API: Add inline exception for dummy models

If an API key sends a dummy model, it shouldn't error as the server
is catering to clients that expect specific OAI model names. This
is a problem with inline model loading since these names would error
by default. Therefore, add an exception if the provided name is in the
dummy model names (which also doubles as inline strict exceptions).

However, the dummy model names weren't configurable, so add a new
option to specify exception names, otherwise the default is gpt-3.5-turbo.

Signed-off-by: kingbri <bdashore3@proton.me>

common/config_models.py

@@ -141,14 +141,25 @@ class ModelConfig(BaseConfigModel):
         False,
         description=(
             "Allow direct loading of models "
-            "from a completion or chat completion request (default: False)."
+            "from a completion or chat completion request (default: False).\n"
+            "This method of loading is strict by default.\n"
+            "Enable dummy models to add exceptions for invalid model names."
         ),
     )
     use_dummy_models: Optional[bool] = Field(
         False,
         description=(
-            "Sends dummy model names when the models endpoint is queried.\n"
-            "Enable this if the client is looking for specific OAI models."
+            "Sends dummy model names when the models endpoint is queried. "
+            "(default: False)\n"
+            "Enable this if the client is looking for specific OAI models.\n"
+        ),
+    )
+    dummy_model_names: List[str] = Field(
+        default=["gpt-3.5-turbo"],
+        description=(
+            "A list of fake model names that are sent via the /v1/models endpoint. "
+            '(default: ["gpt-3.5-turbo"])\n'
+            "Also used as bypasses for strict mode if inline_model_loading is true."
         ),
     )
     model_name: Optional[str] = Field(

config_sample.yml

@@ -49,12 +49,18 @@ model:
   model_dir: models
 
   # Allow direct loading of models from a completion or chat completion request (default: False).
+  # This method of loading is strict by default.
+  # Enable dummy models to add exceptions for invalid model names.
   inline_model_loading: false
 
-  # Sends dummy model names when the models endpoint is queried.
+  # Sends dummy model names when the models endpoint is queried. (default: False)
   # Enable this if the client is looking for specific OAI models.
   use_dummy_models: false
 
+  # A list of fake model names that are sent via the /v1/models endpoint. (default: ["gpt-3.5-turbo"])
+  # Also used as bypasses for strict mode if inline_model_loading is true.
+  dummy_model_names: ["gpt-3.5-turbo"]
+
   # An initial model to load.
   # Make sure the model is located in the model directory!
   # REQUIRED: This must be filled out to load a model on startup.

endpoints/OAI/utils/completion.py

@@ -130,18 +130,33 @@ async def load_inline_model(model_name: str, request: Request):
 
         return
 
-    # Error if an invalid key is passed
-    if get_key_permission(request) != "admin":
-        error_message = handle_request_error(
-            f"Unable to switch model to {model_name} because "
-            + "an admin key isn't provided",
-            exc_info=False,
-        ).error.message
+    is_dummy_model = (
+        config.model.use_dummy_models and model_name in config.model.dummy_model_names
+    )
 
-        raise HTTPException(401, error_message)
+    # Error if an invalid key is passed
+    # If a dummy model is provided, don't error
+    if get_key_permission(request) != "admin":
+        if not is_dummy_model:
+            error_message = handle_request_error(
+                f"Unable to switch model to {model_name} because "
+                + "an admin key isn't provided",
+                exc_info=False,
+            ).error.message
+
+            raise HTTPException(401, error_message)
+        else:
+            return
 
     # Start inline loading
     # Past here, user is assumed to be admin
+
+    # Skip if the model is a dummy
+    if is_dummy_model:
+        logger.warning(f"Dummy model {model_name} provided. Skipping inline load.")
+
+        return
+
     model_path = pathlib.Path(config.model.model_dir)
     model_path = model_path / model_name
 

endpoints/core/router.py

@@ -39,6 +39,7 @@ from endpoints.core.utils.lora import get_active_loras, get_lora_list
 from endpoints.core.utils.model import (
     get_current_model,
     get_current_model_list,
+    get_dummy_models,
     get_model_list,
     stream_model_load,
 )
@@ -82,7 +83,7 @@ async def list_models(request: Request) -> ModelList:
         models = await get_current_model_list()
 
     if config.model.use_dummy_models:
-        models.data.insert(0, ModelCard(id="gpt-3.5-turbo"))
+        models.data[:0] = get_dummy_models()
 
     return models
 

endpoints/core/utils/model.py

@@ -92,6 +92,13 @@ def get_current_model():
     return model_card
 
 
+def get_dummy_models():
+    if config.model.dummy_model_names:
+        return [ModelCard(id=dummy_id) for dummy_id in config.model.dummy_model_names]
+    else:
+        return [ModelCard(id="gpt-3.5-turbo")]
+
+
 async def stream_model_load(
     data: ModelLoadRequest,
     model_path: pathlib.Path,