Chatbot development has become easier than ever, even for beginners with no coding experience. In today’s digital era, businesses, websites, and personal projects greatly benefit from automated conversations that improve engagement and customer support. If you’re wondering how to make a chatbot in a few basic steps for FREE, you’re in the right place! This guide will walk you through simple, beginner-friendly methods to build your own chatbot without spending money — using popular tools and platforms that offer free plans. Whether you want a chatbot for customer service, lead generation, or personal assistance, you’ll be able to create understand and launch one effortlessly by the end of this article. lets first learn what a chatbot is.
What is a Chatbot?
A chatbot is a piece of software that mimics human speech or text communication. It understands user inquiries and automatically generates pertinent answers using natural language processing (NLP) and artificial intelligence (AI). Chatbots are used in customer support systems, messaging apps, websites, and apps to help users and businesses communicate more quickly and effectively without requiring human intervention.
Chatbots are frequently employed for:
- Responding to questions from customer service
- Helping people navigate websites
- Automating reservations and information retrieval
- serving as personal helpers
I hope we now know what a chatbot is. In the following step, we will discover why we are using Livekit.
What is Livekit?
LiveKit is an open-source platform designed for building real-time audio, video, and data streaming applications. It provides the infrastructure and APIs needed to enable live communication features, such as voice calls, video calls, and interactive streaming, directly inside your applications.
Key features of LiveKit include:
- Ultra-low latency communication
- Scalable architecture for large audiences
- WebRTC-based real-time media streaming
- Support for multiple languages and frameworks
- Open-source flexibility for developers
Why we are using Livekit?
In order to create sophisticated, interactive AI chatbots that can listen, react, and speak instantly, just like a human, we use LiveKit because it facilitates real-time communication.
LiveKit is the best option for the following reasons:
- Because LiveKit manages low-latency streaming, your chatbot can hear and react instantly. Conversations become more fluid and organic as a result.
- LiveKit integrates seamlessly with speech-to-text (Deepgram) and text-to-speech (Cartesia), allowing you to build voice-enabled AI assistants instead of basic text-only bots.
- LiveKit scales effectively whether you’re building for 10 users or 10,000. It is designed to support real-time applications such as live support systems, virtual classrooms, and conferencing tools.
- LiveKit can be integrated with backend systems, mobile apps, Python, and JavaScript. It is adaptable and compatible with Gemini and other AI APIs.
in the next step we are going to learn about all the tools we are using to create chatbot and why we are using that.
Tools we are using.
When learning How To Make A Chatbot, choosing the right tools is the most important step. The best part? You can build a smart and voice-enabled chatbot completely free using modern AI technologies. Below are the essential tools we will use to create a chatbot that understands speech, talks naturally, and engages users in real time.
1. Gemini API
Google’s Gemini API adds powerful AI to your chatbot. It helps analyze user input, understand context, and generate smart responses — a key feature when learning How To Make A Chatbot with advanced conversational abilities.
API Link : https://aistudio.google.com/api-keys
2. LiveKit
LiveKit enables real-time communication. If you want your chatbot to support live voice or video interaction, LiveKit makes it possible with fast, low-latency streaming technology.
API Link: https://cloud.livekit.io/projects/p_5h4bzla2rzz/settings/keys
Note: You must create and Livekit Account and create a sandbox to get API Keys.
3. Deepgram
Deepgram provides speech-to-text capabilities. It listens to the user’s voice and converts spoken words into text, helping your chatbot respond accurately during voice conversations.
API Link: https://developers.deepgram.com/docs/create-additional-api-keys#create-an-api-key-using-the-deepgram-api
Cartesia
Cartesia handles text-to-speech, giving your chatbot a natural and human-like voice. This creates a more interactive and realistic chatbot experience.
API Link: https://play.cartesia.ai/keys
Now that we have learned everything about chatbot, next step will get into the core coding.
The coding part
Now that you have all the required API keys, it’s time to build your chatbot! Follow these simple steps to set up your project and start coding your first AI chatbot for free.
✅ Step 1: Create a Project Folder in VS Code
Start by opening Visual Studio Code and creating a new project folder. This will be the main workspace where you will write your Python code and store configuration files needed for the chatbot.
Tip: Name the project something clear like
voice-chatbot-projectso you can easily locate it later.
✅ Step 2: Set Up Environment Variables (API Keys)
Inside your project, create a .env file and safely store all your API keys from Gemini, LiveKit, Deepgram, and Cartesia.
This keeps your sensitive keys secure and separate from your main code.
