GroQ SQL Travel Planner: Book Flights, Hotels, Tours,

Weather‑Based Recommendations and Chatbot Support with

Firebase Login and SuperBase Captcha

Gayathri Ramasamy, Gurupriya M., Gamidi Rohan, Vinitha Chowdary A.,

Tejaswi Muppala and M. Hemasri

Department of Computer Science and Engineering, Amrita School of Computing, Bengaluru, Karnataka, India

Keywords: Chatbot Support, Firebase Authentication, Flight Booking, Google Sign‑In, GroQ API, Guided Tours, Hotel

Reservations, MySQL Database, Node.js Backend, OpenWeatherMap API, React.js Frontend, RESTful API,

Superbase CAPTCHA, Travel Planner, Weather Recommendations.

Abstract: GroQ SQL travel planner is an online portal encompassing all the important features to make and manage a

scheduled trip such as flight booking, hotel reservation, guided tours, with weather-based recommendations

and a chatbot support. For a seamless user experience, this application employs a React.js frontend, a MySQL

database, and Node.js and Express for the backend. For authentication, Firebase provides Authentication and

Google Sign-in and to avoid bot access Superbase provides CAPTCHA. The system has the ability to make

use of RESTful APIs to dynamically connect the frontend with that backend and database and filter the options

in real-time improving the way in which the frontend is linked to the backend and database. Weather data

from Open Weather Map API and a GroQ-based chatbot further enrich users’ experience to provide an AI

driven approach. This application can further filter users’ needs matching, searching for certain places,

services, and personalizing the trip, and thus, making this a robust application which provides travel solutions.

1 INTRODUCTION

Tour planning can be seen as dealing with a disparate

set of services for scheduling flights, accommodation,

and excursions as well as such issues as weather

conditions, security and individual customers. This

makes the process rather a lengthy and tedious

exercise and at the same time fraught with several

errors most especially if the end user does not have

prior experience with the tools and/or the resources at

his disposal. Having no single platform just amplifies

the issue, and as a result, there is inconvenience and

compromised satisfaction with travel.

This poses on society disadvantage in that it

denies society the best travel itineraries, leads to

overcharge and has negative effects on the

environment because of wrong travel paths and

overbooking of the accommodation facilities. It also

presents difficulties for the travel operators who are

already under pressure to satisfy user requirements

appropriately. The demand of more simplified and

easier to approach solution is highly essential to

improve the UX and business performances.

These challenges are responded to by the ‘GroQ

SQL Travel Planner’ that provides a single package

for flight procurement, as well as hotel bookings,

guiding services, and even climate-dependent

suggestions. Through Firebase Authentication,

Google Sign-In, and superbase CAPTCHA feature it

allows secure and efficient user login. Weather

Application by OpenWeatherMap API integrated

with AI along with GroQ empowered weather

Chatbot gives real time weather details \&

personalized travel recommendations. Besides, users

can sort places according to personal choice, for

example, the cost or the weather or other interests

they have thus providing results which will meet the

customers’ needs most.

This work is unique, as it proposes a true

integration of AI, safe authentication, and on-demand

dynamic data offering to create a customized travel

experience. The platform is accountable to UN

Sustainable Development Goals (UN SDGs) 9 and 12

758

Ramasamy, G., M., G., Rohan, G., A., V. C., Muppala, T. and Hemasri, M.

GroQ SQL Travel Planner: Book Flights, Hotels, Tours, Weather-Based Recommendations and Chatbot Support with Firebase Login and SuperBase Captcha.

DOI: 10.5220/0013943300004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 5, pages

758-766

ISBN: 978-989-758-777-1

on Industry; Innovation \& Infrastructure and

Responsible Consumption \& Production

respectively because it helps in reducing unending

wastage of resources while planning for travel.

The rest of this paper is organized as follows:

Section II contains the literature review followed by

Section III will give an overview of how the system

is implemented and the methodology and what major

features are. Section IV will provide details on

results. Section V will give information regarding

future work and conclusion and possible expansions

of this system.

2 RELATED WORKS

Ramasamy et al. developed a brain tumor

segmentation model based on Link-Net, using

ResNet152 as the backbone architecture and four

MRI modalities as the input. The proposed model

obtains a very promising performance in the BraTS

2020 dataset with a Dice coefficient of 0.7773 and a

Jaccard index of 0.7169. Future work will focus on

improving efficiency and performance at the pixel

level.

Tuba et al. present the porting of FreeRTOS to a

RISC-V architecture on the SPIKE simulator, with

improvements in documentation and maintenance.

