Hard Word Extractor - Project Outline & Progress Tracker

Last Updated: October 12, 2025
Current Phase: Phase 1 (MVP)
Overall Progress: 95% Complete
Status: ✅ Backend Complete | ✅ Frontend Complete | ✅ Docker Complete | ❌ Testing Pending

📋 Important Documentation Files

This project has multiple documentation files that should be kept updated:

PROJECT_OUTLINE.md (this file) - Complete task breakdown with checkboxes
docs/API.md - Complete REST API documentation (✅ Complete - update when adding endpoints)
docs/SETUP.md - Development setup guide (✅ Complete - update when adding setup steps)
README.md - Project overview (✅ Complete - update with new features)
docs/DOCKER-QUICKSTART.md - Docker deployment quick start guide (✅ Complete)
docs/DOCKER.md - Docker detailed reference (✅ Complete)

Note: When adding new features, update relevant documentation files.

🎯 Project Overview

Project Name: Hard Word Extractor
Purpose: A web application that processes audio/video files to extract and classify vocabulary words by CEFR language levels (A1-C2), providing transcription and vocabulary analysis for language learners.

Tech Stack

Backend: Django 5.2+ with Django REST Framework
Frontend: React 18+ with TypeScript, Material-UI
AI/ML: OpenAI Whisper (local), Groq API (Phase 1), Local LLM (Phase 3)
Task Queue: Celery with Redis
Database: PostgreSQL (production), SQLite (development)
Deployment: Docker, Docker Compose
Server: Gunicorn + Nginx

Key Features

✅ Audio transcription with word-level timestamps
✅ CEFR level classification (A1-C2)
✅ Word context extraction
✅ Vocabulary statistics and analytics
✅ Interactive results display
❌ Video support (Phase 2)
❌ User authentication (Phase 2)
❌ Local LLM (Phase 3)

📊 Overall Progress Summary

Phase 1: MVP (95% Complete) ⏳

✅ Backend (100%)
✅ API (100%)
✅ Frontend (95%)
✅ Docker (100%)
❌ Testing (0%)

Phase 2: Enhanced Features (0% Complete) ❌

Not started

Phase 3: Full Local Processing (0% Complete) ❌

Not started

Phase 4: Production Ready (0% Complete) ❌

Not started

🚀 PHASE 1: MVP - CURRENT PHASE

Goal: Create a functional prototype with core features using external APIs where necessary.

Completion: 88% ✅✅✅✅✅✅✅✅▒▒

1. PROJECT SETUP & ARCHITECTURE (100% Complete ✅)

1.1 Initialize Project Structure ✅

1.1.1 Create main project directory structure

HardWordExtractor/
├── backend/          ✅
├── frontend/         ✅
├── docker/           ✅ (empty)
├── docs/             ✅
├── scripts/          ✅ (empty)
├── .gitignore        ✅
├── .env.example      ✅
└── README.md         ✅

1.1.2 Initialize Git repository
- Create .gitignore for Python, Node.js, and Docker
- Create initial commits with project structure
1.1.3 Create documentation structure
- API documentation (docs/API.md)
- Development setup guide (docs/SETUP.md)
- README.md with project overview

Status: ✅ COMPLETE

1.2 Backend Setup - Django Project (100% Complete ✅)

1.2.1 Create Django project

Created config/ Django project
Created transcription/ Django app

Created requirements.txt with all dependencies:

Django>=4.2.0
djangorestframework>=3.14.0
django-cors-headers>=4.3.0
python-dotenv>=1.0.0
openai-whisper>=20231117
groq>=0.4.0
celery>=5.3.0
redis>=5.0.0
psycopg2-binary>=2.9.9
gunicorn>=21.2.0
spacy>=3.7.0
pytest>=7.4.0
pytest-django>=4.5.0

1.2.2 Configure Django settings
- Created config/settings/ directory
- Split settings into: base.py, development.py, production.py, __init__.py
- Configured CORS settings
- Set up media file handling for uploads
- Configured REST framework
- Configured logging
1.2.3 Set up environment variables
- Created .env.example file with all required variables
- Configured environment-based settings

Status: ✅ COMPLETE

1.3 Database Configuration (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/models.py (5 models, ~200 lines)

1.4 Celery Configuration (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/config/celery.py
backend/config/__init__.py (updated)

1.5 Admin Interface (100% Complete ✅)

1.5.1 Register models in admin
- AudioFileAdmin - File management interface
  - Custom list display with file size in MB
  - Status filtering
  - Processing time calculation
  - Organized fieldsets
- TranscriptionAdmin - Transcription management
  - Language filtering
  - Word count display
  - Full text search
- WordAdmin - Word database management
  - CEFR level filtering with color badges
  - Frequency display
  - Search by word or lemma
- ExtractedWordAdmin - Word occurrence management
  - Context display
  - Timestamp and position tracking
- WordStatisticsAdmin - Statistics overview
  - Level distribution display
  - Total word calculations

Status: ✅ COMPLETE

Files Created:

backend/transcription/admin.py (~150 lines)

2. BACKEND CORE FEATURES (100% Complete ✅)

2.1 Whisper Integration (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/services/whisper_service.py (~150 lines)

2.2 Groq LLM Integration (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/services/groq_service.py (~200 lines)

2.3 Word Extraction and Processing (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/services/word_processor.py (~300 lines)
backend/transcription/services/__init__.py

2.4 Celery Tasks (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/tasks.py (~300 lines)

3. REST API (100% Complete ✅)

3.1 API Serializers (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/serializers.py (~160 lines)

3.2 API Views (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/transcription/views.py (~270 lines)

3.3 URL Configuration (100% Complete ✅)

3.3.1 Create app URLs
- Created transcription/urls.py
- Registered ViewSets with router
- Added custom endpoints
3.3.2 Configure main URLs
- Updated config/urls.py
- Included app URLs under /api/
- Added admin URLs
- Configured media file serving for development

3.3.3 URL structure created:

/api/                                     - API root
/api/upload/                              - Upload audio
/api/status/<id>/                         - Check status
/api/audio/                               - List audio files
/api/audio/<id>/                          - Audio details
/api/audio/<id>/status/                   - Status action
/api/transcriptions/                      - List transcriptions
/api/transcriptions/<id>/                 - Transcription details
/api/transcriptions/<id>/words/           - Get words (with CEFR filter)
/api/transcriptions/<id>/statistics/      - Get statistics
/api/words/                               - List all words
/api/words/<id>/                          - Word details
/admin/                                   - Django admin

Status: ✅ COMPLETE

Files Created:

backend/transcription/urls.py
backend/config/urls.py (updated)

3.4 API Documentation (100% Complete ✅)

Status: ✅ COMPLETE

Note: Keep API.md updated when adding new endpoints.

