211 lines
10 KiB
YAML
211 lines
10 KiB
YAML
services:
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postgres:
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image: postgres:14-alpine
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restart: always
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# comment out if you want to externally connect DB
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# ports:
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# - 5432:5432
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volumes:
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- ./postgres-data:/var/lib/postgresql/data
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environment:
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- PGDATA=/var/lib/postgresql/data/pgdata
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- POSTGRES_USER=skyvern
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- POSTGRES_PASSWORD=skyvern
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- POSTGRES_DB=skyvern
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U skyvern"]
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interval: 5s
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timeout: 5s
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retries: 5
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skyvern:
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image: public.ecr.aws/skyvern/skyvern:latest
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restart: on-failure
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env_file:
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- .env
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# comment out if you want to externally call skyvern API
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ports:
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- 8000:8000
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- 9222:9222 # for cdp browser forwarding
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volumes:
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- ./artifacts:/data/artifacts
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- ./videos:/data/videos
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- ./har:/data/har
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- ./log:/data/log
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- ./.streamlit:/app/.streamlit
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# Uncomment the following two lines if you want to connect to any local changes
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# - ./skyvern:/app/skyvern
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# - ./alembic:/app/alembic
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environment:
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- DATABASE_STRING=postgresql+psycopg://skyvern:skyvern@postgres:5432/skyvern
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- BROWSER_TYPE=chromium-headful
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- ENABLE_CODE_BLOCK=true
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# - BROWSER_TYPE=cdp-connect
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# Use this command to start Chrome with remote debugging:
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# "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
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# /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
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# - BROWSER_REMOTE_DEBUGGING_URL=http://host.docker.internal:9222/
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# =========================
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# LLM Settings - Recommended to use skyvern CLI, `skyvern init llm` to setup your LLM's
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# =========================
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# OpenAI Support:
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# If you want to use OpenAI as your LLM provider, uncomment the following lines and fill in your OpenAI API key.
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# - ENABLE_OPENAI=true
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# - LLM_KEY=OPENAI_GPT4O
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# - OPENAI_API_KEY=<your_openai_key>
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# Gemini Support:
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# 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.
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# - LLM_KEY=GEMINI
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# - ENABLE_GEMINI=true
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# - GEMINI_API_KEY=YOUR_GEMINI_KEY
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# - LLM_KEY=GEMINI_3.0_FLASH
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# If you want to use other LLM provider, like azure and anthropic:
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# - ENABLE_ANTHROPIC=true
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# - LLM_KEY=ANTHROPIC_CLAUDE3.5_SONNET
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# - ANTHROPIC_API_KEY=<your_anthropic_key>
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# Microsoft Azure OpenAI support:
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# If you'd like to use Microsoft Azure OpenAI as your managed LLM service integration with Skyvern, use the environment variables below.
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# In your Microsoft Azure subscription, you will need to provision the OpenAI service and deploy a model, in order to utilize it.
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# 1. Login to the Azure Portal
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# 2. Create an Azure Resource Group
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# 3. Create an OpenAI resource in the Resource Group (choose a region and pricing tier)
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# 4. From the OpenAI resource's Overview page, open the "Azure AI Foundry" portal (click the "Explore Azure AI Foundry Portal" button)
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# 5. In Azure AI Foundry, click "Shared Resources" --> "Deployments"
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# 6. Click "Deploy Model" --> "Deploy Base Model" --> select a model (specify this model "Deployment Name" value for the AZURE_DEPLOYMENT variable below)
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# - ENABLE_AZURE=true
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# - LLM_KEY=AZURE_OPENAI # Leave this value static, don't change it
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# - AZURE_DEPLOYMENT=<your_azure_deployment> # Use the OpenAI model "Deployment Name" that you deployed, using the steps above
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# - AZURE_API_KEY=<your_azure_api_key> # Copy and paste Key1 or Key2 from the OpenAI resource in Azure Portal
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# - 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/)
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# - 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
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# Amazon Bedrock Support:
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# Amazon Bedrock is a managed service that enables you to invoke LLMs and bill them through your AWS account.
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# To use Amazon Bedrock as the LLM provider for Skyvern, specify the following environment variables.
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# 1. In the AWS IAM console, create a new AWS IAM User (name it whatever you want)
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# 2. Assign the "AmazonBedrockFullAccess" policy to the user
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# 3. Generate an IAM Access Key under the IAM User's Security Credentials tab
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# 4. In the Amazon Bedrock console, go to "Model Access"
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# 5. Click Modify Model Access button
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# 6. Enable "Claude 3.5 Sonnet v2" and save changes
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# - ENABLE_BEDROCK=true
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# - 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.
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# - AWS_REGION=us-west-2 # Replace this with a different AWS region, if you desire
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# - AWS_ACCESS_KEY_ID=FILL_ME_IN_PLEASE
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# - AWS_SECRET_ACCESS_KEY=FILL_ME_IN_PLEASE
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# Ollama Support:
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# Ollama is a local LLM provider that can be used to run models locally on your machine.
