A repository for a RAG model project in CS 579 at ISU
We used llamaIndex as the process pipeline and pinecone as vector storage.
We have a <data_lovecraft> folder which contains a collection of pdf files of H.P. Lovecraft's work that will be loaded into the vector storage.
The text chunk size is set to <512>
The embedding model is set to <bge-small-en-v1.5>
To Use: after adding a valid PineCone API key to the source code, call python load.py <your/path/filename.pdf> --index "index_name" to perform a commandline file upload.