llama-stack-mirror/llama_stack/providers/tests/inference/test_embeddings.py

62 lines
2.2 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import pytest
from llama_stack.apis.inference import EmbeddingsResponse, ModelType
# How to run this test:
# pytest -v -s llama_stack/providers/tests/inference/test_embeddings.py
class TestEmbeddings:
@pytest.mark.asyncio
async def test_embeddings(self, embedding_model, embedding_stack):
inference_impl, models_impl = embedding_stack
model = await models_impl.get_model(embedding_model)
if model.model_type != ModelType.embedding_model:
pytest.skip("This test is only applicable for embedding models")
response = await inference_impl.embeddings(
model_id=embedding_model,
contents=["Hello, world!"],
)
assert isinstance(response, EmbeddingsResponse)
assert len(response.embeddings) > 0
assert all(isinstance(embedding, list) for embedding in response.embeddings)
assert all(
isinstance(value, float)
for embedding in response.embeddings
for value in embedding
)
@pytest.mark.asyncio
async def test_batch_embeddings(self, embedding_model, embedding_stack):
inference_impl, models_impl = embedding_stack
model = await models_impl.get_model(embedding_model)
if model.model_type != ModelType.embedding_model:
pytest.skip("This test is only applicable for embedding models")
texts = ["Hello, world!", "This is a test", "Testing embeddings"]
response = await inference_impl.embeddings(
model_id=embedding_model,
contents=texts,
)
assert isinstance(response, EmbeddingsResponse)
assert len(response.embeddings) == len(texts)
assert all(isinstance(embedding, list) for embedding in response.embeddings)
assert all(
isinstance(value, float)
for embedding in response.embeddings
for value in embedding
)
embedding_dim = len(response.embeddings[0])
assert all(len(embedding) == embedding_dim for embedding in response.embeddings)