Skip to content

Chima200057/RepLog

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

55 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

RepLog. 🦾✨

The AI-Powered Coaching Journal for Elite Athletes and Creators.

RepLog is a high-performance web application designed for the IBM WatsonX Hackathon 2026. It transforms raw practice logs into actionable coaching intelligence, powered by IBM's industry-leading Granite Foundation Models.


📽️ Project Overview

In a world of data overflow, athletes and creators often struggle to turn "practice volume" into "performance progress." RepLog bridges this gap by acting as a 24/7 AI coach. By analyzing training logs, sensory feedback, and performance metrics, RepLog provides structured, psychological, and technical feedback to help users achieve their "Peak Rep."


🎨 Design Philosophy: Glassmorphism 2.0

RepLog features a bespoke Glassmorphic UI designed for focus and flow:

  • Ultra-Modern Aesthetics: Translucent layers with dynamic blur effects and vibrant gradients.
  • Micro-Animations: Subtle transitions that provide tactile feedback without distraction.
  • Mobile First: Responsive architecture that works on the track, in the gym, or at the desk.

🚀 Core Features

🧠 IBM WatsonX "Bob" AI Coach

  • Granite-Powered Insights: Leveraging ibm/granite-3-8b-instruct to perform domain-specific analysis across sports, coding, and music.
  • Structured Coaching Loop: Every response follows a high-impact pattern:
    • 🎉 Small Wins: Immediate positive reinforcement.
    • 🔍 Pattern Observation: Identifying technical or mental trends.
    • 🎯 Next Practice Focus: Concrete, actionable steps for the next session.
  • Semantic Auto-Titling: Bob analyzes the start of your session and automatically generates a title to keep your history organized.

🧵 Multi-Session Architecture

  • Parallel Threads: Maintain separate coaching sessions for "Cardio," "Strength," and "Skill Work" simultaneously.
  • Persistence: For registered users, sessions are preserved across reloads with optimized local caching.
  • Session Management: Full control to resume, jump back to history, or delete old sessions.

📚 Professional Markdown Notebook

  • Drag-&-Drop Intelligence: Seamlessly drag coaching advice or previous logs directly into your persistent journal.
  • Read-Only for Guests: Default welcome guides are provided as read-only templates to ensure system integrity.
  • User-Scoped Storage: Implements prefix_userEmail storage logic to ensure multi-user data isolation on shared machines.

🛠️ Technical Architecture

Frontend: The High-Fidelity Interface

  • React (Vite): Lightning-fast HMR and build times.
  • Vanilla CSS: Custom design system built from the ground up (no generic frameworks).
  • Lucide Icons: Crisp, medical-grade iconography for professional appearance.
  • React-Markdown: Full support for GFM-enhanced coaching summaries.

Backend: The WatsonX Pipeline

  • Node.js / Express: Secure proxy layer to mask API credentials.
  • IBM WatsonX AI SDK: Direct integration with @ibm-cloud/watsonx-ai.
  • Robust Parsing Engine: Custom regex-based JSON extractor that handles truncated or malformed LLM responses gracefully.

🏁 Getting Started

1. Prerequisites

  • Node.js v18 or higher.
  • IBM Cloud Account with a WatsonX.ai project instance.

2. Deployment Setup

Create a .env file in the root directory:

IBM_CLOUD_API_KEY=your_ibm_api_key
IBM_PROJECT_ID=your_watsonx_project_id
PORT=3001

3. Installation & Launch

# 1. Install dependencies
npm install

# 2. Launch the AI Backend (Terminal 1)
node server/index.js

# 3. Launch the Frontend (Terminal 2)
npm run dev

📖 Feature Guides


🏆 Hackathon Submission Notes

  • Innovation: Real-time conversion of unstructured practice logs into structured coaching plans.
  • Reliability: Implements robust error handling for AI inference and secure authentication workflows.
  • Scalability: Designed for multi-user expansion while maintaining strict data privacy via user-scoped storage.

Created with 🦾 by Team Vireon for the IBM WatsonX Hackathon 2026. "Optimize every rep. Log every gain."

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors