---
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

```python
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`.