| """
|
| retriever.py
|
| ────────────
|
| Given a Romanian question, finds the most relevant legal articles
|
| using semantic search over the FAISS index.
|
|
|
| Usage:
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| python retriever.py
|
| """
|
|
|
| import sys
|
| import json
|
| import faiss
|
| import numpy as np
|
| from sentence_transformers import SentenceTransformer
|
|
|
| MODEL_NAME = "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"
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| INDEX_FILE = "data/faiss.index"
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| METADATA_FILE = "data/metadata.jsonl"
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| TOP_K = 5
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|
|
|
|
| def load_metadata(path: str) -> list[dict]:
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| metadata = []
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| with open(path, encoding="utf-8") as f:
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| for line in f:
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| line = line.strip()
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| if line:
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| metadata.append(json.loads(line))
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| return metadata
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|
|
|
|
| def search(query: str, index, metadata: list[dict], model, k: int = TOP_K):
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| query_vector = model.encode(
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| [query],
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| convert_to_numpy=True,
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| normalize_embeddings=True,
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| ).astype("float32")
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|
|
| scores, positions = index.search(query_vector, k)
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|
|
| results = []
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| for score, pos in zip(scores[0], positions[0]):
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| if pos == -1:
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| continue
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| article = metadata[pos]
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| results.append({
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| "score": float(score),
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| "law_title": article["law_title"],
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| "article_number": article["article_number"],
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| "text": article["text"],
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| })
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| return results
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|
|
|
|
| def main():
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| print("Loading model and index...")
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| model = SentenceTransformer(MODEL_NAME)
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| index = faiss.read_index(INDEX_FILE)
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| metadata = load_metadata(METADATA_FILE)
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| print(f"Ready. Index has {index.ntotal} articles.\n")
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|
|
| while True:
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| try:
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| query = input("Intrebare (sau 'exit'): ").strip()
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| except (EOFError, KeyboardInterrupt):
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| print("\nLa revedere!")
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| break
|
|
|
| if query.lower() == "exit":
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| break
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| if not query:
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| continue
|
|
|
| results = search(query, index, metadata, model)
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|
|
| print(f"\nTop {TOP_K} rezultate pentru: '{query}'\n")
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| for i, r in enumerate(results, 1):
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| print(f"[{i}] scor={r['score']:.3f} | {r['law_title']} | {r['article_number']}")
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| print(f" {r['text'][:200]}")
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| print()
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|
|
|
|
| if __name__ == "__main__":
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| main()
|
|
|
