examples VS askai

StepZen is a platform to build and deploy GraphQL APIs that integrates and aggregate data from various sources. In the demo section, I will show how to build a GraphQL API in declarative code using StepZen.

Great! With this, we've implemented the login flow using Auth0 and StepZen. You can find the complete source code for this blog post on GitHub.

The final step is to use GraphQL. We'll create a free account on StepZen. Once logged-in, we can access the Account, Admin Key and API Key.

You can find a complete example of using StepZen to implement the Authorization Code flow in the StepZen GitHub repository.

Have a look at https://stepzen.com, which allows you to federate any data source no matter the framework or service used to create it. It has a generous free tier

When moving away from Apollo Server, and you're looking for a replacement built with JavaScript or TypeScript, let me give you some options. If you want to keep building your GraphQL API schema first, you might want to consider Mercurius (which relies on Fastify) or GraphQL Yoga. If you're going to build your GraphQL API code or resolver first, have a look at TypeGraphQL or Nexus. Alternatively, there are great GraphQL-as-a-Service solutions such as StepZen in case you no longer want to build, maintain and host your own GraphQL API.

But you can also build a GraphQL API using a code-first GraphQL server library. This means you can write the resolvers and then generate the schema from the resolvers. Code-first libraries are much closer to tRPC in terms of Developer Experience but still more challenging than using a GraphQL-as-a-service like StepZen.

After installing, you can choose to run StepZen locally using Docker or in the cloud by signing up for a free account at stepzen.com. For this example, we'll be using the cloud version, for which you can sign up for a free account using your GitHub account.

StepZen is participating in Hacktoberfest, and you can contribute by adding a new integration or improving an existing integration in our Examples repository. Every PR to this repository will count towards your Hacktoberfest goals.

To get a GraphQL using StepZen, you can connect your data source or use one of the pre-built examples from Github. In this post, we'll be taking a GraphQL API created on top off a MySQL database from the examples. By cloning this repository to your local machine, you'll get a set of configuration files and .graphql files containing the GraphQL schema. To run the GraphQL API and deploy it to the cloud, you need to be using the StepZen CLI.

This API allows you to interact with ChatGPT programmatically, and I've built some cool agents on top of it. Check out the code and let me know what you think! :

ChatGPT unofficial API :

This project is a Node.js application that interacts with the ChatGPT conversational AI model using Puppeteer, a Node.js library for automating web browsers.

Files chatgptv1.js: This file contains the main logic for the ChatGPT bot, including methods for initializing the browser, sending messages, receiving replies, and handling errors.

bart.js: This file contains a function that uses the Cloudflare API to summarize the conversation history when an error occurs, in order to resume the conversation.

twochatbotsconv.js: This file is simple use of the API , which creates two instances of the ChatGPT class, initiates a conversation between them, and saves the conversation history to a file.

.env: This file contains the API token for the Cloudflare API, which is used in the bart.js file.

Dependencies :

puppeteer: A Node.js library for automating web browsers. fs: The built-in file system module in Node.js. winston: A logging library for Node.js. crypto: The built-in cryptography module in Node.js. axios: A popular HTTP client library for Node.js. dotenv: A zero-dependency module that loads environment variables from a .env file.

Usage:

Install the dependencies by running npm install in your project directory. Create a .env file in the project directory and add your Cloudflare API token:

API_TOKEN=YourfreeCloudFlareAPIToken In your code, create a new instance of the ChatGPT class and use the sendMessage and getReply methods to interact with the ChatGPT model:

const ChatGPT = require('./chatgptv1');

const chatgpt = new ChatGPT(); await chatgpt.initializeBrowser();

await chatgpt.sendMessage('Hello, ChatGPT!'); const reply = await chatgpt.getReply(); console.log(reply);

await chatgpt.closeBrowser(); If an error occurs during the conversation, the handleError method will attempt to save the conversation history and resume the conversation using the summarized context.

Before Running :

run Google chrom in the debug mode using 9220 port , run : google-chrome-stable --remote-debugging-port=9222

Customization :

You can customize the behavior of the ChatGPT bot by passing options to the ChatGPT constructor:

chatbotUrl: The URL of the ChatGPT interface (default: 'https://chat.openai.com/'). headless: Whether to run the browser in headless mode (default: false). saveConversationCallback: A callback function that will be called with the conversation summary and the conversation file name when an error occurs.

License:

This project is licensed under the MIT License.

After wrestling with it for a bit and eventually giving up, I instead turned to ChatGPT to see if it is smart enough for the task. With my free plan, I asked ChatGPT 3.5 the following:

Go to chat.openai.com and log in

In this tutorial, we will learn how to use Strapi, ChatGPT, and Next.js to build an app that displays recipes using AI.