diff --git a/backend/requirements.txt b/backend/requirements.txt
index ee6a49bff..9836a1cb7 100644
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -1,33 +1,33 @@
 asyncio==3.4.3
-boto3==1.35.90
-botocore==1.35.90
+boto3==1.36.2
+botocore==1.36.2
 certifi==2024.8.30
 fastapi==0.115.6
 fastapi-health==0.4.0
-google-api-core==2.23.0
-google-auth==2.36.0
+google-api-core==2.24.0
+google-auth==2.37.0
 google_auth_oauthlib==1.2.1
 google-cloud-core==2.4.1
 json-repair==0.30.2
 pip-install==1.3.5
-langchain==0.3.13
-langchain-aws==0.2.10
-langchain-anthropic==0.3.0
-langchain-fireworks==0.2.5
-langchain-community==0.3.13
-langchain-core==0.3.28
+langchain==0.3.15
+langchain-aws==0.2.11
+langchain-anthropic==0.3.3
+langchain-fireworks==0.2.6
+langchain-community==0.3.15
+langchain-core==0.3.31
 langchain-experimental==0.3.4
-langchain-google-vertexai==2.0.7
-langchain-groq==0.2.1
-langchain-openai==0.2.14
-langchain-text-splitters==0.3.4
+langchain-google-vertexai==2.0.11
+langchain-groq==0.2.3
+langchain-openai==0.3.1
+langchain-text-splitters==0.3.5
 langchain-huggingface==0.1.2
 langdetect==1.0.9
-langsmith==0.2.4
-langserve==0.3.0
+langsmith==0.2.11
+langserve==0.3.1
 neo4j-rust-ext
 nltk==3.9.1
-openai==1.58.1
+openai==1.59.9
 opencv-python==4.10.0.84
 psutil==6.1.0
 pydantic==2.9.2
@@ -56,7 +56,6 @@ google-cloud-logging==3.11.3
 pypandoc==1.13
 graphdatascience==1.12
 Secweb==1.11.0
-ragas==0.2.6
+ragas==0.2.11
 rouge_score==0.1.2
-langchain-neo4j==0.2.0
-
+langchain-neo4j==0.3.0
diff --git a/backend/src/make_relationships.py b/backend/src/make_relationships.py
index 333f0c550..bccfa1ddd 100644
--- a/backend/src/make_relationships.py
+++ b/backend/src/make_relationships.py
@@ -161,7 +161,8 @@ def create_chunk_vector_index(graph):
                                     graph=graph,
                                     node_label="Chunk", 
                                     embedding_node_property="embedding",
-                                    index_name="vector"
+                                    index_name="vector",
+                                    embedding_dimension=EMBEDDING_DIMENSION
                                     )
             vector_store.create_new_index()
             logging.info(f"Index created successfully. Time taken: {time.time() - start_time:.2f} seconds")