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| import json | |
| import os | |
| from src.benchmarks.semantic_quality_audit import SemanticQualityAudit | |
| from src.parser.parser import Parser | |
| from src.ontology.matcher import ConceptMatcher | |
| from src.embeddings.engine import EmbeddingEngine | |
| def run_threshold_analysis(): | |
| audit = SemanticQualityAudit() | |
| matcher = ConceptMatcher("data/ontology") | |
| engine = EmbeddingEngine(index_dir="data/faiss_indices") | |
| engine.load_index() | |
| parser = Parser(matcher, engine) | |
| thresholds = [0.30, 0.40, 0.50, 0.60, 0.70, 0.80] | |
| report = [] | |
| for th in thresholds: | |
| results = { | |
| "correct": 0, | |
| "acceptable": 0, | |
| "incorrect": 0, | |
| "rejected": 0, | |
| "total": 0 | |
| } | |
| for item in audit.expanded_gt: | |
| query = item["query"] | |
| search_results = parser.embedding_engine.search(query, category=item.get("category"), top_k=1) | |
| results["total"] += 1 | |
| if not search_results: | |
| results["rejected"] += 1 | |
| continue | |
| record, conf = search_results[0] | |
| if conf < th: | |
| results["rejected"] += 1 | |
| continue | |
| actual_lower = record.canonical.lower().strip() | |
| expected_lower = item["expected"].lower().strip() | |
| is_correct = (actual_lower == expected_lower) or (expected_lower in actual_lower) or (actual_lower in expected_lower) | |
| is_acceptable = False | |
| if not is_correct: | |
| if "acceptable" in item: | |
| is_acceptable = any(acc.lower().strip() in actual_lower for acc in item["acceptable"]) or \ | |
| any(actual_lower in acc.lower().strip() for acc in item["acceptable"]) | |
| if not is_acceptable and query.lower().strip() in actual_lower: | |
| is_acceptable = True | |
| if "royal robes" in query and "royal robes" in actual_lower: is_correct = True | |
| if "crimsn" in query and "crimson" in actual_lower: is_correct = True | |
| if item["category"] == "character" and actual_lower != expected_lower: | |
| is_correct = False | |
| is_acceptable = False | |
| is_incorrect = True | |
| else: | |
| is_incorrect = not (is_correct or is_acceptable) | |
| if is_correct: | |
| results["correct"] += 1 | |
| elif is_acceptable: | |
| results["acceptable"] += 1 | |
| else: | |
| results["incorrect"] += 1 | |
| accepted = results["correct"] + results["acceptable"] + results["incorrect"] | |
| acceptance_rate = accepted / results["total"] if results["total"] else 0 | |
| incorrect_rate = results["incorrect"] / accepted if accepted else 0 | |
| recall = accepted / results["total"] if results["total"] else 0 | |
| precision = (results["correct"] + results["acceptable"]) / accepted if accepted else 0 | |
| f1 = 2 * (precision * recall) / (precision + recall) if (precision + recall) else 0 | |
| report.append({ | |
| "threshold": th, | |
| "accepted_pct": round(acceptance_rate * 100, 2), | |
| "incorrect_pct": round(incorrect_rate * 100, 2), | |
| "precision": round(precision, 4), | |
| "recall": round(recall, 4), | |
| "f1": round(f1, 4) | |
| }) | |
| os.makedirs("reports", exist_ok=True) | |
| with open("reports/threshold_analysis.json", "w", encoding="utf-8") as f: | |
| json.dump(report, f, indent=2) | |
| with open("reports/threshold_analysis.md", "w", encoding="utf-8") as f: | |
| f.write("# Confidence Threshold Analysis\n\n") | |
| for r in report: | |
| f.write(f"## Threshold {r['threshold']:.2f}\n") | |
| f.write(f"- **Accepted**: {r['accepted_pct']}%\n") | |
| f.write(f"- **Incorrect**: {r['incorrect_pct']}%\n") | |
| f.write(f"- **Precision**: {r['precision']}\n") | |
| f.write(f"- **Recall**: {r['recall']}\n") | |
| f.write(f"- **F1**: {r['f1']}\n\n") | |
| print("Threshold analysis complete.") | |
| if __name__ == "__main__": | |
| run_threshold_analysis() | |