Search Results for "data json"

json_repair is an open-source Python library designed to automatically fix malformed JSON data and convert it into valid, parseable structures. The tool is particularly useful in scenarios where JSON output is generated by large language models or external services that may produce syntactically invalid responses. Instead of failing when encountering errors such as missing quotes, trailing commas, or incomplete objects, the library analyzes the malformed data and reconstructs it into valid JSON.

Token-Oriented Object Notation is an open specification and toolkit for a data serialization format called Token-Oriented Object Notation (TOON), designed specifically to optimize how structured data is passed to large language models. The format aims to reduce token overhead compared with traditional formats like JSON while remaining human-readable and structurally expressive. TOON represents the same data model as JSON but removes unnecessary syntax such as braces and quotes, relying instead on indentation and structured tokens to represent objects and arrays. ...

TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. This makes the...

DocStrange is an open-source document understanding and extraction library designed to convert complex files into structured, LLM-ready outputs such as Markdown, JSON, CSV, and HTML. Developed by Nanonets, the project combines OCR, layout detection, table understanding, and structured extraction into one end-to-end pipeline, which reduces the need to stitch together multiple separate services. It is built for developers who need high-quality parsing from scans, photos, PDFs, office files,...

TONL is a cutting-edge data platform built around a production-ready serialization format designed to be both compact and powerful, combining human readability with performance features that make it suitable for large-scale applications and AI workflows. It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems.

LangChain Extract is an open-source reference application designed to demonstrate how large language models can be used to extract structured data from unstructured text and document files. The project implements a lightweight web service that allows developers to define extraction schemas and apply them to various sources such as plain text, HTML, or PDF documents. Built using FastAPI and the LangChain framework, the application exposes a REST API that can process documents and return structured outputs that match user-defined JSON schemas. ...

...Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation (exceeding 8,000 tokens), and structured data comprehension, such as tables and JSON formats. They support context lengths up to 128,000 tokens and offer multilingual capabilities in over 29 languages, including Chinese, English, French, Spanish, and more. The models are open-source under the Apache 2.0 license, with resources and documentation available on platforms like Hugging Face and ModelScope. ...