add cloud run commands

README.md

@@ -29,9 +29,101 @@ To run web server from command line:
 cargo run -- --minchar 200 --maxchar 500 --input-files nah --dir /data/inputs -o /data -w
 ```
 
+To build Docker image:
+```
+docker build . -t <image-name> -f Dockerfile
+```
+
 To run web server in Docker:
 
 ```
 docker run -v /home/user777/code/rust/text-splitter/tests:/data <image-name> /target/release/text-splitter --minchar 200 --maxchar 500 --input-files nah --dir /data/inputs -o /data -w
 ```
 
+Follow these steps to deploy this service to GCP cloud run:
+
+- Create project for our Cloud Run deployment, or reuse an existing one.
+- Create Cloud Storage bucket named text-splitter-data.
+- Install gcloud tool, run ```gcloud init```. 
+
+Run this in command line:
+```
+PROJECT=$(gcloud config get-value project)
+```
+This will set PROJECT environment variable for our GCP project.
+We can also set LOCATION environment variable for our GCP project:
+```
+LOCATION=<type your location here>
+```
+
+Run this to list available locations sorted by price:
+```
+gcloud compute regions list --format="table(name,location,description,available)" --sort-by price
+```
+
+Then we need to enable Artifact Registry in our project:
+```
+gcloud services enable artifactregistry.googleapis.com
+```
+Now, create repository for your company:
+```
+gcloud artifacts repositories create --location $LOCATION
+--repository-format docker <type-your-company-name>
+```
+Here is an example:
+```
+gcloud artifacts repositories create --location us --repository-format docker  example-company
+```
+
+We can now construct the image URL in another environment variable:
+```
+IMAGE=$LOCATION-docker.pkg.dev/$PROJECT/cloud-run-book/hello
+```
+Finally, you need to build and tag the container image. Make sure you are in the
+directory with the source and run docker build:
+```
+docker build . -t $IMAGE -f Dockerfile
+```
+You now have the container image with the correct URL, but it’s still stored on your local machine (run ```docker images``` to list all local images).
+
+To let Docker push the local image to Artifact Registry, you need to set up credentials:
+```
+gcloud auth configure-docker <location>-docker.pkg.dev
+```
+We can now push the image to Artifact Registry:
+```docker push $IMAGE```
+
+And then we deploy it:
+```
+gcloud run deploy --image $IMAGE --execution-environment gen2 --add-volume=name=data,type=cloud-storage,bucket=text-splitter-data --add-volume-mount=volume=data,mount-path=/data --command /text-splitter --args="-w"
+```
+Then we navigate to GCP console to get the url of our Cloud Run service and save it in the environment variable:
+```
+ENDPOINT = <our-service-url>
+```
+
+By default, Cloud Run is deployed in private mode by default, this means that unauthenticated user, or authenticated user with the role roles/run.invoker, can’t invoke the service (or an another role with the required permissions).
+Therefore, we need to use a project owner account. Follow steps below:
+```
+gcloud auth list
+```
+This will list available accounts for our gcloud command, including project owner account. Then run this command to set active account to project owner:
+```
+gcloud config set account <project_owner_account>
+```
+
+Finally, print the token for project owner account:
+```
+gcloud auth print-identity-token
+```
+Now we can use that token for api calls.
+Before we call our service, we need to upload text files to our bucket.
+Our service will process files in this bucket and save it in output folder.
+
+```
+curl -X POST \
+  $ENDPOINT/api/v1/run \
+  -H 'Content-Type: application/json' \
+  -d '{"list_of_files": ["example--vesting.mdx", "example--gift-card.mdx"]}'
+```
+