services:
  postgres:
    image: postgres:14-alpine
    restart: always
    # comment out if you want to externally connect DB
    # ports:
    #   - 5432:5432
    volumes:
      - ./postgres-data:/var/lib/postgresql/data
    environment:
      - PGDATA=/var/lib/postgresql/data/pgdata
      - POSTGRES_USER=skyvern
      - POSTGRES_PASSWORD=skyvern
      - POSTGRES_DB=skyvern
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U skyvern"]
      interval: 5s
      timeout: 5s
      retries: 5
  skyvern:
    image: public.ecr.aws/skyvern/skyvern:latest
    restart: on-failure
    env_file:
      - .env
    # comment out if you want to externally call skyvern API
    ports:
      - 8000:8000
      - 9222:9222 # for cdp browser forwarding
    volumes:
      - ./artifacts:/data/artifacts
      - ./videos:/data/videos
      - ./har:/data/har
      - ./log:/data/log
      - ./.streamlit:/app/.streamlit
      # Uncomment the following two lines if you want to connect to any local changes
      # - ./skyvern:/app/skyvern
      # - ./alembic:/app/alembic
    environment:
      - DATABASE_STRING=postgresql+psycopg://skyvern:skyvern@postgres:5432/skyvern
      - BROWSER_TYPE=chromium-headful
      - ENABLE_CODE_BLOCK=true
      # - BROWSER_TYPE=cdp-connect
      # Use this command to start Chrome with remote debugging:
      # "C:\Program Files\Google\Chrome\Application\chrome.exe" --remote-debugging-port=9222 --user-data-dir="C:\chrome-cdp-profile" --no-first-run --no-default-browser-check
      # /Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome --remote-debugging-port=9222 --user-data-dir="/Users/yourusername/chrome-cdp-profile" --no-first-run --no-default-browser-check
      # - BROWSER_REMOTE_DEBUGGING_URL=http://host.docker.internal:9222/
    # =========================
    #       LLM Settings - Recommended to use skyvern CLI, `skyvern init llm` to setup your LLM's
    # =========================
    # OpenAI Support:
    # If you want to use OpenAI as your LLM provider, uncomment the following lines and fill in your OpenAI API key.
    # - ENABLE_OPENAI=true
    # - LLM_KEY=OPENAI_GPT4O
    # - OPENAI_API_KEY=<your_openai_key>
    #  Gemini Support:
    # Gemini is a new LLM provider that is currently in beta. You can use it by uncommenting the following lines and filling in your Gemini API key.
    # - LLM_KEY=GEMINI
    # - ENABLE_GEMINI=true
    # - GEMINI_API_KEY=YOUR_GEMINI_KEY
    # - LLM_KEY=GEMINI_2.5_PRO_PREVIEW_03_25
    # If you want to use other LLM provider, like azure and anthropic:
    # - ENABLE_ANTHROPIC=true
    # - LLM_KEY=ANTHROPIC_CLAUDE3.5_SONNET
    # - ANTHROPIC_API_KEY=<your_anthropic_key>
    # Microsoft Azure OpenAI support:
    # If you'd like to use Microsoft Azure OpenAI as your managed LLM service integration with Skyvern, use the environment variables below.
    # In your Microsoft Azure subscription, you will need to provision the OpenAI service and deploy a model, in order to utilize it.
