Prompt_Engineering_using_Precision_RAG and Prompt-Engineering-GPT-Assistants-API-using-RAG

About Prompt_Engineering_using_Precision_RAG

GetachewAbebe/Prompt_Engineering_using_Precision_RAG

This project aims to develop an enterprise-grade Retrieval-Augmented Generation (RAG) system by automating the prompt engineering process. The goal is to create a comprehensive solution that simplifies the task of crafting effective prompts for Language Models (LLMs), enabling businesses to leverage advanced AI capabilities more efficiently.

About Prompt-Engineering-GPT-Assistants-API-using-RAG

GvHemanth/Prompt-Engineering-GPT-Assistants-API-using-RAG

This project showcases the implementation of a prompt engineering using the OpenAI Assistant API, specifically leveraging the Retrieval-Augmented Generation (RAG) system. By integrating cutting-edge language models, the system demonstrates advanced natural language understanding and generation capabilities.

This project helps researchers and academics quickly generate concise abstracts from long research papers. You provide a research paper, and the system outputs an abstract tailored to your desired length and tone. It's designed for anyone who needs to summarize complex documents efficiently, like scientists, students, or editors.