Release 10,000 benchmark-disjoint PDBThink coordinate tasks

LICENSE

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README.md

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+---
+pretty_name: PDBThink Coordinate Tasks
+license: apache-2.0
+language: [en]
+task_categories: [text-generation]
+tags: [protein, structural-biology, coordinate-reasoning, harbor, reinforcement-learning, no-tools]
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: data/train-*.parquet
+      - split: validation
+        path: data/validation-*.parquet
+      - split: test
+        path: data/test-*.parquet
+---
+
+# PDBThink Coordinate Tasks
+
+10,000 new coordinate-interpretation tasks across all 19 active PDBThink families,
+from 1,922 experimental PDB entries in 1,249 source groups.
+Version 1.0.0; deterministic seed 2026100101.
+
+The model receives sanitised, rotated, rounded protein coordinates and a question.
+It must answer without tools. This release contains **no sequence-to-structure
+prediction tasks and no retired MECH tasks**. It is intended for additional evaluation,
+RL with deterministic rewards, and generating oracle-checked SFT demonstrations.
+
+## Relationship to the benchmark
+
+These are new tasks, not the published benchmark questions. Acquisition excluded every
+source configured in the frozen benchmark inventory, exact full-entity and observed-chain
+protein sequences, and RCSB 30% sequence clusters associated with those sources. Every
+protein partner in a candidate entry was audited, even when only one chain was shown.
+The frozen inventory, source checks and file hashes are in `audits/` and `manifest.json`.
+All released source, sequence and cluster intersections with that inventory are zero.
+This does **not** establish absence from foundation-model pretraining.
+
+Gold answers are recomputed from the coordinates actually shown, after transformation,
+rounding and permitted cropping, and checked again after parsing the displayed PDB text.
+Existing PDBThink operational definitions and family oracles are used unchanged.
+Scientific ambiguities and failed generation criteria are recorded in `ledger.parquet`.
+This is an automatically verified training/evaluation release, not a curator-reviewed benchmark.
+
+## Format
+
+The archive columns follow [Open Athena Task Trove](https://huggingface.co/datasets/open-athena/task-trove):
+`path`, `source`, `family`, `template_id`, `converter`, `mode`, `dockerfile_id`, `language`,
+`tags`, `has_solution`, `task_binary`, and `solution_binary`.
+Each binary is a gzip-compressed tar archive with deterministic member order and timestamps.
+
+`task_binary` contains `instruction.md`, `task.toml`, `prompt.json`, `environment/Dockerfile`,
+`tests/test.sh`, `tests/verifier.toml`, and a self-contained Python verifier with hidden gold.
+**Oracle solutions are separate in `solution_binary`**, never baked into the environment.
+The custom `pdbthink-coordinate` verifier is bundled; it is not a built-in tasktrove-verify mode.
+The verifier writes exact correctness to `/logs/verifier/reward.txt` and diagnostic partial
+credit to `details.json`. Contact sets must be completely correct for unit reward.
+
+Additional columns include `split`, `source_group`, `input_tokens`, `atom_count`,
+`answer_schema`, `prompt_sha256`, `semantic_key`, `task_sha256`, `source_entries`, and
+`provenance`. Provenance and test/solution files are evaluator-only and must never be
+included in a model prompt. Token counts use cl100k_base as a reference; compute exact
+native token counts before selecting an evaluation cohort or assigning output budgets.
+
+```python
+from datasets import load_dataset
+tasks = load_dataset("open-athena/pdbthink-coordinate-tasks", split="train")
+contacts = tasks.filter(lambda row: row["family"] in ["S06", "I01"])
+```
+
+## Tool-free execution
+
+Ordinary terminal agents do not satisfy this scientific protocol. The source snapshot includes
+`pdbthink.taskgen.no_tools_agent:CoordinateNoToolsAgent`, a Harbor adapter which sends only
+the system/user prompt, explicitly disables model tools and the OpenRouter web plugin,
+retains raw responses, audits tool events, and writes the returned answer to `/app/answer.txt`
+on the host's behalf. It never executes a model-generated command or tool call.
+Use an exact per-prompt budget manifest containing native input counts, context and output
+limits, tokenizer revision and endpoint-limit provenance. The adapter allocates the largest
+supported output budget that fits. Truncated responses remain flagged for budget audit.
+
+For offline oracle validation only, unpack `solution_binary` beside the task and run Harbor's
+oracle agent. Do not unpack oracle solutions into an evaluated model's environment.
+For SFT generation, provide only `prompt.json` to the teacher; check its response using the
+same verifier. Oracle answer files are final answers, not teacher-written worked solutions.
+
+## Splits and composition
+
+All entries connected by exact protein sequences or RCSB 30% clusters stay in one split.
+The target allocation is 90% train / 5% validation / 5% test at source-group level, so task
+counts need not have those exact proportions. Do not randomly split rows or rotate a
+training structure and call it an independent held-out example. Multiple tasks may share
+a source structure; no task is counted solely because of a different rigid rotation.
+
+| Split | Tasks |
+|---|---:|
+| train | 9157 |
+| test | 385 |
+| validation | 458 |
+
+| Family | Tasks |
+|---|---:|
+| G01 | 589 |
+| G02 | 589 |
+| G03 | 589 |
+| G04 | 232 |
+| I01 | 228 |
+| N01 | 588 |
+| P01 | 589 |
+| P02 | 589 |
+| P03 | 589 |
+| S01 | 589 |
+| S02 | 534 |
+| S03 | 589 |
+| S04 | 589 |
+| S05 | 588 |
+| S06 | 355 |
+| S07 | 438 |
+| S08 | 560 |
+| S09 | 588 |
+| T01 | 588 |
+
+The selector balances families subject to the available unambiguous, non-overlapping
+source pool. Family counts and categorical label distributions are recorded in the manifest.
+
+## Reproduction and licence
+
+`generator_source.tar.gz` contains the Python package, versioned definitions and project
+metadata. `reproduction_inputs.tar.gz` contains the frozen source selections, exclusion
+inventory, sequence-cluster snapshots and acquisition audits; unpack it into the work directory.
+Acquisition is the network stage; generation, verification and packaging run offline.
+Source selections, raw-source hashes and exclusion snapshots are retained for audit.
+See the bundled `pdbthink.taskgen` CLI and `manifest.json` for build settings and code hashes.
+
+Task-generation code is distributed under the repository's Apache 2.0 licence. Protein coordinates
+come from the public Protein Data Bank; original entries are identified in evaluator-only
+provenance. No assertion of experimental folding ground truth is made beyond the supplied
+coordinate-reasoning definitions.

