Promptd

Promptd is a set of tools to help you manage AI prompts. Below are instructions on how to use it as part of your application.

🔨 Installation

The Javascript client is available from NPM (opens in a new tab):

yarn add @promptd-js/client      # yarn
npm install @promptd-js/client   # npm

📖 Quick start

Fetch template

For this example, we're going to fetch an existing prompt template defined in the Promptd dashboard, whose slug (our way of uniquely identifying a prompt) is say-hello-to-user.

First we need to instantiated a Promptd object, and fetch the prompt template by its slug:

const promptd = new Promptd({ apiKey: promptdApiKey });
const template = promptd.template(promptSlug);

Render prompt

What we get is a Mustache template (opens in a new tab), which we can turn into text by feeding the necessary template variables into the render() method. The template might look like Say hello to {{ name }} in a cheerful way..

const prompt = await template.render({ name });

The raw prompt rendered can be accessed with the text() method:

const raw_prompt = await prompt.text();

Generate response

At this point, we can then ask our LLM of choice to generate a response based on the full prompt. In this example, we're using llm-api (opens in a new tab) to abstract away all the underlying LLM, but promptd does not impose anything for that side of things.

Under the hood, we use zod-gpt (opens in a new tab) to enforce fully validated and typed responses from LLM.

import { OpenAIChatApi } from 'llm-api';
 
const ai = new OpenAIChatApi({ apiKey: openAiKey }, { model: 'gpt-4-turbo' });
const result = await prompt.generate(
  {
    schema: z.object({
      message: z.string().describe('The message to be sent to user.'),
    }),
  },
  ai,
);
return result.data.message;

To get unstructured response, simply leave the schema empty:

const ai = new OpenAIChatApi({ apiKey: openAiKey }, { model: 'gpt-4-turbo' });
const result = await prompt.generate({}, ai);
return result.data;

You may also specify the default LLM model to use for this prompt when fetching the template:

const template = promptd.template(promptSlug, { ai });
const prompt = await template.render({ name });
const result = await prompt.generate({});

Full listing

import { z } from 'zod';
import { Promptd } from '@promptd-js/client';
import { OpenAIChatApi } from 'llm-api';
 
const promptdApiKey = 'xxx'; // Grab this in your Promptd project settings page.
const promptSlug = 'say-hello-to-user'; // Find this on the prompt page in the Promptd dashboard.
 
const promptd = new Promptd({ apiKey: promptdApiKey });
const template = promptd.template(promptSlug); // `template` is a Mustache template
 
// We're using Open AI's GPT4 model in this example, but we're LLM-agnostic:
const openAiKey = 'yyy'; // Grab this in your Open AI account.
const ai = new OpenAIChatApi({ apiKey: openAiKey },{ model: 'gpt-4-turbo' });
 
export const sayHello = async(name: string) => {
  // For example, the prompt body might be: "Say hello to {{ name }} in a cheerful way."
  const prompt = await template.render({ name });
  // If we called sayHello('Alice'), prompt would be "Say hello to Alice in a cheerful way."
  const result = await prompt.generate({
    schema: z.object({
        message: z.string().describe("The message to be sent to user."),
    }),
  }, ai);
  // The result might now contain something akin to "Hello, Alice, what a pleasure to meet you!"
  return result.data.message;
};

Prompt