AutoGen Code Interpreter with E2B

An open-source cookbook example of a code interpreter using AutoGen agents was recently developed by community contributor Keegan McCallum, founder of Xler.ai, which is a multi-agent platform offering services like evaluation and deployment. This example project executes LLM-generated code in the cloud using E2B sandbox, a secure, long-running cloud environment that mirrors local execution and supports various LLMs, including GPTs and Claude. E2B, fully open-sourced, provides an infrastructure layer for running AI applications securely, offering a solution to the limitations and risks of local execution via Docker. Users can explore E2B sandboxes for free through its documentation, and the E2B cookbook encourages contributions of LLM-powered code interpreters or coding AI agents that utilize E2B sandboxes.