@@ -240,6 +240,63 @@ Demonstration of the Streamlit app:
240240
241241[ ![ streamlit.png] ( ./images/streamlit.png )] ( https://youtu.be/undxBwyJ3Sc )
242242
243+ ### Option 6: Docker (Production deployment)
244+
245+ You can run the application in Docker for consistent deployment across environments:
246+
247+ #### Building the Docker Image
248+
249+ ``` shell
250+ # Build the Docker image locally
251+ make docker-build
252+
253+ # Or build with specific tag
254+ docker build -t ks6088ts/template-langgraph:latest .
255+ ```
256+
257+ #### Running Streamlit in Docker
258+
259+ ``` shell
260+ # Run Streamlit app with Docker
261+ make docker-run-streamlit
262+
263+ # Or run manually with environment file
264+ docker run --rm \
265+ -p 8501:8501 \
266+ -v ./.env:/app/.env \
267+ ks6088ts/template-langgraph:latest \
268+ streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
269+ ```
270+
271+ #### Using Pre-built Images
272+
273+ You can also use pre-built images from Docker Hub or GitHub Container Registry:
274+
275+ ``` shell
276+ # From Docker Hub
277+ docker run --rm \
278+ -p 8501:8501 \
279+ -v ./.env:/app/.env \
280+ ks6088ts/template-langgraph:latest \
281+ streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
282+
283+ # From GitHub Container Registry
284+ docker run --rm \
285+ -p 8501:8501 \
286+ -v ./.env:/app/.env \
287+ ghcr.io/ks6088ts-labs/template-langgraph:latest \
288+ streamlit run template_langgraph/services/streamlits/main.py --server.address 0.0.0.0
289+ ```
290+
291+ #### Multi-Architecture Support
292+
293+ The Docker images are built for both ` amd64 ` and ` arm64 ` architectures, making them compatible with:
294+ - Intel/AMD x64 processors
295+ - Apple Silicon (M1/M2/M3/M4) processors
296+ - ARM-based servers
297+
298+ Access the Streamlit app at [ http://localhost:8501 ] ( http://localhost:8501 ) after running the container.
299+
243300### More agent runs
244301
245302- Issue formatter (structured output):
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