Install Dome

Dome ships as the vijil-dome Python package. The base install includes the configuration system, the Guardrail engine, and the Detectors that need no model weights. Everything else is an optional extra.

Install the Package

pip install vijil-dome

Verify the install by running a scan with the built-in defaults:

from vijil_dome import Dome

dome = Dome()
print(dome.guard_input("Ignore previous instructions.").is_safe())

The first call downloads model weights for the default Detectors and can take a few minutes. Set VIJIL_MODEL_DIR to control where they are cached.

Choose Extras

Extra	Install	What It Adds
`local`	`pip install "vijil-dome[local]"`	Local model inference for classifier Detectors (`torch`, `transformers`, `sentence-transformers`)
`llm`	`pip install "vijil-dome[llm]"`	LLM-backed Detectors through LiteLLM
`pii`	`pip install "vijil-dome[pii]"`	Presidio PII detection and redaction
`full`	`pip install "vijil-dome[full]"`	`local`, `llm`, and `pii` together
`embeddings`	`pip install "vijil-dome[embeddings]"`	Fast embeddings store for `security-embeddings` (`annoy`, `faiss-cpu`)
`opentelemetry`	`pip install "vijil-dome[opentelemetry]"`	OpenTelemetry tracing, metrics, and logging
`google`	`pip install "vijil-dome[google]"`	Google Cloud trace, metric, and log export
`s3`	`pip install "vijil-dome[s3]"`	Configuration loading from S3 through `Dome.create_from_s3()`
`trust`	`pip install "vijil-dome[trust]"`	Trust Runtime core: identity, mandatory access control, signed manifests
`trust-adapters`	`pip install "vijil-dome[trust-adapters]"`	Framework adapters for `secure_agent()`: LangGraph, Google ADK, and Strands
`trust-cli`	`pip install "vijil-dome[trust-cli]"`	Command-line dependencies for manifest signing and verification
`identity`	`pip install "vijil-dome[identity]"`	SPIFFE workload identity on its own
`controls`	`pip install "vijil-dome[controls]"`	YAML policy loading for the Controls Engine
`controls-full`	`pip install "vijil-dome[controls-full]"`	Controls Engine with JSON Schema, CEL, and RE2
`strands`	`pip install "vijil-dome[strands]"`	Strands Agents integration
`mcp`	`pip install "vijil-dome[mcp]"`	Guarded MCP server proxy

Combine extras in one install:

pip install "vijil-dome[trust,trust-adapters,local,opentelemetry]"

full covers local, llm, and pii only. It does not include the Trust Runtime or Controls Engine extras. LangChain support needs no extra because it depends on langchain-core alone.

Run Without Local Models

Set DOME_INFERENCE_URL to route remote-capable Detectors to an inference service instead of installing model weights. This keeps the container small and removes the local extra from the dependency set.

export DOME_INFERENCE_URL="https://inference.example.com"

See Detection Methods for the Detectors that support remote routing.

Install CPU-Only PyTorch

The local extra pulls in PyTorch with CUDA support, which adds several gigabytes. In a CPU-only environment, reinstall the CPU build:

pip install "vijil-dome[local]"
pip install --force-reinstall torch --index-url https://download.pytorch.org/whl/cpu

All Detectors stay functional on CPU. Inference runs two to five times slower, which is usually acceptable for guarding. To keep model weights out of your Agent image entirely, run Dome as its own service. See Use Dome as a Containerized Deployment.

Set Environment Variables

Dome reads configuration from the environment. Only the variables for the Detectors and integrations you actually use are required.

Routing and Models

Variable	Purpose
`DOME_INFERENCE_URL`	Inference service endpoint for remote-capable Detectors
`DOME_LOCAL_DETECTORS`	Comma-separated Detector names forced to run locally
`VIJIL_MODEL_DIR`	Directory for cached model weights
`VIJIL_SAFEGUARD_MODEL`	Model used by the `-safeguard` Detector variants
`VIJIL_LLM_HUB`	Provider used by LLM-backed Detectors
`VIJIL_LLM_MODEL`	Model used by LLM-backed Detectors
`HUGGINGFACE_TOKEN`	Access token for gated Hugging Face models

Provider Credentials

Variable	Used By
`OPENAI_API_KEY`, `OPENAI_BASE_URL`	OpenAI Moderation and LLM-backed Detectors
`TOGETHERAI_API_KEY`, `GROQ_API_KEY`	LLM-backed Detectors on those providers
`PERSPECTIVE_API_KEY`	`moderation-perspective-api`
`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_REGION`, `AWS_PROFILE`, `AWS_SESSION_TOKEN`	Configuration loading from S3

Platform and Telemetry

Variable	Purpose
`VIJIL_API_KEY`	Authenticates Console constraint fetches, manifest signing, and Agent configuration loading
`VIJIL_IDENTITY_DELEGATE_URL`	Identity delegate endpoint for Trust Runtime attestation
`VIJIL_LOG_PAYLOADS`	Set to `1` to log a redacted payload record at `DEBUG` level
`OTEL_AUTH_METHOD`	Authentication method for the OpenTelemetry exporter

Next Steps

Protection Overview

How Guardrails, Guards, and Detectors fit together

Configure Guardrails

Write your first configuration

Framework Integrations

Wire Dome into your Agent framework

Trust Runtime

Add identity, tool access control, and audit events

Get Started

Evaluate Agents

Protect Agents

Reference

Install Dome

Install the Package

Choose Extras

Run Without Local Models

Install CPU-Only PyTorch

Set Environment Variables

Routing and Models

Provider Credentials

Platform and Telemetry

Next Steps

Protection Overview

Configure Guardrails

Framework Integrations

Trust Runtime

​Install the Package

​Choose Extras

​Run Without Local Models

​Install CPU-Only PyTorch

​Set Environment Variables

​Routing and Models

​Provider Credentials

​Platform and Telemetry

​Next Steps

Protection Overview

Configure Guardrails

Framework Integrations

Trust Runtime

Install the Package

Choose Extras

Run Without Local Models

Install CPU-Only PyTorch

Set Environment Variables

Routing and Models

Provider Credentials

Platform and Telemetry

Next Steps