Comprehensive documentation for API endpoints, deployment guides, and ML model

[navyajain7105]

Summary

Adds comprehensive documentation for API endpoints, deployment guides,
and ML model specifications to improve project discoverability and
contributor onboarding.

Changes

• API_DOCUMENTATION.md - API reference with examples (cURL, Python, JS)
• MODELS.md - Whisper and BERTweet model documentation with benchmarks
• README.md - Enhanced with architecture diagrams and expanded guides

🤖 MODELS.md (~700 lines)

Detailed ML model documentation:

✓ Whisper model: 5 sizes comparison (tiny to large)
✓ 99 language support with performance metrics
✓ BERTweet sentiment analysis: architecture & features
✓ Performance benchmarks (WER, inference speed)
✓ How to switch/upgrade models
✓ System requirements and specifications
✓ Limitations and best practices
Key Feature: Technical depth showing understanding of the ML models

📄 API_DOCUMENTATION.md (~1200 lines)

Complete REST API reference with:

✓ All 5 endpoints fully documented (Ping, Audio Extract, Transcription, Sentiment, Pipeline)
✓ cURL, Python, and JavaScript examples for every endpoint
✓ Request/response formats with detailed parameter tables
✓ Error handling guide with HTTP codes and solutions
✓ Rate limiting & best practices section
✓ 3 integration examples (single file, segment processing, batch processing)
Key Feature: Production-ready API reference that developers can immediately use