ImadSaddik/RAG_With_Gemini
Providing useful context by using Retrieval Augmented Generation (RAG) to Gemini
This project helps you build a system that can answer questions using your own documents, like PDFs or JSON files. It takes your documents, breaks them into small pieces, and stores them in a way that makes them easy to search. When you ask a question, the system finds the most relevant pieces of your documents and uses them to give you a detailed answer. This is ideal for anyone who needs to quickly get answers from large amounts of specific information, like researchers, analysts, or customer support.
No commits in the last 6 months.
Use this if you want to create a custom chatbot or question-answering system that provides accurate information directly from your specific collection of documents.
Not ideal if you're looking for a pre-built, plug-and-play solution or if your primary goal is general knowledge question-answering without needing to reference your own files.
Stars
10
Forks
13
Language
Jupyter Notebook
License
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Category
Last pushed
Jan 18, 2024
Commits (30d)
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