Chore/116 refactor indexes Query and Search

README.md

@@ -71,10 +71,9 @@ func main() {
 	docs, _ := loader.NewPDFToTextLoader("./kb").WithTextSplitter(textsplitter.NewRecursiveCharacterTextSplitter(2000, 200)).Load(context.Background())
 	openaiEmbedder := openaiembedder.New(openaiembedder.AdaEmbeddingV2)
 	simplevectorindex.New("db", ".", openaiEmbedder).LoadFromDocuments(context.Background(), docs)
-	similarities, _ := simplevectorindex.New("db", ".", openaiEmbedder).SimilaritySearch(context.Background(), query, indexoption.WithTopK(3))
-	qapipeline.New(openai.NewChat().WithVerbose(true)).Run(context.Background(), query, similarities.ToDocuments())
+	results, _ := simplevectorindex.New("db", ".", openaiEmbedder).Query(context.Background(), query, indexoption.WithTopK(3))
+	qapipeline.New(openai.NewChat().WithVerbose(true)).Run(context.Background(), query, results.ToDocuments())
 }
-
 ```
 
 This is the _famous_ 6-lines **lingoose** knowledge base chatbot. 🤖

examples/embeddings/knowledge_base/main.go

@@ -49,7 +49,7 @@ func main() {
 			break
 		}
 
-		similarities, err := docsVectorIndex.SimilaritySearch(context.Background(), query, indexoption.WithTopK(3))
+		similarities, err := docsVectorIndex.Query(context.Background(), query, indexoption.WithTopK(3))
 		if err != nil {
 			panic(err)
 		}

examples/embeddings/pinecone/main.go

@@ -47,7 +47,7 @@ func main() {
 	}
 
 	query := "What is the purpose of the NATO Alliance?"
-	similarities, err := pineconeIndex.SimilaritySearch(
+	similarities, err := pineconeIndex.Query(
 		context.Background(),
 		query,
 		indexoption.WithTopK(3),

examples/embeddings/qdrant/main.go

@@ -45,7 +45,7 @@ func main() {
 	}
 
 	query := "What is the purpose of the NATO Alliance?"
-	similarities, err := qdrantIndex.SimilaritySearch(
+	similarities, err := qdrantIndex.Query(
 		context.Background(),
 		query,
 		indexoption.WithTopK(3),

examples/embeddings/simpleVector/main.go

@@ -31,7 +31,7 @@ func main() {
 	}
 
 	query := "Describe within a paragraph what is the purpose of the NATO Alliance."
-	similarities, err := docsVectorIndex.SimilaritySearch(
+	similarities, err := docsVectorIndex.Query(
 		context.Background(),
 		query,
 		indexoption.WithTopK(3),

examples/embeddings/simplekb/main.go

@@ -17,6 +17,6 @@ func main() {
 	docs, _ := loader.NewPDFToTextLoader("./kb").WithTextSplitter(textsplitter.NewRecursiveCharacterTextSplitter(2000, 200)).Load(context.Background())
 	openaiEmbedder := openaiembedder.New(openaiembedder.AdaEmbeddingV2)
 	simplevectorindex.New("db", ".", openaiEmbedder).LoadFromDocuments(context.Background(), docs)
-	similarities, _ := simplevectorindex.New("db", ".", openaiEmbedder).SimilaritySearch(context.Background(), query, indexoption.WithTopK(3))
-	qapipeline.New(openai.NewChat().WithVerbose(true)).Run(context.Background(), query, similarities.ToDocuments())
+	results, _ := simplevectorindex.New("db", ".", openaiEmbedder).Query(context.Background(), query, indexoption.WithTopK(3))
+	qapipeline.New(openai.NewChat().WithVerbose(true)).Run(context.Background(), query, results.ToDocuments())
 }

index/index.go

@@ -18,11 +18,15 @@ const (
 	DefaultKeyContent = "content"
 )
 
-type SearchResult struct {
+type Data struct {
 	ID       string
 	Values   []float64
 	Metadata types.Meta
-	Score    float64
+}
+
+type SearchResult struct {
+	Data
+	Score float64
 }
 
 func (s *SearchResult) Content() string {

index/pinecone/pinecone.go

@@ -126,7 +126,7 @@ func (p *Index) IsEmpty(ctx context.Context) (bool, error) {
 
 }
 
-func (p *Index) SimilaritySearch(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
+func (p *Index) Search(ctx context.Context, values []float64, opts ...option.Option) (index.SearchResults, error) {
 
 	pineconeOptions := &option.Options{
 		TopK: defaultTopK,
@@ -140,7 +140,7 @@ func (p *Index) SimilaritySearch(ctx context.Context, query string, opts ...opti
 		pineconeOptions.Filter = map[string]string{}
