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