I've made an open-source tool (called Omni-NLI) for natural language inference. It can use different models to check if
a piece of text (called a premise) supports another piece of text (a hypothesis). The main application of a tool like
this is for soft fact-checking and consistency checking between pieces of texts like sentences.
Currently, Omni-NLI has the following features:
- Can be installed as a Python package with `pip install omni-nli[huggingface]`.
- Can be used on your own computer, so your data stays local and private.
- Has an MCP interface (for agents) and a REST API for conventional use as a microservice.
- Supports using models from different sources (Ollama, OpenRouter, and HuggingFace).
- Can be used to check if it seems that a model is contradicting itself.
- Supports showing the reasoning so you can see why it thinks a claim is wrong.
In any case, if you are interested in knowing more, there is more information in the links below:
I've made an open-source tool (called Omni-NLI) for natural language inference. It can use different models to check if a piece of text (called a premise) supports another piece of text (a hypothesis). The main application of a tool like this is for soft fact-checking and consistency checking between pieces of texts like sentences.
Currently, Omni-NLI has the following features:
In any case, if you are interested in knowing more, there is more information in the links below:
Project's GitHub repo: https://github.com/CogitatorTech/omni-nli
Project's documentation: https://cogitatortech.github.io/omni-nli/