In a recent personal project, a Microsoft employee explored the potential of Azure OpenAI Service to transform their team’s cumbersome Wiki into an easily navigable resource. The enormous size of their internal Wiki, a common feature of projects that have been around for years, posed significant challenges to finding relevant information quickly. To tackle this, the author leveraged Azure’s “OpenAI on Your Data,” which allows users to execute advanced AI models like GPT-4 on their business data without requiring model training or fine-tuning. Although originating as an internal project, this idea not only increases efficiency but also potentially broadens its application scope thanks to its scalable and adaptable nature.
The implementation process started with a tutorial to establish the core functionality using Azure services such as Blob Storage, Azure AI Search, and the Azure OpenAI Service. A key development was making the bot dynamic through the use of an Indexer to accommodate updates within the Wiki. Moreover, to automate data parsing from Azure DevOps Wiki, a Python script was employed, while custom metadata indexing provided users with more contextual responses. Challenges arose with SDK coverage and integrating Managed Identity, but those hurdles were tackled with ingenuity and determination. The entire setup highlights the capability of AI in enhancing access to information and underscores ongoing improvement areas, such as securing the infrastructure against unauthorized access.
News: I Built a Bot to Chat with Our Team’s Wiki Using Azure OpenAI Service
Documentation: Azure Open AI on Your Data
