Added SingleStoreDB Vector Store (#5619)

- Added `SingleStoreDB` vector store, which is a wrapper over the
SingleStore DB database, that can be used as a vector storage and has an
efficient similarity search.
- Added integration tests for the vector store
- Added jupyter notebook with the example

@dev2049

---------

Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

tests/integration_tests/vectorstores/test_singlestoredb.py

@@ -0,0 +1,142 @@
+"""Test SingleStoreDB functionality."""
+from typing import List
+
+import numpy as np
+import pytest
+
+from langchain.docstore.document import Document
+from langchain.vectorstores.singlestoredb import SingleStoreDB
+from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
+
+TEST_SINGLESTOREDB_URL = "root:pass@localhost:3306/db"
+TEST_SINGLE_RESULT = [Document(page_content="foo")]
+TEST_SINGLE_WITH_METADATA_RESULT = [Document(page_content="foo", metadata={"a": "b"})]
+TEST_RESULT = [Document(page_content="foo"), Document(page_content="foo")]
+
+try:
+    import singlestoredb as s2
+
+    singlestoredb_installed = True
+except ImportError:
+    singlestoredb_installed = False
+
+
+def drop(table_name: str) -> None:
+    with s2.connect(TEST_SINGLESTOREDB_URL) as conn:
+        conn.autocommit(True)
+        with conn.cursor() as cursor:
+            cursor.execute(f"DROP TABLE IF EXISTS {table_name};")
+
+
+class NormilizedFakeEmbeddings(FakeEmbeddings):
+    """Fake embeddings with normalization. For testing purposes."""
+
+    def normalize(self, vector: List[float]) -> List[float]:
+        """Normalize vector."""
+        return [float(v / np.linalg.norm(vector)) for v in vector]
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        return [self.normalize(v) for v in super().embed_documents(texts)]
+
+    def embed_query(self, text: str) -> List[float]:
+        return self.normalize(super().embed_query(text))
+
+
+@pytest.fixture
+def texts() -> List[str]:
+    return ["foo", "bar", "baz"]
+
+
+@pytest.mark.skipif(not singlestoredb_installed, reason="singlestoredb not installed")
+def test_singlestoredb(texts: List[str]) -> None:
+    """Test end to end construction and search."""
+    table_name = "test_singlestoredb"
+    drop(table_name)
+    docsearch = SingleStoreDB.from_texts(
+        texts,
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    output = docsearch.similarity_search("foo", k=1)
+    assert output == TEST_SINGLE_RESULT
+    drop(table_name)
+
+
+@pytest.mark.skipif(not singlestoredb_installed, reason="singlestoredb not installed")
+def test_singlestoredb_new_vector(texts: List[str]) -> None:
+    """Test adding a new document"""
+    table_name = "test_singlestoredb_new_vector"
+    drop(table_name)
+    docsearch = SingleStoreDB.from_texts(
+        texts,
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    docsearch.add_texts(["foo"])
+    output = docsearch.similarity_search("foo", k=2)
+    assert output == TEST_RESULT
+    drop(table_name)
+
+
+@pytest.mark.skipif(not singlestoredb_installed, reason="singlestoredb not installed")
+def test_singlestoredb_from_existing(texts: List[str]) -> None:
+    """Test adding a new document"""
+    table_name = "test_singlestoredb_from_existing"
+    drop(table_name)
+    SingleStoreDB.from_texts(
+        texts,
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    # Test creating from an existing
+    docsearch2 = SingleStoreDB(
+        NormilizedFakeEmbeddings(),
+        table_name="test_singlestoredb_from_existing",
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    output = docsearch2.similarity_search("foo", k=1)
+    assert output == TEST_SINGLE_RESULT
+    drop(table_name)
+
+
+@pytest.mark.skipif(not singlestoredb_installed, reason="singlestoredb not installed")
+def test_singlestoredb_from_documents(texts: List[str]) -> None:
+    """Test from_documents constructor."""
+    table_name = "test_singlestoredb_from_documents"
+    drop(table_name)
+    docs = [Document(page_content=t, metadata={"a": "b"}) for t in texts]
+    docsearch = SingleStoreDB.from_documents(
+        docs,
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    output = docsearch.similarity_search("foo", k=1)
+    assert output == TEST_SINGLE_WITH_METADATA_RESULT
+    drop(table_name)
+
+
+@pytest.mark.skipif(not singlestoredb_installed, reason="singlestoredb not installed")
+def test_singlestoredb_add_texts_to_existing(texts: List[str]) -> None:
+    """Test adding a new document"""
+    table_name = "test_singlestoredb_add_texts_to_existing"
+    drop(table_name)
+    # Test creating from an existing
+    SingleStoreDB.from_texts(
+        texts,
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    docsearch = SingleStoreDB(
+        NormilizedFakeEmbeddings(),
+        table_name=table_name,
+        host=TEST_SINGLESTOREDB_URL,
+    )
+    docsearch.add_texts(["foo"])
+    output = docsearch.similarity_search("foo", k=2)
+    assert output == TEST_RESULT
+    drop(table_name)