Thank you to MariaDB + MindsDB for sponsoring this series.
⦿ Code: https://github.com/codingforentrepreneurs/ai-travel-agent
⦿ Subscribe: https://cfe.sh/youtube
⦿ Go Pro: https://cfe.sh/enroll
⦿ Setup Video for Python 3 & Django 3: https://youtu.be/e5o1miB0nyk
Services used
⦿ MariaDB: https://mariadb.me/3RXuYup
⦿ MindsDB: https://mindsdb.com/
⦿ Gretel: https://gretel.ai/
⦿ AWS EC2: https://aws.amazon.com/ec2/
⦿ OpenAI: https://www.openai.com/
Software used
⦿ MariaDB Docker Image: https://hub.docker.com/_/mariadb/
⦿ Docker Engine https://docs.docker.com/engine/
⦿ Python: https://www.python.org/
⦿ Node.js: https://nodejs.org/
⦿ FastAPI: https://fastapi.tiangolo.com/
⦿ Next.js: https://nextjs.org/
⦿ Flowbite: https://www.flowbite.com/
Chapters
00:00:00 Welcome
00:03:34 Overview
00:07:59 References and Requirements
00:11:05 Provision EC2 Instance
00:16:58 Connect to EC2 Instance via SSH
00:21:11 Install Docker on EC2 Instance
00:23:35 Provision MariaDB with Docker Compose
00:34:04 Connect to EC2-Docker-based MariaDB Instance Locally
00:40:55 Configure Virtual Environment and Jupyter
00:47:54 Loading Dotenv with Python Decouple and Jupyter
00:56:43 Connect to MariaDB via SQLAlchemy
01:03:52 Load a Kaggle Dataset to MariaDB
01:15:47 Create MariaDB User for MindsDB
01:23:13 Integrate MariaDB & MindsDB
01:31:31 Creating a Forecasting Model with MindsDB
01:40:39 Predicting Future Values with MindsDB
01:46:37 Load Flight Prices Dataset to MariaDB
01:53:28 Prepare Flight Data for Predictions
02:03:25 MindsDB Predictor for Flight Price Data
02:08:09 More Data Features for Better Predictions
02:17:21 SQLAlchemy Model from Database Table
02:29:26 Pydantic Schema for SQLAlchemy Model
02:34:05 SQLAlchemy Lookup Functions for Model Data
02:39:04 MindsDB SQL Queries via Rest API and Python Part 1
02:47:25 MindsDB SQL Queries via Rest API and Python Part 2
02:59:34 FastAPI Backend App
03:07:32 Why the FastAPI Backend
03:10:16 Create the Next.js Frontend
03:16:56 FastAPI CORS for Nextjs
03:26:26 Integrate MariaDB to FastAPI
03:31:02 Listing Database Data via API View
03:34:32 Detail View and Schema with FastAPI and Pydantic
03:39:32 Listing API Data with Next.js
03:44:37 Styling a Link with Tailwind
03:46:44 Dynamic URL Route Detail Page in Next.js
03:53:03 Next.js Layout & CSS Class
03:58:17 Reusable Next.js Link Component
04:03:09 Backend API Client in Next.js
04:08:38 Handling request errors with swr and Next.js
04:15:05 Nextjs Form sending POST Requests to FastAPI
04:23:43 MindsDB with FastAPI and Nextjs
04:30:23 Generate and Load Airport Data in MariaDB and FastAPI
04:39:36 Airport Dropdown Selector
04:45:32 Handling POST Data with FastAPI and Pydantic
04:50:51 Prevent Duplicate Airports in Next.js
04:57:56 Improve Flight Price Prediction UI
05:06:10 TailwindCSS Global Styles
05:14:16 Form Styling with Flowbite References
05:21:38 Prediction Results UI Table
05:35:36 Integrate MindsDB with OpenAI to Make Flight Recommendations
05:45:39 OpenAI Recommendation Response in UI
05:56:28 Unique Request ID for Forecasts
05:59:24 Recommendation Display
06:05:47 Purchase Links
06:10:08 Starting to Handle New Data
06:11:51 Export Data and Train a Gretel Model
06:16:49 Load Gretel Data to MariaDB via Pandas
06:31:52 Train MindsDB Forecast Model via Jupyter
06:43:07 Final Clean Up
06:45:04 Thank you and your next challenge
