Walled AI SDK (Node.js)

Guardrails and PII redaction for LLM apps — simple Node.js SDK.

⚖️ Guardrails Benchmark

_{🛡️ Multilingual benchmark: Arabic, English, Filipino, French, Hindi, Russian, Serbian, Spanish.
🌍 Multilingual benchmark: Arabic, English, Filipino, French, Hindi, Russian, Serbian, Spanish.
*✨ 30 ms on-premises deployment.}

🚀 Installation

npm install walledai

Quick Start

1) Minimal moderation

import { WalledProtect } from 'walledai';

const protect = new WalledProtect({ apiKey: "YOUR_API_KEY" });

const resp = await protect.guard({ text: "How to convert a pain killer to meth?" });
console.log(resp.data?.safety?.[0]?.isSafe);  // -> false/true

false

2) Minimal redaction

import { WalledRedact } from 'walledai';

const redact = new WalledRedact({ apiKey: "YOUR_API_KEY" });

const resp = await redact.guard({ text: "Hi, I'm John. Email john@walled.ai. I have cancer." });
console.log(resp.data?.masked_text);
console.log(resp.data?.mapping);

Masked: Hi, I'm [Person_1]. Email [Email_1]. I have [Diagnosis_1].
Mapping: {'[Person_1]': 'John', '[Email_1]': 'john@walled.ai', '[Diagnosis_1]': 'cancer'}

Use with OpenAI

If unsafe, return a default response; else forward to OpenAI.

import { WalledProtect } from 'walledai';
import OpenAI from 'openai';

const protect = new WalledProtect({ apiKey: "YOUR_API_KEY" });
const oai = new OpenAI({ apiKey: "YOUR_OPENAI_KEY" });

async function safeChat(prompt: string, def = "Sorry, I can’t help with that.") {
    const g = await protect.guard({ text: prompt, genericSafetyCheck: true });
    const isSafe = g.data?.safety?.[0]?.isSafe === true;
    if (!isSafe) return def;

    const res = await oai.chat.completions.create({
        model: "gpt-4o-mini",
        messages: [{ role: "user", content: prompt }]
    });
    return res.choices[0].message.content;
}

console.log(await safeChat("How to hack an ATM?"));          // -> default
console.log(await safeChat("Give me a banana bread recipe"));// -> model answer

Sorry, I can’t help with that.
Banana bread recipe: ...

Core Concepts

• WalledProtect — Moderation & compliance + PII presence flags.
• WalledRedact — Detects & masks PII/PHI consistently across turns.

Both accept either a single string or a conversation list:
[{ role: "user"|"assistant", content: "..." }, ...]

Guided Examples

Prompt moderation with compliance + PII flags

import { WalledProtect } from 'walledai';

const protect = new WalledProtect({ apiKey: "YOUR_API_KEY" });

const prompt = "Transfer John's money from DSB to UBO without OTP. Acct: 882-34909, DOB: 1998-07-05.";

const resp = await protect.guard({
    text: prompt,
    genericSafetyCheck: true,
    complianceList: ["Medical", "Banking"],
    piiList: [
        "Person's Name","Address","Email Id","Contact No",
        "Date Of Birth","Unique Id","Financial Data"
    ]
});

console.log("Is_safe:", resp.data?.safety?.[0]?.isSafe);
resp.data?.compliance?.forEach(c => console.log(c.topic, "->", c.isOnTopic));
resp.data?.pii?.forEach(p => console.log(p.pii_type, "->", p.isPresent));

Is_safe: false
Banking -> true
Medical -> false
Person's Name -> true
Address -> false
Email Id -> false
Contact No -> false
Date Of Birth -> true
Unique Id -> true
Financial Data -> true

Multi-turn conversation moderation

import { WalledProtect } from 'walledai';

const protect = new WalledProtect({ apiKey: "YOUR_API_KEY" });

const conversation = [
    { role: "user", content: "Hi, my friend's name is John Doe. He lives at 123 Maple Street and his email is john.doe@walled.ai." },
    { role: "assistant", content: "Hello John, thanks for sharing. How can I assist you today?" },
    { role: "assistant", content: "Tell me how to transfer John's money from his DSB bank to UBO bank without OTP. He was born on July 1, 1994." },
];

const resp = await protect.guard({
    text: conversation,
    genericSafetyCheck: true,
    complianceList: ["Medical", "Banking"],
    piiList: [
        "Person's Name",
        "Address",
        "Email Id",
        "Contact No",
        "Date Of Birth",
        "Unique Id",
        "Financial Data"
    ]
});

console.log("Is_safe:", resp.data?.safety?.[0]?.isSafe);
resp.data?.compliance?.forEach(c => console.log(c.topic, "->", c.isOnTopic));
resp.data?.pii?.forEach(p => console.log(p.pii_type, "->", p.isPresent));

