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Features > Runpod Integration
Deploying to Runpod is effortless. You can deploy your models on a serverless platform, create an endpoint, and begin making requests to your model in no time. 🚀
Check out the AI Services tutorial To understand how to deploy your custom AI models on Runpod.
Retrieve your model's endpoint URL on Runpod and change: api/ai/runpod.ts to send requests to your model within your NuxtStarter project
api/ai/runpod.ts
1
2 let data = JSON.stringify({ // Modify the data object to match the request body of your API
3 input: {
4 image: base64,
5 prompt: requestBody.prompt,
6 seed: requestBody.seed,
7 style: requestBody.style,
8 },
9 });
10
11 let config = {
12 method: "post",
13 maxBodyLength: Infinity,
14 url: "#YOUR_RUNPOD_ENDPOINT#", // place in your endpoint here or use environment variables
15 headers: {
16 Authorization: "Bearer #YOUR_RUNPOD_API_KEY#", // place in your API key here or use environment variables
17 "Content-Type": "application/json",
18 },
19 data: data,
20 };
21
22
23 ....
24
25 try {
26 // Custom retry logic to handle failed AI requests
27 axiosRetry(axios, {
28 retryDelay: (retryCount) => {
29 return retryCount * 1;
30 },
31 retries: 15,
32 });
33
34 const result = await axios.request(config);
35 if (result.status === 200) {
36 return result.data;
37 } else {
38 return result.data;
39 }
40 } catch (error) {
41 throw createError({
42 statusCode: 400,
43 message: error.response.data
44 })
45 }
46 Input Type
We've utilized base64 encoding for the image input, as it's the most commonly used method for image generation models.Adjust the input type to match the request body of your API if your model necessitates different input types.