OpenAI recently introduced custom GPTs. Let’s briefly sum-up what GPTs are compared to classical ChatGPT:
It contains custom predefined instructions It has custom conversation starters It can now contain multiple capabilities at once (in classic ChatGPT you had to choose one). Those are: Web browsing DALL-E image generation Code interpreter Custom Actions (plugins got kind of deprecated) Especially, The last option is interesting, as it is now much easier to create integrations with custom actions.
This article is for developers who haven’t yet tried the ChatGPT API. I recently gave it a try and must conclude that it offers great potential. So, here’s a detailed guide on how to get started.
What is a “Token” and How Much Do OpenAI API Queries Cost? How Much Do OpenAI API Queries Cost? Setting up the Environment for Working with the OpenAI GPT-3.5 API Installing Necessary Libraries Creating an API Key for Authenticating Our Requests to the OpenAI API Setting Up OpenAI API Credentials Sending a Basic Request Understanding the Response Explanation of “Roles” Working with Conversation Context Some Advanced API Features Maximum Response Length “Temperature” Additional Parameters Limiting Tokens in Queries Sample Project: Automated RSS Reader Preparation Loading the RSS Feed Creating a Custom Profile Article Analysis Conclusion Before we start .
Efficiency is a cornerstone of any CI/CD pipeline. Running the full suite of Jest tests for every small modification can be a resource-intensive task that slows down the development process. We will learn how to run only those Jest tests that are impacted by the changes in a GitHub Pull Request.
