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AI in Rapise

Overview

We have integrated AI capabilities directly into Rapise, allowing users to harness the power of AI without needing to switch between applications. Everything can be managed within Rapise itself. Moreover, the AI in Rapise is well-versed with Rapise's Global Object API, the currently open testing framework, its modules, and object repositories. This knowledge enables the generation of precise and specialized responses. In its initial release, Rapise’s AI features include RVL and JavaScript code generation, as well as data generation functionalities. Rapise 8.2 supports OpenAI and Azure OpenAI models, including multimodal ones that can accept image input. The AI workflow in Rapise also supports incremental improvements in code generation quality by allowing users to save positive and negative examples for use in subsequent prompts.

A key feature of Rapise 8.2 is the AI Command, which translates human-readable test step descriptions into executable code using AI. Once the code is generated for an AI Command, it can be executed independently of AI. If the AI Command text is modified, the code is regenerated accordingly. When generating code for an AI Command, Rapise considers available Global Objects, as well as Modules/Page Objects and objects from the Object Repository associated with the test case containing the AI Command (including objects linked with Repository command).

When using AI Commands, the recommended workflow for test creation is as follows: first, define Page Objects with high-level actions (e.g., Login, Logout, OpenModule, AddRecord, UpdateRecord, DeleteRecord). Then, learn and add test case-specific objects to the Object Repository, and finally, write your test case using AI Commands. The AI will translate these commands into executable JavaScript, which you can review and edit. Once all commands are translated into code, the test case is ready for execution.

Rapise provides two primary interfaces for interacting with AI:

  • The AI Dashboard allows you to configure AI options, chat with the AI, and view your chat history.

  • The AI Panel is linked to the active RVL document and is used to translate AI Commands into executable JavaScript code.

AI Dashboard

How to Open

To open the AI Dashboard, go to the main menu and select View > AI Dashboard.

The dashboard comprises three pages:

Dashboard Tabs

AI Dashboard tabs: Settings, Chats, Snapshots.

  • Settings: Configure your AI API key, select the default model, and set framework-specific options here.
  • Chats: This page displays the history of AI chats. You can open any chat and continue interacting with the AI.
  • Snapshots: Starred chats will appear on this page.

Settings

In its initial release, Rapise supports both OpenAI and Azure OpenAI models. To use OpenAI models, you only need an OpenAI Api Key. For Azure OpenAI, you also need to specify the endpoint URL.

Dashboard Settings

Options Tab

  • Scope: global | local (Selected: local)

Default Model

  • Provider: Amazon Bedrock | Azure | OpenAI (Selected: OpenAI)
  • Model Name: gpt-4o
  • API Key: [hidden]
  • Proxy: http://localhost:8000

Test Model: [Button]

You can create options that are local to the current testing framework. Simply click the local[create] button. If local options exist, Rapise will prioritize them over global ones. To delete local options, click ... > Delete Local.

Amazon Bedrock

Rapise 8.3 adds support for Amazon Bedrock. To configure Amazon Bedrock connection specify AWS Region, AWS Access Key and AWS Secret Access Key.

Proxy

If you are behind a proxy, specify it's URL in the Proxy field (works for all providers).

Chats

On the Chats page, you can select a previous chat and continue interacting with the AI. You can also start a new chat. When creating a new chat, you’ll be prompted to select a workflow. Supported workflows include:

AI Chat

This is a general-purpose chat with an AI model. You can ask questions and receive answers. You can also enhance prompts by adding screenshots and files.

AI Chat

USER: What are main features of a good UI testing framework?

AI: A good UI testing framework should have several key features to ensure it is effective, efficient, and user-friendly. Here are the main features to consider:

  1. Cross-Browser Compatibility: The framework should support testing across multiple browsers (e.g., Chrome, Firefox, Safari, Edge) to ensure consistent behavior of the application.

  2. Cross-Platform Support: It should be able to test applications on various platforms (e.g., web, mobile, desktop) to accommodate different user environments.

  3. Ease of Use: The framework should have a user-friendly interface and clear documentation, making it easy for testers and developers to write and maintain tests.

AI Command

This chat type is typically generated by Rapise when processing an AI Command. The result of prompt processing is JavaScript code. In this chat, you can edit the generated code, copy it to a JavaScript file, or convert it to RVL and apply it to the active RVL sheet.

AI Command

USER: Open browser at https://libraryinformationsystem.org

AI: 

Navigator.Open("https://libraryinformationsystem.org")

Generate Data List

Generates a list of data values that can be directly inserted into an RVL sheet from the chat.

