metadata
license: apache-2.0
language:
- en
task_categories:
- question-answering
tags:
- search-agent
- tool-use
- react
- multi-hop-qa
- deep-search
pretty_name: SynSearch-Data
size_categories:
- 1K<n<10K
SynSearch-Data
SynSearch-Data is an environment-aligned Search Agent training dataset produced through task synthesis and Solver-in-the-Loop verification. This first release contains 5,000 high-quality multi-hop ReAct trajectories covering 4,182 audited tasks.
Data format
Each JSONL row contains:
messages: the complete ReAct conversation, including tool calls and tool responses;metadata.task_id/run_idx/trajectory_rank: trajectory provenance;metadata.seed: source seed and evolution generation;metadata.hops,difficulty,evolution_iterations,turns;metadata.question,answer,predicted_answer;metadata.final_eval: Solver-in-the-Loop aggregate statistics.
Quality controls
- 5,000 trajectories, 4,182 unique tasks;
- 100% multi-hop (
hops >= 2); - 100% solver-verified correct trajectories;
- 100% exact message-hash traceability to retained source trajectories;
- no duplicate
(task_id, run_idx)pairs.
Distribution
| Hops | Samples |
|---|---|
| 2 | 1,965 |
| 3 | 1,732 |
| 4 | 786 |
| 5 | 287 |
| 6+ | 230 |
Load
import json
with open("SynSearch-Data.jsonl", encoding="utf-8") as f:
samples = [json.loads(line) for line in f]
The companion models are alibaba-pai/SearchQwen2.5-7B, alibaba-pai/SearchQwen2.5-3B, and alibaba-pai/SearchQwen3-8B.