Tyk AI Studio provides a Budget Control system to help organizations manage and limit spending on Large Language Model (LLM) usage.

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Purpose

The primary goals of the Budget Control system are:
  • Prevent Overspending: Set hard limits on costs associated with LLM API calls.
  • Cost Allocation: Track and enforce spending limits at different granularities (e.g., per organization, per specific LLM configuration).
  • Predictability: Provide better predictability for monthly AI operational costs.

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Scope & Configuration

Budgets are typically configured by administrators and applied at specific levels:
  • Organization Level: A global budget limit for all LLM usage within the organization.
  • LLM Configuration Level: A specific budget limit tied to a particular LLM setup (e.g., a dedicated budget for a high-cost gpt-4 configuration).
  • (Potentially) Application/User Level: Granular budgets might be assignable to specific applications or teams (depending on implementation specifics).
Configuration Parameters:
  • Limit Amount: The maximum monetary value allowed (e.g., $500).
  • Currency: The currency the budget is defined in (e.g., USD).
  • Time Period: The reset interval for the budget, typically monthly (e.g., resets on the 1st of each month).
  • Scope: Which entity the budget applies to (Organization, specific LLM Configuration ID, etc.).
Administrators configure these budgets via the Tyk AI Studio UI or API. Budget Config UI

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Enforcement

Budget enforcement primarily occurs at the Proxy & API Gateway:
  1. Request Received: The Proxy receives a request destined for an LLM.
  2. Cost Estimation: Before forwarding the request, the Proxy might estimate the potential maximum cost (or rely on post-request cost calculation).
  3. Budget Check: The Proxy checks the current spending against all applicable budgets (e.g., the specific LLM config budget AND the overall organization budget) for the current time period.
  4. Allow or Deny:
    • If the current spending plus the estimated/actual cost of the request does not exceed the limit(s), the request is allowed to proceed.
    • If the request would cause a budget limit to be exceeded, the request is blocked, and an error is returned to the caller.

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Integration with Other Systems

  • Analytics & Monitoring: The Analytics system provides the cost data used to track spending against budgets. The current spent amount for a budget period is derived from aggregated analytics data.
  • Model Pricing: The pricing definitions are essential for the Analytics system to calculate costs accurately, which in turn feeds the Budget Control system.
  • Notification System: Budgets can be configured to trigger notifications when spending approaches or reaches defined thresholds (e.g., alert admin when 80% of budget is consumed, notify user/admin when budget is exceeded).

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Benefits

  • Financial Control: Prevents unexpected high bills from LLM usage.
  • Resource Management: Ensures fair distribution of AI resources according to allocated budgets.
  • Accountability: Tracks spending against specific configurations or organizational units.
Budget Control is a critical feature for organizations looking to adopt AI technologies responsibly and manage their operational costs effectively.