diff --git a/Dockerfile b/Dockerfile
index f0642ded9..5f76aff3a 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -41,6 +41,8 @@ RUN apt-get update -q && \
         /var/tmp/*
 
 WORKDIR /app
+# Set the PYTHONPATH environment variable to include the /app directory
+ENV PYTHONPATH=/app
 
 COPY cognitive_architecture/ /app/cognitive_architecture
 COPY main.py /app
diff --git a/cognitive_architecture/config.py b/cognitive_architecture/config.py
index a113fd5ad..33b4a32f1 100644
--- a/cognitive_architecture/config.py
+++ b/cognitive_architecture/config.py
@@ -36,6 +36,7 @@ class Config:
     db_user: str = os.getenv("DB_USER", "cognee")
     db_password: str = os.getenv("DB_PASSWORD", "cognee")
     sqlalchemy_logging: bool = os.getenv("SQLALCHEMY_LOGGING", True)
+    graph_name = os.getenv("GRAPH_NAME", "cognee_graph.pkl")
 
     # Model parameters
     model: str = "gpt-4-1106-preview"
diff --git a/cognitive_architecture/database/graphdb/networkx/networkx_graph.py b/cognitive_architecture/database/graphdb/networkx/networkx_graph.py
index ae005ccdf..137ae07ca 100644
--- a/cognitive_architecture/database/graphdb/networkx/networkx_graph.py
+++ b/cognitive_architecture/database/graphdb/networkx/networkx_graph.py
@@ -1,10 +1,16 @@
 import pickle
-
+from pathlib import Path
+from cognitive_architecture.config import Config
 import networkx as nx
+config = Config()
+config  = config.load()
+
 
 
 class NetworkXGraphDB:
-    def __init__(self, filename="cognee_graph.pkl"):
+    """A class to manage a graph database using NetworkX"""
+    graph_path = (Path(config.base_path) / config.graph_name).absolute()
+    def __init__(self, filename=graph_path):
         self.filename = filename
         try:
             self.graph = self.load_graph()  # Attempt to load an existing graph
diff --git a/cognitive_architecture/fetch_secret.py b/cognitive_architecture/fetch_secret.py
index 9c8b992d6..65b5326a9 100644
--- a/cognitive_architecture/fetch_secret.py
+++ b/cognitive_architecture/fetch_secret.py
@@ -12,12 +12,11 @@ parent_dir = os.path.dirname(current_dir)
 # Add the parent directory to sys.path
 sys.path.insert(0, parent_dir)
 
-# API_ENABLED = os.environ.get("API_ENABLED", "False").lower() == "true"
-
 environment = os.getenv("AWS_ENV", "dev")
 
 
-def fetch_secret(secret_name, region_name, env_file_path):
+def fetch_secret(secret_name:str, region_name:str, env_file_path:str):
+    """Fetch the secret from AWS Secrets Manager and write it to the .env file."""
     print("Initializing session")
     session = boto3.session.Session()
     print("Session initialized")
@@ -28,20 +27,19 @@ def fetch_secret(secret_name, region_name, env_file_path):
         response = client.get_secret_value(SecretId=secret_name)
     except Exception as e:
         print(f"Error retrieving secret: {e}")
-        return None
+        return f"Error retrieving secret: {e}"
 
     if "SecretString" in response:
         secret = response["SecretString"]
     else:
         secret = response["SecretBinary"]
 
+    with open(env_file_path, "w") as env_file:
+        env_file.write(secret)
+        print("Secrets are added to the .env file.")
+
     if os.path.exists(env_file_path):
         print(f"The .env file is located at: {env_file_path}")
-
-        with open(env_file_path, "w") as env_file:
-            env_file.write(secret)
-            print("Secrets are added to the .env file.")
-
         load_dotenv()
         print("The .env file is loaded.")
     else:
diff --git a/cognitive_architecture/utils.py b/cognitive_architecture/utils.py
index a5335e884..80654059c 100644
--- a/cognitive_architecture/utils.py
+++ b/cognitive_architecture/utils.py
@@ -1,3 +1,5 @@
+""" This module contains utility functions for the cognitive architecture. """
+
 import os
 import random
 import string
@@ -13,7 +15,13 @@ from cognitive_architecture.database.relationaldb.models.user import User
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.future import select
 import logging
-
+from cognitive_architecture.database.relationaldb.models.operation import Operation
+from cognitive_architecture.database.relationaldb.database_crud import (
+    session_scope,
+    add_entity,
+    update_entity,
+    fetch_job_id,
+)
 
 class Node:
     def __init__(self, id, description, color):
@@ -72,6 +80,7 @@ def get_document_names(doc_input):
 
 
 def format_dict(d):
+    """ Format a dictionary as a string."""
     # Initialize an empty list to store formatted items
     formatted_items = []
 
@@ -93,6 +102,7 @@ def format_dict(d):
 
 
 def append_uuid_to_variable_names(variable_mapping):
+    """ Append a UUID to the variable names to make them unique."""
     unique_variable_mapping = {}
     for original_name in variable_mapping.values():
         unique_name = f"{original_name}_{uuid.uuid4().hex}"
@@ -102,6 +112,7 @@ def append_uuid_to_variable_names(variable_mapping):
 
 # Update the functions to use the unique variable names
 def create_node_variable_mapping(nodes):
+    """ Create a mapping of node identifiers to unique variable names."""
     mapping = {}
     for node in nodes:
         variable_name = f"{node['category']}{node['id']}".lower()
@@ -110,6 +121,7 @@ def create_node_variable_mapping(nodes):
 
 
 def create_edge_variable_mapping(edges):
+    """ Create a mapping of edge identifiers to unique variable names."""
     mapping = {}
     for edge in edges:
         # Construct a unique identifier for the edge
@@ -124,17 +136,10 @@ def generate_letter_uuid(length=8):
     return "".join(random.choice(letters) for _ in range(length))
 
 
-from cognitive_architecture.database.relationaldb.models.operation import Operation
-from cognitive_architecture.database.relationaldb.database_crud import (
-    session_scope,
-    add_entity,
-    update_entity,
-    fetch_job_id,
-)
-
 
 
 async def get_vectordb_namespace(session: AsyncSession, user_id: str):
+    """ Asynchronously retrieves the latest memory names for a given user."""
     try:
         result = await session.execute(
             select(MemoryModel.memory_name)
@@ -151,6 +156,7 @@ async def get_vectordb_namespace(session: AsyncSession, user_id: str):
 
 
 async def get_vectordb_document_name(session: AsyncSession, user_id: str):
+    """ Asynchronously retrieves the latest memory names for a given user."""
     try:
         result = await session.execute(
             select(DocsModel.doc_name)
@@ -167,6 +173,7 @@ async def get_vectordb_document_name(session: AsyncSession, user_id: str):
 
 
 async def get_model_id_name(session: AsyncSession, id: str):
+    """ Asynchronously retrieves the latest memory names for a given user."""
     try:
         result = await session.execute(
             select(MemoryModel.memory_name)
@@ -236,12 +243,6 @@ async def get_unsumarized_vector_db_namespace(session: AsyncSession, user_id: st
 
     return memory_details, docs
 
-    # except Exception as e:
-    #     # Handle the exception as needed
-    #     print(f"An error occurred: {e}")
-    #     return None
-
-
 async def get_memory_name_by_doc_id(session: AsyncSession, docs_id: str):
     """
     Asynchronously retrieves memory names associated with a specific document ID.