Define contracts
Distinguish valid structure, business rules and evidence support.
Practical AI · EDITION 1.0.0
Validate Structured AI Outputs
Build strict parsing, field validation, evidence correspondence and refusal handling for synthetic extraction responses.
By Sanjaay Gowda T S · For python developers integrating generated data into applications.
You need: Basic Python dictionaries and exceptions; Familiarity with JSON objects and strings
Runtime and hardware details
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Basic Python dictionaries and exceptions; Familiarity with JSON objects and strings.
Full setup and scope ↓$2.99USD · one-time purchase
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review remains pending. Automated checks and agent review are not certification.
PDF + EPUB + companion project. Any applicable tax is shown at checkout. Single-reader ebook terms; companion code is MIT licensed.
TRY THE FREE SAMPLE
See how the guide teaches.
Read 7 sample pages to explore the introduction, first chapter and teaching approach before you choose the complete edition.
Read free sample PDF · No checkout required
WHAT YOU WILL LEARN
Understand each part.
Inspect every boundary.
Reject ambiguous output
Handle duplicate keys, wrong types and unsupported fields explicitly.
Retain failures
Design bounded repair and contract migrations with meaningful tests.
INSIDE THE BOOK
9 focused chapters.
- Specify the output contract
- Parse without silent repair
- Validate types and fields
- Check cross-field meaning
- Attach evidence to extraction
- Handle abstention and errors
- Design bounded repair
- Test contract migrations
- Integrate with a reviewed workflow
Your download includes
- 21-page tagged PDF with linked contents
- Reflowable EPUB for ebook readers
- Local Python project, fictional input, recorded expected JSON output and 13 companion tests
- 3 explanatory diagrams
- 9 chapters with exercises and worked answers
Before you begin
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Learning prerequisites: Basic Python dictionaries and exceptions; Familiarity with JSON objects and strings.
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review is pending.
The included examples are synthetic teaching material. Model access, software subscriptions, hosting, ongoing updates and consulting are not included.
CLEAR EXPECTATIONS
Before you buy.
What will I build?
Build strict parsing, field validation, evidence correspondence and refusal handling for synthetic extraction responses. The local companion uses fictional teaching fixtures. Project limits: Checks exact fields and shallow source-text correspondence, rather than semantic entailment. It includes no model API, action execution, automatic repair or full JSON Schema engine.
What was tested?
The 13 companion tests passed on the packaged project. The supplied fictional fixture produced its recorded expected JSON output. EPUBCheck reported no errors or warnings; DAISY Ace and PDF/UA automated checks passed. These local teaching checks are not production accuracy claims or certification. Independent human technical, editorial and assistive-technology reader review remains pending.
How do I get the files?
Complete the secure Lemon Squeezy checkout to access the PDF, EPUB and companion ZIP. Keep your receipt and download access private. This is a one-time purchase of edition 1.0.0; ongoing updates and consulting are not included.
Can I share the book or the companion code?
The full ebook is licensed to one reader. The labelled free sample may be shared unchanged. The companion project is MIT licensed and may be adapted or shared with its licence notice. See the exact ebook terms.
Turn plausible JSON into a reviewable data contract.
One book. A complete learning project. Evidence you can inspect.
AI-assisted · Independent human review pending
$2.99USDBuy ebook