Prepare AWS deployment (#8)

.dockerignore

@@ -1 +1,3 @@
-secrets
+secrets
+secrets.json
+.vscode

.github/workflows/github_cd.yaml

@@ -1,6 +1,7 @@
-name: Upload Python Package
+name: Continuous Deployment Workflow
 
 on:
+  workflow_dispatch:
   release:
     types: [published]
 
@@ -28,6 +29,7 @@ jobs:
       with:
         name: release-dists
         path: dist/
+
   pypi-publish:
     runs-on: ubuntu-latest
     needs:
@@ -45,3 +47,57 @@ jobs:
           path: dist/
       - name: Publish release distributions to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
+        continue-on-error: true
+
+  upload-docker-images:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - name: Build Docker images
+      run: |
+        # Define public ECR repository URL
+        PUBLIC_ECR_URL=public.ecr.aws/e7b5q5z5/nam685
+        # LangGraph API server
+        docker build -t chatbot -f src/chatbot/Dockerfile .
+        docker tag chatbot:latest $PUBLIC_ECR_URL/chatbot:${{ github.sha }}
+        # API
+        docker build -t chatbot-api -f api/Dockerfile .
+        docker tag chatbot-api:latest $PUBLIC_ECR_URL/chatbot-api:${{ github.sha }}
+        # UI
+        docker build -t chatbot-ui -f ui/Dockerfile ./ui
+        docker tag chatbot-ui:latest $PUBLIC_ECR_URL/chatbot-ui:${{ github.sha }}
+    - name: Configure AWS credentials
+      uses: aws-actions/configure-aws-credentials@v4.1.0
+      with:
+        aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+        aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+        aws-region: ${{ secrets.AWS_REGION }}
+    - name: Log in to Amazon ECR
+      run: |
+        aws ecr-public get-login-password --region us-east-1 | \
+        docker login --username AWS --password-stdin public.ecr.aws
+    - name: Push Docker images to ECR
+      run: |
+        PUBLIC_ECR_URL=public.ecr.aws/e7b5q5z5/nam685
+        docker push $PUBLIC_ECR_URL/chatbot:${{ github.sha }}
+        docker push $PUBLIC_ECR_URL/chatbot-api:${{ github.sha }}
+        docker push $PUBLIC_ECR_URL/chatbot-ui:${{ github.sha }}
+
+  deploy-ecs-by-cloudformation:
+    runs-on: ubuntu-latest
+    needs:
+      - upload-docker-images
+    steps:
+    - uses: actions/checkout@v4
+    - name: Configure AWS credentials
+      uses: aws-actions/configure-aws-credentials@v4.1.0
+      with:
+        aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+        aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+        aws-region: ${{ secrets.AWS_REGION }}
+    - name: Deploy CloudFormation stack
+      uses: aws-actions/aws-cloudformation-github-deploy@v1
+      with:
+        name: chatbot-ecs
+        template: ecs-infrastructure.yaml
+        parameter-overrides: "GitCommitHash=${{ github.sha }}"

.gitignore

@@ -8,4 +8,5 @@ __pycache__/
 .ruff_cache
 .langgraph_api
 dist
-ui/node_modules
+ui/node_modules
+secrets.json

README.md

@@ -13,9 +13,12 @@ Agent architecture: use 2 chat models for separation of concern
 - Helper model to classify if conversation is sensitive or not
 - Main model equiped with tools
 
-Added minimal unit tests
+I also made FastAPI backend and NextJS frontend to interact with chatbot
+Deploy chatbot as standalone container via LangGraph Platform
 
-Prepared for deployment as standalone container via LangGraph Platform
+Deploy to AWS ECS as separate services
+Current deployment's URL: http://chatbot-alb-468353364.eu-central-1.elb.amazonaws.com/
+(I don't keep this URL if I take it down, because I don't pay money for a fixed one))
 
 [![PyPI - Version](https://img.shields.io/pypi/v/chatbot.svg)](https://pypi.org/project/chatbot)
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/chatbot.svg)](https://pypi.org/project/chatbot)

api/Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.12
+FROM python:3.12-alpine
 