  1. Prompt AI to generate a list of values. E.g.: Generate 10 fake company names.

    Generate List

    USER: Generate 10 fake company names

    AI: 

    Companies
InnovaTech  
EcoSphere  
NexGen Solutions  
Quantum Dynamics  
AeroFusion  
CrestWave  
PixelForge  
VitaNova  
Stratosphere Innovations  
BluePeak Industries

  2. Open the RVL file and sheet where you want to insert the result.

  3. Return to the AI Dashboard and click Apply . You can also edit values before inserting them into the RVL.

    Apply List

  4. The list will be inserted into the RVL.

    List Result

    Flow Type Object Action ParamName ParamType ParamValue
    Map Rows Companies
    Companies
    Innovatech
    EcoSphere
    NexGen Solutions
    Quantum Dynamics
    AeroFusion
    CrestWave
    PixelForge
    VitaNova
    Stratosphere Innovations
    BluePeak Industries
    End

Generate Data Table

Generates a table with columns and rows. The result can be directly inserted into an RVL sheet as a Map. The workflow is similar to generating a Data List.

  1. Prompt AI to generate a table of values. E.g.: Generate a table with 10 records and columns: Zip, City, Street Address.

    Generate Table

    USER: Generate a table with 10 records and columns: Zip, City, Street Address

    AI: 

    {  
"data": [  
    {  
    "Zip": "10001",  
    "City": "New York",  
    "Street Address": "123 Main St"  
    },  
    {  
    "Zip": "20001",  
    "City": "Washington",  
    "Street Address": "456 Elm St"  
    },  
    {  
    "Zip": "30301",  
    "City": "Atlanta",  
    "Street Address": "789 Pine St"  
    },  
    {  
    "Zip": "60601",  
    "City": "Chicago",  
    "Street Address": "101 Maple St"  
    },  
    {  
    "Zip": "70112",  
    "City": "New Orleans",  
    "Street Address": "202 Oak St"  
    },  
    {  
    "Zip": "94105",  
    "City": "San Francisco",  
    "Street Address": "303 Cedar St"  
    },  
    {  
    "Zip": "33101",  
    "City": "Miami",  
    "Street Address": "404 Birch St"  
    },  
    {  
    "Zip": "80202",  
    "City": "Denver",  
    "Street Address": "505 Walnut St"  
    },  
    {  
    "Zip": "98101",  
    "City": "Seattle",  
    "Street Address": "606 Spruce St"  
    },  
    {  
    "Zip": "85001",  
    "City": "Phoenix",  
    "Street Address": "707 Palm St"  
    }  
]  
}

  2. Apply the AI response to get the result.

    Table Result

    Flow Type Object Action ParamName ParamType ParamValue
    Map Rows TBD
    Zip City Street Address
    10001 New York 123 Main St
    20001 Washington 456 Elm St
    30301 Atlanta 789 Pine St
    60601 Chicago 101 Maple St
    70112 New Orleans 202 Oak St
    94105 San Francisco 303 Cedar St
    33101 Miami 404 Birch St
    80202 Denver 505 Walnut St
    98101 Seattle 606 Spruce St
    85001 Phoenix 707 Palm St
    End

Generate More Rows

Use this to generate additional data for an existing table.

  1. Select a row in the current RVL table.

    Select Row

    Flow Type Object Action ParamName ParamType ParamValue
    Map Rows TBD
    Zip City Street Address
    10001 New York 123 Main St
    20001 Washington 456 Elm St
    30301 Atlanta 789 Pine St
    60601 Chicago 101 Maple St
    70112 New Orleans 202 Oak St
    94105 San Francisco 303 Cedar St
    33101 Miami 404 Birch St
    80202 Denver 505 Walnut St
    98101 Seattle 606 Spruce St
    85001 Phoenix 707 Palm St
    End

  2. In the AI Dashboard, create a "Generate More Rows" chat and send a prompt to the AI. For example: Generate 10 more records with cities from countries other than USA.

    Generate Rows

    USER: Generate 10 more records with cities from countries other than USA

    AI: 

    {  
"data": [  
    {  
    "Zip": "10115",  
    "City": "Berlin",  
    "Street Address": "Friedrichstraße 123"  
    },  
    {  
    "Zip": "M5A 1A1",  
    "City": "Toronto",  
    "Street Address": "Queen St E 456"  
    },  
    {  
    "Zip": "SW1A 1AA",  
    "City": "London",  
    "Street Address": "Buckingham Palace Road 1"  
    },  
    {  
    "Zip": "1000",  
    "City": "Brussels",  
    "Street Address": "Rue de la Loi 10"  
    },  
    {  
    "Zip": "1010",  
    "City": "Vienna",  
    "Street Address": "Karntnerring 5"  
    },  
    {  
    "Zip": "1100",  
    "City": "Athens",  
    "Street Address": "Syntagma Square 2"  
    },  
    {  
    "Zip": "75001",  
    "City": "Paris",  
    "Street Address": "Rue de Rivoli 20"  
    },  
    {  
    "Zip": "2000",  
    "City": "Copenhagen",  
    "Street Address": "Købmagergade 30"  
    },  
    {  
    "Zip": "1010",  
    "City": "Amsterdam",  
    "Street Address": "Damstraat 1"  
    },  
    {  
    "Zip": "1010",  
    "City": "Madrid",  
    "Street Address": "Gran Vía 45"  
    }  
]  
}

