Method Rerank

Namespace

LMKit.Embeddings

Assembly

LM-Kit.NET.dll

Rerank(string, PartitionSimilarity, float, CancellationToken)

Reranks the similarity score of a single PartitionSimilarity synchronously by invoking the reranking model and updating its RerankedScore property with the new blended score.

public void Rerank(string query, PartitionSimilarity partitionSimilarity, float rerankedAlpha = 0.5, CancellationToken cancellationToken = default)

Parameters

query string

The input text query used for reranking. Must not be null.

partitionSimilarity PartitionSimilarity

The partition similarity object whose RerankedScore property will be updated. Must not be null.

rerankedAlpha float

A blending factor between the original similarity (top[i]) and the reranker model score (rerank[i]), in the range [0 - 1]. Computed as:

final_score = (α × top[i]) + ((1 − α) × rerank[i])

For example, with α = 0.5:

final_score = (0.5 × 0.95) + (0.5 × 0.07) = 0.475 + 0.035 = 0.510

A typical default is 0.5 for equal weighting.

cancellationToken CancellationToken

A token to cancel the operation if needed.

Exceptions

ArgumentNullException

Thrown if query or partitionSimilarity is null.

Rerank(string, IEnumerable<PartitionSimilarity>, float, CancellationToken)

Reranks the similarity scores of multiple PartitionSimilarity instances synchronously by invoking the reranking model and updating each instance’s RerankedScore property with its new blended score.

public void Rerank(string query, IEnumerable<PartitionSimilarity> partitionSimilarities, float rerankedAlpha = 0.5, CancellationToken cancellationToken = default)

Parameters

query string

The input text query used for reranking. Must not be null.

partitionSimilarities IEnumerable<PartitionSimilarity>

A collection of partition similarity objects whose RerankedScore properties will be updated. Must not be null or empty.

rerankedAlpha float

A blending factor between the original similarity (top[i]) and the reranker model score (rerank[i]), in the range [0 - 1]. Computed as:

final_score = (α × top[i]) + ((1 − α) × rerank[i])

For example, with α = 0.5:

final_score = (0.5 × 0.95) + (0.5 × 0.07) = 0.475 + 0.035 = 0.510

A typical default is 0.5 for equal weighting.

cancellationToken CancellationToken

A token to cancel the operation if needed.

Exceptions

ArgumentNullException

Thrown if query is null or partitionSimilarities is null or empty.