AI · alternatives · 2026
24 alternatives to Anything To JSON – a language model for structured extraction
Hey HN! Erik here from banana.dev We’ve trained a small(ish) language model on structured extraction, and today we’re launching a playground for it at https://anythingtojson.com. Give it a try! This model continues our work on structured generation, following last week’s launch of Fructose[1], a python client for strongly-typed LLM responses. There seem to be two distinct halves of the problem intended to be solved by Fructose and structured generation: 1. the reasoning ability of the model, such as performing chain of thought, creative acts, and natural language tasks. In a way,…
Anything To JSON is a language model from banana.dev trained specifically for extracting structured data from text and converting it to JSON format. It uses constrained generation and fine-tuning to reliably pull… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Anything To JSON – a language model for structured extraction launched in 2024; newer entries below may have overtaken it.
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Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com · its alternatives →
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Hi HN! Erik here from Banana (formerly the serverless GPU platform), excited to show you what we’ve been working on next: Fructose Fructose is a python package to call LLMs as strongly typed functions. It uses function type signatures to guide the generation and guarantee a correctly typed output, in whatever basic/complex python datatype requested. By guaranteeing output structure, we believe this will enable more complex applications to be built, interweaving code with LLMs with code. For now, we’ve shipped Fructose as a client-only library simply calling gpt-4 (by default) with json…
2024 · github.com · its alternatives →
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Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground
2023 · automorphic.ai · its alternatives →
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Hey HN, I've been using GPT a lot lately in some side projects around data generation and benchmarking. During the course of prompt tuning I ended up with a pretty complicated request: the value that I was looking for, an explanation, a criticism, etc. JSON was the most natural output format for this but results would often be broken, have wrong types, or contain missing fields. There's been some positive movement in this space, like with jsonformer (https://github.com/1rgs/jsonformer) the other day. But nothing that was plug and play with GPT. This library consolidates…
2023 · github.com · its alternatives →
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Extract web data into structured JSON, no scraper required.
Jun 2026 · tabstack.ai · its alternatives →
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After two years of improvement, I think it's time to share it with you all. Here’s a quick overview: - Common features include validation, formatting, minification, and more. - Visualize JSON in a graph or table view. - Structured comparison with fallback to text comparison. - Navigate though JSON using JSON pointer. - Supports jq. Would love to hear the community's questions, thoughts and comments!
2024 · github.com · its alternatives →
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When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai · its alternatives →
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Yehuda's start as a programmer and the spec for building API
2016 · changelog.com · its alternatives →
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JSON Master▲82Format, repair, convert, and visualize JSON, XML, YAML, CSV, and TOML. Free developer platform with advanced visualizers and AI-powered syntax repair.
2020 · jsonmaster.com · its alternatives →
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2014 · journal.paul.querna.org · its alternatives →
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the JS/Node.JS library for encoding complex and unconventional data structures. Support for BigInts, TypedArrays, null, undefined, and Symbol. Multiple flavors available. - DO-SAY-GO/WeirdJSON
2020 · github.com · its alternatives →
- 15
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com · its alternatives →
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a lightweight dependency free javascript micro-library for making collapsable trees with JSON
2017 · maxleiter.github.io · its alternatives →
- 17
JSON5 — JSON for Humans. Contribute to json5/json5 development by creating an account on GitHub.
2012 · github.com · its alternatives →
- 18
A lightweight vanilla Javascript micro-library for making collapsible trees with JSON - MaxLeiter/jsonTree
2016 · github.com · its alternatives →
- 19
DocumentAI▲30Process any document to get structured JSON output using AI
2024 · finigami.com · its alternatives →
- 20
The from-scratch guide to building large language models in NodeJS.
9d ago · book.humanexperiences.io · its alternatives →
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An Experimental Regex Engine to Parse and Apply Bulk Changes to a JSON String Without Using 'JSON.parse()' for Deserialization - patternhelloworld/json-knife
2020 · github.com · its alternatives →
- 22
First time ever working on something like this, check it out
2024 · github.com · its alternatives →
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Weird JSON▲19the JS/Node.JS library for encoding complex and unconventional data structures. Support for BigInts, TypedArrays, null, undefined, and Symbol. Multiple flavors available. - DO-SAY-GO/WeirdJSON
2022 · github.com · its alternatives →
- 24
Also compare
- LLMs can generate valid JSON 100% of the time alternatives
- Fructose – LLM calls as strongly typed functions alternatives
- Structured output from LLMs without reprompting alternatives
- GPT-JSON – Structured and typehinted GPT responses in Python alternatives
- Tabstack Structured Extraction alternatives
- JSON For You – Visualize JSON in graph or table views alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →