forked from Archives/langchain
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
"""Test elasticsearch_embeddings embeddings."""
|
|
|
|
import pytest
|
|
|
|
from langchain.embeddings.elasticsearch import ElasticsearchEmbeddings
|
|
|
|
|
|
@pytest.fixture
|
|
def model_id() -> str:
|
|
# Replace with your actual model_id
|
|
return "your_model_id"
|
|
|
|
|
|
def test_elasticsearch_embedding_documents(model_id: str) -> None:
|
|
"""Test Elasticsearch embedding documents."""
|
|
documents = ["foo bar", "bar foo", "foo"]
|
|
embedding = ElasticsearchEmbeddings.from_credentials(model_id)
|
|
output = embedding.embed_documents(documents)
|
|
assert len(output) == 3
|
|
assert len(output[0]) == 768 # Change 768 to the expected embedding size
|
|
assert len(output[1]) == 768 # Change 768 to the expected embedding size
|
|
assert len(output[2]) == 768 # Change 768 to the expected embedding size
|
|
|
|
|
|
def test_elasticsearch_embedding_query(model_id: str) -> None:
|
|
"""Test Elasticsearch embedding query."""
|
|
document = "foo bar"
|
|
embedding = ElasticsearchEmbeddings.from_credentials(model_id)
|
|
output = embedding.embed_query(document)
|
|
assert len(output) == 768 # Change 768 to the expected embedding size
|