• Post category:StudyBullet-13
  • Reading time:7 mins read


Chat App, ChatGPT, DALL-E and Elevenlabs intergration

What you will learn

Setting up a new Flutter project and creating a custom theme for the app

Building login and registration screens, including OTP verification

Connecting the app to Firebase for user authentication and data management for both Android and IOS

Implementing a chat screen with StreamBuilder and handling input messages

Integrating ChatGPT and DALL-E for image generation and displaying the responses in the chat widget

Adding text-to-speech and speech-to-text features using Elevenlabs API

Building a post screen with grid view, like and comment functionality, and user-to-user chat

Add a text-to-speech feature in the application using ElevenLabs API

Configuring Firebase Firestore rules for secure data access

Implementing user-to-user chat using Firebase Cloud Firestore

Description

In this course, you will learn how to build a fully functional chat application with AI integration using Flutter. You will start by setting up the project and creating a theme for your app. Then, you will build the login and registration screens, including user authentication and data management with Firebase.

Next, you will learn how to implement a chat screen, including designing and implementing the landing screen UI, chat screen UI with StreamBuilder, and handling input messages. You will also learn how to use DALL-E API for image generation, parsing and displaying image response from the API, and saving ChatGPT response to Firestore.

In addition, you will learn how to add text-to-speech and speech-to-text functionality to your chat app using Elevenlabs API. You will also create a profile screen UI and add functions to the profile screen.


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Finally, you will learn how to implement a post screen, including adding a grid view, creating a post widget, streaming shared posts from Firestore, and adding a like and comment function.

By the end of this course, you will have a complete understanding of how to build a chat application with AI integration using Flutter and will be equipped with the necessary skills to build your own chat app.

English
language

Content

Introduction

Introduction
Starting up project
Creating a theme
Selecting a theme
Saving the theme

Building the login and registration screens

Adding Bottom navigation bar
6 Login Packages and assets
7 Registration screen part 1
8 Registration screen part 2
9 OTP screen UI
10 User information screen
11 Connecting to Firebase
12 Sign in user part 1
13 Sign in user part 2
14 Login user and SHA keys

Building the OTP and user information screens

15 OPT screen part 1
16 OPT screen part 2
17 User information screen part 1
18 User information screen part 2
19 User information screen part 3
20 User model class

User Authentication and Data Management

21 Setting up Firebase Authentication and Firestore for user data
22 Creating user model and updating user data
23 Handling user authentication and sign-up errors
24 Implementing sign-out functionality
25 Updating user data in Firestore upon profile changes
26 Retrieving user data from Firestore

Chat Screen Implementation

27 Designing and implementing the landing screen UI
28 Implementing chat screen UI with StreamBuilder and handling input messages
29 Implementing chat input field with the send button
30 Implementing a chat provider for sending and receiving messages
31 Implementing a chat stream to listen for incoming messages
32 Setting up API service for image generation with DALL-E
33 Handling image generation errors and responses from DALL-E API

ChatGPT and DALL-E Integration

34 Parsing and displaying image response from DALL-E API
35 Saving ChatGPT response to Firestore
36 Implementing chat widget for ChatGPT and DALL-E
37 Displaying ChatGPT response in the chat widget
38 Implementing text and image button for DALL-E image generation
39 Implementing scroll controller and focus node for a chat widget
40 Saving ChatGPT image to Firestore storage
41 Compressing the generated image before saving it to Firestore