Skip to main content

A utility to help you locate UI elements using HTML and natural language.

Project description

talk2dom — Locate Web Elements with One Sentence

📚 English | 中文

PyPI PyPI Downloads Stars License CI

talk2dom is a focused utility that solves one of the hardest problems in browser automation and UI testing:

Finding the correct UI element on a page.


Watch the demo on YouTube

🧠 Why talk2dom

In most automated testing or LLM-driven web navigation tasks, the real challenge is not how to click or type — it's how to locate the right element.

Think about it:

  • Clicking a button is easy — if you know its selector.
  • Typing into a field is trivial — if you've already located the right input.
  • But finding the correct element among hundreds of <div>, <span>, or deeply nested Shadow DOM trees? That's the hard part.

talk2dom is built to solve exactly that.


🎯 What it does

talk2dom helps you locate elements by:

  • Understands natural language instructions and turns them into browser actions
  • Supports single-command execution or persistent interactive sessions
  • Uses LLMs (like GPT-4 or Claude) to analyze live HTML and intent
  • Returns flexible output: actions, selectors, or both — providing flexible outputs: actions, selectors, or both — depending on the instruction and model response
  • Compatible with both desktop and mobile browsers via Selenium

🗃️ Optional: Enable Locator Caching (PostgreSQL)

To avoid recomputing selectors every time, talk2dom can cache results in a PostgreSQL database.

How it works

  • For each instruction + html pair, a unique SHA256 hash is generated.
  • If a previous result exists, talk2dom reuses it and skips the LLM call.
  • Greatly improves performance and reduces token usage.

Setup

Set the DB_URI environment variable:

export DB_URI="postgresql+psycopg2://user:password@localhost:5432/dbname"

If DB_URI is not set, caching is automatically disabled, and all requests will use LLM inference in real-time.


🤔 Why Selenium?

While there are many modern tools for controlling browsers (like Playwright or Puppeteer), Selenium remains the most robust and cross-platform solution, especially when dealing with:

  • ✅ Safari (WebKit)
  • ✅ Firefox
  • ✅ Mobile browsers
  • ✅ Cross-browser testing grids

These tools often have limited support for anything beyond Chrome-based browsers. Selenium, by contrast, has battle-tested support across all major platforms and continues to be the industry standard in enterprise and CI/CD environments.

That’s why talk2dom is designed to integrate directly with Selenium — it works where the real-world complexity lives.


📦 Installation

pip install talk2dom

🧩 Code-Based ActionChain Mode

For developers and testers who prefer structured Python control, ActionChain lets you drive the browser step-by-step.

Basic Usage

By default, talk2dom uses gpt-4o-mini to balance performance and cost. However, during testing, gpt-4o has shown the best performance for this task.

Make sure you have OPENAI_API_KEY

export OPENAI_API_KEY="..."

Note: All models must support chat completion APIs and follow OpenAI-compatible schema.

Sample Code

from selenium import webdriver
from selenium.webdriver.common.keys import Keys

from talk2dom import ActionChain

driver = webdriver.Chrome()

ActionChain(driver) \
    .open("http://www.python.org") \
    .find("Find the Search box") \
    .type("pycon") \
    .wait(2) \
    .type(Keys.RETURN) \
    .assert_page_not_contains("No results found.") \
    .valid("the 'PSF PyCon Trademark Usage Policy' is displayed") \ 
    .close()

Free Models

You can also use talk2dom with free models like llama-3.3-70b-versatile from Groq.

Full page vs Scoped element queries

The find() function can be used to query the entire page or a specific element. You can pass either a full Selenium driver or a specific WebElement to scope the locator to part of the page.

Why/When use WebElement instead of driver?

  1. Reduce Token Usage — Passing a smaller HTML subtree (like a modal or container) instead of the full page saves LLM tokens, reducing latency and cost.
  2. Improve Locator Accuracy — Scoping the query helps the LLM focus on relevant content, which is especially helpful for nested or isolated components like popups, drawers, and cards.

You don’t need to extract HTML manually — talk2dom will automatically use outerHTML from any WebElement you pass in.


✨ Philosophy

Our goal is not to control the browser — you still control your browser. Our goal is to find the right DOM element, so you can tell the browser what to do.


✅ Key Features

  • 💬 Natural language interface to control the browser
  • 🔁 Persistent session for multi-step interactions
  • 🧠 LLM-powered understanding of high-level intent
  • 🧩 Outputs: actionable XPath/CSS selectors or ready-to-run browser steps
  • 🧪 Built-in assertions and step validations
  • 💡 Works with both CLI scripts and interactive chat

📄 License

Apache 2.0


Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.


💬 Questions or ideas?

We’d love to hear how you're using talk2dom in your AI agents or testing flows.
Feel free to open issues or discussions!
You can also tag us on GitHub if you’re building something interesting with talk2dom!
⭐️ If you find this project useful, please consider giving it a star!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

talk2dom-0.2.3.tar.gz (20.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

talk2dom-0.2.3-py3-none-any.whl (19.3 kB view details)

Uploaded Python 3

File details

Details for the file talk2dom-0.2.3.tar.gz.

File metadata

  • Download URL: talk2dom-0.2.3.tar.gz
  • Upload date:
  • Size: 20.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.8

File hashes

Hashes for talk2dom-0.2.3.tar.gz
Algorithm Hash digest
SHA256 143f5b159b2ffd2aad5c4bcc5687bd37e0ef0c6051836a72f2c3e1ac78138f99
MD5 c09861b6dbed818806faa840141277b6
BLAKE2b-256 5924be56c37c88f6006d3ce859ba5397e4a91ec086ac3722dfe2cf9aebb6c626

See more details on using hashes here.

File details

Details for the file talk2dom-0.2.3-py3-none-any.whl.

File metadata

  • Download URL: talk2dom-0.2.3-py3-none-any.whl
  • Upload date:
  • Size: 19.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.8

File hashes

Hashes for talk2dom-0.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 5cfdc809005ab70b46d4c6356d97e0d1bf80bd9d0fd9f63922853232bab88ab3
MD5 0db5c79c9d854562ba3395df6c325e9c
BLAKE2b-256 91f7d1619263f8a68b2fa6c36724ca7471f1f3d3b6529fa0984540e65e779e50

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page