24/7 customer support without hiring additional staff

“You’ve got to start with the customer experience and work back toward the technology – not the other way around.”

— Steve Jobs

Market monopoly is a myth except for the very rare lucky few. For the rest of us, reducing the time to market from ideation to delivery has gained paramount importance. However, product owners also have to factor in changing expectations of their target market for the customer is the undisputed king.

Digitalization has made user-friendly, quick, and effective customer service even more important as people do not want to wait in queue or listen to an impersonal IVR. They want rapid solutions to their problems and so businesses are hard-pressed in the race to stay up to date or be left behind. After-sales service matters as much as pre-sales which is why the use of chatbots for customer service is gaining popularity.

“You should message a business just the way you would message a friend.”

— Mark Zuckerberg

And this is exactly where a custom java application and OpenAI- ChatGPT enter the picture as customers increasingly want a more personalized and social approach. That is why our team at Sunflower Lab ensures that when providing digital solutions to our clients, we are there from ideation to support. And using language models like ChatGPT can help in naturalizing the interaction process i.e., making it literally feel more humane to users.

Chatbot with ChatGPT & Java Needs :  Framework 

ChatGPT is an interactive pre-trained language model which can function as a powerful tool for IT businesses and enterprises alike. Developers prefer Java as the same language can be used at the front end and back end. By pairing JavaScript with ChatGPT’s powerful NLP interface you have the digital solution recipe to success in customer service solutions.

If you have a project in mind and require an expert’s advice on digital solutions, reach out to our Sunflower Lab team of experts by clicking here!

What is ChatGPT?

ChatGPT has been created by OpenAI as a language model that is able to process natural language responses to inputs from users. Though not specifically created to be geared towards customer service, it is versatile and hence, can be used in building chatbots designed with interactive customer service as the end.

ChatGPT is dynamic and can be integrated into Java web applications adding power to a custom-made Java web applications application. However, API would have to be leveraged for the same as there is no direct ChatGPT Java API. This means you would require a team of experienced developers who are up to the task of providing innovative digital transformation to clients.

Also, the process for such a custom java application would require building the necessary logic in Java so that it is able to handle the user’s input and accordingly display responses. Through the Application Programming Interface (API), developers are able to merge ChatGPT’s capabilities into the Java API or Java web application or platform.

Building a Chatbot with ChatGPT and Java

While ChatGPT can handle several programming languages, Java has come to be preferred. Since ChatGPT does not have a specific language of its own it relies on its API for integration. To simplify the process, our team of experts at Sunflower Lab, have created a 5-point list that details the entire process so that you know what you are getting into.

Through the Natural Language Processing (NLP) and Artificial Intelligence (AI) capabilities of ChatGPT, when paired with Java, users will be provided with a more natural interface during chatbot interactions. It will make the chatbot better able to understand human language and respond accordingly.

To get started building your own custom chatbot using ChatGPT and Java, follow these steps:

(1) Framework

  • For the HTTP requests to ChatGPT’s API a Java framework or library will be required. For this you can use Apache HTTP Client, OkHttp and Java HTTP Client.

(2) API

  • Considering that Java is to be the language, you will need to first have a ChatGPT API account set up. Ensure that Java integration is offered by the provider. Some examples of the same are OpenAI and Hugging Face.

(3) Logic

  • Now comes the communication aspect. The chatbot’s logic is integral as this is what processes the user’s input, then sends the same to the ChatGPT’s API, and then, displays the final response to the user. Java simplifies things here as it has built-in text processing capabilities. These consist of natural language or regular expression processing libraries. These help in understanding as well as interpreting the user’s input.

(4) Integration

  • The next step is the integration of ChatGPT into the chatbot. Now that the basic logic of the chatbot is in place the integration of the ChatGPT’s API has to be done into the Java code. For this Java’s HTTP library will be used for sending requests to ChatGPT’s API and then getting the responses.

(5) Testing

  • And finally, we come to the testing and refining part of things. Post-integration of ChatGPT, things don’t end, and testing is required so that you are certain that things are functioning as they should. Testing needs to be thorough as this will help in checking that appropriate responses are being generated. Also, based on test user feedback and results you might have to refine and fine-tune the chatbot’s logic.
  • Thus, you will need a team that has a fine blend of Java based programming skills with the added understanding of the integration of external API into Java code.

Sunflower Lab can make things easy for you here as we can provide an on-demand digital product team. With the right resources and tools customer support can thus definitely be enhanced by a Java API and ChatGPT-powered chatbot.

Best Practices for Designing User Interfaces with Chatbots

“A user interface is like a joke. If you have to explain it, it’s not that good”.

—  Martin Leblanc

Since we are talking about customer support, just consider what kind of customer support experience you would like yourself. Putting oneself into the customer’s shoes might very well just be the best yardstick out there. And here’s where proper UI and UX design become so integral.

When Nomad Bite wanted an innovative twist to food delivery through a custom app for ethnic cuisine delivery it only came to Sunflower Lab with this objective. However, through the ideation, user profiling, and prototype stages, our team transformed this concept digitally to make the app a feast for the eyes as well as the senses.