4. FRONTEND DEVELOPMENT (95% Complete ✅)

4.1 React Project Setup (100% Complete ✅)

4.1.1 Create React app
- Created React app with TypeScript template
- Cleaned up boilerplate code
4.1.2 Install dependencies
- Installed Axios for API calls
- Installed React Router for navigation
- Installed Material-UI (@mui/material, @emotion/react, @emotion/styled)
- Installed MUI Icons (@mui/icons-material)
4.1.3 Configure environment
- Created .env file with REACT_APP_API_URL
- Configured for development

4.1.4 Set up project structure

src/
├── components/      ✅ - Reusable components
├── pages/           ✅ - Page components
├── services/        ✅ - API services
├── hooks/           ✅ - Custom React hooks (directory created)
├── types/           ✅ - TypeScript interfaces
├── utils/           ✅ - Utility functions
├── theme/           ✅ - MUI theme configuration
└── App.tsx          ✅ - Main app component

Status: ✅ COMPLETE

Files Created:

frontend/.env
frontend/src/types/
frontend/src/services/
frontend/src/components/
frontend/src/pages/
frontend/src/utils/
frontend/src/theme/

4.2 TypeScript Types & Interfaces (100% Complete ✅)

4.2.1 Create types file
- Created src/types/index.ts

4.2.2 Define TypeScript interfaces

interface AudioFile {
  id: number;
  original_filename: string;
  file_size_mb: number;
  duration?: number;
  status: 'pending' | 'processing' | 'transcribing' | 'analyzing' | 'completed' | 'failed';
  error_message?: string;
  uploaded_at: string;
  processing_time?: number;
}

interface Transcription {
  id: number;
  audio_file: AudioFile;
  text: string;
  language: string;
  word_count: number;
  unique_word_count: number;
  statistics?: WordStatistics;
}

interface Word {
  id: number;
  text: string;
  lemma: string;
  cefr_level: string;
  cefr_level_display: string;
  global_frequency: number;
}

interface ExtractedWord {
  id: number;
  word: Word;
  context: string;
  timestamp?: number;
  position: number;
  frequency: number;
}

interface WordStatistics {
  id: number;
  a1_count: number;
  a2_count: number;
  b1_count: number;
  b2_count: number;
  c1_count: number;
  c2_count: number;
  unknown_count: number;
  total_words: number;
  level_distribution: {
    A1: number;
    A2: number;
    B1: number;
    B2: number;
    C1: number;
    C2: number;
    Unknown: number;
  };
}

interface ProcessingStatus {
  id: number;
  status: string;
  progress: number;
  error_message?: string;
  has_transcription: boolean;
  transcription_id?: number;
}

Status: ✅ COMPLETE

Files Created:

frontend/src/types/index.ts (~90 lines with all interfaces including AudioFile, Transcription, Word, ExtractedWord, WordStatistics, ProcessingStatus, UploadResponse, ApiError)

4.3 API Service Layer (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

frontend/src/services/api.ts (~45 lines)
frontend/src/services/audioService.ts (~105 lines)

4.4 Core Components (100% Complete ✅)

Priority: HIGH - These are the main UI components

Status: ✅ COMPLETE

Files Created:

frontend/src/components/AudioUpload.tsx (~180 lines)
frontend/src/components/StatusIndicator.tsx (~140 lines)
frontend/src/components/TranscriptionView.tsx (~135 lines)
frontend/src/components/WordList.tsx (~245 lines)
frontend/src/components/Statistics.tsx (~90 lines)
frontend/src/components/Layout.tsx (~35 lines)
frontend/src/components/Header.tsx (~30 lines)
frontend/src/components/Footer.tsx (~30 lines)

4.5 Pages (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

frontend/src/pages/Home.tsx (~55 lines)
frontend/src/pages/Results.tsx (~145 lines)
frontend/src/pages/NotFound.tsx (~45 lines)

4.6 Routing & App Configuration (100% Complete ✅)

Status: ✅ COMPLETE

Files Created/Updated:

frontend/src/App.tsx (updated, ~27 lines)
frontend/src/theme/theme.ts (~100 lines)
frontend/src/utils/helpers.ts (~150 lines with utility functions)

4.7 Testing & Polish (80% Complete ⏳)

Status: ⏳ NEEDS INTEGRATION TESTING (with backend running)

5. DOCKER CONFIGURATION (100% Complete ✅)

Priority: HIGH - Needed for deployment

Completion Date: October 11-12, 2025

5.1 Backend Dockerfile (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

backend/Dockerfile (production)
backend/Dockerfile.dev (development)
backend/.dockerignore

5.2 Frontend Dockerfile (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

frontend/Dockerfile (production)
frontend/nginx.conf
frontend/.dockerignore

5.3 Docker Compose (100% Complete ✅)

Status: ✅ COMPLETE

Files Created:

docker-compose.yml (production)
docker-compose.dev.yml (development)
Environment variables documented in docs/DOCKER-QUICKSTART.md

Performance:

Startup time: 30-40 seconds (all services)
Resource usage: 3.7GB RAM idle, ~5GB during transcription
Build time: 706s clean build, 30s with cache

5.4 Deployment Scripts (100% Complete ✅)

Status: ✅ COMPLETE (Integrated into Docker Compose)

Implementation:

Health checks defined in docker-compose.yml
Startup scripts integrated into Dockerfile entrypoints
Django migrations run automatically on backend startup
Static files collected automatically

Note: Traditional shell scripts replaced with Docker Compose orchestration and container entrypoints for better reliability and portability.

5.5 Deployment Documentation (100% Complete ✅)

Status: ✅ COMPLETE

Documentation Created:

docs/DOCKER-QUICKSTART.md (comprehensive, user-friendly guide)
docs/DOCKER.md (updated detailed reference)

Tested & Verified:

✅ Complete clean restart tested (docker compose down -v)
✅ All 5 services running healthy
✅ Whisper transcription working (version 20250625)
✅ Resource usage measured and documented
✅ Startup time: 30-40 seconds
✅ Build time: 706s clean, 30s cached

6. TESTING & QUALITY ASSURANCE (0% Complete ❌)

Priority: MEDIUM - Important but can be done in parallel

6.1 Backend Unit Tests (0% Complete ❌)

Status: ❌ NOT STARTED

Files to Create:

backend/conftest.py
backend/transcription/tests/test_models.py
backend/transcription/tests/test_services.py
backend/transcription/tests/test_api.py

6.2 Frontend Unit Tests (0% Complete ❌)

Status: ❌ NOT STARTED

6.3 Integration Testing (0% Complete ❌)

Status: ❌ NOT STARTED

7. DOCUMENTATION & FINAL POLISH (50% Complete ⏳)

7.1 Development Documentation (100% Complete ✅)

Status: ✅ COMPLETE

Note: Keep README.md and SETUP.md updated with new features.

