Q-Ace AI - Quality Assurance AI Assistant

Q-Ace AI is a powerful, AI-driven suite of tools designed to streamline quality assurance workflows and enhance testing efficiency. Built with Python and Streamlit, it leverages Google's Gemini LLM to automate tedious QA tasks, providing structured insights and improving communication across development teams.

🚀 Key Features (AI Modules)

🐞 Bug Polisher

Convert messy notes and informal bug descriptions into professional, structured, and JIRA-ready reports. Q-Ace AI identifies steps to reproduce, expected vs. actual results, and severity.

📊 Test Analyzer

Analyze test logs and patterns with visual charts. Upload test reports in various formats to get instant AI-driven insights and recurring failure patterns.

📝 Test Summary

Create executive summaries from raw test run data. Generate concise reports including key metrics and major issues, perfect for stakeholders.

🔌 API Designer

Generate Postman tests and documentation directly from OpenAPI/Swagger specifications. Seamlessly understand API structures and generate relevant test scenarios.

🧠 Logic Auditor

Perform sanity checks for requirement consistency. Ensure that your project requirements are logical, consistent, and free of contradictions.

🏆 STR Master

Consolidated Software Test Results. Aggregate and manage test results from multiple sources into a single, unified view for better decision-making.

🎲 Data Generator

Generate synthetic edge-case test data. Create high-quality, relevant data for complex testing scenarios and edge cases.

👁️ UI Inspector

AI Vision-powered interface analysis. Use advanced computer vision to analyze user interfaces, detect visual bugs, and ensure design consistency.

🛠 ️ Tech Stack

Frontend: Streamlit (with TailwindCSS integration)
Backend: FastAPI, Python
AI Engine: Google Gemini AI (Vertex AI/Generative AI)
Database: SQLAlchemy (SQLite)
Processing: PyMuPDF (PDF), Pillow (Images), Pydantic (Data Validation)

📋 Installation & Setup

Clone the repository:

git clone https://github.com/your-repo/q-ace-ai.git
cd q-ace-ai

Run Installation Scripts:
- Windows: Double-click install_windows.bat or run:
```
.\install_windows.bat
```
- Mac/Linux:
```
chmod +x install_mac_linux.sh
./install_mac_linux.sh
```
Configure Environment: Create a .env file in the root directory and add your Google Gemini API Key:
```
GOOGLE_API_KEY=your_api_key_here
```
Run the Application:
- Windows: Double-click run_windows.bat or run:
```
.\run_windows.bat
```
- Mac/Linux:
```
./run_mac_linux.sh
```

📂 Project Structure

app.py: Main Streamlit application entry point.
app/: Core application logic and FastAPI backend.
utils/: Utility modules for Gemini interaction, OpenAPI parsing, and exports.
static/: Static assets (images, CSS).
templates/: AI prompt templates.
requirements.txt: Python dependencies.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Built with ❤️ by ATID College

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