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516e1a3e59
# What does this PR do? Adds the sentence transformer provider and the `all-MiniLM-L6-v2` embedding model to the default models to register in the run.yaml for all providers. ## Test Plan llama stack build --template together --image-type conda llama stack run ~/.llama/distributions/llamastack-together/together-run.yaml
62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import pytest
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from llama_stack.apis.inference import EmbeddingsResponse, ModelType
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# How to run this test:
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# pytest -v -s llama_stack/providers/tests/inference/test_embeddings.py
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class TestEmbeddings:
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@pytest.mark.asyncio
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async def test_embeddings(self, inference_model, inference_stack):
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inference_impl, models_impl = inference_stack
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model = await models_impl.get_model(inference_model)
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if model.model_type != ModelType.embedding:
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pytest.skip("This test is only applicable for embedding models")
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response = await inference_impl.embeddings(
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model_id=inference_model,
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contents=["Hello, world!"],
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)
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assert isinstance(response, EmbeddingsResponse)
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assert len(response.embeddings) > 0
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assert all(isinstance(embedding, list) for embedding in response.embeddings)
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assert all(
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isinstance(value, float)
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for embedding in response.embeddings
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for value in embedding
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)
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@pytest.mark.asyncio
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async def test_batch_embeddings(self, inference_model, inference_stack):
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inference_impl, models_impl = inference_stack
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model = await models_impl.get_model(inference_model)
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if model.model_type != ModelType.embedding:
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pytest.skip("This test is only applicable for embedding models")
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texts = ["Hello, world!", "This is a test", "Testing embeddings"]
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response = await inference_impl.embeddings(
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model_id=inference_model,
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contents=texts,
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)
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assert isinstance(response, EmbeddingsResponse)
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assert len(response.embeddings) == len(texts)
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assert all(isinstance(embedding, list) for embedding in response.embeddings)
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assert all(
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isinstance(value, float)
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for embedding in response.embeddings
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for value in embedding
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)
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embedding_dim = len(response.embeddings[0])
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assert all(len(embedding) == embedding_dim for embedding in response.embeddings)
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