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# 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> |
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| .. | ||
| access_control | ||
| conversations | ||
| prompts | ||
| routers | ||
| routing_tables | ||
| server | ||
| store | ||
| ui | ||
| utils | ||
| __init__.py | ||
| build.py | ||
| build_container.sh | ||
| build_venv.sh | ||
| client.py | ||
| common.sh | ||
| configure.py | ||
| datatypes.py | ||
| distribution.py | ||
| external.py | ||
| id_generation.py | ||
| inspect.py | ||
| library_client.py | ||
| providers.py | ||
| request_headers.py | ||
| resolver.py | ||
| stack.py | ||
| start_stack.sh | ||
| testing_context.py | ||