They have made an assessment of its real-time

features-inter-process communication and mutex-

which guarantees that task creation, deletion, and

context switching are very efficient for time-critical

embedded systems.

Traykov et al., propose a testing framework that

could be used for LLPs to test their security

concerning known vulnerabilities, such as prompt

injection and denial of service. It was tested on three

models-Llama3-70b, Mixtral-8x7b, and Gemma-7b-

out of which one had flaws, proving the efficiency of

the framework. Future work includes increasing the

coverage done by tests and integrating it with

blockchain for transparent reporting.

Ramasamy et al., present an XGBoost framework

with hyperparameter tuning for the prediction of

Type-2 Diabetes Mellitus in the context of the PIMA

Indian Diabetes dataset. For this purpose, the model

is aggressively trained by using pre-processing,

feature extraction, and then 10-fold cross-validation.

L Bianchi et al. fine-tuned it with Grid Search; it

attained an accuracy of 94.5\%, outperforming SVM,

K-NN, and QDA.Reddy et al., present an AI-enabled

stress analysis system using GPT-3.5, designed to be

highly scalable by using NoSQL databases. A Flask

web application collects user input, analyzes the text

using AI, and provides specific suggestions regarding

stress management; MongoDB processes real-time

data in a secure manner.

Neszlényi et al., present AssistantGPT, a platform

that utilizes OpenAI's GPT API for both voice and

text-based tasks. Using a React interface and FastAPI

backend, it simplifies tasks like file management and

script execution. Evaluation results demonstrate a

62.5\% reduction in task times and increased user

satisfaction, highlighting its potential to boost

productivity, despite challenges such as internet

reliance and customization complexity.

Dong et al., examine cloud-native databases,

emphasizing their benefits such as elasticity and cost-

efficiency. It covers OLTP/OLAP architectures,

innovations such as compute-storage disaggregation,

and scalability methods. Case studies from

Snowflake, Redshift, and Aurora showcase improved

performance, with future research aimed at serverless

architectures, multi-cloud services, and security.

Zhou et al., examine the role of AI in improving

database functions and how databases support AI

deployment. It highlights innovations like deep

learning for cardinality estimation, reinforcement

learning for query optimization, and AI-powered data

cleaning. The study also explores challenges such as

hybrid data models and AI-DB co-optimization, with

future research focused on integrating AI with

databases to solve complex data challenges.

Pramono et al. present a secure authentication

framework for an employee presence system,

utilizing Firebase Authentication, RESTful APIs, and

JWTs. It ensures secure data exchange and optimal

performance, with future work focused on integrating

multi-factor authentication with biometrics for

enhanced security.

Rajappa et al., discuss the implementation of the

PingER project on Android devices, utilizing

Firebase to monitor global internet performance. The

Android app gathers real-time data on metrics like

latency, jitter, and packet loss, expanding the

coverage of the PingER network. The results

highlight successful performance monitoring, with

future plans to integrate advanced analytics and

visualization tools.

Nitu et al., improve a personalized travel

recommendation system (PTRS) by incorporating

recency effects using Twitter data. The system

employs machine learning for tweet classification,

sentiment analysis, and recency weighting, achieving

75.23\% accuracy and outperforming previous

models. Future efforts will aim to refine the models,

expand the dataset, and integrate additional social

media platforms.

GroQ SQL Travel Planner: Book Flights, Hotels, Tours, Weather-Based Recommendations and Chatbot Support with Firebase Login and

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Singh et al., present a MERN stack-based web

streaming application leveraging WebRTC and

RTMP for real-time, cross-platform video streaming.

The system provides low-latency, scalability, and

security, featuring adaptive bitrate and error recovery

capabilities. Plans for further development include

adding VR support, integrating social media, and

enhancing user analytics.

Kulkarni et al., present the development of an

online food ordering system with a recommendation

module, utilizing ASP.NET, SQL Server, and the K-

Nearest Neighbors algorithm. The system improves

user experience and restaurant operations by

suggesting items based on previous orders. The

results indicate enhanced customer satisfaction and

efficiency. Future developments will focus on

refining recommendations and enabling real-time

adaptation.

Manish et al., utilizess LLMs and NLP to optimize

resume parsing, processing resumes in 2.0 seconds

with high precision. Although format variability

poses a challenge, it enhances ATS by providing

structured and actionable insights.