7.2 Deployment Documentation (0% Complete ❌)

Status: ❌ NOT STARTED

Files to Create:

docs/DEPLOYMENT.md

7.3 User Documentation (0% Complete ❌)

Status: ❌ NOT STARTED

Files to Create:

docs/USER_GUIDE.md

8. FINAL INTEGRATION & LAUNCH (0% Complete ❌)

8.1 Final Testing (0% Complete ❌)

Status: ❌ NOT STARTED

8.2 Deployment to Server (0% Complete ❌)

Status: ❌ NOT STARTED

8.3 Post-Launch (0% Complete ❌)

Status: ❌ NOT STARTED

📊 PHASE 1 SUMMARY

Completion Status

Overall: 88% Complete

Backend Setup:        ████████████████████████████ 100% ✅
Database Models:      ████████████████████████████ 100% ✅
Backend Services:     ████████████████████████████ 100% ✅
Celery Tasks:         ████████████████████████████ 100% ✅
REST API:             ████████████████████████████ 100% ✅
Admin Interface:      ████████████████████████████ 100% ✅
Frontend Setup:       ████████████████████████████ 100% ✅
Frontend Dev:         ███████████████████████████▒  95% ✅
Docker Config:        ████████████████████████████ 100% ✅
Testing:              ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒   0% ❌
Documentation:        ███████████████████████████▒  95% ✅

What's Complete ✅

Project Foundation (100%)
- Directory structure
- Git repository
- Environment configuration
- Documentation structure
Backend (100%)
- Django project with split settings
- 5 database models
- Celery configuration
- Admin interface
- 3 backend services (Whisper, Groq, WordProcessor)
- 4 Celery tasks
- Complete REST API (11 endpoints)
- Serializers and views
- URL routing
Documentation (95%)
- README.md (updated with Docker)
- docs/API.md (complete)
- docs/SETUP.md (complete)
- docs/DOCKER-QUICKSTART.md (complete, 400+ lines)
- docs/DOCKER.md (complete, 600+ lines)
- docs/ARCHITECTURE.md (complete)
- docs/GROQ_SETUP.md (complete)
Frontend (95%)
- React app initialized with TypeScript
- All dependencies installed (Axios, React Router, MUI)
- TypeScript types and interfaces
- API service layer with error handling
- MUI theme with CEFR colors
- Utility helpers
- 8 components (AudioUpload, StatusIndicator, TranscriptionView, WordList, Statistics, Layout, Header, Footer)
- 3 pages (Home, Results, NotFound)
- Routing configured
- Responsive design implemented

What's Remaining ❌

Frontend (5%)
- Integration testing with backend (needs backend + Celery + Redis running)
- Minor UI refinements
Testing (0%)
- Backend unit tests
- Frontend unit tests
- Integration tests
- End-to-end tests
Testing (100%)
- Backend unit tests
- Frontend unit tests
- Integration tests
Final Launch (100%)
- Final testing
- Server deployment
- Monitoring setup

Time Estimates

Frontend Integration Testing: 30 minutes (with backend running)
Docker Configuration: 1-2 hours
Testing: 2-3 hours
Deployment & Polish: 1-2 hours

Total Remaining: ~4-8 hours to complete Phase 1 MVP

🚀 PHASE 2: ENHANCED FEATURES (Not Started)

Goal: Add video support, user authentication, and improved UX

Estimated Time: 2-3 weeks

Key Features to Add:

Video upload and audio extraction (FFmpeg)
User authentication (JWT)
User dashboard with processing history
Enhanced UI/UX with animations
Export functionality (PDF, CSV)
Word cloud visualization
Statistics charts

Status: ❌ NOT STARTED (will be detailed when Phase 1 is complete)

🔧 PHASE 3: FULL LOCAL PROCESSING (Not Started)

Goal: Replace external APIs with local solutions

Estimated Time: 2-3 weeks

Key Features to Add:

Status: ❌ NOT STARTED (will be detailed when Phase 2 is complete)

🌟 PHASE 4: PRODUCTION READY (Not Started)

Goal: Production-grade features and scaling

Estimated Time: 3-4 weeks

Key Features to Add:

Status: ❌ NOT STARTED (will be detailed when Phase 3 is complete)

📝 NEXT SESSION INSTRUCTIONS

If you need to resume this project, share this instruction:

"Read PROJECT_OUTLINE.md and continue with the unchecked tasks. Start with Section 5 (Docker Configuration) as backend and frontend are complete."

Current Focus:

Section 5: Docker Configuration (Backend + Frontend Dockerfiles, docker-compose.yml)
Section 6: Testing & Quality Assurance
Section 8: Final Integration & Launch

Priority Order:

Docker Configuration (Section 5) - HIGH PRIORITY
Integration Testing with Backend Running (Section 4.7.1)
Testing & QA (Section 6)
Final Launch (Section 8)

📈 SUCCESS METRICS

Phase 1 MVP Goals:

Backend can transcribe audio files
Words are classified by CEFR level
REST API is functional
Frontend displays results
Application is dockerized
Deployment documentation is complete

Code Quality:

🔑 KEY TECHNICAL DECISIONS

Whisper Model: Using 'base' model for MVP (good speed/accuracy balance)
LLM: Groq API for Phase 1 (fast), will replace with local LLM in Phase 3
Word Processing: Basic for MVP, optional spaCy for advanced features
Caching: Word classifications cached in database to reduce API calls
Batch Size: 50 words per Groq API call (balances efficiency and token limits)
Frontend: React + TypeScript + Material-UI for modern, type-safe UI
Deployment: Docker Compose for easy deployment and scaling

🐛 KNOWN ISSUES & TODOs

TODO in tasks.py: Calculate actual word position in transcription (line 228)
Missing spaCy model: Need to download en_core_web_sm if using spaCy
No authentication: Phase 2 will add JWT authentication
No rate limiting: Phase 2 will add rate limiting
Single language: English only, Phase 4 for multi-language
External API dependency: Groq API, Phase 3 for local LLM

📞 GETTING HELP

Resources:

API Documentation: docs/API.md
Setup Guide: docs/SETUP.md
Django Docs: https://docs.djangoproject.com/
React Docs: https://react.dev/
Material-UI: https://mui.com/

Common Commands:

Backend:

cd backend
source venv/bin/activate
python manage.py runserver          # Start Django
celery -A config worker -l info     # Start Celery
python manage.py shell               # Django shell
pytest                               # Run tests

Frontend:

cd frontend
npm start                            # Start dev server
npm test                             # Run tests
npm run build                        # Build for production

Docker:

docker-compose up --build            # Build and start all services
docker-compose down                  # Stop all services
docker-compose logs -f backend       # View backend logs
docker-compose ps                    # Check service status

Last Updated: October 8, 2025
Version: 1.1
Maintainer: Project Team

Status: ✅ Ready for Frontend Development!

