fix: Pydantic v2 discriminated union default handling

Remove invalid default parameters from KVStoreConfig and SqlStoreConfig
  Annotated types which were causing UnsupportedFieldAttributeWarning and
  producing incorrect string values instead of proper config objects.

  Add proper default_factory to all KVStoreConfig and SqlStoreConfig fields
  across core datatypes and provider configs, ensuring they instantiate
  SqliteKVStoreConfig or SqliteSqlStoreConfig objects with correct defaults.

  This improves usability by allowing configs to be instantiated without
  explicitly providing storage configuration while maintaining type safety
  and discriminated union functionality.

Signed-off-by: Charlie Doern <cdoern@redhat.com>

llama_stack/providers/remote/datasetio/huggingface/config.py

@@ -5,7 +5,7 @@
 # the root directory of this source tree.
 from typing import Any
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 from llama_stack.providers.utils.kvstore.config import (
     KVStoreConfig,
@@ -14,7 +14,7 @@ from llama_stack.providers.utils.kvstore.config import (
 
 
 class HuggingfaceDatasetIOConfig(BaseModel):
-    kvstore: KVStoreConfig
+    kvstore: KVStoreConfig = Field(default_factory=SqliteKVStoreConfig)
 
     @classmethod
     def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]:

llama_stack/providers/remote/files/s3/config.py

@@ -24,7 +24,9 @@ class S3FilesImplConfig(BaseModel):
     auto_create_bucket: bool = Field(
         default=False, description="Automatically create the S3 bucket if it doesn't exist"
     )
-    metadata_store: SqlStoreConfig = Field(description="SQL store configuration for file metadata")
+    metadata_store: SqlStoreConfig = Field(
+        default_factory=SqliteSqlStoreConfig, description="SQL store configuration for file metadata"
+    )
 
     @classmethod
     def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:

llama_stack/providers/remote/vector_io/chroma/config.py

@@ -15,7 +15,7 @@ from llama_stack.schema_utils import json_schema_type
 @json_schema_type
 class ChromaVectorIOConfig(BaseModel):
     url: str | None
-    kvstore: KVStoreConfig = Field(description="Config for KV store backend")
+    kvstore: KVStoreConfig = Field(default_factory=SqliteKVStoreConfig, description="Config for KV store backend")
 
     @classmethod
     def sample_run_config(cls, __distro_dir__: str, url: str = "${env.CHROMADB_URL}", **kwargs: Any) -> dict[str, Any]:

llama_stack/providers/remote/vector_io/milvus/config.py

@@ -17,7 +17,7 @@ class MilvusVectorIOConfig(BaseModel):
     uri: str = Field(description="The URI of the Milvus server")
     token: str | None = Field(description="The token of the Milvus server")
     consistency_level: str = Field(description="The consistency level of the Milvus server", default="Strong")
-    kvstore: KVStoreConfig = Field(description="Config for KV store backend")
+    kvstore: KVStoreConfig = Field(default_factory=SqliteKVStoreConfig, description="Config for KV store backend")
 
     # This configuration allows additional fields to be passed through to the underlying Milvus client.
     # See the [Milvus](https://milvus.io/docs/install-overview.md) documentation for more details about Milvus in general.

llama_stack/providers/remote/vector_io/qdrant/config.py

@@ -6,7 +6,7 @@
 
 from typing import Any
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 from llama_stack.providers.utils.kvstore.config import (
     KVStoreConfig,
@@ -27,7 +27,7 @@ class QdrantVectorIOConfig(BaseModel):
     prefix: str | None = None
     timeout: int | None = None
     host: str | None = None
-    kvstore: KVStoreConfig
+    kvstore: KVStoreConfig = Field(default_factory=SqliteKVStoreConfig)
 
     @classmethod
     def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]: