Algis DumbrisandClaude Opus 4.6
5dcb9e6149
Add HNSW-based vector search with configurable embedding providers (OpenAI, Ollama) and automatic FTS5 fallback when no provider is configured. Background pipeline embeds messages asynchronously on ingest, stores vectors in a pure-Go HNSW index, and retries on failure with exponential backoff. The search_messages MCP tool now supports search_mode (auto/semantic/fulltext) and returns ranked results with similarity scores. All existing tests continue to pass, CGO_ENABLED=0 cross-compilation verified. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
60 lines
1.6 KiB
Go
60 lines
1.6 KiB
Go
package embedding
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import "context"
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// MockProvider implements EmbeddingProvider for testing.
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type MockProvider struct {
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dims int
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name string
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embedFunc func(ctx context.Context, text string) ([]float32, error)
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batchFunc func(ctx context.Context, texts []string) ([][]float32, error)
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}
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// NewMockProvider creates a mock provider with the given dimensionality.
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func NewMockProvider(dims int) *MockProvider {
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return &MockProvider{
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dims: dims,
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name: "mock",
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}
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}
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// SetEmbedFunc overrides the default embedding behavior.
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func (m *MockProvider) SetEmbedFunc(fn func(ctx context.Context, text string) ([]float32, error)) {
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m.embedFunc = fn
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}
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// SetBatchFunc overrides the default batch embedding behavior.
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func (m *MockProvider) SetBatchFunc(fn func(ctx context.Context, texts []string) ([][]float32, error)) {
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m.batchFunc = fn
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}
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func (m *MockProvider) Embed(ctx context.Context, text string) ([]float32, error) {
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if m.embedFunc != nil {
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return m.embedFunc(ctx, text)
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}
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// Generate a deterministic vector based on text length
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vec := make([]float32, m.dims)
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for i := range vec {
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vec[i] = float32(len(text)%10+i) / float32(m.dims)
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}
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return vec, nil
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}
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func (m *MockProvider) EmbedBatch(ctx context.Context, texts []string) ([][]float32, error) {
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if m.batchFunc != nil {
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return m.batchFunc(ctx, texts)
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}
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results := make([][]float32, len(texts))
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for i, text := range texts {
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vec, err := m.Embed(ctx, text)
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if err != nil {
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return nil, err
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}
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results[i] = vec
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}
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return results, nil
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}
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func (m *MockProvider) Dimensions() int { return m.dims }
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func (m *MockProvider) Name() string { return m.name }
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