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openai_embedding

v1.0.13

Published

package to help inputting and storing long reference text, and extract information when asking prompt

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8

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hamlet78hamlet78

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Readme

openai_embedding

package to help inputting and storing long reference text, and extract information when asking prompt

Example usage:

//this will return all vector map in {text:{embedding:num[],tokensNum:num}}

let embedMap=await computeDocEmbeddings(["hello, hows it going","come on!","long long long text long long long text long long long text long long long text" + " long long long text long long long text long long long text long long long text"+ " long long long text long long long text long long long text long long long text"+ " long long long text long long long text long long long text long long long text"+ " long long long text long long long text long long long text long long long text"+ " long long long text long long long text long long long text long long long text"]);

//pass the vector map and question text, then //this will return related context in string[]

await constructPrompt("How long is the text?",embedMap);

//this will return an array of text, separated in to coherent sections

intoParagraphs({raw:"some paragraphs text", maxtoken=400});