Notes on Building AI Applications Using Flutter and Google Gemini Pro API

Introduction

Akan welcomes viewers back to the channel.
Purpose: Building AI applications using Flutter and Google Gemini Pro API.
Importance of coding along: Viewers should code along to understand concepts thoroughly.

Part Watching: Viewers should watch the video in parts due to its length.
Using Flutter Gini Package:
- There is a package available for easier app development.
- Akan prefers building from scratch to understand the backend processes and API interactions.

APIs to be Covered:
- Google Gemini Pro API (text-based tasks)
- Google Gemini Vision API (image-based tasks)
Getting Started:
- Visit DeepMind Google for more information.
- Create an API key using Google AI Studio.

Using Playground:
- Create bots or prompts to test the API functionalities.
- Options for working with text (Gemini BR) and images (Gemini Vision).
Parameters:
- Temperature: Controls the randomness of the output.
  - Higher values yield more creative responses.
  - Lower values yield factual responses.
- Top K and Top P: Experiment with these values for output control.

Akan is launching a full-stack mobile app development course.
- Covers Flutter, Node.js, Express.js, TypeScript, Postman for API testing, and render for server hosting.
- Enrollment recommendations due to limited discounts and seats.
Encourages joining the free community for discussions and direct interactions.

Initial Steps: Spend time exploring the API and decide what app to build.
Creating Playground:
- Set up a free-form prompt for testing.
- Experiment and create queries related to space (e.g., Andromeda Galaxy).
Postman Setup:
- Clone API requests in Postman for testing.
- Ensure proper understanding of HTTP basics.
Diving into Flutter:
- Create a new Flutter project called "Space Pod."
- Set up the project structure, including pages, repositories, and block for state management.
User Interface:
- Create a dark-themed application with space-related visuals.
- Add components: Text field for user input, a button for sending messages, and display chat history.
API Calls:
- Implement API calls to send user messages and receive responses.
- Handle responses and display them in the chat view.

Chat Functionality:
- Users can send prompts and receive AI-generated responses.
- Maintain a list of chat messages with proper role assignment (user vs AI).
Loading Indicators: Display loaders while waiting for API responses.
Image Analysis:
- Plan for future implementations to analyze images using the Gemini Vision API.

Frequent use of debugging techniques to troubleshoot issues in API responses.
Importance of testing API calls individually using Postman before integrating them into the application.