GEMINI_API_KEY=your_key_here
LIVEKIT_API_KEY=your_key_here
LIVEKIT_SECRET=your_secret_here
LIVEKIT_URL=your_url_here
DEEPGRAM_API_KEY=your_key_here
CARTESIA_API_KEY=your_key_here
✅ Step 3: Build Your Python File
Create a new Python file — for example, chatbot.py. This file will include all the logic to:
from dotenv import load_dotenv
import os
import asyncio
from livekit import agents
from livekit.agents import AgentSession, Agent, RoomInputOptions
from livekit.plugins import (
cartesia,
deepgram,
noise_cancellation,
silero,
google, # LiveKit Google plugin
)
from livekit.plugins.turn_detector.multilingual import MultilingualModel
# Load environment variables
load_dotenv(".env")
# Ensure GOOGLE_API_KEY is set for the LiveKit Google plugin
gemini_key = os.getenv("GEMINI_API_KEY")
if not gemini_key:
raise RuntimeError("Missing GEMINI_API_KEY in .env")
os.environ["GOOGLE_API_KEY"] = gemini_key # critical for LiveKit plugin
# --- Agent definition ---
class Assistant(Agent):
def __init__(self) -> None:
super().__init__(instructions="You are a helpful voice AI assistant.")
# --- Entrypoint for LiveKit worker ---
async def entrypoint(ctx: agents.JobContext):
deepgram_key = os.getenv("DEEPGRAM_API_KEY")
cartesia_key = os.getenv("CARTESIA_API_KEY")
if not deepgram_key:
raise RuntimeError("Missing DEEPGRAM_API_KEY in .env")
if not cartesia_key:
raise RuntimeError("Missing CARTESIA_API_KEY in .env")
session = AgentSession(
stt=deepgram.STT(
api_key=deepgram_key,
model="nova-3",
language="multi"
),
llm=google.beta.realtime.RealtimeModel(
api_key=gemini_key, # ✅ pass it explicitly
model="gemini-2.0-flash-exp",
voice="Puck",
temperature=0.8,
instructions="You are a helpful multilingual assistant",
),
tts=cartesia.TTS(
api_key=cartesia_key,
model="sonic-2",
voice="f786b574-daa5-4673-aa0c-cbe3e8534c02"
),
vad=silero.VAD.load(),
turn_detection=MultilingualModel(), # default constructor
)
room_options = RoomInputOptions(
noise_cancellation=noise_cancellation.BVC()
)
await session.start(
room=ctx.room,
agent=Assistant(),
room_input_options=room_options
)
await session.generate_reply(
instructions="Greet the user and offer your assistance."
)
if __name__ == "__main__":
agents.cli.run_app(agents.WorkerOptions(entrypoint_fnc=entrypoint))Now run the file using pip
✅ Connect with Gemini API for chatbot responses
✅ Convert speech to text using Deepgram
✅ Convert text to speech using Cartesia
✅ Manage voice communication via LiveKit
This is where the real magic happens — you will write the code that makes your chatbot listen, think, and talk like a human.
Conclusion
Learning How To Make A Chatbot is no longer difficult or expensive. With the free tools we covered — Gemini API, LiveKit, Deepgram, and Cartesia — anyone can build an intelligent, real-time voice chatbot without spending money. By following the simple steps in this guide, you can set up your project, secure your API keys, and start coding your chatbot in just a few minutes.
Whether you’re creating a chatbot for customer support, a business website, or personal use, knowing How To Make A Chatbot gives you a powerful skill in today’s AI-driven world. So don’t wait — explore these free AI tools, experiment with features, and continue learning How To Make A Chatbot more advanced and interactive.
Your first chatbot is just the beginning. Now, you have everything you need to turn your ideas into a smart, talking AI assistant!
FAQs
1. What is the easiest way to learn How To Make A Chatbot?
The easiest way to learn How To Make A Chatbot is by using free AI tools such as Gemini API, LiveKit, Deepgram, and Cartesia. These platforms allow beginners to create intelligent chatbots without advanced coding knowledge.
2. Do I need programming skills to build a chatbot?
Basic programming skills, especially in Python, are helpful. However, you can also use no-code chatbot platforms to quickly build simple chatbots while learning the fundamentals of How To Make A Chatbot.
3. Is it really free to make a chatbot?
Yes. Many AI platforms offer free API plans that allow you to learn How To Make A Chatbot without any cost. Paid plans are only needed if you require higher limits or advanced features.
4. Which programming language is best for chatbot development?
Python is widely recommended for learning How To Make A Chatbot because it is beginner-friendly and supports powerful AI and speech-processing libraries.
5. Can a chatbot talk like a human?
Yes. By integrating text-to-speech tools like Cartesia and advanced AI models like Gemini, your chatbot can understand human input and respond in a natural, human-like voice.
6. Where can I deploy my chatbot once it’s ready?
You can deploy your chatbot on websites, mobile apps, messaging platforms like WhatsApp or Telegram, or business tools such as CRM and helpdesk systems.
7. How long does it take to make a chatbot?
By following a step-by-step guide and using free APIs, you can build a functional chatbot in just a few hours. With practice, creating more advanced chatbots becomes faster.
