HannahIgboke/Building-a-RAG-System
A Retrieval Augmented Generation (RAG) system leveraging the Gemini API to answer questions on the “Leave No Context Behind” paper published by Google on April 10, 2024.
No commits in the last 6 months.
Stars
1
Forks
2
Language
Python
License
—
Category
Last pushed
May 01, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/HannahIgboke/Building-a-RAG-System"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
talkdai/dialog
RAG LLM Ops App for easy deployment and testing
michelderu/build-your-own-rag-chatbot
Workshop to build and deploy your own Chat Agent using Retrieval Augmented Generation with Astra DB
ronantakizawa/cacheaugmentedgeneration
A Demo of Cache-Augmented Generation (CAG) in an LLM
nicolaric/rahmenabkommen-gpt
"Ask your question about the new framework agreement between Switzerland and the EU." Answers...
ARUNAGIRINATHAN-K/pdf-RAG-question-answering
Upload PDFs → ask questions → get grounded answers.