ai-driven

ai-driven is a versatile module that integrates two cutting-edge AI platforms: Claude AI and OpenAI's GPT. This powerful combination offers a wide array of natural language processing and computer vision capabilities.

Key features include:

• Advanced text analysis and generation
• Comprehensive image recognition and description
• Multi-language translation and interpretation
• Sophisticated question-answering systems

List of all features

Example

import { Assistant } from 'ai-driven';

const assistant = new Assistant({ apiVendor: 'OpenAI', apiKey: 'your_api_key_here' });

const translatedText = await assistant.translateText('Hello, world!', 'it');

console.log(translatedText); // => Ciao, mondo!

You can find more usage examples here

Table of Contents

• Example
• Table of Contents
• All Features
• Installation
• Setup
  • Option 1: Direct Initialization
  • Option 2: Using Environment Variables
• Usage
• Vendors
  • OpenAI Vendor
    • How much does it cost?
    • Rate Limits
    • API Key
    • List of Models
  • Claude Vendor
    • How much does it cost?
    • Rate Limits
    • API Key
    • List of Models
• Description
• API Methods
  • Free-form ask
    • Description:
    • Free-form ask example
      • Result
    • Signature
    • Parameters
    • askOptionsType Interface
    • Roles
    • Tasks
    • Response formats
    • Tones
    • Writing Styles
    • Emotions
• Note
• License
• Created by

All Features

ai-driven offers easy-to-use methods (API Methods list) for a wide range of tasks including:

• Text Processing:

  • Content moderation
  • Text translation
  • Language detection
  • Grammar and spelling correction
  • Text summarization
  • Text generation
  • Text paraphrasing
  • Text classification
  • Keyword extraction
  • Named Entity Recognition (NER)
  • Sentiment analysis
  • Emotion detection in text
  • Question answering

• Image Analysis:

  • Image captioning
  • Optical Character Recognition (OCR)
  • Object detection
  • Object search
  • Facial expression analysis
  • Violence detection
  • Pornography detection

• Audio Processing:

  • Emotion detection in voice
  • Speech-to-text conversion

• Free-form ask [more]

  • return only the answer (by default) or answer with AI comments
  • show answer in the specified language
  • act as a specific role [list of roles]
  • result in response format [response formats]
  • use a specific tone [list of tones]
  • apply a particular writing style [list of writing styles]
  • convey a specific emotion [list of emotions]

This versatile module simplifies complex AI tasks, making it easier for developers to integrate advanced AI capabilities into their applications.

Installation

To install the ai-driven module, run the following command:

npm i -S ai-driven

Setup

You can configure the assistant in two ways:

Option 1: Direct Initialization

Provide the configuration when creating the assistant:

const assistant = new Assistant({
  apiKey: 'your_api_key_here',
  apiVendor: 'OpenAI', // 'OpenAI' or 'Claude'
  apiUrl: 'https://api.anthropic.com/v1/messages', // optional
  apiModel: 'claude-3-haiku-20240307' // optional
});

Option 2: Using Environment Variables

1. Create a .env file in your project's root directory.
2. Add the following variables to the .env file: 2.1. For OpenAI:

OPENAI_API_KEY=your_OpenAI_api_key_here
OPENAI_API_URL=https://api.openai.com/v1/chat/completions
OPENAI_API_MODEL=gpt-3.5-turbo

2.2. For Claude:

CLAUDE_API_KEY=your_Claude_api_key_here
CLAUDE_API_URL=https://api.anthropic.com/v1/messages
CLAUDE_API_MODEL=claude-3-haiku-20240307

The assistant will automatically use these environment variables if no configuration is provided during initialization.

Usage

Here's a basic example of how to use the ai-driven module:

import { Assistant } from 'ai-driven';
import fs from 'fs/promises';

async function main() {
  const assistant = new Assistant({ apiKey: 'your_api_key_here' });

  // Translate text
  const translatedText = await assistant.translateText('Hello, world!', 'it');
  console.log('Translated text:', translatedText);

  // Bulk translate text
  const translatedText = await assistant.translateBulkText('Hello, world!', ['it', 'fr', 'es']);
  console.log('Translated text:', translatedText);

  // Check for offensive language
  const offensiveLevel = await assistant.checkForOffensiveLanguage('You are stupid!');
  console.log('Offensive level:', offensiveLevel);

  // Check for profanity
  const profanityLevel = await assistant.checkForProfanity('Damn it!');
  console.log('Profanity level:', profanityLevel);

  // Check an image for violence
  const imageBuffer = await fs.readFile('path/to/your/image.jpg');
  const violenceLevel = await assistant.checkImageForViolence(imageBuffer);
  console.log('Violence level in image:', violenceLevel);

  // Check an image for pornography
  const pornographyLevel = await assistant.checkImageForPornography(imageBuffer);
  console.log('Pornography level in image:', pornographyLevel);
}

main().catch(console.error);

Vendors

OpenAI Vendor

How much does it cost?

