GPTI

This package simplifies your interaction with various GPT models, eliminating the need for tokens or other methods to access GPT. It also allows you to use three artificial intelligences to generate images: DALL·E, Prodia, and more, some of which are premium while others are free, all of this without restrictions or limits.

Installation

You can install the package via NPM

npm i gpti

Available Models

GPTI provides access to a variety of artificial intelligence models to meet various needs. Currently, the available models include:

ChatGPT
ChatGPT v2
ChatGPT Web
Bing
LLaMA-2
DALL·E
DALL-E 2 (PRO)
DALL-E Mini
Prodia
Prodia Stable-Diffusion
Prodia Stable-Diffusion XL (PRO)
Pixart-A (PRO)
Pixart-LCM (PRO)
Stable-Diffusion 1.5
Stable-Diffusion 2.1
Stable-Diffusion XL (PRO)
EMI
Render3D (PRO)
PixelArt (PRO)
Animagine-XL (PRO)
Playground (PRO)

Api key

If you want to access the premium models, enter your credentials. You can obtain them by clicking here.

// import { nexra } from "gpti";
// import { nexra } from "gpti/promise";
// const { nexra } = require("gpti/promise");

const { nexra } = require("gpti");

nexra("user-xxxxxxxx", "nx-xxxxxxx-xxxxx-xxxxx");

Usage GPT

// const { gpt } = require("gpti/promise");
const { gpt } = require("gpti");

let history = [
    {
        role: "assistant",
        content: "Hello! How are you today?"
    },
    {
        role: "user",
        content: "Hello, my name is Yandri."
    },
    {
        role: "assistant",
        content: "Hello, Yandri! How are you today?"
    }
];

gpt.v1({
    messages: history,
    prompt: "Can you repeat my name?",
    model: "GPT-4",
    markdown: false
}, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { gpt } from "gpti/promise";
const { gpt } = require("gpti/promise");

try {
    let data = await gpt.v1({
        messages: history,
        prompt: "Can you repeat my name?",
        model: "GPT-4",
        markdown: false
    });

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "model": "gpt-4",
    "gpt": "Hello, Yandri! How can I assist you today?",
    "original": null
}

Models

Select one of these available models in the API to enhance your experience.

gpt-4
gpt-4-0613
gpt-4-32k
gpt-4-0314
gpt-4-32k-0314
gpt-3.5-turbo
gpt-3.5-turbo-16k
gpt-3.5-turbo-0613
gpt-3.5-turbo-16k-0613
gpt-3.5-turbo-0301
text-davinci-003
text-davinci-002
code-davinci-002
gpt-3
text-curie-001
text-babbage-001
text-ada-001
davinci
curie
babbage
ada
babbage-002
davinci-002

Usage GPT v2

It's quite similar, with the difference that it has the capability to generate real-time responses via streaming using gpt-3.5-turbo.

// import { gpt } from "gpti";
const { gpt } = require("gpti");

let history = [
    {
        "role": "assistant",
        "content": "Hello! How are you today?"
    },
    {
        "role": "user",
        "content": "Hello, my name is Yandri."
    },
    {
        "role": "assistant",
        "content": "Hello, Yandri! How are you today?"
    },
    {
        "role": "user",
        "content": "Can you repeat my name?"
    }
];

gpt.v2({
    messages: history,
    markdown: false,
    stream: false
}, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { gpt } from "gpti/promise";
const { gpt } = require("gpti/promise");

try {
    let data = await gpt.v2({
        messages: history,
        markdown: false
    });

    console.log(data);

    // streaming
    gpt.v2_strm({
        messages: history,
        markdown: false
    }, (err, data) => {
        if(err != null){
            console.log(err);
        } else {
            console.log(data);
        }
    });
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "model": "ChatGPT",
    "message": "Of course, Yandri! How can I assist you today?",
    "original": null
}

JSON Streaming

{"message":"","original":null,"finish":false,"error":false}
{"message":"Of","original":null,"finish":false,"error":false}
{"message":"Of course","original":null,"finish":false,"error":false}
{"message":"Of course,","original":null,"finish":false,"error":false}
{"message":"Of course, Yand","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri!","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist you","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist you today","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist you today?","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist you today?","original":null,"finish":false,"error":false}
{"message":"Of course, Yandri! How can I assist you today?","original":null,"finish":false,"error":false}
{"message":null,"original":null,"finish":true,"error":false}

Usage GPT Web

GPT-4 has been enhanced by me, but errors may arise due to technological complexity. It is advisable to exercise caution when relying entirely on its accuracy for online queries.

