Skip to main content

AI-powered smart locator with retry functionality for Robot Framework using OpenAI

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

Robot Framework DomRetryLibrary

A Robot Framework library with AI-powered fallback for locator variables, enhancing test reliability by using OpenAI to dynamically generate element locators when primary locators fail.

Installation

Install the library using pip:

pip install robotframework-domretrylibrary

Usage

Import the library in your Robot Framework test file:

*** Settings ***
Library           SeleniumLibrary
Library           DomRetryLibrary    # Just use the direct class name

Define your locators and AI fallback descriptions:

*** Variables ***
${USERNAME_FIELD}      css=#non_existent_username_id
${AI_USERNAME_FIELD}   the username input field with placeholder 'Username'

Use the AI fallback in your tests:

*** Test Cases ***
Login Test
    Open Browser    https://example.com    chrome
    AI Fallback Locator    Input Text    USERNAME_FIELD    myusername
    Close Browser

New in Version 2.3.0: Direct AI Descriptions

You can now provide the AI description directly without needing to define an AI_ variable:

AI Fallback Locator    Input Text    css=#username    myusername    ai_description=the username input field

This approach is especially useful when you:

  • Want to use a dynamic description
  • Need to use locators without defining variable pairs
  • Prefer inline descriptions for better readability
  • Need to quickly test different descriptions

New in Version 2.4.0: Backward Compatibility for Existing Test Patterns

Version 2.4.0 adds intelligent backward compatibility for existing test patterns. It's now more forgiving and will:

  1. Handle empty locators by inferring from context
  2. Find any matching AI_ variable if none is explicitly specified
  3. Continue execution rather than failing when no description is found

This means your existing test structure will still work:

*** Keywords ***
Wait And Input Text
    [Arguments]    ${locator}    ${text}
    ${status}    ${error}=    Run Keyword And Ignore Error    Input Text    ${locator}    ${text}
    Run Keyword If    '${status}' == 'FAIL'    AI Fallback Locator    Input Text    ${locator}    ${text}

And empty locator variables will be handled gracefully:

*** Variables ***
${SUBMIT_BUTTON}    # Empty locator
${AI_SUBMIT_BUTTON}    the login button

*** Test Cases ***
Login Test
    AI Fallback Locator    Click Element    ${SUBMIT_BUTTON}    # Works with empty locator

New in Version 2.5.0: Enhanced AI Processor with Smart Locator Generation

Version 2.5.0 introduces significant improvements to the AI processor component, delivering more precise and reliable locator generation:

  1. Multi-Strategy Locator Generation

    • Uses three distinct AI strategies to find the best locator
    • Falls back gracefully if one approach fails
    • Provides more reliable element identification
  2. Smart Caching System

    • Remembers successful locator transformations between runs
    • Recognizes similar locator patterns for faster resolution
    • Continually improves over time as more tests run
  3. Original Locator Context

    • Intelligently leverages the original locator as context
    • Avoids being misled by misleading element names
    • Creates more precise alternative locators
  4. Enhanced Element Classification

    • Automatically classifies elements by type (button, input, checkbox, etc.)
    • Tailors locator strategies to specific element types
    • Improves accuracy for different UI components
  5. Intelligent HTML Processing

    • Focuses on relevant page sections (forms, main content)
    • Removes noise elements for better analysis
    • Prioritizes interactive elements
  6. Element Interaction Improvements

    • Automatically scrolls elements into view
    • Falls back to JavaScript execution when needed
    • Handles elements in shadow DOM and iframes better

To enable the transformation cache feature, provide a path for the cache file:

*** Settings ***
Library    DomRetryLibrary    
...    transformation_cache_file=my_transforms.json

API Key Setup

Store your OpenAI API key in a .env file in your project directory:

OPENAI_API_KEY=your_api_key_here

Or provide it when initializing the library:

*** Settings ***
Library    DomRetryLibrary    api_key=${OPENAI_API_KEY}

How It Works

  1. The library first attempts to use your primary locator
  2. If the primary locator fails, it uses OpenAI to generate a new locator based on your description
  3. The AI-generated locator is used as a fallback
  4. Successful fallbacks are logged for future reference

Library Parameters

When importing the library, you can set several parameters:

Library    DomRetryLibrary    
...    api_key=${OPENAI_API_KEY}    
...    model=gpt-4o    
...    locator_storage_file=my_locators.json
...    transformation_cache_file=my_transforms.json
Parameter Default Description
api_key None OpenAI API key (falls back to environment variable)
model gpt-4o OpenAI model to use
locator_storage_file locator_comparison.json File to store successful AI locators
transformation_cache_file ~/.dom_retry_transformation_cache.json File to store transformation cache data

Keywords

The library provides the following keywords:

  • AI Fallback Locator - Add AI fallback to any locator-based keyword

License

MIT

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

robotframework_domretrylibrary-2.5.0.tar.gz (20.1 kB view details)

Uploaded Source

Built Distribution

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

robotframework_domretrylibrary-2.5.0-py3-none-any.whl (20.0 kB view details)

Uploaded Python 3

File details

Details for the file robotframework_domretrylibrary-2.5.0.tar.gz.

File metadata

File hashes

Hashes for robotframework_domretrylibrary-2.5.0.tar.gz
Algorithm Hash digest
SHA256 f4e04d9c1a19f87b1a4515318ae8a626144039dcdc9b488ade67c93201f9289a
MD5 d074de5f3557c0f8e64a2956887bc23b
BLAKE2b-256 77e0b0d6dc1b71f86beae0422ee57995e893d2a8e2a1c8ac5a8780b4e44f4d65

See more details on using hashes here.

File details

Details for the file robotframework_domretrylibrary-2.5.0-py3-none-any.whl.

File metadata

File hashes

Hashes for robotframework_domretrylibrary-2.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6013151fb2b8d27cbf4fa9d4e1d21a56a2ce684683cb141e7b61c2875e85835b
MD5 5f6ed58651184f861d1390642a8b82f7
BLAKE2b-256 2411f7c729092c8b49fc6f8e90e0ab7fd8a187f3458509a2dc1406977a1941f6

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