    # 1. Login to the Azure Portal
    # 2. Create an Azure Resource Group
    # 3. Create an OpenAI resource in the Resource Group (choose a region and pricing tier)
    # 4. From the OpenAI resource's Overview page, open the "Azure AI Foundry" portal (click the "Explore Azure AI Foundry Portal" button)
    # 5. In Azure AI Foundry, click "Shared Resources" --> "Deployments"
    # 6. Click "Deploy Model" --> "Deploy Base Model" --> select a model (specify this model "Deployment Name" value for the AZURE_DEPLOYMENT variable below)
    # - ENABLE_AZURE=true
    # - LLM_KEY=AZURE_OPENAI                          # Leave this value static, don't change it
    # - AZURE_DEPLOYMENT=<your_azure_deployment>      # Use the OpenAI model "Deployment Name" that you deployed, using the steps above
    # - AZURE_API_KEY=<your_azure_api_key>            # Copy and paste Key1 or Key2 from the OpenAI resource in Azure Portal
    # - AZURE_API_BASE=<your_azure_api_base>          # Copy and paste the "Endpoint" from the OpenAI resource in Azure Portal (eg. https://xyzxyzxyz.openai.azure.com/)
    # - AZURE_API_VERSION=<your_azure_api_version>    # Specify a valid Azure OpenAI data-plane API version (eg. 2024-08-01-preview) Docs: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference
    # Amazon Bedrock Support:
    # Amazon Bedrock is a managed service that enables you to invoke LLMs and bill them through your AWS account.
    # To use Amazon Bedrock as the LLM provider for Skyvern, specify the following environment variables.
    # 1. In the AWS IAM console, create a new AWS IAM User (name it whatever you want)
    # 2. Assign the "AmazonBedrockFullAccess" policy to the user
    # 3. Generate an IAM Access Key under the IAM User's Security Credentials tab
    # 4. In the Amazon Bedrock console, go to "Model Access"
    # 5. Click Modify Model Access button
    # 6. Enable "Claude 3.5 Sonnet v2" and save changes
    # - ENABLE_BEDROCK=true
    # - LLM_KEY=BEDROCK_ANTHROPIC_CLAUDE3.5_SONNET   # This is the Claude 3.5 Sonnet "V2" model. Change to BEDROCK_ANTHROPIC_CLAUDE3.5_SONNET_V1 for the non-v2 version.
    # - AWS_REGION=us-west-2                         # Replace this with a different AWS region, if you desire
    # - AWS_ACCESS_KEY_ID=FILL_ME_IN_PLEASE
    # - AWS_SECRET_ACCESS_KEY=FILL_ME_IN_PLEASE
    # Ollama Support:
    # Ollama is a local LLM provider that can be used to run models locally on your machine.
    # - LLM_KEY=OLLAMA
    # - ENABLE_OLLAMA=true
    # - OLLAMA_MODEL=qwen2.5:7b-instruct
    # - OLLAMA_SERVER_URL=http://host.docker.internal:11434
    # - OLLAMA_SUPPORTS_VISION=false
    # Open Router Support:
    # - ENABLE_OPENROUTER=true
    # - LLM_KEY=OPENROUTER
    # - OPENROUTER_API_KEY=<your_openrouter_api_key>
    # - OPENROUTER_MODEL=mistralai/mistral-small-3.1-24b-instruct
    # Groq Support:
    # - ENABLE_GROQ=true
    # - LLM_KEY=GROQ
    # - GROQ_API_KEY=<your_groq_api_key>
    # - GROQ_MODEL=llama-3.1-8b-instant

