# Guardrails ### **Introduction** Guardrails in FastRouter allow you to validate and monitor requests and responses flowing through your LLM gateway. They help you: * Prevent sensitive information (PII) from being exposed * Ensure responses adhere to specific topics or formats * Block toxic or inappropriate content * Validate output structure (regex patterns) **⚠️ Feature Note** Guardrails do not support streaming (`stream=true`). Ensure that `stream=false` in your request payload when using guardrails. ### Guardrail Actions Each guardrail can be configured with one of two actions that determine how the system behaves when a guardrail check fails: | Action | Default State | Behavior | Use Case | | -------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Validate | — |

On Request & Response:

| Use when guardrails are critical and a failed check should block the request entirely. **Recommended:** Test on a subset of requests first to understand the impact. | | Observe | ✓ Default |

On Request & Response:

| Use when you want to log guardrail results without affecting your application flow. Ideal for monitoring and gathering insights before enforcing strict validation. | ⚠️ **Testing Recommendation** We strongly recommend running guardrails in **Observe** mode first on a subset of your requests to understand their impact before switching to **Validate** mode. ### Status Codes FastRouter uses specific status codes to communicate guardrail results: | Status Code | Description | | ----------- | ---------------------------------------------------------------------------------------------------------------------------- | | `200` | All guardrail checks passed. Request/response processed successfully. | | `246` | **Observe mode:** One or more guardrail checks failed, but the request/response was still processed. Check logs for details. | | `446` | **Validate mode:** One or more guardrail checks failed. Request was blocked and not processed. | ### Using Guardrails in Requests After creating guardrails in the FastRouter dashboard, you'll receive a **Config ID** (e.g., `gr_a8f3k9m2`) for each guardrail. Use these IDs to apply guardrails to your requests: #### Adding Guardrails to Requests Include the `input_guardrails` and/or `output_guardrails` parameters in your request body with an array of guardrail config IDs: ```shellscript { "model": "openai/gpt-3.5-turbo", "messages": [ { "role": "user", "content": "What is the meaning of life?" } ], "input_guardrails": ["gr_e9k2v7h5"], "output_guardrails": ["gr_a8f3k9m2", "gr_b2n7p1q4"] } ``` In this example: * `input_guardrails` - Applied to the incoming user request before it's sent to the LLM * `output_guardrails` - Applied to the LLM's response before returning it to your application #### Multiple Guardrails You can apply multiple guardrails at each stage. They will be evaluated in the order specified: ```shellscript { "model": "openai/gpt-4", "messages": [ { "role": "user", "content": "Tell me about product pricing" } ], "input_guardrails": [ "gr_e9k2v7h5", // Topic Adherence "gr_a8f3k9m2" // PII Check ], "output_guardrails": [ "gr_b2n7p1q4", // Toxicity Detection "gr_c5x8r3w9" // Competitor Mention ] } ``` ### Guardrail Types #### Basic Guardrails Deterministic guardrails that run quickly and don't require LLM evaluation: * **RegEx Check** - Validate content against custom regex patterns #### LLM Judge Guardrails Intelligent guardrails that use LLM evaluation for complex checks: * **PII Check** - Detect and optionally redact emails, phone numbers, SSN, credit cards * **Topic Adherence** - Ensure conversations stay on allowed topics * **Toxicity Detection** - Detect hate speech, harassment, violence, and inappropriate content **💡 Performance Note** Basic guardrails execute in milliseconds. LLM Judge guardrails require an additional LLM call and may add 500ms-2s latency depending on your Default Guardrails Key configuration. ### Creating Guardrails To create a new guardrail: 1. Navigate to **Guardrails** in your FastRouter dashboard 2. Click the **Browse Templates** tab 3. Choose a template and click **Create** 4. Configure your guardrail settings: * **Name** - A descriptive name for your guardrail * **Action** - Choose `Observe` or `Validate` * **Stage** - Choose `Input` or `Output` * Template-specific settings (e.g., PII types, word limits, regex patterns) 5. Click **Create Guardrail** 6. Copy the generated **Config ID** to use in your requests ### Best Practices * **Start with Observe mode** - Monitor guardrail behavior before enforcing validation * **Test incrementally** - Apply guardrails to a small percentage of traffic first * **Layer guardrails** - Use both Basic and LLM Judge guardrails for comprehensive protection * **Monitor costs** - LLM Judge guardrails consume tokens from your Default Guardrails Key * **Keep guardrails focused** - Create specific guardrails for specific use cases rather than one large guardrail * **Review logs regularly** - Check status `246` responses to understand when guardrails are triggered ### Example: Complete Request Flow ```shellscript // Request with input and output guardrails POST https://api.fastrouter.ai/v1/chat/completions Authorization: Bearer YOUR_API_KEY { "model": "openai/gpt-4", "messages": [ { "role": "user", "content": "What's your email for support?" } ], "input_guardrails": ["gr_e9k2v7h5"], "output_guardrails": ["gr_a8f3k9m2"] } // Response (200 - All checks passed) { "id": "fr_...", "model": "gpt-4", "choices": [...], "guardrails": { "input": { "passed": true, "checks": [ { "id": "gr_e9k2v7h5", "name": "Topic Adherence", "passed": true, "cost": 0.00011 } ] }, "output": { "passed": true, "checks": [ { "id": "gr_a8f3k9m2", "name": "PII Check", "passed": true, "cost": 0.00012 } ] } } } // Response (246 - Check failed in Observe mode) // Request still processed, but guardrail logged failure { "id": "fr_...", "model": "gpt-4", "choices": [...], "guardrails": { "output": { "passed": false, "checks": [ { "id": "gr_a8f3k9m2", "name": "PII Check", "passed": false, "cost": 0.00013 } ] } } } // Response (446 - Check failed in Validate mode) // Request blocked { "error": { "message": "Guardrail validation failed", "type": "guardrail_error", "code": 446, "guardrails": { "output": { "passed": false, "checks": [ { "id": "gr_a8f3k9m2", "name": "PII Check", "passed": false, "cost": 0.00014 } ] } } } } ```
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