Add PGVector collection metadata (#1887)

The `CollectionStore` for `PGVector` has a `cmetadata` field but it's
never used. This PR add the ability to save metadata information to the
collection.

langchain/vectorstores/pgvector.py

@@ -5,7 +5,7 @@ from typing import Any, Dict, Iterable, List, Optional, Tuple
 
 import sqlalchemy
 from pgvector.sqlalchemy import Vector
-from sqlalchemy.dialects.postgresql import UUID
+from sqlalchemy.dialects.postgresql import JSON, UUID
 from sqlalchemy.orm import Mapped, Session, declarative_base, relationship
 
 from langchain.docstore.document import Document
@@ -29,7 +29,7 @@ class CollectionStore(BaseModel):
     __tablename__ = "langchain_pg_collection"
 
     name = sqlalchemy.Column(sqlalchemy.String)
-    cmetadata = sqlalchemy.Column(sqlalchemy.JSON)
+    cmetadata = sqlalchemy.Column(JSON)
 
     embeddings = relationship(
         "EmbeddingStore",
@@ -57,7 +57,7 @@ class CollectionStore(BaseModel):
         if collection:
             return collection, created
 
-        collection = cls(name=name, metadata=cmetadata)
+        collection = cls(name=name, cmetadata=cmetadata)
         session.add(collection)
         session.commit()
         created = True
@@ -121,6 +121,7 @@ class PGVector(VectorStore):
         connection_string: str,
         embedding_function: Embeddings,
         collection_name: str = _LANGCHAIN_DEFAULT_COLLECTION_NAME,
+        collection_metadata: Optional[dict] = None,
         distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
         pre_delete_collection: bool = False,
         logger: Optional[logging.Logger] = None,
@@ -128,6 +129,7 @@ class PGVector(VectorStore):
         self.connection_string = connection_string
         self.embedding_function = embedding_function
         self.collection_name = collection_name
+        self.collection_metadata = collection_metadata
         self.distance_strategy = distance_strategy
         self.pre_delete_collection = pre_delete_collection
         self.logger = logger or logging.getLogger(__name__)
@@ -168,7 +170,9 @@ class PGVector(VectorStore):
         if self.pre_delete_collection:
             self.delete_collection()
         with Session(self._conn) as session:
-            CollectionStore.get_or_create(session, self.collection_name)
+            CollectionStore.get_or_create(
+                session, self.collection_name, cmetadata=self.collection_metadata
+            )
 
     def delete_collection(self) -> None:
         self.logger.debug("Trying to delete collection")

tests/integration_tests/vectorstores/test_pgvector.py

@@ -2,6 +2,8 @@
 import os
 from typing import List
 
+from sqlalchemy.orm import Session
+
 from langchain.docstore.document import Document
 from langchain.vectorstores.pgvector import PGVector
 from tests.integration_tests.vectorstores.fake_embeddings import (
@@ -79,3 +81,21 @@ def test_pgvector_with_metadatas_with_scores() -> None:
     )
     output = docsearch.similarity_search_with_score("foo", k=1)
     assert output == [(Document(page_content="foo", metadata={"page": "0"}), 0.0)]
+
+
+def test_pgvector_collection_with_metadata() -> None:
+    """Test end to end collection construction"""
+    pgvector = PGVector(
+        collection_name="test_collection",
+        collection_metadata={"foo": "bar"},
+        embedding_function=FakeEmbeddingsWithAdaDimension(),
+        connection_string=CONNECTION_STRING,
+        pre_delete_collection=True,
+    )
+    session = Session(pgvector.connect())
+    collection = pgvector.get_collection(session)
+    if collection is None:
+        assert False, "Expected a CollectionStore object but received None"
+    else:
+        assert collection.name == "test_collection"
+        assert collection.cmetadata == {"foo": "bar"}