backend/rag/reranker.py

from sentence_transformers import CrossEncoder

reranker = CrossEncoder("cross-encoder/ms-marco-MiniLM-L-6-v2")

def rerank(query, docs, top_k=5):
    if not docs:
        return []
    pairs = [(query, doc['content']) for doc in docs]
    scores = reranker.predict(pairs)

    ranked = sorted(
        zip(docs, scores),
        key=lambda x: x[1],
        reverse=True
    )

    return [doc for doc, score in ranked[:top_k]]