| 1 | import unittest |
| 2 | |
| 3 | from lib import render, schema |
| 4 | |
| 5 | |
| 6 | class RenderHiringSignalsTests(unittest.TestCase): |
| 7 | def test_render_hiring_signals_block_with_citations(self): |
| 8 | report = schema.Report( |
| 9 | topic="Listen Labs", |
| 10 | range_from="2026-05-16", |
| 11 | range_to="2026-06-16", |
| 12 | generated_at="2026-06-16T00:00:00Z", |
| 13 | provider_runtime=schema.ProviderRuntime("mock", "mock", "mock"), |
| 14 | query_plan=schema.QueryPlan( |
| 15 | intent="product", |
| 16 | freshness_mode="balanced_recent", |
| 17 | cluster_mode="none", |
| 18 | raw_topic="Listen Labs", |
| 19 | subqueries=[], |
| 20 | source_weights={}, |
| 21 | ), |
| 22 | clusters=[], |
| 23 | ranked_candidates=[], |
| 24 | items_by_source={}, |
| 25 | errors_by_source={}, |
| 26 | artifacts={ |
| 27 | "hiring_signals": { |
| 28 | "mode": "standard", |
| 29 | "company_size_tier": "startup", |
| 30 | "include": True, |
| 31 | "signals": [ |
| 32 | { |
| 33 | "theme": "enterprise readiness", |
| 34 | "interpretation": "appears to be increasing focus on enterprise readiness", |
| 35 | "confidence": "medium", |
| 36 | "evidence_count": 2, |
| 37 | "evidence": [ |
| 38 | { |
| 39 | "title": "Enterprise Security Engineer", |
| 40 | "url": "https://example.com/jobs/1", |
| 41 | "department": "Engineering", |
| 42 | "published_at": "2026-06-01", |
| 43 | } |
| 44 | ], |
| 45 | } |
| 46 | ], |
| 47 | } |
| 48 | }, |
| 49 | ) |
| 50 | block = "\n".join(render._render_hiring_signals(report)) |
| 51 | self.assertIn("Hiring Signals", block) |
| 52 | self.assertIn("[Enterprise Security Engineer](https://example.com/jobs/1)", block) |
| 53 | self.assertIn("not exact roadmap predictions", block) |
| 54 | html_md = render.render_for_html(report) |
| 55 | self.assertIn("Hiring Signals", html_md) |
| 56 | self.assertIn("[Enterprise Security Engineer](https://example.com/jobs/1)", html_md) |
| 57 | synthesized_html_md = render.render_for_html( |
| 58 | report, |
| 59 | synthesis_md="What I learned:\n\nHiring points toward enterprise readiness.", |
| 60 | ) |
| 61 | self.assertIn("What I learned", synthesized_html_md) |
| 62 | self.assertIn("Hiring Signals", synthesized_html_md) |
| 63 | self.assertIn("[Enterprise Security Engineer](https://example.com/jobs/1)", synthesized_html_md) |
| 64 | context = render.render_context(report) |
| 65 | self.assertIn("Hiring Signals", context) |
| 66 | self.assertIn("[Enterprise Security Engineer](https://example.com/jobs/1)", context) |
| 67 | |
| 68 | def test_standard_mode_omits_weak_signal(self): |
| 69 | report = schema.Report( |
| 70 | topic="Apple", |
| 71 | range_from="2026-05-16", |
| 72 | range_to="2026-06-16", |
| 73 | generated_at="2026-06-16T00:00:00Z", |
| 74 | provider_runtime=schema.ProviderRuntime("mock", "mock", "mock"), |
| 75 | query_plan=schema.QueryPlan( |
| 76 | intent="product", |
| 77 | freshness_mode="balanced_recent", |
| 78 | cluster_mode="none", |
| 79 | raw_topic="Apple", |
| 80 | subqueries=[], |
| 81 | source_weights={}, |
| 82 | ), |
| 83 | clusters=[], |
| 84 | ranked_candidates=[], |
| 85 | items_by_source={}, |
| 86 | errors_by_source={}, |
| 87 | artifacts={ |
| 88 | "hiring_signals": { |
| 89 | "mode": "standard", |
| 90 | "company_size_tier": "mega-cap", |
| 91 | "include": False, |
| 92 | "signals": [], |
| 93 | "omitted_reason": "jobs evidence is too diffuse", |
| 94 | } |
| 95 | }, |
| 96 | ) |
| 97 | self.assertEqual([], render._render_hiring_signals(report)) |
| 98 | |
| 99 | |
| 100 | if __name__ == "__main__": |
| 101 | unittest.main() |
| 102 | |
| 103 | |
| 104 | class JobsFooterTests(unittest.TestCase): |
| 105 | def test_jobs_only_run_still_emits_law5_footer(self): |
| 106 | report = schema.Report( |
| 107 | topic="Listen Labs", |
| 108 | range_from="2026-05-16", |
| 109 | range_to="2026-06-16", |
| 110 | generated_at="2026-06-16T00:00:00Z", |
| 111 | provider_runtime=schema.ProviderRuntime("mock", "mock", "mock"), |
| 112 | query_plan=schema.QueryPlan( |
| 113 | intent="product", freshness_mode="balanced_recent", cluster_mode="none", |
| 114 | raw_topic="Listen Labs", subqueries=[], source_weights={}, |
| 115 | ), |
| 116 | clusters=[], ranked_candidates=[], |
| 117 | items_by_source={ |
| 118 | "jobs": [ |
| 119 | schema.SourceItem( |
| 120 | item_id="AB1", source="jobs", |
| 121 | title="Founding Research Scientist, Human Simulation", |
| 122 | body="", url="https://jobs.ashbyhq.com/listenlabs/abc", |
| 123 | engagement={"open_roles": 1}, |
| 124 | ) |
| 125 | ] |
| 126 | }, |
| 127 | errors_by_source={}, |
| 128 | artifacts={}, |
| 129 | ) |
| 130 | footer = "\n".join(render._render_emoji_footer(report, "/tmp/x.md")) |
| 131 | self.assertIn("All agents reported back", footer) |
| 132 | self.assertIn("Jobs: 1 role", footer) |
| 133 | |
| 134 | |
| 135 | class HiringSignalsBannerSuppressionTests(unittest.TestCase): |
| 136 | def _report(self): |
| 137 | return schema.Report( |
| 138 | topic="Listen Labs", range_from="2026-05-16", range_to="2026-06-16", |
| 139 | generated_at="2026-06-16T00:00:00Z", |
| 140 | provider_runtime=schema.ProviderRuntime("mock", "mock", "mock"), |
| 141 | query_plan=schema.QueryPlan( |
| 142 | intent="concept", freshness_mode="evergreen_ok", cluster_mode="none", |
| 143 | raw_topic="Listen Labs", subqueries=[], source_weights={}), |
| 144 | clusters=[], ranked_candidates=[], items_by_source={}, errors_by_source={}, |
| 145 | artifacts={"plan_source": "deterministic", "hiring_signals_mode": True}, |
| 146 | ) |
| 147 | |
| 148 | def test_hiring_signals_suppresses_degraded_and_pre_research_banners(self): |
| 149 | report = self._report() |
| 150 | self.assertEqual([], render._render_degraded_run_warning(report)) |
| 151 | self.assertEqual([], render._render_pre_research_warning(report)) |
| 152 | |
| 153 | def test_non_hiring_named_entity_still_warns(self): |
| 154 | report = self._report() |
| 155 | report.artifacts["hiring_signals_mode"] = False |
| 156 | self.assertTrue(render._render_degraded_run_warning(report)) |
| 157 |