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Dome protects your AI agent by filtering requests and responses through configurable guardrails. Deploying Dome requires integrating the Dome SDK into your agent code.

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What Developers Need

To deploy Dome, your development team will:
  1. Install the SDK — Add vijil-dome to your Python dependencies
  2. Wrap LLM calls — Insert guard checks before and after your agent’s LLM interactions
  3. Configure guards — Load configuration from the Vijil Console or define it in code
  4. Handle blocked content — Return safe responses when guards trigger

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Integration Pattern

The basic pattern wraps your agent’s LLM calls: 
from vijil_dome import Dome

dome = Dome.create_from_vijil_agent(
    agent_id="your-agent-id",
    api_key="your-api-key"
)

def protected_chat(user_message: str) -> str:
    # Guard the input
    input_scan = dome.guard_input(user_message)
    if not input_scan.is_safe():
        return input_scan.guarded_response()

    # Your existing agent logic here
    response = your_agent.generate(input_scan.guarded_response())

    # Guard the output
    output_scan = dome.guard_output(response)
    return output_scan.guarded_response()

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Configuration Sync

When you configure guardrails in the Console, your developers can pull that configuration directly into code using Dome.create_from_vijil_agent(). This keeps your security policies in sync between the Console UI and deployed agents.

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Framework Support

Dome integrates with popular agent frameworks:
  • LangChain / LangGraph — Use GuardrailRunnable in your chains
  • Google ADK — Register Dome callbacks with your agent
  • Custom agents — Wrap any LLM client with guard calls

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Next Steps

Dome SDK Guide

Complete deployment instructions for developers

Monitor Performance

View traces and metrics after deployment

Configuring Guardrails

Set up guard policies in the Console