# RUC-NLPIR/Search-o1

🔍 Search-o1: Agentic Search-Enhanced Large Reasoning Models [EMNLP 2025]

Repository: https://github.com/RUC-NLPIR/Search-o1
Canonical: https://ross.abutalabs.com/products/search-o1
Language: Python
License: MIT
License Family: permissive
Topics: aimo, amc, gpqa, livecode, math, o1, qwq, r1, rag, reasoning
Last push: 2025-11-17T08:56:42+00:00

## Health v2 (maintenance only)
Score: 44/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 52, release rhythm 35, longevity 43
- inputs: {"age_days": 607, "days_push": 289, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1241, forks 108 (observed 2026-08-28T04:04:06.430722+00:00)

## What it is
Search-o1 is a research framework that enhances large reasoning models (like QwQ and R1) with agentic search and retrieval-augmented generation during multi-step reasoning. It accompanies an EMNLP 2025 paper and provides code for reproducing experiments on benchmarks such as AIME, AMC, GPQA, and LiveCode.

## Use cases
- add web search to a reasoning LLM's chain of thought
- run RAG-enhanced inference with QwQ or DeepSeek R1
- evaluate reasoning models on math and science benchmarks
- reproduce the Search-o1 paper experiments
- build an agentic search pipeline for LLM reasoning

## When to choose
- you want to augment reasoning models with retrieval during inference
- you need a research baseline for search-enhanced LLM reasoning
- you're benchmarking on AIME, AMC, GPQA, or LiveCode

## When to avoid
- you need a production-ready RAG service
- you don't have GPU resources for large reasoning models
- you want a plug-and-play chatbot rather than a research codebase

## Facets
- artifact type: library
- maturity: active
- function: rag, agent-framework, llm-inference, search-engine, machine-learning
- domain: large-language-models
- platform: python
- tags: reasoning-models, agentic-search, research-framework, emnlp-2025, math-reasoning, retrieval-augmented-generation, ai-agents, natural-language-processing, linux, gpu

## Member repositories
- RUC-NLPIR/Search-o1 (main) score 44

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:06.430722+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:08:27.023205+00:00, confidence not recorded.
  - readme: https://github.com/RUC-NLPIR/Search-o1 (fetched 2026-08-28T04:04:06.430722+00:00, sha 17a7d20932cf)
- Data as of 2026-08-30T08:39:29.467469+00:00.