Yeong et al., presents a telematics system that

utilizes IoT, cloud computing, and analytics for real-

time alerts and data-driven decisions, facilitating

machinery monitoring and optimization with the

potential for predictive analytics.

3 METHODOLOGY

The GroQ SQL Travel Planner is a web-based tool

implemented with a highly customizable and flexible

structure to support travel planning with a dynamic

and modular architecture. The architecture adopted in

the system development entails frontend, backend

and the database levels. Furthermore, other external

APIs and AI capabilities are incorporated to improve

the user interface of the application.

3.1 Frontend

• Built using React.js to provide an interactive

and responsive user interface.

• Includes pages for login, sign-up, and forgot

password, home, Navigation Bar, Hotel cards

along with main features like flight booking,

hotel reservation, guided tours, and weather

based travel recommendation chatbot.

• User authentication is handled through

Firebase, enabling secure login via

email/password or Google Sign-In.

• CAPTCHA verification is implemented using

hCaptcha to prevent bot access.

Figure 1: Entity-relationship diagram of GroQ-SQL travel

booking.

3.2 Backend

• Developed using Node.js and Express.js, the backend

serves as the intermediary between the frontend and

the database. Implements RESTful APIs for handling

user actions such as booking flights and hotels,

retrieving weather recommendations, and interacting

with guided tours. Includes custom endpoints to

dynamically fetch and filter user preferences in real-

time.

3.3 Database

• Uses MySQL to store and manage data such as user

information, hotels, flights, places, and booking

records. Structured with normalized tables for

optimized data retrieval and storage. User-related

data (e.g., name, email, and phone) is securely stored

and accessed through structured queries.

The Entity-Relationship (ER) diagram for the

GroQ: Shown in the context of the Travel Planner

Figure.1., proposed is a logical and well thought

through concept of the database schema which will

take the role in the system and allow the application

to readily support the process of travel management.

Fundamentally, there is the database relates many to

many relationship Users who make many Hotel

bookings Flights bookings and can be part of many

tours. They are linked with entities as Hotels which

have fields of hotel name, price and ratings, Flights

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containing fields such as source, destination and price

etc. It also include Places, in which hotels and flights

are directly connected to destinations, and Tours

which enables users to travel through various guided

tours. With relationships clearly defined through

cardinalities like 1: n and n: n, the schema has no

problem accommodating these transformational

scenarios and provides a solid foundation for

functionalities such as dynamic filters, real-time

updates and recommendation. Front-end is based on

React.js Framework, Back-end is Node.js, Database

is MySQL, and the system incorporates RESTful API

features such as an Open Weather Map for integrating

weather-based recommendations and a GroQ-based

AI Chat bot. For security guarantees, there is Firebase

Authentication to eliminate bot access while

Superbase CAPTCHA also helps to safe the system

from bot activity. Combined, this design enables the

user to have an easy way to plan and organize their

trip from one interface to another seamlessly.

3.4 External APIs and AI

OpenWeatherMap API: Provides weather data to

recommend travel destinations and activities based on

real- time conditions.

GroQ-based Chatbot: AI-driven chatbot assists users

with queries related to travel planning and

personalized recommendations.

Firebase Authentication: Ensures secure user login

with support for email/password authentication and

Google Sign-In.

Superbase Authentication: Superbase for Captcha

authentication and API using hCaptcha integration.

4 FUNCTIONAL MODULES

4.1 User Authentication and

Management

The module for User Authentication and

Management enforces proper access control when

users login into the application. Both the email &

password registration and Google sign-in are

supported for the application using Firebase

Authentication. The user enters their name, email,

phone number, validates the email format and

password and the application safely signs them up on

Firebase. Also, the collected user data is transferred

to the backend and saved into MySQL including

personal user data. The login process includes

Firebase authentication, and, to stop bots, we use

HCaptcha. Google Sign-In is also fortified with

CAPTCHA validation to make user verification

extremely effective. Users are offered two options to

regain access to their account if they forgot the

password: through email or phone number. If the reset

type is email, a password reset e-mail is forwarded to

the user, and they are given instructions on how to

safely alter a password. For phone-based resets,

Firebase’s RecaptchaVerifier is used to perform the

verification by sending the code to the user’s phone

then the password updates upon confirming the code.

Checks such as data format check, mismatch on

passwords, and reCAPTCHA add the security aspect

and improve the authenticity of the system to deliver

a safe authentication method. Figure. 2. Shows the

forgot password page while Figure. 4. Shows the

sign-up page.

Figure 2: Login page.

Figure 3: Forgot password page.

