Apply LLM guardrails with agentgateway

In this free, on-demand technical lab, learn how to apply guardrails to LLM requests and responses with agentgateway. Build filters that detect sensitive information and reject or mask requests containing Personally Identifiable Information (PII).

• Set up the environment: Deploy the lab environment and configure agentgateway to route requests to an LLM.
• Send LLM requests: Make requests through agentgateway and observe how traffic flows between clients and the LLM.
• Configure LLM guardrails: Apply filters to inspect LLM requests and responses for sensitive content.
• Reject sensitive requests: Configure guardrails to detect PII in requests and reject them before they reach the LLM.
• Mask sensitive responses: Apply response filtering to detect and mask PII returned by the LLM.

Gain hands-on experience using agentgateway to enforce guardrails around LLM traffic and protect sensitive information as AI applications interact with models.

Learn to apply filters to LLM requests and responses to reject or mask content with Personally Identifiable Information.

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