Update README.md

Changed the production recommendation - docker first, running gunicorn as alternative

README.md

@@ -252,18 +252,15 @@ client = OpenAI(base_url="http://localhost:8000/v1/my-namespace")
 
 Canopy is using FastAPI as the web framework and Uvicorn as the ASGI server. It is recommended to use Gunicorn as the production server, mainly because it supports multiple worker processes and can handle multiple requests in parallel, more details can be found [here](https://www.uvicorn.org/deployment/#using-a-process-manager).
 
-To run the canopy server for production, please run:
-
-```bash
-gunicorn canopy_server.app:app --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:PORT --workers WORKER_COUNT
-```
-
-Note: replace `PORT` and `WORKER_COUNT` with values.
-
-Alternatively, consider utilizing the Canopy Docker image available on [GitHub Packages](https://github.com/pinecone-io/canopy/pkgs/container/canopy) 
+To use Canopy in production, it is recommended to utilize Canopy's docker image available on [GitHub Packages](https://github.com/pinecone-io/canopy/pkgs/container/canopy) 
 for your production needs. For guidance on deploying Canopy on the Google Cloud Platform (GCP), refer to the example provided in the
 [Deployment to GCP](docs/deployment-gcp.md) documentation.
 
+Alternatively, you can run the canopy server with `gunicorn` WSGI, which is designed for procuction.  
+Set your desired `PORT` and `WORKER_COUNT` envrionment variables, and start the server with:
+```bash
+gunicorn canopy_server.app:app --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:$PORT --workers $WORKER_COUNT
+```
 
 > [!IMPORTANT]
 >  The server interacts with services like Pinecone and OpenAI using your own authentication credentials.