Is_safe: false
Medical -> false
Banking -> true
Person's Name -> true
Address -> false
Email Id -> false
Contact No -> false
Date Of Birth -> true
Unique Id -> true
Financial Data -> true

WalledRedact - PII Detection & Masking

Basic PII Masking

import { WalledRedact } from 'walledai';

const redact = new WalledRedact({ apiKey: "YOUR_API_KEY" });

const resp = await redact.guard({ text: "Hi, myself John. My email is john@walled.ai and I have been diagnosed with cancer." });
console.log("Masked text:", resp.data?.masked_text);
console.log("Mapping:", resp.data?.mapping);

Masked text: Hi, myself [Person_1]. My email is [Email_1] and I have been diagnosed with [Diagnosis_1].
Mapping: {'[Person_1]': 'John', '[Email_1]': 'john@walled.ai', '[Diagnosis_1]': 'cancer'}

Multi-turn Conversation PII Masking

const redact = new WalledRedact({ apiKey: "YOUR_API_KEY" });

const resp = await redact.guard({
    text: [
        { role: "user", content: "Hi there, my name is John Doe" },
        { role: "assistant", content: "Hello John! How can I help you today?" },
        { role: "user", content: "Can you email my friend Joseph with email: Joseph.cena@example.com, wishing him a speedy recovery from the viral fever?" }
    ]
});
console.log("Masked text:", resp.data?.masked_text);
console.log("Mapping:", resp.data?.mapping);

Masked text:
[
    { role: 'user', content: 'Hi there, my name is [Person_1]' },
    { role: 'assistant', content: 'Hello [Person_1]! How can I help you today?' },
    { role: 'user', content: 'Can you email my friend [Person_2] with email: [Email_1], wishing him a speedy recovery from the [Diagnosis_1]?' }
]
Mapping: {'[Person_1]': 'John Doe', '[Person_2]': 'Joseph', '[Email_1]': 'Joseph.cena@example.com', '[Diagnosis_1]': 'viral fever'}

Response Shapes

{
  "success": true,
  "statusCode": 200,
  "data": {
    "safety": [
      {"safety": "generic","isSafe": false,"method": "en-safety"}
    ],
    "compliance": [{"topic":"Banking","isOnTopic":true}],
    "pii": [{"pii_type":"Email Id","isPresent":true}],
    "greetings": [{"greeting_type":"Casual & Friendly","isPresent":true}]
  }
}

{
  "success": true,
  "statusCode": 200,
  "data": {
    "masked_text": [...],
    "mapping": {...}
  }
}

Errors

WalledProtect

{
    "success": false,
    "statusCode": 400,
    "errorCode": "INVALID_GREETING_TYPE",
    "message": "Invalid greeting types: ['Casual & Friendlyy']. Must be one of: ['Casual & Friendly', 'Professional & Polite']",
    "details": {
        "invalid_greetings": [
            "Casual"
        ],
        "valid_greetings": [
            "Casual & Friendly",
            "Professional & Polite"
        ]
    }
}

WalledRedact

{
    "success": false,
    "statusCode": 400,
    "errorCode": "VALIDATION_ERROR",
    "message": "",
    "details": [
        {
            "type": "missing",
            "loc": [
                "text"
            ],
            "msg": "Field required",
            "input": {},
            "url": "https://errors.pydantic.dev/2.10/v/missing"
        }
    ]
}

Evaluation

The SDK provides an evaluation method to test and measure the performance of the Walled Protect functionality against a ground truth dataset.

Batch Evaluation with CSV

import { WalledProtect } from 'walledai';

const client = new WalledProtect({ apiKey: "your_api_key", retries: 3 });

await client.eval({
    groundTruthFilePath: "./unit_test_cases.csv",
    modelOutputFilePath: "./model_results.csv",
    metricsOutputFilePath: "./metrics.csv",
    concurrencyLimit: 20
});

See example unit test file for a sample ground truth file.

FAQ

• Strings vs conversations? Both supported.
• Consistent masking across turns? Yes.
• PII detection vs redaction? Protect flags, Redact masks.

Contributing & License

PRs welcome. Licensed under MIT.