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Quick Start

This guide walks you through the basic workflow: setting your API key, creating a client, fetching a prompt, and using it with the Vercel AI SDK. By the end, your prompts will be managed in the Promptly CMS - not hardcoded in your codebase.

  1. Set your API key

    Add your Promptly API key to your environment. Create a .env file in your project root:

    .env
    PROMPTLY_API_KEY=pk_live_...

  2. Create a client

    src/index.ts
    import { createPromptlyClient } from '@promptlycms/prompts';
    

    const promptly = createPromptlyClient();

    You can omit apiKey if PROMPTLY_API_KEY is set in your environment - the SDK picks it up automatically.

  3. Fetch a prompt

    src/index.ts
    const result = await promptly.getPrompt('JPxlUpstuhXB5OwOtKPpj');
    

    // Prompt content - exactly what you wrote in the editor
    result.systemMessage; // 'You are a helpful assistant.'
    result.promptName;    // 'Code Review Helper'
    

    // Model config - from the sidebar settings in the editor
    result.model;         // LanguageModel (auto-resolved)
    result.temperature;   // 0.7
    

    // Template variables - interpolate ${variables} from your user message
    const message = result.userMessage({
      name: 'Alice',
      task: 'code review',
    });

  4. Use with the Vercel AI SDK

    Destructure getPrompt() and pass the properties directly to generateText() or streamText():

    src/index.ts
    import { generateText } from 'ai';
    

    const { userMessage, systemMessage, temperature, model } = await promptly.getPrompt('JPxlUpstuhXB5OwOtKPpj');
    

    const { text } = await generateText({
      model,
      system: systemMessage,
      prompt: userMessage({ name: 'Alice', task: 'code review' }),
      temperature,
    });

Complete example

Section titled “Complete example”
src/index.ts
import { createPromptlyClient } from '@promptlycms/prompts';
import { generateText } from 'ai';


const { getPrompt } = createPromptlyClient();


const { userMessage, systemMessage, temperature, model } = await getPrompt(
  'JPxlUpstuhXB5OwOtKPpj',
);


const { text } = await generateText({
  model,
  system: systemMessage,
  prompt: userMessage({ name: 'Alice', task: 'code review' }),
  temperature,
});


console.log(text);

Next steps

Section titled “Next steps”