This product is a book titled "Build AI Applications with FastAPI." It provides a guide for creating a large language model hub using FastAPI and Ollama. The book covers topics such as FastAPI fundamentals, Ollama integration, database management, asynchronous processing, authentication, deployment strategies, testing, performance optimization, and the use of a preprocessor system. It includes practical examples and source code for an LLM hub. The book is aimed at Python developers, data scientists, ML engineers, and software engineers interested in AI web applications.
Features
FastAPI Fundamentals
Learn to create efficient APIs with FastAPI, including route definition, request handling, and response management.
Ollama Integration
Learn to integrate Ollama for managing and running large language models, including creating custom models and adjusting parameters.
Database Management
Explore FastAPI-SQL integration, database migrations with Alembic, and CRUD operations using SQLAlchemy.
Asynchronous Processing
Implement Celery and Redis for handling long-running tasks, ensuring responsiveness under load.
Authentication and Security
Implement JWT-based authentication and learn best practices for securing your FastAPI application.
Deployment Strategies
Discover deployment strategies using Docker, Docker Compose, and Cloudflare Tunnels.
Testing and Quality Assurance
Write effective unit and integration tests, including integration with GitHub Actions for continuous integration.
Performance Optimization
Implement caching strategies, optimize database queries, and handle high concurrency.
Preprocessor System
Explore the flexible preprocessor system for intelligent input transformation, including a powerful LLM content extractor.