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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>
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48 changed files with 973 additions and 818 deletions
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@ -29,6 +29,7 @@ from llama_stack.apis.scoring_functions import ScoringFunctions
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from llama_stack.apis.shields import Shields
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from llama_stack.apis.telemetry import Telemetry
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from llama_stack.apis.tools import ToolGroups, ToolRuntime
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from llama_stack.apis.vector_dbs import VectorDBs
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from llama_stack.apis.vector_io import VectorIO
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from llama_stack.apis.version import LLAMA_STACK_API_V1ALPHA
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from llama_stack.core.client import get_client_impl
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@ -81,6 +82,7 @@ def api_protocol_map(external_apis: dict[Api, ExternalApiSpec] | None = None) ->
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Api.inspect: Inspect,
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Api.batches: Batches,
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Api.vector_io: VectorIO,
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Api.vector_dbs: VectorDBs,
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Api.models: Models,
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Api.safety: Safety,
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Api.shields: Shields,
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