A functional, user-friendly and intuitive interface is what gives the best user experience as the Nomad Bite App proves. And the same guiding principles apply to customer support as well.

Here are some best practice tips to get you started:

  • Institutive Design – A chatbot needs to be natural and conversational with a simple user interface that is easy to use (refer to the quote). When people have a question they want an immediate answer, they certainly don’t want to waste time learning how to get to that answer, Thus, your user needs to be able to intuitively understand what the next step and they need to have clear options listed.
  • Language – With ChatGPT on board things should be more natural due to its use of NLP. Users prefer a conversational style of answers that are to the point and easy to understand. If the language is more natural and like real life, users will be able to derive more value from the exchange which is what we are looking for. Technical jargon and complex sentences, therefore, need to be steered clear from as they would only serve to confuse.
  • Accessibility – The text should be easy to read, and the layout shouldn’t be distracting. A minimalist design is best with the sparing use of colors. Also, since communication is about information processing here, we need plain language with the use of images only when actually required. Commands (if any) need to be clearly listed.
  • Clarity – It is important that the user is confident about the chatbot’s understanding of the request or query. For this, the chatbot should be programmed to provide an update on its understanding of the same and its course of action. Furthermore, if users can review their past interactions, it will make the process easier for them.
  • Test – User experience can only be improved through monitoring and frequent testing of the chatbot as the interface might have to be changed from time to time. There are, after all, always avenues for improvement and so user feedback is crucial here. Also, an interface of a sequence of single question-answer is easier.

While designing an effective UI isn’t always easy, it’s important if you want your users to have a positive experience interacting with your chatbot! Sunflower Lab can take away this hassle by providing you with an experienced and on-demand team! Here’s a look at work done by our experts.

The Advantages of Using ChatGPT & Java API for Customer Support Chatbots

Advantages ChatGPT  Advantages of Java 
Understands & emulates human-like responses  It has several libraries and frameworks that can be used int eh building of chatbots like Apache Lucene, Spring Boot and Vaadin 
Able to understand complex subject due to a vast knowledge bank  Scalable and so can handle peaks and traffic as well as serving several users at the same time 
Improves responses based on interaction  Multi-platform compatibility allows it to run consistently in Linux, Mac, and Windows 
Versatile and hence, can be used to create chatbots for websites, voice assistance, messaging apps & social media, etc.  Highly secure and thus, can handle sensitive client data without compromising it 


Through the integration of ChatGPT and Java with chatbots, a more efficient and competition savvy chatbot can be built. With the right designers and developers on the team you can maximize the potential offered. For instance, you could integrate the Java API with your CRM system for a more personalized user-experience.

Sunflower Lab can assist you with this and other digital needs of your project. Furthermore, your idea will be 100% protected by our non-disclosure agreement. So, let’s discuss your project today!

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Kotlin Vs. Java - Which One To Choose?

Even though Java has more universal acceptance over Kotlin, there are a few instances where Kotlin scores over Java. Find how Kotlin is a better choice.

The newer, lightweight Kotlin, ideally suited for designing back-end systems for large sized companies, aimed to make existing Java models more powerful, resolve API related issues and improve the Android mobile development platform.

The release of Java 8 presented many new features that developers were eagerly waiting for. However, Java is not a modern language. Android supports a few Java 8 features. Moreover, Java has some well documented language issues, including endless try-catch blocks, a lack of extendibility and null pointer exception issue – Not to mention a lack of support for programming features

In spite of the fact that Java has begun to add some functional programming elements – lambda expressions and functional interfaces – at its core Java is still a procedural language. Java supports a verbose syntax, unlike many other advanced programming languages.

Advantages of Kotlin

So you may want to consider switching to one of the many modern programming languages designed to run on JVM. There is no shortage of programming languages which compile to Java bytecode. There are a few factors that make Kotlin stand out from the crowd:

Like many modern programming languages, Kotlin aims to bring you the best of both the worlds by combining certain elements and concepts from procedural and functional programming.

What Java has that Kotlin does not

  • Checked exceptions
  • Primitive types that are not classes
  • Static members
  • Non-private fields
  • Wildcard-types
  • Ternary-operator a ? b : c

What Kotlin has that Java does not

  • Lambda expressions + Inline functions = performant custom control structures
  • Extension functions
  • Null-safety
  • Smart casts
  • String templates
  • Properties
  • Primary constructors
  • First-class delegation
  • Type inference for variable and property types
  • Singletons
  • Declaration-site variance & Type projections
  • Range expressions
  • Operator overloading
  • Companion objects
  • Data classes
  • Separate interfaces for read-only and mutable collections
  • Co-routines

custom jackson serializer

Using Jackson To Write A Custom Jackson Serializer

JsonNullSerializer to send empty string instead of null value – Set them to “empty string”.

In this article, we’re going to look at a more advanced “use-case” of using Jackson to write a custom serializer.

Here are the steps (for Jackson < 2.0):

Step 1: Add Jackson libraries to your environment.

