| import sys |
| import os |
|
|
| sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
| from rag_engine.retriever import OncoRAGRetriever |
|
|
| def main(): |
| queries = [ |
| "Patient with Stage III colon cancer, KRAS mutated", |
| "Paciente masculino de 65 años con cáncer de colon en Estadio III, mutación KRAS", |
| "Tratamiento para glioblastoma recurrente en adultos mayores", |
| "How to treat a common cold with vitamin C", |
| "Melanoma metastásico con mutación BRAF V600E, progresión tras ipilimumab", |
| "Receta para hacer una torta de chocolate", |
| "Non-small cell lung cancer stage IV with EGFR exon 19 deletion", |
| "Dolor de cabeza leve y fiebre baja en niño de 8 años" |
| ] |
| |
| retriever = OncoRAGRetriever() |
| |
| for q in queries: |
| print(f"\n{'='*60}\nQuery: {q}") |
| candidates, distances = retriever._bi_encoder_retrieve(q, 5) |
| for i, (cand, dist) in enumerate(zip(candidates, distances)): |
| pass_gate = "PASS" if dist <= retriever.distance_threshold else "FAIL" |
| print(f" [{i}] Dist: {dist:.4f} [{pass_gate}] | Source: {cand['source']} - {cand['header']}") |
|
|
| if __name__ == '__main__': |
| main() |
|
|