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USAGE.md

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+# Coordinate tasks for evaluation and post-training
+
+The `pdbthink.taskgen` pipeline packages new tasks for all 19 active coordinate
+families. It reuses the existing generators, operational definitions and answer
+scorers. It does not modify the frozen benchmark or include MECH/F01/F02.
+
+Install `.[taskgen,tokenizer]` for acquisition, generation and Parquet export.
+Harbor integration additionally needs Python 3.12+ and `.[harbor]`.
+
+## Build stages
+
+```bash
+python -m pdbthink.taskgen acquire --work data/taskgen_v1 --workers 12
+python -m pdbthink.taskgen acquire-pairs --work data/taskgen_v1 --workers 8
+python -m pdbthink.taskgen build --work data/taskgen_v1 --workers 24
+python -m pdbthink.taskgen build-pairs --work data/taskgen_v1 --workers 16
+python -m pdbthink.taskgen export --work data/taskgen_v1 --count 10000
+python -m pdbthink.taskgen validate --dataset data/taskgen_v1/release --workers 16
+```
+
+Only acquisition uses the network. Source selections, sequence clusters and
+benchmark exclusions are frozen before generation. Source-view shards make
+builds resumable; use a fresh work directory when changing the seed, per-source
+sampling or scientific implementation. A release directory cannot be silently
+overwritten.
+
+The source pool uses the existing frozen RCSB expansion queries for small
+proteins, ligands and interfaces, with a separate query for phosphoproteins.
+The exclusion snapshot covers every configured benchmark source, its complete
+and observed protein sequences, and every RCSB 30% sequence cluster containing
+one of those entries. Candidate entries are checked across all protein
+partners, even when the task shows one chain. The snapshot includes its input
+file hashes and fails closed if a benchmark source cannot be sequence-audited.
+Published audit records contain sequence hashes; they do not distribute the
+excluded benchmark's raw sequences.
+
+T01 uses additional experimental structures in the same RCSB 90% sequence
+cluster, then applies the benchmark's sequence mapping, alignment and
+unambiguous contact-change checks. Distinct candidate-pair lists are distinct
+questions; different rigid rotations alone never count as new instances.
+
+Every retained task has its gold recomputed from the rotated, rounded, possibly
+cropped coordinates. A separate parser reconstructs the structures from the
+actual PDB text and runs the oracle again. Disagreement rejects the task.
+The verifier also checks that the oracle answer receives exact reward 1 and
+that empty and deliberately incorrect answers receive exact reward 0.
+
+## Release format
+
+Parquet rows use Task Trove's metadata columns, `task_binary`, and separate
+`solution_binary`. Archives have deterministic timestamps and contain normal
+Harbor 1.4 task directories. Hidden tests include a self-contained copy of the
+coordinate answer parser/scorer; no installation or model judge is needed at
+verification time. The custom `pdbthink-coordinate` verifier mode is bundled
+and is not a built-in mode of the separate `tasktrove-verify` package.
+
+The primary reward is exact correctness, including the benchmark's numerical
+tolerances. Partial-set F1 and other diagnostics are written separately. Gold,
+provenance, oracle solutions and source identifiers are evaluator-only data.
+Teacher/Snowball inputs must come exclusively from `prompt.json` or the exact
+Harbor instruction.
+
+All entries connected by protein sequences, RCSB 30% clusters, or a two-state
+pair belong to one source group. Groups are assigned deterministically to
+train/validation/test in a target 90/5/5 allocation. Multiple questions may
+share a protein, but related source groups never cross these splits. These
