AutoGen Code Interpreter with E2B
Blog post from 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.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 4 | 2,642 | 331 | 143 | -5% |
| AI Agents | 1 | 140 | 51 | 26 | +18% |
| AI Model Fine-tuning | 1 | 488 | 102 | 67 | +10% |
| Local AI | 1 | 8 | 5 | 4 | -20% |
| Multi-agent systems | 1 | 14 | 9 | 7 | -44% |
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