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Information Assistant, built with Azure OpenAI Service, Industry Accelerator

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Information Assistant Accelerator

This accelerator demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure Cognitive Search for data indexing and retrieval.


Responsible AI

The Information Assistant (IA) Accelerator and Microsoft are committed to the advancement of AI driven by ethical principles that put people first.

Read our Transparency Note

Find out more with Microsoft's Responsible AI resources


Process Flow

Features

  • Chat and Q&A interfaces
  • File Upload and automated chunking and indexing for PDF, HTML, and DOCX
  • Monitoring the status of files uploaded and processed by the accelerator
  • Interacting with your data in supported native languages*
  • Explores various options to help users evaluate the trustworthiness of responses with citations, tracking of source content, etc.
  • Shows possible approaches for data preparation, prompt construction, and orchestration of interaction between model (ChatGPT) and retriever (Cognitive Search)
  • Settings directly in the UX to tweak the behavior and experiment with options

*See Configuring your own language ENV file for supported languages

Chat screen

For a detailed review see our Features page.


Getting Started

The IA Accelerator relies on multiple Azure services and has certain prerequisites that need to be met before deployment. It's essential to procure these prerequisites prior to proceeding with the deployment instructions in this guide.


Prerequisites

To get started with the IA Accelerator you will need the following:

  • An azure subscription with access enabled for the Azure OpenAI service. You can request access here *
  • Administrative rights on the Azure Subscription
  • Visual studio code

You can sign up for an Azure subscription here.

Once you have your prerequisite items, please move on to the Deployment Configuration step.

NOTICE: This codebase relies on the Azure OpenAI Service which must be procured first separately, subject to any applicable license agreement. Access to this code does not grant you a license or right to use Azure OpenAI Service.

Deployment Configuration

The deployment process for the IA Accelerator, uses a concept of Developing inside a Container to containerize all the necessary pre-requisite component without requiring them to be installed on the local machine. The environment you will work in will be created using a development container, or dev container hosted on a virtual machine using GitHub Codespaces.

Open in GitHub Codespaces

Begin by setting up your own Codespace using our Developing in a Codespaces documentation.

If you want to configure your local deskop for development container, follow our Configuring your System for Development Containers guide. More information can be found at Developing inside a Container.

Once you have the completed the setting up Codespaces, please move on to the Sizing Estimation step.


Sizing Estimator

The IA Accelerator needs to be sized appropriately based on your use case. Please review our Sizing Estimator to help find the configuration that fits your needs.

Once you have completed the Sizing Estimator, please move on to the Deployment steps.


Deployment

There are several steps to deploying the IA Accelerator. The following checklist will guide you through configuring the IA Accelerator in your environments. Please follow the steps in the order they are provided as values from one step may be used in subsequent steps.

  1. Configure Local Development Environment
  2. Configure Azure resources

Using IA Accelerator for the first time

Now that you have successfully deployed the IA Accelerator, you are ready to use the accelerator to process some data.

To use the IA Accelerator, you need to follow these steps:

  1. Prepare your data and upload it to Azure.
  2. Once uploaded the system will automatically process and make the document(s) available to you and other users of the deployment.
  3. Begin having conversations with your data by selecting the appropriate interaction method.

For more detailed information review the Features section of the documentation.


Resources

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft’s Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party’s policies.

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Reporting Security Issues

For security concerns, please see Security Guidelines

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