mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-23 19:41:54 +00:00
c2a3021bb0
Signed-off-by: ChengZi <chen.zhang@zilliz.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Dan O'Donovan <dan.odonovan@gmail.com> Co-authored-by: Tom Daniel Grande <tomdgrande@gmail.com> Co-authored-by: Grande <Tom.Daniel.Grande@statsbygg.no> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: ccurme <chester.curme@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Tomaz Bratanic <bratanic.tomaz@gmail.com> Co-authored-by: ZhangShenao <15201440436@163.com> Co-authored-by: Friso H. Kingma <fhkingma@gmail.com> Co-authored-by: ChengZi <chen.zhang@zilliz.com> Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: Morgante Pell <morgantep@google.com>
54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
"""Test VoyageAI embeddings."""
|
|
|
|
from langchain_voyageai import VoyageAIEmbeddings
|
|
|
|
# Please set VOYAGE_API_KEY in the environment variables
|
|
MODEL = "voyage-2"
|
|
|
|
|
|
def test_langchain_voyageai_embedding_documents() -> None:
|
|
"""Test voyage embeddings."""
|
|
documents = ["foo bar"]
|
|
embedding = VoyageAIEmbeddings(model=MODEL) # type: ignore[call-arg]
|
|
output = embedding.embed_documents(documents)
|
|
assert len(output) == 1
|
|
assert len(output[0]) == 1024
|
|
|
|
|
|
def test_langchain_voyageai_embedding_documents_multiple() -> None:
|
|
"""Test voyage embeddings."""
|
|
documents = ["foo bar", "bar foo", "foo"]
|
|
embedding = VoyageAIEmbeddings(model=MODEL, batch_size=2)
|
|
output = embedding.embed_documents(documents)
|
|
assert len(output) == 3
|
|
assert len(output[0]) == 1024
|
|
assert len(output[1]) == 1024
|
|
assert len(output[2]) == 1024
|
|
|
|
|
|
def test_langchain_voyageai_embedding_query() -> None:
|
|
"""Test voyage embeddings."""
|
|
document = "foo bar"
|
|
embedding = VoyageAIEmbeddings(model=MODEL) # type: ignore[call-arg]
|
|
output = embedding.embed_query(document)
|
|
assert len(output) == 1024
|
|
|
|
|
|
async def test_langchain_voyageai_async_embedding_documents_multiple() -> None:
|
|
"""Test voyage embeddings."""
|
|
documents = ["foo bar", "bar foo", "foo"]
|
|
embedding = VoyageAIEmbeddings(model=MODEL, batch_size=2)
|
|
output = await embedding.aembed_documents(documents)
|
|
assert len(output) == 3
|
|
assert len(output[0]) == 1024
|
|
assert len(output[1]) == 1024
|
|
assert len(output[2]) == 1024
|
|
|
|
|
|
async def test_langchain_voyageai_async_embedding_query() -> None:
|
|
"""Test voyage embeddings."""
|
|
document = "foo bar"
|
|
embedding = VoyageAIEmbeddings(model=MODEL) # type: ignore[call-arg]
|
|
output = await embedding.aembed_query(document)
|
|
assert len(output) == 1024
|