END OF PROJECT OUTLINE Django>=4.2.0 djangorestframework>=3.14.0 django-cors-headers>=4.3.0 python-dotenv>=1.0.0 openai-whisper>=20231117 groq>=0.4.0 celery>=5.3.0 redis>=5.0.0 psycopg2-binary>=2.9.9 gunicorn>=21.2.0 ```

1.2.2 Create Django app for core functionality
- Run: python manage.py startapp transcription
- Register app in config/settings.py
1.2.3 Configure Django settings
- Create config/settings/ directory
- Split settings into: base.py, development.py, production.py
- Configure CORS settings
- Set up media file handling for uploads
- Configure REST framework
1.2.4 Set up environment variables
- Create .env.example file
- Add: SECRET_KEY, DEBUG, ALLOWED_HOSTS, GROQ_API_KEY, DATABASE_URL

Acceptance Criteria:

Django project runs successfully
Settings are properly configured
Environment variables are set up

1.3 Backend Setup - Database Configuration

Task: Configure PostgreSQL database

Steps:

1.3.1 Create database models
- Create transcription/models.py with:
  - AudioFile model (file, uploaded_at, status, user)
  - Transcription model (audio_file, text, language, created_at)
  - Word model (text, cefr_level, frequency)
  - ExtractedWord model (transcription, word, timestamp, context)
1.3.2 Create and run migrations
- Run: python manage.py makemigrations
- Run: python manage.py migrate
1.3.3 Create database indexes
- Add indexes for frequently queried fields
- Add full-text search indexes

Acceptance Criteria:

Models are created and migrated
Database schema is properly indexed

1.4 Backend Setup - Celery Configuration

Task: Set up Celery for asynchronous task processing

Steps:

1.4.1 Create Celery configuration
- Create config/celery.py
- Configure Celery with Redis broker
- Set up task routing
1.4.2 Create tasks module
- Create transcription/tasks.py
- Define task: process_audio_file
- Define task: transcribe_audio
- Define task: extract_and_classify_words
1.4.3 Configure Celery settings
- Set task time limits
- Configure result backend
- Set up task queues

Acceptance Criteria:

Celery is properly configured
Tasks can be queued and executed
Redis connection works

2. Backend Core Features

2.1 Whisper Integration

Task: Integrate local Whisper for audio transcription

Steps:

2.1.1 Create Whisper service module
- Create transcription/services/whisper_service.py
- Implement WhisperTranscriber class
- Add model initialization (use 'base' model for MVP)
- Implement transcription method with word-level timestamps
2.1.2 Handle audio file preprocessing
- Install ffmpeg for audio conversion
- Create audio format validation
- Implement audio file conversion to WAV
2.1.3 Implement transcription task
- Load audio file
- Run Whisper transcription
- Extract word-level timestamps
- Store transcription in database
2.1.4 Add error handling
- Handle unsupported audio formats
- Handle corrupted files
- Handle timeout scenarios
- Log errors properly

Acceptance Criteria:

Whisper successfully transcribes audio files
Word-level timestamps are captured
Errors are handled gracefully

2.2 Groq LLM Integration

Task: Integrate Groq API for word classification

Steps:

2.2.1 Create Groq service module
- Create transcription/services/groq_service.py
- Implement GroqClassifier class
- Configure API client with retry logic
2.2.2 Design prompt for word classification
- Create prompt template for CEFR classification
- Include context about CEFR levels (A1-C2)
- Request structured JSON output
- Example prompt:
```
Classify the following words by CEFR level (A1, A2, B1, B2, C1, C2).
Return JSON format: {"word": "level"}
Words: [list of words]
```
2.2.3 Implement word extraction and classification
- Extract unique words from transcription
- Filter out common stop words
- Batch words for API efficiency (max 50 words per request)
- Call Groq API with classification prompt
- Parse and validate JSON response
2.2.4 Implement caching mechanism
- Cache classified words in database
- Check cache before API calls
- Update cache with new classifications
2.2.5 Add rate limiting and error handling
- Implement exponential backoff
- Handle API rate limits
- Log API errors

Acceptance Criteria:

Words are successfully classified by CEFR level
Caching reduces API calls
Rate limiting prevents API errors

2.3 Word Extraction and Processing

Task: Implement word extraction and filtering logic

Steps:

2.3.1 Create word processing service
- Create transcription/services/word_processor.py
- Implement text tokenization
- Implement lemmatization (use spaCy or NLTK)
2.3.2 Implement filtering logic
- Remove punctuation and special characters
- Convert to lowercase
- Filter stop words
- Remove numbers
- Keep only alphabetic words
2.3.3 Extract word context
- For each word, extract surrounding sentence
- Store context with word reference
- Link to timestamp in audio
2.3.4 Calculate word statistics
- Count word frequency in transcription
- Calculate unique words
- Group by CEFR level

Acceptance Criteria:

Words are properly extracted and cleaned
Context is captured for each word
Statistics are calculated correctly

2.4 API Endpoints

Task: Create REST API endpoints for frontend

Steps:

2.4.1 Create serializers
- Create transcription/serializers.py
- AudioFileSerializer
- TranscriptionSerializer
- ExtractedWordSerializer
- WordStatisticsSerializer
2.4.2 Create API views
- Create transcription/views.py
- AudioFileUploadView (POST)
- TranscriptionDetailView (GET)
- WordsByLevelView (GET)
- ProcessingStatusView (GET)
2.4.3 Configure URL routing
- Create transcription/urls.py
- Routes:
  - POST /api/upload/ - Upload audio file
  - GET /api/transcription/<id>/ - Get transcription
  - GET /api/words/<id>/?level=<cefr> - Get words by level
  - GET /api/status/<id>/ - Get processing status
2.4.4 Add request validation
- Validate file size (max 100MB for MVP)
- Validate file format (mp3, wav, m4a)
- Validate CEFR level parameter
2.4.5 Implement response formatting
- Return consistent JSON structure
- Include error messages
- Add pagination for word lists

Acceptance Criteria:

All endpoints are functional
Request validation works
Response format is consistent

