GraphiQL is a tool that was created to help developers explore GraphQL APIs, maintained by the GraphQL Foundation. But when GraphiQL became more and more popular, developers started to create additional GraphQL IDEs. A good example of this was GraphQL Playground, which quickly became the most popular GraphQL IDE. It was loosely based on GraphiQL, but had more features and a better UI. - Source: dev.to / over 1 year ago

I went to a GraphQL meetup and they used the gql playground and a similar schema generator to what I was using, and it made me feel relevant. - Source: dev.to / about 2 years ago

Here, we'll create a simple GraphQL server and subscribe to a subject from our resolver. We'll use GraphQL playground to mock client side behavior. Once we're connected we'll use NATS CLI to send a payload to our subject and see the changes on the client. - Source: dev.to / over 2 years ago

Now we can consume created GraphQL API. In the GitHub Repo same functionality has been added with REST approach and GraphQL endpoint. Also widely used Swagger configured for Web API Endpoints as well as AltairUI added for GraphQL endpoint testing. Naturally, AltairUI it not a must for GraphQL, you can also use Swagger, GraphiQL, or GraphQL Playground. - Source: dev.to / over 2 years ago

Navigate to http://localhost:3000/graphql. NestJS uses graphql playground by default. It's a lovely GraphQL IDE. We can check our schema here. - Source: dev.to / over 2 years ago

Are you referring to this? https://openai.com/blog/chatgpt-plugins Rabbit's approach is one-sided (train their model to generate needed API calls, and maybe also perform Selenium-style simulated actions?) which should make it more flexible if inherently less reliable than dedicated plugins written by developers from the apps looking to be called via AI. - Source: Hacker News / 2 months ago

To enable the plugin, simply navigate to your settings and locate the "Beta Features" section. There, you'll find the option to activate the ChatGPT code interpreter plugin and unlock its powerful capabilities. - Source: dev.to / 8 months ago

The output from an AI model in response to a prompt is typically textual. To translate these "ideas" into actionable outcomes, AI services need to call APIs. These APIs can initiate actions in the real or digital world, such as making payments, booking an appointment, sending messages, or adjusting room temperatures. In essence, APIs act as the hands of an AI service, enabling it to interact with its environment.... - Source: dev.to / 9 months ago

ChatGPT is an AI language model developed by OpenAI, known for its ability to generate human-like text based on input prompts. It is widely used for various applications, including chatbots, content generation, and data analysis. ChatGPT can access and parse information from websites through plugins and OpenAIs web crawler, making it essential for website owners who don't want their data trained on by AI models to... - Source: dev.to / 10 months ago

As you can see, you get the expected output and this is quite simple to achieve since ChatGPT is context-aware now. However, the issue with this method is that the model’s context is restricted (gpt-4 maximum text length is 8,192 tokens). This strategy will quickly become problematic when input data is huge you may expect thousands of items discovered in sales and you can not provide this large amount of data as... - Source: dev.to / 10 months ago