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"""Test huggingface embeddings.""" | |
from langchain.embeddings.huggingface import ( | |
HuggingFaceEmbeddings, | |
HuggingFaceInstructEmbeddings, | |
) | |
def test_huggingface_embedding_documents() -> None: | |
"""Test huggingface embeddings.""" | |
documents = ["foo bar"] | |
embedding = HuggingFaceEmbeddings() | |
output = embedding.embed_documents(documents) | |
assert len(output) == 1 | |
assert len(output[0]) == 768 | |
def test_huggingface_embedding_query() -> None: | |
"""Test huggingface embeddings.""" | |
document = "foo bar" | |
embedding = HuggingFaceEmbeddings(encode_kwargs={"batch_size": 16}) | |
output = embedding.embed_query(document) | |
assert len(output) == 768 | |
def test_huggingface_instructor_embedding_documents() -> None: | |
"""Test huggingface embeddings.""" | |
documents = ["foo bar"] | |
embedding = HuggingFaceInstructEmbeddings() | |
output = embedding.embed_documents(documents) | |
assert len(output) == 1 | |
assert len(output[0]) == 768 | |
def test_huggingface_instructor_embedding_query() -> None: | |
"""Test huggingface embeddings.""" | |
query = "foo bar" | |
embedding = HuggingFaceInstructEmbeddings() | |
output = embedding.embed_query(query) | |
assert len(output) == 768 | |