Retrieval API¶
Retriever ¶
Retriever(vector_store: BaseVectorStore, number_of_chunks: int, method: Literal['simple'] = 'simple', search_mode: Literal['vector', 'hybrid'] = 'vector', ranker_strategy: str | None = None, ranker_k: int | None = None, ranker_alpha: float | None = None)
Class responsible for retrieving data from given vector store.
Parameters:
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vector_store(BaseVectorStore) –Vector store / vector index to retrieve data from.
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method(Literal['simple'], default:'simple') –Method describing how data should be retrieved.
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number_of_chunks(int) –Number of chunks to retrieve.
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search_mode(Literal['vector', 'hybrid'], default:"vector") –Search mode passed to the vector store: "vector" or "hybrid".
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ranker_strategy(str | None, default:None) –Ranking strategy for hybrid search: "rrf", "weighted", or "normalized".
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ranker_k(int | None, default:None) –Parameter k for the ranking function.
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ranker_alpha(float | None, default:None) –Alpha parameter for weighted ranking strategy.
Source code in ai4rag/rag/retrieval/retriever.py
Methods:¶
retrieve ¶
Retrieve relevant chunks from vector store.
Parameters:
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query(str) –Question for which chunks should be retrieved.
Returns:
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list[AI4RAGChunk]–Chunks with their metadata corresponding to the query.