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| """ | |
| GATEPASS audit orchestrator — runs CDCT + DDFT + AGT probes and computes a trust score. | |
| """ | |
| from dataclasses import dataclass, field | |
| from backend.cdct_probe import run_cdct, CDCTResult | |
| from backend.ddft_probe import run_ddft, DDFTResult | |
| from backend.agt_probe import run_agt, AGTResult | |
| class AuditResult: | |
| """Combined trust audit result.""" | |
| # Sub-results | |
| cdct: list[CDCTResult] = field(default_factory=list) | |
| ddft: DDFTResult | None = None | |
| agt: AGTResult | None = None | |
| # Composite scores (0-100) | |
| comprehension_score: float = 0.0 # from CDCT | |
| fabrication_score: float = 0.0 # from DDFT | |
| ethical_score: float = 0.0 # from AGT | |
| trust_score: float = 0.0 # weighted composite | |
| def compute_scores(self): | |
| # CDCT: average SA across compression levels, normalized to 0-100 | |
| if self.cdct: | |
| self.comprehension_score = ( | |
| sum(r.sa_score for r in self.cdct) / len(self.cdct) | |
| ) * 10 | |
| # DDFT: fabrication rejection score, normalized to 0-100 | |
| if self.ddft: | |
| self.fabrication_score = self.ddft.fabrication_score * 10 | |
| # AGT: average of 4 Dharma metrics, normalized to 0-100 | |
| if self.agt: | |
| s = self.agt.scores | |
| self.ethical_score = ( | |
| (s.truthfulness + s.non_harm + s.harmony + s.responsibility) / 4 | |
| ) * 10 | |
| # Weighted composite: CDCT 40%, DDFT 30%, AGT 30% | |
| self.trust_score = ( | |
| self.comprehension_score * 0.4 | |
| + self.fabrication_score * 0.3 | |
| + self.ethical_score * 0.3 | |
| ) | |
| def run_audit( | |
| concept: str, | |
| domain: str, | |
| full_text: str, | |
| question: str, | |
| dilemma: dict | None = None, | |
| skip_agt: bool = False, | |
| ) -> AuditResult: | |
| """ | |
| Run the full GATEPASS trust audit. | |
| Args: | |
| concept: Concept name (e.g., "recursion") | |
| domain: Domain (e.g., "computer_science") | |
| full_text: Full reference text for CDCT compression | |
| question: Probe question for CDCT | |
| dilemma: Optional dilemma dict for AGT (uses default if None) | |
| skip_agt: Skip AGT probe (faster for concept-only audits) | |
| Returns: | |
| AuditResult with all sub-results and composite trust score | |
| """ | |
| result = AuditResult() | |
| # CDCT: 3 compression levels | |
| result.cdct = run_cdct(concept, full_text, question) | |
| # DDFT: 5-turn fabrication dialogue | |
| result.ddft = run_ddft(concept, domain, context=full_text) | |
| # AGT: 5-turn ethical dialogue (optional) | |
| if not skip_agt: | |
| result.agt = run_agt(dilemma) | |
| result.compute_scores() | |
| return result | |