  3. Apply the generated values to see the result.

    Rows Result

    Flow Type Object Action ParamName ParamType ParamValue
    Map Rows TBD
    Zip City Street Address
    10001 New York 123 Main St
    20001 Washington 456 Elm St
    30301 Atlanta 789 Pine St
    60601 Chicago 101 Maple St
    70112 New Orleans 202 Oak St
    94105 San Francisco 303 Cedar St
    33101 Miami 404 Birch St
    80202 Denver 505 Walnut St
    98101 Seattle 606 Spruce St
    85001 Phoenix 707 Palm St
    10115 Berlin Friedrichstraße 123
    M5A 1A1 Toronto Queen St E 456
    SW1A 1AA London Buckingham Palace R
    1000 Brussels Rue de la Loi 10
    1010 Vienna Karntnerring 5
    1100 Athens Syntagma Square 2
    75001 Paris Rue de Rivoli 20
    2000 Copenhagen Købmagergade 30
    1010 Amsterdam Damstraat 1
    1010 Madrid Gran Vía 45
    End

Test Scenario from Text

Generates a sequence of AI Commands based on a text prompt.

  1. Provide a high-level description of the scenario you want to implement. For example: Generate an end-to-end scenario to create and delete a book in a web based Library Information System. A step-by-step scenario will be generated.

    Scenario from Text

    USER: Generate an end-to-end scenario to create and delete a book in a web based Library Information System

    AI: 

    1. Open the web browser and navigate to the Library Information System URL {library_url}.  
2. Click on the "Login" button.  
3. Enter the username {username} in the username field.  
4. Enter the password {password} in the password field.  
5. Click on the "Submit" button to log in.  
6. Once logged in, navigate to the "Books" section of the system.  
7. Click on the "Add New Book" button.  
8. Fill in the book title {book_title} in the title field.  
9. Fill in the author name {author_name} in the author field.  
10. Fill in the ISBN number {isbn_number} in the ISBN field.  
11. Select the genre {genre} from the dropdown menu.  
12. Click on the "Save" button to create the book entry.  
13. Verify that the book {book_title} appears in the list of books.  
14. Locate the newly created book {book_title} in the list.  
15. Click on the "Delete" button next to the book {book_title}.  
16. Confirm the deletion in the pop-up dialog.  
17. Verify that the book {book_title} no longer appears in the list of books.  
18. Log out of the Library Information System.

  2. Select an RVL sheet for insertion, then return to the AI Dashboard and click the Apply icon. A sequence of AI commands will be inserted into the RVL sheet.

    Scenario from Text Result

    Flow Type Object Action ParamName ParamType ParamValue
    AI Open the web browser and navigate to the Library Information System URL
    Param library_url string library_url
    AI Click on the "Login" button.
    AI Enter the username {username} in the username field.
    Param username string username
    AI Enter the password {password} in the password field.
    Param password string password
    AI Click on the "Submit" button to log in.
    AI Once logged in, navigate to the "Books" section of the system.
    AI Click on the "Add New Book" button.
    AI Fill in the book title {book_title} in the title field.
    Param book_title string book_title
    AI Fill in the author name {author_name} in the author field.
    Param author_name string author_name
    AI Fill in the ISBN number {isbn_number} in the ISBN field.
    Param isbn_number string isbn_number
    AI Select the genre {genre} from the dropdown menu.
    Param genre string genre
    AI Click on the "Save" button to create the book entry.
    AI Verify that the book {book_title} appears in the list of books.
    Param book_title string book_title
    AI Locate the newly created book {book_title} in the list.
    Param book_title string book_title
    AI Click on the "Delete" button next to the book {book_title}.
    Param book_title string book_title
    AI Confirm the deletion in the pop-up dialog.
    AI Verify that the book {book_title} no longer appears in the list of books.
    Param book_title string book_title
    AI Log out of the Library Information System.

Test Scenario from Image

Generates a sequence of AI Commands from an image and a text prompt.

