Hmm, I don't know enough to give you a confident answer yet. The extracts provided do not contain specific information on how to implement a custom API in a GPT model. However, they do provide some general guidance on working with the OpenAI API and creating schemas for API requests.
For instance, one extract from the OpenAI community forum provides a sample schema for a GET request. This schema could potentially be adapted to work with your isEven API. Here's the relevant part of the schema:
{
"openapi": "3.1.0",
"info": {
"title": "WebdadiAPI",
"version": "0.1.0"
},
"servers": [
{
"url": "MyFQDN/"
}
],
"paths": {
"/search": {
"get": {
"summary": "Search GPT-generated content",
"operationId": "searchGPTContent",
"parameters": [
{
"name": "input_text",
"in": "query",
"required": true,
"schema": {
"type": "string"
}
}
],
You would need to replace the url under servers with your API's base URL, and adjust the paths and parameters to match your API's endpoints and parameters.
For more detailed guidance, I recommend checking out the OpenAI Cookbook (https://cookbook.openai.com/), which provides examples and tutorials on various topics related to working with OpenAI's models and APIs.
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon: