COVERAGE BEFORE
===============
tasks.py 2,117 lines ZERO tests
gitea_client.py 539 lines ZERO tests (in this repo)
Total: 2,656 lines of orchestration with no safety net
COVERAGE AFTER
==============
test_tasks_core.py — 63 tests across 12 test classes:
TestExtractFirstJsonObject (10) — JSON parsing from noisy LLM output
Every @huey.task depends on this. Tested: clean JSON, markdown
fences, prose-wrapped, nested, malformed, arrays, unicode, empty
TestParseJsonOutput (4) — stdout/stderr fallback chain
TestNormalizeCandidateEntry (12) — knowledge graph data cleaning
Confidence clamping, status validation, deduplication, truncation
TestNormalizeTrainingExamples (5) — autolora training data prep
Fallback when empty, alternative field names, empty prompt/response
TestNormalizeRubricScores (3) — eval score clamping
TestReadJson (4) — defensive file reads
Missing files, corrupt JSON, deep-copy of defaults
TestWriteJson (3) — atomic writes with sorted keys
TestJsonlIO (9) — JSONL read/write/append/count
Missing files, blank lines, append vs overwrite
TestWriteText (3) — trailing newline normalization
TestPathUtilities (4) — newest/latest path resolution
TestFormatting (6) — batch IDs, profile summaries,
tweet prompts, checkpoint defaults
test_gitea_client_core.py — 22 tests across 9 test classes:
TestUserFromDict (3) — all from_dict() deserialization
TestLabelFromDict (1)
TestIssueFromDict (4) — null assignees/labels (THE bug)
TestCommentFromDict (2) — null body handling
TestPullRequestFromDict (3) — null head/base/merged
TestPRFileFromDict (1)
TestGiteaError (2) — error formatting
TestClientHelpers (1) — _repo_path formatting
TestFindUnassigned (3) — label/title/assignee filtering
TestFindAgentIssues (2) — case-insensitive matching
WHY THESE TESTS MATTER
======================
A bug in extract_first_json_object() corrupts every @huey.task
that processes LLM output — which is all of them. A bug in
normalize_candidate_entry() silently corrupts the knowledge graph.
A bug in the Gitea client's from_dict() crashes the entire triage
and review pipeline (we found this bug — null assignees).
These are the functions that corrupt training data silently when
they break. No one notices until the next autolora run produces
a worse model.
FULL SUITE: 108/108 pass, zero regressions.
Signed-off-by: gemini <gemini@hermes.local>
