AI Scrum Master - Web-Based Virtual Assistant

A comprehensive web application that acts as a virtual AI Scrum Master, automating Scrum Master responsibilities while keeping humans in the loop for oversight.

🚀 Features

• Automated Daily Standups: AI-powered standup summaries from Slack and Jira
• Intelligent Backlog Grooming: Auto-refinement of user stories with duplicate detection
• Sprint Planning Assistance: Data-driven sprint recommendations and capacity analysis
• Burndown Charts & Velocity Tracking: Automated progress monitoring and reporting
• Multi-Tool Integration: Seamless integration with Jira, Slack, GitHub, and more
• Human-in-the-Loop: AI suggestions with human oversight and approval

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   React Frontend │    │  FastAPI Backend │    │  External APIs  │
│   (TypeScript)   │◄──►│    (Python)      │◄──►│ Jira/Slack/Git │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                              │
                              ▼
                    ┌──────────────────┐
                    │   AI Engine      │
                    │ GPT-4 + LangChain│
                    └──────────────────┘
                              │
                              ▼
                    ┌──────────────────┐
                    │  Vector DB +     │
                    │  PostgreSQL      │
                    └──────────────────┘

🛠️ Tech Stack

• Backend: Python, FastAPI, SQLAlchemy, Celery
• Frontend: React, TypeScript, Material-UI
• AI/LLM: OpenAI GPT-4, LangChain
• Database: PostgreSQL, ChromaDB/Pinecone (Vector DB)
• Integrations: Atlassian API, Slack SDK, GitHub API
• Infrastructure: Docker, Redis, nginx

🚦 Quick Start

Prerequisites

• Docker & Docker Compose (recommended)
• Python 3.11+ (for local development)
• OpenAI API Key (required)

Fastest Setup (MVP Ready in 5 minutes!)

1. Clone and configure:

git clone <repository-url>
cd scrum
cp backend/.env.example backend/.env
# Edit backend/.env with your OpenAI API key

2. Start everything with Docker:

docker-compose up -d --build

3. Test the MVP:

python scripts/test_mvp.py

4. Access the system:
   • API Docs: http://localhost:8000/docs
   • Health Check: http://localhost:8000/health
   • Generate standup summary via API

Manual Setup (Development)

# Backend
cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload

# In another terminal - start PostgreSQL and Redis
docker-compose up postgres redis -d

Environment Variables

Create a .env file with the following:

# OpenAI
OPENAI_API_KEY=your_openai_api_key

# Database
DATABASE_URL=postgresql://user:password@localhost:5432/scrum_db

# Slack
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_SIGNING_SECRET=your_slack_signing_secret

# Jira
JIRA_URL=https://your-domain.atlassian.net
JIRA_USERNAME=your_jira_email
JIRA_API_TOKEN=your_jira_api_token

# GitHub (optional)
GITHUB_TOKEN=your_github_token

# Redis
REDIS_URL=redis://localhost:6379

🏃‍♂️ Development

Backend Development

cd backend
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Frontend Development

cd frontend
npm start

Running Tests

# Backend tests
cd backend && python -m pytest

# Frontend tests  
cd frontend && npm test

📋 Development Phases

• Phase 1: Project Infrastructure Setup ✅
• Phase 2: Core MVP (Basic Standup Summary) ✅
• Phase 3: Backlog Grooming Assistant (API Ready)
• Phase 4: Sprint Planning Automation (Foundation Built)
• Phase 5: Burndown Charts & Reporting
• Phase 6: Advanced Integrations
• Phase 7: UI/UX Enhancements
• Phase 8: Production Deployment

🎉 MVP Status: COMPLETE!

The core AI Scrum Master is now functional with:

• ✅ AI-powered standup summary generation
• ✅ Slack & Jira integrations
• ✅ Vector database for context storage
• ✅ Comprehensive API endpoints
• ✅ Docker containerization
• ✅ Automated testing suite

🔐 Security & Privacy

• OAuth 2.0 for all third-party integrations
• Encrypted storage of API tokens
• Data anonymization for LLM processing
• Audit logging for all AI actions
• GDPR compliance features

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support and questions, please open an issue in the GitHub repository or contact the development team.