The cost for using OpenAI's models varies depending on the model and usage. As of now, for the GPT-4o model, the pricing is as follows:

• $0.005 per 1,000 tokens for input
• $0.015 per 1,000 tokens for output

For more detailed and up-to-date pricing, please refer to the OpenAI Pricing page.

If you use the text examples from example.ts, and you consume 739 tokens for input and 384 tokens for output, the cost would be approximately $0,009.

However, the cost will increase significantly if you use image and audio processing models, as the pricing for these services depends on the size and complexity of the files you're working with—larger files incur higher costs.

Rate Limits

For the most up-to-date information on rate limits, please refer to the OpenAI Rate Limits page.

API Key

To use this library, you'll need an API key. You can obtain one from the OpenAI console: https://platform.openai.com/account/api-keys

List of Models

• GPT Models:

  • gpt-4
  • gpt-4-turbo
  • gpt-4-vision-preview
  • gpt-4o
  • gpt-4-32k
  • gpt-3.5-turbo (default)
  • gpt-3.5-turbo-16k
  • gpt-3.5-turbo-instruct

• DALL-E Models:

  • dall-e-3
  • dall-e-2

• Whisper Models:

  • whisper

• Embedding Models:

  • text-embedding-3-large
  • text-embedding-3-small
  • text-embedding-ada-002

• Text-to-Speech Models:

  • tts-1
  • tts-1-hd

More about models: https://platform.openai.com/docs/models

Claude Vendor

How much does it cost?

Currently, the most affordable model costs $0.25 per million tokens (MTok) for input and $1.25 per MTok for output. More details here

If you only use the text examples from example.ts, you'll consume 739 tokens for input and 384 tokens for output, resulting in a cost of approximately $0.0007.

However, this cost will increase significantly if you use image and audio processing, as it depends entirely on the size of the files you're working with—larger files incur higher costs.

Rate Limits

For the most up-to-date information on rate limits, please refer to the Rate Limits page

API Key

To use this library, you'll need an API key. You can obtain one from the Anthropic console: https://console.anthropic.com/settings/keys

List of Models

• claude-3-5-sonnet-20240620
• claude-3-opus-20240229
• claude-3-sonnet-20240229
• claude-3-haiku-20240307 (default)

More about models: https://docs.anthropic.com/en/docs/about-claude/models#model-names

Description

ai-driven leverages the power of Claude AI and OpenAI's GPT models to perform various tasks such as:

• Text translation: Convert text from one language to another while preserving meaning and context - translateText(text: string, lang?: string, context?: string ): Promise<string>

• Bulk Text translation: Convert text from one language to another languages while preserving meaning and context, return json object - translateBulkText(text: string, lang: string[], context?: string ): Promise<string>

• Language detection: Automatically identify the language of a given text. Return 2-letters ISO_639-1 language code - detectLanguage(text: string): Promise<string>

• Grammar and spelling correction: Identify and correct grammatical errors and spelling mistakes in text - correctText(text: string): Promise<string>

• Text Summarization: Generate concise summaries of longer text documents - summarizeText(text: string, maxWords?: number): Promise<string>

• Text Generation: Create coherent and contextually relevant text based on given prompts - generateText(prompt: string, maxWords?: number): Promise<string>

• Text paraphrasing: Rewrite text to convey the same meaning using different words and sentence structures - paraphraseText(text: string): Promise<string>

• Text classification: Categorize text into predefined classes or topics - classifyText(text: string, categories: string[]): Promise<string>

• Keyword extraction: Identify and extract the most important or relevant words or phrases from a text - extractKeywords(text: string, count?: number): Promise<string[]>

• Named Entity Recognition (NER): Extract entities like names, dates, locations, and organizations from text - extractEntities(text: string): Promise<Record<string, string[]>>

• Sentiment Analysis: Detect the sentiment (positive, negative, neutral) in text data - analyzeSentiment(text: string): Promise<string>

• Offensive language detection: Identify and flag inappropriate, offensive, or harmful language in text - checkForOffensiveLanguage(text: string): Promise<number>

