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- Data cleansing mechanisms: Set up a policy to automatically clear outdated conversations (e.g., keep the last 30 days of records).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.
This answer comes from the articleKunAvatar (kun-lab): a native lightweight AI dialog client based on OllamaThe