Multilingual Chatbot with Azure AI Studio, Phi-3 Mini, GPT-4 and Azure AI Translator
Published May 21 2024 09:00 AM 2,482 Views

In today's globalized world, businesses and developers are increasingly seeking to create applications that can interact seamlessly with users across different languages. A multilingual chatbot is a powerful tool for achieving this, allowing for real-time interaction in the users' native languages. This guide will introduce you to creating a sophisticated chatbot using Azure AI Studio, Phi-3-mini deployment for the chatbot framework, GPT-4 for assistant framework, Azure AI Translator for real-time translation to improve Phi-3-mini and GPT-4 response quality for international languages.


In this era of globalization, creating applications that cater to a global audience is more crucial than ever. A multilingual chatbot serves as an effective tool for businesses aiming to provide seamless customer service across different languages. This technical guide will walk you through developing a multilingual chatbot using Azure AI Studio to deploy Phi-3-Mini for chatbot and GPT-4 for Assistants. Translator is added to the workflow to improve Phi-3 and GPT-4 response quality for international languages. 


Overview of Technologies

  • Azure AI Studio: A comprehensive suite of machine learning tools that allow developers to deploy and finetune AI models.
  • Phi-3 Mini: A lightweight version of the Phi-3 framework designed for building intelligent and scalable chatbots with ease.
  • GPT-4: For assistants' framework.
  • Translator: A cloud-based API that provides real-time text translation across multiple languages.
  • React: A popular JavaScript library for building user interfaces, particularly single-page applications that are dynamic and high performing.
  • Uvicorn and Quart: An Asynchronous Server Gateway Interface for FastAPI applications for async web calls between React and backend services which handles Phi-3-mini and GPT-4 API calls.


Building the solution

Step 1: Prerequisites
  • Log into Azure AI Studio: Start by creating a new project and selecting the Phi-3-mini model best suited for your chatbot, likewise GPT-4 for assistant. Azure AI Studio offers various pre-built models or the option to finetune a custom model. This solution leverages Phi-3 and GPT-4.
  • Test and Deploy: After deploying a model, test within Azure AI Studio playground to ensure it accurately understands and processes queries. Once satisfied, collect the model endpoint and API key. Refer to Deploy models, flows, and web apps with Azure AI Studio - Azure AI Studio | Microsoft Learn for more details.

Step 2: Setting Up Your Development Environment

Clone the project from GitHub repo and follow the project setup mentioned in README file.

GitHub repoMicrosoftTranslator/azure-phi3-gpt4-AzureTranslator-playground (


Step 3: Building your own Chatbot/Assistant solution with React 

  1. Use the playground as a starting point to implement multilingual chatbot/assistant agent – Once the playground UI is running, you can make query requests to both Phi-3-mini and GPT-4 while toggling Azure Translator switch to see the quality impact when the using low resource languages.
  2. Take a deep dive into the code to learn how to use the Azure OpenAI chat and assistants APIs, and Azure Translator.
  3. Integrate Azure AI Model: Use the endpoint and API key from Azure AI Studio to integrate your solution with Phi-3-mini and GPT-4. 
  4. Add Microsoft Translator – Enhance your chatbot to support multiple languages by integrating Microsoft Translator. Wrap user inputs and chatbot responses with translation calls to ensure your chatbot can understand and respond in the user's preferred language.


This short video explains the business use-case and benefits.


Responsible AI Best Practices and Development Considerations 

  • Privacy and Data Handling – Ensure you comply with data protection regulations, especially when dealing with user inputs in different languages.
  • Cultural Sensitivity – Be mindful of cultural differences in your chatbot's responses. What works in one language or culture might not be appropriate in another.
  • Continuous Improvement: Use analytics and user feedback to continuously improve your chatbot's performance and user experience.
  • Leverage Microsoft Responsible AI principles using Azure AI Content Safety.
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Last update:
‎May 15 2024 12:23 PM
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