Release all 100 Astra BEHAVIOR trajectories with prompts, actions and score provenance

README.md

@@ -10,7 +10,7 @@ tags:
 # RoboHarness assets
 
 Large files for [RoboHarness](https://github.com/BinceQu/RoboHarness) and its
-[project page](https://bincequ.github.io/RoboHarness/), kept out of the git
+[project page](https://roboharness-lab.github.io/), kept out of the git
 repository so that `git clone` stays small.
 
 ## Paper
@@ -33,6 +33,7 @@ repository so that `git clone` stays small.
 
 | Path | Contents |
 | --- | --- |
+| `astra-v2-behavior/` | 100 GPT-6 Astra trajectories, head-camera videos, prompts, tools and scores |
 | `v1/docs/assets/` | Project-page videos (method film and head-camera rollouts) |
 | `v1/reference_results/` | Archived reference evaluator results checked by the V1 runner |
 | `v1/validation_results/` | V1 evaluation reports and audits |
@@ -53,3 +54,11 @@ To recover the original repository with its original commit IDs:
 git clone roboharness-v1-full-history-6f3fcdb.bundle RoboHarness-v1
 git -C RoboHarness-v1 checkout 6f3fcdbc432c0eca7c311af5b20f29604271a9e9
 ```
+
+## GPT-6 Astra × RoboHarness V2
+
+[Browse the 100 BEHAVIOR trajectories](astra-v2-behavior/README.md).
+Mean Q is **0.457166 over 100 tasks**, comprising 99 official evaluator results
+and one explicitly marked video estimate (T08, Q ≈ 0.50). The official-only
+mean is 0.456734. Each task includes its prompt, conversation, tool calls,
+returned images, executed joint commands and continuous head-camera video.

astra-v2-behavior/README.md

@@ -0,0 +1,98 @@
+# GPT-6 Astra × RoboHarness V2: 100 BEHAVIOR trajectories
+
+GPT-6 Astra runs inside a fresh RoboHarness V2 workspace to control the R1 Pro
+on all 100 BEHAVIOR Challenge 2026 tasks. This release contains the counted
+attempt for every task, including successes, partial scores and failures.
+
+[Project](https://roboharness-lab.github.io/) ·
+[Code](https://github.com/BinceQu/RoboHarness) ·
+[Download files](https://huggingface.co/datasets/BinceQu/RoboHarness-assets/tree/main/astra-v2-behavior)
+
+## Scores
+
+| Set | Tasks | Mean Q |
+| --- | ---: | ---: |
+| All tasks, including one video estimate | 100 | 0.457166 |
+| Official evaluator results only | 99 | 0.456734 |
+
+There are 26 full successes, 43 partial scores and 31 zero scores when the
+estimate is included. `score_source` distinguishes `official` from `video_estimate`.
+
+T08, *rearranging kitchen furniture*, stopped at tick 11904 of 13414 without an
+official final score. Its **estimated Q is 0.50**: the final head-camera view
+shows the toaster and French press inside the same cabinet, while the food
+processor remains outside and the cabinet doors remain open. Each of these
+four conditions contributes 0.25. The estimate concerns the recorded endpoint;
+RGB video cannot establish the evaluator's exact geometric predicates.
+`estimates.json` records the conditions, evidence and limitations. The estimate
+is included in the 100-task mean, but is never presented as an official score.
+
+## Files
+
+| Path | Contents |
+| --- | --- |
+| `episodes.json` | Scores, exact task prompts, shared agent settings and media checksums |
+| `index.csv` | One row per task, with its trajectory archive and checksum |
+| `trajectories.json` | Archive sizes, SHA-256 checksums, source attempt and record counts |
+| `trajectories/tNN.tar.gz` | Agent-visible trajectory and executed joint commands for task NN |
+| `videos/tNN-head.mp4` | Continuous head-camera recording, 448 × 448, original frame rate |
+| `previews/tNN-head.mp4` | Eight-second head-camera time-lapse |
+| `posters/tNN-head.jpg` | Head-camera poster |
+| `card/` | Synchronized video wall used on the project homepage |
+| `estimates.json` | T08 video-based score estimate |
+| `evidence/` | Contact sheets supporting the T08 estimate |
+
+Each trajectory archive contains:
+
