Autotuned Guardrails

TL;DR: Evaluate your Agent with Vijil, then call Dome.create_from_vijil_evaluation(evaluation_id, api_key) to build a Guardrail configuration tuned to the vulnerabilities that evaluation found. Optionally pass a latency_threshold to trade coverage for speed.

Rather than hand-picking Guards, you can let a Vijil evaluation drive your Dome configuration. This tutorial evaluates an unprotected Agent, generates a recommended configuration from the results, and re-evaluates the protected Agent to confirm the improvement. The full runnable code is in the AutotunedGuardrails tutorial folder.

Prerequisites

Install the dependencies and set your keys:

pip install vijil-dome vijil

OPENAI_API_KEY=<your OpenAI key>
VIJIL_API_KEY=<your Vijil API key>

Obtain a Vijil API key from evaluate.vijil.ai. If you are on the free plan, you also need an Ngrok authtoken (NGROK_AUTHTOKEN), which Vijil uses to create a private HTTPS endpoint to your Agent. Premium users can skip this.

Walkthrough

Evaluate the Baseline Agent

Run safety and security harnesses against your unprotected Agent. When the evaluation completes, note its evaluation ID from the logs or from the Vijil Console.

python -m evaluate_baseline_agent

Build Guardrails From the Evaluation

Dome.create_from_vijil_evaluation fetches the recommended configuration for that evaluation and returns a ready-to-use Dome:

from vijil_dome import Dome

dome = Dome.create_from_vijil_evaluation(
    evaluation_id=YOUR_EVALUATION_ID,
    api_key=VIJIL_API_KEY,
)

Wrap your Agent so every request passes through the tuned Guardrails:

class ProtectedAgent:
    def __init__(self, agent, dome: Dome):
        self.agent = agent
        self.dome = dome

    async def guardrailed_invoke(self, prompt: str) -> str:
        input_guard_result = await self.dome.async_guard_input(prompt)
        if input_guard_result.flagged:
            return "Input was flagged by Vijil Dome. This request violates the agent's usage policy."

        agent_response = await self.agent.invoke(prompt)

        output_guard_result = await self.dome.async_guard_output(agent_response)
        if output_guard_result.flagged:
            return "This output was blocked by Vijil Dome."

        return agent_response

Re-run the evaluation against the protected Agent:

python -m evaluate_protected_agent --evaluation-id=YOUR_EVALUATION_ID

Optimize for Latency

Pass a latency_threshold (in seconds) to bias the recommendation toward faster Guards:

python -m evaluate_protected_agent --evaluation-id=YOUR_EVALUATION_ID --latency-threshold=1.0

In code, the same argument is available on the factory:

dome = Dome.create_from_vijil_evaluation(
    evaluation_id=YOUR_EVALUATION_ID,
    api_key=VIJIL_API_KEY,
    latency_threshold=1.0,
)

Troubleshooting

Some Windows antivirus tools flag Ngrok. Ngrok is safe, and Vijil guarantees that traffic reaching your Agent through Ngrok originates only from Vijil services, so your Agent is never publicly exposed.

Get Started

Evaluate Agents

Protect Agents

Reference

Autotuned Guardrails

Prerequisites

Walkthrough

Troubleshooting

Next Steps

Configure Guardrails

Understand Results

​Prerequisites

​Walkthrough

​Troubleshooting

​Next Steps

Configure Guardrails

Understand Results

Prerequisites

Walkthrough

Troubleshooting

Next Steps