🐉 Automate Browser-based workflows using LLMs and Computer Vision 🐉

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a Playwright-compatible SDK that adds AI functionality on top of playwright, as well as a no-code workflow builder to help both technical and non-technical users automate manual workflows on any website, replacing brittle or unreliable automation solutions.

Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed.

Instead of only relying on code-defined XPath interactions, Skyvern relies on Vision LLMs to learn and interact with the websites.

How it works

Skyvern was inspired by the Task-Driven autonomous agent design popularized by BabyAGI and AutoGPT -- with one major bonus: we give Skyvern the ability to interact with websites using browser automation libraries like Playwright.

Skyvern uses a swarm of agents to comprehend a website, and plan and execute its actions:

This approach has a few advantages:

1. Skyvern can operate on websites it's never seen before, as it's able to map visual elements to actions necessary to complete a workflow, without any customized code
2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate
3. Skyvern is able to take a single workflow and apply it to a large number of websites, as it's able to reason through the interactions necessary to complete the workflow A detailed technical report can be found here.

Demo

https://github.com/user-attachments/assets/5cab4668-e8e2-4982-8551-aab05ff73a7f

Quickstart

Skyvern Cloud

Skyvern Cloud is a managed cloud version of Skyvern that allows you to run Skyvern without worrying about the infrastructure. It allows you to run multiple Skyvern instances in parallel and comes bundled with anti-bot detection mechanisms, proxy network, and CAPTCHA solvers.

If you'd like to try it out, navigate to app.skyvern.com and create an account.

Run Locally (UI + Server)

Choose your preferred setup method:

Database default: skyvern quickstart and skyvern run server default to a SQLite database at ~/.skyvern/data.db so the pip path works without Postgres or Docker. To use Postgres instead, pass --postgres for a local container or --database-string for an existing database. Docker Compose always uses the bundled Postgres service.

Option A: pip install (Recommended for Python-managed local setup)

Dependencies needed: - Python 3.11, 3.12, or 3.13

Additionally, for Windows: - Rust - VS Code with C++ dev tools and Windows SDK

1. Install Skyvern

pip install "skyvern[all]"

2. Run Skyvern

skyvern quickstart

The pip quickstart uses SQLite by default. For a local Postgres container, run skyvern quickstart --postgres.

Option B: Docker Compose

Use this option if you want everything containerized (Postgres, API, UI) and don't want to install Python/Node locally.

1. Install Docker Desktop
2. Clone the repository: bash git clone https://github.com/skyvern-ai/skyvern.git && cd skyvern
3. Configure your LLM provider in .env (the quickstart --docker-compose command below will create it from .env.example if missing): bash cp .env.example .env # if not already created # edit .env to add your LLM API key
4. Start everything: bash docker compose up -d
5. Open http://localhost:8080

Troubleshooting

(sqlite3.OperationalError) table organizations already exists — You hit a known bug in pip install skyvern==1.0.31. Fix:

rm ~/.skyvern/data.db   # remove the leftover SQLite file
pip install --upgrade skyvern   # 1.0.32+ contains the fix
skyvern quickstart

If you are still on 1.0.31 and cannot upgrade, install via uv instead:

uv pip install skyvern

pip install skyvern fails with ResolutionImpossible (litellm / fastmcp) — You hit a dependency-resolution conflict in 1.0.31. Either upgrade to 1.0.32+ or use uv: uv pip install skyvern.

SDK

Skyvern is a Playwright extension that adds AI-powered browser automation. It gives you the full power of Playwright with additional AI capabilities—use natural language prompts to interact with elements, extract data, and automate complex multi-step workflows.

Installation: - Python SDK / cloud API: pip install skyvern - Local server + packaged UI: pip install "skyvern[all]" then run skyvern quickstart - Local server + packaged UI with Postgres: pip install "skyvern[all]" then run skyvern quickstart --postgres - Packaged UI for an existing API: pip install "skyvern[ui]" then run skyvern run ui --api-url <api-url> --api-key <api-key> - TypeScript: npm install @skyvern/client

AI-Powered Page Commands

Skyvern adds four core AI commands directly on the page object:

Command	Description
page.act(prompt)	Perform actions using natural language (e.g., "Click the login button")
page.extract(prompt, schema)	Extract structured data from the page with optional JSON schema
page.validate(prompt)	Validate page state, returns bool (e.g., "Check if user is logged in")
page.prompt(prompt, schema)	Send arbitrary prompts to the LLM with optional response schema

Additionally, page.agent provides higher-level workflow commands:

Command	Description
page.agent.run_task(prompt)	Execute complex multi-step tasks
page.agent.login(credential_type, credential_id)	Authenticate with stored credentials (Skyvern, Bitwarden, 1Password)
page.agent.download_files(prompt)	Navigate and download files
page.agent.run_workflow(workflow_id)	Execute pre-built workflows

AI-Augmented Playwright Actions

All standard Playwright actions support an optional prompt parameter for AI-powered element location:

