@inductiv/node-red-openai-api/src/embeddings/help.html

Enhance your Node-RED projects with advanced AI capabilities.

<section>
    <details>
        <summary style="font-weight: bold;">🔗 Embeddings</summary>
        <a href="https://developers.openai.com/api/reference/typescript/resources/embeddings/" target="_blank">Official Documentation
            <i class="fa fa-external-link fa-sm" aria-hidden="true"></i></a>
        <h4 style="font-weight: bolder;"> ⋙ Create Embeddings</h4>
        <p>Creates an embedding vector representing the input text.</p>
        <dl class="message-properties">
            <h4>msg.payload Properties</h4>

            <dt>
                input
                <span class="property-type">string | array</span>
            </dt>
            <dd>Input text to embed, encoded as a string or array of tokens.</dd>
            <dt>
                model
                <span class="property-type">string</span>
            </dt>
            <dd>ID of the model to use.</dd>
            <dt class="optional">
                encoding_format
                <span class="property-type">string</span>
            </dt>
            <dd>
                The format to return the embeddings in. Can be either float or base64.
            </dd>
            <dt class="optional">
                dimensions
                <span class="property-type">integer</span>
            </dt>
            <dd>
                The number of dimensions the resulting output embeddings should have.
                Only supported in text-embedding-3 and later models.
            </dd>
            <dt class="optional">
                user
                <span class="property-type">string</span>
            </dt>
            <dd>
                A unique identifier representing your end-user, which can help OpenAI to
                monitor and detect abuse.
            </dd>
        </dl>

    </details>
</section>