---
title: Safety Guardrails
description: Implement safety measures and content moderation in Llama Stack applications
sidebar_label: Safety
sidebar_position: 9
---

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

# Safety Guardrails

Safety is a critical component of any AI application. Llama Stack provides a comprehensive Shield system that can be applied at multiple touchpoints to ensure responsible AI behavior and content moderation.

## Shield System Overview

The Shield system in Llama Stack provides:
- **Content filtering** for both input and output messages
- **Multi-touchpoint protection** across your application flow
- **Configurable safety policies** tailored to your use case
- **Integration with agents** for automated safety enforcement

## Basic Shield Usage

### Registering a Safety Shield

<Tabs>
<TabItem value="registration" label="Shield Registration">

```python
# Register a safety shield
shield_id = "content_safety"
client.shields.register(
    shield_id=shield_id,
    provider_shield_id="llama-guard-basic"
)
```

</TabItem>
<TabItem value="manual-check" label="Manual Safety Check">

```python
# Run content through shield manually
response = client.safety.run_shield(
    shield_id=shield_id,
    messages=[{"role": "user", "content": "User message here"}]
)

if response.violation:
    print(f"Safety violation detected: {response.violation.user_message}")
    # Handle violation appropriately
else:
    print("Content passed safety checks")
```

</TabItem>
</Tabs>

## Agent Integration

Shields can be automatically applied to agent interactions for seamless safety enforcement:

<Tabs>
<TabItem value="input-shields" label="Input Shields">

```python
from llama_stack_client import Agent

# Create agent with input safety shields
agent = Agent(
    client,
    model="meta-llama/Llama-3.2-3B-Instruct",
    instructions="You are a helpful assistant",
    input_shields=["content_safety"],  # Shield user inputs
    tools=["builtin::websearch"],
)

session_id = agent.create_session("safe_session")

# All user inputs will be automatically screened
response = agent.create_turn(
    messages=[{"role": "user", "content": "Tell me about AI safety"}],
    session_id=session_id,
)
```

</TabItem>
<TabItem value="output-shields" label="Output Shields">

```python
# Create agent with output safety shields
agent = Agent(
    client,
    model="meta-llama/Llama-3.2-3B-Instruct",
    instructions="You are a helpful assistant",
    output_shields=["content_safety"],  # Shield agent outputs
    tools=["builtin::websearch"],
)

session_id = agent.create_session("safe_session")

# All agent responses will be automatically screened
response = agent.create_turn(
    messages=[{"role": "user", "content": "Help me with my research"}],
    session_id=session_id,
)
```

</TabItem>
<TabItem value="both-shields" label="Input & Output Shields">

```python
# Create agent with comprehensive safety coverage
agent = Agent(
    client,
    model="meta-llama/Llama-3.2-3B-Instruct",
    instructions="You are a helpful assistant",
    input_shields=["content_safety"],   # Screen user inputs
    output_shields=["content_safety"],  # Screen agent outputs
    tools=["builtin::websearch"],
)

session_id = agent.create_session("fully_protected_session")

# Both input and output are automatically protected
response = agent.create_turn(
    messages=[{"role": "user", "content": "Research question here"}],
    session_id=session_id,
)
```

</TabItem>
</Tabs>

## Available Shield Types

### Llama Guard Shields

Llama Guard provides state-of-the-art content safety classification:

<Tabs>
<TabItem value="basic" label="Basic Llama Guard">

```python
# Basic Llama Guard for general content safety
client.shields.register(
    shield_id="llama_guard_basic",
    provider_shield_id="llama-guard-basic"
)
```

**Use Cases:**
- General content moderation
- Harmful content detection
- Basic safety compliance

</TabItem>
<TabItem value="advanced" label="Advanced Llama Guard">

```python
# Advanced Llama Guard with custom categories
client.shields.register(
    shield_id="llama_guard_advanced",
    provider_shield_id="llama-guard-advanced",
    config={
        "categories": [
            "violence", "hate_speech", "sexual_content",
            "self_harm", "illegal_activity"
        ],
        "threshold": 0.8
    }
)
```

**Use Cases:**
- Fine-tuned safety policies
- Domain-specific content filtering
- Enterprise compliance requirements

</TabItem>
</Tabs>

### Custom Safety Shields

Create domain-specific safety shields for specialized use cases:

```python
# Register custom safety shield
client.shields.register(
    shield_id="financial_compliance",
    provider_shield_id="custom-financial-shield",
    config={
        "detect_pii": True,
        "financial_advice_warning": True,
        "regulatory_compliance": "FINRA"
    }
)
```

## Safety Response Handling

When safety violations are detected, handle them appropriately:

