- Remove hardcoded API keys from config.py
- Move all API keys to environment variables
- Create .env.example file with template
- Update .gitignore to exclude .env files
- Add environment variable validation
- Implement secure API key loading with pydantic-settings
- Fix requirements.txt version conflicts
- Pin all dependency versions for stability
- Create separate requirements-dev.txt for development
- Add python-version specification (3.9+)
- Update module.qlooapi requirements.txt
- Add dependency vulnerability scanning
- Create Dockerfile for main application
- Create docker-compose.yml for local development
- Add Docker health checks
- Create .dockerignore file
- Test Docker build and run locally
- Add multi-stage Docker build for optimization
- Add MIT License file
- Create CONTRIBUTING.md guide
- Add CHANGELOG.md for version tracking
- Update README.md with screenshots
- Add API documentation with examples
- Create architecture diagram
- Add troubleshooting section
- Run all existing tests and fix failures
- Add integration tests for API endpoints
- Add unit tests for core components
- Set up test coverage reporting
- Add performance benchmarks
- Test in multiple Python versions (3.9, 3.10, 3.11)
- Add type hints to all functions
- Implement proper error handling
- Add comprehensive logging
- Follow PEP 8 style guidelines
- Add docstrings to all classes and functions
- Remove unused imports and dead code
- Create .github/workflows/ci.yml
- Set up automated testing on push/PR
- Add code quality checks (linting, formatting)
- Set up security scanning
- Add automated dependency updates
- Create release workflow
- Rename module.qlooapi to qloo-api-module
- Reorganize docs/ folder structure
- Add examples/ folder with demo scripts
- Create templates/ folder for boilerplate code
- Add assets/ folder for images and media
- Standardize file naming conventions
- Create comprehensive repository description
- Add relevant topics and tags
- Set up issue templates
- Create pull request templates
- Add code of conduct
- Set up branch protection rules
- Add application performance monitoring
- Implement usage analytics
- Add error tracking and reporting
- Create metrics dashboard
- Set up health check endpoints
- Add logging aggregation
- Ensure there is a valid AssemblyAI API key (
ASSEMBLYAI_API_KEY) in the.envfile. - Verify that the key is correct and has Universal-Streaming access.
- Check that the environment variable is correctly read in the backend code.
- Restart the backend.
- Test getting a token by making a request to the
POST /api/assemblyai-tokenendpoint. - If you get an error, examine the backend logs and fix it.
- Add the necessary JavaScript code for microphone access in the frontend.
- Start audio recording when the microphone button is clicked.
- Collect audio data in real-time and store it in a buffer.
- Add necessary libraries for WebSocket connection in the frontend.
- Get a token from the backend when the microphone is active.
- Establish AssemblyAI WebSocket connection with the received token.
- Check connection status and handle error situations.
- Send microphone data to AssemblyAI via WebSocket.
- Set the audio format correctly (16kHz, PCM, mono).
- Send audio data in chunks.
- Receive real-time transcript data from AssemblyAI.
- Display transcript data in the frontend.
- Get the final transcript when speech ends.
- Send the final transcript to the
/chatendpoint in the backend. - Get relevant data with the Qloo API.
- Process the transcript with LLM and generate a response.
- Send the response back to the frontend and display it.
- Visually show microphone active/inactive states.
- Add a "listening" animation during speech.
- Update transcript in real-time while it's being written.
- Inform the user in error situations.
- Catch and handle WebSocket connection errors.
- Check microphone access errors.
- Examine backend logs and add error messages to task.md.
- Update solution steps if necessary.
- Test the entire flow end-to-end.
- Test in different browsers.
- Optimize audio quality and latency times.
- Track performance metrics.
- Manage WebSocket connections securely.
- Check and renew token expiration.
- Optimize memory usage.
- Add rate limiting (if necessary).
- Add loading states and animations
- Implement responsive design improvements
- Add keyboard shortcuts
- Create user onboarding flow
- Add accessibility features (ARIA labels)
- Implement dark/light theme toggle
- Add user preferences storage
- All tests passing
- No security vulnerabilities
- Documentation complete
- Docker builds successfully
- Environment variables properly configured
- API endpoints tested
- Frontend responsive on all devices
- Performance benchmarks met
- Error handling comprehensive
- Logging properly configured
- Monitor GitHub repository metrics
- Respond to issues and pull requests
- Update documentation based on feedback
- Plan next feature releases
- Create community guidelines
- Set up automated releases
- Monitor application performance
- Collect user feedback
Priority Order:
- 🔐 Security (CRITICAL - Must be done first)
- 📦 Dependencies (HIGH - Required for stability)
- 🐳 Containerization (HIGH - Required for deployment)
- 📄 Documentation (MEDIUM - Required for adoption)
- 🧪 Testing (MEDIUM - Required for quality)
- 🚀 CI/CD (LOW - Nice to have)
- 🎨 UX (LOW - Enhancement)
Notes:
- Mevcut AssemblyAI entegrasyonu görevleri korundu
- GitHub'a yükleme öncesi kritik güvenlik iyileştirmeleri eklendi
- Proje kalitesini artıracak tüm alanlar kapsandı
- Öncelik sırası belirlendi
- Her görev için checkbox eklendi