stepci VS openai-node

Location: EU, Germany

Remote: Yes

Willing to relocate: Yes

Technologies: HTML, CSS, TailwindCSS, JavaScript, TypeScript, Node.js, React/Next.js, Vue/Nuxt, GraphQL, REST, Postgres, Git, AWS, Docker + K8s

GitHub: https://github.com/mishushakov

LinkedIn: https://linkedin.com/in/mishushakov

Email: hey at mish.co

Most recently, I worked at Step CI a Technical Founder and authored the API-Testing Framework (https://stepci.com) and Garph (https://garph.dev), a full-stack API-Framework, which brings the developer-experience of tRPC to GraphQL.

My passion is in making tools developers love using and make them more productive.

For automated testing, you should give Step CI (https://github.com/stepci/stepci) a try

Ps. I helped build it

The problem is that you can import commonjs modules in ESM but not the other way around. For stepci (https://stepci.com) we have chosen to not support ESM for this very reason. We want that the library “just works” for all our users

Hopscotch is not a Postman fork as far as I know.

You can also do request chaining with Step CI (https://stepci.com) and Hurl (https://hurl.dev)

There’s also Step CI: https://stepci.com

Disclaimer: I’m one of the authors

It's a config driven uptime monitoring service powered by Step CI, an open source API testing framework.

You might try DiY-ing it with this open-source framework - https://stepci.com/

Okay, now we've confirmed the API endpoint is working, let's connect it to OpenAI first, install the OpenAI package, navigate to the route directory, and run the command below in our terminal

For my setup, I am using the node version of the openai sdk.

We try to keep it to a minimum, especially in JS (though we have some nice improvements coming soon when we deprecate node-fetch in favor of built-in fetch). The package sizes aren't tiny because we include thorough types and sourcemaps, but the bundle sizes are fairly tidy.

Here's an example of a typical RESTful endpoint (Lithic's `client.cards.create()`:

https://github.com/lithic-com/lithic-node/blob/36d4a6a70597e...

Here are some example repos produced by Stainless:

1. https://github.com/openai/openai-node

Have you seen/tried the `.runTools()` helper?

Docs: https://github.com/openai/openai-node?tab=readme-ov-file#aut...

Example: https://github.com/openai/openai-node/blob/bb4bce30ff1bfb06d...

(if what you're fundamentally trying to do is really just get JSON out, then I can see how json_mode is still easier).

And so, I impulsively upgraded to the latest version of openai (I guess not anymore) without the fear of getting cut by cutting edge 😝 and got it working for some random text

UPDATE 2023/11/15: I used fetch and custom streams because at the time of writing, the openai module on NPM did not properly support streaming responses. That issue has been fixed, and I think a better solution would be to use that module and pipe their data through a TransformStream to send to the client. That version is not reflected here.

You may notice the JavaScript package available on NPM called openai. We will not be using this, as it doesn’t quite support some things we’ll want to do, that fetch can.

openai - For using the GPT-3.5-turbo model to answer the questions

We have a bit of context about this in the readme: https://github.com/lastmile-ai/aiconfig#what-problem-it-solv.... The main issue with keeping it in code is that it tangles application code with prompts and model-specific logic.

That makes it hard to evaluate the genAI parts of the application, and also iterating on the prompts is not as straightforward as opening up a playground.

Having the config be the source of truth let's you connect it to your application code (and still source controlled), lets you evaluate the config as the AI artifact, and also lets you open the config in a playground to edit and iterate.

For example, compare how much simpler openai function calling becomes with storing the stuff as a config: https://github.com/lastmile-ai/aiconfig/blob/main/cookbooks/... vs using vanilla openai directly (https://github.com/openai/openai-node/blob/v4/examples/funct...)

In your preferred serverless environment, make sure you install the OpenAI API Library and Vercel AI library to get started.