Extract fields from LLM JSON responses
Parse and access specific fields from structured JSON responses returned by language models.
Updated Open in Colab
Working with the Pixeltable CLI
You defined a multimodal pipeline in Python and now need to inspect tables, debug computed columns, roll back changes, and expose HTTP endpoints without writing more application code.
Core Operations · Notebook · Updated
Colab runs it in your browser. If it calls a model provider, it asks for that provider's API key in a cell.
How it works
The pxt CLI ships with Pixeltable (v0.7.4+). Catalog commands talk to a local daemon (~40 ms per call after the first invocation). Write tables in Python, then inspect and serve them from the terminal.
See the CLI reference for every flag.
What it covers
- Inspect catalogs with pxt ls, describe, columns, and idxs
- Query and debug rows with pxt rows, count, get, and errors
- Manage versions with pxt history and pxt revert
- Script and automate with --json, -f, and pxt shell
- Write tables and routes in app.py. pxt schema update creates the tables; pxt service diff / update starts HTTP
What it uses
- Install
- terminalpip install 'pixeltable[serve]'
- Pixeltable calls
video.frame_iterator()pxt.create_table()pxt.create_view()@pxt.udfadd_computed_column()insert()
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Combine data from multiple tables using inner, left, and cross joins.
Updated Open in ColabTrack changes and revert to previous versions
Undo mistakes, audit changes, and create point-in-time snapshots of your data.
Updated Open in Colab