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54ccd67ca8
Builds on #4824 by Nick (merged into main). ### Workflow 1. Each branch is resolved to one SHA. 2. Each shard fetches that exact SHA. 3. The workflow overlays these source directories: - `libs/deepagents` - `libs/code` - `libs/partners/quickjs` 4. These are copied into the Harbor LangGraph project's `.local_deps`. 5. Harbor installs those local source packages when constructing the sandbox environment. 6. The sandboxed agent imports the installed packages normally. ### What this PR adds - Resolves the branch's head via `git ls-remote --exit-code refs/heads/<branch>` and hardens it as the SHA (previously used `refs/<branch>` and took the first result). - Verifies `FETCH_HEAD` matches `BRANCH_SHA`; fails the shard on mismatch. - Adds branch-to-SHA mappings to the GitHub workflow summary — all leaves include a `source_sha`, and prep emits a sources list of `{branch, sha}` pairs. - Adds SHA provenance throughout result files: - `_harbor_run.yml` passes `branch_sha` to the shard aggregator. - Each leaf `summary.json` records `source_sha`. - Each combined Unified result row records `source_sha`. - Missing-leaf placeholder rows retain the expected SHA, making it easy to identify the redeployment command if a shard fails. - Adds test coverage for all of the above. ### Notes - No product wheels — unnecessary for this change. - Evaluator harness stays pinned to the workflow reference (main branch). - `unified_evals.yml` still supports single-branch testing via the standard workflow input. - No trace analysis, retry/timeout controls, or LangSmith usage/cost analysis (planned for future PRs). ### Tests - 141 focused prep, workflow, provenance, and aggregation tests passed. - Ruff checks passed on all changed Python files. - Both modified workflow YAML files parsed successfully. - One unrelated macOS temp-directory test was excluded — system Python creates an xcrun cache entry in its asserted-empty temp directory. --------- Co-authored-by: Nick Hollon <nick.hollon@langchain.dev> Co-authored-by: Mason Daugherty <github@mdrxy.com>
576 lines
19 KiB
Python
576 lines
19 KiB
Python
"""Tests for aggregate_shards.py.
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Runs under pytest, and also standalone via `python3 test_aggregate_shards.py`
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(a minimal runner at the bottom provides a temp dir to tests that need one).
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"""
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from __future__ import annotations
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import json
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import os
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import sys
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from pathlib import Path
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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import aggregate_shards as agg
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import aggregate_unified as unified
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def _write_trial(
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dirpath: Path,
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task,
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reward=None,
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errored=False,
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model="m1",
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job_id="job1",
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include_config=True,
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):
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"""Create a trial folder with a result.json shaped like Harbor's.
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`reward` is written verbatim, so a test can pass a non-numeric value (e.g. a
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string) to exercise coercion/malformed handling. Set `include_config=False`
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to omit the `config` block entirely (an early-failing trial).
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"""
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dirpath.mkdir(parents=True, exist_ok=True)
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result = {
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"task_name": task,
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"verifier_result": None if errored else {"rewards": {"reward": reward}},
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"exception_info": {"exception_type": "SomeError"} if errored else None,
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}
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if include_config:
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result["config"] = {"agent": {"model_name": model}, "job_id": job_id}
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(dirpath / "result.json").write_text(json.dumps(result))
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def test_aggregate_and_summary(tmp_path: Path):
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specs = {
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"taskA": [1.0, 0.0, 0.0], # 1 of 3
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"taskB": [0.0, 0.0, 0.0], # 0 of 3
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"taskC": [1.0, 1.0, 1.0], # 3 of 3
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}
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i = 0
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# A job-level result.json (no task_name) that must be ignored.
