feat: Enable setting a default embedding model in the stack (#3803)

# What does this PR do?

Enables automatic embedding model detection for vector stores and by
using a `default_configured` boolean that can be defined in the
`run.yaml`.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
- Unit tests
- Integration tests
- Simple example below:

Spin up the stack:
```bash
uv run llama stack build --distro starter --image-type venv --run
```
Then test with OpenAI's client:
```python
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8321/v1/", api_key="none")
vs = client.vector_stores.create()
```
Previously you needed:

```python
vs = client.vector_stores.create(
    extra_body={
        "embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
        "embedding_dimension": 384,
    }
)
```

The `extra_body` is now unnecessary.

---------

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

tests/integration/vector_io/test_openai_vector_stores.py

@@ -159,6 +159,12 @@ def test_openai_create_vector_store(
     assert hasattr(vector_store, "created_at")
 
 
+def test_openai_create_vector_store_default(compat_client_with_empty_stores, client_with_models):
+    skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
+    vector_store = compat_client_with_empty_stores.vector_stores.create()
+    assert vector_store.id
+
+
 def test_openai_list_vector_stores(
     compat_client_with_empty_stores, client_with_models, embedding_model_id, embedding_dimension
 ):