ClarifAI is an intelligent requirement management system designed to help Product Managers (PMs) better formulate and refine product requirements, enabling researchers and data scientists to solve problems more efficiently.

• Support for multi-role login (PM/Researcher)
• Test accounts provided:
  • PM account: pm@test.com / password123
  • Researcher account: researcher@test.com / password123

• Business goal and data scope definition
• File upload support
• Expected output selection
• Timeline setting
• AI intelligent feedback based on Azure OpenAI (GPT-4o-mini)
• "Verify Requirement" feature for real-time AI analysis
• Requirement Scorecard including:
  • Clarity
  • Feasibility
  • Completeness

• View requirement details
• Provide solutions
• Interactive discussion with PMs

• Backend: Flask
• Frontend: HTML + CSS + JavaScript
• Database: PostgreSQL
• AI Model: Azure OpenAI GPT-4o-mini for requirement analysis

ClarifAI/
├── app/
│   ├── __init__.py         # Flask application initialization
│   ├── routes.py           # Flask routes
│   ├── database.py         # Database configuration
│   ├── ai_service.py       # Azure OpenAI integration
│   ├── models/             # Data models
│   ├── static/             # Static files
│   └── templates/          # HTML templates
├── requirements.txt        # Project dependencies
├── .env                    # Environment variables (not tracked by Git)
├── config.py               # Application configuration
└── README.md               # Project documentation

1. Install dependencies:

pip install -r requirements.txt

2. Configure Azure OpenAI: Create a .env file in the root directory with the following content:

# Azure OpenAI API Configuration
AZURE_OPENAI_ENDPOINT=your_azure_openai_endpoint
AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_API_VERSION=2023-05-15
AZURE_OPENAI_DEPLOYMENT=gpt-4o-mini

# PostgreSQL Configuration
POSTGRES_SERVER=localhost
POSTGRES_USER=postgres
POSTGRES_PASSWORD=your_password
POSTGRES_DB=clarifai

3. Initialize the database:

flask db init
flask db migrate
flask db upgrade
python init_db.py

4. Run the application locally:

flask run

5. Access the system: Open your browser and go to http://localhost:5000

1. Create a PostgreSQL database on Azure:

   • Go to Azure Portal
   • Create a new Azure Database for PostgreSQL server
   • Configure firewall rules to allow your application

2. Configure Azure App Service:

   • Create a new Web App service
   • Set up deployment from Git repository or VS Code
   • Configure environment variables in App Service Configuration

3. Deploy the application:

az login
az webapp up --name YourAppName --resource-group YourResourceGroup --location "East US" --sku B1

4. Set environment variables in Azure:

   • Go to your App Service in Azure Portal
   • Navigate to Configuration > Application settings
   • Add all the environment variables from your .env file

5. Access your deployed app:

   • Open your browser and go to https://your-app-name.azurewebsites.net

1. Fill out all fields in the requirement form
2. Click the "Verify Requirement" button
3. The system will analyze your requirement using Azure OpenAI and provide:
   • Clarity Score
   • Feasibility Score
   • Completeness Score
   • Detailed feedback with suggestions for improvement
4. If the Clarity Score is at least 70%, the "Submit Requirement" button will be enabled
5. Make any necessary improvements based on the AI feedback
6. Submit the finalized requirement when ready