This is a Node.js module for mocking OpenAI API responses in a development environment.
It's useful for testing and development purposes when you don't want to make actual API calls.
The module supports the following OpenAI API endpoints:
- chat completions
- chat completions with streaming
- chat completions with functions
- image generations
This module is powering the sandbox mode for Aipify.
You can install this module using npm as a dev dependency :
npm install -D openai-api-mock
The module supports both ESM and CommonJS imports:
// ESM
import { mockOpenAIResponse } from 'openai-api-mock';
// CommonJS
const { mockOpenAIResponse } = require('openai-api-mock');
Then, call the mockOpenAIResponse function to set up the mock response:
// Basic usage
mockOpenAIResponse();
// Force mocking regardless of environment
mockOpenAIResponse(true);
// With configuration options
mockOpenAIResponse(false, {
includeErrors: true, // Simulate random API errors
latency: 1000, // Add 1 second delay to responses
logRequests: true // Log incoming requests to console
});
The function accepts two parameters:
-
force
(boolean): Determines whether the mock response should be used regardless of the environment. If false or not provided, mocking only occurs in development environment. -
options
(object): Additional configuration options-
includeErrors
(boolean): When true, randomly simulates API errors -
latency
(number): Adds artificial delay to responses in milliseconds -
logRequests
(boolean): Logs incoming requests to console for debugging
-
The function returns an object with control methods:
const mock = mockOpenAIResponse();
// Check if mocking is active
console.log(mock.isActive);
// Stop all mocks
mock.stopMocking();
// Add custom endpoint mock (uses api.openai.com as base url)
mock.addCustomEndpoint('POST', '/v1/custom', (uri, body) => {
return [200, { custom: 'response' }];
});
// Call the mockOpenAIResponse function once to set up the mock
mockOpenAIResponse()
// Now, when you call the OpenAI API, it will return a mock response
const response = await openai.chat.completions.create({
model: "gpt-3.5",
messages: [
{ role: 'system', content: "You're an expert chef" },
{ role: 'user', content: "Suggest at least 5 recipes" },
]
});
In this example, the response
constant will contain mock data, simulating a response from the OpenAI API:
{
choices: [
{
finish_reason: 'stop',
index: 0,
message: [Object],
logprobs: null
}
],
created: 1707040459,
id: 'chatcmpl-tggOnwW8Lp2XiwQ8dmHHAcNYJ8CfzR',
model: 'gpt-3.5-mock',
object: 'chat.completion',
usage: { completion_tokens: 17, prompt_tokens: 57, total_tokens: 74 }
}
The library also supports mocking stream
responses
// Call the mockOpenAIResponse function once to set up the mock
mockOpenAIResponse()
// Now, when you call the OpenAI API, it will return a mock response
const response = await openai.chat.completions.create({
model: "gpt-3.5",
stream : true,
messages: [
{ role: 'system', content: "You're an expert chef" },
{ role: 'user', content: "Suggest at least 5 recipes" },
]
});
// then read it
for await (const part of response) {
console.log(part.choices[0]?.delta?.content || '')
}
This module uses the nock
library to intercept HTTP calls to the following OpenAI API endpoints:
-
https://api.openai.com/v1/chat/completions
: This endpoint is used for generating chat completions. -
https://api.openai.com/v1/images/generations
: This endpoint is used for generating images.
This module depends on the following npm packages:
- nock : For intercepting HTTP calls.
- @faker-js/faker : For generating fake data.
This project is licensed under the MIT License.