You can implement a Multi-Hop Retrieval Mechanism by chaining multiple retrieval steps using tools like FAISS and a retriever model to iteratively refine context for complex question answering.
Here is the code snippet below:

In the above code we are using the following key points:
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SentenceTransformer and FAISS to build fast vector search retrieval.
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Two-step (multi-hop) retrieval by refining the query after the first search.
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Transformers pipeline to perform QA on the expanded multi-hop context.
Hence, multi-hop retrieval enhances QA systems by progressively deepening context for more accurate answers to complex queries.