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fix: Error out when creating vector store with unknown embedding model (#4154)

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# What does this PR do?
Error out when creating vector store with unknown embedding model

Closes https://github.com/llamastack/llama-stack/issues/4047

## Test Plan
Added tests

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
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Francisco Arceo 2025-11-13 16:43:31 -05:00 • committed by GitHub
parent 2441ca9389
commit a82b79ce57
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2 changed files with 46 additions and 1 deletions
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10
src/llama_stack/core/routers/vector_io.py
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@ -14,7 +14,9 @@ from llama_stack_api import (
HealthResponse,
HealthStatus,
InterleavedContent,
ModelNotFoundError,
ModelType,
ModelTypeError,
OpenAICreateVectorStoreFileBatchRequestWithExtraBody,
OpenAICreateVectorStoreRequestWithExtraBody,
QueryChunksResponse,
@ -124,6 +126,14 @@ class VectorIORouter(VectorIO):
if embedding_model is not None and embedding_dimension is None:
embedding_dimension = await self._get_embedding_model_dimension(embedding_model)
# Validate that embedding model exists and is of the correct type
if embedding_model is not None:
model = await self.routing_table.get_object_by_identifier("model", embedding_model)
if model is None:
raise ModelNotFoundError(embedding_model)
if model.model_type != ModelType.embedding:
raise ModelTypeError(embedding_model, model.model_type, ModelType.embedding)
# Auto-select provider if not specified
if provider_id is None:
num_providers = len(self.routing_table.impls_by_provider_id)