@@ -404,6 +456,7 @@
{{ sub.llm_findings.summary }}
{% endif %}
{% if sub.llm_findings.findings %}
+
Security findings
| Severity | Category | File | Explanation | Fix hint |
|---|
@@ -420,8 +473,58 @@
{% endfor %}
- {% else %}
-
No findings — model verdict was clean.
+ {% endif %}
+ {# Content-quality issues. Pre-fix the template only rendered
+ the security findings table, so a submission blocked
+ purely on content_quality (e.g. weak description) showed
+ up as 'No findings — model verdict was clean' even though
+ status was blocked_llm. Surfaced live by an admin
+ investigating a blocked re-restore of an already-approved
+ bundle. #}
+ {% set cq = sub.llm_findings.content_quality %}
+ {% if cq and cq.issues %}
+
+ Content quality issues
+ {{ cq.verdict }}
+
+
+
+ | File | Field | Issue | Suggested rewrite |
|---|
+
+
+ {% for issue in cq.issues %}
+
+ {{ issue.file }} |
+ {{ issue.field }} |
+ {{ issue.issue }} |
+ {{ issue.hint or "" }} |
+
+ {% endfor %}
+
+
+ {% endif %}
+ {% if not sub.llm_findings.findings and not (cq and cq.issues) %}
+ {% if sub.status in ['blocked_llm', 'review_error'] %}
+
+ Blocked but no findings recorded.
+ This is usually a transient LLM non-determinism: the
+ reviewer returned a fail verdict without enumerating
+ the offending items. Click Rescan to re-run
+ the pipeline, or Override with a written
+ reason if you've verified the bundle offline.
+
+ {% else %}
+
No findings — model verdict was clean.
+ {% endif %}
+ {% endif %}
+ {% if sub.llm_findings.reused_from_submission_id %}
+
{% endif %}
{% endif %}
{% elif sub.status in ['pending_inline', 'pending_llm'] %}
diff --git a/pyproject.toml b/pyproject.toml
index b6c5d37..d5f0c31 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "agnes-the-ai-analyst"
-version = "0.54.23"
+version = "0.54.24"
description = "Agnes — AI Data Analyst platform for AI analytical systems"
requires-python = ">=3.11,<3.14"
license = "MIT"
diff --git a/src/repositories/store_submissions.py b/src/repositories/store_submissions.py
index bfc0981..6a4a0d2 100644
--- a/src/repositories/store_submissions.py
+++ b/src/repositories/store_submissions.py
@@ -451,10 +451,16 @@ class StoreSubmissionsRepository:
history = []
item["entity_version_history"] = history
item["version_no"] = None
- sub_hash = item.get("version")
+ # Look up THIS submission's version_no by submission_id,
+ # NOT by hash. Hash-based lookup mislabeled every
+ # byte-identical reupload (and every reused-verdict
+ # restore — common after PR #332) as v1 because the loop
+ # picked the FIRST history entry with matching hash.
+ # Same fix-pattern as PR #330 for runner / override.
+ sub_id = item.get("id")
for entry in history:
try:
- if entry.get("hash") == sub_hash:
+ if entry.get("submission_id") == sub_id:
item["version_no"] = int(entry.get("n"))
break
except (TypeError, ValueError):
diff --git a/tests/test_store_entity_versions.py b/tests/test_store_entity_versions.py
index 798a1bb..6e0ffd0 100644
--- a/tests/test_store_entity_versions.py
+++ b/tests/test_store_entity_versions.py
@@ -1992,3 +1992,221 @@ class TestRescanPromotesNonCurrent:
assert ent_after["version"] != v1_hash, (
"entity.version hash must move to v2 after rescan promote"
)
+
+class TestRestoreReusesApprovedVerdict:
+ """Live-bug fix: a second restore of an already-approved version
+ sometimes flipped to `blocked_llm` because Anthropic structured
+ output is non-deterministic — same bytes, different
+ `content_quality.verdict` across calls. Restore now detects
+ byte-identical bundles backed by a prior `approved` submission
+ (same reviewed_by_model) and reuses that verdict."""
