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Newsletter #282: Build Structured LLM Outputs with Guidance Constraints

Newsletter #282: Build Structured LLM Outputs with Guidance Constraints

Grab your coffee. Here are this week’s highlights.


๐Ÿค COLLABORATION

What Data Engineers Really Think About Airflow (5.8K Surveyed)

What Data Engineers Really Think About Airflow (5.8K Surveyed)

Astronomer analyzed 5.8k+ responses from data engineers on how they are navigating Airflow today and the findings might surprise you.

You’ll learn:

  • How early adopters are using Airflow 3 features in production
  • Which teams are bringing AI into production and what’s holding others back
  • 94% believe that Airflow is beneficial to their career

๐Ÿ“… Today’s Picks

Build Structured LLM Outputs with Guidance Constraints

Code example: Build Structured LLM Outputs with Guidance Constraints

Problem

Tools like Instructor and PydanticAI validate outputs after generation. If validation fails, they send the error back to the LLM and retry.

Each retry means paying for tokens that didn’t produce usable output.

Solution

Guidance works differently. It constrains tokens during generation, so invalid outputs can’t be produced in the first place.

Key capabilities:

  • Constrained outputs via regex patterns and selection functions
  • Python control flow (if/else, loops) during generation
  • JSON generation with Pydantic schema validation

pandas 3.0: The End of SettingWithCopyWarning

Code example: pandas 3.0: The End of SettingWithCopyWarning

Problem

When you filter a DataFrame and modify the result, you expect the original to stay unchanged.

But sometimes pandas modified your original data anyway, triggering the SettingWithCopyWarning.

Solution

pandas 3.0 fixes this. Filtering now always creates a separate copy, so modifying the result never affects your original data.

Upgrade to pandas 3.0 with “pip install -U pandas”.


โ˜•๏ธ Weekly Finds

fake2db [Data] – Create custom test databases populated with fake data across SQLite, MySQL, PostgreSQL, MongoDB, Redis, and CouchDB

POT [ML] – Python Optimal Transport library providing solvers for optimization problems in signal processing, image processing, and machine learning

graphic-walker [Data Viz] – Open-source Tableau alternative for data scientists to analyze data and visualize patterns with drag-and-drop operations

Looking for a specific tool? Explore 70+ Python tools โ†’

๐Ÿ“š Latest Deep Dives

From CSS Selectors to Natural Language: Web Scraping with ScrapeGraphAI – Web scraping without selector maintenance. ScrapeGraphAI uses LLMs to extract data from any site using plain English prompts and Pydantic schemas.


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