> ## Documentation Index
> Fetch the complete documentation index at: https://vijil-mintlify-a91c9b66.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Autotuned Guardrails
> Generate a recommended Dome configuration directly from a Vijil evaluation.
**TL;DR:** Evaluate your [Agent](/owner-guide/register-agents/what-is-an-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](https://github.com/vijilAI/vijil-dome/tree/main/vijil_dome/tutorials/AutotunedGuardrails).
## Prerequisites
Install the dependencies and set your keys:
```bash theme={null}
pip install vijil-dome vijil
```
```bash theme={null}
OPENAI_API_KEY=
VIJIL_API_KEY=
```
Obtain a Vijil API key from [evaluate.vijil.ai](https://evaluate.vijil.ai). If you are on the free plan, you also need an [Ngrok authtoken](https://dashboard.ngrok.com/get-started/setup/python) (`NGROK_AUTHTOKEN`), which Vijil uses to create a private HTTPS endpoint to your Agent. Premium users can skip this.
## Walkthrough
Run safety and security [harnesses](/concepts/evaluation-components/harness) against your unprotected Agent. When the evaluation completes, note its evaluation ID from the logs or from the Vijil Console.
```bash theme={null}
python -m evaluate_baseline_agent
```
`Dome.create_from_vijil_evaluation` fetches the recommended configuration for that evaluation and returns a ready-to-use `Dome`:
```python theme={null}
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:
```python theme={null}
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:
```bash theme={null}
python -m evaluate_protected_agent --evaluation-id=YOUR_EVALUATION_ID
```
Pass a `latency_threshold` (in seconds) to bias the recommendation toward faster Guards:
```bash theme={null}
python -m evaluate_protected_agent --evaluation-id=YOUR_EVALUATION_ID --latency-threshold=1.0
```
In code, the same argument is available on the factory:
```python theme={null}
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](https://ngrok.com/docs/faq/#is-ngrok-a-virus), and Vijil guarantees that traffic reaching your Agent through Ngrok originates only from Vijil services, so your Agent is never publicly exposed.
## Next Steps
Fine-tune the recommended configuration
Read the evaluation that drives the configuration