Chatbots in Kotlin: Creating a Smart Assistant from Scratch

Why Kotlin is the Ideal Language for Chatbots?

Have you ever wondered why more and more developers are choosing Kotlin for creating chatbots? This language is a true Swiss Army knife in the programming world. It combines the conciseness of Python, the power of Java, and modern features that turn writing a bot from a chore into a pleasure.

Imagine: you are writing a bot for Telegram that needs to handle hundreds of requests per second. In Python, you would struggle with the GIL (Global Interpreter Lock); in Java, you would drown in boilerplate code. Kotlin, however, offers coroutines for asynchrony and zero-cost abstractions. In this guide, we will create a full-fledged chatbot from scratch — from registration in Telegram to deployment on a server.

What will you get in the end?

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• A working bot that responds to commands and carries on a conversation
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• An understanding of chatbot architecture in Kotlin
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• Ready-to-use code that you can immediately apply in your projects
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Step 1: Setting Up the Environment and Getting a Token

First, you will need a bot token. Go to Telegram, find @BotFather, and create a new bot. The /newbot command — and you get the coveted token in the form 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11. Save it in local.properties — never commit tokens to the repository!

Now create a project. I recommend using Gradle Kotlin DSL — it's the modern standard. Here is the minimal build.gradle.kts:

plugins {\n    kotlin("jvm") version "1.9.22"\n    application\n}\n\ndependencies {\n    implementation("io.ktor:ktor-client-core:2.3.7")\n    implementation("io.ktor:ktor-client-cio:2.3.7")\n    implementation("org.jetbrains.kotlinx:kotlinx-coroutines-core:1.8.0")\n    implementation("com.google.code.gson:gson:2.10.1")\n}\n\napplication {\n    mainClass.set("MainKt")\n}

Note: we use Ktor Client for HTTP requests to the Telegram API and Gson for parsing JSON. Kotlin serialization would also work, but Gson is simpler to start with.

Step 2: Basic Bot Structure

Any chatbot is an infinite loop: get an update → process it → send a response. Telegram uses long polling (the getUpdates method) or webhooks. We will implement polling — it's simpler for local development.

Create a base class TelegramBot:

class TelegramBot(private val token: String) {\n    private val client = HttpClient(CIO)\n    private val baseUrl = "https://api.telegram.org/bot$token"\n\n    suspend fun getUpdates(offset: Long = 0): List<Update> {\n        val response: HttpResponse = client.get("$baseUrl/getUpdates") {\n            parameter("offset", offset)\n            parameter("timeout", 30)\n        }\n        val body = response.body<String>()\n        val apiResponse = Gson().fromJson(body, ApiResponse::class.java)\n        return apiResponse.result ?: emptyList()\n    }\n\n    suspend fun sendMessage(chatId: Long, text: String) {\n        client.post("$baseUrl/sendMessage") {\n            parameter("chat_id", chatId)\n            parameter("text", text)\n        }\n    }\n}

The Update class is a data class that maps to the JSON response from Telegram. Here is what it looks like:

data class Update(\n    @SerializedName("update_id") val updateId: Long,\n    val message: Message? = null\n)\n\ndata class Message(\n    @SerializedName("message_id") val messageId: Long,\n    val text: String? = null,\n    val chat: Chat\n)\n\ndata class Chat(val id: Long)\ndata class ApiResponse(\n    val ok: Boolean,\n    val result: List<Update>? = null\n)

Step 3: Command Handling — The Heart of the Bot

Now for the most interesting part — let's teach the bot to understand commands. In Kotlin, this can be done el