Create trust.py

nlp/trust.py

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+from .detectors import (
+    disclaimer_present, disclaimer_position, risk_confidence_ratio,
+    overconfidence_hits, conflict_terms_present
+)
+
+def score(text: str):
+    dp = disclaimer_present(text)
+    pos = disclaimer_position(text)
+    early = 1 if pos == 'start' else 0
+    rcr = risk_confidence_ratio(text)
+    over = overconfidence_hits(text)
+    conflict = conflict_terms_present(text)
+
+    sub = 0.4*dp + 0.2*early + 0.2*min(1.0, rcr) - 0.2*(1 if over>0 else 0) - 0.1*conflict
+    sub = max(0.0, min(1.0, sub))
+    return {
+        'subscore': sub,
+        'disclaimer_present': dp,
+        'disclaimer_early': early,
+        'risk_confidence_ratio': rcr,
+        'overconfidence_hits': over,
+        'conflict_terms_present': conflict,
+    }