Structured Output Parsing and Validation
Force LLMs to return reliable structured data using output parsers and schemas, and validate or retry when the model produces malformed output.
The Problem with Free Text
LLMs return prose by default, but your code needs structured data: JSON, a list, a typed object. Parsing free text with regex is fragile.
This lesson covers getting reliable structured output from models.
Asking for a Format
The first step is simply instructing the model to produce a specific format. But instruction alone is not enough; models drift, add prose, or wrap output in markdown.
prompt = 'Extract name and age as JSON: "Lena is 30"'
# model might reply: 'Sure! {"name":"Lena","age":30}'All lessons in this course
- Effective Prompt Design Techniques
- Integrating LLMs with LangChain
- Managing Model Parameters & Costs
- Structured Output Parsing and Validation