to that center for the final results.# By default the result document will be ordered/grouped by clusters.filter_ordered_cluster = EmbeddingsClusteringFilter(    embeddings=filter_embeddings,    num_clusters=10,    num_closest=1,)# If you want the final document to be ordered by the original retriever scores# you need to add the "sorted" parameter.filter_ordered_by_retriever = EmbeddingsClusteringFilter(    embeddings=filter_embeddings,    num_clusters=10,    num_closest=1,    sorted=True,)pipeline = DocumentCompressorPipeline(transformers=[filter_ordered_by_retriever])compression_retriever = ContextualCompressionRetriever(    base_compressor=pipeline, base_retriever=lotr)Re-order results to avoid performance degradation.‚ÄãNo matter the architecture of your model, there is a sustancial performance degradation when you include 10+ retrieved documents.
Lord of the Retrievers, also known as MergerRetriever, takes a list of retrievers as input and merges the results of their getrelevantdocuments() methods into a single list. The merged results will be a list of documents that are relevant to the query and that have been ranked by the different retrievers.
Lord of the Retrievers, also known as MergerRetriever, takes a list of retrievers as input and merges the results of their getrelevantdocuments() methods into a single list. The merged results will be a list of documents that are relevant to the query and that have been ranked by the different retrievers. ->: to that center for the final results.# By default the result document will be ordered/grouped by clusters.filter_ordered_cluster = EmbeddingsClusteringFilter(    embeddings=filter_embeddings,    num_clusters=10,    num_closest=1,)# If you want the final document to be ordered by the original retriever scores# you need to add the "sorted" parameter.filter_ordered_by_retriever = EmbeddingsClusteringFilter(    embeddings=filter_embeddings,    num_clusters=10,    num_closest=1,    sorted=True,)pipeline = DocumentCompressorPipeline(transformers=[filter_ordered_by_retriever])compression_retriever = ContextualCompressionRetriever(    base_compressor=pipeline, base_retriever=lotr)Re-order results to avoid performance degradation.‚ÄãNo matter the architecture of your model, there is a sustancial performance degradation when you include 10+ retrieved documents.