Azure Container Apps' dynamic sessions offer a secure and efficient environment for executing Python code, particularly enhancing the capabilities of language learning models (LLMs) like LangChain by overcoming their limitations in computational tasks. The integration allows LLMs to write and execute Python code securely within a Hyper-V sandbox, providing strong isolation, rapid startup, scalability, and managed lifecycle. Preinstalled with popular packages like NumPy and pandas, these sessions support high-scale concurrent executions and allow for private data access. The LangChain integration simplifies the process of setting up Azure Container Apps for executing LLM-generated code, which is beneficial for applications such as data analysis through agents like LangGraph. This integration represents a significant advancement in leveraging LLMs for complex problem solving by offloading computational tasks to code execution tools, thereby improving productivity and performance.