DocArrayRetriever()| Name | Type | Description |
|---|---|---|
index* | unknown | One of the above-mentioned index instances |
embeddings* | unknown | Embedding model to represent text as vectors |
search_field* | unknown | Field to consider for searching in the documents. Should be an embedding/vector/tensor. |
content_field* | unknown | Field that represents the main content in your document schema.
Will be used as a |
search_type* | unknown | Type of search to perform (similarity / mmr) |
filters* | unknown | Filters applied for document retrieval. |
top_k* | unknown |
DocArray Document Indices retriever.
Currently, it supports 5 backends: InMemoryExactNNIndex, HnswDocumentIndex, QdrantDocumentIndex, ElasticDocIndex, and WeaviateDocumentIndex.
Number of documents to return