RUC-NLPIR/Search-o1
🔍 Search-o1: Agentic Search-Enhanced Large Reasoning Models [EMNLP 2025]
This project helps anyone working with large language models to tackle complex questions more accurately. It takes your existing large reasoning model and a question, then automatically searches for information and integrates it into the model's thinking process to produce more reliable and precise answers. It's ideal for researchers, educators, or data scientists who rely on AI for advanced problem-solving.
1,182 stars.
Use this if your large reasoning model frequently struggles with knowledge gaps or produces uncertain answers when tackling challenging, multi-step questions like complex scientific Q&A, advanced math, or intricate coding problems.
Not ideal if your tasks are simple, single-step questions that don't require external information retrieval or deep analytical reasoning, or if you prefer a system that doesn't dynamically search for information.
Stars
1,182
Forks
104
Language
Python
License
MIT
Category
Last pushed
Nov 17, 2025
Commits (30d)
0
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