress))
+                            (cls.model.progress != -1) &
+                            ((prog == -1) | (prog > cls.model.progress))
                     )
                 ).execute()
         else:
@@ -343,6 +343,7 @@ def queue_tasks(doc: dict, bucket: str, name: str, priority: int):
         - Task digests are calculated for optimization and reuse
         - Previous task chunks may be reused if available
     """
+
     def new_task():
         return {
             "id": get_uuid(),
@@ -515,7 +516,7 @@ def queue_dataflow(tenant_id:str, flow_id:str, task_id:str, doc_id:str=CANVAS_DE
     task["file"] = file
 
     if not REDIS_CONN.queue_product(
-        get_svr_queue_name(priority), message=task
+            get_svr_queue_name(priority), message=task
     ):
         return False, "Can't access Redis. Please check the Redis' status."
 

api/db/services/tenant_llm_service.py

@@ -57,8 +57,10 @@ class TenantLLMService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_my_llms(cls, tenant_id):
-        fields = [cls.model.llm_factory, LLMFactories.logo, LLMFactories.tags, cls.model.model_type, cls.model.llm_name, cls.model.used_tokens]
-        objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where(cls.model.tenant_id == tenant_id, ~cls.model.api_key.is_null()).dicts()
+        fields = [cls.model.llm_factory, LLMFactories.logo, LLMFactories.tags, cls.model.model_type, cls.model.llm_name,
+                  cls.model.used_tokens]
+        objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where(
+            cls.model.tenant_id == tenant_id, ~cls.model.api_key.is_null()).dicts()
 
         return list(objs)
 
@@ -122,7 +124,8 @@ class TenantLLMService(CommonService):
                     model_config = {"llm_factory": llm[0].fid, "api_key": "", "llm_name": mdlnm, "api_base": ""}
             if not model_config:
                 if mdlnm == "flag-embedding":
-                    model_config = {"llm_factory": "Tongyi-Qianwen", "api_key": "", "llm_name": llm_name, "api_base": ""}
+                    model_config = {"llm_factory": "Tongyi-Qianwen", "api_key": "", "llm_name": llm_name,
+                                    "api_base": ""}
                 else:
                     if not mdlnm:
                         raise LookupError(f"Type of {llm_type} model is not set.")
@@ -137,27 +140,33 @@ class TenantLLMService(CommonService):
         if llm_type == LLMType.EMBEDDING.value:
             if model_config["llm_factory"] not in EmbeddingModel:
                 return
-            return EmbeddingModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"])
+            return EmbeddingModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
+                                                               base_url=model_config["api_base"])
 
         if llm_type == LLMType.RERANK:
             if model_config["llm_factory"] not in RerankModel:
                 return
-            return RerankModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"])
+            return RerankModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
+                                                            base_url=model_config["api_base"])
 
         if llm_type == LLMType.IMAGE2TEXT.value:
             if model_config["llm_factory"] not in CvModel:
                 return
-            return CvModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], lang, base_url=model_config["api_base"], **kwargs)
+            return CvModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], lang,
+                                                        base_url=model_config["api_base"], **kwargs)
 
         if llm_type == LLMType.CHAT.value:
             if model_config["llm_factory"] not in ChatModel:
                 return
-            return ChatModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], base_url=model_config["api_base"], **kwargs)
+            return ChatModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
+                                                          base_url=model_config["api_base"], **kwargs)
 
         if llm_type == LLMType.SPEECH2TEXT:
             if model_config["llm_factory"] not in Seq2txtModel:
                 return
-            return Seq2txtModel[model_config["llm_factory"]](key=model_config["api_key"], model_name=model_config["llm_name"], lang=lang, base_url=model_config["api_base"])
+            return Seq2txtModel[model_config["llm_factory"]](key=model_config["api_key"],
+                                                             model_name=model_config["llm_name"], lang=lang,
+                                                             base_url=model_config["api_base"])
         if llm_type == LLMType.TTS:
             if model_config["llm_factory"] not in TTSModel:
                 return
@@ -194,11 +203,14 @@ class TenantLLMService(CommonService):
         try:
             num = (
                 cls.model.update(used_tokens=cls.model.used_tokens + used_tokens)
-                .where(cls.model.tenant_id == tenant_id, cls.model.llm_name == llm_name, cls.model.llm_factory == llm_factory if llm_factory else True)
+                .where(cls.model.tenant_id == tenant_id, cls.model.llm_name == llm_name,
+                       cls.model.llm_factory == llm_factory if llm_factory else True)
                 .execute()
             )
         except Exception:
-            logging.exception("TenantLLMService.increase_usage got exception,Failed to update used_tokens for tenant_id=%s, llm_name=%s", tenant_id, llm_name)
+            logging.exception(
+                "TenantLLMService.increase_usage got exception,Failed to update used_tokens for tenant_id=%s, llm_name=%s",
+                tenant_id, llm_name)
             return 0
 
         return num
@@ -206,7 +218,9 @@ class TenantLLMService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_openai_models(cls):
-        objs = cls.model.select().where((cls.model.llm_factory == "OpenAI"), ~(cls.model.llm_name == "text-embedding-3-small"), ~(cls.model.llm_name == "text-embedding-3-large")).dicts()
+        objs = cls.model.select().where((cls.model.llm_factory == "OpenAI"),
+                                        ~(cls.model.llm_name == "text-embedding-3-small"),
+                                        ~(cls.model.llm_name == "text-embedding-3-large")).dicts()
         return list(objs)
 
