Blame for docs/trajectory_sources.md

# Trajectory source inventory

Audit date: 2026-10-14. Counts below distinguish upstream rows, imported
canonical records and records passing the strict multi-action/context gate.
`data/coverage/trajectory_sources.json` is the machine-readable counterpart;
`data/library/manifest.json` hashes every local canonical shard.

“Complete import” means the full identified upstream population for that
release/split, not every artifact ever published for a benchmark. “Protected”
means usable for evaluation/inspection but blocked from training export.
Source outcomes were not independently replayed unless explicitly stated.

> **Release note:** the detailed sections below document the original v0.3.0
> build. The append-only v0.4.0 release expands the inventory from 155,278 to
> 235,876 trajectories without rebuilding those records. See the
> [v0.4.0 incremental audit](v0.4.0_incremental_audit.md) for its pinned
> sources, accepted/rejected counts, rights decisions and exact append command.

## Measured coverage

`Imported` counts successfully canonicalized source rows before exact
deduplication. `Canonical` collapses only records with the same causal
interaction **and** the same outcome/reward/completeness/verification evidence;
all contributing IDs and locators remain in `duplicate_provenance.jsonl.gz`.
S/F/U are canonical success/failure/unknown counts. `Strict` is the retained
canonical count passing the complete multi-action/context gate.

| Source | Upstream rows | Imported | Canonical | Unique tasks | Strict | S/F/U | Missing or collapsed |
|---|---:|---:|---:|---:|---:|---:|---|
| SWE-Gym OpenHands SFT | 491 | 491 | 491 | 293 | 491 | 491/0/0 | none |
| SWE-Gym Sampled | 6,055 | 6,055 | 5,502 | 2,438 | 5,502 | 491/5,011/0 | 553 identical records collapsed |
| SWE-bench Verified trajectories | 5,000 | 5,000 | 4,544 | 500 | 4,532 | 3,392/1,152/0 | 456 identical records collapsed; 12 retained partials |
| SWE-bench Multilingual trajectories | 129 | 129 | 129 | 43 | 110 | 8/121/0 | 19 retained partials |
| SWE-smith `tool` | 24,100 | 24,100 | 24,100 | 10,637 | 24,100 | 9,427/14,673/0 | alternate XML/ticks serializations excluded |
| NVIDIA v1.2/OpenHands | 677,815 all-release | 51,626 | 51,626 | 33,444 | 51,626 | 24,743/26,883/0 | 626,189 other version/scaffold rows not imported |
| Terminal-Bench trajectories | 52,104 | 34,462 | 34,263 | 89 | 24,086 | 11,051/23,212/0 | 17,642 have no steps; 199 identical records collapsed |
| TerminalTraj | 20,000 | 20,000 | 20,000 | 17,787 | 19,143 | 0/0/20,000 | 857 retained short/partial traces |
| AgentSuite τ² | 8,340 | 8,340 | 8,340 | 228 | 8,337 | 3,375/4,965/0 | 3 retained incomplete traces |
| Official τ³ checked result | 200 | 200 | 200 | 50 | 0 | 100/100/0 | protected; not SFT-complete under strict gate |
| BrowseComp rollouts | 5,064 | 5,063 | 5,063 | 1,266 | 5,063 | 1,211/3,852/0 | 1 malformed row |
| Mind2Web exposed conversion | 1,009 | 1,009 | 1,009 | 1,009 | 1,009 | 0/0/1,009 | binary task outcome absent |
| ToolBench checked examples | 15 | 11 | 11 | 11 | 0 | 7/4/0 | 4 fail final gate; source flags are not semantic proof |
| AgentSuite BFCL | 115,466 | 0 | 0 | 0 | 0 | 0/0/0 | final calls only; no observations |
| ALFWorld planner records | 7,080 | 0 | 0 | 0 | 0 | 0/0/0 | actions lack paired observations |

Across the final inputs, 156,486 source rows became 155,278 canonical
interactions after 1,208 exact duplicates were collapsed. They cover 67,610
normalized tasks; 143,999 interactions pass the strict gate and 110,208 are
also training-eligible after protected-source separation. The coverage
manifest additionally records official final-answer/task registries and the
DeepSWE search result that do not enter this table as trajectory releases.