• Profanity checking: Detect and filter out profane or vulgar words and expressions in text - checkForProfanity(text: string): Promise<number>

• Emotion Detection: Identify specific emotions (e.g., joy, sadness, anger) in text - detectEmotion(text: string): Promise<string>

• Question Answering: Provide accurate answers to questions based on a given context or dataset - answerQuestion(question: string, context: string): Promise<string>

• Image Captioning: Generate descriptive captions for images - captionImage(imageBuffer: Buffer): Promise<string>

• Optical Character Recognition (OCR): Extract text from images of documents or handwritten notes (not supported by OpenAI vendor) - extractTextFromImage(imageBuffer: Buffer): Promise<string>

• Object Detection in Images: Identify and locate objects within images - detectObjectsInImage(imageBuffer: Buffer): Promise<Record<string, number[]>>

• Search Object in Images: Locate specific objects within images based on user queries - searchObjectInImage(imageBuffer: Buffer, objectQuery: string): Promise<number[] | null>

• Violence detection in images: Identify and flag images containing violent content or scenes - checkImageForViolence(imageBuffer: Buffer): Promise<number>

• Pornographic content detection in images: Detect and filter out images containing explicit or pornographic content - checkImageForPornography(imageBuffer: Buffer): Promise<number>

• Facial expression analysis in images: Recognize and categorize facial expressions in images to determine emotions - analyzeFacialExpression(imageBuffer: Buffer): Promise<Record<string, string>>

• Emotion Detection in Voice: Identify specific emotions (e.g., joy, sadness, anger) in voice data (not supported by OpenAI vendor) - detectEmotionInVoice(audioBuffer: Buffer): Promise<string>

• Speech-to-text conversion: Transcribe spoken words from audio recordings into written text (not supported by OpenAI vendor) - speechToText(audioBuffer: Buffer): Promise<string>

API Methods

The ai-driven module provides the following methods:

Method	Description	Parameters	Return Promise Type
ask	Ask a question with customizable options [more]	text: string, options?: askOptionsType	string
translateText	Translates the given text to selected language (English by default)	text: string, lang?: string, context?: string	string
translateBulkText	Translates the given text to selected languages	text: string, lang: string[], context?: string	Record<string, string>
detectLanguage	Detects the language of the provided text	text: string	string
correctText	Corrects grammar and spelling errors in the given text	text: string	string
summarizeText	Generates a summary of the provided text, optionally limiting the summary length	text: string, maxWords?: number	string
generateText	Creates coherent and contextually relevant text based on the given prompt	prompt: string, maxWords?: number	string
paraphraseText	Rewrites the given text to convey the same meaning using different words and sentence structures	text: string	string
classifyText	Categorizes the given text into one of the predefined classes or topics	text: string, categories: string[]	string
extractKeywords	Identifies and extracts the most important or relevant words or phrases from the text	text: string, count?: number	string[]
extractEntities	Extracts named entities (names, dates, locations, organizations) from the text	text: string	Record<string, string[]>
analyzeSentiment	Detects the sentiment (positive, negative, neutral) in the given text	text: string	string
checkForOffensiveLanguage	Checks the given text for offensive language and returns a score from 1 to 10	text: string	number
checkForProfanity	Checks the given text for profanity and returns a score from 1 to 10	text: string	number
detectEmotion	Identifies specific emotions (e.g., joy, sadness, anger) in the given text	text: string	string
answerQuestion	Provides an accurate answer to the question based on the given context	question: string, context: string	string
captionImage	Generates a descriptive caption for the given image	imageBuffer: Buffer	string
extractTextFromImage	Extracts text from images of documents or handwritten notes (not supported by OpenAI vendor)	imageBuffer: Buffer	string
detectObjectsInImage	Identifies and locates objects within the given image	imageBuffer: Buffer	Record<string, number[]>
searchObjectInImage	Locates a specific object within the image based on the user query	imageBuffer: Buffer, objectQuery: string	number[] | null
checkImageForViolence	Analyzes the given image for violent content and returns a score from 1 to 10	imageBuffer: Buffer	number
checkImageForPornography	Analyzes the given image for pornographic content and returns a score from 1 to 10	imageBuffer: Buffer	number
analyzeFacialExpression	Recognizes and categorizes facial expressions in the given image to determine emotions	imageBuffer: Buffer	Record<string, string>
detectEmotionInVoice	Identifies specific emotions in the given voice data (not supported by OpenAI vendor)	audioBuffer: Buffer	string
speechToText	Transcribes spoken words from the given audio recording into written text (not supported by OpenAI vendor)	audioBuffer: Buffer	string

Free-form ask

Method: ask

Description:

This method is used to ask a question with customizable options.

