The article also provides installation instructions for Python and JavaScript, along with examples of how to use the Code Interpreter SDK. It explains how the code generated by LLMs is often split into code blocks, with each subsequent block referencing the previous one, a common pattern in Jupyter notebooks. The new code interpreter template runs a Jupyter server inside the sandbox, allowing for sharing context between code executions and improving support for plotting charts. The article concludes by mentioning the availability of pre-installed Python packages inside the sandbox and the possibility of building a custom template using the Code Interpreter SDK.
Key takeaways:
- The Code Interpreter SDK allows running AI-generated Python code and each run shares the context, meaning subsequent runs can reference variables, definitions, etc from past code execution runs.
- The code interpreter runs inside the E2B Sandbox, an open-source secure micro VM made for running untrusted AI-generated code and AI agents.
- The SDK supports streaming content like charts and stdout, stderr, works with any LLM and AI framework, and is 100% open source.
- The new code interpreter template runs a Jupyter server inside the sandbox, which allows for sharing context between code executions and improves support for plotting charts.