Quiet Mind

Overview

Quiet Mind is a modern web application that transforms journaling into a powerful tool for emotional self-awareness. Users write journal entries which are analyzed by AI to extract mood, sentiment scores, tags, and personalized advice.Key Features

1. AI-Powered Emotional Analysis

Write freely about your day, and our AI analyzes your entries to identify:

• Mood Detection: Happy, Sad, Anxious, or Neutral
• Sentiment Score: 1-5 scale indicating emotional positivity
• Smart Tags: Automatically extracted themes from your writing
• Personalized Advice: Empathetic, context-aware suggestions

2. Interactive Dashboard

• Real-time emotional overview with key metrics
• Mood trends visualization with interactive charts
• Recent entries at a glance
• Weekly/monthly statistics

3. Journal Entries Management

• Chronological list of all journal entries
• Quick mood indicators with color coding
• Sentiment scores at a glance
• Pagination for large datasets

4. AI Analysis Detail View

• Full entry content with AI analysis
• Mood and sentiment breakdown
• Auto-extracted themes as hashtags
• Personalized daily wisdom/advice

5. Analytics & Insights

• Mood distribution pie chart
• Top themes bar chart
• Journaling activity over time
• Streak tracking for consistency

6. Secure Authentication

• OAuth integration with Google and GitHub
• Secure session management with NextAuth.js v5
• User data synced to Supabase on sign-in

7. New Entry Creation

• Clean, focused writing experience
• Character counter (1000 max)
• Optional title field
• Instant AI analysis on save

8. Beautiful, Responsive UI

• Clean, minimalist design inspired by modern wellness apps
• Fully responsive across all devices
• Smooth animations and transitions
• Dark/light mode support ready

Tech Stack

Architecture

Data Flow

1. User writes a journal entry (max 1000 characters)
2. Server validates auth and daily limit (5 entries/day)
3. OpenAI GPT-4o-mini analyzes the text with structured prompts
4. Analysis result saved to Supabase diary_entries table
5. Dashboard updates with new insights and mood trends

Technical Challenges & Solutions

Challenge 1: Structured AI Responses

Problem: Getting consistent, parseable responses from GPT for mood analysis.

Solution: Implemented structured prompting with explicit JSON schema requirements and TypeScript validation:

Challenge 2: Real-time User Sync

Problem: Keeping user data in sync between NextAuth sessions and Supabase.

Solution: Used NextAuth callbacks to automatically create/update users in Supabase on sign-in, storing the Supabase user ID in the JWT token for subsequent requests.

Challenge 3: Rate Limiting & Abuse Prevention

Problem: Preventing API abuse while keeping the free tier accessible.

Solution: Implemented server-side validation for:

• Daily entry limits (5/day per user)
• Character limits (1000 chars max)
• Authentication checks on all API routes

Challenge 4: Type-Safe Full Stack

Problem: Maintaining type consistency between frontend and backend.

Solution: Centralized type definitions in lib/types.ts shared across the entire codebase, with Zod validation at API boundaries.

What I Learned

• Next.js 16 App Router: Deep dive into server components, route groups, and the latest React Server Components patterns
• NextAuth.js v5 Beta: Working with cutting-edge authentication patterns and JWT strategies
• OpenAI API Integration: Prompt engineering for consistent structured outputs
• Supabase: Real-time database with row-level security policies
• Modern UI/UX: Building polished, accessible interfaces with shadcn/ui