🌐 Playwright Browser Automation

SLM Web Agent

Autonomous browser navigation agent powered by Playwright and local small language models for headless form filling and data extraction.

🚀 Overview & Capabilities

Autonomous browser navigation agent powered by Playwright and local small language models for headless form filling and data extraction.

Key Features

Headless browser interaction via Playwright
Automated form navigation and locator selection
DOM snapshot reduction for small model context windows
Zero external API calls

💻 Installation

Install the local package using pip:

Terminal

              $pip install slm-web-agent

🐙 Checkout from GitHub

Clone only this agent's folder from the monorepo using Git sparse-checkout — no need to download the full repository:

Option 1 — Sparse Checkout (Recommended)

Terminal — Git Sparse Checkout

              # 1. Create and enter a new directory
$ mkdir slm_web_agent && cd slm_web_agent

# 2. Initialise empty git repo and add remote
$ git init
$ git remote add origin https://github.com/t00114218-stack/SLMAgents.git

# 3. Enable sparse-checkout and set target folder
$ git sparse-checkout init --cone
$ git sparse-checkout set slm_web_agent

# 4. Pull only that agent's source
$ git pull origin main
            

Option 2 — Full Repository Clone

Terminal — Full Clone

              $ git clone https://github.com/t00114218-stack/SLMAgents.git
$ cd SLMAgents/slm_web_agent
            

💡 Tip: After checkout, install the package locally with pip install -e ./slm_web_agent to run in editable mode without publishing to PyPI.

⚙️ Configuration API

Constructor Parameters

Instantiate SLMWebAgent with performance and runtime options:

Parameter	Type / Default	Description
`headless`	bool \| True	Run browser in headless background mode. Default: True.
`temperature`	float \| 0.0	Action planning temperature. Default: 0.0.
`top_p`	float \| 0.9	Nucleus sampling cutoff. Default: 0.9.
`max_tokens`	int \| 256	Max token output limit. Default: 256.
`n_threads`	int \| 4	CPU threads for model execution. Default: 4.

Methods

Method Signature	Return Type	Description
`browse(goal, start_url, ...)`	dict	Executes multi-step Playwright web browsing tasks autonomously.

Execution Parameters

Complete list of execution parameters accepted by the primary agent method:

Parameter	Type / Default	Description
`goal`	str	Target browser automation goal description.
`start_url`	str	Initial Web URL to navigate to.
`system_prompt`	str \| None	Custom system instruction prompt override. Default: None.
`user_input`	str \| None	Optional additional user form fill values. Default: None.
`temperature`	float \| 0.0	Sampling temperature. Default: 0.0.
`top_p`	float \| 0.9	Nucleus sampling probability. Default: 0.9.
`max_tokens`	int \| 256	Maximum token limit. Default: 256.

Quick Start

Python Example

              from slm_web_agent import SLMWebAgent

web = SLMWebAgent(headless=True, n_threads=4)
res = web.browse(
    goal="Navigate to portal signup and enter test email",
    start_url="https://portal.slmagents.ai/signup",
    system_prompt="Wait 2 seconds after submit",
    user_input="Email: dev@slmagents.ai",
    temperature=0.0,
    top_p=0.9,
    max_tokens=256
)
print(res)
            

🔍 Verified Output Logs

Diagnostic execution console output running locally on CPU:

Output Console

              → INPUT:
Goal: Navigate to portal signup and enter test email
URL: https://portal.slmagents.ai/signup

← OUTPUT:
{
  'status': '200 OK',
  'goal': 'Navigate to portal signup and enter test email',
  'success': True,
  'steps_taken': 3
}
            