// import { gpt } from "gpti";
const { gpt } = require("gpti");

gpt.web({
    prompt: "Are you familiar with the movie Wonka released in 2023?",
    markdown: false
}, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { gpt } from "gpti/promise";
const { gpt } = require("gpti/promise");

try {
    let data = await gpt.web({
        prompt: "Are you familiar with the movie Wonka released in 2023?",
        markdown: false
    });

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "gpt": "Yes, I am familiar with the movie Wonka released in 2023. Wonka is a musical fantasy film directed by Paul King, adapted from the character at the center of Roald Dahl's iconic children's book, \"Charlie and the Chocolate Factory.\" The film follows the story of a young and poor Willy Wonka as he dreams of opening a shop in a chocolate-renowned city and discovers that the industry is controlled by a greedy cartel. The film has a rating of 7.1/10 and has received positive reviews with a score of 83% on Rotten Tomatoes. It was released on December 15, 2023, and has earned $552.1 million at the box office. The cast includes actors such as Timothée Chalamet. Unfortunately, I couldn't find information on whether the movie is available on Netflix.",
    "original": null
}

Usage Bing

// import { bing } from "gpti";
const { bing } = require("gpti");

let history = [
    {
        role: "assistant",
        content: "Hello! How can I help you today? 😊"
    },
    {
        role: "user",
        content: "Hi, tell me the names of the movies released in 2023."
    },
    {
        role: "assistant",
        content: "Certainly! Here are some movies that were released in 2023:\n\n1.  **About My Father** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n2.  **The Little Mermaid** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n3.  **Fast X** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n4.  **Spider-Man: Across the Spider-Verse** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n5.  **The Machine** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n6.  **Book Club: The Next Chapter** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n7.  **Guardians of the Galaxy Vol. 3** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n8.  **John Wick: Chapter 4** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n9.  **Are You There God? It's Me, Margaret** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n10.  **Evil Dead Rise** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n11.  **The Super Mario Bros. Movie** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n12.  **Love Again** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n13.  **Kandahar** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n14.  **Dungeons & Dragons: Honor Among Thieves** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n15.  **Shin Kamen Rider** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n16.  **Knights of the Zodiac** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n17.  **The Pope's Exorcist** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n18.  **Shazam! Fury of the Gods** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n19.  **All That Breathes** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n20.  **Sailor Moon Cosmos** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n21.  **Hypnotic** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n22.  **Sound of Freedom** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n23.  **The Boogeyman** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n24.  **Chicken Run: Dawn of the Nugget** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n25.  **A Lot of Nothing** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n26.  **Followers** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n27.  **Big George Foreman** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n28.  **Asterix & Obelix: The Middle Kingdom** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n29.  **Ant-Man and the Wasp: Quantumania** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n30.  **Transformers: Rise of the Beasts** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n31.  **Follow Her** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n32.  **Prom Pact** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n33.  **God Is a Bullet** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n34.  **Still: A Michael J. Fox Movie** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n35.  **Nefarious** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n36.  **Nanny Dearest** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n37.  **Monica** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n38.  **Wild Life** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n39.  **Palm Trees and Power Lines** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n40.  **What's Love Got to Do with It?** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n41.  **Creed III** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n42.  **One True Loves** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n43.  **BlackBerry** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n44.  **Suzume** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n45.  **Rock Dog 3: Battle the Beat** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n46.  **Gridman Universe** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n47.  **Digimon Adventure 02: The Beginning** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n48.  **Woman of the Photographs** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n49.  **El Tonto** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n50.  **Seriously Red** [^1^](https://editorial.rottentomatoes.com/guide/best-movies-of-2023/)\n\nI hope this helps! Let me know if you have any other questions."
    },
    {
        role: "user",
        content: "Can you tell me how many movies you've told me about?"
    }
];

bing({
    messages: history,
    conversation_style: "Balanced",
    markdown: false,
    stream: false
}, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { bing } from "gpti/promise";
const { bing } = require("gpti/promise");

try {
    let data = await bing.asc({
        messages: history,
        conversation_style: "Balanced",
        markdown: false
    });

    console.log(data);

    // streaming
    bing.strm({
        messages: history,
        conversation_style: "Balanced",
        markdown: false
    }, (err, data) => {
        if(err != null){
            console.log(err);
        } else {
            console.log(data);
        }
    });
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "model": "Bing",
    "message": "I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with?",
    "original:": null
}

JSON Streaming

{"message":"I","original":null,"finish":false,"error":false}
{"message":"I have","original":null,"finish":false,"error":false}
{"message":"I have told","original":null,"finish":false,"error":false}
{"message":"I have told you","original":null,"finish":false,"error":false}
{"message":"I have told you about","original":null,"finish":false,"error":false}
{"message":"I have told you about \\*\\*","original":null,"finish":false,"error":false}
{"message":"I have told you about \\*\\*50","original":null,"finish":false,"error":false}
{"message":"I have told you about \\*\\*50 movies","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies**","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 202","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023.","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with?","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with?","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with?","original":null,"finish":false,"error":false}
{"message":"I have told you about **50 movies** that were released in 2023. Is there anything else I can help you with?","original":null,"finish":false,"error":false}
{"message":null,"original":null,"finish":true,"error":false}

Parameters

Parameter	Default	Description
conversation_style	Balanced	You can use between: "Balanced", "Creative" and "Precise"
markdown	false	You can convert the dialogues into continuous streams or not into Markdown
stream	false	You are given the option to choose whether you prefer the responses to be in real-time or not

