diff --git a/docs/extras/modules/data_connection/retrievers/integrations/weaviate-hybrid.ipynb b/docs/extras/modules/data_connection/retrievers/integrations/weaviate-hybrid.ipynb
index f790dd7bda4..f256d49d068 100644
--- a/docs/extras/modules/data_connection/retrievers/integrations/weaviate-hybrid.ipynb
+++ b/docs/extras/modules/data_connection/retrievers/integrations/weaviate-hybrid.ipynb
@@ -48,9 +48,9 @@
     "import os\n",
     "\n",
     "WEAVIATE_URL = os.getenv(\"WEAVIATE_URL\")\n",
+    "auth_client_secret = (weaviate.AuthApiKey(api_key=os.getenv(\"WEAVIATE_API_KEY\")),)\n",
     "client = weaviate.Client(\n",
     "    url=WEAVIATE_URL,\n",
-    "    auth_client_secret=weaviate.AuthApiKey(api_key=os.getenv(\"WEAVIATE_API_KEY\")),\n",
     "    additional_headers={\n",
     "        \"X-Openai-Api-Key\": os.getenv(\"OPENAI_API_KEY\"),\n",
     "    },\n",
@@ -68,10 +68,7 @@
     {
      "name": "stderr",
      "output_type": "stream",
-     "text": [
-      "/workspaces/langchain/langchain/vectorstores/analyticdb.py:20: MovedIn20Warning: The ``declarative_base()`` function is now available as sqlalchemy.orm.declarative_base(). (deprecated since: 2.0) (Background on SQLAlchemy 2.0 at: https://sqlalche.me/e/b8d9)\n",
-      "  Base = declarative_base()  # type: Any\n"
-     ]
+     "text": []
     }
    ],
    "source": [
@@ -87,7 +84,11 @@
    "outputs": [],
    "source": [
     "retriever = WeaviateHybridSearchRetriever(\n",
-    "    client, index_name=\"LangChain\", text_key=\"text\"\n",
+    "    client=client,\n",
+    "    index_name=\"LangChain\",\n",
+    "    text_key=\"text\",\n",
+    "    attributes=[],\n",
+    "    create_schema_if_missing=True,\n",
     ")"
    ]
   },
@@ -152,11 +153,11 @@
     {
      "data": {
       "text/plain": [
-       "['eda16d7d-437d-4613-84ae-c2e38705ec7a',\n",
-       " '04b501bf-192b-4e72-be77-2fbbe7e67ebf',\n",
-       " '18a1acdb-23b7-4482-ab04-a6c2ed51de77',\n",
-       " '88e82cc3-c020-4b5a-b3c6-ca7cf3fc6a04',\n",
-       " 'f6abd9d5-32ed-46c4-bd08-f8d0f7c9fc95']"
+       "['3a27b0a5-8dbb-4fee-9eba-8b6bc2c252be',\n",
+       " 'eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907',\n",
+       " '7ebbdae7-1061-445f-a046-1989f2343d8f',\n",
+       " 'c2ab315b-3cab-467f-b23a-b26ed186318d',\n",
+       " 'b83765f2-e5d2-471f-8c02-c3350ade4c4f']"
       ]
      },
      "execution_count": 6,
@@ -238,6 +239,41 @@
     "    },\n",
     ")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ae2899e",
+   "metadata": {},
+   "source": [
+    "Do a hybrid search with scores:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4fffd0af",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Document(page_content='Prof. Sterling explores the potential for harmonious coexistence between humans and artificial intelligence. The book discusses how AI can be integrated into society in a beneficial and non-disruptive manner.', metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907 contributed 0.00819672131147541 to the score\\n(hybrid) Document eeb9fd9b-a3ac-4d60-a55b-a63a25d3b907 contributed 0.00819672131147541 to the score', 'score': '0.016393442'}}),\n",
+       " Document(page_content=\"In his follow-up to 'Symbiosis', Prof. Sterling takes a look at the subtle, unnoticed presence and influence of AI in our everyday lives. It reveals how AI has become woven into our routines, often without our explicit realization.\", metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document b83765f2-e5d2-471f-8c02-c3350ade4c4f contributed 0.0078125 to the score\\n(hybrid) Document b83765f2-e5d2-471f-8c02-c3350ade4c4f contributed 0.008064516129032258 to the score', 'score': '0.015877016'}}),\n",
