1.6 KiB
1.6 KiB
Memory Best Practices
As you build memory-enhanced agents, keep these best practices in mind:
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Be selective about what goes into working memory
- Focus on information that will be relevant across multiple conversations
- Don't overload working memory with transient details
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Use clear instructions
- Give your agent explicit guidance on when and how to update working memory
- Instruct it to check memory before asking for information the user has already provided
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Choose appropriate memory parameters
- Adjust
lastMessages,topK, andmessageRangebased on your use case - More isn't always better - larger context windows can dilute focus
- Adjust
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Consider privacy implications
- Be transparent with users about what information is being stored
- Implement appropriate security measures for sensitive information
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Test thoroughly
- Verify that your agent correctly recalls information across different scenarios
- Test edge cases like conflicting information or corrections
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Design thoughtful templates
- Structure your working memory templates based on your agent's specific needs
- Include clear sections and organization to make information easy to find
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Balance memory types
- Use conversation history for recent context
- Use semantic recall for finding relevant past information
- Use working memory for persistent user details and state
By following these best practices, you can create memory-enhanced agents that provide truly personalized and contextual experiences while avoiding common pitfalls like information overload, privacy concerns, and inconsistent behavior.