GroQ SQL Travel Planner: Book Flights, Hotels, Tours, Weather-Based Recommendations and Chatbot Support with Firebase Login and

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Figure 4: Signup page.

4.2 Home and Navbar

The Home Page is the primary system interface that

allows users to make a direct connection to primary

travel planning facilities such as flight schedules and

booking, hotel reservations, etc., weather and other

updates. As for it, the Navbar contains clear

navigation icons for such main areas as user

identification, history of orders, and travel

preferences. Figure.5. below shows the navigation

bar.

4.3 Chatbot

Chatbot GroQ Chatbot: Offers AI-driven assistance

to address user queries and provide personalized

travel recommendations. The ChatBotPopUp

component is integrated here as a button pop - up

which hovers over the screen on the bottom - right

corner. It moves up and down based on the visibility

of the” backToTop” button which has similar looks

and behavior. This window/ pop - up that hovers, has

two tabs where one is a chatbot that recommends the

user based on his location and holiday preference. It

can take everything into consideration from budget,

location, likes and dislikes. The GroQ based Chatbot

works with the ”llama3-8b-8192” model with an API

key that’s assigned to new users. Once a client object

is created in the code, it is programmed to take two

inputs: One is where we initialize a message to tell the

model how to perform. This gives the model context

of how it is supposed to behave, and what it’s

supposed to know before beginning a chat. This is

where we describe the bot that it is a travel

recommendation bot focused on India, and that its

goal is to provide specific travel recommendations

based on user input. The bot begins by greeting the

user and asking for their preferences, then provides a

destination suggestion. Since the bot has issues with

maintaining token length, and it looks odd in the chat

window, we ask it to maintain short and crisp

answers, and questions. And to address another issue

where it asks questions again and again, we ask the

model to not ask more than 3 questions whatever the

case is.

Figure 5: Home and navbar page.

After the initial message, we route the user

messages to the chat area, to which the model starts

to respond. These responses are then put into the chat

window which in turn makes it look interactive.

Weather Integration: Integrates

OpenWeatherMap API to offer real-time weather-

based suggestions. The weather integration is

implemented as a new tab since it gets complicated to

not get deeply involved with a model yourselves and

only depend on the API. This is because, to have a

model that does both recommendation based on user

preferences and recommend based on weather

conditions on the next few days. The major problem

is the one we arrive to over here, world standard, and

widely accepted models like LLaMa or GPT are not

given internet access to access weather APIs or

monitor weather conditions, or get regular updates on

news or whatever. So what we do here is, we update

the database once in every 24hrs of the latest data of

major cities in India, put it onto superbase’s

PostgreSQL database, it’s about 1160 reading (1

reading every 3 hours for over 5 days) monitoring

conditions like date - time, temperature, humidity,

weather description, and city name. Now this

PostgreSQL database can be read by a RAG model to

make decisions with the help of a base backbone

model like GPT or oLLaMa or Anthropic, with

combination of user preferences and season to make

a very sophisticated and specific combination and

concoction which works beautifully. Figure 6 shows

the Database UML Diagram.

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4.4 Database

• MySQL Database:

– Stores user details, flight and hotel data,

booking records, and guided tours.

– Ensures efficient data retrieval and secure

management of sensitive user information.

– Table Relationships: Designed to maintain data

integrity and optimize search and filter

operations.

Figure 6: Database UML diagram.

4.5 Airplane Booking

The flight booking system consists of three input

parameters that include source, destination, and travel

date to generate flight fares in real-time. Users can

choose flight options and a record is made in a

MySQL database which contains details of the

booking and the user is notified through a

confirmation pop up. It also guarantees easy linking

with a backend API to get place options and their

prices and update the price field in real time. The

locations are in dropdowns and dates in a calendar to

make the booking as easy as possible for the clients.

Figure 7. shows the flight bookings component.

Figure 7: Flights booking.

4.6 Tour Booking

The booking of the tours involves choosing from

available tour destinations provided, the cost for the

tour, image, and the reviews of the tour. With just a

click, users can secure the tours they want and will

only need a click to confirm the choice with the pop

up box; the tours are saved in a database associated

with the user account. A backend API is integrated to

save the bookings while the system was designed

with an attractive graphical design and dynamic

features to enhance the users’ interest. Figure. 10.

Shows the tour booking page.

