refactoring: LlmsManager => ModelsManager

backend/api/LlmsView.py

@@ -1,15 +1,15 @@
 from starlette.responses import JSONResponse
-from backend.managers.LlmsManager import LlmsManager
+from backend.managers.ModelsManager import ModelsManager
 from backend.pagination import parse_pagination_params
 from backend.schemas import LlmSchema
 from litellm.exceptions import BadRequestError
 
 class LlmsView:
     def __init__(self):
-        self.llmm = LlmsManager()
+        self.mm = ModelsManager()
 
     async def get(self, id: str):
-        llm = await self.llmm.get_llm(id)
+        llm = await self.mm.get_llm(id)
         if llm is None:
             return JSONResponse(headers={"error": "LLM not found"}, status_code=404)
         llm_schema = LlmSchema(id=llm.id, name=llm.name, full_name=f"{llm.provider}/{llm.name}",
@@ -23,7 +23,7 @@ async def search(self, filter: str = None, range: str = None, sort: str = None):
 
         offset, limit, sort_by, sort_order, filters = result
 
-        llms, total_count = await self.llmm.retrieve_llms(limit=limit, offset=offset, sort_by=sort_by, sort_order=sort_order, filters=filters)
+        llms, total_count = await self.mm.retrieve_llms(limit=limit, offset=offset, sort_by=sort_by, sort_order=sort_order, filters=filters)
         results = [LlmSchema(id=llm.id, name=llm.name, full_name=f"{llm.provider}/{llm.name}",
                              provider=llm.provider, api_base=llm.api_base,
                              is_active=llm.is_active)
@@ -36,7 +36,7 @@ async def search(self, filter: str = None, range: str = None, sort: str = None):
 
     async def completion(self, id: str, body: dict):
         print("completion.  body: {}".format(body))
-        llm = await self.llmm.get_llm(id)
+        llm = await self.mm.get_llm(id)
         if llm:
             messages = []
             if 'messages' in body and body['messages']:
@@ -45,7 +45,7 @@ async def completion(self, id: str, body: dict):
             if 'optional_params' in body and body['optional_params']:
                 opt_params = body['optional_params']
             try:
-                response = self.llmm.completion(llm, messages, **opt_params)
+                response = self.mm.completion(llm, messages, **opt_params)
                 return JSONResponse(response.model_dump(), status_code=200)
             except BadRequestError as e:
                 return JSONResponse(status_code=400, content={"message": e.message})

backend/managers/LlmsManager.py → backend/managers/ModelsManager.py

@@ -12,15 +12,15 @@
 import logging
 logger = logging.getLogger(__name__)
 
-class LlmsManager:
+class ModelsManager:
     _instance = None
     _lock = Lock()
 
     def __new__(cls, *args, **kwargs):
         if not cls._instance:
             with cls._lock:
                 if not cls._instance:
-                    cls._instance = super(LlmsManager, cls).__new__(cls, *args, **kwargs)
+                    cls._instance = super(ModelsManager, cls).__new__(cls, *args, **kwargs)
         return cls._instance
 
     def __init__(self):
@@ -80,7 +80,7 @@ def completion(self, llm, messages, **optional_params) -> Union[ModelResponse, C
             response = self.router.completion(model=llm.llm_name,
                                               messages=messages,
                                               **optional_params)
-            # below is the direct way to call the LLM (i.e. not using the router):
+            # below is the direct way to call the model (i.e. not using the router):
             #response = completion(model=llm.llm_name,
             #                      messages=messages,
             #                      **optional_params)
@@ -98,7 +98,7 @@ async def _init_router(self):
             await asyncio.gather(ollama_task,
                                  openai_task,
                                  return_exceptions=True)
-            # collect the available LLMs
+            # collect the available models
             llms, total_llms = await self.retrieve_llms()
             # configure router
             model_list = []