> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getbifrost.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# 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**](https://www.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](https://app.patronus.ai/experiments).

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.

<Note>
  **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](/enterprise/guardrails#streaming-output-guardrails) for details.
</Note>

## 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

<Tabs group="patronus-config">
  <Tab title="Web UI">
    1. Go to **Guardrails** > **Providers**.
    2. Select **Patronus AI**.
    3. Click **Add Configuration**.

    <Frame>
      <img src="https://mintcdn.com/bifrost/Rw9aUmTlXGVfOga4/media/ui-patronus-config.png?fit=max&auto=format&n=Rw9aUmTlXGVfOga4&q=85&s=d7bb6726b3c9258d434d37542d63d4cb" alt="Patronus AI configuration in Bifrost dashboard" width="2998" height="1652" data-path="media/ui-patronus-config.png" />
    </Frame>

    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**.
  </Tab>

  <Tab title="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.

    ```bash theme={null}
    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`.
  </Tab>

  <Tab title="config.json">
    ```json theme={null}
    {
      "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]
          }
        ]
      }
    }
    ```
  </Tab>

  <Tab title="Helm">
    ```yaml theme={null}
    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]
    ```
  </Tab>
</Tabs>

For provider comparison and information on configuring guardrail rules and profiles, see [Guardrails](/enterprise/guardrails).