<Tabs>
<TabItem value="basic-handling" label="Basic Handling">

```python
response = client.safety.run_shield(
    shield_id="content_safety",
    messages=[{"role": "user", "content": "Potentially harmful content"}]
)

if response.violation:
    violation = response.violation
    print(f"Violation Type: {violation.violation_type}")
    print(f"User Message: {violation.user_message}")
    print(f"Metadata: {violation.metadata}")

    # Log the violation for audit purposes
    logger.warning(f"Safety violation detected: {violation.violation_type}")

    # Provide appropriate user feedback
    return "I can't help with that request. Please try asking something else."
```

</TabItem>
<TabItem value="advanced-handling" label="Advanced Handling">

```python
def handle_safety_response(safety_response, user_message):
    """Advanced safety response handling with logging and user feedback"""

    if not safety_response.violation:
        return {"safe": True, "message": "Content passed safety checks"}

    violation = safety_response.violation

    # Log violation details
    audit_log = {
        "timestamp": datetime.now().isoformat(),
        "violation_type": violation.violation_type,
        "original_message": user_message,
        "shield_response": violation.user_message,
        "metadata": violation.metadata
    }
    logger.warning(f"Safety violation: {audit_log}")

    # Determine appropriate response based on violation type
    if violation.violation_type == "hate_speech":
        user_feedback = "I can't engage with content that contains hate speech. Let's keep our conversation respectful."
    elif violation.violation_type == "violence":
        user_feedback = "I can't provide information that could promote violence. How else can I help you today?"
    else:
        user_feedback = "I can't help with that request. Please try asking something else."

    return {
        "safe": False,
        "user_feedback": user_feedback,
        "violation_details": audit_log
    }

# Usage
safety_result = handle_safety_response(response, user_input)
if not safety_result["safe"]:
    return safety_result["user_feedback"]
```

</TabItem>
</Tabs>

## Safety Configuration Best Practices

### 🛡️ **Multi-Layer Protection**
- Use both input and output shields for comprehensive coverage
- Combine multiple shield types for different threat categories
- Implement fallback mechanisms when shields fail

### 📊 **Monitoring & Auditing**
- Log all safety violations for compliance and analysis
- Monitor false positive rates to tune shield sensitivity
- Track safety metrics across different use cases

### ⚙️ **Configuration Management**
- Use environment-specific safety configurations
- Implement A/B testing for shield effectiveness
- Regularly update shield models and policies

### 🔧 **Integration Patterns**
- Integrate shields early in the development process
- Test safety measures with adversarial inputs
- Provide clear user feedback for violations

## Advanced Safety Scenarios

### Context-Aware Safety

```python
# Safety shields that consider conversation context
agent = Agent(
    client,
    model="meta-llama/Llama-3.2-3B-Instruct",
    instructions="You are a healthcare assistant",
    input_shields=["medical_safety"],
    output_shields=["medical_safety"],
    # Context helps shields make better decisions
    safety_context={
        "domain": "healthcare",
        "user_type": "patient",
        "compliance_level": "HIPAA"
    }
)
```

### Dynamic Shield Selection

```python
def select_shield_for_user(user_profile):
    """Select appropriate safety shield based on user context"""
    if user_profile.age < 18:
        return "child_safety_shield"
    elif user_profile.context == "enterprise":
        return "enterprise_compliance_shield"
    else:
        return "general_safety_shield"

# Use dynamic shield selection
shield_id = select_shield_for_user(current_user)
response = client.safety.run_shield(
    shield_id=shield_id,
    messages=messages
)
```

## Compliance and Regulations

### Industry-Specific Safety

<Tabs>
<TabItem value="healthcare" label="Healthcare (HIPAA)">

```python
# Healthcare-specific safety configuration
client.shields.register(
    shield_id="hipaa_compliance",
    provider_shield_id="healthcare-safety-shield",
    config={
        "detect_phi": True,  # Protected Health Information
        "medical_advice_warning": True,
        "regulatory_framework": "HIPAA"
    }
)
```

</TabItem>
<TabItem value="financial" label="Financial (FINRA)">

```python
# Financial services safety configuration
client.shields.register(
    shield_id="finra_compliance",
    provider_shield_id="financial-safety-shield",
    config={
        "detect_financial_advice": True,
        "investment_disclaimers": True,
        "regulatory_framework": "FINRA"
    }
)
```

</TabItem>
<TabItem value="education" label="Education (COPPA)">

```python
# Educational platform safety for minors
client.shields.register(
    shield_id="coppa_compliance",
    provider_shield_id="educational-safety-shield",
    config={
        "child_protection": True,
        "educational_content_only": True,
        "regulatory_framework": "COPPA"
    }
)
```

</TabItem>
</Tabs>

## Related Resources

- **[Agents](./agent)** - Integrating safety shields with intelligent agents
- **[Agent Execution Loop](./agent_execution_loop)** - Understanding safety in the execution flow
- **[Evaluations](./evals)** - Evaluating safety shield effectiveness
- **[Telemetry](./telemetry)** - Monitoring safety violations and metrics
- **[Llama Guard Documentation](https://github.com/meta-llama/PurpleLlama/tree/main/Llama-Guard3)** - Advanced safety model details
