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Announcing ReasoningLens — Visualizing and Diagnosing LLM Reasoning at a Glance

Blog post from HuggingFace

Post Details
Company
Date Published
Author
Jun Zhang, Jason Zheng, Boxi Cao, and ReasoningLens
Word Count
693
Language
-
Hacker News Points
-
Summary

ReasoningLens is a developer-centric toolkit designed to help users visualize, understand, and debug the reasoning chains of large language models (LLMs) by transforming complex and lengthy reasoning traces into an interactive, hierarchical map. The tool aims to alleviate the challenge of deciphering long-form reasoning, such as those produced by models like OpenAI o1 and DeepSeek-R1, by separating critical logic from repetitive procedural steps. It features hierarchical visualization to provide clarity, automated error detection to identify hallucinations and logical inconsistencies efficiently, and model profiling to aggregate and analyze patterns across multiple conversations. ReasoningLens is open-source, built on Open WebUI, and integrates tools like a calculator for verifying arithmetic steps, making it a versatile resource for the open-source community to enhance model transparency and reasoning interpretability.