Microsoft Agent Framework Memory with Supermemory

Microsoft Agent Framework’s documented Python integration with Supermemory uses a shared AgentSupermemory connection and context provider to retrieve background information before an agent run, while authorized user scope and conversation IDs should remain distinct to support user isolation and session tracking. Credentials and scopes should be controlled by the server-side application rather than supplied through prompts, and developers should begin with a single retrieval mechanism before adding tools or middleware to avoid duplicate retrieval or unclear storage behavior. Conversation saving is disabled by default and requires explicit decisions about included messages, grouping IDs, retention, and ownership of operational records. The guidance recommends defined fallback behavior for retrieval failures, distinguishing empty memory results from authentication errors, processing delays, and timeouts, especially when account-specific information is required. It also calls for tests across multiple sessions and user scopes to verify retrieval, correction, deletion, cache behavior, and isolation. Although the provider constructor was checked with Python 3.12 and specified package versions, no live model, cloud memory write, or deployed workflow was tested, so production claims should await end-to-end testing with a Supermemory API key and fictional data.

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