Questions and Answers

3 min read • September 2023 (October 17, 2026)

Table of contents

  1. Do you validate a user’s text/image prompts to ensure they are passing AI services’ safety requirements?
  2. How POST raw content to runwayml/assets and minimax/files using Make.com and similar nocode tools?

Do you validate a user’s text/image prompts to ensure they are passing AI services’ safety requirements?

It is common practice for AI services to ban users for violating prompt guidelines. Our API does not perform any prompt pre-validations — it will return an error status code when the underlying AI service moderates the job.

Generally speaking, if you’re planning to use the API for a public Telegram bot (which is one of the popular use cases) or in similar scenarios where you do not control the quality of the prompt, it might be a good idea to use a combination of a ban/stop word list along with OpenAI ChatGPT or Google Gemini to check if the prompts meet safety requirements. Gemini offers a free tier with some RPM (requests per minute) limitations.

We also offer LLM models, specifically MiniMax-Text-01, a fast instructional multimodal model that is free to use and can validate both text and images for safety. Please see POST minimax/llm.

How POST raw content to runwayml/assets and minimax/files using Make.com and similar nocode tools?

We recommend using module called 0codekit to run JavaScript and return a result.

0codekit JavaScript example 
async function fetchFromURLandPOST(imageURL, name) {
  const apiToken = "<Your useapi.net API key>"; // https://useapi.net/docs/start-here/setup-useapi
  // Runway https://useapi.net/docs/api-runwayml-v1/post-runwayml-assets
  const apiUrl = `https://api.useapi.net/v1/runwayml/assets/?name=${name}`;
  // MiniMax https://useapi.net/docs/api-minimax-v1/post-minimax-files
  // const apiUrl = `https://api.useapi.net/v1/minimax/files/`;

  try {
    // Fetch the image from the URL
    const responseImage = await fetch(imageURL);

    if (!responseImage.ok) 
      throw new Error(`Failed to fetch ${imageURL}: ${responseImage.statusText}`);

    // Convert the response to a Blob
    const blob = await responseImage.blob();

    // Prepare headers for the POST request
    const headers = {
      "Authorization": `Bearer ${apiToken}`, 
      "Content-Type": blob.type,
    };

    // Make the POST request with the blob as the body
    const response = await fetch(apiUrl, {
      method: "POST",
      headers: headers,
      body: blob,
    });

    const result = await response.json();
    return { data: result };
  } catch (error) {
    return { error: error.message };
  }
}

// Calling the function
result = await fetchFromURLandPOST("https:\\website.com\image.jpeg", "my_image");