nadeesha/structlm
Token-efficient schema definition for getting structured output from LLMs.
This helps developers working with Large Language Models (LLMs) to define and enforce specific data formats for the LLM's output. You input a clearly defined schema (a blueprint for your data), and the LLM then generates structured data that precisely matches that blueprint. This tool is ideal for software engineers, AI/ML engineers, and data scientists who need to ensure LLM responses are consistent and usable by other systems.
No commits in the last 6 months. Available on npm.
Use this if you need a token-efficient way to guide LLMs to produce structured data that adheres to a precise, custom schema, and you also need to validate the LLM's output against that schema.
Not ideal if you just need free-form text generation from an LLM, or if you are not a developer and don't work with LLM integrations or TypeScript/JavaScript.
Stars
8
Forks
1
Language
TypeScript
License
Apache-2.0
Category
Last pushed
Aug 03, 2025
Commits (30d)
0
Dependencies
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/nadeesha/structlm"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Ahoo-Wang/fetcher
Fetcher is not just another HTTP client—it's a complete ecosystem designed for modern web...
eric-tramel/slop-guard
Slop Scoring to Stop Slop
arena-ai/structured-logprobs
OpenAI's Structured Outputs with Logprobs
567-labs/instructor-js
structured extraction for llms
martosaur/instructor_lite
Structured outputs for LLMs in Elixir