 	}
 
-	matches, err := p.similaritySearch(ctx, query, pineconeOptions)
+	matches, err := p.similaritySearch(ctx, values, pineconeOptions)
 	if err != nil {
 		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
 	}
@@ -150,18 +150,46 @@ func (p *Index) SimilaritySearch(ctx context.Context, query string, opts ...opti
 	return index.FilterSearchResults(searchResults, pineconeOptions.TopK), nil
 }
 
-func (p *Index) similaritySearch(ctx context.Context, query string, opts *option.Options) ([]pineconeresponse.QueryMatch, error) {
+func (p *Index) Query(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
 
-	err := p.getProjectID(ctx)
+	pineconeOptions := &option.Options{
+		TopK: defaultTopK,
+	}
+
+	for _, opt := range opts {
+		opt(pineconeOptions)
+	}
+
+	if pineconeOptions.Filter == nil {
+		pineconeOptions.Filter = map[string]string{}
+	}
+
+	matches, err := p.query(ctx, query, pineconeOptions)
 	if err != nil {
 		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
 	}
 
+	searchResults := buildSearchResultsFromPineconeMatches(matches, p.includeContent)
+
+	return index.FilterSearchResults(searchResults, pineconeOptions.TopK), nil
+}
+
+func (p *Index) query(ctx context.Context, query string, opts *option.Options) ([]pineconeresponse.QueryMatch, error) {
+
 	embeddings, err := p.embedder.Embed(ctx, []string{query})
 	if err != nil {
 		return nil, err
 	}
 
+	return p.similaritySearch(ctx, embeddings[0], opts)
+}
+
+func (p *Index) similaritySearch(ctx context.Context, values []float64, opts *option.Options) ([]pineconeresponse.QueryMatch, error) {
+	err := p.getProjectID(ctx)
+	if err != nil {
+		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
+	}
+
 	includeMetadata := true
 	res := &pineconeresponse.VectorQuery{}
 	err = p.pineconeClient.VectorQuery(
@@ -170,7 +198,7 @@ func (p *Index) similaritySearch(ctx context.Context, query string, opts *option
 			IndexName:       p.indexName,
 			ProjectID:       *p.projectID,
 			TopK:            int32(opts.TopK),
-			Vector:          embeddings[0],
+			Vector:          values,
 			IncludeMetadata: &includeMetadata,
 			Namespace:       &p.namespace,
 			Filter:          opts.Filter.(map[string]string),
@@ -374,10 +402,12 @@ func buildSearchResultsFromPineconeMatches(matches []pineconeresponse.QueryMatch
 		}
 
 		searchResults[i] = index.SearchResult{
-			ID:       id,
-			Metadata: metadata,
-			Values:   match.Values,
-			Score:    score,
+			Data: index.Data{
+				ID:       id,
+				Metadata: metadata,
+				Values:   match.Values,
+			},
+			Score: score,
 		}
 	}
 

index/qdrant/qdrant.go

@@ -115,8 +115,7 @@ func (p *Index) IsEmpty(ctx context.Context) (bool, error) {
 
 }
 
-func (q *Index) SimilaritySearch(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
-
+func (q *Index) Search(ctx context.Context, values []float64, opts ...option.Option) (index.SearchResults, error) {
 	qdrantOptions := &option.Options{
 		TopK: defaultTopK,
 	}
@@ -125,7 +124,7 @@ func (q *Index) SimilaritySearch(ctx context.Context, query string, opts ...opti
 		opt(qdrantOptions)
 	}
 
-	matches, err := q.similaritySearch(ctx, query, qdrantOptions)
+	matches, err := q.similaritySearch(ctx, values, qdrantOptions)
 	if err != nil {
 		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
 	}
@@ -135,25 +134,40 @@ func (q *Index) SimilaritySearch(ctx context.Context, query string, opts ...opti
 	return index.FilterSearchResults(searchResults, qdrantOptions.TopK), nil
 }
 
-func (p *Index) similaritySearch(ctx context.Context, query string, opts *option.Options) ([]qdrantresponse.PointSearchResult, error) {
+func (q *Index) Query(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
+
+	qdrantOptions := &option.Options{
+		TopK: defaultTopK,
+	}
+
+	for _, opt := range opts {
+		opt(qdrantOptions)
+	}
 
-	embeddings, err := p.embedder.Embed(ctx, []string{query})
+	matches, err := q.query(ctx, query, qdrantOptions)
 	if err != nil {