+
+ def test_restore_of_approved_version_skips_llm_and_reuses_verdict(
+ self, web_client, monkeypatch,
+ ):
+ from pathlib import Path
+ from app.utils import get_store_dir
+ from src.repositories.store_submissions import StoreSubmissionsRepository
+ from src.store_guardrails.runner import run_llm_review
+
+ monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-fake-for-reuse")
+ owner_id, owner_cookies = _create_user(web_client, "reuse@x.com")
+ eid = _upload_clean(web_client, owner_cookies, name="reuseme")
+
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_enabled", lambda: True,
+ )
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_llm_provider_ready", lambda: True,
+ )
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_review_model",
+ lambda: "claude-haiku-4-5-test",
+ )
+ # Stub the BG-task scheduler so only our direct `run_llm_review`
+ # call writes the verdict (real BG uses default_model_loader
+ # which resolves to a different reviewed_by_model and would
+ # win the terminal-state CAS race).
+ monkeypatch.setattr(
+ "app.api.store._schedule_llm_review",
+ lambda *a, **kw: None,
+ )
+
+ approve_calls = {"n": 0}
+
+ def mock_approve(*a, **kw):
+ approve_calls["n"] += 1
+ return {
+ "risk_level": "safe", "summary": "ok",
+ "findings": [], "template_placeholders_found": 0,
+ "reviewed_by_model": "claude-haiku-4-5-test",
+ "error": None,
+ "content_quality": {"verdict": "pass", "issues": []},
+ }
+ monkeypatch.setattr(
+ "src.store_guardrails.llm_review.review_bundle", mock_approve,
+ )
+
+ v2_zip = _make_skill_zip("reuseme", body="V2 body unique " * 30)
+ r = web_client.put(
+ f"/api/store/entities/{eid}",
+ files={"file": ("v2.zip", v2_zip, "application/zip")},
+ cookies=owner_cookies,
+ )
+ assert r.status_code == 200, r.text
+ conn = get_system_db()
+ v2_sub_id = StoreSubmissionsRepository(conn).latest_for_entity(eid)["id"]
+ conn.close()
+ run_llm_review(
+ v2_sub_id,
+ plugin_dir=Path(get_store_dir()) / eid / "versions" / "v2" / "plugin",
+ conn_factory=get_system_db,
+ api_key_loader=lambda: "sk",
+ model_loader=lambda: "claude-haiku-4-5-test",
+ )
+ calls_after_v2 = approve_calls["n"]
+
+ v3_zip = _make_skill_zip("reuseme", body="V3 body unique " * 30)
+ r = web_client.put(
+ f"/api/store/entities/{eid}",
+ files={"file": ("v3.zip", v3_zip, "application/zip")},
+ cookies=owner_cookies,
+ )
+ assert r.status_code == 200, r.text
+ conn = get_system_db()
+ v3_sub_id = StoreSubmissionsRepository(conn).latest_for_entity(eid)["id"]
+ conn.close()
+ run_llm_review(
+ v3_sub_id,
+ plugin_dir=Path(get_store_dir()) / eid / "versions" / "v3" / "plugin",
+ conn_factory=get_system_db,
+ api_key_loader=lambda: "sk",
+ model_loader=lambda: "claude-haiku-4-5-test",
+ )
+ calls_after_v3 = approve_calls["n"]
+ # BG task in TestClient may fire run_llm_review on its own
+ # in addition to our direct call, so don't assert exact count
+ # difference — only check the restore window.
+ assert calls_after_v3 > calls_after_v2
+
+ # Restore v2 → byte-identical to v2 approved entry. Reuse
+ # must fire → no new LLM call.
+ r = web_client.post(
+ f"/api/store/entities/{eid}/versions/2/restore",
+ cookies=owner_cookies,
+ )
+ assert r.status_code == 200, r.text
+ assert approve_calls["n"] == calls_after_v3, (
+ f"restore of approved version must NOT call LLM; "
+ f"count grew from {calls_after_v3} to {approve_calls['n']}"
+ )
+
+ conn = get_system_db()
+ ent_after = StoreEntitiesRepository(conn).get(eid)
+ v4_sub_id = next(
+ (e["submission_id"] for e in ent_after["version_history"]
+ if int(e["n"]) == 4),
+ None,
+ )
+ v4_sub = StoreSubmissionsRepository(conn).get(v4_sub_id) if v4_sub_id else None
+ conn.close()
+ assert v4_sub is not None
+ assert v4_sub["status"] == "approved"
+ assert v4_sub["reviewed_by_model"] == "claude-haiku-4-5-test"
+ assert (v4_sub["llm_findings"] or {}).get(
+ "reused_from_submission_id"
+ ) == v2_sub_id
+ assert ent_after["version_no"] == 4
+
+ def test_restore_legacy_v1_falls_back_to_llm(
+ self, web_client, monkeypatch,
+ ):
+ """v1 seed (guardrails-OFF approval, no reviewed_by_model) is
+ NOT eligible for reuse. Restoring v1 must schedule a real
+ LLM review under guardrails-on."""
+ from pathlib import Path
+ from app.utils import get_store_dir
+ from src.repositories.store_submissions import StoreSubmissionsRepository
+ from src.store_guardrails.runner import run_llm_review
+
+ monkeypatch.setenv("ANTHROPIC_API_KEY", "sk-ant-fake-fallback")
+ owner_id, owner_cookies = _create_user(web_client, "noreuse@x.com")
+ eid = _upload_clean(web_client, owner_cookies, name="noreuse")
+
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_enabled", lambda: True,
+ )
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_llm_provider_ready", lambda: True,
+ )
+ monkeypatch.setattr(
+ "app.api.store.get_guardrails_review_model",
+ lambda: "claude-haiku-4-5-test",
+ )
+ # Stub the BG-task scheduler so only our direct `run_llm_review`
+ # call writes the verdict (real BG uses default_model_loader
+ # which resolves to a different reviewed_by_model and would
+ # win the terminal-state CAS race).
+ monkeypatch.setattr(
+ "app.api.store._schedule_llm_review",
+ lambda *a, **kw: None,
+ )
+
+ approve_calls = {"n": 0}
+
+ def mock_approve(*a, **kw):
+ approve_calls["n"] += 1
+ return {
+ "risk_level": "safe", "summary": "ok",
+ "findings": [], "template_placeholders_found": 0,
+ "reviewed_by_model": "claude-haiku-4-5-test",
+ "error": None,
+ "content_quality": {"verdict": "pass", "issues": []},
+ }
+ monkeypatch.setattr(
+ "src.store_guardrails.llm_review.review_bundle", mock_approve,
+ )
+
+ v2_zip = _make_skill_zip("noreuse", body="V2 body " * 30)
+ r = web_client.put(
+ f"/api/store/entities/{eid}",
+ files={"file": ("v2.zip", v2_zip, "application/zip")},
+ cookies=owner_cookies,
+ )
+ assert r.status_code == 200, r.text
+ conn = get_system_db()
+ v2_sub_id = StoreSubmissionsRepository(conn).latest_for_entity(eid)["id"]
+ conn.close()
+ run_llm_review(
+ v2_sub_id,
+ plugin_dir=Path(get_store_dir()) / eid / "versions" / "v2" / "plugin",
+ conn_factory=get_system_db,
+ api_key_loader=lambda: "sk",
+ model_loader=lambda: "claude-haiku-4-5-test",
+ )
+ calls_after_v2 = approve_calls["n"]
+
+ r = web_client.post(
+ f"/api/store/entities/{eid}/versions/1/restore",
+ cookies=owner_cookies,
+ )
+ assert r.status_code == 200, r.text
+ conn = get_system_db()
+ v3_sub_id = StoreSubmissionsRepository(conn).latest_for_entity(eid)["id"]
+ conn.close()
+ run_llm_review(
+ v3_sub_id,
+ plugin_dir=Path(get_store_dir()) / eid / "versions" / "v3" / "plugin",
+ conn_factory=get_system_db,
+ api_key_loader=lambda: "sk",
+ model_loader=lambda: "claude-haiku-4-5-test",
+ )
+ # No reuse: BG/manual LLM calls fired (count grew).
+ assert approve_calls["n"] > calls_after_v2
+ conn = get_system_db()
+ v3_sub = StoreSubmissionsRepository(conn).get(v3_sub_id)
+ conn.close()
+ assert v3_sub["status"] == "approved"
+ assert (v3_sub["llm_findings"] or {}).get(
+ "reused_from_submission_id"
+ ) is None