TherapyBridge

AI-powered therapy session transcription and analysis platform

Transform therapy sessions into actionable insights with automatic transcription, speaker diarization, and intelligent analysis.

---

🚀 Quick Start (Local Development)

Prerequisites

• Node.js 20+
• Supabase account (free tier)
• OpenAI API key

Setup

1. Clone and install

   git clone <your-repo>
   cd "peerbridge proj/frontend"
   npm install

2. Configure environment

   # Edit frontend/.env.local with your credentials:
   # - NEXT_PUBLIC_SUPABASE_URL
   # - NEXT_PUBLIC_SUPABASE_ANON_KEY
   # - OPENAI_API_KEY

3. Set up Supabase

   • Create project at supabase.com
   • Run supabase/schema.sql in SQL Editor
   • Copy URL and anon key to .env.local

4. Run development server

   npm run dev

   Open http://localhost:3000/patient/dashboard-v3

---

📦 Deployment (Hackathon-Ready)

Deploy in 10 minutes: See RAILWAY_DEPLOYMENT.md

Stack:

• ✅ Railway - Next.js hosting + backend support ($5 FREE credit)
• ✅ Supabase - PostgreSQL + file storage (FREE)
• ⚠️ OpenAI - Whisper API + GPT-4 (~$0.40 per session)

Why Railway over Vercel: Transparent pricing, no dark patterns, developer-first platform

---

✨ Features

Patient Dashboard

• Session Timeline - Chronological view of all therapy sessions
• AI Chat (Dobby) - Ask questions about your therapy journey
• Notes & Goals - Track progress and treatment plans
• Progress Patterns - Visualize mood and topic trends
• Upload Page - Drag-drop audio files for processing

Audio Processing

• Automatic Transcription - OpenAI Whisper API (accurate, fast)
• Speaker Diarization - Identify Therapist vs. Client
• Session Analysis - GPT-4 extracts:
  • Overall mood/tone
  • Main topics discussed
  • Key insights
  • Action items
  • Brief summary

Real-Time Progress

• Live progress bar during processing
• Status polling every 2 seconds
• Estimated completion time

---

🏗️ Architecture

┌─────────────────────────────────┐
│   Next.js 16 + React 19         │
│   (Deployed on Railway)         │
│   - App Router                  │
│   - Server Components           │
│   - API Routes                  │
└───────────┬─────────────────────┘
            │
            ├─► Supabase
            │   - PostgreSQL (sessions, users, notes)
            │   - Storage (audio files)
            │   - Row Level Security
            │
            └─► OpenAI APIs
                - Whisper (transcription)
                - GPT-4 (analysis)

Database Schema

Core Tables:

• users - Therapists and patients
• patients - Extended patient info
• therapy_sessions - Session metadata + results
• session_notes - AI-extracted clinical notes
• treatment_goals - Goal tracking

Storage:

• audio-sessions bucket - Uploaded audio files

---

Project Structure

peerbridge proj/
├── frontend/                      # Next.js application
│   ├── app/
│   │   ├── api/                   # Serverless API routes
│   │   │   ├── upload/            # File upload endpoint
│   │   │   ├── process/           # Audio processing
│   │   │   ├── status/[id]/       # Status polling
│   │   │   └── trigger-processing/ # Async trigger
│   │   └── patient/dashboard-v3/  # Main dashboard
│   │       ├── upload/            # Upload page
│   │       └── components/        # UI components
│   ├── lib/
│   │   ├── supabase.ts            # Supabase client + types
│   │   └── api-client.ts          # API helpers
│   └── package.json
│
├── audio-transcription-pipeline/  # Original pipeline (reference)
│   ├── src/
│   │   ├── pipeline.py            # CPU/API pipeline
│   │   └── pipeline_gpu.py        # GPU pipeline (legacy)
│   └── ui-web/                    # React UI (reference)
│
├── supabase/
│   └── schema.sql                 # Database schema
│
├── DEPLOYMENT.md                  # Deployment guide
└── README.md                      # This file

Quick Start

Each project is self-contained with its own:

• Virtual environment (venv/)
• Dependencies (requirements.txt)
• Configuration (.env, .python-version)
• Tests and documentation

Run Pipeline:

cd audio-transcription-pipeline
source venv/bin/activate
python tests/test_full_pipeline.py

Run Backend:

cd backend
source venv/bin/activate
uvicorn app.main:app --reload

Documentation

• Master documentation: Project MDs/TherapyBridge.md (start here!)
• Organization rules: .claude/CLAUDE.md
• Orchestration methodology: .claude/DYNAMIC_WAVE_ORCHESTRATION.md
• Pipeline docs: audio-transcription-pipeline/README.md
• Backend docs: backend/README.md
• Frontend docs: frontend/README.md

Environment Setup

Each project needs its own .env file:

Pipeline:

cd audio-transcription-pipeline
cp .env.example .env
# Edit .env with your OpenAI and HuggingFace keys

Backend:

cd backend
cp .env.example .env
# Edit .env with your database URL and OpenAI key

Repository Organization

This repo follows strict organization rules (see .claude/CLAUDE.md):

• Minimize file count
• One README per component
• No implementation plans (execute and delete)
• No duplicate configs
• Value over volume

Tech Stack

• Transcription: OpenAI Whisper API / faster-whisper (GPU)
• Diarization: pyannote.audio 3.1
• Backend: FastAPI + PostgreSQL (Neon)
• AI Extraction: OpenAI GPT-4o
• Frontend: Next.js 16 + React 19 + Tailwind CSS

Development

Each project has independent development:

• Separate virtual environments
• Separate dependencies
• Separate test suites
• Can be deployed independently

License

Proprietary - TherapyBridge Project