Add model_alias option to override model_path in completions. Closes #39

llama_cpp/llama.py

@@ -522,7 +522,7 @@ class Llama:
             if tokens_or_none is not None:
                 tokens.extend(tokens_or_none)
 
-    def create_embedding(self, input: str) -> Embedding:
+    def create_embedding(self, input: str, model: Optional[str] = None) -> Embedding:
         """Embed a string.
 
         Args:
@@ -532,6 +532,7 @@ class Llama:
             An embedding object.
         """
         assert self.ctx is not None
+        _model: str = model if model is not None else self.model_path
 
         if self.params.embedding == False:
             raise RuntimeError(
@@ -561,7 +562,7 @@ class Llama:
                     "index": 0,
                 }
             ],
-            "model": self.model_path,
+            "model": _model,
             "usage": {
                 "prompt_tokens": n_tokens,
                 "total_tokens": n_tokens,
@@ -598,6 +599,7 @@ class Llama:
         mirostat_mode: int = 0,
         mirostat_tau: float = 5.0,
         mirostat_eta: float = 0.1,
+        model: Optional[str] = None,
     ) -> Union[Iterator[Completion], Iterator[CompletionChunk]]:
         assert self.ctx is not None
         completion_id: str = f"cmpl-{str(uuid.uuid4())}"
@@ -610,6 +612,7 @@ class Llama:
         text: bytes = b""
         returned_characters: int = 0
         stop = stop if stop is not None else []
+        _model: str = model if model is not None else self.model_path
 
         if self.verbose:
             llama_cpp.llama_reset_timings(self.ctx)
@@ -708,7 +711,7 @@ class Llama:
                     "id": completion_id,
                     "object": "text_completion",
                     "created": created,
-                    "model": self.model_path,
+                    "model": _model,
                     "choices": [
                         {
                             "text": text[start:].decode("utf-8", errors="ignore"),
@@ -737,7 +740,7 @@ class Llama:
                 "id": completion_id,
                 "object": "text_completion",
                 "created": created,
-                "model": self.model_path,
+                "model": _model,
                 "choices": [
                     {
                         "text": text[returned_characters:].decode(
@@ -807,7 +810,7 @@ class Llama:
             "id": completion_id,
             "object": "text_completion",
             "created": created,
-            "model": self.model_path,
+            "model": _model,
             "choices": [
                 {
                     "text": text_str,
@@ -842,6 +845,7 @@ class Llama:
         mirostat_mode: int = 0,
         mirostat_tau: float = 5.0,
         mirostat_eta: float = 0.1,
+        model: Optional[str] = None,
     ) -> Union[Completion, Iterator[CompletionChunk]]:
         """Generate text from a prompt.
 
@@ -883,6 +887,7 @@ class Llama:
             mirostat_mode=mirostat_mode,
             mirostat_tau=mirostat_tau,
             mirostat_eta=mirostat_eta,
+            model=model,
         )
         if stream:
             chunks: Iterator[CompletionChunk] = completion_or_chunks
@@ -909,6 +914,7 @@ class Llama:
         mirostat_mode: int = 0,
         mirostat_tau: float = 5.0,
         mirostat_eta: float = 0.1,
+        model: Optional[str] = None,
     ) -> Union[Completion, Iterator[CompletionChunk]]:
         """Generate text from a prompt.
 
@@ -950,6 +956,7 @@ class Llama:
             mirostat_mode=mirostat_mode,
             mirostat_tau=mirostat_tau,
             mirostat_eta=mirostat_eta,
+            model=model,
         )
 
     def _convert_text_completion_to_chat(
@@ -1026,6 +1033,7 @@ class Llama:
         mirostat_mode: int = 0,
         mirostat_tau: float = 5.0,
         mirostat_eta: float = 0.1,
+        model: Optional[str] = None,
     ) -> Union[ChatCompletion, Iterator[ChatCompletionChunk]]:
         """Generate a chat completion from a list of messages.
 
@@ -1064,6 +1072,7 @@ class Llama:
             mirostat_mode=mirostat_mode,
             mirostat_tau=mirostat_tau,
             mirostat_eta=mirostat_eta,
+            model=model,
         )
         if stream:
             chunks: Iterator[CompletionChunk] = completion_or_chunks  # type: ignore

llama_cpp/server/app.py

@@ -16,6 +16,10 @@ class Settings(BaseSettings):
     model: str = Field(
         description="The path to the model to use for generating completions."
     )
+    model_alias: Optional[str] = Field(
+        default=None,
+        description="The alias of the model to use for generating completions.",
+    )
     n_ctx: int = Field(default=2048, ge=1, description="The context size.")
     n_gpu_layers: int = Field(
         default=0,
@@ -64,6 +68,7 @@ class Settings(BaseSettings):
 
 router = APIRouter()
 
+settings: Optional[Settings] = None
 llama: Optional[llama_cpp.Llama] = None
 
 
@@ -101,6 +106,12 @@ def create_app(settings: Optional[Settings] = None):
     if settings.cache:
         cache = llama_cpp.LlamaCache(capacity_bytes=settings.cache_size)
         llama.set_cache(cache)
+
+    def set_settings(_settings: Settings):
+        global settings
+        settings = _settings
+
+    set_settings(settings)
     return app
 
 
@@ -112,6 +123,10 @@ def get_llama():
         yield llama
 
 
+def get_settings():
+    yield settings
+
+
 model_field = Field(description="The model to use for generating completions.")
 
 max_tokens_field = Field(
@@ -236,7 +251,6 @@ def create_completion(
     completion_or_chunks = llama(
         **request.dict(
             exclude={
-                "model",
                 "n",
                 "best_of",
                 "logit_bias",
@@ -274,7 +288,7 @@ CreateEmbeddingResponse = create_model_from_typeddict(llama_cpp.Embedding)
 def create_embedding(
     request: CreateEmbeddingRequest, llama: llama_cpp.Llama = Depends(get_llama)
 ):
-    return llama.create_embedding(**request.dict(exclude={"model", "user"}))
+    return llama.create_embedding(**request.dict(exclude={"user"}))
 
 
 class ChatCompletionRequestMessage(BaseModel):
@@ -335,7 +349,6 @@ def create_chat_completion(
     completion_or_chunks = llama.create_chat_completion(
         **request.dict(
             exclude={
-                "model",
                 "n",
                 "logit_bias",
                 "user",
@@ -378,13 +391,16 @@ GetModelResponse = create_model_from_typeddict(ModelList)
 
 @router.get("/v1/models", response_model=GetModelResponse)
 def get_models(
+    settings: Settings = Depends(get_settings),
     llama: llama_cpp.Llama = Depends(get_llama),
 ) -> ModelList:
     return {
         "object": "list",
         "data": [
             {
-                "id": llama.model_path,
+                "id": settings.model_alias
+                if settings.model_alias is not None
+                else llama.model_path,
                 "object": "model",
                 "owned_by": "me",
                 "permissions": [],