Add FastAPI deployment tutorial for MONAI models

[engmohamedsalah]

This tutorial demonstrates how to deploy MONAI model bundles as production-ready REST APIs using FastAPI.

Features:

• Complete FastAPI application with inference endpoints
• MONAI model bundle integration (spleen_ct_segmentation)
• Singleton pattern for efficient model loading
• Async/await for optimal performance
• Pydantic validation for type safety
• Auto-generated API documentation (Swagger/ReDoc)
• Docker deployment with multi-stage builds
• Comprehensive unit tests
• Example client code and HTTP requests
• Production-ready error handling and logging

Structure:

• app/: FastAPI application code
• tests/: Unit test suite
• docker/: Containerization configs
• examples/: Usage examples
• README.md: Complete tutorial documentation

Addresses #2048

Fixes # .

Description

A few sentences describing the changes proposed in this pull request.

Checks

• Avoid including large-size files in the PR.
• Clean up long text outputs from code cells in the notebook.
• For security purposes, please check the contents and remove any sensitive info such as user names and private key.
• Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the ./figure folder
• Notebook runs automatically ./runner.sh -t <path to .ipynb file>

[ericspod]

Hi @engmohamedsalah thanks for this tutorial on deployment (sorry for not responding to your original issue proposing this). I think this looks great as it is so we can hopefully merge this soon. We have automated testing for notebooks which this example doesn't use so we won't be tested regularly, we may want to return sometime later to see if we can integrate the tests into the CICD system.