0063df0a87
- Бэкенд: FastAPI + SQLAlchemy async + PostgreSQL, JWT-аутентификация, Qdrant multi-tenant векторное хранилище, Celery воркер - Фронтенд: React + Vite + TypeScript SPA (логин, регистрация, дашборд, поиск по коллекциям, настройки) - Инфраструктура: docker-compose, Helm-чарт, GitHub Actions CI, Prometheus/Grafana мониторинг - Embedding через OpenRouter (nvidia/llama-nemotron-embed-vl-1b-v2:free) - LLM: google/gemma-4-31b-it:free через OpenRouter
27 lines
772 B
Python
27 lines
772 B
Python
from sentence_transformers import CrossEncoder
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reranker = CrossEncoder(
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"cross-encoder/mmarco-mMiniLMv2-L12-H384-v1",
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max_length=512,
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device="cpu",
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)
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def rerank(query: str, results: list[dict], k: int = 5) -> list[dict]:
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if not results:
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return []
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pairs = [(query, r["payload"]["full_text"]) for r in results]
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scores = reranker.predict(pairs)
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scored = []
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for i, score in enumerate(scores):
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scored.append({
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"ticket_id": results[i]["payload"]["ticket_id"],
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"score": float(score),
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"full_text": results[i]["payload"]["full_text"],
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"category": results[i]["payload"].get("category", ""),
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})
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scored.sort(key=lambda x: x["score"], reverse=True)
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return scored[:k]
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