Harnessing OpenAI's function calling for Processing JSON Objects

In the realm of artificial intelligence, OpenAI’s GPT-3.5 Turbo has been a game-changer, providing developers a powerful tool to tackle a plethora of tasks. One such task is processing JSON objects, a common requirement in today’s data-centric world. JSON (JavaScript Object Notation) is a lightweight data-interchange format that is easy for humans to read and write, and easy for machines to parse and generate.

OpenAI provides an API that developers can interact with to leverage the capabilities of GPT-3.5 Turbo. In this blog post, we’ll explore how to structure a request to process a list of JSON objects using a custom function through the OpenAI API.

Below is the Python code snippet that demonstrates how to make a POST request to the OpenAI API, invoking a custom function to process a list of JSON objects. We’ve defined a function called process_json_objects which is structured to accept an array of JSON objects, each containing at least two string properties key1 and key2.

import requests
import json

# Define the data
data = {
"model": "gpt-3.5-turbo-0613",
"messages": [{"role": "user", "content": "Process these JSON objects."}],
"functions": [{
"name": "process_json_objects",
"description": "Processes a list of JSON objects.",
"parameters": {
"type": "object",
"properties": {
"json_objects": {
"type": "array",
"description": "A list of JSON objects.",
"items": {
"type": "object",
"properties": {
"key1": {"type": "string", "description": "Description of key1."},
"key2": {"type": "string", "description": "Description of key2."}
// ...other keys
"required": ["key1", "key2"] # specify required keys here
"required": ["json_objects"]
"function_call":{"name": "process_json_objects"}

# Define the URL and headers
url = "https://api.openai.com/v1/chat/completions" # Updated endpoint URL
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"

# Make the POST request
response = requests.post(url, headers=headers, data=json.dumps(data))

# Print the response

In this code snippet:

  1. We import the necessary libraries, requests and json.
  2. Define the data structure for our request, specifying the model, messages, and the custom function with its parameters.
  3. Set the URL to the /v1/chat/completions endpoint of the OpenAI API and the headers, including the authorization header with your API key.
  4. Make a POST request to the OpenAI API with the defined data and headers.
  5. Print the response to the console.

Make sure to replace “YOUR_API_KEY” with your actual OpenAI API key.

This code provides a structured way to process an undetermined number of JSON objects through the OpenAI API, demonstrating the flexibility and power of GPT-3.5 Turbo in handling various data processing tasks.

Author: robot learner
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