+checks establish separation from the frozen PDBThink inventory, not freedom
+from all foundation-model pretraining data.
+
+## Tool-free Harbor adapter
+
+Download and unpack a chosen evaluation cohort:
+
+```bash
+hf download open-athena/pdbthink-coordinate-tasks --repo-type dataset --local-dir coordinate-tasks
+python -m pdbthink.taskgen unpack --dataset coordinate-tasks --output harbor-tasks --split test --families G01 S06 I01 --limit 100
+```
+
+This leaves oracle solutions out of the task directories. Add `--include-solutions`
+only when preparing an offline Harbor oracle check.
+
+Use `pdbthink.taskgen.no_tools_agent:CoordinateNoToolsAgent` with Harbor's custom
+agent import option. It accepts `endpoint`, `api_key_env`, `budget_manifest`,
+and optional `request_extra`. The host sends one OpenAI-compatible chat
+completion with tools explicitly disabled, audits the raw response, and writes
+the returned text to `/app/answer.txt`. No model-generated tool request or
+command is executed. Generic terminal agents do not satisfy this protocol.
+
+The budget manifest is a JSON object keyed by the row's `prompt_sha256`:
+
+```json
+{
+  "<prompt_sha256>": {
+    "input_tokens": 15000,
+    "context_window": 32768,
+    "native_output_limit": 32768,
+    "tokenizer_revision": "<exact native tokenizer and chat-template revision>",
+    "endpoint_limit_source": "<verified endpoint configuration or documentation>"
+  }
+}
+```
+
+These numbers are illustrative. Populate them by tokenising each exact prompt
+with the endpoint's actual tokenizer, chat template and thinking configuration.
+The adapter requests `min(native_output_limit, context_window - input_tokens)`;
+it never substitutes the dataset's reference cl100k count. Raw requests,
+responses, budgets, usage and termination reasons are retained. Truncation
+requires an endpoint/budget audit before an evaluation is treated as final.
+No provider call is made by task generation or release validation.
+
+For mechanical Harbor validation, merge the task and solution archives on the
+host and use the oracle agent. Do not merge oracle archives for actual model
+evaluation. For teacher-generated SFT, retain only verified outputs, inspect
+important intermediate calculations, and keep the grouped split boundaries.

audits/phosphoproteins.query.json

@@ -0,0 +1,67 @@
+{
+  "query": {
+    "type": "group",
+    "logical_operator": "and",
+    "nodes": [
+      {
+        "type": "terminal",
+        "service": "text",
+        "parameters": {
+          "attribute": "entity_poly.rcsb_entity_polymer_type",
+          "operator": "exact_match",
+          "value": "Protein"
+        }
+      },
+      {
+        "type": "terminal",
+        "service": "text",
+        "parameters": {
+          "attribute": "rcsb_polymer_entity_container_identifiers.chem_comp_monomers",
+          "operator": "in",
+          "value": [
+            "SEP",
+            "TPO",
+            "PTR"
+          ]
+        }
+      },
+      {
+        "type": "terminal",
+        "service": "text",
+        "parameters": {
+          "attribute": "entity_poly.rcsb_sample_sequence_length",
+          "operator": "range",
+          "value": {
+            "from": 10,
+            "to": 195
+          }
+        }
+      },
+      {
+        "type": "terminal",
+        "service": "text",
+        "parameters": {
+          "attribute": "rcsb_entry_info.resolution_combined",
+          "operator": "less_or_equal",
+          "value": 3.0
+        }
+      },
+      {
+        "type": "terminal",
+        "service": "text",
+        "parameters": {
+          "attribute": "exptl.method",
+          "operator": "exact_match",
+          "value": "X-RAY DIFFRACTION"
+        }
+      }
+    ]
+  },
+  "return_type": "polymer_entity",
+  "request_options": {
+    "paginate": {
+      "start": 0,
+      "rows": 10000
+    }
+  }
+}

