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refactor: standardize InferenceRouter model handling (#2965)
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4 changed files with 28 additions and 38 deletions
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@ -8,7 +8,7 @@ from typing import Any
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from pydantic import TypeAdapter
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from llama_stack.apis.common.errors import ModelNotFoundError, VectorStoreNotFoundError
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from llama_stack.apis.common.errors import ModelNotFoundError, ModelTypeError, VectorStoreNotFoundError
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from llama_stack.apis.models import ModelType
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from llama_stack.apis.resource import ResourceType
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from llama_stack.apis.vector_dbs import ListVectorDBsResponse, VectorDB, VectorDBs
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@ -66,7 +66,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
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if model is None:
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raise ModelNotFoundError(embedding_model)
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if model.model_type != ModelType.embedding:
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raise ValueError(f"Model {embedding_model} is not an embedding model")
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raise ModelTypeError(embedding_model, model.model_type, ModelType.embedding)
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if "embedding_dimension" not in model.metadata:
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raise ValueError(f"Model {embedding_model} does not have an embedding dimension")
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vector_db_data = {
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