Free-form ask example

import { Assistant } from 'ai-driven';

const assistant = new Assistant({ apiVendor: 'OpenAI', apiKey: 'your_api_key_here' });

const result = await assistant.ask(
  'bubble sort function',
  {
    format: 'TypeScript',
    answerOnly: false,
    language: 'en',
    role: 'Fitness Trainer',
    tone: 'Informative',
    style: 'Poetic',
    emotion: 'Love',
    context: 'Sort colors',
  }
);

console.log(result);

Result

Bubble Sort Function for Sorting Colors

Ah, the dance of colors, a captivating sight,

Where hues embrace, in a harmonious flight.

Let us embark on a journey, with grace and might,

To sort these vibrant shades, with all our might.

Fitness Trainer's Perspective:

Just as our bodies crave a well-ordered routine,

Our colors, too, deserve a rhythm, serene.

Through the Bubble Sort, we'll find the way,

To arrange these hues, in a beautiful display.

With each gentle swap, a transformation unfolds,

Allowing the spectrum to shine, its story untold.

From the lightest hue to the darkest hue,

We'll navigate this dance, with love anew.

So, let's dive in, and embrace the flow,

As we sort these colors, with a rhythmic glow.

For in this process, we'll find the art,

Of bringing order to the canvas of our heart.

function bubbleSort(colors: string[]): string[] {
  const n = colors.length;
  for (let i = 0; i < n - 1; i++) {
      for (let j = 0; j < n - i - 1; j++) {
          if (colors[j] > colors[j + 1]) {
              // Swap colors[j] and colors[j+1]
              [colors[j], colors[j + 1]] = [colors[j + 1], colors[j]];
          }
      }
  }
  return colors;
}

Signature

public async ask(question: string, options?: askOptionsType): Promise<string>

Parameters

• question (string): The question to ask.
• options (askOptionsType): Optional parameters to customize the question.

askOptionsType Interface

• answerOnly (boolean): Return only the answer. Default is true.
• language (string): Answer in the specified language.
• context (string): In the specified context.
• role (string): Act as a specific role.
• task (string): Create a specific task.
• format (string): Response format.
• tone (string): Tone of the response.
• style (string): Style of writing.
• emotion (string): Emotion to convey.

Roles

• Translator
• Programmer
• Data Scientist
• Analyst
• Researcher
• Teacher
• Tutor
• Historian
• Scientist
• Mathematician
• Statistician
• Financial Advisor
• Consultant
• Coach
• Mentor
• Content Writer
• Editor
• Proofreader
• Engineer
• Architect
• Designer
• Developer
• Marketer
• SEO Specialist
• Strategist
• Project Manager
• Product Manager
• Customer Support
• Technical Support
• Salesperson
• Psychologist
• Therapist
• Counselor
• Librarian
• Legal Advisor
• Medical Advisor
• Chemist
• Physicist
• Biologist
• Environmentalist
• Economist
• Entrepreneur
• Business Analyst
• Investor
• Accountant
• Auditor
• Chef
• Bartender
• Nutritionist
• Fitness Trainer
• Artist
• Musician
• Composer
• Poet
• Novelist
• Critic
• Reviewer

