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When a user sends a query, azure ai agents decide if grounding with bing search should be leveraged or not This sample demonstrates how to use agent operations with the bing grounding tool from the azure agents service using a synchronous client. If so, it will leverage bing to search over public web data and return relevant chunks

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Lastly, azure ai agents will use returned chunks to generate a response. This plan enables grounding with bing search tool in azure ai foundry Learn how to ground azure ai agents using bing search results

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You need to create a grounding with bing search resource, and then connect this resource to your azure ai agents.

Grounding conversations with bing is one of several tools provided by the foundry agent service Grounding with bing allows your app to search for information relevant to the conversation and that cannot be provided in advance to the agent in a vector store or sql db. Check out our documentation for detailed guides on how to integrate grounding with bing search into your azure ai agent service and visit azure to sign up and try it out With just a few steps, you’ve deployed a fully functional azure ai foundry environment connected to bing search, all managed with terraform

This approach ensures your infrastructure is reproducible, auditable, and easy to manage For the full code, check out the sample in github Grounding with bing custom search allows you to search within a configurable set of public web domains Let's set up grounding with bing search first

We go to the azure portal.

Microsoft has introduced a compelling alternative through azure openai agents with the “grounding with bing search” tool, seamlessly integrated with semantic kernel This comprehensive guide covers the complete migration process, from azure ai foundry project setup to implementing grounding capabilities in your.net applications. When your agent or backend service tries to use bing custom search, it must have the correct permissions (data. Configure a custom search space to ground ai models