  1. In the AUT, navigate to the screen/page you want to use.

    Scenario from Image - AUT

    Library Information System
    Logged in as Librarian, Logout

    Create New Book

    Name
    Enter book name (text input)

    Author
    A.A. Milne (dropdown selection)

    Genre
    Adventure (dropdown selection)

    Out of Print
    [ ] (checkbox)

    10/07/2020 (date picker)

    [Save Book] (button)

  2. In the AI Dashboard, create a "Test Scenario from Image" chat and provide the image along with a text prompt. For example: Fill the form.

    Scenario from Image - Prompt

    USER: Fill the form (screenshot of the form is attached)

    AI: 

    1. Enter {book_name} in the "Name" field.  
2. Select {author_name} from the "Author" dropdown.  
3. Select {genre} from the "Genre" dropdown.  
4. Check the "Out of Print" checkbox if {out_of_print} is true.  
5. Enter {date} in the date field.  
6. Click the "Save Book" button.

  3. Select an RVL sheet for insertion, then return to the AI Dashboard and click the Apply icon. A sequence of AI commands will be inserted into the RVL sheet.

    Scenario from Image - Result

    Flow Type Object Action ParamName ParamType ParamValue
    AI Enter {book_name} in the "Name" field.
    Param book_name string book_name
    AI Select {author_name} from the "Author" dropdown.
    Param author_name string author_name
    AI Select {genre} from the "Genre" dropdown.
    Param genre string genre
    AI Check the "Out of Print" checkbox if {out_of_print} is true.
    Param out_of_print string out_of_print
    AI Enter {date} in the date field.
    Param date string date
    AI Click the "Save Book" button.

Snapshots

On this page, find starred chats. To add a chat to Snapshots, locate it in history, and hover your mouse pointer over its top-right corner to reveal the ... icon:

Session Menu

Click the icon to expand the popup menu and select Snapshot.

Make Snapshot

If you no longer need a chat on the Snapshots page, you can remove it.

Delete Snapshot

AI Panel

AI panel is used to work with AI Commands.

How to Open

To open the panel, double-click the line number of an AI Command or click the Show AI Panel button that appears when you hover your mouse over the corresponding cell.

AI Panel

It’s also possible to work with multiple AI Commands simultaneously. Simply select a range of commands and click Show AI Panel.

AI Panel Multiple Commands

There is also a toolbar button that shows all AI Commands on the active RVL sheet.

AI Panel Show All Commands

Command Menu

You can perform various actions with each command.

Command Menu

  • - generate or regenerate code for the command.
  • - run the code for this command.
  • - copy the command ID to the clipboard.
  • - open the corresponding chat session in the AI Dashboard.
  • - like the result of code generation. This will be used as a positive example in subsequent AI Command prompts.
  • - dislike the result of code generation. This will be used as a negative example in subsequent AI Command prompts.

Panel Menu

The panel also includes a top-level menu.

Top Level Menu More Menu Items

  • - generate or regenerate code for all the commands opened in the AI Panel.
  • - run all the commands opened in the AI Panel sequentially.
  • - undock the panel.
  • - dock the panel to the right.
  • - dock the panel to the bottom.
  • - hide the panel.
  • - open the Workflow selection page.

Framework Folders

When you work with AI in Rapise, it creates a set of folders in the root framework directory.

  • Root Framework Folder
    • AI - root folder for AI-related files.
      • commands - cache for AI Commands, containing generated JavaScript code. This folder must be stored along with the framework; do not delete it. [Deprecated]
      • messages - archive of AI chat messages.
      • sessions - high-level information about AI chat sessions (name, ID, timestamp).
      • options.json - local options that override the global ones stored in C:\ProgramData\Inflectra\Rapise\AI\options.json.
      • screenshot.base64 - last screenshot taken in Chats.
      • AIExamples.txt - the list of liked/disliked examples of generated code.
      • AIPrompt.txt - text to add to each AI prompt for AI Command processing.
      • ai.commands.json - Since Rapise 8.3 command cache is split per Test Case/Page Object folders. For each RVL file that contains AI commands an ai.commands.json is created in the same folder as the RVL file.

Source Control

When you put a framework under source control it is important to add

  • options.json
  • AIExamples.txt
  • AIPrompt.txt
  • commands folder with all the files in it. [Deprecated]
  • ai.commands.json files

The following folders are optional (this is just an archive of AI chats)

  • messages
  • sessions

Rapise 8.3 AI Command Cache Changes

If you have AI tests created with Rapise 8.2, all code generated for AI commands will be still successfully loaded from AI\commands folder. If you will regenerate code for a command or generate code for a new command, it will be placed into corresponding ai.commands.json file located in the same folder as the RVL file.