Usage LLaMA-2

// import { llama2 } from "gpti";
const { llama2 } = require("gpti");

let history = [
    {
        "role": "assistant",
        "content": "Hello! How are you?"
    },
    {
        "role": "user",
        "content": "Hello! How are you? Could you tell me your name?"
    }
];

llama2({
    messages:  history,
    system_message: "",
    temperature: 0.9,
    max_tokens: 4096,
    top_p: 0.6,
    repetition_penalty: 1.2,
    markdown: false,
    stream: false
}, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { llama2 } from "gpti/promise";
const { llama2 } = require("gpti/promise");

try {
    let data = await llama2.asc({
        messages:  history,
        system_message: "",
        temperature: 0.9,
        max_tokens: 4096,
        top_p: 0.6,
        repetition_penalty: 1.2,
        markdown: false
    });

    console.log(data);

    // streaming
    llama2.strm({
        messages:  history,
        system_message: "",
        temperature: 0.9,
        max_tokens: 4096,
        top_p: 0.6,
        repetition_penalty: 1.2,
        markdown: false
    }, (err, data) => {
        if(err != null){
            console.log(err);
        } else {
            console.log(data);
        }
    });
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "model": "LLaMA2",
    "message": "Sure, my name is LLaMA. I'm doing well, thanks for asking! Is there anything else you would like to chat about or ask me?",
    "original": null
}

JSON Streaming

{"message":"Hello","original":null,"finish":false,"error":false}
{"message":"Hello!","original":null,"finish":false,"error":false}
{"message":"Hello! I","original":null,"finish":false,"error":false}
{"message":"Hello! I'","original":null,"finish":false,"error":false}
{"message":"Hello! I'm","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well,","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking.","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is L","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLa","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA,","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of research","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta A","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI.","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you?","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What brings","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What brings you","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What brings you here","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What brings you here today","original":null,"finish":false,"error":false}
{"message":"Hello! I'm doing well, thanks for asking. My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. How about you? What brings you here today?","original":null,"finish":false,"error":false}
{"message":null,"original":null,"finish":true,"error":false}

Parameters

Parameter	Default	Description
system_message		Explain what specific task you want the artificial intelligence to perform
max_tokens	4096	Min: 0, Max: 4096
temperature	0.9	Min: 0, Max: 1
top_p	0.6	Min: 0, Max: 1
repetition_penalty	1.2	Min: 1, Max: 2
markdown	false	You can convert the dialogues into continuous streams or not into Markdown
stream	false	You are given the option to choose whether you prefer the responses to be in real-time or not

Usage DALL·E

// import { dalle } from "gpti";
const { dalle } = require("gpti");

let data_js = {
    prompt: "starry sky over the city"
};

dalle.v1(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { dalle } from "gpti/promise";
const { dalle } = require("gpti/promise");

try {
    let data = await dalle.v1(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "starry sky over the city",
    "model": "DALL·E",
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Usage DALL·E 2 (PRO)

// import { dalle } from "gpti";
const { dalle } = require("gpti");

let data_js = {
    prompt: "An extensive green valley stretches toward imposing mountains, adorned with meadows and a winding stream. The morning sun paints the sky with warm tones, illuminating the landscape with a serenity that invites contemplation and peace.",
    data: {
        prompt_negative: "",
        width: 1024,
        height: 1024,
        guidance_scale: 6
    }
};

dalle.v2(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { dalle } from "gpti/promise";
const { dalle } = require("gpti/promise");

try {
    let data = await dalle.v2(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An extensive green valley stretches toward imposing mountains, adorned with meadows and a winding stream. The morning sun paints the sky with warm tones, illuminating the landscape with a serenity that invites contemplation and peace.",
    "model": "DALL·E-2",
    "data": {
        "prompt_negative": "(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, (NSFW:1.25)",
        "width": 1024,
        "height": 1024,
        "guidance_scale": 6
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative	(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, (NSFW:1.25)	Indicates what the AI should not do
width	1024	Min: 512, Max: 2048
height	1024	Min: 512, Max: 2048
guidance_scale	6	Min: 0.1, Max: 20

Usage DALL·E Mini

// import { dalle } from "gpti";
const { dalle } = require("gpti");

let data_js = {
    prompt: "An extensive green valley stretches toward imposing mountains, adorned with meadows and a winding stream. The morning sun paints the sky with warm tones, illuminating the landscape with a serenity that invites contemplation and peace."
};

dalle.mini(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { dalle } from "gpti/promise";
const { dalle } = require("gpti/promise");

try {
    let data = await dalle.mini(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An extensive green valley stretches toward imposing mountains, adorned with meadows and a winding stream. The morning sun paints the sky with warm tones, illuminating the landscape with a serenity that invites contemplation and peace.",
    "model": "DALL·E-mini",
    "images": [
        "data:image/jpeg;base64,...",
        "..."
    ]
}

Usage Prodia

// import { prodia } from "gpti";
const { prodia } = require("gpti");

let data_js = {
    prompt: "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    data: {
        model: "absolutereality_V16.safetensors [37db0fc3]",
        steps: 25,
        cfg_scale: 7,
        sampler: "DPM++ 2M Karras",
        negative_prompt: ""
    }
};

prodia.v1(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { prodia } from "gpti/promise";
const { prodia } = require("gpti/promise");

try {
    let data = await prodia.v1(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    "model": "Prodia",
    "data": {
        "model": "absolutereality_V16.safetensors [37db0fc3]",
        "steps": 25,
        "cfg_scale": 7,
        "sampler": "DPM++ 2M Karras",
        "negative_prompt": ""
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Models