     @classmethod
@@ -250,8 +264,9 @@ class LLM4Tenant:
         langfuse_keys = TenantLangfuseService.filter_by_tenant(tenant_id=tenant_id)
         self.langfuse = None
         if langfuse_keys:
-            langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key, host=langfuse_keys.host)
+            langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key,
+                                host=langfuse_keys.host)
             if langfuse.auth_check():
                 self.langfuse = langfuse
                 trace_id = self.langfuse.create_trace_id()
-                self.trace_context = {"trace_id": trace_id}
+                self.trace_context = {"trace_id": trace_id}

api/db/services/user_canvas_version.py

@@ -2,22 +2,22 @@ from api.db.db_models import UserCanvasVersion, DB
 from api.db.services.common_service import CommonService
 from peewee import DoesNotExist
 
+
 class UserCanvasVersionService(CommonService):
     model = UserCanvasVersion
-    
-    
+
     @classmethod
     @DB.connection_context()
     def list_by_canvas_id(cls, user_canvas_id):
         try:
             user_canvas_version = cls.model.select(
-                *[cls.model.id, 
-                cls.model.create_time,
-                cls.model.title,
-                cls.model.create_date, 
-                cls.model.update_date,
-                cls.model.user_canvas_id, 
-                cls.model.update_time]
+                *[cls.model.id,
+                  cls.model.create_time,
+                  cls.model.title,
+                  cls.model.create_date,
+                  cls.model.update_date,
+                  cls.model.user_canvas_id,
+                  cls.model.update_time]
             ).where(cls.model.user_canvas_id == user_canvas_id)
             return user_canvas_version
         except DoesNotExist:
@@ -46,18 +46,16 @@ class UserCanvasVersionService(CommonService):
     @DB.connection_context()
     def delete_all_versions(cls, user_canvas_id):
         try:
-            user_canvas_version = cls.model.select().where(cls.model.user_canvas_id == user_canvas_id).order_by(cls.model.create_time.desc())
+            user_canvas_version = cls.model.select().where(cls.model.user_canvas_id == user_canvas_id).order_by(
+                cls.model.create_time.desc())
             if user_canvas_version.count() > 20:
                 delete_ids = []
                 for i in range(20, user_canvas_version.count()):
                     delete_ids.append(user_canvas_version[i].id)
-                
+
                 cls.delete_by_ids(delete_ids)
             return True
         except DoesNotExist:
             return None
         except Exception:
             return None
-
-
-

api/settings.py

@@ -65,8 +65,8 @@ OAUTH_CONFIG = None
 DOC_ENGINE = None
 docStoreConn = None
 
-retrievaler = None
-kg_retrievaler = None
+retriever = None
+kg_retriever = None
 
 # user registration switch
 REGISTER_ENABLED = 1
@@ -174,7 +174,7 @@ def init_settings():
 
     OAUTH_CONFIG = get_base_config("oauth", {})
 
-    global DOC_ENGINE, docStoreConn, retrievaler, kg_retrievaler
+    global DOC_ENGINE, docStoreConn, retriever, kg_retriever
     DOC_ENGINE = os.environ.get("DOC_ENGINE", "elasticsearch")
     # DOC_ENGINE = os.environ.get('DOC_ENGINE', "opensearch")
     lower_case_doc_engine = DOC_ENGINE.lower()
@@ -187,10 +187,10 @@ def init_settings():
     else:
         raise Exception(f"Not supported doc engine: {DOC_ENGINE}")
 
-    retrievaler = search.Dealer(docStoreConn)
+    retriever = search.Dealer(docStoreConn)
     from graphrag import search as kg_search
 
-    kg_retrievaler = kg_search.KGSearch(docStoreConn)
+    kg_retriever = kg_search.KGSearch(docStoreConn)
 
     if int(os.environ.get("SANDBOX_ENABLED", "0")):
         global SANDBOX_HOST

api/utils/api_utils.py

@@ -60,6 +60,7 @@ from rag.utils.mcp_tool_call_conn import MCPToolCallSession, close_multiple_mcp_
 
 requests.models.complexjson.dumps = functools.partial(json.dumps, cls=CustomJSONEncoder)
 
+
 def serialize_for_json(obj):
     """
     Recursively serialize objects to make them JSON serializable.
@@ -68,8 +69,8 @@ def serialize_for_json(obj):
     if hasattr(obj, '__dict__'):
         # For objects with __dict__, try to serialize their attributes
         try:
-            return {key: serialize_for_json(value) for key, value in obj.__dict__.items() 
-                   if not key.startswith('_')}
+            return {key: serialize_for_json(value) for key, value in obj.__dict__.items()
+                    if not key.startswith('_')}
         except (AttributeError, TypeError):
             return str(obj)
     elif hasattr(obj, '__name__'):
@@ -85,6 +86,7 @@ def serialize_for_json(obj):
         # Fallback: convert to string representation
         return str(obj)
 
