Add Docker multi-architecture support and fix Streamlit module imports

.github/workflows/docker-release.yaml

@@ -6,10 +6,12 @@ on:
 jobs:
   release:
     runs-on: "ubuntu-latest"
-    timeout-minutes: 5
+    timeout-minutes: 10
     steps:
       - name: Check out the repo
         uses: actions/checkout@v5
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
       - name: Log in to Docker Hub
         uses: docker/login-action@v3
         with:
@@ -32,6 +34,7 @@ jobs:
         uses: docker/build-push-action@v6
         with:
           context: .
+          platforms: linux/amd64,linux/arm64
           push: true
           build-args: |
             GIT_REVISION=${{ github.sha }}

.github/workflows/ghcr-release.yaml

@@ -8,12 +8,14 @@ env:
 jobs:
   ghcr:
     runs-on: ubuntu-latest
-    timeout-minutes: 5
+    timeout-minutes: 10
     permissions:
       packages: write
       contents: read
     steps:
       - uses: actions/checkout@v5
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
       - uses: docker/login-action@v3
         with:
           registry: ghcr.io
@@ -43,5 +45,6 @@ jobs:
         with:
           push: true
           context: .
+          platforms: linux/amd64,linux/arm64
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}

Dockerfile

@@ -37,4 +37,7 @@ RUN pip install --no-cache-dir --upgrade -r /app/requirements.txt
 # Copy application code after dependencies are installed
 COPY . .
 
+# Set PYTHONPATH to include the working directory for module imports
+ENV PYTHONPATH="${PYTHONPATH}:/app"
+
 CMD ["python", "template_langgraph/core.py"]

Makefile

@@ -76,6 +76,14 @@ docker-build: ## build Docker image
 docker-run: ## run Docker container
 	docker run --rm $(DOCKER_REPO_NAME)/$(DOCKER_IMAGE_NAME):$(GIT_TAG) $(DOCKER_COMMAND)
 
+.PHONY: docker-run-streamlit
+docker-run-streamlit: ## run Docker container with Streamlit app
+	docker run --rm \
+		-p 8501:8501 \
+		-v $(PWD)/.env:/app/.env \
+		$(DOCKER_REPO_NAME)/$(DOCKER_IMAGE_NAME):$(GIT_TAG) \
+		streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+
 .PHONY: docker-lint
 docker-lint: ## lint Dockerfile
 	docker run --rm -i hadolint/hadolint < Dockerfile

docs/index.ja.md

@@ -240,6 +240,58 @@ Streamlit アプリのデモ：
 
 [![streamlit.png](./images/streamlit.png)](https://youtu.be/undxBwyJ3Sc)
 
+### オプション 6: Docker（本番デプロイ）
+
+アプリケーションを Docker で実行すると、環境差による違いを減らし、一貫したデプロイが可能になります。ここではイメージのビルド、Streamlit のコンテナ実行、事前ビルド済みイメージの利用、マルチアーキテクチャ対応について説明します。
+
+#### Docker イメージのビルド
+
+```shell
+# ローカルで Docker イメージをビルド
+make docker-build
+
+# または特定のタグでビルド
+docker build -t ks6088ts/template-langgraph:latest .
+```
+
+#### Streamlit を Docker で実行
+
+```shell
+# Docker で Streamlit アプリを実行する（Makefile ターゲット）
+make docker-run-streamlit
+
+# または .env をコンテナにマウントして手動で実行
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ks6088ts/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+```
+
+#### 事前ビルド済みイメージの使用
+
+```shell
+# Docker Hub から実行
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ks6088ts/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+
+# GitHub Container Registry から実行
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ghcr.io/ks6088ts-labs/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+```
+
+#### マルチアーキテクチャ対応
+
+このリポジトリの Docker イメージは `amd64` と `arm64` 両アーキテクチャ向けにビルドされています。これにより、Intel/AMD の x64 マシンや Apple Silicon（M1/M2/M3/M4）などの ARM 環境でも動作します。
+
+コンテナを起動したら、ブラウザで [http://localhost:8501](http://localhost:8501) にアクセスして Streamlit アプリを確認できます。
+
 ### 追加の実行例
 
 - Issue formatter（構造化出力）:

docs/index.md

@@ -240,6 +240,63 @@ Demonstration of the Streamlit app:
 
 [![streamlit.png](./images/streamlit.png)](https://youtu.be/undxBwyJ3Sc)
 
+### Option 6: Docker (Production deployment)
+
+You can run the application in Docker for consistent deployment across environments:
+
+#### Building the Docker Image
+
+```shell
+# Build the Docker image locally
+make docker-build
+
+# Or build with specific tag
+docker build -t ks6088ts/template-langgraph:latest .
+```
+
+#### Running Streamlit in Docker
+
+```shell
+# Run Streamlit app with Docker
+make docker-run-streamlit
+
+# Or run manually with environment file
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ks6088ts/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+```
+
+#### Using Pre-built Images
+
+You can also use pre-built images from Docker Hub or GitHub Container Registry:
+
+```shell
+# From Docker Hub
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ks6088ts/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+
+# From GitHub Container Registry  
+docker run --rm \
+  -p 8501:8501 \
+  -v ./.env:/app/.env \
+  ghcr.io/ks6088ts-labs/template-langgraph:latest \
+  streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
+```
+
+#### Multi-Architecture Support
+
+The Docker images are built for both `amd64` and `arm64` architectures, making them compatible with:
+- Intel/AMD x64 processors
+- Apple Silicon (M1/M2/M3/M4) processors
+- ARM-based servers
+
+Access the Streamlit app at [http://localhost:8501](http://localhost:8501) after running the container.
+
 ### More agent runs
 
 - Issue formatter (structured output):