4.7 Hotel Booking

The hotels page comprises a list of Hotels filtered by

locations and prices to help the users in selecting the

required hotels. Booking of the hotels can be done

very easily with all the bookings recorded in the

database and optional recommendations from the site

being included for greater usability. The system is

also dynamic especially with regards to input such as

destination and price range to ensure that a user gets

a friendly interface for efficient hotel bookings.

Figure. 11. Shows the Hotel bookings.

Figure 8: Hotel booking.

GroQ SQL Travel Planner: Book Flights, Hotels, Tours, Weather-Based Recommendations and Chatbot Support with Firebase Login and

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Figure 9: Tour booking.

Figure 10: Tour booking.

Figure 11: Hotel booking.

4.8 Backend

Express.js was used to create the backend which

interacts with a MySQL database to offer a variety of

travel-related services among them are the services of

user management, flight and accommodations, and

tour booking services. The endpoints include signing

up the user, getting flight prices, getting hotels by

location and price, and processing bookings; all

mysql database information is encrypted. Improper

backend also has capability to manage the last active

user which is quite useful for bespoke operations. The

high level of constants’ check, dynamic SQL

statement execution, and data validation are

considered as the crisp factors for the application and

its steady growth.

5 RESULTS

5.1 Hotel Booking

In the hotel booking part we have two ways, one is

through the search bar and one is through the home

page. when i click on the search bar in the navbar, a

list of places in the dropdown list will appear, when

you select a place it will redirect you to a new page

where all the hotels corresponding to that place will

be fetched from the database and displayed. when you

click on the ”+” button, an alert will appear if you

want to confirm the booking, if you click on okay then

the, the hotel bookings table in the database will be

undated. another way is to set the price range and

based on the price range and the selected place, the

filtered hotels based on the price range will be fetched

and displayed. The images related to Hotel Bookings

are displayed in Figure. 8.

5.2 Tour Bookings

In tour bookings the user can book multiple tours, and

once the + button is clicked an alert will be displayed

to confirm booking and the tour will be booked and

updated in the database. Figure. 9. shows all the

related images for Tour Bookings.

5.3 Airplane Booking

In the Airplane Bookings, the user has to choose the

source, destination and dates for travelling and the

price changes according to the source and destination

selected. If any one of the fields is not selected and

the ‘Book Flight’ button is clicked then a message

box will be shown. If all the details are filled it will

result in successful booking in the database. The alert

is shown in Figure. 12. while the database after a

booking is shown in Figure. 13.

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Figure 12: Alert for empty field before booking.

Figure 13: Updated database after airplane booking.

5.4 ChatBot Integration

Implementing a chatbot within the platform provided

a highly individualized travel planning due to the

GroQ-based model run by LLaMa3-8b. It was very

smart in anticipating the kind of inputs that you would

want to input like location, budget and preferred

locale to offer relevant travel advice. The AI

Integrated chatbot successfully provided contextual

recommendations with the integration of weather

details opted from the Open Weather Map API as

shown in Figure. 14. Metered logical data being used

was updated every one day to ensure that it was

sufficient and timely. For improved efficiency, the

use of follow-ups was moderate at most three in order

to avoid long strings of conversations that may bore

the user.

The user interface of the chatbot was designed to

appear as a pop up so as not to intrude with the rest of

the other modules of the platform. Its AI-based logic

focused on providing fluent and low delay

interactions that will enhance users’ perceived

satisfaction. The combination of the dynamic

visualizations of the weather updates as well as the

smart suggestion systems made the chatbot a very

useful tool that folds into the design of the interactive

travel planning well and effectively.

Figure 14: GroQ ChatBot integration.

6 CONCLUSIONS

Enter the GroQ SQL Travel Planner A Complete

Intelligent Solution to Modern Travel Planning

Problems It streamlines user convenience by

combining flight booking, hotel reservation, and

guided tours into one service. Utilizing current

technologies such as React. js, Node. js, and

MySQL, the system enables efficient and seamless

interactions. Adding Firebase Authentication and

Superbase CAPTCHA, protects your application

from unwanted interference. The user experience is

more personalized with real-time weather-based

recommendations and a GroQ-based chatbot that

makes travel more flexible and informative. The

modularity of the architecture allows for scalability

and future improvements/expansions. A well-

structured ER model enables dynamic filtering and

fast decisions, ensuring efficient data handling. This

example demonstrates the power of AI fetch-focused

help through its integration of the LLaMa and

OpenWeatherMap APIs. In conclusion, the project

takes a well-rounded approach by providing

optimized travel suggestions that account for both

user needs and environmental considerations. A solid

potential for application in the real world and allow

its evolvement in this travel tech space.

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