Fast + local semantic search over select body of Wikipedia pages.
Using pip:
pip install -r requirements.txtTo construct the search index:
python construct_index.py --save_dir=<directory name> --title=<title of main Wikipedia list>To query over the index:
python search.py --save_dir=<directory name>I chose to use prebuilt LLM orchestration tools such as LangChain and LlamaIndex for their efficiency and simplistic usage. Saves having to manually implement text chunking, embedding, and vector lookup via an algorithm like FAISS.
I also chose to use the open-source FastEmbed embeddings model (defaults to BAAI/bge-base-en on HuggingFace). This prioritizes latency and end-user experience while maintaining accuracy of the lookup.
A command line interface was chosen for simplicity and ease of implementation.