Hello @Josra Erraddahi thanks for the question.
Connecting an Azure AI Search index directly with a local fileshare and a private SharePoint isn't currently possible due to limitations with data sources:
- Local Files: Azure Search can't directly access data stored on local file shares. Azure Search works with cloud-based data sources for security and scalability reasons.
- Private SharePoint: While there is a connector for public SharePoint Online, there isn't a direct connector for private SharePoint at this time .
You can view the full list of Limitations and considerations in this Azure document. Here's a screenshot for quick reference:
However, there are workarounds to achieve a similar outcome for your ticketing chatbot:
Option 1: Use Azure Blob Storage as an intermediary:
- Upload Local Files: Upload your local files (tickets or relevant data) to an Azure Blob Storage container. Azure Blob Storage is a cloud storage solution that integrates well with Azure Search.
- Connect Azure Search to Blob Storage: Create an Azure Search index and configure it to connect to your Azure Blob Storage container. Azure Search can then process and index the uploaded files.
- Private SharePoint Integration (Optional): If your private SharePoint holds additional relevant data, explore third-party connectors that might bridge the gap between private SharePoint and Azure Blob Storage. These connectors can synchronize data between the two platforms, keeping your Azure Blob Storage container up-to-date.
Option 2: Use a Custom Indexer:
- Develop a Custom Indexer: This approach requires some development effort. Build a custom indexer using Azure Functions or Azure Logic Apps. This custom indexer can connect to your local file share and private SharePoint using their respective APIs.
- Extract and Transform Data: The custom indexer can extract relevant data from your local files and SharePoint, transform it into a format suitable for Azure Search, and then push the data to your Azure Search index.
- Maintenance: This approach requires maintaining the custom indexer to ensure it continues to function as expected with any changes to your data sources or Azure Search schema.
Hope that helps.
Best,
Grace