3. Frontend Development

3.1 React Project Setup

Task: Initialize React frontend application

Steps:

3.1.1 Create React app
- Navigate to frontend/ directory
- Run: npx create-react-app . --template typescript
- Clean up boilerplate code
3.1.2 Install dependencies
- Install Axios: npm install axios
- Install React Router: npm install react-router-dom
- Install UI library: npm install @mui/material @emotion/react @emotion/styled
- Install icons: npm install @mui/icons-material
3.1.3 Configure proxy for development
- Add proxy in package.json: "proxy": "http://backend:8000"
- Create .env file with REACT_APP_API_URL

3.1.4 Set up project structure

src/
├── components/
├── pages/
├── services/
├── hooks/
├── types/
├── utils/
└── App.tsx

Acceptance Criteria:

React app runs successfully
Dependencies are installed
Project structure is organized

3.2 API Service Layer

Task: Create API service for backend communication

Steps:

3.2.1 Create API client
- Create src/services/api.ts
- Configure Axios instance with base URL
- Add request/response interceptors
3.2.2 Create TypeScript interfaces
- Create src/types/index.ts
- Define: AudioFile, Transcription, Word, WordStatistics
3.2.3 Implement API methods
- uploadAudio(file: File): Promise<AudioFile>
- getTranscription(id: string): Promise<Transcription>
- getWordsByLevel(id: string, level: string): Promise<Word[]>
- getProcessingStatus(id: string): Promise<Status>
3.2.4 Add error handling
- Handle network errors
- Handle API errors
- Parse error messages

Acceptance Criteria:

API service communicates with backend
TypeScript types are defined
Error handling works

3.3 Upload Component

Task: Create audio file upload interface

Steps:

3.3.1 Create upload component
- Create src/components/AudioUpload.tsx
- Implement drag-and-drop zone
- Add file input button
- Show file preview
3.3.2 Implement file validation
- Check file format (mp3, wav, m4a)
- Check file size (max 100MB)
- Show validation errors
3.3.3 Add CEFR level selector
- Create dropdown with A1-C2 options
- Allow multiple level selection
- Set default to all levels
3.3.4 Implement upload progress
- Show upload progress bar
- Display processing status
- Handle upload cancellation
3.3.5 Add loading states
- Show spinner during upload
- Disable submit during processing
- Show success/error messages

Acceptance Criteria:

File upload works smoothly
Validation prevents invalid uploads
Progress is visible to user

3.4 Results Display Component

Task: Create component to display transcription and word results

Steps:

3.4.1 Create results page
- Create src/pages/Results.tsx
- Fetch data on component mount
- Handle loading state
3.4.2 Create transcription display
- Create src/components/TranscriptionView.tsx
- Show full transcription text
- Make text scrollable
- Add copy button
3.4.3 Create word list component
- Create src/components/WordList.tsx
- Display words grouped by CEFR level
- Show word frequency
- Display word context on hover
3.4.4 Add filtering and sorting
- Filter by CEFR level
- Sort by frequency or alphabetically
- Search within words
3.4.5 Implement word highlighting
- Highlight selected level words in transcription
- Color-code by CEFR level
- Add click-to-highlight functionality

Acceptance Criteria:

Results are displayed clearly
Filtering and sorting work
User can interact with words

3.5 Layout and Navigation

Task: Create app layout and navigation

Steps:

3.5.1 Create header component
- Create src/components/Header.tsx
- Add app logo and title
- Add navigation links (for future phases)
3.5.2 Create main layout
- Create src/components/Layout.tsx
- Include header
- Add main content area
- Add footer with credits
3.5.3 Set up routing
- Create src/App.tsx with routes
- Route: / - Upload page
- Route: /results/:id - Results page
- Route: * - 404 page
3.5.4 Add responsive design
- Make layout mobile-friendly
- Test on different screen sizes
- Use Material-UI breakpoints

Acceptance Criteria:

Navigation works correctly
Layout is responsive
UI is consistent across pages

4. Docker and Deployment

4.1 Backend Dockerfile

Task: Create Dockerfile for Django backend

Steps:

4.1.1 Create backend Dockerfile
- Create backend/Dockerfile
- Use Python 3.11 base image
- Install system dependencies (ffmpeg, libsndfile1)
- Copy requirements and install Python packages
- Download Whisper model during build
- Set up working directory
- Expose port 8000
4.1.2 Create .dockerignore
- Exclude: __pycache__, *.pyc, .env, db.sqlite3, media/, staticfiles/
4.1.3 Optimize image size
- Use multi-stage build
- Clean up apt cache
- Remove unnecessary files

Dockerfile Structure:

FROM python:3.11-slim

# Install system dependencies
RUN apt-get update && apt-get install -y \
    ffmpeg \
    libsndfile1 \
    && rm -rf /var/lib/apt/lists/*

# Set working directory
WORKDIR /app

# Install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Download Whisper model
RUN python -c "import whisper; whisper.load_model('base')"

# Copy application
COPY . .

# Run migrations and collect static files
CMD ["gunicorn", "config.wsgi:application", "--bind", "0.0.0.0:8000"]

Acceptance Criteria:

Backend Docker image builds successfully
Image includes all dependencies
Whisper model is pre-downloaded

4.2 Frontend Dockerfile

Task: Create Dockerfile for React frontend

Steps:

4.2.1 Create frontend Dockerfile
- Create frontend/Dockerfile
- Use Node.js 18 for build stage
- Use nginx for production stage
- Build React app
- Copy build to nginx html directory
4.2.2 Create nginx configuration
- Create frontend/nginx.conf
- Configure reverse proxy to backend
- Set up client_max_body_size for uploads
- Enable gzip compression
4.2.3 Create .dockerignore
- Exclude: node_modules/, build/, .env

Dockerfile Structure:

# Build stage
FROM node:18-alpine AS build
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM nginx:alpine
COPY --from=build /app/build /usr/share/nginx/html
COPY nginx.conf /etc/nginx/conf.d/default.conf
EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]

Acceptance Criteria:

Frontend Docker image builds successfully
Nginx serves React app
API proxy works correctly

4.3 Docker Compose Configuration

Task: Create docker-compose.yml for orchestration

Steps:

4.3.1 Create docker-compose.yml
- Define services: backend, frontend, db, redis, celery, celery-beat
- Configure networks
- Set up volumes for persistence
- Define health checks
4.3.2 Configure environment variables
- Create .env.docker file
- Set database credentials
- Set Groq API key
- Set Django secret key
4.3.3 Set up volumes
- PostgreSQL data volume
- Redis data volume
- Media files volume
- Static files volume
4.3.4 Configure service dependencies
- Backend depends on db and redis
- Celery depends on backend and redis
- Frontend depends on backend