+
 def request(**kwargs):
     sess = requests.Session()
     stream = kwargs.pop("stream", sess.stream)
@@ -105,7 +107,8 @@ def request(**kwargs):
                         settings.HTTP_APP_KEY.encode("ascii"),
                         prepped.path_url.encode("ascii"),
                         prepped.body if kwargs.get("json") else b"",
-                        urlencode(sorted(kwargs["data"].items()), quote_via=quote, safe="-._~").encode("ascii") if kwargs.get("data") and isinstance(kwargs["data"], dict) else b"",
+                        urlencode(sorted(kwargs["data"].items()), quote_via=quote, safe="-._~").encode(
+                            "ascii") if kwargs.get("data") and isinstance(kwargs["data"], dict) else b"",
                     ]
                 ),
                 "sha1",
@@ -127,7 +130,7 @@ def request(**kwargs):
 def get_exponential_backoff_interval(retries, full_jitter=False):
     """Calculate the exponential backoff wait time."""
     # Will be zero if factor equals 0
-    countdown = min(REQUEST_MAX_WAIT_SEC, REQUEST_WAIT_SEC * (2**retries))
+    countdown = min(REQUEST_MAX_WAIT_SEC, REQUEST_WAIT_SEC * (2 ** retries))
     # Full jitter according to
     # https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/
     if full_jitter:
@@ -158,11 +161,12 @@ def server_error_response(e):
     if len(e.args) > 1:
         try:
             serialized_data = serialize_for_json(e.args[1])
-            return get_json_result(code= settings.RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=serialized_data)
+            return get_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=serialized_data)
         except Exception:
             return get_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=None)
     if repr(e).find("index_not_found_exception") >= 0:
-        return get_json_result(code=settings.RetCode.EXCEPTION_ERROR, message="No chunk found, please upload file and parse it.")
+        return get_json_result(code=settings.RetCode.EXCEPTION_ERROR,
+                               message="No chunk found, please upload file and parse it.")
 
     return get_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e))
 
@@ -207,7 +211,8 @@ def validate_request(*args, **kwargs):
                 if no_arguments:
                     error_string += "required argument are missing: {}; ".format(",".join(no_arguments))
                 if error_arguments:
-                    error_string += "required argument values: {}".format(",".join(["{}={}".format(a[0], a[1]) for a in error_arguments]))
+                    error_string += "required argument values: {}".format(
+                        ",".join(["{}={}".format(a[0], a[1]) for a in error_arguments]))
                 return get_json_result(code=settings.RetCode.ARGUMENT_ERROR, message=error_string)
             return func(*_args, **_kwargs)
 
@@ -222,7 +227,8 @@ def not_allowed_parameters(*params):
             input_arguments = flask_request.json or flask_request.form.to_dict()
             for param in params:
                 if param in input_arguments:
-                    return get_json_result(code=settings.RetCode.ARGUMENT_ERROR, message=f"Parameter {param} isn't allowed")
+                    return get_json_result(code=settings.RetCode.ARGUMENT_ERROR,
+                                           message=f"Parameter {param} isn't allowed")
             return f(*args, **kwargs)
 
         return wrapper
@@ -239,6 +245,7 @@ def active_required(f):
         if not usr or not usr.is_active == ActiveEnum.ACTIVE.value:
             return get_json_result(code=settings.RetCode.FORBIDDEN, message="User isn't active, please activate first.")
         return f(*args, **kwargs)
+
     return wrapper
 
 
@@ -259,7 +266,7 @@ def send_file_in_mem(data, filename):
     return send_file(f, as_attachment=True, attachment_filename=filename)
 
 
-def get_json_result(code=settings.RetCode.SUCCESS, message="success", data=None):
+def get_json_result(code: settings.RetCode = settings.RetCode.SUCCESS, message="success", data=None):
     response = {"code": code, "message": message, "data": data}
     return jsonify(response)
 
@@ -314,7 +321,7 @@ def construct_result(code=settings.RetCode.DATA_ERROR, message="data is missing"
     return jsonify(response)
 
 
-def construct_json_result(code=settings.RetCode.SUCCESS, message="success", data=None):
+def construct_json_result(code: settings.RetCode = settings.RetCode.SUCCESS, message="success", data=None):
     if data is None:
         return jsonify({"code": code, "message": message})
     else:
@@ -347,27 +354,39 @@ def token_required(func):
         token = authorization_list[1]
         objs = APIToken.query(token=token)
         if not objs:
-            return get_json_result(data=False, message="Authentication error: API key is invalid!", code=settings.RetCode.AUTHENTICATION_ERROR)
+            return get_json_result(data=False, message="Authentication error: API key is invalid!",
+                                   code=settings.RetCode.AUTHENTICATION_ERROR)
         kwargs["tenant_id"] = objs[0].tenant_id
         return func(*args, **kwargs)
 
     return decorated_function
 
 
-def get_result(code=settings.RetCode.SUCCESS, message="", data=None):
-    if code == 0:
+def get_result(code=settings.RetCode.SUCCESS, message="", data=None, total=None):
+    """
+    Standard API response format:
+    {
+        "code": 0,
+        "data": [...],        # List or object, backward compatible
+        "total": 47,          # Optional field for pagination
+        "message": "..."      # Error or status message
+    }
+    """
+    response = {"code": code}
+
+    if code == settings.RetCode.SUCCESS:
         if data is not None:
-            response = {"code": code, "data": data}
-        else:
-            response = {"code": code}
+            response["data"] = data
+        if total is not None:
+            response["total_datasets"] = total
     else:
-        response = {"code": code, "message": message}
+        response["message"] = message or "Error"
+
     return jsonify(response)
 
-
 def get_error_data_result(
-    message="Sorry! Data missing!",
-    code=settings.RetCode.DATA_ERROR,
+        message="Sorry! Data missing!",
+        code=settings.RetCode.DATA_ERROR,
 ):
     result_dict = {"code": code, "message": message}
     response = {}
@@ -402,7 +421,8 @@ def get_parser_config(chunk_method, parser_config):
 
