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chore: Updating how default embedding model is set in stack (#3818)

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# 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>
This commit is contained in:
Francisco Arceo 2025-10-20 17:22:45 -04:00 • committed by GitHub
parent 2c43285e22
commit 48581bf651
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48 changed files with 973 additions and 818 deletions
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8
tests/integration/fixtures/common.py
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@ -21,6 +21,7 @@ from llama_stack_client import LlamaStackClient
from openai import OpenAI
from llama_stack import LlamaStackAsLibraryClient
from llama_stack.core.datatypes import VectorStoresConfig
from llama_stack.core.stack import run_config_from_adhoc_config_spec
from llama_stack.env import get_env_or_fail
@ -236,6 +237,13 @@ def instantiate_llama_stack_client(session):
if "=" in config:
run_config = run_config_from_adhoc_config_spec(config)
# --stack-config bypasses template so need this to set default embedding model
if "vector_io" in config and "inference" in config:
run_config.vector_stores = VectorStoresConfig(
embedding_model_id="inline::sentence-transformers/nomic-ai/nomic-embed-text-v1.5"
)
run_config_file = tempfile.NamedTemporaryFile(delete=False, suffix=".yaml")
with open(run_config_file.name, "w") as f:
yaml.dump(run_config.model_dump(mode="json"), f)