The Fake News Detector based on BABYAGI is an AI-powered system that uses OpenAI's natural language processing (NLP) capabilities to detect fake news.The objective of this project is to develop a fake news detector using the BABYAGI platform that can browse the internet to verify the authenticity of news articles. The implementation of this project involves the use of OpenAI's API to complete tasks based on the context of the objective and the current task. The script runs an infinite loop that pulls the first task from the task list, sends it to the execution agent, enriches the result, and stores it in Chroma/Weaviate.The system leverages BABYAGI's task management system to create, prioritize, and execute tasks based on the objective of detecting fake news.
The system works by taking a piece of text as input and sending it to the execution agent, which uses OpenAI's API to analyze the text and determine whether it contains fake news. The result is then enriched and stored in Chroma/Weaviate for context.
Based on the result of the previous task and the predefined objective of detecting fake news, the system creates new tasks using BABYAGI's task_creation_agent() function. The prioritization_agent() function is used to reprioritize the task list based on the current task's ID.
The Fake News Detector based on BABYAGI aims to be simple and easy to understand while providing accurate results. This project can be extended by adding new features to improve the accuracy of fake news detection, such as incorporating additional datasets, training models, and refining the task management system.
Overall, the Fake News Detector based on BABYAGI is a promising solution to the growing problem of fake news, offering a scalable and adaptable approach to detecting and mitigating its harmful effects on individuals and society.