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(tmp_path / "job").mkdir()
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(tmp_path / "job" / "result.json").write_text(json.dumps({"stats": {"n": 9}}))
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for task, rewards in specs.items():
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for reward in rewards:
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_write_trial(tmp_path / f"{task}__{i}", task, reward=reward)
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i += 1
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result = agg.aggregate(tmp_path)
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by_task = result.by_task
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assert by_task["taskA"] == {"trials": 3, "passed": 1, "errored": 0}
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assert by_task["taskB"] == {"trials": 3, "passed": 0, "errored": 0}
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assert by_task["taskC"] == {"trials": 3, "passed": 3, "errored": 0}
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assert result.models == {"m1"}
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assert result.job_ids == {"job1"}
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assert result.empty_shards == set()
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assert result.skipped_files == 0
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assert result.malformed_rewards == 0
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dataset_passk, avg_at_k, totals, per_task = agg.build_summary(by_task, 3)
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# pass@K (K=3), scalar: mean over tasks of "passed at least once" = (1+0+1)/3.
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assert abs(dataset_passk - (1 + 0 + 1) / 3) < 1e-6
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assert totals == {
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"tasks": 3,
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"trials": 9,
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"expected_trials": 9,
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"passed": 4,
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"errored": 0,
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}
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# avg@K: passing trials / expected trials = 4 / (3 tasks * 3 rollouts) = 4/9.
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assert abs(avg_at_k - 4 / 9) < 1e-6
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assert len(per_task) == 3
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# per-task pass@K is a scalar under a dynamic "pass@{K}" key.
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assert {r["task"]: r["pass@3"] for r in per_task} == {
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"taskA": 1.0,
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"taskB": 0.0,
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"taskC": 1.0,
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}
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def test_errored_and_missing_count_as_fail(tmp_path: Path):
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_write_trial(tmp_path / "t__0", "taskX", reward=1.0)
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_write_trial(
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tmp_path / "t__1", "taskX", errored=True
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) # exception -> fail + errored
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_write_trial(
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tmp_path / "t__2", "taskX", reward=None
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) # no verifier reward -> fail + errored
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by_task = agg.aggregate(tmp_path).by_task
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assert by_task["taskX"] == {"trials": 3, "passed": 1, "errored": 2}
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def test_partial_reward_is_not_a_pass(tmp_path: Path):
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_write_trial(tmp_path / "t__0", "taskY", reward=0.5)
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by_task = agg.aggregate(tmp_path).by_task
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assert by_task["taskY"] == {"trials": 1, "passed": 0, "errored": 0}
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def test_end_to_end_writes_files(tmp_path: Path):
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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_write_trial(tmp_path / "a__1", "taskA", reward=0.0)
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out = tmp_path / "out"
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rc = agg.main(
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[str(tmp_path), "--rollouts", "2", "--out-dir", str(out), "--dataset", "ds/x"]
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)
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assert rc == 0
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summary = json.loads((out / "summary.json").read_text())
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assert summary["dataset"] == "ds/x"
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assert summary["model"] == "m1"
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assert summary["totals"] == {
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"tasks": 1,
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"trials": 2,
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"expected_trials": 2,
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"passed": 1,
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"errored": 0,
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}
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assert summary["pass@2"] == 1.0 # pass@2: taskA passed at least once
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assert summary["avg@2"] == 0.5 # 1 passing trial of 2 expected
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assert summary["incomplete"] is False # 2 trials == 2 expected, no shard gate
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rows = [
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json.loads(line) for line in (out / "per_task.jsonl").read_text().splitlines()
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]
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assert rows == [
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{"task": "taskA", "trials": 2, "passed": 1, "errored": 0, "pass@2": 1.0}
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]
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def test_missing_rollouts_count_as_failures(tmp_path: Path):
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# taskA ran only 1 of 3 rollouts (a shard died mid-task) and it passed.
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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out = tmp_path / "out"
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rc = agg.main([str(tmp_path), "--rollouts", "3", "--out-dir", str(out)])
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assert rc == 0
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summary = json.loads((out / "summary.json").read_text())
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# pass@3 is 1.0 (it did pass once), but avg@3 must be 1/3, not 1/1.
