phase 14-15: docker build validation and helm deployment

tests/test_evidence_ranking.py

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+"""Tests for evidence ranking — composite scoring for supporting/opposing docs.
+
+Requirements: 6.5
+"""
+from datetime import datetime, timedelta, timezone
+
+from services.aggregation.evidence import (
+    EvidenceRankConfig,
+    compute_evidence_rank,
+    rank_evidence,
+    rank_evidence_detailed,
+)
+from services.aggregation.scoring import WeightedSignal, compute_signal_weight
+
+NOW = datetime(2026, 4, 11, 12, 0, 0, tzinfo=timezone.utc)
+
+
+def _sw(
+    doc_id: str = "doc-1",
+    sentiment: float = 1.0,
+    impact: float = 0.7,
+    credibility: float = 0.8,
+    confidence: float = 0.8,
+    age_hours: float = 1.0,
+) -> WeightedSignal:
+    published = NOW - timedelta(hours=age_hours)
+    weight = compute_signal_weight(
+        published_at=published,
+        reference_time=NOW,
+        window="7d",
+        source_credibility=credibility,
+        extraction_confidence=confidence,
+    )
+    return WeightedSignal(
+        document_id=doc_id,
+        weight=weight,
+        sentiment_value=sentiment,
+        impact_score=impact,
+    )
+
+
+# ---------------------------------------------------------------------------
+# compute_evidence_rank
+# ---------------------------------------------------------------------------
+
+
+def test_rank_score_positive():
+    sig = _sw("d1", sentiment=1.0, impact=0.9, credibility=1.0)
+    ranked = compute_evidence_rank(sig)
+    assert ranked.rank_score > 0
+    assert ranked.document_id == "d1"
+    assert ranked.sentiment_value == 1.0
+
+
+def test_higher_impact_ranks_higher():
+    low = _sw("low", impact=0.3)
+    high = _sw("high", impact=0.9)
+    r_low = compute_evidence_rank(low)
+    r_high = compute_evidence_rank(high)
+    assert r_high.rank_score > r_low.rank_score
+
+
+def test_fresher_doc_ranks_higher():
+    old = _sw("old", age_hours=100.0)
+    fresh = _sw("fresh", age_hours=1.0)
+    r_old = compute_evidence_rank(old)
+    r_fresh = compute_evidence_rank(fresh)
+    assert r_fresh.rank_score > r_old.rank_score
+
+
+def test_higher_credibility_ranks_higher():
+    low_cred = _sw("low", credibility=0.2)
+    high_cred = _sw("high", credibility=1.0)
+    r_low = compute_evidence_rank(low_cred)
+    r_high = compute_evidence_rank(high_cred)
+    assert r_high.rank_score > r_low.rank_score
+
+
+# ---------------------------------------------------------------------------
+# rank_evidence
+# ---------------------------------------------------------------------------
+
+
+def test_rank_evidence_separates_sides():
+    signals = [
+        _sw("pos1", sentiment=1.0, impact=0.9),
+        _sw("pos2", sentiment=1.0, impact=0.3),
+        _sw("neg1", sentiment=-1.0, impact=0.7),
+        _sw("neutral", sentiment=0.0, impact=0.5),
+    ]
+    supporting, opposing = rank_evidence(signals)
+    assert "pos1" in supporting
+    assert "pos2" in supporting
+    assert "neg1" in opposing
+    assert "neutral" not in supporting and "neutral" not in opposing
+
+
+def test_rank_evidence_ordered_by_composite():
+    signals = [
+        _sw("weak", sentiment=1.0, impact=0.2, credibility=0.3),
+        _sw("strong", sentiment=1.0, impact=0.9, credibility=1.0),
+    ]
+    supporting, _ = rank_evidence(signals)
+    assert supporting[0] == "strong"
+
+
+def test_rank_evidence_respects_max_refs():
+    signals = [_sw(f"d{i}", sentiment=1.0) for i in range(20)]
+    cfg = EvidenceRankConfig(max_refs=3)
+    supporting, opposing = rank_evidence(signals, config=cfg)
+    assert len(supporting) == 3
+    assert len(opposing) == 0
+
+
+def test_rank_evidence_empty():
+    supporting, opposing = rank_evidence([])
+    assert supporting == []
+    assert opposing == []
+
+
+# ---------------------------------------------------------------------------
+# rank_evidence_detailed
+# ---------------------------------------------------------------------------
+
+
+def test_detailed_returns_ranked_evidence_objects():
+    signals = [
+        _sw("pos1", sentiment=1.0, impact=0.9),
+        _sw("neg1", sentiment=-1.0, impact=0.7),
+    ]
+    sup, opp = rank_evidence_detailed(signals)
+    assert len(sup) == 1
+    assert sup[0].document_id == "pos1"
+    assert sup[0].rank_score > 0
+    assert len(opp) == 1
+    assert opp[0].document_id == "neg1"