Building a Multilingual Chatbot with SEA-LION: A Step-by-Step Guide

ByAISG | AI Products

In today’s rapidly evolving digital landscape, the ability to communicate across languages is more important than ever. Whether you’re building a customer service bot, an AI assistant, or any other type of interactive application, ensuring your chatbot can handle multiple languages is a step toward reaching a global audience.

Enter SEA-LION — a multilingual large language model (LLM) that enables developers to integrate multilingual capabilities into their chatbots. SEA-LION offers out-of-the-box support for English, Thai, Vietnamese and Bahasa Indonesia. In this guide, we’ll walk you through the process of leveraging SEA-LION to run a chatbot that can engage users in multiple languages.

Multilingual Chatbot

The chatbot is powered by the SEA-LION v3 model, the latest model at the time of writing. It acts as a starting point for a chatbot web app, that can be further extended to include features like retrieval-augmented generation (RAG).

Under the hood, the chatbot is built with Chainlit, an open-source async Python framework which allows developers to build scalable conversational AI applications.

Prerequisites

Before diving into the multilingual chatbot with SEA-LION, there are a few tools that are required on your development machine.

Guide

Pull the SEA-LION model with Ollama.

ollama pull aisingapore/Gemma-SEA-LION-v3-9B-IT:q4_k_m

Clone the repository: https://github.com/aisingapore/sealion-chainlit-ollama

git clone https://github.com/aisingapore/sealion-chainlit-ollama

Change the location to the project directory.

cd sealion-chainlit-ollama

Before launching the chatbot, it is a good practice to create a virtual environment to isolate the app. Please follow these steps to create a virtual environment, or feel free to use your preferred tool.

Create a virtual environment in the project directory.

python -m venv venv

Activate the virtual environment.

source venv/bin/activate

Copy .env and update the values, if necessary.

cp .env.example .env

Install the packages.

pip install -r requirements.txt

Launch the app.

chainlit run src/main.py -w

Navigate to http://localhost:8000 to access the chatbot.

Further Work

Please feel free to fork the repository at https://github.com/aisingapore/sealion-chainlit-ollama and add more features. For example, integrate a knowledge base or external API to expand the chatbot’s ability to provide more specific and dynamic responses.

The SEA-LION models are available for download from Hugging Face (https://huggingface.co/aisingapore) and Ollama (https://ollama.com/aisingapore). SEA-LION is released under the MIT License, which allows users to freely use, modify, and distribute the software, subject to certain conditions.

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