Gemini API and Flutter: Practical, AI-driven apps with Google AI tools

Introduction to Large Language Models (LLMs), their use in generative AI, and their ability to create new content such as text, images, and code.

Discussion on the rapid advancements in generative AI tools for developers, the challenges in choosing the right tools, and the importance of staying updated with new AI products.

Overview of the journey of building a cooking app using generative AI with the Google AI SDK for Dart, focusing on the Gemini API.

Process of learning and experimenting with generative AI using the Google AI Studio, exploring various prompts and building features for flutter apps using generative AI.

Explanation of prompt design for the Gemini API, including the selection of prompt types, experimenting with free form prompts, and ensuring safety considerations in prompt instructions.

Description of conducting a proof of concept with the Gemini models for image-to-recipe generation, addressing safety considerations like allergens, and incorporating safety parameters in prompt design.

Process of integrating the Gemini API into the app, sharing prompts between team members, setting up API keys, adding the Google generative AI package to the flutter app, and making requests to the Gemini API.

Explanation of customizing the app for personalized recipe requests, incorporating dietary restrictions, and enhancing Chef Noodle's personality with AI prompts.

Discussion on formatting prompts for the Gemini API responses, addressing challenges in parsing complex prompt data, adding expected types to prompts, and ensuring consistent response formats.

Overview of the app's functionality, benefits of using generative AI for building apps, future plans for leveraging the Gemini API chat feature, and accessing additional resources.