Add complete Mail Fine-Tuning Web-App for macOS Apple Silicon

Implemented a full-stack web application for fine-tuning LLMs on email data, optimized for Apple Silicon (M4 Pro with 24GB RAM).

Features:
- Mail import with drag & drop support (.mbox, .eml, .txt)
- Automated mail cleaning and preprocessing
- Interactive labeling interface with keyboard shortcuts
- Training data export to JSONL format
- MLX-based LoRA fine-tuning with live updates
- Model evaluation and comparison interface
- Server-Sent Events for real-time training progress
- Dark theme UI optimized for extended use

Technical Stack:
- Backend: FastAPI with SQLite database
- Frontend: Vanilla HTML/CSS/JavaScript (no external dependencies)
- ML Framework: MLX for Apple Silicon optimization
- Models: Support for Mistral 7B and Llama 3 8B via MLX

Components:
- data_manager.py: SQLite operations for mail storage and labeling
- mail_parser.py: Parser for multiple mail formats with cleaning
- training.py: MLX training wrapper with LoRA support
- inference.py: Model loading and inference for evaluation
- main.py: FastAPI backend with REST API and SSE
- Frontend: Complete UI with all features

Documentation:
- Comprehensive README with installation and usage guide
- Quick-start guide for rapid setup
- Example mails for testing
- Troubleshooting and best practices

Ready for local deployment and fine-tuning workflows.

training/example_mails/test2.txt

@@ -0,0 +1,16 @@
+Subject: Frage zu Invoice #2847
+From: michael.schmidt@example.com
+To: support@company.de
+Date: 2024-03-16
+
+Hallo,
+
+ich habe eine Frage zur Rechnung #2847 vom 15. März.
+Der Betrag scheint nicht mit unserem ursprünglichen Angebot übereinzustimmen.
+
+Laut Angebot sollten es 1.250€ sein, auf der Rechnung stehen aber 1.450€.
+
+Könnten Sie das bitte prüfen und mir Bescheid geben?
+
+Vielen Dank
+Michael Schmidt