fix duplicated llm name betweeen different suppliers (#2477)

### What problem does this PR solve?

#2465

### Type of change

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

api/apps/chunk_app.py

@@ -27,7 +27,7 @@ from rag.utils.es_conn import ELASTICSEARCH
 from rag.utils import rmSpace
 from api.db import LLMType, ParserType
 from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.services.llm_service import TenantLLMService
+from api.db.services.llm_service import LLMBundle
 from api.db.services.user_service import UserTenantService
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.db.services.document_service import DocumentService
@@ -141,8 +141,7 @@ def set():
             return get_data_error_result(retmsg="Tenant not found!")
 
         embd_id = DocumentService.get_embd_id(req["doc_id"])
-        embd_mdl = TenantLLMService.model_instance(
-            tenant_id, LLMType.EMBEDDING.value, embd_id)
+        embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING, embd_id)
 
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
@@ -235,8 +234,7 @@ def create():
             return get_data_error_result(retmsg="Tenant not found!")
 
         embd_id = DocumentService.get_embd_id(req["doc_id"])
-        embd_mdl = TenantLLMService.model_instance(
-            tenant_id, LLMType.EMBEDDING.value, embd_id)
+        embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING.value, embd_id)
 
         v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
         v = 0.1 * v[0] + 0.9 * v[1]
@@ -281,16 +279,14 @@ def retrieval_test():
         if not e:
             return get_data_error_result(retmsg="Knowledgebase not found!")
 
-        embd_mdl = TenantLLMService.model_instance(
-            kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
+        embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
 
         rerank_mdl = None
         if req.get("rerank_id"):
-            rerank_mdl = TenantLLMService.model_instance(
-                kb.tenant_id, LLMType.RERANK.value, llm_name=req["rerank_id"])
+            rerank_mdl = LLMBundle(kb.tenant_id, LLMType.RERANK.value, llm_name=req["rerank_id"])
 
         if req.get("keyword", False):
-            chat_mdl = TenantLLMService.model_instance(kb.tenant_id, LLMType.CHAT)
+            chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
 
         retr = retrievaler if kb.parser_id != ParserType.KG else kg_retrievaler

api/db/services/dialog_service.py

@@ -78,6 +78,7 @@ def message_fit_in(msg, max_length=4000):
 
 
 def llm_id2llm_type(llm_id):
+    llm_id = llm_id.split("@")[0]
     fnm = os.path.join(get_project_base_directory(), "conf")
     llm_factories = json.load(open(os.path.join(fnm, "llm_factories.json"), "r"))
     for llm_factory in llm_factories["factory_llm_infos"]:
@@ -89,9 +90,15 @@ def llm_id2llm_type(llm_id):
 def chat(dialog, messages, stream=True, **kwargs):
     assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
     st = timer()
-    llm = LLMService.query(llm_name=dialog.llm_id)
+    tmp = dialog.llm_id.split("@")
+    fid = None
+    llm_id = tmp[0]
+    if len(tmp)>1: fid = tmp[1]
+
+    llm = LLMService.query(llm_name=llm_id) if not fid else LLMService.query(llm_name=llm_id, fid=fid)
     if not llm:
-        llm = TenantLLMService.query(tenant_id=dialog.tenant_id, llm_name=dialog.llm_id)
+        llm = TenantLLMService.query(tenant_id=dialog.tenant_id, llm_name=llm_id) if not fid else \
+            TenantLLMService.query(tenant_id=dialog.tenant_id, llm_name=llm_id, llm_factory=fid)
         if not llm:
             raise LookupError("LLM(%s) not found" % dialog.llm_id)
         max_tokens = 8192

api/db/services/llm_service.py

@@ -17,7 +17,7 @@ from api.db.services.user_service import TenantService
 from api.settings import database_logger
 from rag.llm import EmbeddingModel, CvModel, ChatModel, RerankModel, Seq2txtModel, TTSModel
 from api.db import LLMType
-from api.db.db_models import DB, UserTenant
+from api.db.db_models import DB
 from api.db.db_models import LLMFactories, LLM, TenantLLM
 from api.db.services.common_service import CommonService
 
@@ -36,7 +36,11 @@ class TenantLLMService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_api_key(cls, tenant_id, model_name):
-        objs = cls.query(tenant_id=tenant_id, llm_name=model_name)
+        arr = model_name.split("@")
+        if len(arr) < 2:
+            objs = cls.query(tenant_id=tenant_id, llm_name=model_name)
+        else:
+            objs = cls.query(tenant_id=tenant_id, llm_name=arr[0], llm_factory=arr[1])
         if not objs:
             return
         return objs[0]
@@ -81,14 +85,17 @@ class TenantLLMService(CommonService):
             assert False, "LLM type error"
 
         model_config = cls.get_api_key(tenant_id, mdlnm)
+        tmp = mdlnm.split("@")
+        fid = None if len(tmp) < 2 else tmp[1]
+        mdlnm = tmp[0]
         if model_config: model_config = model_config.to_dict()
         if not model_config:
             if llm_type in [LLMType.EMBEDDING, LLMType.RERANK]:
-                llm = LLMService.query(llm_name=llm_name if llm_name else mdlnm)
+                llm = LLMService.query(llm_name=mdlnm) if not fid else LLMService.query(llm_name=mdlnm, fid=fid)
                 if llm and llm[0].fid in ["Youdao", "FastEmbed", "BAAI"]:
-                    model_config = {"llm_factory": llm[0].fid, "api_key":"", "llm_name": llm_name if llm_name else mdlnm, "api_base": ""}
+                    model_config = {"llm_factory": llm[0].fid, "api_key":"", "llm_name": mdlnm, "api_base": ""}
             if not model_config:
-                if llm_name == "flag-embedding":
+                if mdlnm == "flag-embedding":
                     model_config = {"llm_factory": "Tongyi-Qianwen", "api_key": "",
                                 "llm_name": llm_name, "api_base": ""}
                 else:

rag/app/naive.py

@@ -76,7 +76,7 @@ class Docx(DocxParser):
                         if last_image:
                             image_list.insert(0, last_image)
                             last_image = None
-                        lines.append((self.__clean(p.text), image_list, p.style.name))
+                        lines.append((self.__clean(p.text), image_list, p.style.name if p.style else ""))
                 else:
                     if current_image := self.get_picture(self.doc, p):
                         if lines: