Data Validation tools

GuardRails

This is an open-source Python package for specifying structure and type, validating and correcting the outputs of large language models (LLMs).

• https://www.guardrailsai.com/docs

NeMo (by Nvidia)

This is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational applications. Guardrails (or "rails" for short) are specific ways of controlling the output of a large language model, such as not talking about politics, responding in a particular way to specific user requests, following a predefined dialog path, using a particular language style, extracting structured data, and more.

• https://github.com/NVIDIA/NeMo-Guardrails

TypeChat (by Microsoft)

This is a library that makes it easy to build natural language interfaces using types.

• https://github.com/microsoft/TypeChat
• https://microsoft.github.io/TypeChat/docs/introduction/

OpenAI Function

While it's possible to produce structured output without using function calling via careful prompting, function calling is more reliable at producing output that conforms to a particular format.

• https://platform.openai.com/docs/guides/function-calling

Langchain Output Parser

Output parsers are responsible for taking the output of an LLM and transforming it to a more suitable format. This is very useful when you are using LLMs to generate any form of structured data.

• https://python.langchain.com/docs/modules/model_io/output_parsers/