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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

Monitor Performance

View traces and metrics after deployment

Dome SDK Guide

Complete deployment instructions for developers

Configure Guardrails

Set up guard policies in the Console
Last modified on April 20, 2026