List of models

3Guofeng3_v34.safetensors [50f420de]
absolutereality_V16.safetensors [37db0fc3]
absolutereality_v181.safetensors [3d9d4d2b]
amIReal_V41.safetensors [0a8a2e61]
analog-diffusion-1.0.ckpt [9ca13f02]
anythingv3_0-pruned.ckpt [2700c435]
anything-v4.5-pruned.ckpt [65745d25]
anythingV5_PrtRE.safetensors [893e49b9]
AOM3A3_orangemixs.safetensors [9600da17]
blazing_drive_v10g.safetensors [ca1c1eab]
breakdomain_I2428.safetensors [43cc7d2f]
breakdomain_M2150.safetensors [15f7afca]
cetusMix_Version35.safetensors [de2f2560]
childrensStories_v13D.safetensors [9dfaabcb]
childrensStories_v1SemiReal.safetensors [a1c56dbb]
childrensStories_v1ToonAnime.safetensors [2ec7b88b]
Counterfeit_v30.safetensors [9e2a8f19]
cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]
cyberrealistic_v33.safetensors [82b0d085]
dalcefo_v4.safetensors [425952fe]
deliberate_v2.safetensors [10ec4b29]
deliberate_v3.safetensors [afd9d2d4]
dreamlike-anime-1.0.safetensors [4520e090]
dreamlike-diffusion-1.0.safetensors [5c9fd6e0]
dreamlike-photoreal-2.0.safetensors [fdcf65e7]
dreamshaper_6BakedVae.safetensors [114c8abb]
dreamshaper_7.safetensors [5cf5ae06]
dreamshaper_8.safetensors [9d40847d]
edgeOfRealism_eorV20.safetensors [3ed5de15]
EimisAnimeDiffusion_V1.ckpt [4f828a15]
elldreths-vivid-mix.safetensors [342d9d26]
epicphotogasm_xPlusPlus.safetensors [1a8f6d35]
epicrealism_naturalSinRC1VAE.safetensors [90a4c676]
epicrealism_pureEvolutionV3.safetensors [42c8440c]
ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]
indigoFurryMix_v75Hybrid.safetensors [91208cbb]
juggernaut_aftermath.safetensors [5e20c455]
lofi_v4.safetensors [ccc204d6]
lyriel_v16.safetensors [68fceea2]
majicmixRealistic_v4.safetensors [29d0de58]
mechamix_v10.safetensors [ee685731]
meinamix_meinaV9.safetensors [2ec66ab0]
meinamix_meinaV11.safetensors [b56ce717]
neverendingDream_v122.safetensors [f964ceeb]
openjourney_V4.ckpt [ca2f377f]
pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]
portraitplus_V1.0.safetensors [1400e684]
protogenx34.safetensors [5896f8d5]
Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]
Realistic_Vision_V2.0.safetensors [79587710]
Realistic_Vision_V4.0.safetensors [29a7afaa]
Realistic_Vision_V5.0.safetensors [614d1063]
redshift_diffusion-V10.safetensors [1400e684]
revAnimated_v122.safetensors [3f4fefd9]
rundiffusionFX25D_v10.safetensors [cd12b0ee]
rundiffusionFX_v10.safetensors [cd4e694d]
sdv1_4.ckpt [7460a6fa]
v1-5-pruned-emaonly.safetensors [d7049739]
v1-5-inpainting.safetensors [21c7ab71]
shoninsBeautiful_v10.safetensors [25d8c546]
theallys-mix-ii-churned.safetensors [5d9225a4]
timeless-1.0.ckpt [7c4971d4]
toonyou_beta6.safetensors [980f6b15]

Parameters

Parameter	Default	Description
negative_prompt		Indicates what the AI should not do
model	absolutereality_V16.safetensors [37db0fc3]	Select from the list of models
cfg_scale	7	Min: 0, Max: 20
steps	25	Min: 1, Max: 30
sampler	DPM++ 2M Karras	Select from these: "Euler","Euler a","Heun","DPM++ 2M Karras","DPM++ SDE Karras","DDIM"

Usage Prodia Stable-Diffusion

// import { prodia } from "gpti";
const { prodia } = require("gpti");

let data_js = {
    prompt: "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    data: {
        prompt_negative: "",
        model: "absolutereality_v181.safetensors [3d9d4d2b]",
        sampling_method: "DPM++ 2M Karras",
        sampling_steps: 25,
        width: 512,
        height: 512,
        cfg_scale: 7
    }
};

prodia.stablediffusion(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { prodia } from "gpti/promise";
const { prodia } = require("gpti/promise");

try {
    let data = await prodia.stablediffusion(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    "model": "Prodia-StableDiffusion",
    "data": {
        "prompt_negative": "",
        "model": "absolutereality_v181.safetensors [3d9d4d2b]",
        "sampling_method": "DPM++ 2M Karras",
        "sampling_steps": 25,
        "width": 512,
        "height": 512,
        "cfg_scale": 7
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Models

