IntelliNode

Access the latest AI models like ChatGPT, LLaMA, Diffusion, Gemini Hugging face, and beyond through a unified prompt layer and performance evaluation

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IntelliNode is a javascript module that integrates cutting-edge AI models like ChatGPT, LLaMA, WaveNet, Gemini, and Stable diffusion into projects. It offers functions for generating text, speech, and images, as well as semantic search, multi-model evaluation, and chatbot capabilities. The module provides a wrapper layer for low-level model access, a controller layer for unified input handling, and a function layer for abstract functionality tailored to various use cases.

README:

Unified prompt, evaluation, and production integration to any large model

Intelligent Node

IntelliNode is a javascript module that integrates cutting-edge AI into your project. With its intuitive functions, you can easily feed data to models like ChatGPT, LLaMA, WaveNet, Gemini and Stable diffusion and receive generated text, speech, or images. It also offers high-level functions such as semantic search, multi-model evaluation, and chatbot capabilities.

Access the module

Install

One command and get access to latest models:

npm i intellinode

For detailed usage instructions, refer to the documentation.

Examples

Gen

The Gen function quickly generates tailored content in one line.

import:

const { Gen } = require('intellinode');

call:

// one line to generate html page code (openai gpt4 is default)
text = 'a registration page with flat modern theme.'
await Gen.save_html_page(text, folder, file_name, openaiKey);

// or generate blog post (using cohere)
const blogPost = await Gen.get_blog_post(prompt, apiKey, provider='cohere');

Chatbot

import:

const { Chatbot, ChatGPTInput } = require('intellinode');

call:

// set chatGPT system mode and the user message.
const input = new ChatGPTInput('You are a helpful assistant.');
input.addUserMessage('What is the distance between the Earth and the Moon?');

// get chatGPT responses.
const chatbot = new Chatbot(OPENAI_API_KEY, 'openai');
const responses = await chatbot.chat(input);

Gemini Chatbot

IntelliNode enable effortless swapping between AI models.

imports:

const { Chatbot, GeminiInput, SupportedChatModels } = require('intellinode');

call:

const input = new GeminiInput();
input.addUserMessage('Who painted the Mona Lisa?');

const geminiBot = new Chatbot(apiKey, SupportedChatModels.GEMINI);
const responses = await geminiBot.chat(input);

The documentation to switch the chatbot provider between ChatGPT, LLama, Cohere, Mistral and more can be found in the IntelliNode Wiki.

Semantic search

import:

const { SemanticSearch } = require('intellinode');

call:

const search = new SemanticSearch(apiKey);
// pivotItem is the item to search.
const results = await search.getTopMatches(pivotItem, searchArray, numberOfMatches);
const filteredArray = search.filterTopMatches(results, searchArray)

Prompt engineering

Generate improved prompts using LLMs:

const promptTemp = await Prompt.fromChatGPT("fantasy image with ninja jumping across buildings", openaiApiKey);
console.log(promptTemp.getInput());

Language models

import:

const { RemoteLanguageModel, LanguageModelInput } = require('intellinode');

call openai model:

const langModel = new RemoteLanguageModel('openai-key', 'openai');
model_name = 'gpt-3.5-turbo-instruct'

const results = await langModel.generateText(new LanguageModelInput({
  prompt: 'Write a product description for smart plug that works with voice assistant.',
  model: model_name,
  temperature: 0.7
}));

console.log('Generated text:', results[0]);

change to call cohere models:

const langModel = new RemoteLanguageModel('cohere-key', 'cohere');
model_name = 'command-xlarge-20221108'
// ... same code

Image models

import:

const { RemoteImageModel, SupportedImageModels, ImageModelInput } = require('intellinode');

call DALL·E:

provider=SupportedImageModels.OPENAI;

const imgModel = new RemoteImageModel(apiKey, provider);
const images = await imgModel.generateImages(new ImageModelInput({
    prompt: 'teddy writing a blog in times square',
    numberOfImages: 1
}));

change to call Stable Diffusion:

provider=SupportedImageModels.STABILITY;
// ... same code

Openai advanced access

To access Openai services from your Azure account, you have to call the following function at the beginning of your application:

const { ProxyHelper } = require('intellinode');
ProxyHelper.getInstance().setAzureOpenai(resourceName);

To access Openai from a proxy for restricted regions:

ProxyHelper.getInstance().setOpenaiProxyValues(openaiProxyJson);

For more details and in-depth code, check the samples.

The code repository setup

First setup

Initiate the project:

cd IntelliNode
npm install

Create a .env file with the access keys:

OPENAI_API_KEY=<key_value>
COHERE_API_KEY=<key_value>
GOOGLE_API_KEY=<key_value>
STABILITY_API_KEY=<key_value>
HUGGING_API_KEY=<key_value>

Test cases

run the remote language models test cases: node test/integration/RemoteLanguageModel.test.js
run the remote image models test cases: node test/integration/RemoteImageModel.test.js
run the remote speech models test cases: node test/integration/RemoteSpeechModel.test.js
run the embedding test cases: node test/integration/RemoteEmbedModel.test.js
run the chatBot test cases: node test/integration/Chatbot.test.js

📕 Documentation

IntelliNode Wiki: Check the wiki page for indepeth instructions and practical use cases.
Showcase: Experience the potential of Intellinode in action, and use your keys to generate content and html pages.
Samples: Explore a code sample with detailed setup documentation to get started with Intellinode.
Model Evaluation: Demonstrate a swift approach to compare the performance of multiple models against designated target answers.
Semantic Search: In-memory semantic search with iterator over large data.

Pillars

The module foundation:

The wrapper layer provides low-level access to the latest AI models
The controller layer offers a unified input to any AI model by handling the differences. So you can switch between models like Openai and Cohere without changing the code.
The function layer provides abstract functionality that extends based on the app's use cases. For example, an easy-to-use chatbot or marketing content generation utilities.

Roadmap

Call for contributors: registration form .

[x] Add support to OpenAI completion & GPT4.
[x] Add support to OpenAI DALL·E 2.
[ ] Add support to other OpenAI functions.
[x] Add support to cohere generate models.
[ ] Add support to Google language models.
[x] Add support to Google speech models.
[x] Add support to LLaMa AWS private deployment.
[ ] Add support to Anthropic claude.
[ ] Add support to Midjourney image generation.
[x] Add support to Stable diffusion.
[x] Add support to hugging face inference.
[x] Add more high-level functions like semantic search, evaluation, etc.

License

Apache License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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