A simple context retrieval RAG (Retrieval-Augmented Generation) pipeline involves several steps: data indexing, retrieval, and generation. First, the data is loaded, split into smaller chunks, then embeddings are created for the chunks and stored in a vector database. When a query is received, retrieves the most relevant chunks from the database.
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A simple context retrieval RAG (Retrieval-Augmented Generation) pipeline involves several steps: data indexing, retrieval, and generation. First, the data is loaded, split into smaller chunks, then embeddings are created for the chunks and stored in a vector database. When a query is received, retrieves the most relevant chunks from the database.
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mohsinraza2999/Simple-RAG-Context-Retrieval
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A simple context retrieval RAG (Retrieval-Augmented Generation) pipeline involves several steps: data indexing, retrieval, and generation. First, the data is loaded, split into smaller chunks, then embeddings are created for the chunks and stored in a vector database. When a query is received, retrieves the most relevant chunks from the database.
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