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assert summary["pass@3"] == 1.0
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assert abs(summary["avg@3"] - 1 / 3) < 1e-6
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assert summary["totals"]["trials"] == 1
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assert summary["totals"]["expected_trials"] == 3
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assert summary["incomplete"] is True # 1 trial < 3 expected
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def test_shard_failure_flags_incomplete(tmp_path: Path):
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# A complete task, but the matrix job did not fully succeed (a shard failed).
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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_write_trial(tmp_path / "a__1", "taskA", reward=1.0)
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out = tmp_path / "out"
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rc = agg.main(
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[
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str(tmp_path),
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"--rollouts",
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"2",
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"--harbor-result",
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"failure",
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"--out-dir",
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str(out),
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]
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)
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assert rc == 0
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summary = json.loads((out / "summary.json").read_text())
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assert summary["harbor_result"] == "failure"
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assert summary["incomplete"] is True
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def test_filtered_run_with_success_is_not_incomplete(tmp_path: Path):
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# Only one task's results landed (other shard slices were empty by task
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# filtering), but every present task ran all K rollouts and the job succeeded.
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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_write_trial(tmp_path / "a__1", "taskA", reward=0.0)
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out = tmp_path / "out"
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rc = agg.main(
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[
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str(tmp_path),
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"--rollouts",
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"2",
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"--harbor-result",
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"success",
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"--out-dir",
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str(out),
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]
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)
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assert rc == 0
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summary = json.loads((out / "summary.json").read_text())
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assert summary["shards_found"] == 1
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assert summary["incomplete"] is False # empty shards are not losses
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def test_multiple_models_is_rejected(tmp_path: Path):
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0, model="m1")
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_write_trial(tmp_path / "a__1", "taskA", reward=0.0, model="m2")
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try:
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agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(tmp_path / "o")])
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except SystemExit as exc:
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assert exc.code not in (0, None)
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return
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raise AssertionError("expected SystemExit for multiple models")
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def test_empty_tree_is_no_op(tmp_path: Path):
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rc = agg.main([str(tmp_path), "--rollouts", "3", "--out-dir", str(tmp_path)])
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assert rc == 0
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summary = json.loads((tmp_path / "summary.json").read_text())
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assert summary["totals"]["tasks"] == 0
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assert summary["pass@3"] is None
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# No data -> avg@K abstains with None (not a concrete 0.0 that would drag a
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# future cross-category average downward).
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assert summary["avg@3"] is None
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assert summary["incomplete"] is False # nothing expected, nothing missing
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def test_unreadable_and_non_object_json_are_skipped_and_flag_incomplete(tmp_path: Path):
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# One good trial, one corrupt file, one valid-but-non-object result.json.
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_write_trial(tmp_path / "good__0", "taskA", reward=1.0)
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(tmp_path / "corrupt").mkdir()
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(tmp_path / "corrupt" / "result.json").write_text("{ not valid json")
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(tmp_path / "array").mkdir()
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(tmp_path / "array" / "result.json").write_text("[1, 2, 3]")
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result = agg.aggregate(tmp_path)
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# The good trial still tallies; the two bad files are counted as skipped.
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assert result.by_task["taskA"] == {"trials": 1, "passed": 1, "errored": 0}
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assert result.skipped_files == 2
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out = tmp_path / "out"
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rc = agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(out)])
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assert rc == 0
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summary = json.loads((out / "summary.json").read_text())
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assert summary["skipped_files"] == 2
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assert summary["incomplete"] is True # a lost result can't be vouched for
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def test_numeric_string_reward_is_coerced(tmp_path: Path):
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# Harbor could serialize a reward as a string; it must not be a silent fail.
