A real-time visualization tool for Claude Code and Codex agent orchestration that makes complex agent behaviors visible through interactive node graphs. It allows developers to monitor how agents think, branch, and coordinate during execution, facilitating easier debugging of tool call chains and reasoning processes.
- Live agent visualization via an interactive node graph with real-time streaming
- Concurrent support for Claude Code and Codex runtimes
- Integrated VS Code extension for direct workspace monitoring
- Interactive canvas with pan and zoom capabilities to inspect details
- Timeline, transcript panels, and JSONL log file replay functionality
- Live agent visualization via an interactive node graph with real-time streaming
- Concurrent support for Claude Code and Codex runtimes
- Integrated VS Code extension for direct workspace monitoring
- Interactive canvas with pan and zoom capabilities to inspect details
- Timeline, transcript panels, and JSONL log file replay functionality
This system transforms unstructured text documents into interactive knowledge graphs by using an LLM to extract knowledge in the form of Subject-Predicate-Object triplets. It features automated text chunking, entity standardization to ensure consistent naming across segments, and relationship inference to discover connections between disconnected parts of the data. The final output is an interactive HTML visualization that includes color-coded communities, node sizing based on importance metrics, and both original and inferred relationship types.
- Support for any OpenAI-compatible API endpoint including Ollama and vLLM
- Multi-pass processing for triple extraction, entity alignment, and relationship inference
- Interactive visualization with zoom, pan, and physics controls
- Community detection using the Louvain method
- Support for any OpenAI-compatible API endpoint including Ollama and vLLM
- Multi-pass processing for triple extraction, entity alignment, and relationship inference
- Interactive visualization with zoom, pan, and physics controls
- Community detection using the Louvain method
An interactive tool designed to visualize the relationships and flow of code reviews within a development team or project. It helps developers and managers understand how changes move through the review process, identifying bottlenecks and key contributors in the codebase evolution.
- Visual mapping of pull requests and code reviews
- Analysis of reviewer engagement and response times
- Identification of workflow patterns and potential delays
- Visual mapping of pull requests and code reviews
- Analysis of reviewer engagement and response times
- Identification of workflow patterns and potential delays
This article explores the field of mechanistic interpretability, aiming to understand how large language models (LLMs) work internally by reverse-engineering their computations. It discusses techniques for identifying and analyzing the functions of individual neurons and circuits within these models, offering insights into their decision-making processes.
"Talk to your data. Instantly analyze, visualize, and transform."
Analyzia is a data analysis tool that allows users to talk to their data, analyze, visualize, and transform CSV files using AI-powered insights without coding. It features natural language queries, Google Gemini integration, professional visualizations, and interactive dashboards, with a conversational interface that remembers previous questions. The tool requires Python 3.11+, a Google API key, and uses Streamlit, LangChain, and various data visualization libraries
Analyzia is a data analysis tool that allows users to talk to their data, analyze, visualize, and transform CSV files using AI-powered insights without coding. It features natural language queries, Google Gemini integration, professional visualizations, and interactive dashboards, with a conversational interface that remembers previous questions. The tool requires Python 3.11+, a Google API key, and uses Streamlit, LangChain, and various data visualization libraries
Google has enhanced Google Sheets with an AI-powered upgrade using its Gemini technology. This update allows users to automatically convert spreadsheets into charts, identify trends, and create advanced visualizations like heatmaps. Users can interact with the Gemini feature directly through a chat interface within Sheets.
DeepMind's Gemma Scope provides researchers with tools to better understand how Gemma 2 language models work through a collection of sparse autoencoders. This helps in understanding the inner workings of these models and addressing concerns like hallucinations and potential manipulation.
An overview of the LIDA library, including how to get started, examples, and considerations going forward, with a focus on large language models (LLMs) and image generation models (IGMs) in data visualization and business intelligence.
Inspectus is a versatile visualization tool for large language models, offering multiple views to provide diverse insights into language model behaviors. It runs in Jupyter notebooks via a Python API and supports visualization of attention maps, token heatmaps, and dimension heatmaps. The library can be installed using pip and provides API documentation and tutorials for Huggingface models and custom attention maps.
