Learn how to seamlessly incorporate the OpenAI API into more complex systems, mastering the art of manipulating the response format and adeptly handling errors. This chapter provides essential knowledge for those looking to build components of AI systems that are not just interactive but also robust and efficient.

Structuring an API call

Decoding the response

Formatting model response as JSON

Handling errors

Options

AuthenticationError

BadRequestError

RateLimitError

Interpreting error messages

Handling exceptions

Batching

Avoiding rate limits with retry

Batching messages

Setting token limits

Structuring End-to-End Applications

Dive into the mechanics of function calling, where you'll master defining parameters to call specific functions, extracting structured data, and working with multiple functions. Learn to seamlessly integrate external APIs and manipulate responses to communicate with other systems, to develop enhanced AI system interactions.

Defining function calling

Function calling definition

Function calling steps

Extracting structured data from text

Using the tools parameter

Building a function dictionary

Extracting the response

Working with multiple functions

Parallel function calling

Setting a specific function

Avoiding inconsistent responses

Calling external APIs

Defining a function with external APIs

Calling an external API

Handling the response with external API calls

Function Calling

Elevate your OpenAI API skills to follow the industry's best practices. Learn to moderate content with precision, validate model behavior for consistency, and implement safety measures for secure API usage. This final chapter is an essential part of building robust AI-powered applications.

Moderation

Mitigating prompt injection

Moderation API

Adding guardrails

Validation

Potential for model errors

Adversarial testing

Safety best practices

Minimizing model risks

Including end-user IDs

Wrap-up

Best Practices for Production Applications

Get your AI applications ready for production with this OpenAI API course. You’ll discover best practices for developing applications on the OpenAI API, including moderation and validation, testing, and practices for improved safety. You’ll also learn how to connect your application with external systems and APIs through function calling. This course builds on core OpenAI functionalities introduced in Working with the OpenAI API and prompt writing best practices from Prompt Engineering with the OpenAI API to help you elevate your projects from proof of concept to production-ready systems.

Python Toolbox

Prompt Engineering with the OpenAI API

Leverage the OpenAI API to get your AI applications ready for production.

Developing AI Systems with the OpenAI API

Associate AI Engineer for Developers

Developing AI Applications

OpenAI Fundamentals

**Definition**: Your API key or token was invalid, expired, or revoked

**Possible solution**: Check that your API key or token is correct and has not been revoked or expired

**Definition**: Your request is missing required parameters, or some of the parameters are invalid

**Possible solution**: Double check the variables and parameters you are passing as input and ensure they are valid and in the correct format

**Definition**: You have exceeded the number of requests you can send within a given time

**Possible solution**: decrease the number of requests you are sending to the API within a given time

Interpreting error messages

Developing AI Systems with the OpenAI API

Praktische interactieve oefening