Open Source AI Models Integration

Overview

Integration with various open-source AI models for transcription and understanding, enabling local deployment and customization options.

Project Details

• Complexity: Large
• Estimated Time: 120-160 hours
• Mentors: Bodhish (BE), Bijoy (BE)
• Project Links:
  • Backend: https://github.com/medispeak/medispeak-backend
  • Frontend: https://github.com/medispeak/medispeak-app

Skills Required

• Python
• TensorFlow/PyTorch
• Ruby on Rails
• Docker
• Machine Learning fundamentals
• Audio processing
• API development

Acceptance Criteria

1. Successfully integrate at least 2 open-source speech-to-text models
2. Implement model switching capability
3. Achieve 90%+ accuracy in medical terminology transcription
4. Support local model deployment
5. Enable model fine-tuning for medical specialties
6. Implement performance monitoring and optimization
7. Complete documentation for model integration and deployment

Milestones

Phase 1: Research & Setup (30-40 hours)

• Research and select suitable open-source models
• Set up development environment
• Create proof of concept with one model
• Document initial findings and approach

Phase 2: Core Integration (40-50 hours)

• Implement model integration framework
• Develop API endpoints for model interaction
• Create model switching mechanism
• Set up basic model training pipeline

Phase 3: Optimization & Features (30-40 hours)

• Implement local deployment support
• Add model fine-tuning capabilities
• Optimize performance
• Add monitoring and logging

Phase 4: Testing & Documentation (20-30 hours)

• Comprehensive testing across different scenarios
• Performance benchmarking
• Complete technical documentation
• Create user guides and deployment documentation