community[patch]: vectorstores import update (#21169)

Issue: we have several helper functions to import third-party libraries
like lancedb.import_lancedb in
[community.vectorstores](https://api.python.langchain.com/en/latest/vectorstores/langchain_community.vectorstores.lancedb.import_lancedb.html#langchain_community.vectorstores.lancedb.import_lancedb).
And we have core.utils.utils.guard_import that works exactly for this
purpose.
The import_<package> functions work inconsistently and rather be private
functions.
Change: replaced these functions with the guard_import function.

Related to #21133

libs/community/langchain_community/vectorstores/annoy.py

@@ -10,6 +10,7 @@ from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
 import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
+from langchain_core.utils import guard_import
 from langchain_core.vectorstores import VectorStore
 
 from langchain_community.docstore.base import Docstore
@@ -22,14 +23,7 @@ DEFAULT_METRIC = "angular"
 
 def dependable_annoy_import() -> Any:
     """Import annoy if available, otherwise raise error."""
-    try:
+    return guard_import("annoy")
-        import annoy
-    except ImportError:
-        raise ImportError(
-            "Could not import annoy python package. "
-            "Please install it with `pip install --user annoy` "
-        )
-    return annoy
 
 
 class Annoy(VectorStore):
@@ -300,7 +294,7 @@ class Annoy(VectorStore):
                     f"Expected one of {list(INDEX_METRICS)}"
                 )
             )
-        annoy = dependable_annoy_import()
+        annoy = guard_import("annoy")
         if not embeddings:
             raise ValueError("embeddings must be provided to build AnnoyIndex")
         f = len(embeddings[0])
@@ -459,7 +453,7 @@ class Annoy(VectorStore):
             )
         path = Path(folder_path)
         # load index separately since it is not picklable
-        annoy = dependable_annoy_import()
+        annoy = guard_import("annoy")
         # load docstore and index_to_docstore_id
         with open(path / "index.pkl", "rb") as file:
             docstore, index_to_docstore_id, config_object = pickle.load(file)

libs/community/langchain_community/vectorstores/lancedb.py

@@ -7,20 +7,13 @@ from typing import Any, Iterable, List, Optional
 
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
+from langchain_core.utils import guard_import
 from langchain_core.vectorstores import VectorStore
 
 
 def import_lancedb() -> Any:
     """Import lancedb package."""
-
+    return guard_import("lancedb")
-    try:
-        import lancedb
-    except ImportError as e:
-        raise ImportError(
-            "Could not import pinecone lancedb package. "
-            "Please install it with `pip install lancedb`."
-        ) from e
-    return lancedb
 
 
 class LanceDB(VectorStore):
@@ -64,7 +57,7 @@ class LanceDB(VectorStore):
         mode: Optional[str] = "overwrite",
     ):
         """Initialize with Lance DB vectorstore"""
-        lancedb = import_lancedb()
+        lancedb = guard_import("lancedb")
         self._embedding = embedding
         self._vector_key = vector_key
         self._id_key = id_key

libs/community/langchain_community/vectorstores/scann.py

@@ -9,6 +9,7 @@ from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple
 import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
+from langchain_core.utils import guard_import
 from langchain_core.vectorstores import VectorStore
 
 from langchain_community.docstore.base import AddableMixin, Docstore
@@ -26,14 +27,7 @@ def dependable_scann_import() -> Any:
     """
     Import `scann` if available, otherwise raise error.
     """
-    try:
+    return guard_import("scann")
-        import scann
-    except ImportError:
-        raise ImportError(
-            "Could not import scann python package. "
-            "Please install it with `pip install scann` "
-        )
-    return scann
 
 
 class ScaNN(VectorStore):
@@ -312,7 +306,7 @@ class ScaNN(VectorStore):
         normalize_L2: bool = False,
         **kwargs: Any,
     ) -> ScaNN:
-        scann = dependable_scann_import()
+        scann = guard_import("scann")
         distance_strategy = kwargs.get(
             "distance_strategy", DistanceStrategy.EUCLIDEAN_DISTANCE
         )
@@ -494,7 +488,7 @@ class ScaNN(VectorStore):
         scann_path = path / "{index_name}.scann".format(index_name=index_name)
         scann_path.mkdir(exist_ok=True, parents=True)
         # load index separately since it is not picklable
-        scann = dependable_scann_import()
+        scann = guard_import("scann")
         index = scann.scann_ops_pybind.load_searcher(str(scann_path))
 