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# - LLM_KEY=OLLAMA
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# - ENABLE_OLLAMA=true
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# - OLLAMA_MODEL=qwen2.5:7b-instruct
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# - OLLAMA_SERVER_URL=http://host.docker.internal:11434
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# - OLLAMA_SUPPORTS_VISION=false
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# Open Router Support:
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# - ENABLE_OPENROUTER=true
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# - LLM_KEY=OPENROUTER
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# - OPENROUTER_API_KEY=<your_openrouter_api_key>
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# - OPENROUTER_MODEL=mistralai/mistral-small-3.1-24b-instruct
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# Groq Support:
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# - ENABLE_GROQ=true
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# - LLM_KEY=GROQ
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# - GROQ_API_KEY=<your_groq_api_key>
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# - GROQ_MODEL=llama-3.1-8b-instant
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# Maximum tokens to use: (only set for OpenRouter and Ollama)
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# - LLM_CONFIG_MAX_TOKENS=128000
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# Bitwarden Settings
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# If you are looking to integrate Skyvern with a password manager (eg Bitwarden), you can use the following environment variables.
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# - BITWARDEN_SERVER=http://localhost # OPTIONAL IF YOU ARE SELF HOSTING BITWARDEN
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# - BITWARDEN_SERVER_PORT=8002 # IF YOU ARE SELF HOSTING BITWARDEN AND USE THIS COMPOSE FILE, PORT IS 8002 UNLESS CHANGED
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# - SKYVERN_AUTH_BITWARDEN_ORGANIZATION_ID=your-org-id-here
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# - SKYVERN_AUTH_BITWARDEN_CLIENT_ID=user.your-client-id-here
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# - SKYVERN_AUTH_BITWARDEN_CLIENT_SECRET=your-client-secret-here
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# - SKYVERN_AUTH_BITWARDEN_MASTER_PASSWORD=your-master-password-here
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# 1Password Integration
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# If you are looking to integrate Skyvern with 1Password, you can use the following environment variables.
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# OP_SERVICE_ACCOUNT_TOKEN=""
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depends_on:
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postgres:
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condition: service_healthy
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healthcheck:
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test: ["CMD", "test", "-f", "/app/.streamlit/secrets.toml"]
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interval: 5s
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timeout: 5s
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retries: 5
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skyvern-ui:
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image: public.ecr.aws/skyvern/skyvern-ui:latest
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restart: on-failure
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ports:
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- 8080:8080
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- 9090:9090
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volumes:
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- ./artifacts:/data/artifacts
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- ./videos:/data/videos
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- ./har:/data/har
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- ./.streamlit:/app/.streamlit
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env_file:
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- skyvern-frontend/.env
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environment: {}
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# - VITE_ENABLE_CODE_BLOCK=true
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# if you want to run skyvern on a remote server,
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# you need to change the host in VITE_WSS_BASE_URL and VITE_API_BASE_URL to match your server ip
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# If you're self-hosting this behind a dns, you'll want to set:
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# A route for the API: api.yourdomain.com -> localhost:8000
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# A route for the UI: yourdomain.com -> localhost:8080
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# A route for the artifact API: artifact.yourdomain.com -> localhost:9090 (maybe not needed)
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# - VITE_WSS_BASE_URL=ws://localhost:8000/api/v1
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# - VITE_ARTIFACT_API_BASE_URL=http://localhost:9090
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# - VITE_API_BASE_URL=http://localhost:8000/api/v1
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# - VITE_SKYVERN_API_KEY=<get this from "settings" in the Skyvern UI>
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depends_on:
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skyvern:
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condition: service_healthy
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# uncomment for local usage of `vaultwarden` & bitwarden-cli - see more at: https://github.com/dani-garcia/vaultwarden
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# First this container needs to be started and configured to sign up, create master password and organization
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# Once created, under SETTINGS/SECURITY/KEYS/API you should be able to get client id and secret for CLI & Skyvern integrations
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# vaultwarden:
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# image: vaultwarden/server:latest-alpine
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# container_name: vaultwarden
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# restart: unless-stopped
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# environment:
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# # 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
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# SIGNUPS_ALLOWED: "true" # Deactivate this with "false" after you have created your account so that no strangers can register
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# volumes:
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# - ~/vw-data/:/data/ # the path before the : can be changed
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# ports:
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# - 127.0.0.1:11002:80 # you can replace the 11002 with your preferred port
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# Bitwarden CLI Server (provides REST API endpoints for Skyvern)
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# 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
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# bitwarden-cli:
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# build:
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# context: ./bitwarden-cli-server
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# dockerfile: Dockerfile
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# environment:
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# # Vaultwarden server URL
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# BW_HOST: "http://vaultwarden"
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# # API credentials for vaultwarden
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# BW_CLIENTID: "user.your-client-id-here"
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# BW_CLIENTSECRET: "your-client-secret-here"
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# # Master password for unlocking vault
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# BW_PASSWORD: "your-master-password-here"
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# ports:
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# # Bind to localhost only for security
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# - "127.0.0.1:8002:8087"
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# restart: unless-stopped
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# healthcheck:
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# test: [ "CMD", "curl", "-f", "http://localhost:8087/status" ]
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# interval: 30s
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# timeout: 10s
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# retries: 5
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# start_period: 30s
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# depends_on:
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# vaultwarden:
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# condition: service_healthy
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# volumes:
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# # Optional: persist Bitwarden CLI config
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# - ~/bitwarden-cli-config:/app/.config
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# labels:
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# - "traefik.enable=false" # Don't expose via reverse proxy
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