List of models

absolutereality_v181.safetensors [3d9d4d2b]
3Guofeng3_v34.safetensors [50f420de]
absolutereality_V16.safetensors [37db0fc3]
amIReal_V41.safetensors [0a8a2e61]
analog-diffusion-1.0.ckpt [9ca13f02]
anythingv3_0-pruned.ckpt [2700c435]
anything-v4.5-pruned.ckpt [65745d25]
anythingV5_PrtRE.safetensors [893e49b9]
AOM3A3_orangemixs.safetensors [9600da17]
blazing_drive_v10g.safetensors [ca1c1eab]
cetusMix_Version35.safetensors [de2f2560]
childrensStories_v13D.safetensors [9dfaabcb]
childrensStories_v1SemiReal.safetensors [a1c56dbb]
childrensStories_v1ToonAnime.safetensors [2ec7b88b]
Counterfeit_v30.safetensors [9e2a8f19]
cuteyukimixAdorable_midchapter3.safetensors [04bdffe6]
cyberrealistic_v33.safetensors [82b0d085]
dalcefo_v4.safetensors [425952fe]
deliberate_v2.safetensors [10ec4b29]
deliberate_v3.safetensors [afd9d2d4]
dreamlike-anime-1.0.safetensors [4520e090]
dreamlike-diffusion-1.0.safetensors [5c9fd6e0]
dreamlike-photoreal-2.0.safetensors [fdcf65e7]
dreamshaper_6BakedVae.safetensors [114c8abb]
dreamshaper_7.safetensors [5cf5ae06]
dreamshaper_8.safetensors [9d40847d]
edgeOfRealism_eorV20.safetensors [3ed5de15]
EimisAnimeDiffusion_V1.ckpt [4f828a15]
elldreths-vivid-mix.safetensors [342d9d26]
epicrealism_naturalSinRC1VAE.safetensors [90a4c676]
ICantBelieveItsNotPhotography_seco.safetensors [4e7a3dfd]
juggernaut_aftermath.safetensors [5e20c455]
lofi_v4.safetensors [ccc204d6]
lyriel_v16.safetensors [68fceea2]
majicmixRealistic_v4.safetensors [29d0de58]
mechamix_v10.safetensors [ee685731]
meinamix_meinaV9.safetensors [2ec66ab0]
meinamix_meinaV11.safetensors [b56ce717]
neverendingDream_v122.safetensors [f964ceeb]
openjourney_V4.ckpt [ca2f377f]
pastelMixStylizedAnime_pruned_fp16.safetensors [793a26e8]
portraitplus_V1.0.safetensors [1400e684]
protogenx34.safetensors [5896f8d5]
Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]
Realistic_Vision_V2.0.safetensors [79587710]
Realistic_Vision_V4.0.safetensors [29a7afaa]
Realistic_Vision_V5.0.safetensors [614d1063]
redshift_diffusion-V10.safetensors [1400e684]
revAnimated_v122.safetensors [3f4fefd9]
rundiffusionFX25D_v10.safetensors [cd12b0ee]
rundiffusionFX_v10.safetensors [cd4e694d]
sdv1_4.ckpt [7460a6fa]
v1-5-pruned-emaonly.safetensors [d7049739]
v1-5-inpainting.safetensors [21c7ab71]
shoninsBeautiful_v10.safetensors [25d8c546]
theallys-mix-ii-churned.safetensors [5d9225a4]
timeless-1.0.ckpt [7c4971d4]
toonyou_beta6.safetensors [980f6b15]

Methods

List of methods:

DPM++ 2M Karras
Euler
Euler a
LMS
Heun
DPM2
DPM2 a
DPM++ 2S a
DPM++ 2M
DPM++ SDE
DPM fast
DPM adaptive
LMS Karras
DPM2 Karras
DPM2 a Karras
DPM++ 2S a Karras
DPM++ 2M Karras
DPM++ SDE Karras
DDIM
PLMS
DPM++ 2M Karras

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
model	absolutereality_v181.safetensors [3d9d4d2b]	Select from the list of models
sampling_method	DPM++ 2M Karras	Select from the list of methods
sampling_steps	25	Min: 1, Max: 30
width	512	Min: 50, Max: 1024
height	512	Min: 50, Max: 1024
cfg_scale	7	Min: 1, Max: 20

Usage Prodia Stable-Diffusion XL (PRO)

// import { prodia } from "gpti";
const { prodia } = require("gpti");

let data_js = {
    prompt: "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    data: {
        prompt_negative: "",
        model: "sd_xl_base_1.0.safetensors [be9edd61]",
        sampling_method: "DPM++ 2M Karras",
        sampling_steps: 25,
        width: 1024,
        height: 1024,
        cfg_scale: 7
    }
};

prodia.stablediffusion_xl(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { prodia } from "gpti/promise";
const { prodia } = require("gpti/promise");

try {
    let data = await prodia.stablediffusion_xl(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "Friends gathered around a bonfire in an ancient forest. Laughter, stories, and a starry sky paint an unforgettable moment of connection beneath the shadows of the mountains.",
    "model": "Prodia-StableDiffusion-xl",
    "data": {
        "prompt_negative": "",
        "model": "sd_xl_base_1.0.safetensors [be9edd61]",
        "sampling_method": "DPM++ 2M Karras",
        "sampling_steps": 25,
        "width": 1024,
        "height": 1024,
        "cfg_scale": 7
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Models

