In the legends of Greek mythology, the god Hermes was gifted the Talaria—golden winged sandals that granted him the power of flight, swiftness, and the ability to journey between worlds. They symbolized speed, agility, and the divine gift of connection.
Project Talaria carries this spirit into the modern age. Just as Hermes used the Talaria to bridge the realms of gods and mortals, this innovation bridges the gap between human movement and deeper self-awareness. By embedding intelligence into footwear, Project Talaria transforms every step into insight—tracking motion, stride, and heart rhythm to empower individuals with knowledge about their health, vitality, and performance.
Project Talaria is more than technology; it is a call to elevate human potential. It embodies the timeless pursuit of strength, speed, and balance, inspiring us to not only move forward but to move with purpose. Through every stride, it reminds us that like Hermes, we too can transcend limits and walk closer to greatness.
This directory contains comprehensive documentation for the Talaria project.
| Document | Description | When to Read |
|---|---|---|
| SETUP.md | Complete setup instructions | First time setup |
| DEPLOYMENT.md | Deploy to production (Vercel) | When deploying |
| Document | Description | When to Read |
|---|---|---|
| ARCHITECTURE.md | System architecture & design | Understanding the codebase |
| ML_MODELS.md | Machine learning integration | Working with predictions |
| Document | Description | When to Read |
|---|---|---|
| CHANGELOG.md | Version history & updates | Tracking changes |
- New to the project? → Start with SETUP.md
- Understanding the code? → Read ARCHITECTURE.md
- Working with ML? → Check ML_MODELS.md
- Deploying? → Follow DEPLOYMENT.md
- Review ARCHITECTURE.md for component structure
- Check CHANGELOG.md for recent updates
- Follow setup in SETUP.md
- DEPLOYMENT.md - Vercel deployment guide
- SETUP.md - Environment configuration
docs/
├── README.md # This file - documentation index
├── SETUP.md # Setup guide (Firebase, Vertex AI, local dev)
├── DEPLOYMENT.md # Vercel deployment & production checklist
├── ARCHITECTURE.md # System architecture & tech stack
├── ML_MODELS.md # ML integration & API documentation
└── CHANGELOG.md # Version history & updates
# 1. Read SETUP.md
# 2. Configure Firebase
# 3. Set up environment variables
# 4. Run npm install
# 5. Start dev server: npm run dev# 1. Read DEPLOYMENT.md
# 2. Connect GitHub to Vercel
# 3. Configure environment variables in Vercel
# 4. Deploy# 1. Read ML_MODELS.md
# 2. Set up Vertex AI credentials
# 3. Test predictions locally
# 4. Deploy with service account| Issue | Solution Document |
|---|---|
| Setup problems | SETUP.md - Troubleshooting |
| Deployment errors | DEPLOYMENT.md - Troubleshooting |
| ML predictions not working | ML_MODELS.md - Troubleshooting |
| Architecture questions | ARCHITECTURE.md |
- Next.js Docs: nextjs.org/docs
- Firebase Docs: firebase.google.com/docs
- Vertex AI Docs: cloud.google.com/vertex-ai/docs
- Vercel Docs: vercel.com/docs
When updating documentation:
- Keep it current - Update docs when code changes
- Be clear - Use simple language
- Add examples - Include code snippets and screenshots
- Test instructions - Verify setup steps work
- Update README - Keep this index current
- Use Markdown formatting
- Include code examples with syntax highlighting
- Add table of contents for long documents
- Use emojis sparingly for visual cues
- Keep line length reasonable (80-100 chars)
- Update "Last Updated" date when editing
| Event | Update Required |
|---|---|
| New feature added | CHANGELOG.md, ARCHITECTURE.md |
| Deployment process changes | DEPLOYMENT.md |
| Setup steps change | SETUP.md |
| ML model updated | ML_MODELS.md |
| Dependencies updated | SETUP.md, package.json |
| API changes | ML_MODELS.md, ARCHITECTURE.md |
Questions? Open an issue on GitHub or contact the development team.
Last Updated: October 2025
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