-		return nil, err
+		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
 	}
 
+	searchResults := buildSearchResultsFromQdrantMatches(matches, q.includeContent)
+
+	return index.FilterSearchResults(searchResults, qdrantOptions.TopK), nil
+}
+
+func (q *Index) similaritySearch(ctx context.Context, values []float64, opts *option.Options) ([]qdrantresponse.PointSearchResult, error) {
+
 	if opts.Filter == nil {
 		opts.Filter = qdrantrequest.Filter{}
 	}
 
 	includeMetadata := true
 	res := &qdrantresponse.PointSearch{}
-	err = p.qdrantClient.PointSearch(
+	err := q.qdrantClient.PointSearch(
 		ctx,
 		&qdrantrequest.PointSearch{
-			CollectionName: p.collectionName,
+			CollectionName: q.collectionName,
 			Limit:          opts.TopK,
-			Vector:         embeddings[0],
+			Vector:         values,
 			WithPayload:    &includeMetadata,
 			Filter:         opts.Filter.(qdrantrequest.Filter),
 		},
@@ -166,6 +180,15 @@ func (p *Index) similaritySearch(ctx context.Context, query string, opts *option
 	return res.Result, nil
 }
 
+func (q *Index) query(ctx context.Context, query string, opts *option.Options) ([]qdrantresponse.PointSearchResult, error) {
+	embeddings, err := q.embedder.Embed(ctx, []string{query})
+	if err != nil {
+		return nil, err
+	}
+
+	return q.similaritySearch(ctx, embeddings[0], opts)
+}
+
 func (q *Index) createCollectionIfRequired(ctx context.Context) error {
 
 	if q.createCollection == nil {
@@ -299,10 +322,12 @@ func buildSearchResultsFromQdrantMatches(matches []qdrantresponse.PointSearchRes
 		}
 
 		searchResults[i] = index.SearchResult{
-			ID:       match.ID,
-			Metadata: metadata,
-			Values:   match.Vector,
-			Score:    match.Score,
+			Data: index.Data{
+				ID:       match.ID,
+				Metadata: metadata,
+				Values:   match.Vector,
+			},
+			Score: match.Score,
 		}
 	}
 

index/simpleVectorIndex/simpleVectorIndex.go

@@ -140,7 +140,24 @@ func (s *Index) IsEmpty() (bool, error) {
 	return len(s.data) == 0, nil
 }
 
-func (s *Index) SimilaritySearch(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
+func (s *Index) Search(ctx context.Context, values []float64, opts ...option.Option) (index.SearchResults, error) {
+	sviOptions := &option.Options{
+		TopK: defaultTopK,
+	}
+
+	for _, opt := range opts {
+		opt(sviOptions)
+	}
+
+	err := s.load()
+	if err != nil {
+		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
+	}
+
+	return s.similaritySearch(ctx, values, sviOptions)
+}
+
+func (s *Index) Query(ctx context.Context, query string, opts ...option.Option) (index.SearchResults, error) {
 
 	sviOptions := &option.Options{
 		TopK: defaultTopK,
@@ -160,24 +177,35 @@ func (s *Index) SimilaritySearch(ctx context.Context, query string, opts ...opti
 		return nil, fmt.Errorf("%s: %w", index.ErrInternal, err)
 	}
 
-	scores := s.cosineSimilarityBatch(embeddings[0])
+	return s.similaritySearch(ctx, embeddings[0], sviOptions)
+}
+
+func (s *Index) similaritySearch(
+	ctx context.Context,
+	embedding embedder.Embedding,
+	opts *option.Options,
+) (index.SearchResults, error) {
+
+	scores := s.cosineSimilarityBatch(embedding)
 
 	searchResults := make([]index.SearchResult, len(scores))
 
 	for i, score := range scores {
 		searchResults[i] = index.SearchResult{
-			ID:       s.data[i].ID,
-			Values:   s.data[i].Values,
-			Metadata: s.data[i].Metadata,
-			Score:    score,
+			Data: index.Data{
+				ID:       s.data[i].ID,
+				Values:   s.data[i].Values,
+				Metadata: s.data[i].Metadata,
+			},
+			Score: score,
 		}
 	}
 
-	if sviOptions.Filter != nil {
-		searchResults = sviOptions.Filter.(SimpleVectorIndexFilterFn)(searchResults)
+	if opts.Filter != nil {
+		searchResults = opts.Filter.(SimpleVectorIndexFilterFn)(searchResults)
 	}
 
-	return index.FilterSearchResults(searchResults, sviOptions.TopK), nil
+	return index.FilterSearchResults(searchResults, opts.TopK), nil
 }
 
 func (s *Index) cosineSimilarity(a embedder.Embedding, b embedder.Embedding) float64 {