For Maven

<!– https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-core –>






For Gradle

// https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-core
compile group: ‘com.fasterxml.jackson.core’, name: ‘jackson-core’, version: ‘2.9.4’

Step 2: Write your custom null serializer.

import java.io.IOException;
import com.fasterxml.jackson.databind.JsonSerializer;
import com.fasterxml.jackson.databind.SerializerProvider;

public class NullSerializer extends JsonSerializer<Object>

public void serialize(Object o, com.fasterxml.jackson.core.JsonGenerator jsonGenerator, SerializerProvider serializerProvider) throws IOException,    com.fasterxml.jackson.core.JsonProcessingException { jsonGenerator.writeString(“”);


Step 3: Register this with Jackson object mapper.

import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.ser.DefaultSerializerProvider;
import com.XXX.NullSerializer;

public class CustomObjectMapper extends ObjectMapper
public CustomObjectMapper()

DefaultSerializerProvider.Impl sp = new DefaultSerializerProvider.Impl();
sp.setNullValueSerializer(new NullSerializer());

Step 4: Register this object mapper with Spring MVC by creating a bean in your Spring application class.

package com.sfl.is.mfn;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.SerializationConfig;
import com.XXX.CustomObjectMapper;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.actuate.autoconfigure.*;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.boot.autoconfigure.liquibase.LiquibaseProperties;
import org.springframework.boot.context.properties.EnableConfigurationProperties;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.ComponentScan;
import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
import org.springframework.web.servlet.config.annotation.WebMvcConfigurerAdapter;

import javax.annotation.PostConstruct;
import java.net.InetAddress;
import java.net.UnknownHostException;
import java.util.Arrays;
import java.util.Collection;

@EnableAutoConfiguration(exclude = { MetricFilterAutoConfiguration.class, MetricRepositoryAutoConfiguration.class })
@EnableConfigurationProperties({ LiquibaseProperties.class, ApplicationProperties.class })

public class NullToEmptyApplication
private static final Logger log = LoggerFactory.getLogger(MindfullnessWebApiApp.class);
public NullToEmptyApplication()


public static void main(String[] args) throws UnknownHostException
SpringApplication app = new SpringApplication(NullToEmptyApplication.class);

public ObjectMapper jacksonObjectMapper()
return new CustomObjectMapper();

public SerializationConfig serializationConfig()
return jacksonObjectMapper()

java lambda expressions

Java Lambda Expressions

Lambda expression is one of the new features of Java 8. It is mainly used to implement functional interfaces. This article covers 3 aspects:

  1. Traditional Approach (Anonymous Inner Class)
  2. New approach (Lambda Expression)
  3. Pros and cons of Lambda

1. Anonymous inner class

It is used for implementing interfaces or evoking the override methods of a class and/or an interface. it is declared and instanced at the same time. Just like creating an instance and defining local variables, it is created locally in the method, or at the class level. It does not have a name for itself so that’s why it is called an “Anonymous” inner class.

Image 1

In the above code, the snippet PerformCalulation is implemented when its interface is called. This is the anonymous inner class and its implementation overrides the calculate method.

Lambda Expression

It is used for implementing the functional interface.

What is a functional interface?

An Interface with only one abstract method is called a functional interface. A “@FunctionalInterfaceannotation is used to indicate a functional interface.

Image 2

In the above code, the snippet PerformCalculation interface is the functional interface. If you check Image 1 and Image 2, both will print 5. In image 2 we have used a Lambda Expression in lines 10 to 12.

Syntax of Lambda

(Parameter 1,Parameter 2)  ->  { method body }


  • Parameters 1 and 2 are argument lists which are passed on to the method.
  • The arrow mark is used to separate the argument list and the method body.
  • (the method body is the actual implementation of the method)

There are other syntaxes for lambdas and they depend upon the argument list as well as the method body:


Syntax Explanation
() -> true; // 0 parameters
a -> a.startsWith(“test”);   // 1 parameter
(String a) -> a.startsWith(“test”); // 1 parameter
(a, b) -> a.startsWith(“test”);      // 2 parameters
(String a, String b) -> a.startsWith(“test”); // 2 parameters
a, b -> a.startsWith(“test”); // DOES NOT COMPILE
a -> { a.startsWith(“test”); }; // DOES NOT COMPILE
a -> { return a.startsWith(“test”) }; // DOES NOT COMPILE

The sixth snippet is not compiled because if there is more than one argument it should be enclosed in a parentheses “().” Moreover, if you define an argument, it should be enclosed in parentheses too.

The seventh snippet is not compiled because it does not have a “return statement” – If you use braces “{}”  in the body than you should have a return statement in the body.

The eighth snippet will not compile because the line is missing a semicolon.

3. Pros and Cons of Lambda


  1. It has a simple, and easily readable syntax as compared to the anonymous inner class.
  2. It reduces the number of lines and boilerplate code in comparison to the anonymous inner class. In the code below, the highlighted blue syntax lines can be removed if we use Lambda.

3. When we compile the class containing the anonymous inner class, it will create one extra class file for the anonymous  class.

      Here the Lambda1$1.class file is created due to the anonymous class. However, if we  

      compile Lambda it will not create a class file.


We can only use it when we implement the functional interface.