AutoPR VS E2B

The github is : https://github.com/irgolic/AutoPR

Check it out, and let me know if you have any ideas on how you'd like to use it or make it better.https://github.com/irgolic/AutoPR

Added a manual trigger, here's the PR your issue generated: https://github.com/irgolic/AutoPR/pull/27

Agreed. Would love to see this project take off: https://github.com/irgolic/AutoPR

- Opens PRs for the generated code, making it easy to review and merge changes.

By using this GitHub Action, you can skip the manual steps of prompt design, and let the AI handle code generation and PR creation for you.

Here's how I used AutoPR to make the license for itself: https://github.com/irgolic/AutoPR/pull/4

Feel free to give it a try, and I would love to hear your feedback! It's still in alpha and it works for straightforward tasks, but I have a plan to scale it up. Let's see how far we can push GPT-4 and create a more efficient development process together.

Happy coding!

So I have been toying on an automated PR GitHub Action for a bit but seeing this spurred me to actually put it into a format for y'all to try. It uses GPT-4 to automatically generate code based on issues in your repo and opens pull requests for those changes.

You can find my solution here: https://github.com/irgolic/AutoPR/

What I can do:

- Automatically generates code based on issues in your repo.

E2B | https://e2b.dev | San Francisco, CA | Full-time | In-person

[E2B](https://e2b.dev) is building a secure open-source runtime that will power next billion of AI apps & agents.

We found an early traction with making it easy for developers to add [code interpreting](https://github.com/e2b-dev/code-interpreter) to their AI apps with our SDK built on top of our [agentic runtime](https://github.com/e2b-dev/e2b). We have paying customers from seed to enterprise companies.

We're hiring:

- Frontend/Product Engineer

- Infrastructure Engineer

Check the roles here https://e2b.dev/careers

Hi, I'm the CEO of the company that built this SDK.

We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].

You can think of us as giving small cloud computers to LLMs.

We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense

The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].

We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to Claude [5].

Our long-term plan is to build an automated AWS for AI apps and agents.

Happy to answer any questions and hear feedback!

[0] https://e2b.dev/

[1] https://github.com/e2b-dev

[2] https://github.com/firecracker-microvm/firecracker

[3] https://e2b.dev/docs

[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...

[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/c...

Hey folks, we're building an open source runtime for AI agents at E2B.