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.

33
/ 100
Emerging

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.

No commits in the last 6 months.

Use this if you need to chat with your own documents to quickly retrieve information, without manually searching through each file.

Not ideal if you need to perform complex data analysis, summarize entire reports, or you're looking for a general-purpose conversational AI.

document-search information-retrieval knowledge-management research-assistance data-extraction
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 18 / 25

How are scores calculated?

Stars

38

Forks

15

Language

Jupyter Notebook

License

Last pushed

May 09, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/Lizhecheng02/RAG-ChatBot"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.