time-ai

Time-aware utilities for LLM applications - parse dates, add temporal context, and optimize prompts

Links

• Project site: https://time-ai.blueprintlab.io
• NPM package: https://www.npmjs.com/package/@blueprintlabio/time-ai

Features

• Natural Language Date Parsing - Parse dates from text like "next Friday", "end of month", "tomorrow at 3pm"
• LLM Context Enhancement - Add temporal context to prompts for better AI understanding
• Multiple Formatting Strategies - Preserve, normalize, or hybrid date formatting
• Timezone Aware - Handle dates across different timezones
• Locale Support - Format dates according to different locales
• TypeScript First - Full type safety and IntelliSense support

Installation

npm install @blueprintlabio/time-ai

Quick Start

import { TimeAI } from '@blueprintlabio/time-ai';

const timeAI = new TimeAI({
  timezone: 'America/New_York',
  locale: 'en-US'
});

// Enhance prompts with temporal context
const result = timeAI.enhancePrompt("Schedule a meeting next Friday at 2pm");
console.log(result.enhancedText);
// "Schedule a meeting next Friday (2025-09-19) at 2pm"

// Add current date context to any prompt
const prompt = timeAI.addContext("What's the weather like?");
console.log(prompt);
// Current date: 2025-09-15 (Sunday, 2025)
// Timezone: America/New_York
// 
// What's the weather like?

// Parse dates from natural language
const date = timeAI.parseDate("tomorrow at 3pm");
console.log(date?.resolvedDate);
// Date object for tomorrow at 3pm

API Reference

TimeAI Class

Constructor

new TimeAI(config?: TimeAIConfig)

Config Options:

• timezone?: string - Target timezone (default: system timezone)
• locale?: string - Locale for formatting (default: system locale)
• strategy?: 'preserve' | 'normalize' | 'hybrid' - Date formatting strategy (default: 'hybrid')
• includeContext?: boolean - Whether to include temporal context (default: true)

Methods

enhancePrompt(text: string, options?: { strategy?: 'preserve' | 'normalize' | 'hybrid' }): EnhancedPrompt

Enhance text with temporal context and date disambiguation.

const result = timeAI.enhancePrompt("Meet next Friday", { strategy: 'hybrid' });
// Returns: {
//   originalText: "Meet next Friday",
//   enhancedText: "Meet next Friday (2025-09-19)", 
//   context: "Current date: 2025-09-15...",
//   extractions: [...],
//   tokensAdded: 12
// }

Strategies:

• preserve - Keep original date text unchanged
• normalize - Replace with absolute dates (YYYY-MM-DD)
• hybrid - Combine relative and absolute: "next Friday (2025-09-19)"

parseDate(text: string): DateExtraction | null

Parse the first date found in text.

const extraction = timeAI.parseDate("tomorrow at 3pm");
// Returns: {
//   originalText: "tomorrow at 3pm",
//   resolvedDate: Date,
//   confidence: 0.95,
//   type: 'relative',
//   start: 0,
//   end: 16,
//   grain: 'hour'
// }

parseDates(text: string): DateExtraction[]

Parse all dates found in text.

formatDate(date: Date, style: FormatStyle): string

Format dates for different use cases.

Format Styles:

• context - "Today is Monday, September 15, 2025"
• hybrid - "next Friday (Sep 19)"
• compact - "2025-09-15"
• human - "Monday, September 15, 2025"
• iso - "2025-09-15T00:00:00.000Z"
• relative - "in 3 days"

addContext(prompt: string): string

Add temporal context to any prompt.

timeAI.addContext("What should I do today?");
// "Current date: 2025-09-15 (Sunday, 2025)\nTimezone: America/New_York\n\nWhat should I do today?"

Convenience Functions

import { enhancePrompt, parseDate, addContext } from '@blueprintlabio/time-ai';

// Use default instance
const result = enhancePrompt("Meet tomorrow");
const date = parseDate("next week");
const prompt = addContext("Hello world");

// Or with custom config
const result = enhancePrompt("Meet tomorrow", { timezone: 'UTC' });

Legacy Compatibility

For easy migration from existing time utilities:

import { getCurrentTimeContext, formatDateForOpenAI, addDateContextToPrompt } from '@blueprintlabio/time-ai';

// Drop-in replacements for your existing functions
const context = getCurrentTimeContext();
const formatted = formatDateForOpenAI(new Date());
const enhanced = addDateContextToPrompt("Your prompt here");

Use Cases

LLM Prompt Enhancement

const timeAI = new TimeAI({ strategy: 'hybrid' });

// Before
const prompt = "Schedule a demo call next Tuesday and send reminder tomorrow";

// After
const enhanced = timeAI.enhancePrompt(prompt);
console.log(enhanced.enhancedText);
// "Schedule a demo call next Tuesday (2025-09-23) and send reminder tomorrow (2025-09-16)"

Task Scheduling

const timeAI = new TimeAI({ strategy: 'normalize' });

const userInput = "Remind me to call client next Friday";
const result = timeAI.enhancePrompt(userInput);

// Extract absolute date for scheduling
const dateExtraction = result.extractions[0];
const scheduleDate = dateExtraction.resolvedDate; // Exact Date object

Multi-timezone Applications

// User in New York
const nyTimeAI = new TimeAI({ timezone: 'America/New_York' });

// User in London  
const londonTimeAI = new TimeAI({ timezone: 'Europe/London' });

// Same relative date, different absolute times
const prompt = "Meet tomorrow at 9am";
const nyResult = nyTimeAI.enhancePrompt(prompt);
const londonResult = londonTimeAI.enhancePrompt(prompt);

Chatbot Context

const timeAI = new TimeAI();

function processMessage(userMessage: string) {
  // Add temporal awareness to every conversation
  const enhanced = timeAI.addContext(userMessage);
  
  // Send to LLM with temporal context
  return callLLM(enhanced);
}

Advanced Usage

Custom Date Patterns

The library uses chrono-node internally and includes custom parsers for business contexts:

• "next business day"
• "end of this week" (Friday)
• "end of quarter"
• "next workday"

Timezone Handling

const timeAI = new TimeAI({ timezone: 'UTC' });

// Change timezone dynamically
timeAI.setTimezone('Asia/Tokyo');
timeAI.setLocale('ja-JP');

// Check timezone-aware comparisons
const isTodayInTokyo = timeAI.isToday(someDate);

Performance Considerations

The library provides token count estimation for LLM optimization:

const result = timeAI.enhancePrompt("Long prompt with many dates...");
console.log(`Added ${result.tokensAdded} tokens`);

// Use compact context for token-sensitive applications
const timeAI = new TimeAI({ includeContext: false });

Test Coverage

Coverage from latest test run:

• Statements: 91.83%
• Branches: 82.53%
• Functions: 88.88%
• Lines: 92.50%

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

MIT © Blueprint Lab

Related Projects

• chrono-node - Natural language date parser
• date-fns - Modern JavaScript date utility library
• dayjs - Lightweight date library