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### Motivation and Context I have added Azure CosmosDB MongoDB vCore as a data store. MongoDB vCore now supports vector search on embeddings, and it could be used to seamlessly integrate your AI-based applications with your data stored in the Azure CosmosDB. More details about Mongo vCore can be found here: https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/vector-search. Issue https://github.com/microsoft/semantic-kernel/issues/2375 <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, by providing the following information: --> 1. Why is this change required? **MongoDB vCore now supports vector search on embeddings, and it could be used to seamlessly integrate your AI-based applications with your data stored in the Azure CosmosDB.** 2. What problem does it solve? This adds a new memory store MongoDB vCore(Azure CosmosDB) ### Description <!-- Describe your changes, the overall approach, and the underlying design. These notes will help you understand how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [ ] The code builds clean without any errors or warnings - [ ] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [ ] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄 --------- Co-authored-by: Abby Harrison <[email protected]> Co-authored-by: Abby Harrison <[email protected]> Co-authored-by: Mark Wallace <[email protected]>