Action	Playwright	AI-Augmented
Click	page.click("#btn")	page.click(prompt="Click login button")
Fill	page.fill("#email", "a@b.com")	page.fill(prompt="Email field", value="a@b.com")
Select	page.select_option("#country", "US")	page.select_option(prompt="Country dropdown", value="US")
Upload	page.upload_file("#file", "doc.pdf")	page.upload_file(prompt="Upload area", files="doc.pdf")

Three interaction modes:

# 1. Traditional Playwright - CSS/XPath selectors
await page.click("#submit-button")

# 2. AI-powered - natural language
await page.click(prompt="Click the green Submit button")

# 3. AI fallback - tries selector first, falls back to AI if it fails
await page.click("#submit-btn", prompt="Click the Submit button")

Core AI Commands - Examples

# act - Perform actions using natural language
await page.act("Click the login button and wait for the dashboard to load")

# extract - Extract structured data with optional JSON schema
result = await page.extract("Get the product name and price")
result = await page.extract(
    prompt="Extract order details",
    schema={"order_id": "string", "total": "number", "items": "array"}
)

# validate - Check page state (returns bool)
is_logged_in = await page.validate("Check if the user is logged in")

# prompt - Send arbitrary prompts to the LLM
summary = await page.prompt("Summarize what's on this page")

Quick Start Examples

Run via UI:

skyvern run all

Navigate to http://localhost:8080 to run tasks through the web interface. If the packaged UI is missing, skyvern run ui will offer to install the matching UI package. For non-interactive setup, use skyvern run ui --install-ui or skyvern run all --install-ui.

To run only the packaged UI against an existing Skyvern API, install skyvern[ui] and pass --api-url; the CLI infers --wss-url from the API URL unless you override it. You can also set VITE_API_BASE_URL, VITE_WSS_BASE_URL, VITE_ARTIFACT_API_BASE_URL, VITE_SKYVERN_API_KEY, and VITE_BROWSER_STREAMING_MODE before running skyvern run ui.

Python SDK:

from skyvern import Skyvern

# Local mode
skyvern = Skyvern.local()

# Or connect to Skyvern Cloud
skyvern = Skyvern(api_key="your-api-key")

# Launch browser and get page
browser = await skyvern.launch_cloud_browser()
page = await browser.get_working_page()

# Mix Playwright with AI-powered actions
await page.goto("https://example.com")
await page.click("#login-button")  # Traditional Playwright
await page.agent.login(credential_type="skyvern", credential_id="cred_123")  # AI login
await page.click(prompt="Add first item to cart")  # AI-augmented click
await page.agent.run_task("Complete checkout with: John Snow, 12345")  # AI task

TypeScript SDK:

import { Skyvern } from "@skyvern/client";

const skyvern = new Skyvern({ apiKey: "your-api-key" });
const browser = await skyvern.launchCloudBrowser();
const page = await browser.getWorkingPage();

// Mix Playwright with AI-powered actions
await page.goto("https://example.com");
await page.click("#login-button");  // Traditional Playwright
await page.agent.login("skyvern", { credentialId: "cred_123" });  // AI login
await page.click({ prompt: "Add first item to cart" });  // AI-augmented click
await page.agent.runTask("Complete checkout with: John Snow, 12345");  // AI task

await browser.close();

Simple task execution:

from skyvern import Skyvern

skyvern = Skyvern()
task = await skyvern.run_task(prompt="Find the top post on hackernews today")
print(task)

Advanced Usage

Control your own browser (Chrome)

Let Skyvern control your existing Chrome browser — with all your cookies, logins, and extensions.

Step 1: Enable remote debugging in Chrome

1. Open Chrome and navigate to chrome://inspect/#remote-debugging
2. Click Enable to start the debugging server
3. You should see: Server running at: 127.0.0.1:9222

[!TIP] The skyvern init browser command can do this automatically — it opens chrome://inspect/#remote-debugging, waits for you to enable it, and saves the config.

Step 2: Connect Skyvern

Option A — Python Code:

from skyvern import Skyvern

skyvern = Skyvern(
    base_url="http://localhost:8000",
    api_key="YOUR_API_KEY",
    browser_address="http://127.0.0.1:9222",
)
task = await skyvern.run_task(
    prompt="Find the top post on hackernews today",
)

Option B — Skyvern Service:

Add two variables to your .env file:

BROWSER_TYPE=cdp-connect
BROWSER_REMOTE_DEBUGGING_URL=http://127.0.0.1:9222

Restart Skyvern service skyvern run all and run the task through UI or code

Connect Skyvern Cloud to your local browser

Let Skyvern Cloud control a Chrome browser running on your machine — with all your existing cookies, logins, and extensions. Useful for automating sites where you're already logged in or behind a VPN.

# One command to start Chrome + create a tunnel to Skyvern Cloud
skyvern browser serve --tunnel

Then use the tunnel URL in your task:

from skyvern import Skyvern

skyvern = Skyvern(api_key="your-api-key")
task = await skyvern.run_task(
    prompt="Download the latest invoice from my account",
    browser_address="https://abc123.ngrok-free.dev",
)

[!WARNING] Always use --api-key when exposing your browser via a tunnel. Without it, anyone with the URL has full control of your browser. See the security docs.

See the full documentation for all options, manual tunnel setup, and