Update index.mdx

Author: fpagny

tutorials/how-to-implement-rag-generativeapis/index.mdx

@@ -34,7 +34,7 @@ In this tutorial, you will learn how to implement RAG using LangChain, a leading
 
 ### Install required packages
 
-1. Run the following command to install the required Python packages:
+Run the following command to install the required Python packages:
 
    ```sh
    pip install langchain langchainhub langchain_openai langchain_community langchain_postgres unstructured "unstructured[pdf]" libmagic python-dotenv psycopg2 boto3
@@ -48,7 +48,7 @@ In this tutorial, you will learn how to implement RAG using LangChain, a leading
 
 ### Create a .env file
 
-2. Create a `.env` file and add the following variables. These will store your API keys, database connection details, and other configuration values.
+Create a `.env` file and add the following variables. These will store your API keys, database connection details, and other configuration values.
 
    ```sh
    # .env file
@@ -69,8 +69,8 @@ In this tutorial, you will learn how to implement RAG using LangChain, a leading
    # Scaleway Object Storage bucket configuration
    ## Will be used to store your proprietary data (PDF, CSV etc)
    SCW_BUCKET_NAME=your_scaleway_bucket_name
-   SCW_REGION=fr-par
-   SCW_BUCKET_ENDPOINT="https://s3.{{SCW_REGION}}.scw.cloud" # Object Storage main endpoint, e.g., https://s3.fr-par.scw.cloud
+   SCW_REGION=fr-par # Region where your bucket is located
+   SCW_BUCKET_ENDPOINT="https://s3.fr-par.scw.cloud" # Object Storage main endpoint, e.g., https://s3.fr-par.scw.cloud for fr-par region
 
    # Scaleway Generative APIs endpoint
    ## LLM and Embedding model are served through this base URL