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_write_trial(tmp_path / "t__0", "taskA", reward="1.0")
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result = agg.aggregate(tmp_path)
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assert result.by_task["taskA"] == {"trials": 1, "passed": 1, "errored": 0}
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assert result.malformed_rewards == 0
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def test_non_numeric_reward_is_malformed_and_flags_incomplete(tmp_path: Path):
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# A present-but-unparseable reward is counted as errored AND flagged malformed.
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_write_trial(tmp_path / "t__0", "taskA", reward="not-a-number")
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result = agg.aggregate(tmp_path)
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assert result.by_task["taskA"] == {"trials": 1, "passed": 0, "errored": 1}
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assert result.malformed_rewards == 1
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out = tmp_path / "out"
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agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(out)])
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summary = json.loads((out / "summary.json").read_text())
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assert summary["incomplete"] is True
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def test_errored_trial_with_reward_counts_as_pass_and_error(tmp_path: Path):
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# exception_info is diagnostic. A trial can still pass when Harbor records a
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# verifier-passing reward alongside the exception.
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dirpath = tmp_path / "t__0"
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dirpath.mkdir()
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(dirpath / "result.json").write_text(
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json.dumps(
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{
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"task_name": "taskA",
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"config": {"agent": {"model_name": "m1"}, "job_id": "job1"},
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"verifier_result": {"rewards": {"reward": 1.0}},
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"exception_info": {"exception_type": "BoomError"},
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}
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)
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)
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by_task = agg.aggregate(tmp_path).by_task
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assert by_task["taskA"] == {"trials": 1, "passed": 1, "errored": 1}
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def test_missing_config_is_handled_gracefully(tmp_path: Path):
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# A trial that failed before config was written: no model, no job_id.
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_write_trial(tmp_path / "t__0", "taskA", reward=1.0, include_config=False)
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result = agg.aggregate(tmp_path)
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assert result.by_task["taskA"] == {"trials": 1, "passed": 1, "errored": 0}
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assert result.models == set()
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assert result.job_ids == set()
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out = tmp_path / "out"
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agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(out)])
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summary = json.loads((out / "summary.json").read_text())
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assert summary["model"] is None
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assert summary["shards_found"] == 0
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def test_rollouts_below_one_is_rejected(tmp_path: Path):
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try:
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agg.main([str(tmp_path), "--rollouts", "0", "--out-dir", str(tmp_path)])
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except SystemExit as exc:
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assert exc.code not in (0, None)
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return
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raise AssertionError("expected SystemExit for --rollouts 0")
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def test_duplicate_rollouts_flag_incomplete(tmp_path: Path):
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# A task with MORE than K trials (e.g. a double-download) must not silently
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# inflate avg@K past 1.0 without flagging the run.
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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_write_trial(tmp_path / "a__1", "taskA", reward=1.0)
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out = tmp_path / "out"
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agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(out)])
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summary = json.loads((out / "summary.json").read_text())
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assert summary["totals"]["trials"] == 2
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assert summary["totals"]["expected_trials"] == 1
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assert summary["totals"]["passed"] == 2
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assert summary["avg@1"] == 1.0
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assert summary["incomplete"] is True # trials != expected
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def test_duplicate_rollout_summary_is_accepted_by_unified_aggregator(
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tmp_path: Path,
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):
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
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_write_trial(tmp_path / "a__1", "taskA", reward=1.0)
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out = tmp_path / "out"
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agg.main(
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[
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str(tmp_path),
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"--rollouts",
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"1",
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"--out-dir",
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str(out),
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"--model",
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"m1",
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"--category",
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"context",
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]
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)
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leaf = unified.read_leaf(out, expected_rollouts=1)
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assert leaf["model"] == "m1"
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assert leaf["category"] == "context"
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assert leaf["avg_at_k"] == 1.0
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assert leaf["incomplete"] is True
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def test_per_task_rollout_mismatches_do_not_cancel(tmp_path: Path):
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for index in range(3):
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_write_trial(tmp_path / f"a__{index}", "taskA", reward=1.0)
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_write_trial(tmp_path / "b__0", "taskB", reward=1.0)
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out = tmp_path / "out"
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agg.main([str(tmp_path), "--rollouts", "2", "--out-dir", str(out)])
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summary = json.loads((out / "summary.json").read_text())
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assert summary["totals"]["trials"] == 4
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assert summary["totals"]["expected_trials"] == 4
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assert summary["totals"]["passed"] == 4
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assert summary["avg@2"] == 0.75
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assert summary["incomplete"] is True
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def test_expected_shards_shortfall_flags_incomplete(tmp_path: Path):
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# Two full rollouts landed under one job_id, but the caller declared 3 shards.