     # Define default configurations for each chunking method
     key_mapping = {
-        "naive": {"chunk_token_num": 512, "delimiter": r"\n", "html4excel": False, "layout_recognize": "DeepDOC", "raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
+        "naive": {"chunk_token_num": 512, "delimiter": r"\n", "html4excel": False, "layout_recognize": "DeepDOC",
+                  "raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
         "qa": {"raptor": {"use_raptor": False}, "graphrag": {"use_graphrag": False}},
         "tag": None,
         "resume": None,
@@ -441,16 +461,16 @@ def get_parser_config(chunk_method, parser_config):
 
 
 def get_data_openai(
-    id=None,
-    created=None,
-    model=None,
-    prompt_tokens=0,
-    completion_tokens=0,
-    content=None,
-    finish_reason=None,
-    object="chat.completion",
-    param=None,
-    stream=False
+        id=None,
+        created=None,
+        model=None,
+        prompt_tokens=0,
+        completion_tokens=0,
+        content=None,
+        finish_reason=None,
+        object="chat.completion",
+        param=None,
+        stream=False
 ):
     total_tokens = prompt_tokens + completion_tokens
 
@@ -562,7 +582,9 @@ def verify_embedding_availability(embd_id: str, tenant_id: str) -> tuple[bool, R
         in_llm_service = bool(LLMService.query(llm_name=llm_name, fid=llm_factory, model_type="embedding"))
 
         tenant_llms = TenantLLMService.get_my_llms(tenant_id=tenant_id)
-        is_tenant_model = any(llm["llm_name"] == llm_name and llm["llm_factory"] == llm_factory and llm["model_type"] == "embedding" for llm in tenant_llms)
+        is_tenant_model = any(
+            llm["llm_name"] == llm_name and llm["llm_factory"] == llm_factory and llm["model_type"] == "embedding" for
+            llm in tenant_llms)
 
         is_builtin_model = embd_id in settings.BUILTIN_EMBEDDING_MODELS
         if not (is_builtin_model or is_tenant_model or in_llm_service):
@@ -793,7 +815,9 @@ async def is_strong_enough(chat_model, embedding_model):
                 _ = await trio.to_thread.run_sync(lambda: embedding_model.encode(["Are you strong enough!?"]))
         if chat_model:
             with trio.fail_after(30):
-                res = await trio.to_thread.run_sync(lambda: chat_model.chat("Nothing special.", [{"role": "user", "content": "Are you strong enough!?"}], {}))
+                res = await trio.to_thread.run_sync(lambda: chat_model.chat("Nothing special.", [{"role": "user",
+                                                                                                  "content": "Are you strong enough!?"}],
+                                                                            {}))
             if res.find("**ERROR**") >= 0:
                 raise Exception(res)
 

deepdoc/vision/ocr.py

@@ -84,7 +84,8 @@ def load_model(model_dir, nm, device_id: int | None = None):
     def cuda_is_available():
         try:
             import torch
-            if torch.cuda.is_available() and torch.cuda.device_count() > device_id:
+            target_id = 0 if device_id is None else device_id
+            if torch.cuda.is_available() and torch.cuda.device_count() > target_id:
                 return True
         except Exception:
             return False
@@ -100,10 +101,13 @@ def load_model(model_dir, nm, device_id: int | None = None):
     # Shrink GPU memory after execution
     run_options = ort.RunOptions()
     if cuda_is_available():
+        gpu_mem_limit_mb = int(os.environ.get("OCR_GPU_MEM_LIMIT_MB", "2048"))
+        arena_strategy = os.environ.get("OCR_ARENA_EXTEND_STRATEGY", "kNextPowerOfTwo")
+        provider_device_id = 0 if device_id is None else device_id
         cuda_provider_options = {
-            "device_id": device_id, # Use specific GPU
-            "gpu_mem_limit": 512 * 1024 * 1024, # Limit gpu memory
-            "arena_extend_strategy": "kNextPowerOfTwo",  # gpu memory allocation strategy
+            "device_id": provider_device_id, # Use specific GPU
+            "gpu_mem_limit": max(gpu_mem_limit_mb, 0) * 1024 * 1024,
+            "arena_extend_strategy": arena_strategy,  # gpu memory allocation strategy
         }
         sess = ort.InferenceSession(
             model_file_path,
@@ -111,8 +115,8 @@ def load_model(model_dir, nm, device_id: int | None = None):
             providers=['CUDAExecutionProvider'],
             provider_options=[cuda_provider_options]
             )
-        run_options.add_run_config_entry("memory.enable_memory_arena_shrinkage", "gpu:" + str(device_id))
-        logging.info(f"load_model {model_file_path} uses GPU")
+        run_options.add_run_config_entry("memory.enable_memory_arena_shrinkage", "gpu:" + str(provider_device_id))
+        logging.info(f"load_model {model_file_path} uses GPU (device {provider_device_id}, gpu_mem_limit={cuda_provider_options['gpu_mem_limit']}, arena_strategy={arena_strategy})")
     else:
         sess = ort.InferenceSession(
             model_file_path,

docker/docker-compose-base.yml

@@ -77,7 +77,7 @@ services:
     container_name: ragflow-infinity
     profiles:
       - infinity
-    image: infiniflow/infinity:v0.6.0-dev5
+    image: infiniflow/infinity:v0.6.0-dev7
     volumes:
       - infinity_data:/var/infinity
       - ./infinity_conf.toml:/infinity_conf.toml

docs/references/http_api_reference.md

@@ -830,7 +830,8 @@ Success:
             "update_time": 1728533243536,
             "vector_similarity_weight": 0.3
         }
-    ]
+    ],
+    "total": 1
 }
 ```
 
@@ -1280,7 +1281,7 @@ Success:
                 "update_time": 1728897061948
             }
         ],
-        "total": 1
+        "total_datasets": 1
     }
 }
 ```

graphrag/general/index.py

@@ -55,7 +55,7 @@ async def run_graphrag(
     start = trio.current_time()
     tenant_id, kb_id, doc_id = row["tenant_id"], str(row["kb_id"]), row["doc_id"]
     chunks = []
-    for d in settings.retrievaler.chunk_list(doc_id, tenant_id, [kb_id], fields=["content_with_weight", "doc_id"], sort_by_position=True):
+    for d in settings.retriever.chunk_list(doc_id, tenant_id, [kb_id], fields=["content_with_weight", "doc_id"], sort_by_position=True):
         chunks.append(d["content_with_weight"])
 
     with trio.fail_after(max(120, len(chunks) * 60 * 10) if enable_timeout_assertion else 10000000000):
@@ -170,7 +170,7 @@ async def run_graphrag_for_kb(
         chunks = []
         current_chunk = ""
 
