node-red-contrib-openai-ubos

A Node-RED node that interacts with OpenAI machine learning models to generate text like ChatGPT.

Quick Start

Install with the built in Node-RED Palette manager or using npm:

npm install node-red-contrib-openai-ubos

Setup

When editing the nodes properties, to get your OPENAI_API_KEY log in to ChatGPT and then visit https://platform.openai.com/account/api-keys click "+ Create new secret key" then copy and paste the "API key" into the nodes API_KEY property value.

To get your Organization visit https://platform.openai.com/account/org-settings then copy and paste the "OrganizationID" into the nodes Organization property value.

Properties

• msg.OPENAI_API_KEY: This is the API key provided by OpenAI. It is necessary for authentication when making requests to the OpenAI API.

• msg.prompt: This string forms the initial text from which the model will generate its continuation.

• msg.model: This property defines the name of the OpenAI model to be used for generating the text, for example, "text-davinci-003".

• msg.temperature: This property controls the randomness in the output of the model. Higher values result in more random outputs. This is a numerical value.

• msg.max_tokens: This property sets the maximum length of the model output. This is a numerical value.

• msg.messages: This is an array meant to hold any messages that are to be passed along the Node-RED flow. Each object in the array can contain additional properties like role and content. For example:

  "messages": [
      {"role": "system", "content": "Set the behavior"},
      {"role": "assistant", "content": "Provide examples"},
      {"role": "user", "content": "Set the instructions"}
  ]

• msg.top_p: This property is used when nucleus sampling is preferred for generating the text. The value for this property is expected to be a number between 0 and 1.

• msg.frequency_penalty: This property allows for penalization of new tokens based on their frequency. The value should be a number between 0 and 1.

• msg.stop: Up to 4 sequences where the API will stop generating further tokens. For example:

  msg.stop = ["word-1", "word-2"]

• msg.presence_penalty: This property can be used to control the model's preference for introducing new concepts during text generation. Like msg.frequency_penalty, it should be a number between 0 and 1.

Demo

Bugs reports and feature requests

Please report any issues or feature requests at GitHub.

License

MIT License