    # Maximum tokens to use: (only set for OpenRouter and Ollama)
    # - LLM_CONFIG_MAX_TOKENS=128000

    # Bitwarden Settings
    # If you are looking to integrate Skyvern with a password manager (eg Bitwarden), you can use the following environment variables.
    # - BITWARDEN_SERVER=http://localhost  # OPTIONAL IF YOU ARE SELF HOSTING BITWARDEN
    # - BITWARDEN_SERVER_PORT=8002 # IF YOU ARE SELF HOSTING BITWARDEN AND USE THIS COMPOSE FILE, PORT IS 8002 UNLESS CHANGED
    # - SKYVERN_AUTH_BITWARDEN_ORGANIZATION_ID=your-org-id-here
    # - SKYVERN_AUTH_BITWARDEN_CLIENT_ID=user.your-client-id-here
    # - SKYVERN_AUTH_BITWARDEN_CLIENT_SECRET=your-client-secret-here
    # - SKYVERN_AUTH_BITWARDEN_MASTER_PASSWORD=your-master-password-here

    # 1Password Integration
    # If you are looking to integrate Skyvern with 1Password, you can use the following environment variables.
    # OP_SERVICE_ACCOUNT_TOKEN=""
    depends_on:
      postgres:
        condition: service_healthy
    healthcheck:
      test: ["CMD", "test", "-f", "/app/.streamlit/secrets.toml"]
      interval: 5s
      timeout: 5s
      retries: 5
  skyvern-ui:
    image: public.ecr.aws/skyvern/skyvern-ui:latest
    restart: on-failure
    ports:
      - 8080:8080
      - 9090:9090
    volumes:
      - ./artifacts:/data/artifacts
      - ./videos:/data/videos
      - ./har:/data/har
      - ./.streamlit:/app/.streamlit
    env_file:
      - skyvern-frontend/.env
    environment: {}
    #  - VITE_ENABLE_CODE_BLOCK=true
    # if you want to run skyvern on a remote server,
    # you need to change the host in VITE_WSS_BASE_URL and VITE_API_BASE_URL to match your server ip
    # If you're self-hosting this behind a dns, you'll want to set:
    #   A route for the API: api.yourdomain.com -> localhost:8000
    #   A route for the UI: yourdomain.com -> localhost:8080
    #   A route for the artifact API: artifact.yourdomain.com -> localhost:9090 (maybe not needed)
    # - VITE_WSS_BASE_URL=ws://localhost:8000/api/v1
    #   - VITE_ARTIFACT_API_BASE_URL=http://localhost:9090
    #   - VITE_API_BASE_URL=http://localhost:8000/api/v1
    #   - VITE_SKYVERN_API_KEY=<get this from "settings" in the Skyvern UI>
    depends_on:
      skyvern:
        condition: service_healthy

# uncomment for local usage of `vaultwarden` & bitwarden-cli - see more at: https://github.com/dani-garcia/vaultwarden
# First this container needs to be started and configured to sign up, create master password and organization
# Once created, under SETTINGS/SECURITY/KEYS/API you should be able to get client id and secret for CLI & Skyvern integrations
#  vaultwarden:
#    image: vaultwarden/server:latest-alpine
#    container_name: vaultwarden
#    restart: unless-stopped
#    environment:
#      # DOMAIN: "https://vaultwarden.example.com"  # required when using a reverse proxy; your domain; vaultwarden needs to know it's https to work properly with attachments
#      SIGNUPS_ALLOWED: "true" # Deactivate this with "false" after you have created your account so that no strangers can register
#    volumes:
#      - ~/vw-data/:/data/ # the path before the : can be changed
#    ports:
#      - 127.0.0.1:11002:80 # you can replace the 11002 with your preferred port

# Bitwarden CLI Server (provides REST API endpoints for Skyvern)
# Once you have master password and api credentials, you can set them below and this CLI should start providing secure access for Skyvern to Vaultwarden
#  bitwarden-cli:
#    build:
#      context: ./bitwarden-cli-server
#      dockerfile: Dockerfile
#    environment:
#      # Vaultwarden server URL
#      BW_HOST: "http://vaultwarden"
#      # API credentials for vaultwarden
#      BW_CLIENTID: "user.your-client-id-here"
#      BW_CLIENTSECRET: "your-client-secret-here"
#      # Master password for unlocking vault
#      BW_PASSWORD: "your-master-password-here"
#    ports:
#      # Bind to localhost only for security
#      - "127.0.0.1:8002:8087"
#    restart: unless-stopped
#    healthcheck:
#      test: [ "CMD", "curl", "-f", "http://localhost:8087/status" ]
#      interval: 30s
#      timeout: 10s
#      retries: 5
#      start_period: 30s
#    depends_on:
#      vaultwarden:
#        condition: service_healthy
#    volumes:
#      # Optional: persist Bitwarden CLI config
#      - ~/bitwarden-cli-config:/app/.config
#    labels:
#      - "traefik.enable=false"  # Don't expose via reverse proxy