TestPilot AI 🚀

An AI-Powered REST API Test Case Generator

TestPilot AI is a full-stack web application designed to automate the creation of API test cases. By simply providing an HTTP method, endpoint, and a brief description, the application uses Groq AI (Llama 3.1) to instantly generate structured positive, negative, and validation test cases.

This project was built to demonstrate backend API integration, prompt engineering, and clean, layered architecture in Java & Spring Boot.

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🎯 Project Highlights

1. AI Integration via RESTful APIs: Instead of using bulky SDKs, the backend communicates directly with Groq's high-speed OpenAI-compatible REST API using Spring's RestTemplate.
2. Robust JSON Parsing Strategy: Large Language Models (LLMs) can sometimes return unpredictable formats (like markdown code blocks). The backend uses a custom, multi-step parsing strategy (Regex + Jackson ObjectMapper) to guarantee the frontend never crashes due to bad AI output.
3. Prompt Engineering: The AI is strictly instructed via a carefully designed system prompt to generate specific edge-cases (like 1-character boundaries, nulls, and empty fields) and output them in a strict JSON schema.
4. Clean Architecture: The Java backend strictly follows a layered architecture (Controller → Service → API layer) using Data Transfer Objects (DTOs) to decouple the AI response from the client payload.

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⚙️ How it Works (The Architecture)

System Architecture Diagram

graph TD
    Client[React Frontend] -->|JSON Request| Controller[TestCaseController]
    Controller -->|DTO| Service[TestCaseService]
    Service -->|Prompt Builder| LLMService[Groq Service]
    LLMService -->|REST API Call| Groq[Groq Llama 3.1]
    Groq -->|Raw JSON Text| LLMService
    LLMService -->|Regex + Jackson Parse| Service
    Service -->|Structured DTO| Controller
    Controller -->|JSON Response| Client

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Project Structure

SmartAPITester/
├── backend/                  # Spring Boot Java Application
│   ├── src/main/java/.../testpilot/
│   │   ├── controller/       # Exposes REST endpoints to React
│   │   ├── dto/              # Data Transfer Objects (Request/Response)
│   │   ├── exception/        # Global Error Handling
│   │   └── service/          # Business logic & AI Prompt Engineering
│   └── src/main/resources/   # App Config & Environment Variables
│
└── frontend/                 # React UI Application
    ├── src/
    │   ├── components/       # InputForm & ResultSection (Postman UI)
    │   ├── services/         # Axios API Client
    │   ├── App.jsx           # Main State Manager
    │   └── index.css         # Global Theme Variables
    └── package.json          # Node Dependencies

Data Flow

1. The Request: The user enters API details in the React frontend (Postman-inspired UI).
2. The Controller: The React app sends a JSON payload to the Spring Boot TestCaseController.
3. The Prompt: The TestCaseService takes the user data and injects it into a strict instruction prompt engineered for a Senior QA Engineer persona.
4. The AI Call: The GeminiService (now powered by Groq) sends the prompt to the Groq LLM API.
5. The Parsing: The backend receives a raw text response, strips away any markdown artifacts, and safely deserializes the string into Java objects (TestCaseResponse).
6. The Result: The frontend receives the clean JSON and displays it in a 3-column grid, allowing the user to download the final test suite.

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🛠️ Tech Stack

Backend (The Core)

• Java 21
• Spring Boot (Web starter)
• Maven (Dependency management)
• Groq API (Llama 3.1 8B Instant Model)
• Jackson (JSON serialization/deserialization)

Frontend (The UI)

• React 18 (Built with Vite)
• Axios (HTTP client for connecting to the backend)
• Vanilla CSS (Custom Postman-inspired dark theme)

(Note: To keep the project lightweight and focused purely on AI integration, there is no database, no authentication, and no heavy UI frameworks like Tailwind or Material UI).

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🚀 Local Setup Instructions

Want to run this on your own machine? Follow these steps:

1. Prerequisites

• Java 21+ installed
• Node.js & npm installed
• A free Groq API Key

2. Start the Backend (Spring Boot)

Open a terminal, navigate to the backend folder, and set your API key as an environment variable:

Windows (PowerShell):

$env:GROQ_API_KEY="gsk_your_api_key_here"
mvn spring-boot:run

Mac/Linux:

export GROQ_API_KEY="gsk_your_api_key_here"
mvn spring-boot:run

The backend will start on http://localhost:8080

3. Start the Frontend (React)

Open a second terminal, navigate to the frontend folder, and run:

npm install
npm run dev

The frontend will open at http://localhost:5173

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🔮 Future Enhancements

• Web Deployment: Deploy the frontend and backend to the web so users can access the tool publicly without local setup.