Developer details building and scaling a RAG search engine for 10,000 documents

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A developer built a RAG-based search engine called Dalil for a client to search thousands of Russian religious rulings by meaning. The system used retrieval to find relevant document chunks from a structured dataset, focusing on accurate search over answer generation. The process involved data cleanup, chunking records by their inherent structure, and using OpenAI embeddings for semantic search. The developer stored these vectors in Qdrant to enable the system to find documents with similar meanings to user queries.

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