diff --git a/README.md b/README.md
index ebd7a7164b03e8db753ed24b1b3629557a4cb23e..e187f0ec3fe68935f8fffcc82fb2c02c0fed776e 100644
--- a/README.md
+++ b/README.md
@@ -41,14 +41,14 @@ After setting up the S3 bucket and Vector Store, we could process PDF files to g
 
 Run: 
 
-`python3 main.py --bucket_name [YourBucketName] --endpoint [YourVectorDBEndpoint] --index_name [Index_name]`
+`python3 main.py --bucket_name [YourBucketName] --endpoint [YourVectorDBEndpoint] --index_name [Index_name] --local_path [local_path]`
 
 Where: 
 
 - **--bucket_name**: The name of the S3 bucket containing the PDF files.
 - **--endpoint**: Endpoint for the vector database.
 - **--index_name**: The index_name where to store the embeddings in the collection.
-- **--local_dir**: 
+- **--local_path**: local_path  
 
 The main.py script will: