Acuvity

Acuvity provides AI Guard service for scanning LLM inputs and outputs to avoid manipulation of the model, addition of malicious content, and other undesirable data transfers.

To get started with Acuvity, visit their website:

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Using Acuvity with Portkey

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1. Add Acuvity Credentials to Portkey

• Navigate to the Integration page under Sidebar
• Click on the edit button for the Acuvity integration
• Add your Acuvity API Key

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2. Add Acuvity’s Guardrail Check

• Navigate to the Guardrails page and click the Create button
• Search for Acuvity Scan and click Add
• Configure your guardrail settings: toxicity, jail break, biased etc.
• Set any actions you want on your check, and create the Guardrail!

Here’s your updated table with just the parameter names:

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3. Add Guardrail ID to a Config and Make Your Request

• When you save a Guardrail, you’ll get an associated Guardrail ID - add this ID to the input_guardrails or output_guardrails params in your Portkey Config
• Create these Configs in Portkey UI, save them, and get an associated Config ID to attach to your requests. More here.

Here’s an example config:

{
  "input_guardrails": ["guardrails-id-xxx", "guardrails-id-yyy"],
  "output_guardrails": ["guardrails-id-xxx", "guardrails-id-yyy"]
}

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",
    config: "pc-***" // Supports a string config id or a config object
});

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",
    config: "pc-***" // Supports a string config id or a config object
});

portkey = Portkey(
    api_key="PORTKEY_API_KEY",
    config="pc-***" # Supports a string config id or a config object
)

const openai = new OpenAI({
  apiKey: 'OPENAI_API_KEY',
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    apiKey: "PORTKEY_API_KEY",
    config: "CONFIG_ID"
  })
});

client = OpenAI(
    api_key="OPENAI_API_KEY", # defaults to os.environ.get("OPENAI_API_KEY")
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        provider="openai",
        api_key="PORTKEY_API_KEY", # defaults to os.environ.get("PORTKEY_API_KEY")
        config="CONFIG_ID"
    )
)

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-config: $CONFIG_ID" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [{
        "role": "user",
        "content": "Hello!"
      }]
  }'

For more, refer to the Config documentation.

Your requests are now guarded by Acuvity AI’s Guardrail and you can see the Verdict and any action you take directly on Portkey logs!

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Using Raw Guardrails with Acuvity

You can define Acuvity guardrails directly in your code for more programmatic control without using the Portkey UI. This “raw guardrails” approach lets you dynamically configure guardrails based on your application’s needs.

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Get Support

If you face any issues with the Acuvity integration, just ping the Portkey team on the community forum.

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Learn More

• Acuvity Website