Docker Compose Structure:

version: '3.8'

services:
  db:
    image: postgres:15-alpine
    volumes:
      - postgres_data:/var/lib/postgresql/data
    environment:
      - POSTGRES_DB=${DB_NAME}
      - POSTGRES_USER=${DB_USER}
      - POSTGRES_PASSWORD=${DB_PASSWORD}
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${DB_USER}"]
      interval: 10s
      timeout: 5s
      retries: 5

  redis:
    image: redis:7-alpine
    volumes:
      - redis_data:/data
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 5

  backend:
    build: ./backend
    command: gunicorn config.wsgi:application --bind 0.0.0.0:8000 --workers 4
    volumes:
      - ./backend:/app
      - media_files:/app/media
      - static_files:/app/staticfiles
    environment:
      - DATABASE_URL=postgresql://${DB_USER}:${DB_PASSWORD}@db:5432/${DB_NAME}
      - REDIS_URL=redis://redis:6379/0
      - GROQ_API_KEY=${GROQ_API_KEY}
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_healthy
    ports:
      - "8000:8000"

  celery:
    build: ./backend
    command: celery -A config worker -l info
    volumes:
      - ./backend:/app
      - media_files:/app/media
    environment:
      - DATABASE_URL=postgresql://${DB_USER}:${DB_PASSWORD}@db:5432/${DB_NAME}
      - REDIS_URL=redis://redis:6379/0
      - GROQ_API_KEY=${GROQ_API_KEY}
    depends_on:
      - backend
      - redis

  frontend:
    build: ./frontend
    ports:
      - "80:80"
    depends_on:
      - backend

volumes:
  postgres_data:
  redis_data:
  media_files:
  static_files:

Acceptance Criteria:

All services start successfully
Services can communicate with each other
Data persists in volumes

4.4 Deployment Scripts

Task: Create deployment and management scripts

Steps:

4.4.1 Create startup script
- Create scripts/start.sh
- Check environment variables
- Run migrations
- Collect static files
- Start services
4.4.2 Create deployment script
- Create scripts/deploy.sh
- Pull latest changes
- Build Docker images
- Run database migrations
- Restart services with zero downtime
4.4.3 Create backup script
- Create scripts/backup.sh
- Backup PostgreSQL database
- Backup media files
- Create timestamped archives
4.4.4 Create health check script
- Create scripts/healthcheck.sh
- Check service status
- Verify database connection
- Test API endpoints
4.4.5 Make scripts executable
- Run: chmod +x scripts/*.sh

Acceptance Criteria:

Scripts execute without errors
Services start and stop correctly
Backups are created successfully

5. Testing and Quality Assurance

5.1 Backend Unit Tests

Task: Write unit tests for backend services

Steps:

5.1.1 Set up test configuration
- Create backend/conftest.py for pytest
- Configure test database
- Create test fixtures
5.1.2 Write model tests
- Create transcription/tests/test_models.py
- Test model creation
- Test model relationships
- Test model methods
5.1.3 Write service tests
- Create transcription/tests/test_services.py
- Mock Whisper service
- Mock Groq service
- Test word processing logic
5.1.4 Write API tests
- Create transcription/tests/test_api.py
- Test file upload endpoint
- Test retrieval endpoints
- Test error handling
5.1.5 Run tests
- Install pytest: pip install pytest pytest-django
- Run: pytest
- Aim for >80% code coverage

Acceptance Criteria:

All tests pass
Code coverage is >80%
Edge cases are tested

5.2 Frontend Unit Tests

Task: Write unit tests for React components

Steps:

5.2.1 Set up testing environment
- React Testing Library is included with CRA
- Install additional tools if needed
5.2.2 Write component tests
- Test AudioUpload component
- Test TranscriptionView component
- Test WordList component
- Mock API calls
5.2.3 Write service tests
- Test API service methods
- Test error handling
- Mock axios requests
5.2.4 Run tests
- Run: npm test
- Check coverage: npm test -- --coverage

Acceptance Criteria:

Component tests pass
User interactions are tested
API mocking works correctly

5.3 Integration Testing

Task: Test end-to-end workflows

Steps:

5.3.1 Test complete upload workflow
- Upload audio file
- Verify processing
- Check transcription result
- Verify word extraction
5.3.2 Test error scenarios
- Invalid file format
- File too large
- Network errors
- API failures
5.3.3 Test performance
- Upload large files
- Process multiple files concurrently
- Monitor memory usage
5.3.4 Create test data
- Prepare sample audio files
- Create test cases document

Acceptance Criteria:

End-to-end workflows work
Error handling is robust
Performance is acceptable

6. Documentation

6.1 Development Documentation

Task: Create comprehensive development documentation

Steps:

6.1.1 Write README.md
- Project description
- Features list
- Tech stack
- Quick start guide
- Project structure overview
6.1.2 Create SETUP.md
- Prerequisites
- Local development setup
- Environment variables
- Database setup
- Running tests
6.1.3 Create API documentation
- Create docs/API.md
- Document all endpoints
- Include request/response examples
- Document error codes
6.1.4 Create architecture documentation
- Create docs/ARCHITECTURE.md
- System architecture diagram
- Data flow diagram
- Technology decisions

Acceptance Criteria:

Documentation is complete
Examples are accurate
New developers can follow setup

6.2 Deployment Documentation

Task: Create deployment and operations documentation

Steps:

6.2.1 Write DEPLOYMENT.md
- Server requirements (CPU, RAM, disk)
- Docker installation
- Docker Compose setup
- Environment configuration
- SSL/TLS setup (using Let's Encrypt)
6.2.2 Create operations guide
- Create docs/OPERATIONS.md
- Monitoring and logging
- Backup and restore procedures
- Scaling guidelines
- Troubleshooting common issues
6.2.3 Create upgrade guide
- Version update procedures
- Database migration steps
- Rollback procedures
6.2.4 Security guidelines
- Create docs/SECURITY.md
- Environment variable security
- API key management
- File upload security
- Rate limiting

Acceptance Criteria:

Deployment steps are clear
Operations procedures are documented
Security guidelines are comprehensive

6.3 User Documentation

Task: Create end-user documentation

Steps:

6.3.1 Create user guide
- Create docs/USER_GUIDE.md
- How to upload audio
- How to interpret results
- CEFR level explanations
- FAQ section
6.3.2 Create video tutorial
- Record screen capture of workflow
- Add narration explaining steps
- Upload to YouTube (optional)
6.3.3 Create troubleshooting guide
- Common errors and solutions
- Supported file formats
- File size limitations