## SWE-Gym and SWE-bench family

- [SWE-Gym OpenHands SFT](https://huggingface.co/datasets/SWE-Gym/OpenHands-SFT-Trajectories),
  revision `4aaa5a4a4b5861f4799d2336908760c190ac3b17`, MIT: all
  491 `train.success.oss` OpenHands completion trajectories imported. The
  success label is the published split, not local replay. Messages encode tool
  actions/results in content; no arbitrary sample cap was used.
- [SWE-Gym OpenHands Sampled](https://huggingface.co/datasets/SWE-Gym/OpenHands-Sampled-Trajectories),
  revision `baf3a4e4bff514d48ddc08a93a2ade5c126212c7`, no card
  license: all 6,055 attempts imported, including published successful and
  failed execution outcomes, structured tools and reports.
- [tarsur385 SWE-bench Verified trajectories](https://huggingface.co/datasets/tarsur385/swebench-verified-trajectories),
  revision `773748a7c1222e8a642a7059821498e14293562a`, MIT: all
  5,000 mini-SWE-agent files (10 model families × 500 protected tasks)
  imported. Calls, results and source-resolved verdicts are full trajectories;
  all remain protected evaluation data. The official SWE-bench Verified
  instance table contains issues/tests/gold patches, not trajectories.
- [AlienKevin SWE-bench Multilingual trajectories](https://huggingface.co/datasets/AlienKevin/SWE-bench-Multilingual-trajectories),
  revision `7221c09c6cc0ed16d51c9cb9886a1ab484465670`, MIT: all
  129 attempts (three models × 43 Rust tasks) imported; 110 pass the strict
  contextualized multi-action gate. The remaining 19 are explicit tier-5
  partial/short diagnostics. This is a third-party protected rollout release,
  not an official expert-demonstration set.
- [SWE-smith trajectories](https://huggingface.co/datasets/SWE-bench/SWE-smith-trajectories),
  revision `08e109b4a59eaeebf80e4675cd125d42e7ac99a4`, MIT: all
  24,100 `tool` rows imported and accepted. The `xml` (26,076 rows) and `ticks`
  (25,826 rows) configurations are alternate serializations rather than
  additional independent rollouts, so they are deliberately not duplicated.

## NVIDIA Open-SWE-Traces

[nvidia/Open-SWE-Traces](https://huggingface.co/datasets/nvidia/Open-SWE-Traces)
was pinned at `6d0a83373ae0d83abe3d363f1f18cb1822e16586` (CC-BY-4.0).
The release enumerates 677,815 trajectories:

| Version | Rows |
|---|---:|
| v1.0 | 151,219 |
| v1.1 | 263,226 |
| v1.2 | 263,370 |
| **All** | **677,815** |

All 51,626 v1.2/OpenHands records across 24 revision-qualified source Parquet
shards were imported and passed the action/observation gate. Messages, tools
and metadata were JSON-decoded; native instance/model/scaffold/resolved fields
remain intact. The other 626,189 version/scaffold rows were not downloaded:
their source Parquet totals 55,056,684,304 bytes, which exceeds the remaining
workspace budget once lossless canonical records and indexes are retained.
This is an explicitly quantified partial import, not a sample represented as a
complete NVIDIA corpus. The upstream repository advanced during the audit, but
all imported URLs and metadata remained pinned to the stated SHA.

## Terminal agents

- [yoonholee Terminal-Bench trajectories](https://huggingface.co/datasets/yoonholee/terminalbench-trajectories),
  revision `04e8940f5b6736a7ce8d22224fe2f2af74163ed2`, Apache-2.0:
  all 52,104 trial rows enumerated. Exactly 34,462 publish step sequences and
  were imported; 17,642 `steps=null` rows are rejected as absent trajectories.
  Of the deduplicated traces, 24,086 pass the strict gate and the rest remain
  tier-5 partial diagnostics. Model, scaffold, reward, duration, token and cost
  fields are preserved. Observations are source-truncated to 5,000 characters.
  This protected third-party release is distinct from the official task repo.
- [TerminalTraj](https://huggingface.co/datasets/m-a-p/TerminalTraj), revision
  `5c1823f4a8b9ca0cf02c27d2db52c5b35b53a308`, no card license: all
  20,000 command/output records imported; 19,143 pass the multi-action/context
  gate. No trustworthy task-level verdict exists, so outcomes are unknown—not
  failed.
- The [official Terminal-Bench repository](https://github.com/laude-institute/terminal-bench)
  at `d28711d0da2675d0bb1d56de45ae5df6082438a3` contains 241 protected task
  manifests, tests and reference scripts. Those are not completion
  trajectories; 966 audited files carried explicit anti-training canaries.

## τ² and τ³

- [AgentSuite τ² trajectories](https://huggingface.co/datasets/AgentSuite/tau2-bench-trajectories),
  revision `07264f1d253a618fc20966670eddc44246212916`, no card
  license: all 8,340 rollouts (30 models × 278 task slots) imported; 8,337 pass
  the complete action/observation gate and three remain explicit incomplete
  diagnostics because a call has no returned observation. System/user/assistant/tool
  interactions and evaluator correctness/reward are present. Tool definitions
  are absent and declared missing. They are τ²
  rollouts, not assumed version-compatible with τ³.
- [Official τ³ repository rollouts](https://github.com/sierra-research/tau2-bench),
  revision `dd8757d4c8791dad7b3cdaf02a105a3d5f9d86bd`, MIT code plus
  benchmark restrictions: the available checked-in final result file contains
  200 model/user-simulator trials over 50 tasks (100 source successes and 100
  failures). It is imported for evaluation only. Expected actions and solution
  metadata are never treated as expert demonstrations.

