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31 lines
672 B
Python
31 lines
672 B
Python
import sqlite3
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import sqlite_vec
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from sentence_transformers import SentenceTransformer
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db = sqlite3.connect("articles.db")
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db.enable_load_extension(True)
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sqlite_vec.load(db)
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db.enable_load_extension(False)
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model = SentenceTransformer("all-MiniLM-L6-v2")
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query = "sports"
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query_embedding = model.encode(query)
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results = db.execute(
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"""
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select
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article_id,
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headline,
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distance
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from vec_articles
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left join articles on articles.id = vec_articles.article_id
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where headline_embedding match ?
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and k = 8;
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""",
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[query_embedding]
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).fetchall()
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for (article_id, headline, distance) in results:
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print(article_id, headline, distance)
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