LM Studio
Integrates a secure Python sandbox with a Gradio web UI to facilitate tool-based code execution for Large Language Models.
About
This project offers a comprehensive environment for leveraging Large Language Models with code execution capabilities. It features a secure, containerized Python sandbox equipped with a rich data science and machine learning stack, enabling safe execution of Python code. An integrated Artifact Server efficiently stores and serves generated files like plots and data. All interactions are managed through a user-friendly Gradio web interface, allowing users to chat with an LLM, delegate complex tasks requiring code execution to the sandbox, and visualize results directly within the UI. It's designed to work seamlessly with LM Studio, enhancing its capabilities for advanced analytical and developmental tasks.
Key Features
- Secure, containerized Python Sandbox for code execution
- Gradio-based web UI for LLM interaction and task delegation
- Artifact Server for storing and serving generated files (plots, images, data)
- Seamless integration with LM Studio (local chat and developer API modes)
- Optimized for robust tool-based code execution with specific LLM models
- 1 GitHub stars
Use Cases
- Interacting with LLMs to generate and execute code for scientific computing or data visualization
- Developing and testing LLM-powered applications that require dynamic code execution and result display
- Executing Python code in a secure sandbox via LLM prompts for data analysis or ML tasks