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0, job_id="job1")
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_write_trial(tmp_path / "a__1", "taskA", reward=0.0, job_id="job1")
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out = tmp_path / "out"
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agg.main(
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[
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str(tmp_path),
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"--rollouts",
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"2",
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"--expected-shards",
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"3",
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"--harbor-result",
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"success",
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"--out-dir",
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str(out),
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]
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)
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summary = json.loads((out / "summary.json").read_text())
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assert summary["shards_found"] == 1
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assert summary["expected_shards"] == 3
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assert summary["incomplete"] is True # 1 shard reported, 3 expected
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def test_successful_empty_shards_satisfy_expected_count(tmp_path: Path):
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_write_trial(tmp_path / "a__0", "taskA", reward=1.0, job_id="job1")
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_write_trial(tmp_path / "b__0", "taskB", reward=1.0, job_id="job2")
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empty_marker = tmp_path / "shard-2" / "empty-shard-2"
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empty_marker.parent.mkdir()
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empty_marker.touch()
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out = tmp_path / "out"
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agg.main(
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[
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str(tmp_path),
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"--rollouts",
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"1",
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"--expected-shards",
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"3",
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"--harbor-result",
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"success",
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"--out-dir",
|
|
str(out),
|
|
]
|
|
)
|
|
|
|
result = agg.aggregate(tmp_path)
|
|
assert result.empty_shards == {"empty-shard-2"}
|
|
summary = json.loads((out / "summary.json").read_text())
|
|
assert summary["shards_found"] == 3
|
|
assert summary["expected_shards"] == 3
|
|
assert summary["incomplete"] is False
|
|
|
|
|
|
def test_writes_github_step_summary(tmp_path: Path):
|
|
_write_trial(tmp_path / "a__0", "taskA", reward=1.0)
|
|
step_file = tmp_path / "step_summary.md"
|
|
step_file.touch()
|
|
prev = os.environ.get("GITHUB_STEP_SUMMARY")
|
|
os.environ["GITHUB_STEP_SUMMARY"] = str(step_file)
|
|
try:
|
|
agg.main([str(tmp_path), "--rollouts", "1", "--out-dir", str(tmp_path / "out")])
|
|
finally:
|
|
if prev is None:
|
|
os.environ.pop("GITHUB_STEP_SUMMARY", None)
|
|
else:
|
|
os.environ["GITHUB_STEP_SUMMARY"] = prev
|
|
rendered = step_file.read_text()
|
|
assert "## Harbor results" in rendered
|
|
assert "| pass@1 |" in rendered
|
|
assert "| avg@1 |" in rendered
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import inspect
|
|
import tempfile
|
|
import traceback
|
|
|
|
tests = [
|
|
v for k, v in sorted(globals().items()) if k.startswith("test_") and callable(v)
|
|
]
|
|
failures = 0
|
|
for test in tests:
|
|
try:
|
|
if "tmp_path" in inspect.signature(test).parameters:
|
|
with tempfile.TemporaryDirectory() as tmp:
|
|
test(Path(tmp))
|
|
else:
|
|
test()
|
|
print(f"PASS {test.__name__}")
|
|
except Exception: # noqa: BLE001 - report and continue
|
|
failures += 1
|
|
print(f"FAIL {test.__name__}")
|
|
traceback.print_exc()
|
|
print(f"\n{len(tests) - failures}/{len(tests)} passed")
|
|
sys.exit(1 if failures else 0)
|
|
|
|
|
|
def test_model_and_category_recorded_authoritatively(tmp_path: Path):
