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0927f2dd9c
* Run reviewer eval in a GitHub Action; make dashboard a read-only progress view The dashboard launched the eval as a subprocess inside the serving deployment worker, so a container recycle killed long runs and discarded results that had already completed server-side. Move the harness to a workflow_dispatch Action (run on prod). run_eval now publishes status/progress/log-tail to the LangGraph store record the dashboard reads, so /admin/evals stays a live view; a killed Action surfaces as failed via the stale-heartbeat reconcile. * reviewer_eval workflow: pass inputs via env, no shell interpolation Addresses the reviewer finding: workflow_dispatch string inputs were interpolated into the run: block (limit unquoted), allowing shell injection in a job holding LANGSMITH/ANTHROPIC keys. Pass inputs through env and reference quoted "$VARS"; validate limit is numeric and build its flag in bash. --------- Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
132 lines
3.7 KiB
Python
132 lines
3.7 KiB
Python
from __future__ import annotations
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from typing import Any
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import pytest
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from agent.reviewer_findings import new_finding
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from evals.reviewer import target
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def test_eval_target_marks_runs_as_eval_dry_run(monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.delenv("REVIEWER_EVAL_MODEL_ID", raising=False)
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monkeypatch.delenv("REVIEWER_EVAL_REASONING_EFFORT", raising=False)
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configurable = target._build_configurable(
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{
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"repo": "acme/repo",
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"pr_number": 1,
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"pr_url": "https://github.com/acme/repo/pull/1",
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"base_sha": "base",
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"head_sha": "head",
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"head_ref": "branch",
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}
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)
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assert configurable["reviewer_eval"] is True
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assert configurable["eval"] is True
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assert configurable["__is_for_execution__"] is True
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assert "source" not in configurable
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def test_eval_target_passes_model_overrides(monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.setenv("REVIEWER_EVAL_MODEL_ID", "anthropic:claude-opus-4-8")
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monkeypatch.setenv("REVIEWER_EVAL_REASONING_EFFORT", "high")
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configurable = target._build_configurable(
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{
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"repo": "acme/repo",
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"pr_number": 1,
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"pr_url": "https://github.com/acme/repo/pull/1",
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"base_sha": "base",
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"head_sha": "head",
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"head_ref": "branch",
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}
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)
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assert configurable["reviewer_model_id"] == "anthropic:claude-opus-4-8"
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assert configurable["reviewer_reasoning_effort"] == "high"
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def _result_with_findings(findings: list[dict[str, Any]]) -> dict[str, Any]:
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return {"messages": [{"tool_calls": [{"name": "add_finding", "args": f} for f in findings]}]}
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def test_extract_comments_includes_all_confidences() -> None:
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result = _result_with_findings(
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[
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{
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"file": "a.py",
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"severity": "high",
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"confidence": "low",
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"description": "lo",
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"start_line": 1,
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"end_line": 1,
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},
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{
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"file": "b.py",
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"severity": "high",
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"confidence": "high",
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"description": "hi",
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"start_line": 2,
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"end_line": 2,
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},
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]
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)
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comments = target._extract_comments(result)
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assert {c["file"] for c in comments} == {"a.py", "b.py"}
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@pytest.mark.asyncio
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async def test_extract_surfaced_comments_uses_publish_filter(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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high = new_finding(
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severity="high",
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confidence="high",
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category="correctness",
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file="a.py",
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start_line=10,
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end_line=10,
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description="high signal",
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sha="head",
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finding_id="f_high",
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)
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low = new_finding(
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severity="low",
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confidence="high",
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category="style",
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file="b.py",
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start_line=20,
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end_line=20,
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description="low signal",
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sha="head",
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finding_id="f_low",
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)
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class Threads:
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async def get(self, _thread_id: str) -> dict[str, Any]:
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return {"metadata": {"findings": [high, low]}}
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class Client:
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threads = Threads()
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monkeypatch.setenv("REVIEWER_EVAL_SEVERITY_THRESHOLD", "medium")
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monkeypatch.setenv("REVIEWER_EVAL_CAP", "4")
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comments = await target._extract_surfaced_comments(Client(), "tid")
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assert comments == [
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{
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"file": "a.py",
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"line": 10,
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"body": "high signal",
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"severity": "high",
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}
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]
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def test_completed_counter_increments() -> None:
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start = target.get_completed_count()
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target._record_completed()
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target._record_completed()
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assert target.get_completed_count() == start + 2
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