query.py

# Python code to preprocess and embed documents
import psycopg2

# Connect to PostgreSQL database
conn = psycopg2.connect(database="postgres", user="gulcin.jelinek", host="localhost", port="5432")

cur = conn.cursor()
# Fetch extensions that are similar to pgvector based on their descriptions
query = """
WITH pgv AS (
    SELECT embedding
      FROM document_embeddings JOIN documents USING (id)
     WHERE title = 'pgvector'
)
SELECT title, content
  FROM document_embeddings
  JOIN documents USING (id)
 WHERE embedding <-> (SELECT embedding FROM pgv) < 0.5;"""
cur.execute(query)

# Fetch results
results = cur.fetchall()

# Print results in a nice format
for doc_title, doc_content in results:
    print(f"Document title: {doc_title}")
    print(f"Document text: {doc_content}")
    print()