-        for d in settings.retrievaler.chunk_list(
+        for d in settings.retriever.chunk_list(
             doc_id,
             tenant_id,
             [kb_id],

graphrag/general/smoke.py

@@ -62,7 +62,7 @@ async def main():
 
     chunks = [
         d["content_with_weight"]
-        for d in settings.retrievaler.chunk_list(
+        for d in settings.retriever.chunk_list(
             args.doc_id,
             args.tenant_id,
             [kb_id],

graphrag/light/smoke.py

@@ -63,7 +63,7 @@ async def main():
 
     chunks = [
         d["content_with_weight"]
-        for d in settings.retrievaler.chunk_list(
+        for d in settings.retriever.chunk_list(
             args.doc_id,
             args.tenant_id,
             [kb_id],

graphrag/utils.py

@@ -341,7 +341,7 @@ def get_relation(tenant_id, kb_id, from_ent_name, to_ent_name, size=1):
     ents = list(set(ents))
     conds = {"fields": ["content_with_weight"], "size": size, "from_entity_kwd": ents, "to_entity_kwd": ents, "knowledge_graph_kwd": ["relation"]}
     res = []
-    es_res = settings.retrievaler.search(conds, search.index_name(tenant_id), [kb_id] if isinstance(kb_id, str) else kb_id)
+    es_res = settings.retriever.search(conds, search.index_name(tenant_id), [kb_id] if isinstance(kb_id, str) else kb_id)
     for id in es_res.ids:
         try:
             if size == 1:
@@ -398,7 +398,7 @@ async def does_graph_contains(tenant_id, kb_id, doc_id):
 
 async def get_graph_doc_ids(tenant_id, kb_id) -> list[str]:
     conds = {"fields": ["source_id"], "removed_kwd": "N", "size": 1, "knowledge_graph_kwd": ["graph"]}
-    res = await trio.to_thread.run_sync(lambda: settings.retrievaler.search(conds, search.index_name(tenant_id), [kb_id]))
+    res = await trio.to_thread.run_sync(lambda: settings.retriever.search(conds, search.index_name(tenant_id), [kb_id]))
     doc_ids = []
     if res.total == 0:
         return doc_ids
@@ -409,7 +409,7 @@ async def get_graph_doc_ids(tenant_id, kb_id) -> list[str]:
 
 async def get_graph(tenant_id, kb_id, exclude_rebuild=None):
     conds = {"fields": ["content_with_weight", "removed_kwd", "source_id"], "size": 1, "knowledge_graph_kwd": ["graph"]}
-    res = await trio.to_thread.run_sync(settings.retrievaler.search, conds, search.index_name(tenant_id), [kb_id])
+    res = await trio.to_thread.run_sync(settings.retriever.search, conds, search.index_name(tenant_id), [kb_id])
     if not res.total == 0:
         for id in res.ids:
             try:
@@ -562,7 +562,7 @@ def merge_tuples(list1, list2):
 
 
 async def get_entity_type2samples(idxnms, kb_ids: list):
-    es_res = await trio.to_thread.run_sync(lambda: settings.retrievaler.search({"knowledge_graph_kwd": "ty2ents", "kb_id": kb_ids, "size": 10000, "fields": ["content_with_weight"]}, idxnms, kb_ids))
+    es_res = await trio.to_thread.run_sync(lambda: settings.retriever.search({"knowledge_graph_kwd": "ty2ents", "kb_id": kb_ids, "size": 10000, "fields": ["content_with_weight"]}, idxnms, kb_ids))
 
     res = defaultdict(list)
     for id in es_res.ids:

helm/values.yaml

@@ -96,7 +96,7 @@ ragflow:
 infinity:
   image:
     repository: infiniflow/infinity
-    tag: v0.6.0-dev5
+    tag: v0.6.0-dev7
     pullPolicy: IfNotPresent
     pullSecrets: []
   storage:

pyproject.toml

@@ -46,7 +46,7 @@ dependencies = [
     "html-text==0.6.2",
     "httpx[socks]==0.27.2",
     "huggingface-hub>=0.25.0,<0.26.0",
-    "infinity-sdk==0.6.0.dev5",
+    "infinity-sdk==0.6.0.dev7",
     "infinity-emb>=0.0.66,<0.0.67",
     "itsdangerous==2.1.2",
     "json-repair==0.35.0",
@@ -133,6 +133,8 @@ dependencies = [
     "litellm>=1.74.15.post1",
     "flask-mail>=0.10.0",
     "lark>=1.2.2",
+    "mammoth>=1.11.0",
+    "markdownify>=1.2.0",
 ]
 
 [project.optional-dependencies]
@@ -159,7 +161,7 @@ test = [
 ]
 
 [[tool.uv.index]]
-url = "https://mirrors.aliyun.com/pypi/simple"
+url = "https://pypi.tuna.tsinghua.edu.cn/simple"
 
 [tool.setuptools]
 packages = [

rag/app/naive.py

@@ -256,6 +256,49 @@ class Docx(DocxParser):
             tbls.append(((None, html), ""))
         return new_line, tbls
 
