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Add new images and update documentation for LambdaTest AI Cloud GitHu…
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docs/kaneai-github-app.md

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></script>
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# LambdaTest AI Cloud GitHub App Integration
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***
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The **LambdaTest AI Cloud GitHub App** is an enterprise-grade integration that brings intelligent, AI-powered test automation directly into your GitHub development workflow. By seamlessly analyzing pull request changes, the app automatically generates comprehensive test cases, executes them across your testing infrastructure, and provides actionable insights-all within your GitHub interface.
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## 1. Overview
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### Repository Requirements
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- **GitHub Repository Access**: Administrative access to the GitHub repositories where you want to install the app
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- **Repository README**: A well-documented README.md file in your repository (the AI uses this for contextual understanding of your application)
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<!-- - **Repository README**: A well-documented README.md file in your repository (the AI uses this for contextual understanding of your application) -->
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> **Note:** KaneAI access is required to utilize the AI-powered test generation capabilities of this GitHub App. Without it, the app cannot analyze code changes or generate test cases.
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---
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- **Organization-wide Installation**: Select **All repositories** to enable the app across your entire GitHub organization
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- **Selective Installation**: Choose **Only select repositories** and specify individual repositories for more granular control
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After making your selection, complete the installation and authorize LambdaTest to access the selected repositories.
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<img loading="lazy" src={require('../assets/images/kaneai-github-app/github-repository-selection.png').default} alt="Trigger KaneAI workflow" className="doc_img"/>
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After making your selection and clicking the **Install and Authorize** button, you will be redirected to LambdaTest's integration page where under the **My Integrations** section you will be able to see this application.
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<img loading="lazy" src={require('../assets/images/kaneai-github-app/integration-success.png').default} alt="Trigger KaneAI workflow" className="doc_img"/>
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:::tip Best Practice
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For pilot programs or initial rollouts, we recommend installing on a select subset of repositories first. Once your team is comfortable with the workflow, you can expand access organization-wide.
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Confirm the installation was successful by:
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1. Navigating to your GitHub organization's **Settings** page
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2. Selecting **Installed GitHub Apps** from the left sidebar
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3. Verifying that **LambdaTest AI Cloud** appears in the list of installed applications
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2. In left side menu under **Integrations**, click **Applications**.
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3. Selecting **Installed GitHub Apps** from the left sidebar
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4. Verifying that **LambdaTest AI Cloud** appears in the list of installed applications
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You can also click on the app to review and modify repository access permissions at any time.
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<!-- <img loading="lazy" src={require('../assets/images/github-app/github-installation.png').default} alt="github-app-installation" className="doc_img"/> -->
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<img loading="lazy" src={require('../assets/images/kaneai-github-app/github-app-install-success-page.png').default} alt="Trigger KaneAI workflow" className="doc_img"/>
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---
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## 3.1 Uninstalling the GitHub App
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If you need to remove the LambdaTest AI Cloud GitHub App from your organization:
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1. Navigate to the [LambdaTest AI Cloud GitHub App](https://github.com/apps/lambdatest-ai-cloud) on GitHub Marketplace
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2. Click on the **Configure** button to access the app settings
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3. Scroll down to the bottom of the page to find the **Danger Zone** section
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4. Click on the **Uninstall** button to remove the app from your organization
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5. Confirm the uninstallation when prompted
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<img loading="lazy" src={require('../assets/images/kaneai-github-app/uninstall-github-app.png').default} alt="Uninstall GitHub App" className="doc_img"/>
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:::tip caution
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Uninstalling the GitHub App will stop all AI-powered test generation workflows on your pull requests. This action cannot be undone, and you'll need to reinstall the app to restore functionality.
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:::
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|-----------|-------------|---------------|
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| `project_id` | The unique identifier for your LambdaTest Test Manager project | Navigate to your project in Test Manager and copy the ID from the URL |
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| `folder_id` | The folder where generated test cases will be organized | Create or select a folder in Test Manager and obtain its ID from the URL |
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| `assignee` | The LambdaTest user ID who will be assigned to test runs | Found in your LambdaTest account profile settings |
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| `assignee` | The LambdaTest user ID who will be assigned to test runs for executions | Can be referenced from APIs |
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| `environment_id` | The target testing environment (browser, OS, device configurations) | Create environments in Test Manager and reference their IDs |
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| `test_url` | The base URL of your application under test | Your staging or testing environment URL where tests will be executed |
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your-repo/
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├── .lambdatest/
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│ └── config.yaml # LambdaTest configuration
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├── src/ # Your application source code
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├── README.md # Detailed project documentation (used by AI)
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└── agent.md # Optional file for custom instructions to enhance responses
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├── src/ # Your application source code
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├── README.md # Detailed project documentation (used by AI)
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└── ... other project files
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```
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```bash
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@LambdaTest Validate this PR
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#OR
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@LambdaTest Generate test cases
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#OR
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@KaneAI Generate test cases
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@KaneAI Validate this PR
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```
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Any of these commands will initiate the complete AI-powered testing workflow, from analysis to execution and reporting.
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After you post the trigger comment, KaneAI immediately begins working:
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1. **Code Analysis**: The AI examines all code changes in the pull request, including file modifications, additions, and deletions
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2. **Context Gathering**: Your repository's README, existing test patterns, and project structure are analyzed to understand application context
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2. **Context Gathering**: Your repository's README.md, PR Title, Description, Comments and AGENT.md are analyzed to understand application context
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3. **Test Strategy**: Based on the changes and context, the AI determines which areas require testing and what scenarios to cover
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4. **Test Generation**: Intelligent test cases are created with appropriate assertions, validations, and edge case handling
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- **Current Workflow Status**: Real-time updates on which phase is currently executing
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- **Test Case Pipeline**: Progress through analysis, generation, authoring, and code generation phases
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- **Intelligent Test Case Suggestion**: AI suggests semantically similar test cases present in the project
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- **Test Run Management**: Execution status, including configuration, triggering, monitoring, and completion
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- **Reporting Status**: Final report generation and PR approval recommendation
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To prevent test redundancy and optimize your test suite, KaneAI performs semantic analysis against your existing test inventory:
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- **Similar Test Identification**: Finds existing tests that cover similar functionality or user scenarios
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- **Reusability Recommendations**: Suggests whether to reuse, extend, or replace existing tests
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- **Test Suite Optimization**: Helps maintain a lean, efficient test suite by preventing duplicate coverage
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This intelligent analysis ensures your test repository remains organized and maintainable as it grows over time.
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- **Test Run Configuration**: Details about the execution environment, browser matrix, and parallel execution settings
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- **Real-Time Execution Status**: Live updates as tests run, including pass/fail counts and completion percentage
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- **HyperExecute Dashboard Link**: Direct access to detailed logs, screenshots, video recordings, and network traces
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- **Execution Duration**: Time tracking to help optimize CI/CD pipeline performance
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<img loading="lazy" src={require('../assets/images/kaneai-github-app/5-test-run-created.png').default} alt="Test Run Execution" className="doc_img"/>
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<!-- <img loading="lazy" src={require('../assets/images/kaneai-github-app/7-rca-for-failed-tests.png').default} alt="AI RCA for Failed Tests" className="doc_img"/> -->
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### Enterprise Benefits: Unified Visibility
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### Benefits: Unified Visibility
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The GitHub-native workflow provides critical advantages for enterprise teams:
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