+- `prompt.txt`: the exact task prompt delivered to the agent.
+- `episode.json`: task, instance, rollout, settings, score and source attempt.
+- `metrics.json`: the official result, when one exists.
+- `agent/conversation-*.jsonl`: messages, tool calls and tool responses from the
+  native Codex conversation. Embedded images are extracted into `images/` and
+  referenced by archive-relative paths.
+- `agent/stream-*.jsonl`: native Codex event streams.
+- `tool_calls/`: tool inputs, results, returned/click-annotated images,
+  observation metadata and executed `joint_commands.jsonl` sequences.
+- `workspace/`: the available workspace instructions, Python tools and skills.
+- `manifest.json`: per-file sizes and SHA-256 checksums.
+
+The videos show only the head camera. The trajectory bundles retain the images
+actually returned to the agent, which can include wrist-camera observations.
+They are agent-visible interaction records, not simulator checkpoints: raw
+RGB-D caches, provider wire-debug logs, runtime authentication files and
+encrypted transport payloads are excluded. Credentials and machine-local
+service addresses are redacted; the task prompts remain unchanged.
+
+## Use a trajectory
+
+Download one episode with `huggingface_hub`:
+
+```python
+from huggingface_hub import hf_hub_download
+
+archive = hf_hub_download(
+    repo_id="BinceQu/RoboHarness-assets",
+    repo_type="dataset",
+    filename="astra-v2-behavior/trajectories/t08.tar.gz",
+    local_dir="roboharness-astra",
+)
+print(archive)
+```
+
+Extract each archive into its own directory, then read `prompt.txt` and
+`episode.json`. Follow the conversation in `agent/` and the action/observation
+sequence in `tool_calls/`. `joint_commands.jsonl` records the executed actions;
+an archived workspace snapshot alone is not a standalone simulator installation.
+
+## Shared setup
+
+GPT-6 Astra uses native Codex CLI 0.161.0 with medium reasoning effort and auto
+reasoning summaries, inside the RoboHarness V2 R1 Pro workspace. The task prompt
+and readable Python tools provide access to perception and the robot's joint
+controller. The four skills are `behavior-v2-baseline`, `pick-up-object`,
+`place-object-in-container` and `open-doors-and-drawers`.
+
+The benchmark uses official evaluator v3.9.3, public instance 301, rollout 0
+and seed 0. Per-task tick budgets are included in `episodes.json`. All tasks
+use the same agent setup; each has its own task instruction. The release
+contains one counted attempt per task, with its source-attempt identifier.

astra-v2-behavior/checksums.json

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astra-v2-behavior/estimates.json

@@ -0,0 +1,16 @@
+{
+  "t08": {
+    "q": 0.5,
+    "source": "video_estimate",
+    "last_recorded_tick": 11904,
+    "reviewed_video_seconds": [0, 396.8],
+    "conditions": [
+      {"condition": "Toaster inside the chosen cabinet", "estimated_satisfied": true, "credit": 0.25},
+      {"condition": "French press inside the same cabinet", "estimated_satisfied": true, "credit": 0.25},
+      {"condition": "Food processor inside the same cabinet", "estimated_satisfied": false, "credit": 0},
+      {"condition": "Cabinet closed", "estimated_satisfied": false, "credit": 0}
+    ],
+    "evidence": "The final head-camera frames show the toaster and French press on the lower shelf of the same cabinet. The food processor is still held outside the cabinet, and its doors remain open. The final agent messages describe recovering and regrasping the processor after it fell back onto the countertop.",
+    "limitation": "Visual estimate at the recorded endpoint; the evaluator did not produce a final score. Inside/open predicates cannot be verified exactly from RGB alone. No credit is assigned for actions that might have occurred after the recording stopped."
+  }
+}

astra-v2-behavior/index.csv

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