audits/pool_summary.json

@@ -0,0 +1,23 @@
+{
+  "source_views": 3156,
+  "counts": {
+    "G01": 4855,
+    "G02": 5172,
+    "G03": 4845,
+    "G04": 232,
+    "I01": 230,
+    "N01": 4163,
+    "P01": 2826,
+    "P02": 2501,
+    "P03": 5152,
+    "S01": 3680,
+    "S02": 534,
+    "S03": 5157,
+    "S04": 5068,
+    "S05": 1862,
+    "S06": 355,
+    "S07": 438,
+    "S08": 560,
+    "S09": 5170
+  }
+}

audits/selection.json

@@ -0,0 +1,5688 @@
+{
+  "seed": 2026100101,
+  "choices": {
+    "interfaces": [
+      "3IGE_1",
+      "2AHY_1",
+      "5Z4Y_1",
+      "5HMA_1",
+      "6HBA_1",
+      "3ZZL_1",
+      "3SO6_1",
+      "7T8I_1",
+      "2OJL_1",
+      "2C9L_3",
+      "4G5A_1",
+      "8B6E_1",
+      "3GLA_1",
+      "7K9B_1",
+      "3LAE_1",
+      "8UTK_1",
+      "7AGW_1",
+      "2XCJ_1",
+      "4WTW_1",
+      "4QUT_1",
+      "3LNQ_1",
+      "5WO1_1",
+      "2GBJ_1",
+      "6CZJ_1",
+      "9NKN_1",
+      "2Q3G_1",
+      "3ULR_2",
+      "1UCR_1",
+      "13CT_1",
+      "5H0U_1",
+      "9LNT_1",
+      "1E8A_1",
+      "3JVK_1",
+      "6J4K_1",
+      "7R1L_1",
+      "2ZW2_1",
+      "9OVI_1",
+      "3H0I_1",
+      "2PMY_1",
+      "4CC2_1",
+      "3LWE_1",
+      "5H7H_1",
+      "9CI7_1",
+      "4I8B_1",
+      "2FCW_2",
+      "1LXD_1",
+      "4ATH_1",
+      "5H6X_1",
+      "2GBO_1",
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+      "4UZZ_2",
+      "7KIK_1",
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+      "1D1M_1",
+      "4ZV5_1",
+      "6I31_1",
+      "9SBG_1",
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+      "2XSD_3",
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+      "4DJC_2",
+      "2OTT_1",
+      "1LUZ_1",
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+    ],
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audits/source_groups.json

@@ -0,0 +1,1924 @@
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checks.json

@@ -0,0 +1,35 @@
+{
+  "unit_tests": {
+    "command": "python -m pytest -q",
+    "passed": 472
+  },
+  "benchmark_smoke": {
+    "instances": 19,
+    "renders": 64,
+    "validation_errors": 0,
+    "mock_gold_macro": 1.0,
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+  "harbor_version": "0.23.0",
+  "harbor": {
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+      "trials": 19,
+      "errors": 0,
+      "mean_reward": 1.0
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+    "nop": {
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+      "trials": 19,
+      "errors": 0,
+      "mean_reward": 0.0
+    }
+  },
+  "tool_free_adapter": {
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+    "exact_prompt_checked": true,
+    "budget_checked": true,
+    "response_handoff_checked": true
+  },
+  "live_model_calls": 0
+}

context_lengths.json

@@ -0,0 +1,120 @@
+{
+  "tokenizer": "cl100k_base; reference counts only, not native model counts",
+  "guidance": "Compute exact native prompt tokens and reserve the endpoint-supported output budget. Not all tasks fit 32k contexts.",
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+    "Tool-free evaluation requires the supplied adapter or equivalent enforced controls."
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+}

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