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JinaRerankRetriever

class JinaRerankRetriever(BaseRetriever):
An implementation of the BaseRetriever using the Jina AI Reranker model. This retriever uses Jina AI’s reranking API to re-order retrieved documents based on their relevance to the query. It supports multilingual retrieval across 100+ languages. Parameters:
  • model_name (Union[JinaRerankerModelType, str]): The model name to use for re-ranking.
  • api_key (str, optional): The API key for authenticating with the Jina AI service.
  • References:
  • https: //jina.ai/reranker/

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init

def __init__(
    self,
    model_name: Union[JinaRerankerModelType, str] = JinaRerankerModelType.JINA_RERANKER_V2_BASE_MULTILINGUAL,
    api_key: str | None = None
):
Initializes an instance of the JinaRerankRetriever. This constructor sets up the API key for interacting with the Jina AI Reranker API. Parameters:
  • model_name (Union[JinaRerankerModelType, str]): The name of the model to be used for re-ranking. Can be a JinaRerankerModelType enum value or a string. Defaults to JinaRerankerModelType.JINA_RERANKER_V2_BASE_MULTILINGUAL.
  • api_key (Optional[str]): The API key for authenticating requests to the Jina AI API. If not provided, the method will attempt to retrieve the key from the environment variable ‘JINA_API_KEY’.

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query

def query(
    self,
    query: str,
    retrieved_result: list[dict[str, Any]],
    top_k: int = DEFAULT_TOP_K_RESULTS
):
Queries and compiles results using the Jina AI re-ranking model. Parameters:
  • query (str): Query string for information retriever.
  • retrieved_result (List[Dict[str, Any]]): The content to be re-ranked, should be the output from BaseRetriever like VectorRetriever. Each dict should have a ‘text’ key containing the document text.
  • top_k (int, optional): The number of top results to return during retrieval. Must be a positive integer. Defaults to DEFAULT_TOP_K_RESULTS.
Returns: List[Dict[str, Any]]: Concatenated list of the query results, each containing the original data plus a ‘similarity score’.