Azure AI Search Vector Database Integration

[TeodorZlatanov]

Description

• Summary of changes: This PR integrates the Agno framework with Azure AI Search vector database with multi-mode search capabilities.
• Related issues: No connected issues or fixes.
• Motivation and context: Azure AI Search vector database integration needed.
• Environment or dependencies: Specify any changes in dependencies or environment configurations required for this update.
• Impact on metrics: This change provides more flexible query routing which can help improve search relevance and performance. There are no expected performance regressions; rather, users can now optimize queries for their specific scenario.

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Type of change

Please check the options that are relevant:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Model update (Addition or modification of models)
• Other (please describe):

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Checklist

• Adherence to standards: Code complies with Agno’s style guidelines and best practices.
• Formatting and validation: I have run ./scripts/format.sh and ./scripts/validate.sh to ensure code is formatted and linted.
• Self-review completed: A thorough review has been performed.
• Documentation: Docstrings and comments have been added to cover the new vector database functionality.
• Examples and guides: Relevant cookbook example has been added to demonstrate usage of this new feature.
• Tested in a clean environment: Changes have been tested in a clean environment to confirm expected behavior.
• Tests (optional): Tests have been added or updated to cover any new or changed functionality.

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Additional Notes

This feature integrates seamlessly with the Azure AI Search vector database.