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How to avoid dialog confusion in a multi-user environment?

2025-08-25 1.4 K
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Session management solutions for multi-user environments

To ensure that dialog independence is maintained when multiple users use the same AI client, the following measures can be implemented:

  • Account Segregation Settings: Utilize kun-lab's multi-user support to create separate accounts for each user.
  • Conversation identity management</strong]: 1) create exclusive conversation threads for different projects; 2) use clear conversation naming rules (e.g. "Product Design - Li Ming - 202403")
  • Data cleansing mechanisms: Set up a policy to automatically clear outdated conversations (e.g., keep the last 30 days of records).
  • Permission Control Recommendations: Set administrator privileges for sensitive operations (e.g., model deletion), so that ordinary users can only access the dialogs they create

Best practices for team collaboration scenarios: Create a unified reminder template library; tag shared content with "team knowledge" tags; and periodically export important conversations for archiving. For temporary visitors, it is recommended to enable "guest mode", where conversations are not persistently stored.

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