|
|
# Empty root (the all-errored / null-model case): --model/--category are still
|
|
# recorded, so downstream tooling never sees a null model label.
|
|
out = tmp_path / "out"
|
|
rc = agg.main(
|
|
[
|
|
str(tmp_path),
|
|
"--rollouts",
|
|
"1",
|
|
"--out-dir",
|
|
str(out),
|
|
"--model",
|
|
"openai:gpt-5.6-luna",
|
|
"--category",
|
|
"autonomous",
|
|
]
|
|
)
|
|
assert rc == 0
|
|
summary = json.loads((out / "summary.json").read_text())
|
|
assert summary["model"] == "openai:gpt-5.6-luna"
|
|
assert summary["category"] == "autonomous"
|
|
|
|
|
|
def test_make_summary_records_config():
|
|
summary = agg.make_summary(
|
|
dataset="d",
|
|
model="openai:gpt",
|
|
category="autonomous",
|
|
config="bare",
|
|
branch=None,
|
|
source_sha=None,
|
|
rollouts=3,
|
|
shards_found=1,
|
|
expected_shards=1,
|
|
skipped_files=0,
|
|
harbor_result="success",
|
|
incomplete=False,
|
|
totals={
|
|
"tasks": 1,
|
|
"trials": 3,
|
|
"expected_trials": 3,
|
|
"passed": 1,
|
|
"errored": 0,
|
|
},
|
|
pass_at_k=1.0,
|
|
avg_at_k=1.0,
|
|
)
|
|
assert summary["config"] == "bare"
|
|
assert summary["model"] == "openai:gpt"
|
|
|
|
|
|
def test_main_cli_records_config(tmp_path):
|
|
root = tmp_path / "shards"
|
|
root.mkdir()
|
|
agg.main(
|
|
[
|
|
str(root),
|
|
"--rollouts",
|
|
"3",
|
|
"--config",
|
|
"bare",
|
|
"--model",
|
|
"openai:gpt",
|
|
"--category",
|
|
"autonomous",
|
|
"--dataset",
|
|
"d",
|
|
"--harbor-result",
|
|
"success",
|
|
]
|
|
)
|
|
summary = json.loads((root / "summary.json").read_text())
|
|
assert summary["config"] == "bare"
|
|
|
|
|
|
def test_make_summary_records_branch():
|
|
summary = agg.make_summary(
|
|
dataset="d",
|
|
model="openai:gpt",
|
|
category="autonomous",
|
|
config="bare",
|
|
branch="main",
|
|
source_sha="a" * 40,
|
|
rollouts=3,
|
|
shards_found=1,
|
|
expected_shards=1,
|
|
skipped_files=0,
|
|
harbor_result="success",
|
|
incomplete=False,
|
|
totals={"tasks": 1, "trials": 3, "expected_trials": 3, "passed": 1, "errored": 0},
|
|
pass_at_k=1.0,
|
|
avg_at_k=1.0,
|
|
)
|
|
assert summary["branch"] == "main"
|
|
assert summary["source_sha"] == "a" * 40
|
|
assert summary["config"] == "bare"
|
|
|
|
|
|
def test_main_cli_records_branch(tmp_path):
|
|
root = tmp_path / "shards"
|
|
root.mkdir()
|
|
agg.main(
|
|
[
|
|
str(root), "--rollouts", "3",
|
|
"--config", "bare", "--branch", "main",
|
|
"--model", "openai:gpt", "--category", "autonomous",
|
|
"--dataset", "d", "--harbor-result", "success",
|
|
]
|
|
)
|
|
summary = json.loads((root / "summary.json").read_text())
|
|
assert summary["branch"] == "main"
|