Merge pull request #44 from ks6088ts-labs/feature/issue-43_docker-compose

support docker compose

Author: ks6088ts

Makefile

@@ -55,6 +55,7 @@ DOCKER_IMAGE_COMPONENT ?= backend
 DOCKER_COMMAND ?=
 DOCKER_TAG ?= $(DOCKER_IMAGE_COMPONENT)-$(GIT_TAG)
 DOCKER_FILE ?= ./dockerfiles/$(DOCKER_IMAGE_COMPONENT).Dockerfile
+DOCKER_COMPOSE_FILE ?= ./compose.yaml
 
 # Tools
 TOOLS_DIR ?= $(HOME)/.local/bin
@@ -78,6 +79,10 @@ docker-run: ## run Docker container
 docker-lint: ## lint Dockerfile
 	docker run --rm -i hadolint/hadolint < $(DOCKER_FILE)
 
+.PHONY: docker-compose-lint
+docker-compose-lint: ## lint docker compose file
+	docker compose --file $(DOCKER_COMPOSE_FILE) config --quiet
+
 .PHONY: docker-scan
 docker-scan: ## scan Docker image
 	@# https://aquasecurity.github.io/trivy/v0.18.3/installation/#install-script
@@ -88,7 +93,7 @@ docker-scan: ## scan Docker image
 _ci-test-docker: docker-lint docker-build docker-scan docker-run
 
 .PHONY: ci-test-docker
-ci-test-docker: ## run CI test for Docker
+ci-test-docker: docker-compose-lint ## run CI test for Docker
 	$(MAKE) _ci-test-docker DOCKER_IMAGE_COMPONENT=backend
 	$(MAKE) _ci-test-docker DOCKER_IMAGE_COMPONENT=frontend
 

README.md

@@ -47,7 +47,21 @@ make ci-test-docker
 
 ## Deployment instructions
 
-### Docker Hub
+### Docker compose
+
+Docker compose is used to run the services locally.
+Refer to the following steps to run the services.
+See the actual implementation in the [compose.yaml](./compose.yaml) file.
+
+```shell
+# Create environment files for each service
+cp {NAME}.env.sample {NAME}.env
+
+# Build and run the services
+docker compose up
+```
+
+### Push docker image to Docker Hub
 
 To publish the docker image to Docker Hub via GitHub Actions, you need to set the following secrets in the repository.
 
@@ -56,9 +70,17 @@ gh secret set DOCKERHUB_USERNAME --body $DOCKERHUB_USERNAME
 gh secret set DOCKERHUB_TOKEN --body $DOCKERHUB_TOKEN
 ```
 
-### Azure Functions
+### Deploy Azure Functions
+
+To deploy the Azure Functions, run the following script.
 
-To deploy the Azure Functions, you can refer to the following scripts.
+```shell
+# Deploy the Azure Functions
+sh ./scripts/deploy-azure-functions.sh
+
+# Destroy the Azure Functions
+sh ./scripts/destroy-azure-functions.sh
+```
 
 - [scripts/deploy-azure-functions.sh](./scripts/deploy-azure-functions.sh): Deploy the Azure Functions using Azure CLI.
 - [scripts/destroy-azure-functions.sh](./scripts/destroy-azure-functions.sh): Destroy the Azure Functions using Azure CLI.

compose.yaml

@@ -0,0 +1,30 @@
+services:
+  backend:
+    build:
+      context: .
+      dockerfile: dockerfiles/backend.Dockerfile
+    image: ks6088ts/azure-ai-services-solutions:backend-latest
+    command: python main.py backend --port 8888 --debug
+    ports:
+      - 8888:8888
+    volumes:
+      - ./azure_ai_document_intelligence.env:/app/azure_ai_document_intelligence.env
+      - ./azure_ai_vision.env:/app/azure_ai_vision.env
+      - ./azure_event_grid.env:/app/azure_event_grid.env
+      - ./azure_openai.env:/app/azure_openai.env
+      - ./azure_storage_blob.env:/app/azure_storage_blob.env
+      - ./azure_storage_queue.env:/app/azure_storage_queue.env
+    environment:
+      - PYTHONUNBUFFERED=1
+  frontend:
+    build:
+      context: .
+      dockerfile: dockerfiles/frontend.Dockerfile
+    image: ks6088ts/azure-ai-services-solutions:frontend-latest
+    command: streamlit run main.py --server.port=8501 --server.address=0.0.0.0 -- frontend --solution-name sandbox --backend-url http://backend:8888 --debug
+    ports:
+      - 8501:8501
+    volumes:
+      - ./azure_ai_speech.env:/app/azure_ai_speech.env
+    environment:
+      - PYTHONUNBUFFERED=1

docs/README.md

@@ -1,55 +1,12 @@
-# How to run
-
-## Docker
-
-```shell
-# Build the Docker image (optional)
-make docker-build DOCKER_IMAGE_COMPONENT=backend GIT_TAG=latest
-make docker-build DOCKER_IMAGE_COMPONENT=frontend GIT_TAG=latest
-
-# Create environment files for each service
-cp {NAME}.env.sample {NAME}.env
-
-# Run the Docker container for the backend
-docker run --rm \
-	--publish 8888:8888 \
-	--volume ${PWD}/azure_ai_document_intelligence.env:/app/azure_ai_document_intelligence.env \
-	--volume ${PWD}/azure_ai_vision.env:/app/azure_ai_vision.env \
-	--volume ${PWD}/azure_event_grid.env:/app/azure_event_grid.env \
-	--volume ${PWD}/azure_openai.env:/app/azure_openai.env \
-	--volume ${PWD}/azure_storage_blob.env:/app/azure_storage_blob.env \
-	--volume ${PWD}/azure_storage_queue.env:/app/azure_storage_queue.env \
-	ks6088ts/azure-ai-services-solutions:backend-latest \
-	python main.py backend \
-		--port 8888 \
-		--debug
-
-# Access the backend: http://localhost:8888
-
-# Run ngrok to expose the backend (for testing purposes only)
-ngrok http 8888
-NGROK_URL="<forwarding-url>"
-
-# Run the Docker container for the frontend
-docker run --rm \
-	--publish 8501:8501 \
-	--volume ${PWD}/azure_ai_speech.env:/app/azure_ai_speech.env \
-	ks6088ts/azure-ai-services-solutions:frontend-latest \
-	streamlit run main.py --server.port=8501 --server.address=0.0.0.0 -- frontend \
-		--solution-name sandbox \
-		--backend-url ${NGROK_URL} \
-		--debug
-
-# Access the frontend: http://localhost:8501
-```
-
 # References
 
 ## Common
 
 - [Typer](https://typer.tiangolo.com/#installation)
 - [Kiota > Generate tailored Python and PHP API clients for any API with Kiota](https://devblogs.microsoft.com/microsoft365dev/generate-tailored-python-and-php-api-clients-for-any-api-with-kiota/)
 - [How to exclude multiple directories in pre-commit](https://stackoverflow.com/a/75560858)
+- [Docker Compose Quickstart](https://docs.docker.com/compose/gettingstarted/)
+- [Validating docker-compose yml file](https://stackoverflow.com/a/40158753)
 
 ## Backend