#debugging

Chidori is an open-source platform offering a reactive runtime for developing AI agents. It supports Python and JavaScript execution, providing detailed monitoring and state management. Key features include time-travel debugging and visual representation for effective state control, enhancing integration with existing systems.

Discover early-stage utilities and libraries designed to assist in debugging Go programs. The APIs are subject to changes due to their experimental nature. Participate in the Go community by reporting issues or submitting patches through Gerrit. Keep informed about new updates and issues via the GitHub tracker, ensuring your debugging methods utilize the most current tools.

Model Explorer enhances model understanding through hierarchical graph visualizations, dynamic layer management, and GPU-accelerated rendering. Compatible with formats such as TFLite and PyTorch, it supports customization via extensions, accessible both locally and on Hugging Face. Comprehensive resources aid integration and adaptation.

TensorWatch offers flexible debugging and visualization for ML, integrating with Jupyter Notebook, and supporting tools like PyTorch and TensorFlow. Features include custom visuals, lazy logging, and diverse plots, aiding model training and prediction explanations. Requires Python 3.x and Graphviz.

Stern is a tool for debugging Kubernetes systems, enabling log tailing from multiple pods and containers with color coding for easy analysis. It efficiently filters pods using regex or Kubernetes resource names, eliminating the need for precise identifiers. The tool supports comprehensive installation options including asdf, Homebrew, and Krew, and allows developers to customize log outputs via templates. It also supports concurrent log requests and user-defined log verbosity to effectively diagnose system issues, along with featuring extensive CLI flags for versatile operation.

This tool offers Emacs users a unified interface for debugging, similar to the language server protocol but focused on debuggers. It features support for different types of breakpoints, a variable explorer, REPL, and memory editor, leveraging only Emacs core without external dependencies. It includes predefined configurations for various programming languages and allows for custom configurations. Its seamless integration with Emacs enhances usability, maintaining simplicity and compatibility with numerous debug adapters, making it a suitable choice for developers preferring native Emacs tools.

Custom Dump improves understanding of Swift data structures by providing debugging tools that surpass the standard 'dump' output. Key features include 'customDump' for better data visualization, 'diff' for comparing values, and utilities for asserting changes or consistency in complex data. It offers customization protocols for specific data representation needs, enhancing Swift development, testing, and debugging workflows.

Libfaketime allows the modification of system date and time seen by applications, useful for deterministic builds, debugging time-sensitive issues, and year-2038 compliance testing. It is compatible with Linux and macOS, utilizing dynamic linking, and is limited with statically linked binaries and specific configurations. Advanced options enable setting absolute or relative dates without altering the actual system clock. The included wrapper script facilitates ease of use but encourages direct library usage for comprehensive functionality.

Torchinfo offers in-depth PyTorch model summaries similar to TensorFlow's model.summary(), aiding in debugging neural networks. The project introduces a refined API beyond torchsummary and torchsummaryX, supporting RNNs, LSTMs, and flexible output formats, including use in Jupyter Notebooks. Features such as verbose mode and input data type support make Torchinfo an invaluable resource for developers seeking detailed insights into model parameters, operations, and architecture for PyTorch 1.4.0 and later.

PyStack utilizes enhanced debugging methods to examine stack frames of active Python processes and core dumps. Designed to aid developers in troubleshooting without delving into complex CPython details, PyStack offers compatibility with processes and core dumps, includes GIL status insights, and provides visibility into native function calls. It's considered safe, efficient, and standalone, making it a preferred tool for debugging Python on Linux.

LangSmith SDKs provide tools to debug, evaluate, and monitor language models and intelligent agents. Integrating seamlessly with LangChain's Python and JavaScript libraries, these SDKs support application tracing and performance analysis for any LLM application. Simplify workflows using LangSmith, from the developers of LangChain. Access detailed documentation and tutorials for best practices to fully leverage the LangSmith platform.