llama-stack-mirror/llama_stack/providers/remote
Francisco Arceo 48581bf651
chore: Updating how default embedding model is set in stack (#3818)
# What does this PR do?

Refactor setting default vector store provider and embedding model to
use an optional `vector_stores` config in the `StackRunConfig` and clean
up code to do so (had to add back in some pieces of VectorDB). Also
added remote Qdrant and Weaviate to starter distro (based on other PR
where inference providers were added for UX).

New config is simply (default for Starter distro):

```yaml
vector_stores:
  default_provider_id: faiss
  default_embedding_model:
    provider_id: sentence-transformers
    model_id: nomic-ai/nomic-embed-text-v1.5
```

## Test Plan
CI and Unit tests.

---------

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
2025-10-20 14:22:45 -07:00
..
agents test: add unit test to ensure all config types are instantiable (#1601) 2025-03-12 22:29:58 -07:00
datasetio feat(stores)!: use backend storage references instead of configs (#3697) 2025-10-20 13:20:09 -07:00
eval feat: add static embedding metadata to dynamic model listings for providers using OpenAIMixin (#3547) 2025-09-25 17:17:00 -04:00
files/s3 feat(stores)!: use backend storage references instead of configs (#3697) 2025-10-20 13:20:09 -07:00
inference docs: Documentation update for NVIDIA Inference Provider (#3840) 2025-10-20 09:51:43 -07:00
post_training fix: remove inference.completion from docs (#3589) 2025-09-29 13:14:41 -07:00
safety chore!: Safety api refactoring to use OpenAIMessageParam (#3796) 2025-10-12 08:01:00 -07:00
tool_runtime feat(tools)!: substantial clean up of "Tool" related datatypes (#3627) 2025-10-02 15:12:03 -07:00
vector_io chore: Updating how default embedding model is set in stack (#3818) 2025-10-20 14:22:45 -07:00
__init__.py impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00