HyperUpscale/simple-RAG-with-ollama

The code creates a question-answering system that uses a CSV file as its data source. It reads the CSV, splits text into smaller chunks, and then creates embeddings for a vector store with Chroma. A retriever and a local language model (Ollama) enable retrieval-augmented generation (RAG)

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