jimmyechan
Joined 13 years ago
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433
Submissions
160
Member since
Nov 20
YC alumni - @jimmyechan
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Comment · 1 year ago
Congrats Tom!
Comment · 2 years ago
Congrats! Cool project! I’d been curious about whether GPT would be good for this task. Looks like this answers it!
Why did you choose markdown? Did you try other output formats and see if you get better results?
Also, I wonder how HMTL performs. It would be a way to handle tables with groupings/merged cells
Comment · 2 years ago
No. At the moment all apps work on top of our internal framework. However, you can reuse your existing Python code/libraries. For instance, you could call existing Django models from Dropbase apps. You can also import any PyPI package.
Comment · 2 years ago
I like your take on that! I hadn't thought about it that way before but "Writing two files to build a webapp" indeed sounds quite intriguing. And we could extend that idea to "...and deploy it with 1 click" or some version of that.
I'm curious about what audience you have in mind and what kind of apps would you be interested in building this way? Would love to hear more of your thoughts!
Edit: I should add that our main motivation for integrating GPT is that we had to introduce some new concepts to make this experience work, which increased the app-building learning curve. We thought having GPT generate code and highlighting diffs would be a neat way to teach users how to develop apps without reading a lot of documentation.
Comment · 2 years ago
Thank you! I read your blog post and checked out your project! If I understood it correctly, you’re trying to build a software engineering team in a box. Basically from first issue, to code, to live apps. Very interesting approach adding the collaboration angle! ASTs are neat but I’d imagine it could get hard to manage with more complex code.
In our case, we regenerate the `main.py` file each time. One of the hacks we did was to start with boilerplate code, which is why you see it modifying the code as opposed to generating from scratch the first time. We also feed the model with some context/rules on app building using our web framework, so the output is more bounded.
We haven’t tested it on really big files yet, though I'd imagine it could be a problem later. At the moment, we don’t generate HTML, JS/TS, or React code from scratch so our files tend to be relatively smaller than if we did. Our UI is defined via the `properties.json` file, which abstracts much of the underlying code, therefore keeping the files small. It’s much easier for LLMs to generate json and map it to UI behavior, than generate of the client code needed to do all of it.
We don’t have issues with the LLMs changing function/method code, but it occasionally implements one of boilerplate methods we didn’t explicitly ask for. In those cases, a developer has to remove that code manually, which is why showing code diff is critical.
Many other hacks come down to lots of prompt engineering! Something along the lines of "Only implement or modify a method/function corresponding to a user's prompt. Leave all others intact"
Happy to chat more!
Also you might find this blog post we wrote interesting: https://www.dropbase.io/post/an-internal-tools-builder-that-...
Comment · 2 years ago
Interesting approach to just do json instead of protobuf!
Comment · 2 years ago
Can you provide examples of 2 services that interact with one another? Do the services call each other, or do clients call a service that then calls another service?
Comment · 2 years ago
Co-founder of Dropbase here. We're a better fit for you given your comments about Django and being in the same repo.
We are an internal tools builder that works with your existing Python codebase, in the same repo as your core app. You can call/use your exiting Django models from Dropbase UI components, and build fullstack internal tools with just Python.
Comment · 2 years ago
This is awesome!!! I'm really impressed with the demo. In particular, with how fast it seems to work given the number of models you use, the client-server back and forth, and the required processing and text gen. How did you do that? And at which point do you start to get bigger latencies e.g. writing an email, an essay, or a novel where you change the spelling of a character's name 2 chapters earlier.
Comment · 2 years ago
Cofounder @ Dropbase (dropbase.io) here. If you just need to build internal tools with Python or want to build internal tools on top of your existing Python codebase, give us a try. We have granular permission built-in so you can share internal tools with others easily, down to who can use or edit each internal tool you build.
For context, we're a more niche cousin to Reflex that's specifically designed to build internal tools. Reflex seems to be a more general framework to build anything you want; quite powerful, and possibly an easier to use Django replacement.
It's awesome to see frameworks like Reflex. I think the Python ecosystem needs this.