diff --git a/duas_query.py b/duas_query.py
index 20cdfce..9c786e4 100644
--- a/duas_query.py
+++ b/duas_query.py
@@ -1,11 +1,12 @@
 from langchain_openai import OpenAIEmbeddings
 from dotenv import load_dotenv
 from langchain_postgres import PGVector
-
+import os
 load_dotenv()
 
-CONNECTION_STRING = 'postgresql+psycopg2://postgres:test@localhost:5433/vector_db'
-COLLECTION_NAME = 'duas_tags_vectors'
+CONNECTION_STRING = os.getenv('CONNECTION_STRING')
+COLLECTION_NAME = os.getenv('COLLECTION_NAME')
+
 
 # Initialize embeddings (needed for query encoding only)
 embeddings = OpenAIEmbeddings(model="text-embedding-3-small")
diff --git a/generate_dua_tags_embedding.py b/generate_dua_tags_embedding.py
index 40cacdf..103f373 100644
--- a/generate_dua_tags_embedding.py
+++ b/generate_dua_tags_embedding.py
@@ -5,12 +5,13 @@ from langchain_postgres import PGVector
 # from langchain.schema import Document
 from langchain_core.documents import Document
 from dotenv import load_dotenv
-
+import os
 load_dotenv()
 
 # Database configuration
-CONNECTION_STRING = 'postgresql+psycopg2://postgres:test@localhost:5433/vector_db'
-COLLECTION_NAME = 'duas_tags_vectors'
+
+CONNECTION_STRING = os.getenv('CONNECTION_STRING')
+COLLECTION_NAME = os.getenv('COLLECTION_NAME')
 
 # Load JSON data
 with open('duas_directus_published.json', 'r', encoding='utf-8') as f:
diff --git a/main.py b/main.py
index 1d035b2..b8a4549 100644
--- a/main.py
+++ b/main.py
@@ -6,6 +6,7 @@ from langchain_openai import OpenAIEmbeddings
 from langchain_postgres import PGVector
 from dotenv import load_dotenv
 import uvicorn
+import os
 
 load_dotenv()
 
@@ -26,8 +27,9 @@ app.add_middleware(
 )
 
 # Database configuration
-CONNECTION_STRING = 'postgresql+psycopg2://postgres:test@localhost:5433/vector_db'
-COLLECTION_NAME = 'duas_tags_vectors'
+CONNECTION_STRING = os.getenv('CONNECTION_STRING')
+COLLECTION_NAME = os.getenv('COLLECTION_NAME')
+
 
 # Initialize embeddings and vector store
 embeddings = OpenAIEmbeddings(model="text-embedding-3-small")