+    def to_markdown(self, filename=None, binary=None, inline_images: bool = True):
+        """
+        This function uses mammoth, licensed under the BSD 2-Clause License.
+        """
+
+        import base64
+        import uuid
+
+        import mammoth
+        from markdownify import markdownify
+
+        docx_file = BytesIO(binary) if binary else open(filename, "rb")
+
+        def _convert_image_to_base64(image):
+            try:
+                with image.open() as image_file:
+                    image_bytes = image_file.read()
+                encoded = base64.b64encode(image_bytes).decode("utf-8")
+                base64_url = f"data:{image.content_type};base64,{encoded}"
+
+                alt_name = "image"
+                alt_name = f"img_{uuid.uuid4().hex[:8]}"
+
+                return {"src": base64_url, "alt": alt_name}
+            except Exception as e:
+                logging.warning(f"Failed to convert image to base64: {e}")
+                return {"src": "", "alt": "image"}
+
+        try:
+            if inline_images:
+                result = mammoth.convert_to_html(docx_file, convert_image=mammoth.images.img_element(_convert_image_to_base64))
+            else:
+                result = mammoth.convert_to_html(docx_file)
+
+            html = result.value
+
+            markdown_text = markdownify(html)
+            return markdown_text
+
+        finally:
+            if not binary:
+                docx_file.close()
+
 
 class Pdf(PdfParser):
     def __init__(self):
@@ -512,7 +555,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
             callback(0.2, "Visual model detected. Attempting to enhance figure extraction...")
         except Exception:
             vision_model = None
-        
+
         if vision_model:
             # Process images for each section
             section_images = []

rag/app/tag.py

@@ -133,14 +133,14 @@ def label_question(question, kbs):
     if tag_kb_ids:
         all_tags = get_tags_from_cache(tag_kb_ids)
         if not all_tags:
-            all_tags = settings.retrievaler.all_tags_in_portion(kb.tenant_id, tag_kb_ids)
+            all_tags = settings.retriever.all_tags_in_portion(kb.tenant_id, tag_kb_ids)
             set_tags_to_cache(tags=all_tags, kb_ids=tag_kb_ids)
         else:
             all_tags = json.loads(all_tags)
         tag_kbs = KnowledgebaseService.get_by_ids(tag_kb_ids)
         if not tag_kbs:
             return tags
-        tags = settings.retrievaler.tag_query(question,
+        tags = settings.retriever.tag_query(question,
                                               list(set([kb.tenant_id for kb in tag_kbs])),
                                               tag_kb_ids,
                                               all_tags,

rag/benchmark.py

@@ -52,7 +52,7 @@ class Benchmark:
         run = defaultdict(dict)
         query_list = list(qrels.keys())
         for query in query_list:
-            ranks = settings.retrievaler.retrieval(query, self.embd_mdl, self.tenant_id, [self.kb.id], 1, 30,
+            ranks = settings.retriever.retrieval(query, self.embd_mdl, self.tenant_id, [self.kb.id], 1, 30,
                                             0.0, self.vector_similarity_weight)
             if len(ranks["chunks"]) == 0:
                 print(f"deleted query: {query}")

rag/flow/parser/parser.py

@@ -52,6 +52,7 @@ class ParserParam(ProcessParamBase):
             ],
             "word": [
                 "json",
+                "markdown",
             ],
             "slides": [
                 "json",
@@ -247,13 +248,15 @@ class Parser(ProcessBase):
         conf = self._param.setups["word"]
         self.set_output("output_format", conf["output_format"])
         docx_parser = Docx()
-        sections, tbls = docx_parser(name, binary=blob)
-        sections = [{"text": section[0], "image": section[1]} for section in sections if section]
-        sections.extend([{"text": tb, "image": None} for ((_,tb), _) in tbls])
-        # json
-        assert conf.get("output_format") == "json", "have to be json for doc"
+
         if conf.get("output_format") == "json":
+            sections, tbls = docx_parser(name, binary=blob)
+            sections = [{"text": section[0], "image": section[1]} for section in sections if section]
+            sections.extend([{"text": tb, "image": None} for ((_,tb), _) in tbls])
             self.set_output("json", sections)
+        elif conf.get("output_format") == "markdown":
+            markdown_text = docx_parser.to_markdown(name, binary=blob)
+            self.set_output("markdown", markdown_text)
 
     def _slides(self, name, blob):
         from deepdoc.parser.ppt_parser import RAGFlowPptParser as ppt_parser

rag/llm/cv_model.py

@@ -614,7 +614,7 @@ class NvidiaCV(Base):
         response = response.json()
         return (
             response["choices"][0]["message"]["content"].strip(),
-            response["usage"]["total_tokens"],
+            total_token_count_from_response(response),
         )
 
     def _request(self, msg, gen_conf={}):
@@ -637,7 +637,7 @@ class NvidiaCV(Base):
         response = self._request(vision_prompt)
         return (
             response["choices"][0]["message"]["content"].strip(),
-            response["usage"]["total_tokens"],
+            total_token_count_from_response(response)
         )
 
     def chat(self, system, history, gen_conf, images=[], **kwargs):
@@ -645,7 +645,7 @@ class NvidiaCV(Base):
             response = self._request(self._form_history(system, history, images), gen_conf)
             return (
                 response["choices"][0]["message"]["content"].strip(),
-                response["usage"]["total_tokens"],
+                total_token_count_from_response(response)
             )
         except Exception as e:
             return "**ERROR**: " + str(e), 0
@@ -656,7 +656,7 @@ class NvidiaCV(Base):
             response = self._request(self._form_history(system, history, images), gen_conf)
             cnt = response["choices"][0]["message"]["content"]
             if "usage" in response and "total_tokens" in response["usage"]:
-                total_tokens += response["usage"]["total_tokens"]
+                total_tokens +=  total_token_count_from_response(response)
             for resp in cnt:
                 yield resp
         except Exception as e:

rag/prompts/toc_relevance_system.md

@@ -0,0 +1,118 @@
+# System Prompt: TOC Relevance Evaluation
+
+You are an expert logical reasoning assistant specializing in hierarchical Table of Contents (TOC) relevance evaluation.
+
+## GOAL
+You will receive:
+1. A JSON list of TOC items, each with fields:
+   ```json
+   {
+     "level": <integer>,   // e.g., 1, 2, 3
+     "title": <string>     // section title
+   }
+   ```
+2. A user query (natural language question).
+
+You must assign a **relevance score** (integer) to every TOC entry, based on how related its `title` is to the `query`.
+
+---
+
+## RULES
+
+### Scoring System
+- 5 → highly relevant (directly answers or matches the query intent)
+- 3 → somewhat related (same topic or partially overlaps)
+- 1 → weakly related (vague or tangential)
+- 0 → no clear relation
+- -1 → explicitly irrelevant or contradictory
+
+### Hierarchy Traversal
+- The TOC is hierarchical: smaller `level` = higher layer (e.g., level 1 is top-level, level 2 is a subsection).
+- You must traverse in **hierarchical order** — interpret the structure based on levels (1 > 2 > 3).
+- If a high-level item (level 1) is strongly related (score 5), its child items (level 2, 3) are likely relevant too.
+- If a high-level item is unrelated (-1 or 0), its deeper children are usually less relevant unless the titles clearly match the query.
+- Lower (deeper) levels provide more specific content; prefer assigning higher scores if they directly match the query.
+
+### Output Format
+Return a **JSON array**, preserving the input order but adding a new key `"score"`:
+
+```json
+[
+  {"level": 1, "title": "Introduction", "score": 0},
+  {"level": 2, "title": "Definition of Sustainability", "score": 5}
+]
+```
+
+### Constraints
+- Output **only the JSON array** — no explanations or reasoning text.
+
+### EXAMPLES
+
+#### Example 1
+Input TOC:
+[
+  {"level": 1, "title": "Machine Learning Overview"},
+  {"level": 2, "title": "Supervised Learning"},
+  {"level": 2, "title": "Unsupervised Learning"},
+  {"level": 3, "title": "Applications of Deep Learning"}
+]
+
+Query:
+"How is deep learning used in image classification?"
+
+Output:
+[
+  {"level": 1, "title": "Machine Learning Overview", "score": 3},
+  {"level": 2, "title": "Supervised Learning", "score": 3},
+  {"level": 2, "title": "Unsupervised Learning", "score": 0},
+  {"level": 3, "title": "Applications of Deep Learning", "score": 5}
+]
+
+---
+
+#### Example 2
+Input TOC:
+[
+  {"level": 1, "title": "Marketing Basics"},
+  {"level": 2, "title": "Consumer Behavior"},
+  {"level": 2, "title": "Digital Marketing"},
+  {"level": 3, "title": "Social Media Campaigns"},
+  {"level": 3, "title": "SEO Optimization"}
+]
+
+Query:
+"What are the best online marketing methods?"
+
+Output:
+[
+  {"level": 1, "title": "Marketing Basics", "score": 3},
+  {"level": 2, "title": "Consumer Behavior", "score": 1},
+  {"level": 2, "title": "Digital Marketing", "score": 5},
+  {"level": 3, "title": "Social Media Campaigns", "score": 5},
+  {"level": 3, "title": "SEO Optimization", "score": 5}
+]
+
+---
+
+#### Example 3
+Input TOC:
+[
+  {"level": 1, "title": "Physics Overview"},
+  {"level": 2, "title": "Classical Mechanics"},
+  {"level": 3, "title": "Newton’s Laws"},
+  {"level": 2, "title": "Thermodynamics"},
+  {"level": 3, "title": "Entropy and Heat Transfer"}
+]
+
+Query:
+"What is entropy?"
+
+Output:
+[
+  {"level": 1, "title": "Physics Overview", "score": 3},
+  {"level": 2, "title": "Classical Mechanics", "score": 0},
+  {"level": 3, "title": "Newton’s Laws", "score": -1},
+  {"level": 2, "title": "Thermodynamics", "score": 5},
+  {"level": 3, "title": "Entropy and Heat Transfer", "score": 5}
+]
+

rag/prompts/toc_relevance_user.md

@@ -0,0 +1,17 @@
+# User Prompt: TOC Relevance Evaluation
+
+You will now receive:
+1. A JSON list of TOC items (each with `level` and `title`)
+2. A user query string.
+
+Traverse the TOC hierarchically based on level numbers and assign scores (5,3,1,0,-1) according to the rules in the system prompt.  
+Output **only** the JSON array with the added `"score"` field.
+
+---
+
+**Input TOC:**
+{{ toc_json }}
+
+**Query:**
+{{ query }}
+

