Method
describeDocumentRetrieverVersion GET
Copy GET

Describe a document retriever version.

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes documentRetrieverVersion str A unique string identifier associated with the document retriever version.
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY TYPE DESCRIPTION
success Boolean true if the call succeeded, false if there was an error
result DocumentRetrieverVersion
KEY TYPE Description
documentRetrieverId str The unique identifier of the Document Retriever.
documentRetrieverVersion str The unique identifier of the Document Retriever version.
createdAt str When the Document Retriever was created.
status str The status of Document Retriever version. It represents indexing status until indexing isn't complete, and deployment status after indexing is complete.
deploymentStatus str The status of deploying the Document Retriever version.
featureGroupId str The feature group id associated with the document retriever.
featureGroupVersion str The unique identifier of the feature group version at which the Document Retriever version is created.
error str The error message when it failed to create the document retriever version.
numberOfChunks int The number of chunks for the document retriever.
embeddingFileSize int The size of embedding file for the document retriever.
warnings list The warning messages when creating the document retriever.
resolvedConfig DocumentRetrieverConfig The resolved configurations, such as default settings, for indexing documents.
KEY TYPE Description
chunkSize int The size of chunks for vector store, i.e., maximum number of words in the chunk.
chunkOverlapFraction float The fraction of overlap between two consecutive chunks.
textEncoder str The text encoder used to encode texts in the vector store.
scoreMultiplierColumn str The values in this metadata column are used to modify the relevance scores of returned chunks.
pruneVectors bool Corpus specific transformation of vectors that applies dimensional reduction techniques to strip common components from the vectors.
indexMetadataColumns bool If True, metadata columns of the FG will also be used for indexing and querying.
useDocumentSummary bool If True, uses the summary of the document in addition to chunks of the document for indexing and querying.
summaryInstructions str Instructions for the LLM to generate the document summary.
Language:

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