How to Dynamically Limit Tool Parameters Based on User Permissions

Implementing Dynamic Tool Permissions in AI Systems

Imagine you are building an app where users can perform different actions, but not everyone can do everything. For example, some users can only view posts, while others can create, edit, or even delete them. You want your AI assistant to only suggest actions the current user is allowed to perform. This prevents errors and keeps the interface clean. How can you achieve this without hardcoding every possibility? The answer lies in dynamically adjusting the available options based on the users permissions.

One common approach is to generate custom schemas for each user. This means before the AI even starts processing, you check what the user is allowed to do, and then only show those options. This is like having a personalized menu where you only see the dishes you can actually order, not the entire kitchen. It reduces confusion and prevents the AI from suggesting actions that would fail. This method is called progressive disclosure, only showing what is relevant and possible for the current context.

• Dynamic schemas adapt to user roles
• Reduces errors by limiting choices
• Improves user experience by simplifying options
• Easier to maintain and update over time

Step-by-Step Implementation Using Pydantic

To implement this, you can use a framework like Pydantic, which allows defining tools with permissions. For example, create a base tool definition and then dynamically filter the allowed actions based on the users role. This way, the AI only sees the options the user can actually use. It is like having a smart assistant that knows your access level and only suggests actions you can complete. This avoids the frustration of trying to use a feature only to be told you are not allowed.

By implementing dynamic schemas, you make the system more robust and user-friendly. It prevents users from seeing options they cannot use, which reduces frustration. This approach is especially useful in multi-user systems where permissions vary. It ensures the AI assistant remains a helpful guide rather than a source of confusion. Always design your tools to adapt to the user, not the other way around.

1. Check the users permissions
2. Generate the list of allowed actions
3. Dynamically update the tool definitions
4. Provide only valid options to the AI