configure dev env part

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

@@ -2,6 +2,11 @@
 meta:
    title: How to implement RAG with managed inference
    description:
+content:
+    h1: How to implement RAG with managed inference
+tags: inference managed postgresql pgvector object storage
+categories:
+    - inference
 ---
 
 RAG (Retrieval-Augmented Generation) is a powerful approach for enhancing a model's knowledge by leveraging your own dataset.
@@ -14,4 +19,42 @@ By utilizing our managed inference services, managed databases, and object stora
 - [Inference Deployment](/ai-data/managed-inference/how-to/create-deployment/): Set up an inference deployment using [sentence-transformers/sentence-t5-xxl](/ai-data/managed-inference/reference-content/sentence-t5-xxl/) on an L4 instance to efficiently process embeddings.
 - [Inference Deployment](/ai-data/managed-inference/how-to/create-deployment/) with the model of your choice.
 - [Object Storage Bucket](/storage/object/how-to/create-a-bucket/) to store all the data you want to inject into your LLM model.
-- [Managed Database](/managed-databases/postgresql-and-mysql/how-to/create-a-database/) to securely store all your embeddings.
+- [Managed Database](/managed-databases/postgresql-and-mysql/how-to/create-a-database/) to securely store all your embeddings.
+
+## Configure your developement environnement
+1. Install necessary packages: run the following command to install the required packages:
+   ```sh
+   pip install langchain psycopg2 python-dotenv scaleway
+   ```
+2. Configure your environnement variables: 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
+
+  # Scaleway API credentials
+  SCW_ACCESS_KEY=your_scaleway_access_key
+  SCW_SECRET_KEY=your_scaleway_secret_key
+  SCW_API_KEY=your_scaleway_api_key
+
+  # Scaleway project and region
+  SCW_DEFAULT_PROJECT_ID=your_scaleway_project_id
+  SCW_DEFAULT_REGION=your_scaleway_region
+
+  # Scaleway managed database (PostgreSQL) credentials
+  SCW_DB_NAME=your_scaleway_managed_db_name
+  SCW_DB_USER=your_scaleway_managed_db_username
+  SCW_DB_PASSWORD=your_scaleway_managed_db_password
+  SCW_DB_HOST=your_scaleway_managed_db_host  # The IP address of your database instance
+  SCW_DB_PORT=your_scaleway_managed_db_port  # The port number for your database instance
+
+  # Scaleway S3 bucket configuration
+  SCW_BUCKET_NAME=your_scaleway_bucket_name
+  SCW_BUCKET_ENDPOINT=your_scaleway_bucket_endpoint  # S3 endpoint, e.g., https://s3.fr-par.scw.cloud
+
+  # Scaleway Inference API configuration (Embeddings)
+  SCW_INFERENCE_EMBEDDINGS_ENDPOINT=your_scaleway_inference_embeddings_endpoint  # Endpoint for sentence-transformers/sentence-t5-xxl deployment
+  SCW_INFERENCE_API_KEY_EMBEDDINGS=your_scaleway_api_key_for_embeddings
+
+  # Scaleway Inference API configuration (LLM deployment)
+  SCW_INFERENCE_DEPLOYMENT_ENDPOINT=your_scaleway_inference_endpoint  # Endpoint for your LLM deployment
+  SCW_INFERENCE_API_KEY=your_scaleway_api_key_for_inference_deployment
+ ```