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ianjennings merged 2 commits into from
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Yassine/v1 #2

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72a6085
remove vscode from deps
ianjennings Apr 14, 2025
9a48a90
first build
ianjennings Apr 14, 2025
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202 changes: 202 additions & 0 deletions LICENSE
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Apache License
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164 changes: 140 additions & 24 deletions README.md
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# Chat Example
<a href="https://testdriver.ai"><img src="https://github.com/dashcamio/testdriver/assets/318295/2a0ad981-8504-46f0-ad97-60cb6c26f1e7"/></a>

Visual Studio Code's Copilot Chat architecture enables extension authors to integrate with the GitHub Copilot Chat experience. A chat extension is a VS Code extension that uses the Chat extension API by contributing a Chat participant. Chat participants are domain experts that can answer user queries within a specific domain.
# TestDriver.ai

The Language Model API enables you to use the Language Model and integrate AI-powered features and natural language processing in your Visual Studio Code extension.
Automate and scale QA with computer-use agents.

When an extension uses the Chat or the Language Model API, we call it a GitHub Copilot Extension, since GitHub Copilot is the provider of the Chat and the Language Model experience.
[Docs](https://docs.testdriver.ai) | [Website](https://testdriver.ai) | [GitHub Action](https://github.com/marketplace/actions/testdriver-ai) | [Join our Discord](https://discord.com/invite/cWDFW8DzPm)

This GitHub Copilot Extension sample shows:
---https://github.com/user-attachments/assets/4719e834-652a-43ba-8b8c-24ea6f357ae3# Install via NPM

- How to contribute a simple chat participant to the GitHub Copilot Chat view. (`@cat`, [simple.ts](src/simple.ts))
- How to use the Language Model API to request access to the Language Model.
- How to use the `@vscode/chat-extension-utils` library to easily create a chat participant that uses tools. (`@catTools`, [chatUtilsSample.ts](src/chatUtilsSample.ts))
- How to contribute a more sophisticated chat participant that uses the LanguageModelTool API to contribute and invoke tools. (`@tool`, [toolParticipant.ts](src/toolParticipant.ts))
```sh
npm install testdriverai -g
```

![demo](./demo.png)
# Run Init

Documentation can be found here:
```sh
testdriverai init
```

- https://code.visualstudio.com/api/extension-guides/cha
- https://code.visualstudio.com/api/extension-guides/language-model
[Follow the instructions on our docs for more.](https://docs.testdriver.ai/overview/quickstart).

## Running the Sample
# About

- Run `npm install` in terminal to install dependencies
- Run the `Run Extension` target in the Debug View. This will:
- Start a task `npm: watch` to compile the code
- Run the extension in a new VS Code window
- You will see the @cat chat participant show in the GitHub Copilot Chat view
TestDriver isn't like any test framework you've used before. TestDriver is an OS Agent for QA. TestDriver uses AI vision along with mouse and keyboard emulation to control the entire desktop. It's more like a QA employee than a test framework. This kind of black-box testing has some major advantages:

## About this sample
- **Easier set up:** No need to add test IDs or craft complex selectors
- **Less Maintenance:** Tests don't break when code changes
- **More Power:** TestDriver can test any application and control any OS setting

This sample shows two different ways to build a chat participant in VS Code:
### Demo (Playing Balatro Desktop)

See [simple.ts](src/simple.ts) for an example of a simple chat participant that makes requests and responds to user queries. It shows how you can create chat participants with or without the [@vscode/prompt-tsx](https://www.npmjs.com/package/@vscode/prompt-tsx) library.
https://github.com/user-attachments/assets/7cb9ee5a-0d05-4ff0-a4fa-084bcee12e98

See [toolParticipant.ts](src/toolParticipant.ts) for an example of a chat participant that invokes tools, either dynamically or using the `toolReferences` that are attached to the request. This is a more advanced example that shows how you can use the [@vscode/prompt-tsx](https://www.npmjs.com/package/@vscode/prompt-tsx) library to implement the LLM tool calling flow and tries to implement all the features of the chat API.
# Examples

# vscode
- Test any user flow on any website in any browser
- Clone, build, and test any desktop app
- Render multiple browser windows and popups like 3rd party auth
- Test `<canvas>`, `<iframe>`, and `<video>` tags with ease
- Use file selectors to upload files to the browser
- Test chrome extensions
- Test integrations between applications
- Integrates into CI/CD via GitHub Actions ($)

Check out [the docs](https://docs.testdriver.ai/).

# Workflow

1. Tell TestDriver what to do in natural language on your local machine using `npm i testdriverai -g`
2. TestDriver looks at the screen and uses mouse and keyboard emulation to accomplish the goal
3. Run TestDriver tests on our test infrastructure

# Quickstart

## Install TestDriver via NPM

Install testdriverai via NPM. This will make testdriverai available as a global command.

```sh
npm install testdriverai -g
```

## Teach TestDriver a test

Let's show TestDriver what we want to test. Run the following command:

```sh
testdriverai .testdriver/test.yaml
```

## Reset the test state

TestDriver best practice is to start instructing TestDriver with your app in it's initial state. For browsers, this means creating a new tab with the website you want to test.

If you have multiple monitors, make sure you do this on your primary display.

## Instruct TestDriver

Now, just tell TestDriver what you want it to do. For now, stick with single commands like "click sign up" and "scroll down."

Later, try to perform higher level objectives like "complete the onboarding."

```yaml
> Click on sign up
TestDriver Generates a Test
TestDriver will look at your screen and generate a test script. TestDriver can see the screen, control the mouse, keyboard, and more!
TestDriver can only see your primary display!
To navigate to testdriver.ai, we need to focus on the
Google Chrome application, click on the search bar, type
the URL, and then press Enter.

Here are the steps:

1. Focus on the Google Chrome application.
2. Click on the search bar.
3. Type "testdriver.ai".
4. Press Enter.

Let's start with focusing on the Google Chrome application
and clicking on the search bar.

commands:
- command: focus-application
name: Google Chrome
- command: hover-text
text: Search Google or type a URL
description: main google search
action: click

After this, we will type the URL and press Enter.
```

## TestDriver executes the test script

TestDriver will execute the commands found in the yml codeblocks of the response.

See the yml TestDriver generated? That's our own schema. You can learn more about it in the [reference](https://docs.testdriver.ai/reference/yml-schema).

> Take your hands off the mouse and keyboard while TestDriver executes! TestDriver is not a fan of backseat drivers.

## Keep going!

Feel free to ask TestDriver to perform some more tasks. Every time you prompt TestDriver it will look at your screen and generate more test step to complete your goal.

```sh
> navigate to airbnb.com
> search for destinations in austin tx
> click check in
> select august 8
```

If something didn't work, you can use `/undo` to remove all of the test steps added since the last prompt.

## Test the test locally

Now it's time to make sure the test plan works before we deploy it. Use testdriver run to run the test file you just created with /save .

```sh
testdriverai run testdriver/test.yaml
```

Make sure to reset the test state!

## Deploy

Now it's time to deploy your test using our GitHub action! testdriver init already did the work for you and will start triggering tests once you commit the new files to your repository.

```sh
git add .
git commit -am "Add TestDriver tests"
gh pr create --web
```

Your test will run on every commit and the results will be posted as a Dashcam.io video within your GitHub summary! Learn more about deploying on CI [here](https://docs.testdriver.ai/continuous-integration/overview).
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