rag/svr/task_executor.py

@@ -380,7 +380,7 @@ async def build_chunks(task, progress_callback):
         examples = []
         all_tags = get_tags_from_cache(kb_ids)
         if not all_tags:
-            all_tags = settings.retrievaler.all_tags_in_portion(tenant_id, kb_ids, S)
+            all_tags = settings.retriever.all_tags_in_portion(tenant_id, kb_ids, S)
             set_tags_to_cache(kb_ids, all_tags)
         else:
             all_tags = json.loads(all_tags)
@@ -393,7 +393,7 @@ async def build_chunks(task, progress_callback):
             if task_canceled:
                 progress_callback(-1, msg="Task has been canceled.")
                 return
-            if settings.retrievaler.tag_content(tenant_id, kb_ids, d, all_tags, topn_tags=topn_tags, S=S) and len(d[TAG_FLD]) > 0:
+            if settings.retriever.tag_content(tenant_id, kb_ids, d, all_tags, topn_tags=topn_tags, S=S) and len(d[TAG_FLD]) > 0:
                 examples.append({"content": d["content_with_weight"], TAG_FLD: d[TAG_FLD]})
             else:
                 docs_to_tag.append(d)
@@ -645,7 +645,7 @@ async def run_raptor_for_kb(row, kb_parser_config, chat_mdl, embd_mdl, vector_si
     chunks = []
     vctr_nm = "q_%d_vec"%vector_size
     for doc_id in doc_ids:
-        for d in settings.retrievaler.chunk_list(doc_id, row["tenant_id"], [str(row["kb_id"])],
+        for d in settings.retriever.chunk_list(doc_id, row["tenant_id"], [str(row["kb_id"])],
                                                  fields=["content_with_weight", vctr_nm],
                                                  sort_by_position=True):
             chunks.append((d["content_with_weight"], np.array(d[vctr_nm])))

web/src/components/home-card.tsx

@@ -41,7 +41,7 @@ export function HomeCard({
         <div className="flex flex-col justify-between gap-1 flex-1 h-full w-[calc(100%-50px)]">
           <section className="flex justify-between w-full">
             <section className="flex gap-1 items-center w-full">
-              <div className="text-[20px] font-bold w-80% leading-5 text-ellipsis overflow-hidden">
+              <div className="text-base font-bold w-80% text-ellipsis overflow-hidden leading-snug">
                 {data.name}
               </div>
               {icon}

web/src/pages/agent/hooks/use-add-node.ts

@@ -116,6 +116,7 @@ export const useInitializeOperatorParams = () => {
       [Operator.UserFillUp]: initialUserFillUpValues,
       [Operator.StringTransform]: initialStringTransformValues,
       [Operator.TavilyExtract]: initialTavilyExtractValues,
+      [Operator.Placeholder]: {},
     };
   }, [llmId]);
 

web/src/pages/data-flow/canvas/index.tsx

@@ -178,11 +178,17 @@ function DataFlowCanvas({ drawerVisible, hideDrawer, showLogSheet }: IProps) {
   };
 
   const onConnectEnd: OnConnectEnd = (event, connectionState) => {
+    const target = event.target as HTMLElement;
     const nodeId = connectionState.fromNode?.id;
+
     // Events triggered by Handle are directly interrupted
-    if (connectionState.toNode !== null || (nodeId && hasChildNode(nodeId))) {
+    if (
+      target?.classList.contains('react-flow__handle') ||
+      (nodeId && hasChildNode(nodeId))
+    ) {
       return;
     }
+
     if ('clientX' in event && 'clientY' in event) {
       const { clientX, clientY } = event;
       setDropdownPosition({ x: clientX, y: clientY });

web/src/pages/data-flow/canvas/node/dropdown/next-step-dropdown.tsx

@@ -52,31 +52,33 @@ function OperatorItemList({
   const getNodeName = useGetNodeName();
   const getNodeDescription = useGetNodeDescription();
 
-  const handleClick = (operator: Operator) => {
-    const contextData = handleContext || {
-      nodeId: '',
-      id: '',
-      type: 'source' as const,
-      position: Position.Right,
-      isFromConnectionDrag: true,
+  const handleClick =
+    (operator: Operator): React.MouseEventHandler<HTMLElement> =>
+    (e) => {
+      const contextData = handleContext || {
+        nodeId: '',
+        id: '',
+        type: 'source' as const,
+        position: Position.Right,
+        isFromConnectionDrag: true,
+      };
+
+      const mockEvent = mousePosition
+        ? {
+            clientX: mousePosition.x,
+            clientY: mousePosition.y,
+          }
+        : e;
+
+      const newNodeId = addCanvasNode(operator, contextData)(mockEvent);
+
+      if (onNodeCreated && newNodeId) {
+        onNodeCreated(newNodeId);
+      }
+
+      hideModal?.();
     };
 
-    const mockEvent = mousePosition
-      ? {
-          clientX: mousePosition.x,
-          clientY: mousePosition.y,
-        }
-      : undefined;
-
-    const newNodeId = addCanvasNode(operator, contextData)(mockEvent);
-
-    if (onNodeCreated && newNodeId) {
-      onNodeCreated(newNodeId);
-    }
-
-    hideModal?.();
-  };
-
   const renderOperatorItem = (operator: Operator) => {
     const commonContent = (
       <div className="hover:bg-background-card py-1 px-3 cursor-pointer rounded-sm flex gap-2 items-center justify-start">
@@ -89,12 +91,12 @@ function OperatorItemList({
       <Tooltip key={operator}>
         <TooltipTrigger asChild>
           {isCustomDropdown ? (
-            <li onClick={() => handleClick(operator)}>{commonContent}</li>
+            <li onClick={handleClick(operator)}>{commonContent}</li>
           ) : (
             <DropdownMenuItem
               key={operator}
               className="hover:bg-background-card py-1 px-3 cursor-pointer rounded-sm flex gap-2 items-center justify-start"
-              onClick={() => handleClick(operator)}
+              onClick={handleClick(operator)}
               onSelect={() => hideModal?.()}
             >
               <OperatorIcon name={operator} />