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Upload query_index.py
Browse files- query_index.py +43 -0
query_index.py
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import argparse
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import logging
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import datasets
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import sentence_transformers
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import utils
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logging.disable(logging.CRITICAL)
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parser = argparse.ArgumentParser()
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parser.add_argument("--query", type=str, required=True)
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parser.add_argument("--k", type=int, default=5)
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args = parser.parse_args()
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model = sentence_transformers.SentenceTransformer(
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"dangvantuan/sentence-camembert-large", device="cuda"
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)
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dataset = datasets.load_dataset("json", data_files=["./data/dataset.json"], split="train")
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dataset.load_faiss_index("embeddings", "index.faiss")
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query_embedding = model.encode(args.query)
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_, retrieved_examples = dataset.get_nearest_examples(
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"embeddings",
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query_embedding,
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k=args.k,
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)
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for text, start, end, title, url in zip(
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retrieved_examples["text"],
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retrieved_examples["start"],
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retrieved_examples["end"],
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retrieved_examples["title"],
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retrieved_examples["url"],
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):
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start = start
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end = end
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print(f"title: {title}")
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print(f"transcript: [{str(start)+' ====> '+str(end)}] {text}")
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print(f"link: {url}")
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print("*" * 10)
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