Class Client

constructor constructs a Client API for use.

Chat generates chat completions based on a conversation history.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Chat() {
    const input = {
        model: 'Neural-Chat-7B',
        messages: [
            {
                role: pg.Roles.User,
                content: 'How do you feel about the world in general',
            },
        ],
        maxTokens: 1000,
        temperature: 0.1,
        topP: 0.1,
        topK: 50,
        options: {
            factuality: true,
            toxicity: true,
            pii: pg.PIIs.Replace,
            piiReplaceMethod: pg.ReplaceMethods.Random,
        },
    };

    var [result, err] = await client.Chat(input);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.createdDate() + ': ' + result.model + ': ' + result.choices[0].message.content);
}

Chat();
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ChatSSE generates a stream of chat completions based on a conversation history.

Example

import * as pg from 'predictiongaurd';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function ChatSSE() {
    const input = {
        model: 'Neural-Chat-7B',
        messages: [
            {
                role: pg.Roles.User,
                content: 'How do you feel about the world in general',
            },
        ],
        maxTokens: 1000,
        temperature: 0.1,
        topP: 0.1,
        topK: 50,
        onMessage: function (event, err) {
            if (err != null) {
                if (err.error == 'EOF') {
                    return;
                }
                console.log(err);
            }

            for (const choice of event.choices) {
                if (choice.delta.hasOwnProperty('content')) {
                    process.stdout.write(choice.delta.content);
                }
            }
        },
    };

    var err = await client.ChatSSE(input);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }
}

ChatSSE();
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ChatVision generates answers a question about an image.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function ChatVision() {
    const image = new pg.ImageNetwork('https://pbs.twimg.com/profile_images/1571574401107169282/ylAgz_f5_400x400.jpg');

    const input = {
        role: pg.Roles.User,
        question: 'is there a deer in this picture',
        image: image,
        maxTokens: 1000,
        temperature: 0.1,
        topP: 0.1,
        topK: 50,
    };

    var [result, err] = await client.ChatVision(input);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.createdDate() + ': ' + result.model + ': ' + result.choices[0].message.content);
}

ChatVision();
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Completion generates text completions based on the provided input.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Completions() {
    const input = {
        model: 'Neural-Chat-7B',
        prompt: 'Will I lose my hair',
        maxTokens: 1000,
        temperature: 0.1,
        topP: 0.1,
        topK: 50,
    };

    var [result, err] = await client.Completion(input);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.choices[0].text);
}

Completions();
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Embedding generates chat completions based on a conversation history.

Example

import * as pg from 'predictiongaurd';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Embedding() {
    const image = new pg.ImageNetwork('https://pbs.twimg.com/profile_images/1571574401107169282/ylAgz_f5_400x400.jpg');

    const input = [
        {
            text: 'This is Bill Kennedy, a decent Go developer.',
            image: image,
        },
    ];

    var [result, err] = await client.Embedding('bridgetower-large-itm-mlm-itc', input);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    for (const dt of result.data) {
        process.stdout.write(dt.embedding.toString());
    }
}

Embedding();
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Factuality checks the factuality of a given text compared to a reference.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Factuality() {
    const fact = `The President shall receive in full for his services during
    the term for which he shall have been elected compensation in the aggregate
    amount of 400,000 a year, to be paid monthly, and in addition an expense
    allowance of 50,000 to assist in defraying expenses relating to or resulting
    from the discharge of his official duties. Any unused amount of such expense
    allowance shall revert to the Treasury pursuant to section 1552 of title 31,
    United States Code. No amount of such expense allowance shall be included in
    the gross income of the President. He shall be entitled also to the use of
    the furniture and other effects belonging to the United States and kept in
    the Executive Residence at the White House.`;

    const text = `The president of the united states can take a salary of one
    million dollars`;

    var [result, err] = await client.Factuality(fact, text);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + JSON.stringify(result.checks[0]));
}

Factuality();
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HealthCheck validates the PG API Service is available.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function HealthCheck() {
    var [result, err] = await client.HealthCheck();
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log(result);
}

HealthCheck();
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Injection detects potential prompt injection attacks in a given prompt.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Injection() {
    const prompt = `A short poem may be a stylistic choice or it may be that you
    have said what you intended to say in a more concise way.`;

    var [result, err] = await client.Injection(prompt);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.checks[0].probability);
}

Injection();
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ReplacePII replaces personal information such as names, SSNs, and emails in a given text.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function ReplacePII() {
    const replaceMethod = pg.ReplaceMethods.Mask;
    const prompt = `My email is bill@ardanlabs.com and my number is 954-123-4567.`;

    var [result, err] = await client.ReplacePII(replaceMethod, prompt);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.checks[0].new_prompt);
}

ReplacePII();
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Toxicity checks the toxicity of a given text.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Toxicity() {
    const text = `Every flight I have is late and I am very angry. I want to
    hurt someone.`;

    var [result, err] = await client.Toxicity(text);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.checks[0].score);
}

Toxicity();
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Translate converts text from one language to another.

Example

import * as pg from 'predictionguard';

const client = new pg.Client('https://api.predictionguard.com', process.env.PGKEY);

async function Translate() {
    const text = `The rain in Spain stays mainly in the plain`;
    const sourceLang = pg.Languages.English;
    const targetLang = pg.Languages.Spanish;
    const useThirdPartyEngine = false;

    var [result, err] = await client.Translate(text, sourceLang, targetLang, useThirdPartyEngine);
    if (err != null) {
        console.log('ERROR:' + err.error);
        return;
    }

    console.log('RESULT:' + result.best_translation);
}

Translate();
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