Show HN: Run LLMs in Docker for any language without prebuilding containers (github.com)

A new tool named "agent-en-place" has been released, enabling developers to run large language models (LLMs) in on-demand Docker containers, without the need for prebuilt images. This innovative utility streamlines the development process by automatically detecting the required programming tools and their versions from various configuration files, such as `.tool-versions`, `mise.toml`, and language-specific version files, creating tailored Docker images based on those specifications. Once set up, users can simply run a command, and the tool will build or reuse an existing Docker image, execute the AI coding tools, and mount the current working directory for seamless integration. This development is significant for the AI/ML community as it simplifies the workflow for developers using multiple programming languages and tools. By leveraging a common platform like Docker, which maintains consistent environments, "agent-en-place" reduces compatibility issues and enhances productivity. The tool supports various providers, including GitHub Copilot and OpenAI's Codex, and allows customization and debugging options, making it a valuable resource for developers working with AI-enabled applications. Overall, this tool facilitates more efficient and organized coding practices in an increasingly complex tech landscape.