## Function calling and general tool use

- [AgentSuite BFCL outputs](https://huggingface.co/datasets/AgentSuite/BFCL-trajectories),
  revision `a86612c6bb68e6566e5e7d206f7b031af889edc0`, no card license:
  all 115,466 rows were audited. They contain user prompts, model final function
  calls, scores and latency but no returned tool observations. Zero qualify as
  trajectories; none enter the canonical library. This is “exists but is only
  final output,” not “no BFCL data exists.”
- [ToolBench](https://github.com/OpenBMB/ToolBench), revision
  `d56fdd89faf8c91fa135090b212bb9057ee5cfc2`, Apache-2.0 repository:
  all 15 checked-in answer examples were inspected, 13 adapted, and 11 pass the
  strict gate. The final cumulative history is used once; cumulative prefixes
  are not duplicated. `win`/`valid_data` are generation flags rather than
  independent semantic success evidence. A complete full-release population
  was not verified.

## Web agents

- [rl-rag BrowseComp rollouts](https://huggingface.co/datasets/rl-rag/browsecomp-gpt-oss-120b-260222),
  revision `ac4854be0eb527cdf90f6c7d09446eeb7a3d1dbd`, no card license:
  5,063/5,064 full research-agent conversations imported; one row lacks a
  conversation. The release normally has four GPT-OSS-120B attempts per
  question, full search results and a source GPT-4o answer-judge verdict.
  Reference answers stay out of model input. This is protected evaluation data;
  official BrowseComp question/answer rows alone are not trajectories.
- [Mind2Web](https://huggingface.co/datasets/osunlp/Mind2Web), revision
  `17ece8eb89862368edc0cc806acee6fca5163474`, CC-BY-4.0: all 1,009
  rows exposed by the hosted partial Parquet conversion imported. These are
  human action sequences with a full pre-action DOM for each target and no
  binary task-success field. Completeness is claimed only for that exposed
  conversion, not every historical artifact.

## ALFWorld and DeepSWE

- [ALFWorld](https://github.com/alfworld/alfworld) release 0.2.2 contains
  7,080 planner `traj_data.json` records (archive SHA-256
  `25171f16e20ad7b048c47275c45b0babf3aa1cbab29cec97387922350a9844bc`).
  They preserve human task text, planner/low actions and image references but
  not action-paired environment observations in the audited artifact. They are
  therefore excluded rather than promoted to full trajectories.
- No exact public, pinned DeepSWE/Datacurve full-trajectory release was found.
  This is the “none found after searching” state—not evidence that no private or
  future trajectory artifact exists. Protected SWE evaluation/reference data
  was not substituted for demonstrations.

## Outcome and permission interpretation

- Expert provenance is used only for human/reference/planner demonstrations;
  successful model rollouts remain recorded agent completions.
- Source-evaluator and source-reported verdicts are distinct from independent
  reproduction. This build performed zero native benchmark replays.
- Conditional sources can populate preparation-time training exports because
  licensing was explicitly out of scope for this data-preparation task.
  Evaluation-only sources remain `protected_evaluation` regardless.
- Failed and unknown outcomes have separate indexes and denominators.

## Reproducing imports

Most hosted releases use the same resumable command (repeat `--split` for
multi-split datasets):

```bash
.venv/bin/python scripts/import_hf_release.py SOURCE_ID DATASET_ID \
  --revision IMMUTABLE_SHA --output data/full/canonical/OUTPUT \
  --cache data/cache/full/OUTPUT --config default --split SPLIT
```

Concrete source/split pairs are recorded in `data/registry/sources.json` and
every generated `release-manifest.json`. NVIDIA uses pinned repository files so
the moving dataset-server conversion cannot change the bytes:

```bash
.venv/bin/python scripts/import_hf_release.py \
  nvidia_open_swe_traces nvidia/Open-SWE-Traces \
  --revision 6d0a83373ae0d83abe3d363f1f18cb1822e16586 \
  --output data/full/canonical/nvidia_v1_2_openhands_original \
  --cache data/cache/full/nvidia_v1_2_openhands_original \
  --config v1.2 --split openhands \
  --original-glob 'data/openhands/qwen38_27b/*/*.parquet' \
  --original-glob 'data/openhands/qwen38_flash_next/*/*.parquet'
```

Native JSON trees (tarsur SWE-bench Verified, AgentSuite τ² and official τ³)
are checked out at the registered SHA and streamed with:

```bash
.venv/bin/python scripts/import_json_tree.py SOURCE_ID PINNED_CHECKOUT \
  --output data/full/canonical/OUTPUT/all.jsonl.gz \
  --revision IMMUTABLE_SHA --url DIRECT_SOURCE_URL --glob '**/*.json*'
```

The combined 211-record seed used by the final build is reproducible from the
official τ³ result and checked-in ToolBench example. First adapt those pinned
files separately; apply `scripts/filter_canonical.py --strict --source
toolbench` to the ToolBench result (13 adapt, 11 pass); then combine the 200 τ³
and 11 ToolBench records with:

```bash
.venv/bin/python scripts/filter_canonical.py \
  data/full/canonical/official_tau3/all.jsonl.gz \
  data/full/canonical/toolbench/strict.jsonl.gz \
  --source official_tau3 --source toolbench \
  --output data/full/canonical/seed_evaluation/official_tau3_toolbench.jsonl.gz
```

Finally run the complete-library, coverage, gallery and evaluation commands in
the root [README](../README.md). No command applies an arbitrary row limit.