Documentation
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Overview ¶
Package embeddings provides a pluggable embedding provider interface. Supported: OpenAI, Voyage AI, and a local stub (returns hash-based pseudo-vectors).
Index ¶
- func Cosine(a, b []float32) float32
- func ExtractRetryDelay(errMsg string) time.Duration
- func GetInputType(model string, mode EmbedMode) string
- func GetMaxBatchSize(model string) int
- type EmbedMode
- type EmbeddingMemo
- type MemoizedProvider
- func (p *MemoizedProvider) Dims() int
- func (p *MemoizedProvider) Embed(ctx context.Context, text string) ([]float32, error)
- func (p *MemoizedProvider) EmbedBatch(ctx context.Context, texts []string) ([][]float32, error)
- func (p *MemoizedProvider) EmbedWithMode(ctx context.Context, text string, mode EmbedMode) ([]float32, error)
- func (p *MemoizedProvider) Memo() *EmbeddingMemo
- func (p *MemoizedProvider) Name() string
- type ModelDefaults
- type Pacer
- type Provider
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func ExtractRetryDelay ¶
ExtractRetryDelay parses rate-limit error messages for the recommended wait time. It recognises patterns such as "Please try again in 1.5s", "retry in 500ms", and "try again in 2 seconds". Returns 0 if no delay is found.
func GetInputType ¶
GetInputType returns the appropriate input_type string for the given model and embed mode. If the model has no asymmetric input types, an empty string is returned.
func GetMaxBatchSize ¶
GetMaxBatchSize returns the maximum batch size for a model, or 64 as the default when the model is unknown.
Types ¶
type EmbedMode ¶
type EmbedMode int
EmbedMode specifies whether a text is a document or a query for asymmetric embedding models.
type EmbeddingMemo ¶
type EmbeddingMemo struct {
// contains filtered or unexported fields
}
EmbeddingMemo caches embeddings by content hash to skip re-embedding unchanged content.
func NewEmbeddingMemo ¶
func NewEmbeddingMemo(maxEntries int) *EmbeddingMemo
NewEmbeddingMemo creates a memo cache with the given max entry count.
func (*EmbeddingMemo) Get ¶
func (m *EmbeddingMemo) Get(content string) ([]float32, bool)
Get returns a cached embedding for the content, if present.
func (*EmbeddingMemo) Len ¶
func (m *EmbeddingMemo) Len() int
Len returns the number of cached entries.
func (*EmbeddingMemo) Put ¶
func (m *EmbeddingMemo) Put(content string, embedding []float32)
Put stores an embedding for the given content, evicting the oldest entry if at capacity.
type MemoizedProvider ¶
type MemoizedProvider struct {
// contains filtered or unexported fields
}
MemoizedProvider wraps a Provider with content-addressed memoization.
func NewMemoizedProvider ¶
func NewMemoizedProvider(inner Provider, maxEntries int) *MemoizedProvider
NewMemoizedProvider wraps an existing Provider with a memo cache.
func (*MemoizedProvider) Dims ¶
func (p *MemoizedProvider) Dims() int
func (*MemoizedProvider) EmbedBatch ¶
func (*MemoizedProvider) EmbedWithMode ¶
func (*MemoizedProvider) Memo ¶
func (p *MemoizedProvider) Memo() *EmbeddingMemo
Memo returns the underlying cache for inspection/testing.
func (*MemoizedProvider) Name ¶
func (p *MemoizedProvider) Name() string
type ModelDefaults ¶
type ModelDefaults struct {
IndexInputType string // e.g., "search_document", "RETRIEVAL_DOCUMENT"
QueryInputType string // e.g., "search_query", "RETRIEVAL_QUERY"
Dimensions int // output dimensions
MaxBatchSize int // max texts per batch request
}
ModelDefaults maps model names to their optimal embedding parameters.
func GetModelDefaults ¶
func GetModelDefaults(model string) (ModelDefaults, bool)
GetModelDefaults returns the defaults for a known model. The second return value is false when the model is not in the table.
type Pacer ¶
type Pacer struct {
// contains filtered or unexported fields
}
Pacer enforces minimum intervals between API requests to stay under rate limits.
func (*Pacer) SetInterval ¶
SetInterval adjusts the pacer's minimum interval dynamically.
type Provider ¶
type Provider interface {
Embed(ctx context.Context, text string) ([]float32, error)
EmbedBatch(ctx context.Context, texts []string) ([][]float32, error)
EmbedWithMode(ctx context.Context, text string, mode EmbedMode) ([]float32, error)
Dims() int
Name() string
}
Provider generates vector embeddings for text.
func NewLocal ¶
func NewLocal() Provider
NewLocal returns a local stub provider that generates deterministic pseudo-vectors from SHA-256 hashes. Useful for testing and offline use. NOT semantically meaningful — use OpenAI/Voyage for real semantic search.
Source Files