RAG-ChatBot and rag-chatgpt
About RAG-ChatBot
Lizhecheng02/RAG-ChatBot
A basic application using langchain, streamlit, and large language models to build a system for Retrieval-Augmented Generation (RAG) based on documents, also includes how to use Groq and deploy your own applications.
This helps you quickly find answers and insights within your own collection of documents, like PDFs, Word files, or text documents. You upload your files, and then you can ask questions in plain language to get concise answers based only on the information in those documents. This is ideal for researchers, analysts, or anyone who needs to extract specific information from a large personal or team document library.
About rag-chatgpt
mkmenta/rag-chatgpt
This is a simple lab I have implemented to test Knowledge Augmented or Retrieval Augmented Generation (RAG) with Large Language Models. In particular, I am using LangChain, Streamlit, and OpenAI ChatGPT API.
This tool helps you converse with an AI chatbot, like ChatGPT, using your own documents as its knowledge base. You input your documents and then ask questions directly through a simple web interface. The output is a conversational response from the AI that is specifically informed by the information in your provided files, making it useful for anyone needing to query specific information within their own text collections.
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