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... | testing_observability | DCAgent/swesmith-sandboxes-with_tests-25k |
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1... | idempotency | DCAgent/swesmith-sandboxes-with_tests-25k |
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
SERAlike-swesmith-25k
A drop-in replacement for DCAgent/swesmith-sandboxes-with_tests-25k where the per-row instruction.md is rewritten from the original specific SWE-Smith bug report into a SERA-style vague, "patch or abstain" prompt.
Why
SERA (2026) trains agents on synthetic data generated by the Soft Verified Generation (SVG) inversion: the teacher is given a vague bug-type hint, the agent invents a bug-fix, and the model's output is taken as ground truth (the "bug" being whatever the model decided to change). SERA's published Sera-4.6-Lite-T2-v4 corpus is generated from the SWE-Smith codebase set (121 repos, per the paper).
This dataset reuses SWE-Smith's existing real-bug task tarballs (Dockerfile + tests + solution all preserved) but replaces the instruction with a SERA-style vague prompt drawn from one of SERA's 51 ROLLOUT_ONE_PROMPTS. The agent is then explicitly given an abstain branch in the prompt: if it cannot identify a real change, it outputs <abstain/> and stops.
The point: at datagen time we get the vagueness of SERA's prompt distribution while keeping SWE-Smith's real test-based verifier — a strict improvement over SVG's line-level recall, since training only retains traces where the existing tests still pass after the agent's patch.
Schema
| column | type | notes |
|---|---|---|
path |
string | row id (swesmith-XXXXXX), inherited from upstream |
task_binary |
bytes | gzipped tar with the same layout as upstream — instruction.md (rewritten), task.toml, environment/Dockerfile, tests/*, solution/* |
bug_label |
string | which of SERA's 51 bug categories was sampled (e.g. state_management, edge_cases) |
source_dataset |
string | DCAgent/swesmith-sandboxes-with_tests-25k |
The bug label is sampled deterministically from sha256(path) so the rewrite is reproducible.
What changes vs upstream
instruction.md— replaced.- Everything else —
task.toml,environment/Dockerfile,tests/test.sh,tests/test_state.py,tests/config.json,solution/solve.sh— unchanged, including the SWE-Smith Docker image reference and the buggy commit checkout.
This means agents see SERA-style vague prompts but the underlying ground-truth bug + the existing test verifier are SWE-Smith's. Patches that don't fix what's actually broken should still fail at verification time, so post-hoc trace filtering is straightforward.
Generation
python -m data.seralike.rewrite # builds shards into ./out/
python -m data.seralike.upload --repo DCAgent/SERAlike-swesmith-25k
Source: OpenThoughts-Agent/data/seralike/.
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