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.txt specializes in making large language models (LLMs) predictable and production-ready by providing structured generation capabilities. Their solutions enable seamless integration of LLMs into software systems, ensuring reliable outputs that adhere to defined schemas.
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A high-performance library for constraining LLM output to match a predefined JSON Schema.
A high-performance library for constraining LLM output to match a predefined regular expression.
A high-performance library for constraining LLM output to match a predefined grammar in EBNF, tree-sitter, or Lark format.
.txt provides structured generation capabilities for large language models, making their outputs predictable and reliable.
Developers and organizations looking to integrate LLMs into their software systems can benefit from .txt's structured outputs.
dotjson can be used for agent protocols, information extraction, annotation, synthetic data, and function calling.
Yes, .txt offers solutions that empower rapid deployment and scaling of large language models on your VPC.
dotjson, dotregex, and dotgrammar are available with APIs for Python, C, C++, and Rust.