Use AI to smart-search your textbooks using Q/A!
To start, boot up the qdrant vector database. this where we'll store and query embeddings.
docker run -p 6333:6333 qdrant/qdrant
Next, upload your textbook using the following script. This will run Unstructured on the pdf, create embeddings, and send them to the database. It might take a while.
python ./upload_corpus.py -f ./DeepLearning.pdf
You're done! It's that easy. You can now open up a search bar and submit queries:
python ./search_library.py
You can upload multiple textbooks to the same database. If you would like to make additional databases you can edit the COLLECTION_NAME variable at the tops of search_library.py and upload_corpus.py.
To clean out unused collections, clean_vdb.py will delete all databases that don't match a certain pattern.
Install submodules:
git submodule update --init --recursive
Install python packages:
pip install -r requirements.txt