 WORKDIR /code
 COPY ./pyproject.toml /code/pyproject.toml

api/healthcheck.py

@@ -0,0 +1,20 @@
+import os
+import urllib.request
+
+
+def health_check():
+    port = os.getenv("CONTAINER_PORT", "8080")
+    url = f"http://localhost:{port}/health"
+    try:
+        with urllib.request.urlopen(url) as response:
+            status_code = response.getcode()
+            body = response.read().decode()
+            print(f"Status code: {status_code}")
+            print(f"Response body: {body}")
+    except Exception as e:
+        print(f"Health check failed: {e}")
+        exit(1)
+
+
+if __name__ == "__main__":
+    health_check()

api/main.py

@@ -1,22 +1,6 @@
 from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
 
 from .routers import router
 
 app = FastAPI()
-
-origins = [
-    "http://127.0.0.1:3000",
-    "http://localhost:3000",
-    "http://ui:3000",
-]
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=origins,
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
 app.include_router(router)

api/routers.py

@@ -1,12 +1,18 @@
+import os
 from typing import Any
 
 from fastapi import APIRouter
 from langgraph_sdk import get_client
 
 from .models import ChatMessage, HumanReview, Thread
 
+langgraph_api_uri = os.getenv("LANGGRAPH_API_URI")
+if not langgraph_api_uri:
+    raise ValueError("LANGGRAPH_API_URI environment variable is not set")
+print(f"LANGGRAPH_API_URI: {langgraph_api_uri}")
+
 router = APIRouter()
-langgraph_client = get_client(url="http://langgraph-api:8000")
+langgraph_client = get_client(url=langgraph_api_uri)
 
 
 def parse_ai_response(
@@ -34,6 +40,11 @@ async def read_main() -> dict:
     return {"msg": "Hello! Welcome to the LangGraph Chat API"}
 
 
+@router.get("/health")
+async def health_check() -> dict:
+    return {"status": "ok"}
+
+
 @router.get("/chat")
 async def list_chat_threads() -> list[Thread]:
     threads_data = await langgraph_client.threads.search(

api/test_main.py

@@ -1,5 +1,9 @@
+import os
+
 from fastapi.testclient import TestClient
 
+os.environ["LANGGRAPH_API_URI"] = "http://localhost:8000"
+
 from .main import app
 
 client = TestClient(app)

app.py

@@ -1,3 +1,5 @@
+# For usage in terminal
+
 from pprint import pprint
 
 from langchain_core.runnables.config import RunnableConfig

compose.yaml

@@ -37,15 +37,45 @@ services:
     env_file:
       - .env
     environment:
+      CONTAINER_PORT: 8000
       REDIS_URI: redis://langgraph-redis:6379
-      POSTGRES_URI: postgres://postgres:postgres@langgraph-postgres:5432/postgres?sslmode=disable
+      DATABASE_URI: postgres://postgres:postgres@langgraph-postgres:5432/postgres?sslmode=disable
+    healthcheck:
+      test: [ "CMD", "python", "src/chatbot/healthcheck.py" ]
+      interval: 10s
+      timeout: 1s
+      retries: 5
+      start_period: 10s
   api:
     image: chatbot-api:latest
     ports:
       - "8080:8080"
+    environment:
+      CONTAINER_PORT: 8080
+      LANGGRAPH_API_URI: http://langgraph-api:8000
+    depends_on:
+      langgraph-api:
+        condition: service_healthy
+    healthcheck:
+      test: [ "CMD", "python", "api/healthcheck.py" ]
+      start_period: 3s
+      timeout: 1s
+      retries: 5
+      interval: 5s
   ui:
     image: chatbot-ui:latest
     ports:
       - "3000:3000"
     environment:
-      - HOSTNAME=0.0.0.0
+      HOSTNAME: 0.0.0.0
+      CONTAINER_PORT: 3000
+      API_URL: http://api:8080
+    depends_on:
+      api:
+        condition: service_healthy
+    healthcheck:
+      test: [ "CMD", "curl", "-f", "http://localhost:3000/health" ]
+      start_period: 3s
+      timeout: 1s
+      retries: 5
+      interval: 5s