Look up structured data with retrieval UDFs

How it works

What it covers

• Create lookup functions from tables with retrieval_udf
• Query by single or multiple keys
• Use lookups in computed columns for data enrichment

What it uses

Install

terminal

$pip install pixeltable

Pixeltable calls

pxt.create_table()pxt.retrieval_udf()insert()add_computed_column()

A look at the code

# Add a computed column that enriches orders with product details
orders.add_computed_column(
    product_info=get_product(sku=orders.product_sku)
)

# View enriched orders
orders.select(
    orders.order_id,
    orders.product_sku,
    orders.quantity,
    orders.product_info,
).collect()

One cell of the notebook, copied as it is. Open it in Colab for the rest.

• Use tool calling and MCP servers with LLMs

  Enable LLMs to call functions and tools, then execute the results automatically.

  Updated Oct 16, 2026Open in Colab

• Agentic Patterns

  Build the six architectural patterns of agentic AI (prompt chaining, routing, parallelization, tool use, evaluator-optimizer, orchestrator-worker) and the ReAct and planning strategies as Pixeltable tables and computed columns.

  Updated Sep 3, 2026Open in Colab

• Build a RAG pipeline

  Create a retrieval-augmented generation system that answers questions using your documents as context.

  Updated Apr 10, 2026Open in Colab

• LLM as judge

  Score model output with a second model, as a chain of computed columns

  Recipe · Updated Sep 8, 2026