List of models:

dreamshaperXL10_alpha2.safetensors [c8afe2ef]
dynavisionXL_0411.safetensors [c39cc051]
juggernautXL_v45.safetensors [e75f5471]
realismEngineSDXL_v10.safetensors [af771c3f]
sd_xl_base_1.0.safetensors [be9edd61]
sd_xl_base_1.0_inpainting_0.1.safetensors [5679a81a]
turbovisionXL_v431.safetensors [78890989]

Methods

List of methods:

DPM++ 2M Karras
Euler
Euler a
LMS
Heun
DPM2
DPM2 a
DPM++ 2S a
DPM++ 2M
DPM++ SDE
DPM fast
DPM adaptive
LMS Karras
DPM2 Karras
DPM2 a Karras
DPM++ 2S a Karras
DPM++ SDE Karras

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
model	sd_xl_base_1.0.safetensors [be9edd61]	Select from the list of models
sampling_method	DPM++ 2M Karras	Select from the list of methods
sampling_steps	25	Min: 1, Max: 30
width	1024	Min: 512, Max: 1536
height	1024	Min: 512, Max: 1536
cfg_scale	7	Min: 1, Max: 20

Usage Pixart-A (PRO)

// import { pixart } from "gpti";
const { pixart } = require("gpti");

let data_js = {
    prompt: "An urban landscape bathed in the sunset, where the warm tones of the sun reflect on modern buildings and the orange and purple sky. In the foreground, there's a group of friends gathered on a rooftop, laughing and enjoying the moment. Their expressions radiate joy and camaraderie as they embrace and point towards something on the horizon. The scene is enveloped in a nostalgic and emotional aura that conveys the beauty of friendship and the warmth of the sunset in a futuristic city with touches of anime style.",
    data: {
        prompt_negative: "",
        sampler: "DPM-Solver",
        image_style: "Anime",
        width: 1024,
        height: 1024,
        dpm_guidance_scale: 4.5,
        dpm_inference_steps: 14,
        sa_guidance_scale: 3,
        sa_inference_steps: 25
    }
};

pixart.a(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { pixart } from "gpti/promise";
const { pixart } = require("gpti/promise");

try {
    let data = await pixart.a(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An urban landscape bathed in the sunset, where the warm tones of the sun reflect on modern buildings and the orange and purple sky. In the foreground, there's a group of friends gathered on a rooftop, laughing and enjoying the moment. Their expressions radiate joy and camaraderie as they embrace and point towards something on the horizon. The scene is enveloped in a nostalgic and emotional aura that conveys the beauty of friendship and the warmth of the sunset in a futuristic city with touches of anime style.",
    "model": "PixArt-a",
    "data": {
        "prompt_negative": "",
        "sampler": "DPM-Solver",
        "image_style": "Anime",
        "width": 1024,
        "height": 1024,
        "dpm_guidance_scale": 4.5,
        "dpm_inference_steps": 14,
        "sa_guidance_scale": 3,
        "sa_inference_steps": 25
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
sampler	DPM-Solver	Choose among these: "DPM-Solver", "SA-Solver"
image_style	(No style)	Choose from various available image types: "(No style)", "Cinematic", "Photographic", "Anime", "Manga", "Digital Art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model"
width	1024	Min: 256, Max: 2048
height	1024	Min: 256, Max: 2048
dpm_guidance_scale	4.5	Min: 1, Max: 10
dpm_inference_steps	14	Min: 5, Max: 40
sa_guidance_scale	3	Min: 1, Max: 10
sa_inference_steps	25	Min: 10, Max: 40

Usage Pixart-LCM (PRO)

// import { pixart } from "gpti";
const { pixart } = require("gpti");

let data_js = {
    prompt: "An enchanted forest with twisted trees, a waterfall cascading into a pond of bright water lilies, and in the background, a magical tower surrounded by mythical creatures like unicorns, fairies, and dragons, under a starry sky and a giant moon.",
    data: {
        prompt_negative: "",
        image_style: "Fantasy art",
        width: 1024,
        height: 1024,
        lcm_inference_steps: 9
    }
};

pixart.lcm(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { pixart } from "gpti/promise";
const { pixart } = require("gpti/promise");

try {
    let data = await pixart.lcm(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An enchanted forest with twisted trees, a waterfall cascading into a pond of bright water lilies, and in the background, a magical tower surrounded by mythical creatures like unicorns, fairies, and dragons, under a starry sky and a giant moon.",
    "model": "PixArt-LCM",
    "data": {
        "prompt_negative": "",
        "image_style": "Fantasy art",
        "width": 1024,
        "height": 1024,
        "lcm_inference_steps": 9
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
image_style	(No style)	Choose from various available image types: "(No style)", "Cinematic", "Photographic", "Anime", "Manga", "Digital Art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model"
width	1024	Min: 256, Max: 2048
height	1024	Min: 256, Max: 2048
lcm_inference_steps	9	Min: 1, Max: 30