+       " Document(page_content='In her second book, Dr. Simmons delves deeper into the ethical considerations surrounding AI development and deployment. It is an eye-opening examination of the dilemmas faced by developers, policymakers, and society at large.', metadata={'_additional': {'explainScore': '(bm25)\\n(hybrid) Document 7ebbdae7-1061-445f-a046-1989f2343d8f contributed 0.008064516129032258 to the score\\n(hybrid) Document 7ebbdae7-1061-445f-a046-1989f2343d8f contributed 0.0078125 to the score', 'score': '0.015877016'}}),\n",
+       " Document(page_content='A comprehensive analysis of the evolution of artificial intelligence, from its inception to its future prospects. Dr. Simmons covers ethical considerations, potentials, and threats posed by AI.', metadata={'_additional': {'explainScore': '(vector) [-0.0071824766 -0.0006682752 0.001723625 -0.01897258 -0.0045127636 0.0024410256 -0.020503938 0.013768672 0.009520169 -0.037972264]...  \\n(hybrid) Document 3a27b0a5-8dbb-4fee-9eba-8b6bc2c252be contributed 0.007936507936507936 to the score', 'score': '0.007936508'}})]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "retriever.get_relevant_documents(\n",
+    "    \"AI integration in society\",\n",
+    "    score=True,\n",
+    ")"
+   ]
   }
  ],
  "metadata": {
@@ -256,7 +292,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.9.17"
   }
  },
  "nbformat": 4,
diff --git a/langchain/retrievers/weaviate_hybrid_search.py b/langchain/retrievers/weaviate_hybrid_search.py
index d6d00d5326c..994d02e212c 100644
--- a/langchain/retrievers/weaviate_hybrid_search.py
+++ b/langchain/retrievers/weaviate_hybrid_search.py
@@ -98,12 +98,16 @@ class WeaviateHybridSearchRetriever(BaseRetriever):
         *,
         run_manager: CallbackManagerForRetrieverRun,
         where_filter: Optional[Dict[str, object]] = None,
+        score: bool = False,
     ) -> List[Document]:
         """Look up similar documents in Weaviate."""
         query_obj = self.client.query.get(self.index_name, self.attributes)
         if where_filter:
             query_obj = query_obj.with_where(where_filter)
 
+        if score:
+            query_obj = query_obj.with_additional(["score", "explainScore"])
+
         result = query_obj.with_hybrid(query, alpha=self.alpha).with_limit(self.k).do()
         if "errors" in result:
             raise ValueError(f"Error during query: {result['errors']}")
diff --git a/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py b/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py
index 581bfe9e231..267820cf2ac 100644
--- a/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py
+++ b/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py
@@ -61,6 +61,29 @@ class TestWeaviateHybridSearchRetriever:
             Document(page_content="bar", metadata={"page": 1}),
         ]
 
+    @pytest.mark.vcr(ignore_localhost=True)
+    def test_get_relevant_documents_with_score(self, weaviate_url: str) -> None:
+        """Test end to end construction and MRR search."""
+        texts = ["foo", "bar", "baz"]
+        metadatas = [{"page": i} for i in range(len(texts))]
+
+        client = Client(weaviate_url)
+
+        retriever = WeaviateHybridSearchRetriever(
+            client=client,
+            index_name=f"LangChain_{uuid4().hex}",
+            text_key="text",
+            attributes=["page"],
+        )
+        for i, text in enumerate(texts):
+            retriever.add_documents(
+                [Document(page_content=text, metadata=metadatas[i])]
+            )
+
+        output = retriever.get_relevant_documents("foo", score=True)
+        for doc in output:
+            assert "_additional" in doc.metadata
+
     @pytest.mark.vcr(ignore_localhost=True)
     def test_get_relevant_documents_with_filter(self, weaviate_url: str) -> None:
         """Test end to end construction and MRR search."""