Acceptance Criteria:

User guide is easy to follow
Screenshots/videos are included
FAQ covers common questions

7. Final Integration and Launch

7.1 Final Testing

Task: Perform comprehensive testing before launch

Steps:

7.1.1 Run all tests
- Backend unit tests
- Frontend unit tests
- Integration tests
- Fix any failing tests
7.1.2 Manual testing
- Test on different browsers
- Test on mobile devices
- Test with various audio files
- Test error scenarios
7.1.3 Performance testing
- Load testing with multiple users
- Test with large audio files (50MB+)
- Monitor resource usage
- Optimize if needed
7.1.4 Security testing
- Test file upload restrictions
- Test API authentication (for future)
- Check for SQL injection vulnerabilities
- Verify CORS configuration

Acceptance Criteria:

All tests pass
No critical bugs found
Performance is acceptable
Security is verified

7.2 Deployment to Server

Task: Deploy application to production server

Steps:

7.2.1 Prepare server
- Set up Linux server (Ubuntu 22.04 recommended)
- Install Docker and Docker Compose
- Configure firewall (allow ports 80, 443)
- Set up domain name (optional)
7.2.2 Clone repository
- SSH into server
- Clone Git repository
- Checkout main branch
7.2.3 Configure environment
- Copy .env.example to .env
- Set production values
- Set strong SECRET_KEY
- Configure GROQ_API_KEY
- Set ALLOWED_HOSTS
7.2.4 Build and start services
- Run: docker-compose build
- Run: docker-compose up -d
- Check service status: docker-compose ps
7.2.5 Run migrations
- Run: docker-compose exec backend python manage.py migrate
- Create superuser: docker-compose exec backend python manage.py createsuperuser
7.2.6 Configure SSL (optional but recommended)
- Install Certbot
- Generate Let's Encrypt certificate
- Update nginx configuration
- Enable HTTPS redirect
7.2.7 Set up monitoring
- Install monitoring tools (optional)
- Configure log aggregation
- Set up alerts for errors

Acceptance Criteria:

Application is accessible via web browser
All services are running
SSL/HTTPS is working (if configured)
Logs are being collected

7.3 Post-Launch Monitoring

Task: Monitor application after launch

Steps:

7.3.1 Monitor application logs
- Backend logs: docker-compose logs -f backend
- Celery logs: docker-compose logs -f celery
- Database logs: docker-compose logs -f db
- Check for errors
7.3.2 Monitor resource usage
- Check CPU usage
- Check memory usage
- Check disk space
- Check network traffic
7.3.3 Test core functionality
- Upload test audio file
- Verify transcription
- Check word extraction
- Verify results display
7.3.4 Set up automated backups
- Configure daily database backups
- Set up backup retention policy
- Test restore procedure
7.3.5 Document any issues
- Create issue tracker (GitHub Issues)
- Document bugs and feature requests
- Prioritize fixes

Acceptance Criteria:

Application runs stably
No critical errors in logs
Resources are within limits
Backups are running

PHASE 2: Enhanced Features (Detailed Implementation)

1. Video Support

1.1 Video Upload and Processing

Task: Add video file upload and audio extraction

Steps:

1.1.1 Update backend models
- Add VideoFile model
- Add video format field
- Link to extracted audio
1.1.2 Implement audio extraction
- Use ffmpeg to extract audio from video
- Support formats: mp4, avi, mov, mkv
- Convert to WAV for processing
1.1.3 Update API endpoints
- Modify upload endpoint to accept video
- Add video validation
- Update file size limit
1.1.4 Update frontend
- Update upload component for video
- Add video preview
- Show extraction progress

Acceptance Criteria:

Video files can be uploaded
Audio is successfully extracted
Processing continues as with audio

2. User Authentication

2.1 User Registration and Login

Task: Implement user authentication system

Steps:

2.1.1 Set up Django authentication
- Install: djangorestframework-simplejwt
- Create custom User model (if needed)
- Configure JWT authentication
2.1.2 Create authentication endpoints
- POST /api/auth/register/
- POST /api/auth/login/
- POST /api/auth/logout/
- POST /api/auth/refresh/
2.1.3 Update models with user relationships
- Add user ForeignKey to AudioFile
- Add user permissions
2.1.4 Create frontend authentication
- Create login page
- Create registration page
- Store JWT token
- Add authentication to API calls
- Implement protected routes

Acceptance Criteria:

Users can register and login
JWT authentication works
Files are associated with users

3. Processing History

3.1 User Dashboard

Task: Create dashboard to view processing history

Steps:

3.1.1 Create history API endpoint
- GET /api/history/ - List user's files
- Add pagination
- Add filtering by date, status
3.1.2 Create dashboard page
- Create src/pages/Dashboard.tsx
- Display list of processed files
- Show processing status
- Add search functionality
3.1.3 Add file management
- View details
- Delete files
- Re-download results

Acceptance Criteria:

Users can view their history
Files can be managed
Dashboard is responsive

4. Enhanced UI/UX

4.1 Improved Design

Task: Enhance user interface and experience

Steps:

4.1.1 Implement better styling
- Create consistent theme
- Add color scheme for CEFR levels
- Improve typography
4.1.2 Add animations
- Upload progress animations
- Loading spinners
- Smooth transitions
4.1.3 Improve results visualization
- Add word cloud
- Add statistics charts (using Chart.js)
- Add exportable reports
4.1.4 Add download functionality
- Export transcription as TXT
- Export words as CSV
- Export full report as PDF

Acceptance Criteria:

UI is polished and professional
User experience is smooth
Results can be exported

PHASE 3: Full Local Processing (Detailed Implementation)

1. Local LLM Integration

1.1 Replace Groq with Local LLM

Task: Implement local language model for word classification

Steps:

1.1.1 Choose and set up local LLM
- Options: Llama 3, Mistral, or smaller model
- Use Ollama or llama.cpp
- Download model during Docker build
1.1.2 Create local LLM service
- Create transcription/services/local_llm_service.py
- Implement model loading
- Implement inference method
1.1.3 Update classification logic
- Replace Groq calls with local LLM
- Optimize prompts for local model
- Implement batching for efficiency
1.1.4 Update Docker configuration
- Add GPU support (optional)
- Increase memory allocation
- Download model in Dockerfile

Acceptance Criteria:

Local LLM runs successfully
Classification accuracy is maintained
Performance is acceptable

2. Performance Optimization

2.1 Caching and Optimization

Task: Optimize application performance

Steps:

2.1.1 Implement advanced caching
- Cache transcriptions
- Cache word classifications
- Use Redis for caching
2.1.2 Optimize database queries
- Add database indexes
- Use select_related and prefetch_related
- Implement query optimization
2.1.3 Optimize Whisper processing
- Use faster Whisper model (tiny or small)
- Implement GPU acceleration
- Optimize audio preprocessing
2.1.4 Implement rate limiting
- Limit uploads per user
- Limit API requests
- Add queue management

Acceptance Criteria:

Response times are improved
Database queries are optimized
Rate limiting prevents abuse

PHASE 4: Production Ready (Overview)

1. Advanced Features

Multi-language support (Spanish, French, German, etc.)
Subtitle generation with CEFR-colored words
Vocabulary flashcard generation
Progress tracking for language learners
Spaced repetition system integration

2. API and Integrations

Public REST API with authentication
Webhook support
Third-party integrations (Anki, Notion, etc.)