Usage Stable-Diffusion 1.5

// import { stablediffusion } from "gpti";
const { stablediffusion } = require("gpti");

let data_js = {
    prompt: "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun."
};

stablediffusion.v1(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { stablediffusion } from "gpti/promise";
const { stablediffusion } = require("gpti/promise");

try {
    let data = await stablediffusion.v1(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun.",
    "model": "StableDiffusion-1.5",
    "images": [
        "data:image/jpeg;base64,...",
        "..."
    ]
}

Usage Stable-Diffusion 2.1

// import { stablediffusion } from "gpti";
const { stablediffusion } = require("gpti");

let data_js = {
    prompt: "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun.",
    data: {
        prompt_negative: "",
        guidance_scale: 9
    }
};

stablediffusion.v2(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { stablediffusion } from "gpti/promise";
const { stablediffusion } = require("gpti/promise");

try {
    let data = await stablediffusion.v2(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun.",
    "model": "StableDiffusion-2.1",
    "data": {
        "prompt_negative": "",
        "guidance_scale": 9
    },
    "images": [
        "data:image/jpeg;base64,...",
        "..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
guidance_scale	9	Min: 0 Max: 50

Usage Stable-Diffusion XL (PRO)

// import { stablediffusion } from "gpti";
const { stablediffusion } = require("gpti");

let data_js = {
    prompt: "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun.",
    data: {
        prompt_negative: "",
        image_style: "(No style)",
        guidance_scale: 7.5
    }
};

stablediffusion.xl(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { stablediffusion } from "gpti/promise";
const { stablediffusion } = require("gpti/promise");

try {
    let data = await stablediffusion.xl(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An serene sunset landscape where a river winds through gentle hills covered in trees. The sky is tinged with warm and soft tones, with scattered clouds reflecting the last glimmers of the sun.",
    "model": "StableDiffusion-XL",
    "data": {
        "prompt_negative": "",
        "image_style": "(No style)",
        "guidance_scale": 7.5
    },
    "images": [
        "data:image/jpeg;base64,...",
        "..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
image_style	(No style)	Choose from various available image types: "(No style)", "Cinematic", "Photographic", "Anime", "Manga", "Digital Art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model"
guidance_scale	7.5	Min: 0, Max: 50

Usage EMI

// import { emi } from "gpti";
const { emi } = require("gpti");

let data_js = {
    prompt: "A beautiful girl in a garden full of bright flowers. Her long, silky hair is adorned with flowers, and her large eyes reflect serenity. She wears a traditional kimono, smiling as she holds a delicate butterfly in her hand.",
};

emi(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { emi } from "gpti/promise";
const { emi } = require("gpti/promise");

try {
    let data = await emi(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "A beautiful girl in a garden full of bright flowers. Her long, silky hair is adorned with flowers, and her large eyes reflect serenity. She wears a traditional kimono, smiling as she holds a delicate butterfly in her hand.",
    "model": "Emi",
    "scene": "a young woman stands in a beautiful garden, full of vibrant flowers. Her long, flowing silk kimono is adorned with the same flowers, and her large, expressive eyes seem to reflect a sense of peaceful serenity. In her hand, she clutches a delicate butterfly, which seems to be caught up in the beauty of the moment. She is surrounded",
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Usage Render3D (PRO)

// import { render3d } from "gpti";
const { render3d } = require("gpti");

let data_js = {
    prompt: "In a remote corner of the galaxy, a star agonizes in its final stage of life. Its brightness, once dazzling, now fades slowly into the void of space, while a bright nebula forms around it.",
    data: {
        prompt_negative: ""
    }
};

render3d(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { render3d } from "gpti/promise";
const { render3d } = require("gpti/promise");

try {
    let data = await render3d(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "In a remote corner of the galaxy, a star agonizes in its final stage of life. Its brightness, once dazzling, now fades slowly into the void of space, while a bright nebula forms around it.",
    "model": "Render3D",
    "data": {
        "prompt_negative": ""
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Usage PixelArt

// import { pixelart } from "gpti";
const { pixelart } = require("gpti");

let data_js = {
    prompt: "A coastal city in the golden hour of the sunset. The sun slowly slips toward the horizon, tinting the sky with golden and pink hues. Skyscrapers stand out against this heavenly backdrop, reflecting the light in their glass windows. In the streets, lights flicker timidly, getting ready to illuminate the night.",
    data: {
        prompt_negative: ""
    }
};

pixelart(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { pixelart } from "gpti/promise";
const { pixelart } = require("gpti/promise");

try {
    let data = await pixelart(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "A coastal city in the golden hour of the sunset. The sun slowly slips toward the horizon, tinting the sky with golden and pink hues. Skyscrapers stand out against this heavenly backdrop, reflecting the light in their glass windows. In the streets, lights flicker timidly, getting ready to illuminate the night.",
    "model": "PixelArt",
    "data": {
        "prompt_negative": ""
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Animagine XL (PRO)

