Incremental Updates: Save 70% on AI Compute Costs

1import pixeltable as pxt
2from pixeltable.functions import openai
3
4# Create table with expensive AI processing
5docs = pxt.create_table('app.docs', {
6    'document': pxt.Document,
7    'title': pxt.String,
8})
9
10# Expensive embedding generation
11docs.add_computed_column(
12    embedding=openai.embeddings(
13        docs.title,  # Simplified for demo
14        model='text-embedding-3-large'
15    )
16)
17
18docs.add_embedding_index('title', embedding=docs.embedding)
19
20# Initial load: processes all 100K documents
21docs.insert([...hundred_k_documents])
22
23# Add 1 new document: processes ONLY the new one
24docs.insert([{'document': 'new.pdf', 'title': 'Latest Report'}])
25# ✅ 1 embedding generated, not 100,001
26
27# Update a title: recomputes ONLY that row's embedding
28docs.update(
29    {'title': 'Updated Report'},
30    where=docs.title == 'Latest Report'
31)
32# ✅ 1 row recomputed, index updated incrementally