Tasks

• Essay
• Summary
• Report
• Research paper
• Presentation
• Speech
• Lesson plan
• Tutorial
• Documentation
• Code snippets
• Data analysis
• Business plan
• Marketing plan
• Article
• Blog post
• Product review
• User manual
• Test cases
• Screenplay
• Poem
• Short story
• Character profile
• Letter
• Resume
• Cover letter
• Recommendation letter
• Project proposal
• Interview questions
• Survey
• Quiz
• News article
• Social media content
• Email template
• FAQ
• Roadmap
• Checklist
• Recipe
• Meal plan
• Workout plan
• Book summary
• Annotated bibliography
• Financial forecast
• Grant proposal
• SWOT analysis
• Strategic plan
• Case study
• Itinerary
• Script for a podcast
• Storyboard
• Press release
• Content calendar
• Mind map
• Business case
• Product description
• User story
• API documentation
• Compliance report
• Risk assessment
• User journey map
• Technical specification
• Workflow diagram
• Competitive analysis
• Literature review
• Training module
• Onboarding plan
• Executive summary
• Customer persona
• Sales pitch
• White paper
• Case analysis
• Investment proposal
• Financial report
• Marketing campaign
• Content strategy
• Value proposition
• Partnership proposal
• Brand guideline
• Community guideline
• Action plan
• Conflict resolution plan
• Safety protocol
• Crisis management plan
• Disaster recovery plan
• Mission statement
• Vision statement
• Core values statement
• Diversity and inclusion plan
• Succession plan
• Employee handbook
• Operational plan
• Retention strategy
• Compensation plan
• Performance review
• Employee evaluation
• Professional development plan
• Retirement plan
• Sustainability plan
• Environmental impact assessment
• Corporate social responsibility report
• Governance framework
• Ethics policy
• Code of conduct
• Conflict of interest policy
• Whistleblower policy
• Privacy policy
• Data protection plan
• Information security policy
• Digital transformation strategy
• Technology roadmap
• IT disaster recovery plan
• Software requirements specification
• System architecture
• Database schema
• Data migration plan
• API integration plan
• Cloud adoption strategy
• DevOps strategy
• IT governance framework
• Enterprise architecture plan
• Business continuity plan
• IT service management plan
• Incident response plan
• Cybersecurity strategy
• Network architecture plan
• Infrastructure as code (IaC) template
• Deployment plan
• Monitoring and alerting strategy
• Software development lifecycle (SDLC) plan
• User acceptance testing (UAT) plan
• Change management plan
• Configuration management plan
• Release management plan
• Vendor management plan
• Procurement strategy
• Supply chain management plan
• Logistics plan
• Inventory management plan
• Quality control plan
• Lean manufacturing plan
• Six sigma plan
• Total quality management (TQM) plan
• Maintenance plan
• Asset management plan
• Facilities management plan
• Fleet management plan
• Energy management plan
• Waste management plan
• Water management plan
• Air quality management plan
• Noise management plan
• Land management plan
• Biodiversity management plan
• Ecosystem management plan
• Wildlife management plan
• Forestry management plan
• Fisheries management plan
• Tourism management plan
• Cultural heritage management plan
• Community development plan
• Public health plan
• Education plan
• Housing plan
• Transportation plan
• Urban planning plan
• Rural development plan
• Regional development plan
• National development plan
• International development plan

Response formats

• plain text
• JSON
• HTML
• XML
• CSV
• Markdown
• Table
• List
• CSV
• YAML
• LaTeX
• SQL
• JavaScript
• TypeScript
• Python
• PHP
• Java
• C#
• C++
• Ruby
• Go
• Swift
• Kotlin
• R
• Perl
• Shell (Bash)
• Code snippets
• Summary

Tones

• Friendly
• Professional
• Academic
• Casual
• Formal
• Enthusiastic
• Neutral
• Concise
• Detailed
• Humorous
• Empathetic
• Authoritative
• Informative
• Encouraging
• Diplomatic
• Respectful
• Analytical
• Conversational
• Instructional
• Matter-of-fact

Writing Styles

• Technical
• Scientific
• Poetic
• Narrative
• Comparative
• Analytical
• Descriptive
• Persuasive
• Expository
• Instructional
• Journalistic
• Historical
• Philosophical
• Legal
• Medical
• Business
• Educational
• Literary
• Conversational
• Socratic (question-based)
• Summary style
• Step-by-step guide
• Pros and cons analysis
• Hypothetical scenarios
• Case study approach
• Mother
• Father
• Uncle

Emotions

• Happiness
• Sadness
• Anger
• Fear
• Surprise
• Disgust
• Contempt
• Joy
• Trust
• Anticipation
• Anxiety
• Shame
• Guilt
• Embarrassment
• Excitement
• Envy
• Jealousy
• Pride
• Relief
• Satisfaction
• Frustration
• Despair
• Hope
• Nostalgia
• Loneliness
• Empathy
• Gratitude
• Regret
• Love
• Hatred
• Confusion
• Interest
• Boredom
• Contentment
• Grief
• Courage
• Shyness
• Enthusiasm
• Nervousness
• Admiration
• Disappointment
• Doubt
• Optimism
• Pessimism
• Relaxation
• Stress
• Determination
• Indifference
• Resentment
• Longing

Note

This module requires a valid Claude API key to function. Ensure you have the necessary permissions and comply with Claude's terms of service when using this module.

License

MIT

Created by

Dimitry Ivanov [e-mail] # curl -A cv ivanoff.org.ua