Zhihu's first quarterly profit: AI integrates into diversified community scenarios
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ReasonGraph is an open source AI tool for visualizing and analyzing large language model (LLM) inference processes , supporting 50+ mainstream models (such as OpenAI, Anthropic, Google). It converts complex inference paths into intuitive graphs , helping users understand AI thinking logic and optimize model performance.
✅ Inference path visualization: supports tree reasoning, sequential reasoning and other reasoning methods.
✅ Compatible with multiple LLMs: adapted to 50+ language models such as OpenAI, Google, Anthropic, etc.
✅ Interactive visualization: update inference paths in real time, supporting parameter adjustment, scaling, and SVG export.
✅ User-friendly interface: Intuitive UI design, convenient for configuring reasoning methods and viewing results.
Inference path analysis: Based on XML parsing, accurately extract the LLM inference process.
Dynamic visualization: The front-end uses Mermaid.js , which supports real-time inference path updates.
Modular backend: Based on Flask , it provides a unified API interface and supports multiple inference methods.
Real-time interaction: The front and back ends communicate through RESTful API to achieve instant feedback on inference results.
Open source and scalability: Developers can expand new inference methods to adapt to the needs of different LLMs.
Academic research: Analyzing reasoning methods and evaluating LLM's performance in complex tasks.
Education field: Teaching AI reasoning logic to improve learning interest and understanding efficiency.
Model optimization: discover inference errors and improve the quality of LLM inference.
Application development: Optimize LLM application logic and improve user experience.
GitHub: ReasonGraph open source repository
Technical papers: arXiv papers
Online experience: Hugging Face Demo
ReasonGraph makes AI reasoning transparent and helps AI research and developers optimize LLM performance!
