config is now backed by pydantic (WIP)

- add models for config options
- add function to regenerate config.yml
- replace references to config with pydantic compatible references
- remove unnecessary unwrap() statements

TODO:

- auto generate env vars
- auto generate argparse
- test loading a model

endpoints/core/router.py

@@ -62,17 +62,17 @@ async def list_models(request: Request) -> ModelList:
     Requires an admin key to see all models.
     """
 
-    model_dir = unwrap(config.model.get("model_dir"), "models")
+    model_dir = config.model.model_dir
     model_path = pathlib.Path(model_dir)
 
-    draft_model_dir = config.draft_model.get("draft_model_dir")
+    draft_model_dir = config.draft_model.draft_model_dir
 
     if get_key_permission(request) == "admin":
         models = get_model_list(model_path.resolve(), draft_model_dir)
     else:
         models = await get_current_model_list()
 
-    if unwrap(config.model.get("use_dummy_models"), False):
+    if config.model.use_dummy_models:
         models.data.insert(0, ModelCard(id="gpt-3.5-turbo"))
 
     return models
@@ -98,7 +98,7 @@ async def list_draft_models(request: Request) -> ModelList:
     """
 
     if get_key_permission(request) == "admin":
-        draft_model_dir = unwrap(config.draft_model.get("draft_model_dir"), "models")
+        draft_model_dir = config.draft_model.draft_model_dir
         draft_model_path = pathlib.Path(draft_model_dir)
 
         models = get_model_list(draft_model_path.resolve())
@@ -122,7 +122,7 @@ async def load_model(data: ModelLoadRequest) -> ModelLoadResponse:
 
         raise HTTPException(400, error_message)
 
-    model_path = pathlib.Path(unwrap(config.model.get("model_dir"), "models"))
+    model_path = pathlib.Path(config.model.model_dir)
     model_path = model_path / data.name
 
     draft_model_path = None
@@ -135,7 +135,7 @@ async def load_model(data: ModelLoadRequest) -> ModelLoadResponse:
 
             raise HTTPException(400, error_message)
 
-        draft_model_path = unwrap(config.draft_model.get("draft_model_dir"), "models")
+        draft_model_path = config.draft_model.draft_model_dir
 
     if not model_path.exists():
         error_message = handle_request_error(
@@ -192,7 +192,7 @@ async def list_all_loras(request: Request) -> LoraList:
     """
 
     if get_key_permission(request) == "admin":
-        lora_path = pathlib.Path(unwrap(config.lora.get("lora_dir"), "loras"))
+        lora_path = pathlib.Path(config.lora.lora_dir)
         loras = get_lora_list(lora_path.resolve())
     else:
         loras = get_active_loras()
@@ -227,7 +227,7 @@ async def load_lora(data: LoraLoadRequest) -> LoraLoadResponse:
 
         raise HTTPException(400, error_message)
 
-    lora_dir = pathlib.Path(unwrap(config.lora.get("lora_dir"), "loras"))
+    lora_dir = pathlib.Path(config.lora.lora_dir)
     if not lora_dir.exists():
         error_message = handle_request_error(
             "A parent lora directory does not exist for load. Check your config.yml?",
@@ -266,9 +266,7 @@ async def list_embedding_models(request: Request) -> ModelList:
     """
 
     if get_key_permission(request) == "admin":
-        embedding_model_dir = unwrap(
-            config.embeddings.get("embedding_model_dir"), "models"
-        )
+        embedding_model_dir = config.embeddings.embedding_model_dir
         embedding_model_path = pathlib.Path(embedding_model_dir)
 
         models = get_model_list(embedding_model_path.resolve())
@@ -302,9 +300,7 @@ async def load_embedding_model(
 
         raise HTTPException(400, error_message)
 
-    embedding_model_dir = pathlib.Path(
-        unwrap(config.embeddings.get("embedding_model_dir"), "models")
-    )
+    embedding_model_dir = pathlib.Path(config.embeddings.embedding_model_dir)
     embedding_model_path = embedding_model_dir / data.name
 
     if not embedding_model_path.exists():

endpoints/core/types/model.py

@@ -4,7 +4,7 @@ from pydantic import BaseModel, Field, ConfigDict
 from time import time
 from typing import List, Literal, Optional, Union
 
-from common.gen_logging import GenLogPreferences
+from common.config_models import logging_config_model
 from common.model import get_config_default
 
 
@@ -33,7 +33,7 @@ class ModelCard(BaseModel):
     object: str = "model"
     created: int = Field(default_factory=lambda: int(time()))
     owned_by: str = "tabbyAPI"
-    logging: Optional[GenLogPreferences] = None
+    logging: Optional[logging_config_model] = None
     parameters: Optional[ModelCardParameters] = None