Real-Time Fact-Checking System

A real-time system that checks claims in text or speech against trusted sources and flags the ones that look false.

A real-time system that checks claims in text or speech against trusted sources and flags the ones that look false. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to work with language models and text or speech: preparing text data, using or fine-tuning a model, evaluating it and building an interface around it.

The main parts are real-time processing of incoming data, text or speech data preparation, model training, fine-tuning or prompting, evaluation with task-appropriate metrics, and a chat or web interface to use it. The reference build uses Apache Kafka, Python, Hugging Face Transformers, spaCy, and PyTorch, with a clear project structure, setup instructions and sample data so that it can be run and extended.