feat: configure vector-io provider with an embedding model

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>

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

@@ -12,6 +12,7 @@ from llama_stack.providers.utils.kvstore.config import (
     KVStoreConfig,
     SqliteKVStoreConfig,
 )
+from llama_stack.providers.utils.vector_io.embedding_config import EmbeddingConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -21,6 +22,13 @@ class WeaviateVectorIOConfig(BaseModel):
     weaviate_cluster_url: str | None = Field(description="The URL of the Weaviate cluster", default="localhost:8080")
     kvstore: KVStoreConfig | None = Field(description="Config for KV store backend (SQLite only for now)", default=None)
 
+
+@json_schema_type
+class WeaviateVectorIOConfig(BaseModel):
+    embedding: EmbeddingConfig | None = Field(
+        default=None,
+        description="Default embedding configuration for this provider. When specified, vector databases created with this provider will use these embedding settings as defaults.",
+    )
     @classmethod
     def sample_run_config(
         cls,
@@ -34,4 +42,9 @@ class WeaviateVectorIOConfig(BaseModel):
                 __distro_dir__=__distro_dir__,
                 db_name="weaviate_registry.db",
             ),
+            # Optional: Configure default embedding model for this provider
+            # "embedding": {
+            #     "model": "${env.WEAVIATE_EMBEDDING_MODEL:=all-MiniLM-L6-v2}",
+            #     "dimensions": 384
+            # },
         }