description:'Based on user intent and dataset descriptions, the Agent autonomously selects the best dataset for querying. Best for applications with distinct, limited datasets.',
},
retrieveMultiWay:{
title:'Multi-path retrieval',
description:'Based on user intent, queries across all datasets, retrieves relevant text from multi-sources, and selects the best results matching the user query after reranking. Configuration of the Rerank model API is required.',
},
rerankModelRequired:'Rerank model is required',
params:'Params',
top_k:'Top K',
top_kTip:'Used to filter segments that are most similar to user questions. The system will also dynamically adjust the value of Top K, according to max_tokens of the selected model.',
score_threshold:'Score Threshold',
score_thresholdTip:'Used to set the similarity threshold for segment filtering.',
retrieveChangeTip:'Modifying the index mode and retrieval mode may affect applications associated with this dataset.',
unavailableTip:'Embedding model is not available, the default embedding model needs to be configured',
datasets:'DATASETS',
datasetsApi:'API',
retrieval:{
semantic_search:{
title:'Vector Search',
description:'Generate query embeddings and search for the text chunk most similar to its vector representation.',
},
full_text_search:{
title:'Full-Text Search',
description:'Index all terms in the document, allowing users to search any term and retrieve relevant text chunk containing those terms.',
},
hybrid_search:{
title:'Hybrid Search',
description:'Execute full-text search and vector searches simultaneously, re-rank to select the best match for the user\'s query. Configuration of the Rerank model APIis necessary.',
recommend:'Recommend',
},
invertedIndex:{
title:'Inverted Index',
description:'Inverted Index is a structure used for efficient retrieval. Organized by terms, each term points to documents or web pages containing it.',