         # load docstore and index_to_docstore_id

libs/community/langchain_community/vectorstores/tiledb.py

@@ -1,4 +1,5 @@
 """Wrapper around TileDB vector database."""
+
 from __future__ import annotations
 
 import pickle
@@ -9,6 +10,7 @@ from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple
 import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
+from langchain_core.utils import guard_import
 from langchain_core.vectorstores import VectorStore
 
 from langchain_community.vectorstores.utils import maximal_marginal_relevance
@@ -24,16 +26,10 @@ MAX_FLOAT = sys.float_info.max
 
 def dependable_tiledb_import() -> Any:
     """Import tiledb-vector-search if available, otherwise raise error."""
-    try:
+    return (
-        import tiledb as tiledb
+        guard_import("tiledb.vector_search"),
-        import tiledb.vector_search as tiledb_vs
+        guard_import("tiledb"),
-    except ImportError:
-        raise ImportError(
-            "Could not import tiledb-vector-search python package. "
-            "Please install it with `conda install -c tiledb tiledb-vector-search` "
-            "or `pip install tiledb-vector-search`"
     )
-    return tiledb_vs, tiledb
 
 
 def get_vector_index_uri_from_group(group: Any) -> str:
@@ -115,7 +111,10 @@ class TileDB(VectorStore):
         self.metric = metric
         self.config = config
 
-        tiledb_vs, tiledb = dependable_tiledb_import()
+        tiledb_vs, tiledb = (
+            guard_import("tiledb.vector_search"),
+            guard_import("tiledb"),
+        )
         with tiledb.scope_ctx(ctx_or_config=config):
             index_group = tiledb.Group(self.index_uri, "r")
             self.vector_index_uri = (
@@ -173,7 +172,7 @@ class TileDB(VectorStore):
         Returns:
             List of Documents and scores.
         """
-        tiledb_vs, tiledb = dependable_tiledb_import()
+        tiledb = guard_import("tiledb")
         docs = []
         docs_array = tiledb.open(
             self.docs_array_uri, "r", timestamp=self.timestamp, config=self.config
@@ -477,7 +476,10 @@ class TileDB(VectorStore):
         metadatas: bool = True,
         config: Optional[Mapping[str, Any]] = None,
     ) -> None:
-        tiledb_vs, tiledb = dependable_tiledb_import()
+        tiledb_vs, tiledb = (
+            guard_import("tiledb.vector_search"),
+            guard_import("tiledb"),
+        )
         with tiledb.scope_ctx(ctx_or_config=config):
             try:
                 tiledb.group_create(index_uri)
@@ -550,7 +552,10 @@ class TileDB(VectorStore):
                     f"Expected one of {list(INDEX_METRICS)}"
                 )
             )
-        tiledb_vs, tiledb = dependable_tiledb_import()
+        tiledb_vs, tiledb = (
+            guard_import("tiledb.vector_search"),
+            guard_import("tiledb"),
+        )
         input_vectors = np.array(embeddings).astype(np.float32)
         cls.create(
             index_uri=index_uri,
@@ -646,7 +651,7 @@ class TileDB(VectorStore):
         Returns:
             List of ids from adding the texts into the vectorstore.
         """
-        tiledb_vs, tiledb = dependable_tiledb_import()
+        tiledb = guard_import("tiledb")
         embeddings = self.embedding.embed_documents(list(texts))
         if ids is None:
             ids = [str(random.randint(0, MAX_UINT64 - 1)) for _ in texts]

libs/community/langchain_community/vectorstores/usearch.py

@@ -5,6 +5,7 @@ from typing import Any, Dict, Iterable, List, Optional, Tuple
 import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
+from langchain_core.utils import guard_import
 from langchain_core.vectorstores import VectorStore
 
 from langchain_community.docstore.base import AddableMixin, Docstore
@@ -15,14 +16,7 @@ def dependable_usearch_import() -> Any:
     """
     Import usearch if available, otherwise raise error.
     """
-    try:
+    return guard_import("usearch.index")
-        import usearch.index
-    except ImportError:
-        raise ImportError(
-            "Could not import usearch python package. "
-            "Please install it with `pip install usearch` "
-        )
-    return usearch.index
 
 
 class USearch(VectorStore):
@@ -170,7 +164,7 @@ class USearch(VectorStore):
             documents.append(Document(page_content=text, metadata=metadata))
 
         docstore = InMemoryDocstore(dict(zip(ids, documents)))
-        usearch = dependable_usearch_import()
+        usearch = guard_import("usearch.index")
         index = usearch.Index(ndim=len(embeddings[0]), metric=metric)
         index.add(np.array(ids), np.array(embeddings))
         return cls(embedding, index, docstore, ids.tolist())