Method RerankAsync
- Namespace
- LMKit.Embeddings
- Assembly
- LM-Kit.NET.dll
RerankAsync(string, PartitionSimilarity, float, CancellationToken)
Reranks the similarity score of a single PartitionSimilarity asynchronously and updates its RerankedScore property with the new blended score.
public Task RerankAsync(string query, PartitionSimilarity partitionSimilarity, float rerankedAlpha = 0.5, CancellationToken cancellationToken = default)
Parameters
query
stringThe input text query used for reranking. Must not be
null
.partitionSimilarity
PartitionSimilarityThe partition similarity object whose RerankedScore property will be updated. Must not be
null
.rerankedAlpha
floatA 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
CancellationTokenA token to cancel the operation if needed.
Returns
- Task
A
Task
representing the asynchronous reranking operation.
Exceptions
- ArgumentNullException
Thrown if
query
orpartitionSimilarity
isnull
.
RerankAsync(string, IEnumerable<PartitionSimilarity>, float, CancellationToken)
Reranks the similarity scores of multiple PartitionSimilarity instances asynchronously and updates each instance’s RerankedScore property with its new blended score.
public Task RerankAsync(string query, IEnumerable<PartitionSimilarity> partitionSimilarities, float rerankedAlpha = 0.5, CancellationToken cancellationToken = default)
Parameters
query
stringThe 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
floatA 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
CancellationTokenA token to cancel the operation if needed.
Returns
- Task
A
Task
representing the asynchronous reranking operation.
Exceptions
- ArgumentNullException
Thrown if
query
isnull
orpartitionSimilarities
isnull
or empty.