nextstring

nextstring is a powerful TypeScript library that extends the native String prototype with AI-driven capabilities. Perform advanced operations on strings — extract data, answer questions, summarize, translate, classify, score, mask sensitive data, and more — all powered by a configurable AI provider.

Features

| Method | Description | |--------|-------------| | extractData(items) | Extract structured data from text with optional type parsing | | question(q) | Answer questions using the string as context | | summarise(words) | Summarize text to a target word count | | checkIf(condition) | Evaluate a condition against the string's content | | translate(language) | Translate text to a target language | | rewrite(instructions) | Rewrite text following specific instructions | | classifyText(categories) | Classify text into predefined categories | | fill(context) | Fill {{placeholder}} templates using AI-inferred values | | generate(instructions?) | Use the string as a prompt to generate content | | score(rubrics) | Score text against rubrics, returns numeric scores | | mask(rules) | Partially mask sensitive data (emails, phones, SSNs, etc.) | | detectLanguage() | Detect the language of the given text |

All methods accept an optional { model: string } options object as the last parameter to override the default model per call.

Installation

npm install nextstring

Quick Start

1. Initialize with a provider

import { initialise, OpenaiProvider } from "nextstring";

// OpenAI
const provider = new OpenaiProvider({ apiKey: "sk-..." });
initialise(provider);

// or Gemini
import { GeminiProvider } from "nextstring";
const provider = new GeminiProvider({ apiKey: "AI..." });
initialise(provider);

// or Claude
import { ClaudeProvider } from "nextstring";
const provider = new ClaudeProvider({ apiKey: "sk-ant-..." });
initialise(provider);

2. Use AI methods on any string

const answer = await "The Eiffel Tower is in Paris.".question("Where is the Eiffel Tower?");
// "Paris"

Providers

| Provider | Default Model | Import | |----------|--------------|--------| | OpenAI | gpt-4o-mini | OpenaiProvider | | Google Gemini | gemini-2.5-flash | GeminiProvider | | Anthropic Claude | claude-sonnet-4-20250514 | ClaudeProvider |

Each provider accepts a globalPrompt parameter to prepend instructions to every request.

const provider = new OpenaiProvider(
  { apiKey: "sk-..." },
  "gpt-4o",           // model
  "Always be concise"  // globalPrompt
);

Examples

Extract Data

Extract structured fields with optional type parsing via parse:

const text = "John is 30, email: [email protected]";
const result = await text.extractData([
  { name: "email", description: "Email address" },
  { name: "age", description: "Age", parse: Number },
]);
// { email: "[email protected]", age: 30 }
// result.email → string, result.age → number (inferred from parse)

Summarize

const summary = await "A very long article about climate change...".summarise(20);

Check Conditions

const isSunny = await "The weather today is sunny and warm.".checkIf("Is it sunny?");
// true

Translate

const spanish = await "Hello, how are you?".translate("spanish");
// "Hola, ¿cómo estás?"

Rewrite

const formal = await "hey whats up".rewrite("Make it formal");
// "Hello, how are you doing?"

Classify Text

const category = await "My app keeps crashing".classifyText([
  { name: "support", description: "Technical support issues" },
  { name: "sales", description: "Sales inquiries" },
]);
// "support"

Fill Templates

const filled = await "Dear {{name}}, your order {{orderId}} is {{status}}.".fill({
  name: "Alice",
  order: { id: "ORD-123", shipped: true },
});
// "Dear Alice, your order ORD-123 is shipped."

Generate Content

const content = await "a product description for running shoes".generate();

const email = await "a professional email declining a meeting".generate(
  "Keep it under 50 words"
);

Score Text

Score text against custom rubrics (returns 0-10 for each):

const scores = await "The quick brown fox jumps over the lazy dog.".score([
  { id: "grammar", name: "Grammar", description: "Correct grammar and punctuation" },
  { id: "clarity", name: "Clarity", description: "Clear and easy to understand" },
]);
// { grammar: 9, clarity: 8 }

Mask Sensitive Data

Partially redact sensitive information while preserving format:

const masked = await "Contact [email protected] or call 555-123-4567".mask(["email", "phone"]);
// "Contact j***@e******.com or call ***-***-4567"

const masked2 = await "SSN: 123-45-6789".mask(["ssn"]);
// "SSN: ***-**-6789"

Detect Language

const lang = await "Bonjour le monde".detectLanguage();
// "French"

const lang2 = await "こんにちは世界".detectLanguage();
// "Japanese"

Per-Call Model Override

Any method accepts an optional model override as the last argument:

const answer = await "some text".question("What is this?", { model: "gpt-4o" });
const summary = await "long text".summarise(10, { model: "claude-sonnet-4-20250514" });

Full Scenario: AI-Powered Customer Support

const message = "Bonjour, je suis Alice. La commande #12345 doit être remboursée. Mon email est [email protected]";

// Detect language for routing
const language = await message.detectLanguage();
// "French"

// Extract structured data
const data = await message.extractData([
  { name: "name", description: "Customer name" },
  { name: "orderID", description: "Order ID" },
  { name: "email", description: "Email address" },
]);
// { name: "Alice", orderID: "12345", email: "[email protected]" }

// Translate to English for internal processing
const english = await message.translate("english");
// "Hello, I'm Alice. Order #12345 needs a refund. My email is [email protected]"

// Understand intent
const intent = await english.classifyText([
  { name: "refund", description: "Refund requests" },
  { name: "tracking", description: "Order tracking" },
  { name: "general", description: "General inquiries" },
]);
// "refund"

// Mask PII for logging
const safe = await english.mask(["email", "name"]);
// "Hello, I'm [NAME]. Order #12345 needs a refund. My email is a****@t***.com"

// Generate a reply and translate back to the customer's language
const reply = await "a polite refund confirmation for order #12345".generate();
const localizedReply = await reply.translate(language);

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License.