Merge PR #10: read the AI-USAGE opt-in at render time
Late AI-USAGE labels now reach the review body. Verified live on this PR: AI-REVIEW then AI-USAGE six seconds later, usage block present in review #131.
This commit was merged in pull request #10.
This commit is contained in:
@@ -66,6 +66,8 @@ SHA_MARKER = "<!-- pragent:sha={sha} -->"
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_SHA_MARKER_RE = re.compile(r"<!-- pragent:sha=([0-9a-f]{7,40}) -->")
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_SHA_MARKER_RE = re.compile(r"<!-- pragent:sha=([0-9a-f]{7,40}) -->")
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AI_REVIEW_LABEL = "AI-REVIEW"
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AI_REVIEW_LABEL = "AI-REVIEW"
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# Opt-in label for the token-usage block. Read at render time — see pr_has_label.
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AI_USAGE_LABEL = "AI-USAGE"
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SEVERITIES = ("critical", "high", "medium", "low")
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SEVERITIES = ("critical", "high", "medium", "low")
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# Severity rank — higher = more severe. Used by `apply_repo_config` to drop
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# Severity rank — higher = more severe. Used by `apply_repo_config` to drop
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# findings below `severity_threshold`. Critical=3, high=2, medium=1, low=0.
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# findings below `severity_threshold`. Critical=3, high=2, medium=1, low=0.
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@@ -156,6 +158,33 @@ def parse_text_blocks(content: list) -> str:
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return "\n".join(out).strip()
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return "\n".join(out).strip()
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def pr_has_label(api: str, repo: str, index: str, token: str, label: str) -> bool:
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"""True if the PR currently carries `label`. False on any failure.
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Read at RENDER time, not at review start. A reviewer labels AI-REVIEW and
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AI-USAGE seconds apart; the review claims on the first event and the
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second is dropped by the in-flight dedupe, so the trigger payload never
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sees the opt-in. Re-reading when the review begins is no better — that is
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still milliseconds after the first click. Only a read taken once the
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review has finished (a minute or more later) reliably sees the label.
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"""
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try:
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code, raw = gitea_get(api, repo, f"issues/{index}/labels", token)
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if code >= 300:
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return False
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data = json.loads(raw.decode() or "[]")
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except Exception as e:
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print(f"pragent: could not re-read labels for {repo}#{index}: {e}",
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file=sys.stderr, flush=True)
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return False
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if not isinstance(data, list):
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return False
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return any(
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(isinstance(x, dict) and x.get("name") == label) or x == label
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for x in data
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)
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def _int_env(name: str, default: int) -> int:
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def _int_env(name: str, default: int) -> int:
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"""Read an int from the environment, falling back on anything unparseable.
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"""Read an int from the environment, falling back on anything unparseable.
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@@ -1896,6 +1925,13 @@ def review_pr(
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file=sys.stderr, flush=True,
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file=sys.stderr, flush=True,
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)
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)
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salvaged = salvage_summary(stdout)
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salvaged = salvage_summary(stdout)
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# The AI-USAGE opt-in is re-checked HERE, at render time: the label
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# is usually applied moments after AI-REVIEW, long after this
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# review was claimed and its trigger payload frozen.
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if not report_usage:
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report_usage = pr_has_label(api, repo, index, token, AI_USAGE_LABEL)
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if report_usage and usage and usage.get('output'):
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compute_attribution(findings, usage['output'])
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usage_section = _render_collapsible_usage(usage, model, config=config) if report_usage else ""
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usage_section = _render_collapsible_usage(usage, model, config=config) if report_usage else ""
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post_review(api, repo, index, token, format_review_body(
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post_review(api, repo, index, token, format_review_body(
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salvaged or "AI review produced no parseable output.",
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salvaged or "AI review produced no parseable output.",
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@@ -1936,6 +1972,13 @@ def review_pr(
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# for it.
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# for it.
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if report_usage and usage and usage.get("output"):
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if report_usage and usage and usage.get("output"):
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compute_attribution(findings, usage["output"])
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compute_attribution(findings, usage["output"])
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# The AI-USAGE opt-in is re-checked HERE, at render time: the label
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# is usually applied moments after AI-REVIEW, long after this
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# review was claimed and its trigger payload frozen.
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if not report_usage:
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report_usage = pr_has_label(api, repo, index, token, AI_USAGE_LABEL)
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if report_usage and usage and usage.get('output'):
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compute_attribution(findings, usage['output'])
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usage_section = _render_collapsible_usage(usage, model, config=config) if report_usage else ""
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usage_section = _render_collapsible_usage(usage, model, config=config) if report_usage else ""
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# Anchor against the RAW diff, never the compressed one. Compression
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# Anchor against the RAW diff, never the compressed one. Compression
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@@ -616,6 +616,35 @@ def test_reference_non_url_renders_as_plain_text():
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assert "](CVE-" not in body
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assert "](CVE-" not in body
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def test_pr_has_label_reads_the_live_labels(monkeypatch):
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# The AI-USAGE opt-in is read at render time, not from the trigger
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# payload: labelling AI-REVIEW then AI-USAGE is two events, the review
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# claims on the first, and the second is dropped by the in-flight dedupe.
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seen = {}
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def _get(api, repo, path, token, accept="application/json"):
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seen["path"] = path
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return 200, b'[{"name": "AI-REVIEW"}, {"name": "AI-USAGE"}]'
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monkeypatch.setattr(ai_review, "gitea_get", _get)
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assert ai_review.pr_has_label("http://api", "o/r", "9", "t", "AI-USAGE") is True
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assert seen["path"] == "issues/9/labels"
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assert ai_review.pr_has_label("http://api", "o/r", "9", "t", "NOPE") is False
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def test_pr_has_label_survives_a_broken_api(monkeypatch):
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def _boom(*a, **k):
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raise RuntimeError("gitea down")
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monkeypatch.setattr(ai_review, "gitea_get", _boom)
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assert ai_review.pr_has_label("http://api", "o/r", "9", "t", "AI-USAGE") is False
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monkeypatch.setattr(ai_review, "gitea_get", lambda *a, **k: (404, b"nope"))
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assert ai_review.pr_has_label("http://api", "o/r", "9", "t", "AI-USAGE") is False
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monkeypatch.setattr(ai_review, "gitea_get", lambda *a, **k: (200, b'{"not": "a list"}'))
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assert ai_review.pr_has_label("http://api", "o/r", "9", "t", "AI-USAGE") is False
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def test_int_env_falls_back_on_garbage(monkeypatch, capsys):
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def test_int_env_falls_back_on_garbage(monkeypatch, capsys):
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monkeypatch.setenv("PRAGENT_DIFF_CONTEXT", "two")
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monkeypatch.setenv("PRAGENT_DIFF_CONTEXT", "two")
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assert ai_review._int_env("PRAGENT_DIFF_CONTEXT", 1) == 1
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assert ai_review._int_env("PRAGENT_DIFF_CONTEXT", 1) == 1
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