cf-ai-agent.yml

name: Build and Push Docker Image to AWS ECR

on:
  push:
    branches:
      - main
    paths:
      - '.github/workflows/cf-ai-agent.yml'
      - 'dodao-ai-agents/crowd-fund-analysis/**'

jobs:
  build-and-push:
    name: Build and Push Docker Image
    runs-on: ubuntu-latest
    env:
      NODE_OPTIONS: --max-old-space-size=8182
      AWS_REGION: us-east-1 # Change this to the AWS region where your ECR repository is located
      ECR_REPOSITORY: crowd-fund-analysis # Replace this with your ECR repository name

    steps:
      - name: Checkout Repository
        uses: actions/checkout@v3

      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v1
        with:
          aws-access-key-id: ${{ secrets.AI_AGENT_AWS_ACCESS_KEY_ID }}
          aws-secret-access-key: ${{ secrets.AI_AGENT_AWS_SECRET_ACCESS_KEY }}
          aws-region: us-east-1

      - name: Login to Amazon ECR
        id: login-ecr
        uses: aws-actions/amazon-ecr-login@v1

      - name: Get Git Commit Info
        working-directory: dodao-ai-agents/crowd-fund-analysis
        run: |
          echo "Writing Git commit info to file..."
          GIT_COMMIT_HASH=$(git rev-parse HEAD)
          GIT_COMMIT_MESSAGE=$(git log -1 --pretty=%B)
          echo "COMMIT_HASH=${GIT_COMMIT_HASH}" > cf_analysis_agent/commit_info.txt
          echo "COMMIT_MESSAGE=${GIT_COMMIT_MESSAGE}" >> cf_analysis_agent/commit_info.txt

      - name: Build Docker Image
        working-directory: dodao-ai-agents/crowd-fund-analysis
        run: |
          IMAGE_TAG=${{ github.sha }}
          docker build -t ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:$IMAGE_TAG .

      - name: Tag Docker Image
        working-directory: dodao-ai-agents/crowd-fund-analysis
        run: |
          IMAGE_TAG=${{ github.sha }}
          docker tag ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:$IMAGE_TAG ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:latest

      - name: Push Docker Image
        working-directory: dodao-ai-agents/crowd-fund-analysis
        run: |
          IMAGE_TAG=${{ github.sha }}
          docker push ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:$IMAGE_TAG
          docker push ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:latest
      - name: Deploy to Lightsail Container Service
        run: |
          aws lightsail create-container-service-deployment \
            --service-name cf-analysis-service \
            --containers '{
              "cf-analysis-container": {
                "image": "729763663166.dkr.ecr.us-east-1.amazonaws.com/crowd-fund-analysis:latest",
                "ports": {
                  "5000": "HTTP"
                },
                "environment": {
                  "OPENAI_API_KEY": "${{ secrets.AI_AGENT_OPENAI_API_KEY }}",
                  "SCRAPINGANT_API_KEY": "${{ secrets.AI_AGENT_SCRAPINGANT_API_KEY }}",
                  "SERPER_API_KEY": "${{ secrets.AI_AGENT_SERPER_API_KEY }}",
                  "SCRAPIN_API_KEY": "${{ secrets.AI_AGENT_SCRAPIN_API_KEY }}",
                  "GOOGLE_CSE_ID": "${{ secrets.AI_AGENT_GOOGLE_CSE_ID }}",
                  "GOOGLE_API_KEY": "${{ secrets.AI_AGENT_GOOGLE_API_KEY }}",
                  "AWS_ACCESS_KEY_ID": "${{ secrets.AI_AGENT_AWS_ACCESS_KEY_ID }}",
                  "AWS_SECRET_ACCESS_KEY": "${{ secrets.AI_AGENT_AWS_SECRET_ACCESS_KEY }}",
                  "S3_BUCKET_NAME": "dodao-ai-insights-agent",
                  "AWS_DEFAULT_REGION": "us-east-1"
                }
              }
            }' \
            --public-endpoint '{"containerName":"cf-analysis-container","containerPort":5000}'
    

      - name: Check Deployment Status
        id: check-status
        run: |
          until [[ $(aws lightsail get-container-services --service-name cf-analysis-service --query "containerServices[0].state" --output text) == "RUNNING" ]]; do
            echo "Waiting for deployment to complete..."
            sleep 15
          done
          echo "Deployment completed successfully."