Skip to main content

Noma Security

Use Noma Security to protect your LLM applications with comprehensive AI content moderation and safety guardrails.

Quick Start​

1. Define Guardrails on your LiteLLM config.yaml​

Define your guardrails under the guardrails section:

litellm config.yaml
model_list:
  - model_name: gpt-4o-mini
    litellm_params:
      model: openai/gpt-4o-mini
      api_key: os.environ/OPENAI_API_KEY

guardrails:
  - guardrail_name: "noma-guard"
    litellm_params:
      guardrail: noma
      mode: "during_call"
      api_key: os.environ/NOMA_API_KEY
      api_base: os.environ/NOMA_API_BASE
  - guardrail_name: "noma-pre-guard"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      api_base: os.environ/NOMA_API_BASE

Supported values for mode​

  • pre_call Run before LLM call, on input
  • post_call Run after LLM call, on input & output
  • during_call Run during LLM call, on input. Same as pre_call but runs in parallel with the LLM call. Response not returned until guardrail check completes
  • pre_mcp_call: Scan MCP tool call inputs before execution
  • during_mcp_call: Monitor MCP tool calls in real-time

2. Start LiteLLM Gateway​

litellm --config config.yaml --detailed_debug

3. Test request​

Expect this to fail since the request contains harmful content:

Curl Request
curl -i http://0.0.0.0:4000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "user", "content": "Tell me how to hack into someone's email account"}
    ]
  }'

Expected response on failure:

{
  "error": {
    "message": "{\n      \"error\": \"Request blocked by Noma guardrail\",\n      \"details\": {\n        \"prompt\": {\n          \"harmfulContent\": {\n            \"result\": true,\n            \"confidence\": 0.95\n          }\n        }\n      }\n    }",
    "type": "None",
    "param": "None",
    "code": "400"
  }
}

Supported Params​

guardrails:
  - guardrail_name: "noma-guard"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      api_base: os.environ/NOMA_API_BASE
      ### OPTIONAL ###
      # application_id: "my-app"
      # monitor_mode: false
      # block_failures: true
      # anonymize_input: false

Required Parameters​

  • api_key: Your Noma Security API key (set as os.environ/NOMA_API_KEY in YAML config)

Optional Parameters​

  • api_base: Noma API base URL (defaults to https://api.noma.security/)
  • application_id: Your application identifier (defaults to "litellm")
  • monitor_mode: If true, logs violations without blocking (defaults to false)
  • block_failures: If true, blocks requests when guardrail API failures occur (defaults to true)
  • anonymize_input: If true, replaces sensitive content with anonymized version (defaults to false)

Environment Variables​

You can set these environment variables instead of hardcoding values in your config:

export NOMA_API_KEY="your-api-key-here"
export NOMA_API_BASE="https://api.noma.security/"   # Optional
export NOMA_APPLICATION_ID="my-app"                 # Optional
export NOMA_MONITOR_MODE="false"                    # Optional
export NOMA_BLOCK_FAILURES="true"                   # Optional
export NOMA_ANONYMIZE_INPUT="false"                 # Optional

Advanced Configuration​

Monitor Mode​

Use monitor mode to test your guardrails without blocking requests:

guardrails:
  - guardrail_name: "noma-monitor"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      monitor_mode: true  # Log violations but don't block

Handling API Failures​

Control behavior when the Noma API is unavailable:

guardrails:
  - guardrail_name: "noma-failopen"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      block_failures: false  # Allow requests to proceed if guardrail API fails

Content Anonymization​

Enable anonymization to replace sensitive content instead of blocking:

guardrails:
  - guardrail_name: "noma-anonymize"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      anonymize_input: true  # Replace sensitive data with anonymized version

Multiple Guardrails​

Apply different configurations for input and output:

guardrails:
  - guardrail_name: "noma-strict-input"
    litellm_params:
      guardrail: noma
      mode: "pre_call"
      api_key: os.environ/NOMA_API_KEY
      block_failures: true

  - guardrail_name: "noma-monitor-output"
    litellm_params:
      guardrail: noma
      mode: "post_call"
      api_key: os.environ/NOMA_API_KEY
      monitor_mode: true

✨ Pass Additional Parameters​

Use extra_body to pass additional parameters to the Noma Security API call, such as dynamically setting the application ID for specific requests.

import openai
client = openai.OpenAI(
    api_key="your-api-key",
    base_url="http://0.0.0.0:4000"
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello, how are you?"}],
    extra_body={
        "guardrails": {
            "noma-guard": {
                "extra_body": {
                    "application_id": "my-specific-app-id"
                }
            }
        }
    }
)

This allows you to override the default application_id parameter for specific requests, which is useful for tracking usage across different applications or components.

Response Details​

When content is blocked, Noma provides detailed information about the violations as JSON inside the message field, with the following structure:

{
  "error": "Request blocked by Noma guardrail",
  "details": {
    "prompt": {
      "harmfulContent": {
        "result": true,
        "confidence": 0.95
      },
      "sensitiveData": {
        "email": {
          "result": true,
          "entities": ["user@example.com"]
        }
      },
      "bannedTopics": {
        "violence": {
          "result": true,
          "confidence": 0.88
        }
      }
    }
  }
}