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This script implements a FastAPI application that extracts text from PDF files, chunks the text, and uses a SentenceTransformer model to create embeddings for a FAISS index. It also provides a search endpoint to retrieve the top-3 passages based on a query.
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This week's task was to create a RAG pipeline using recent arXiv cs.CL papers, converting them into searchable chunks, embedding them, and indexing them with FAISS. We then implement a simple query interface that takes a user question, retrieves the top relevant chunks, and displays them for further processing.
The deliverables are described below and can be found in the following files:
uvicorn main:app --reload --port 5000and make requests by calling /search with param q as your query