code-interpreter VS vortex

The next generation of LMs will need a greater degree of isolation. Cloud providers like Amazon already allow arbitrary users access to their systems without knowing whether the user is a hacker. The startup E2B brings the same secure containerization technology Amazon uses to the AI space. Treating these LMs as if they were potentially malicious human-level hackers and placing similar restrictions on them as cloud providers do on human users should be sufficient to contain the threat.

Hey everyone! 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]. We specifically decided to use Firecrackers instead of containers because of their security and ability to do snapshots.

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 work with an LLM and AI framework. We have different examples on how to use the SDK with Llama models, Anthropic models, LangChain, LangGraph, and more in our cookbook [5].

We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that to our users. We're really just a boring code execution layer that sits at the bottom. We're building for the future software that will be building another software.

Our long-term plan is to build an automated AWS for AI apps and agents where AI can build and deploy its own software while giving developers powerful observability into what's happening inside our sandboxes. With everything being open-source.

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

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

We will show how to build a code interpreter with Llama 3 on Groq, and powered by open-source Code Interpreter SDK by E2B. The E2B Code Interpreter SDK quickly creates a secure cloud sandbox powered by Firecracker. Inside this sandbox is a running Jupyter server that the LLM can use.

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...

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.

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/

Fulcrum | Software Engineer | London or New York | ONSITE | Full-Time

Fulcrum is building next generation storage platform for diverse data of the future. We believe users will need to process non tabular and tabular data together and we need to develop new methods to support them.

We develop Vortex (our core storage primitive) in the open https://github.com/spiraldb/vortex and currently are looking to hire more people to our 5 person team to help build our product.

Tech: Rust, Python, Zig

Reach out to me at hn[at]fulcrum[dot]so