Create AI RAG ChatBot using your own data and Azure AI Studio | Step-by-Step Tutorial

🚀 Create a AI RAG Chatbot using your custom data and azure AI Studio.

In this video, we'll walk you through the process of creating a powerful AI chatbot using your own data! Learn how to leverage AI Studio and deploy GPT models to build a Retrieval-Augmented Generation (RAG) chatbot that can understand and respond to user queries with your customized information.

🌟What you'll learn:

- Getting to know how to set up project and hub in Azure AI Studio.
- Creating resources.
- Deploy GPT models.
- Create a simple Chatbot with your custom data.

📖 Chapters
00:00 Azure AI Overview
01:15 Setting Up Project
07:00 Deploying Models
10:42 Chatbot Configuration
14:04 Custom Data Integration
20:05 Test the Chatbot with custom data
22:06 Conclusion

🔍Azure AI Studio FAQ

1. What is Azure AI Studio?Azure AI Studio is a centralized platform provided by Microsoft Azure that offers a collection of AI services and tools, including access to language models like GPT-3 and GPT-4, as well as machine learning tools and AI services for speech and vision.

3. What are hubs and projects in Azure AI Studio?In Azure AI Studio, a hub allows you to create shared resources that can be used across different projects. A project is where you build individual services that can also be shared and worked on by multiple collaborators.

4. How do I create a new project in Azure AI Studio?To create a new project, click on "New Project" within Azure AI Studio. You'll need to specify settings like the resource group, hub name, and services (e.g., Azure OpenAI or AI Search).

5. How do I add custom data to the chatbot in Azure AI Studio?You can add custom data by clicking on "Add Your Data" and uploading a PDF or other file formats. This data is indexed and can then be used by the chatbot to answer questions using the information from the uploaded document.

6. Can I customize the chatbot responses?Yes, you can customize chatbot responses using system messages. For example, you can set the chatbot to respond in a humorous or beginner-friendly manner by modifying the system message in the chatbot settings.

7. What is the role of Key Vault and storage in Azure AI Studio projects?Key Vault is used for securely storing secrets and tokens required for your projects. Storage accounts are used to store files that can be processed by AI services, such as when you upload custom data like PDFs for chatbot use.

8. What is indexing, and why is it necessary for custom data?Indexing involves processing uploaded data to make it searchable by the AI models. Azure AI Studio uses indexing to break down documents into manageable chunks so that the chatbot can refer to them while answering questions. This is necessary for utilizing custom data effectively.

9. Can I use Azure AI Studio for production?Some features of Azure AI Studio are still in preview and may not be suitable for production environments. For example, the custom data source feature is still in preview, which means its functionality is still being refined.

10. How do I manage shared resources in Azure AI Studio?Shared resources can be managed within the hub. You can create and allocate resources that can be shared across multiple projects, allowing efficient use of AI tools and collaboration between teams.

11. What types of AI services are available in Azure AI Studio?Azure AI Studio provides a variety of AI services, including language models (e.g., GPT-3, GPT-4), machine learning tools, and services for speech recognition, computer vision, and natural language processing.

12. How do I configure system messages for a chatbot?System messages can be configured in the chatbot settings. These messages define the chatbot's behavior, tone, and style of responses, allowing you to tailor the chatbot to suit different use cases or audiences.

13. How can I monitor the indexing process for custom data?The indexing process can be monitored from the Indexes section in Azure AI Studio. You can view the progress of data ingestion and indexing, as well as access job details for more in-depth information.

📌 Resources Mentioned:

👨‍💼 About the Presenter:
As a Microsoft Certified Trainer, Alireza brings firsthand experience and insights into the Azure architecture, new services and software development practices.

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