Patronus AI

Integrate Patronus AI with Bifrost for LLM security and safety including hallucination detection, PII identification, toxicity screening, and custom evaluators.

Overview

Bifrost Enterprise supports Patronus AI as a third-party guardrail provider for evaluating LLM request and response text with Patronus evaluators.

Use it when you want evaluator-based checks such as PII detection, toxicity screening, prompt-injection checks, response quality criteria, or custom evaluators from your Patronus account.

How It Works

You’ll need a Patronus API key to authenticate with their Evaluate API - grab one from the Patronus dashboard.

1. You create a guardrail provider with provider_name: "patronus-ai" and your Patronus API key.
2. You configure one or more Patronus evaluators.
3. You attach that provider to a guardrail rule.
4. The rule decides when to run the provider and whether to evaluate input, output, or both.
5. Bifrost calls the Patronus Evaluate API at /v1/evaluate.
6. If any evaluator returns pass: false, Bifrost returns GUARDRAIL_INTERVENED.

The Patronus evaluator flow supported here is text-based: Bifrost sends selected request or response text as the evaluation input.

Streaming output: When this profile is used in an output or both rule, Bifrost accumulates the stream until the model response is complete, then checks the full response. It does not check individual stream chunks. See Streaming Output Guardrails for details.

Capabilities

• PII Detection: Identify personally identifiable information using Patronus evaluators
• Toxicity Screening: Evaluate text for toxic or unsafe content
• Prompt Injection Checks: Use Patronus judge criteria such as patronus:prompt-injection
• Response Quality Checks: Evaluate outputs for criteria such as conciseness, helpfulness, politeness, JSON validity, code validity, or CSV validity
• Bias Checks: Use Patronus criteria for age, gender, and racial bias checks
• Custom Evaluators: Use evaluator IDs and criteria configured in your Patronus account

Configuration Fields

Field	Type	Required	Default	Description
api_key	string	Yes	-	Patronus API key. Supports env.PATRONUS_API_KEY.
base_url	string	No	https://api.patronus.ai	Custom Patronus API base URL. Bifrost appends /v1/evaluate.
evaluators	array	Yes	-	Patronus evaluator entries to run. At least one is required.
capture	enum	No	none	Controls whether Patronus stores evaluation results: none, fails-only, or all.
timeout	integer	No	30	Provider execution timeout in seconds.

Evaluator Fields

Field	Type	Required	Description
evaluator	string	Yes	Patronus evaluator name, such as pii, toxicity-perspective-api, judge, or a custom evaluator ID.
criteria	string	No	Criteria/profile name for evaluators that require one, for example patronus:is-concise.
explain_strategy	enum	No	When to include evaluator explanations: never, on-fail, on-success, or always.

Capture Modes

Captured evaluation results appear under the Traces section in the Patronus dashboard.

Value	Meaning
none	Do not capture evaluation results in Patronus.
fails-only	Capture only failed evaluator results in Patronus.
all	Capture all evaluator results in Patronus.

Explanation Response Modes

Value	Meaning
never	Do not request evaluator explanations.
on-fail	Request explanations for failed evaluator results.
on-success	Request explanations for passed evaluator results.
always	Request explanations for all evaluator results.

Built-In UI Presets

The Bifrost dashboard exposes common Patronus evaluator presets:

Preset	Evaluator	Criteria
Detect PII	pii	-
Detect Toxicity	toxicity-perspective-api	-
Prompt Injection	judge	patronus:prompt-injection
Answer Refusal	judge	patronus:answer-refusal
Is Concise	judge	patronus:is-concise
Is Helpful	judge	patronus:is-helpful
Is Polite	judge	patronus:is-polite
No Apologies	judge	patronus:no-apologies
No OpenAI Reference	judge	patronus:no-openai-reference
No Age Bias	judge	patronus:no-age-bias
No Gender Bias	judge	patronus:no-gender-bias
No Racial Bias	judge	patronus:no-racial-bias
Is JSON	judge	patronus:is-json
Is Code	judge	patronus:is-code
Is CSV	judge	patronus:is-csv

You can also select Custom evaluator and provide your own evaluator and optional criteria.

Configuration

Web UI

1. Go to Guardrails > Providers.
2. Select Patronus AI.
3. Click Add Configuration.

4. Enter a descriptive Name.
5. Set your API Key directly or through an environment variable.
6. Leave Base URL empty or use the default https://api.patronus.ai, or set a custom Patronus endpoint.
7. Add one or more evaluators.
8. Choose a Capture mode. Bifrost defaults to None.
9. Set the timeout and save the configuration.
10. Attach the configuration to a guardrail rule under Guardrails > Configuration.

API

Create the Patronus AI provider configuration directly with the management API. The Enterprise backend registers guardrail provider APIs at /api/guardrails/{provider}; the provider type is the path segment (patronus-ai), and the API assigns the configuration ID after creation.

curl -X POST http://localhost:8080/api/guardrails/patronus-ai \
  -H "Content-Type: application/json" \
  -d '{
    "name": "patronus-quality-checks",
    "enabled": true,
    "config": {
      "api_key": "env.PATRONUS_API_KEY",
      "base_url": "https://api.patronus.ai",
      "evaluators": [
        {
          "evaluator": "pii",
          "explain_strategy": "on-fail"
        },
        {
          "evaluator": "judge",
          "criteria": "patronus:is-concise",
          "explain_strategy": "on-fail"
        }
      ],
      "capture": "none",
      "timeout": 30
    }
  }'

To attach it to a rule, fetch the generated config ID with GET /api/guardrails/patronus-ai, then reference it in selectedGuardrailProfiles (in the form patronus-ai:<id>) on POST /api/guardrails/rules.

config.json

{
  "guardrails_config": {
    "guardrail_providers": [
      {
        "id": 40,
        "provider_name": "patronus-ai",
        "policy_name": "patronus-quality-checks",
        "enabled": true,
        "timeout": 30,
        "config": {
          "api_key": "env.PATRONUS_API_KEY",
          "base_url": "https://api.patronus.ai",
          "evaluators": [
            {
              "evaluator": "pii",
              "explain_strategy": "on-fail"
            },
            {
              "evaluator": "judge",
              "criteria": "patronus:is-concise",
              "explain_strategy": "on-fail"
            }
          ],
          "capture": "none"
        }
      }
    ],
    "guardrail_rules": [
      {
        "id": 401,
        "name": "patronus-openai-output",
        "description": "Run Patronus checks on OpenAI responses",
        "enabled": true,
        "cel_expression": "provider == 'openai'",
        "apply_to": "output",
        "sampling_rate": 100,
        "timeout": 30,
        "provider_config_ids": [40]
      }
    ]
  }
}

Helm

bifrost:
  guardrails:
    providers:
      - id: 40
        provider_name: "patronus-ai"
        policy_name: "patronus-quality-checks"
        enabled: true
        timeout: 30
        config:
          api_key: "env.PATRONUS_API_KEY"
          base_url: "https://api.patronus.ai"
          evaluators:
            - evaluator: "pii"
              explain_strategy: "on-fail"
            - evaluator: "judge"
              criteria: "patronus:is-concise"
              explain_strategy: "on-fail"
          capture: "none"

    rules:
      - id: 401
        name: "patronus-openai-output"
        description: "Run Patronus checks on OpenAI responses"
        enabled: true
        cel_expression: "provider == 'openai'"
        apply_to: "output"
        sampling_rate: 100
        timeout: 30
        provider_config_ids: [40]

For provider comparison and information on configuring guardrail rules and profiles, see Guardrails.