TypeError: Cannot use scipy.linalg.eigh for sparse A with k >= N. Use scipy.linalg.eigh(A.toarray()) or reduce k. about raptor HOT 4 CLOSED

2024-03-18 21:48:13,833 - Successfully initialized TreeBuilder with Config 
        TreeBuilderConfig:
            Tokenizer: <Encoding 'cl100k_base'>
            Max Tokens: 100
            Num Layers: 2
            Threshold: 0.5
            Top K: 5
            Selection Mode: top_k
            Summarization Length: 100
            Summarization Model: <__main__.ROOTSummarizationModel object at 0x7f3ee5622a10>
            Embedding Models: {'EMB': <__main__.SBertEmbeddingModel object at 0x7f3db828bf50>}
            Cluster Embedding Model: EMB
        
        Reduction Dimension: 5
        Clustering Algorithm: RAPTOR_Clustering
        Clustering Parameters: {}
        
2024-03-18 21:48:13,833 - Successfully initialized ClusterTreeBuilder with Config 
        TreeBuilderConfig:
            Tokenizer: <Encoding 'cl100k_base'>
            Max Tokens: 100
            Num Layers: 2
            Threshold: 0.5
            Top K: 5
            Selection Mode: top_k
            Summarization Length: 100
            Summarization Model: <__main__.ROOTSummarizationModel object at 0x7f3ee5622a10>
            Embedding Models: {'EMB': <__main__.SBertEmbeddingModel object at 0x7f3db828bf50>}
            Cluster Embedding Model: EMB
        
        Reduction Dimension: 5
        Clustering Algorithm: RAPTOR_Clustering
        Clustering Parameters: {}
        
2024-03-18 21:48:13,833 - Successfully initialized RetrievalAugmentation with Config 
        RetrievalAugmentationConfig:
            
        TreeBuilderConfig:
            Tokenizer: <Encoding 'cl100k_base'>
            Max Tokens: 100
            Num Layers: 2
            Threshold: 0.5
            Top K: 5
            Selection Mode: top_k
            Summarization Length: 100
            Summarization Model: <__main__.ROOTSummarizationModel object at 0x7f3ee5622a10>
            Embedding Models: {'EMB': <__main__.SBertEmbeddingModel object at 0x7f3db828bf50>}
            Cluster Embedding Model: EMB
        
        Reduction Dimension: 5
        Clustering Algorithm: RAPTOR_Clustering
        Clustering Parameters: {}
        
            
            
        TreeRetrieverConfig:
            Tokenizer: <Encoding 'cl100k_base'>
            Threshold: 0.5
            Top K: 5
            Selection Mode: top_k
            Context Embedding Model: EMB
            Embedding Model: <__main__.SBertEmbeddingModel object at 0x7f3db828bf50>
            Num Layers: None
            Start Layer: None
        
            
            QA Model: <__main__.ROOTQAModel object at 0x7f3dbc9ec6d0>
            Tree Builder Type: cluster