llama-stack-mirror/llama_stack/core/routers
Francisco Arceo ef4bc70bbe
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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>
2025-10-14 18:25:13 -07:00
..
__init__.py chore!: BREAKING CHANGE removing VectorDB APIs (#3774) 2025-10-11 14:07:08 -07:00
datasets.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
eval_scoring.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
inference.py feat(api)!: support extra_body to embeddings and vector_stores APIs (#3794) 2025-10-12 19:01:52 -07:00
safety.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
tool_runtime.py feat(tools)!: substantial clean up of "Tool" related datatypes (#3627) 2025-10-02 15:12:03 -07:00
vector_io.py feat: Enable setting a default embedding model in the stack (#3803) 2025-10-14 18:25:13 -07:00