community: Add Laser Embedding Integration (#18111)

- **Description:** Added Integration with Meta AI's LASER
Language-Agnostic SEntence Representations embedding library, which
supports multilingual embedding for any of the languages listed here:
https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200,
including several low resource languages
- **Dependencies:** laser_encoders

libs/community/tests/integration_tests/embeddings/test_laser.py

@@ -0,0 +1,29 @@
+"""Test LASER embeddings."""
+import pytest
+
+from langchain_community.embeddings.laser import LaserEmbeddings
+
+
+@pytest.mark.filterwarnings("ignore::UserWarning:")
+@pytest.mark.parametrize("lang", [None, "lus_Latn", "english"])
+def test_laser_embedding_documents(lang: str) -> None:
+    """Test laser embeddings for documents.
+    User warning is returned by LASER library implementation
+    so will ignore in testing."""
+    documents = ["hello", "world"]
+    embedding = LaserEmbeddings(lang=lang)
+    output = embedding.embed_documents(documents)
+    assert len(output) == 2  # type: ignore[arg-type]
+    assert len(output[0]) == 1024  # type: ignore[index]
+
+
+@pytest.mark.filterwarnings("ignore::UserWarning:")
+@pytest.mark.parametrize("lang", [None, "lus_Latn", "english"])
+def test_laser_embedding_query(lang: str) -> None:
+    """Test laser embeddings for query.
+    User warning is returned by LASER library implementation
+    so will ignore in testing."""
+    query = "hello world"
+    embedding = LaserEmbeddings(lang=lang)
+    output = embedding.embed_query(query)
+    assert len(output) == 1024