// import { animagine } from "gpti";
const { animagine } = require("gpti");

let data_js = {
    prompt: "An anime girl surrounded by cherry blossoms",
    data: {
        prompt_negative: "",
        quality_tags: "Standard",
        style_present: "(None)",
        width: 1024,
        height: 1024,
        strength: 0.5,
        upscale: 1.5,
        sampler: "Euler a",
        guidance_scale: 7,
        inference_steps: 28
    }
};

animagine(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { animagine } from "gpti/promise";
const { animagine } = require("gpti/promise");

try {
    let data = await animagine(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An anime girl surrounded by cherry blossoms",
    "model": "Animagine-XL",
    "data": {
        "prompt_negative": "",
        "quality_tags": "Standard",
        "style_present": "(None)",
        "width": 1024,
        "height": 1024,
        "strength": 0.5,
        "upscale": 1.5,
        "sampler": "Euler a",
        "guidance_scale": 7,
        "inference_steps": 28
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
width	1024	Min: 512, Max: 2048
height	1024	Min: 512, Max: 2048
guidance_scale	7	Min: 1, Max: 12
quality_tags	Standard	Select from these: "Standard", "Light", "Heavy", "(None)"
style_present	(None)	Choose from various available image types: "(None)", "Cinematic", "Photographic", "Anime", "Manga", "Digital Art", "Pixel art", "Fantasy art", "Neonpunk", "3D Model"
strength	0.5	Min: 0, Max: 1
upscale	1.5	Min: 1, Max: 1.5
sampler	Euler a	Select from these: "Euler a", "DPM++ 2M Karras", "DPM++ SDE Karras", "DPM++ 2M SDE Karras", "Euler", "DDIM"
inference_steps	28	Min: 1, Max: 50

Playground (PRO)

// import { playground } from "gpti";
const { playground } = require("gpti");

let data_js = {
    prompt: "An illustration of a red owl with bright blue eye",
    data: {
        prompt_negative: "",
        width: 1024,
        height: 1024,
        guidance_scale: 3
    }
};

playground(data_js, (err, data) => {
    if(err != null){
        console.log(err);
    } else {
        console.log(data);
    }
});

/*
import { playground } from "gpti/promise";
const { playground } = require("gpti/promise");

try {
    let data = await playground(data_js);

    console.log(data);
} catch(err){
    console.log(err);
}
*/

JSON

{
    "code": 200,
    "status": true,
    "prompt": "An illustration of a red owl with bright blue eyes.",
    "model": "Playground",
    "data": {
        "prompt_negative": "",
        "width": 1024,
        "height": 1024,
        "guidance_scale": 3
    },
    "images": [
        "data:image/jpeg;base64,..."
    ]
}

Parameters

Parameter	Default	Description
prompt_negative		Indicates what the AI should not do
width	1024	Min: 256, Max: 1536
height	1024	Min: 256, Max: 1536
guidance_scale	3	Min: 0.1, Max: 20

API Reference

Currently, some models require your credentials to access them, while others are free. For more details and examples, please refer to the complete documentation.

Code Errors

These are the error codes that will be presented in case the API fails.

Code	Error	Description
400	BAD_REQUEST	Not all parameters have been entered correctly
500	INTERNAL_SERVER_ERROR	The server has experienced failures
200		The API worked without issues
403	FORBIDDEN	The API credentials are not valid
401	UNAUTHORIZED	API credentials are required

☕ Do you want to support this project?

If this package has helped you save time or solve a problem, consider inviting me for a coffee through Ko-fi. Your support helps me maintain and improve this project for you and other users like you. Furthermore, each donation contributes to the creation and free availability of more AI models in the future. Every small donation counts and is greatly appreciated!

Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
.github		.github
LICENSE		LICENSE
README.md		README.md
index.js		index.js
main.js		main.js
main.ts		main.ts
package-lock.json		package-lock.json
package.json		package.json
promise.js		promise.js
promise.ts		promise.ts
tsconfig.json		tsconfig.json

License

yandricr/gpti-js

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GPTI

Installation

Available Models

Api key

Usage GPT

JSON

Models

Usage GPT v2

JSON

JSON Streaming

Usage GPT Web

JSON

Usage Bing

JSON

JSON Streaming

Parameters

Usage LLaMA-2

JSON

JSON Streaming

Parameters

Usage DALL·E

JSON

Usage DALL·E 2 (PRO)

JSON

Parameters

Usage DALL·E Mini

JSON

Usage Prodia

JSON

Models

Parameters

Usage Prodia Stable-Diffusion

JSON

Models

Methods

Parameters

Usage Prodia Stable-Diffusion XL (PRO)

JSON

Models

Methods

Parameters

Usage Pixart-A (PRO)

JSON

Parameters

Usage Pixart-LCM (PRO)

JSON

Parameters

Usage Stable-Diffusion 1.5

JSON

Usage Stable-Diffusion 2.1

JSON

Parameters

Usage Stable-Diffusion XL (PRO)

JSON

Parameters

Usage EMI

JSON

Usage Render3D (PRO)

JSON

Usage PixelArt

JSON

Animagine XL (PRO)

JSON

Parameters

Playground (PRO)

JSON

Parameters

API Reference

Code Errors

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