3. Advanced Analytics

Usage statistics dashboard
Word difficulty trends
Learning recommendations
A/B testing framework

4. Production Infrastructure

Kubernetes deployment
Horizontal scaling
Load balancing
CDN integration
Advanced monitoring (Prometheus, Grafana)
Automated CI/CD pipeline

Success Metrics

Phase 1 MVP:

Application successfully transcribes audio files
Words are correctly classified by CEFR level
Application is fully dockerized
Deployment documentation is complete
Basic UI is functional and responsive

Phase 2:

Video processing works correctly
User authentication is secure
Users can manage their processing history
UI is polished and professional

Phase 3:

Full local processing (no external APIs)
Performance is optimized
Application runs efficiently on modest hardware

Phase 4:

Production-ready with all advanced features
Public API is documented and functional
Application is scalable and monitored

Technology Stack Summary

Backend:

Framework: Django 4.2+
API: Django REST Framework
Task Queue: Celery + Redis
Database: PostgreSQL
AI/ML: Whisper (local), Groq API (Phase 1), Local LLM (Phase 3)
Server: Gunicorn + Nginx

Frontend:

Framework: React 18+ with TypeScript
UI Library: Material-UI (MUI)
HTTP Client: Axios
Routing: React Router
State Management: React Context (Phase 1), Redux (later phases)

DevOps:

Containerization: Docker, Docker Compose
Orchestration (Phase 4): Kubernetes
CI/CD: GitHub Actions (Phase 4)
Monitoring: Prometheus + Grafana (Phase 4)

Timeline Estimates

Phase 1 (MVP): 3-4 weeks
Phase 2 (Enhanced Features): 2-3 weeks
Phase 3 (Full Local): 2-3 weeks
Phase 4 (Production Ready): 3-4 weeks

Total: 10-14 weeks (2.5-3.5 months)

Next Steps

Review and approve this project outline
Set up development environment
Start with Phase 1, Step 1.1: Project Setup and Architecture
Follow each task sequentially, checking off completed items
Regularly commit changes to Git
Document any deviations or issues encountered

Document Version: 1.0
Last Updated: October 8, 2025
Status: Ready for Implementation

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Hard Word Extractor - Project Outline & Progress Tracker

📋 Important Documentation Files

🎯 Project Overview

Tech Stack

Key Features

📊 Overall Progress Summary

Phase 1: MVP (95% Complete) ⏳

Phase 2: Enhanced Features (0% Complete) ❌

Phase 3: Full Local Processing (0% Complete) ❌

Phase 4: Production Ready (0% Complete) ❌

🚀 PHASE 1: MVP - CURRENT PHASE

1. PROJECT SETUP & ARCHITECTURE (100% Complete ✅)

1.1 Initialize Project Structure ✅

1.2 Backend Setup - Django Project (100% Complete ✅)

1.3 Database Configuration (100% Complete ✅)

1.4 Celery Configuration (100% Complete ✅)

1.5 Admin Interface (100% Complete ✅)

2. BACKEND CORE FEATURES (100% Complete ✅)

2.1 Whisper Integration (100% Complete ✅)

2.2 Groq LLM Integration (100% Complete ✅)

2.3 Word Extraction and Processing (100% Complete ✅)

2.4 Celery Tasks (100% Complete ✅)

3. REST API (100% Complete ✅)

3.1 API Serializers (100% Complete ✅)

3.2 API Views (100% Complete ✅)

3.3 URL Configuration (100% Complete ✅)

3.4 API Documentation (100% Complete ✅)

4. FRONTEND DEVELOPMENT (95% Complete ✅)

4.1 React Project Setup (100% Complete ✅)

4.2 TypeScript Types & Interfaces (100% Complete ✅)

4.3 API Service Layer (100% Complete ✅)

4.4 Core Components (100% Complete ✅)

4.5 Pages (100% Complete ✅)

4.6 Routing & App Configuration (100% Complete ✅)

4.7 Testing & Polish (80% Complete ⏳)

5. DOCKER CONFIGURATION (100% Complete ✅)

5.1 Backend Dockerfile (100% Complete ✅)

5.2 Frontend Dockerfile (100% Complete ✅)

5.3 Docker Compose (100% Complete ✅)

5.4 Deployment Scripts (100% Complete ✅)

5.5 Deployment Documentation (100% Complete ✅)

6. TESTING & QUALITY ASSURANCE (0% Complete ❌)

6.1 Backend Unit Tests (0% Complete ❌)

6.2 Frontend Unit Tests (0% Complete ❌)

6.3 Integration Testing (0% Complete ❌)

7. DOCUMENTATION & FINAL POLISH (50% Complete ⏳)

7.1 Development Documentation (100% Complete ✅)

7.2 Deployment Documentation (0% Complete ❌)

7.3 User Documentation (0% Complete ❌)

8. FINAL INTEGRATION & LAUNCH (0% Complete ❌)

8.1 Final Testing (0% Complete ❌)

8.2 Deployment to Server (0% Complete ❌)

8.3 Post-Launch (0% Complete ❌)

📊 PHASE 1 SUMMARY

Completion Status

What's Complete ✅

What's Remaining ❌

Time Estimates

🚀 PHASE 2: ENHANCED FEATURES (Not Started)

Key Features to Add:

🔧 PHASE 3: FULL LOCAL PROCESSING (Not Started)

Key Features to Add:

🌟 PHASE 4: PRODUCTION READY (Not Started)

Key Features to Add:

📝 NEXT SESSION INSTRUCTIONS

📈 SUCCESS METRICS

Phase 1 MVP Goals:

Code Quality:

🔑 KEY TECHNICAL DECISIONS

🐛 KNOWN ISSUES & TODOs

📞 GETTING HELP

Resources:

Common Commands:

1.3 Backend Setup - Database Configuration