Dep: trying sugarme tokenizer

go.mod

@@ -16,7 +16,7 @@ require (
 	github.com/neurosnap/sentences v1.1.2
 	github.com/playwright-community/playwright-go v0.5700.1
 	github.com/rivo/tview v0.42.0
-	github.com/takara-ai/go-tokenizers v1.0.0
+	github.com/sugarme/tokenizer v0.3.0
 	github.com/yalue/onnxruntime_go v1.27.0
 	github.com/yuin/goldmark v1.4.13
 )
@@ -27,6 +27,7 @@ require (
 	github.com/dustin/go-humanize v1.0.1 // indirect
 	github.com/ebitengine/oto/v3 v3.4.0 // indirect
 	github.com/ebitengine/purego v0.9.1 // indirect
+	github.com/emirpasic/gods v1.18.1 // indirect
 	github.com/gdamore/encoding v1.0.1 // indirect
 	github.com/go-jose/go-jose/v3 v3.0.4 // indirect
 	github.com/go-stack/stack v1.8.1 // indirect
@@ -35,10 +36,14 @@ require (
 	github.com/hajimehoshi/oto/v2 v2.3.1 // indirect
 	github.com/lucasb-eyer/go-colorful v1.3.0 // indirect
 	github.com/mattn/go-isatty v0.0.20 // indirect
+	github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db // indirect
 	github.com/ncruces/go-strftime v1.0.0 // indirect
+	github.com/patrickmn/go-cache v2.1.0+incompatible // indirect
 	github.com/pkg/errors v0.9.1 // indirect
 	github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec // indirect
 	github.com/rivo/uniseg v0.4.7 // indirect
+	github.com/schollz/progressbar/v2 v2.15.0 // indirect
+	github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c // indirect
 	golang.org/x/exp v0.0.0-20251209150349-8475f28825e9 // indirect
 	golang.org/x/net v0.48.0 // indirect
 	golang.org/x/sys v0.39.0 // indirect

go.sum

@@ -21,6 +21,8 @@ github.com/ebitengine/oto/v3 v3.4.0 h1:br0PgASsEWaoWn38b2Goe7m1GKFYfNgnsjSd5Gg+/
 github.com/ebitengine/oto/v3 v3.4.0/go.mod h1:IOleLVD0m+CMak3mRVwsYY8vTctQgOM0iiL6S7Ar7eI=
 github.com/ebitengine/purego v0.9.1 h1:a/k2f2HQU3Pi399RPW1MOaZyhKJL9w/xFpKAg4q1s0A=
 github.com/ebitengine/purego v0.9.1/go.mod h1:iIjxzd6CiRiOG0UyXP+V1+jWqUXVjPKLAI0mRfJZTmQ=
+github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc=
+github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
 github.com/gdamore/encoding v1.0.1 h1:YzKZckdBL6jVt2Gc+5p82qhrGiqMdG/eNs6Wy0u3Uhw=
 github.com/gdamore/encoding v1.0.1/go.mod h1:0Z0cMFinngz9kS1QfMjCP8TY7em3bZYeeklsSDPivEo=
 github.com/gdamore/tcell/v2 v2.13.2 h1:5j4srfF8ow3HICOv/61/sOhQtA25qxEB2XR3Q/Bhx2g=
@@ -61,10 +63,14 @@ github.com/mattn/go-isatty v0.0.20 h1:xfD0iDuEKnDkl03q4limB+vH+GxLEtL/jb4xVJSWWE
 github.com/mattn/go-isatty v0.0.20/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
 github.com/mattn/go-sqlite3 v1.14.22 h1:2gZY6PC6kBnID23Tichd1K+Z0oS6nE/XwU+Vz/5o4kU=
 github.com/mattn/go-sqlite3 v1.14.22/go.mod h1:Uh1q+B4BYcTPb+yiD3kU8Ct7aC0hY9fxUwlHK0RXw+Y=
+github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db h1:62I3jR2EmQ4l5rM/4FEfDWcRD+abF5XlKShorW5LRoQ=
+github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db/go.mod h1:l0dey0ia/Uv7NcFFVbCLtqEBQbrT4OCwCSKTEv6enCw=
 github.com/ncruces/go-strftime v1.0.0 h1:HMFp8mLCTPp341M/ZnA4qaf7ZlsbTc+miZjCLOFAw7w=
 github.com/ncruces/go-strftime v1.0.0/go.mod h1:Fwc5htZGVVkseilnfgOVb9mKy6w1naJmn9CehxcKcls=
 github.com/neurosnap/sentences v1.1.2 h1:iphYOzx/XckXeBiLIUBkPu2EKMJ+6jDbz/sLJZ7ZoUw=
 github.com/neurosnap/sentences v1.1.2/go.mod h1:/pwU4E9XNL21ygMIkOIllv/SMy2ujHwpf8GQPu1YPbQ=
+github.com/patrickmn/go-cache v2.1.0+incompatible h1:HRMgzkcYKYpi3C8ajMPV8OFXaaRUnok+kx1WdO15EQc=
+github.com/patrickmn/go-cache v2.1.0+incompatible/go.mod h1:3Qf8kWWT7OJRJbdiICTKqZju1ZixQ/KpMGzzAfe6+WQ=
 github.com/pkg/errors v0.9.1 h1:FEBLx1zS214owpjy7qsBeixbURkuhQAwrK5UwLGTwt4=
 github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
 github.com/playwright-community/playwright-go v0.5700.1 h1:PNFb1byWqrTT720rEO0JL88C6Ju0EmUnR5deFLvtP/U=
@@ -77,12 +83,17 @@ github.com/rivo/tview v0.42.0 h1:b/ftp+RxtDsHSaynXTbJb+/n/BxDEi+W3UfF5jILK6c=
 github.com/rivo/tview v0.42.0/go.mod h1:cSfIYfhpSGCjp3r/ECJb+GKS7cGJnqV8vfjQPwoXyfY=
 github.com/rivo/uniseg v0.4.7 h1:WUdvkW8uEhrYfLC4ZzdpI2ztxP1I582+49Oc5Mq64VQ=
 github.com/rivo/uniseg v0.4.7/go.mod h1:FN3SvrM+Zdj16jyLfmOkMNblXMcoc8DfTHruCPUcx88=
+github.com/schollz/progressbar/v2 v2.15.0 h1:dVzHQ8fHRmtPjD3K10jT3Qgn/+H+92jhPrhmxIJfDz8=
+github.com/schollz/progressbar/v2 v2.15.0/go.mod h1:UdPq3prGkfQ7MOzZKlDRpYKcFqEMczbD7YmbPgpzKMI=
 github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
+github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
 github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
 github.com/stretchr/testify v1.10.0 h1:Xv5erBjTwe/5IxqUQTdXv5kgmIvbHo3QQyRwhJsOfJA=
 github.com/stretchr/testify v1.10.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
-github.com/takara-ai/go-tokenizers v1.0.0 h1:C+UQl3fPFw08YQdwthzPZbqykh6yumzjPrSs+3OSe7o=
+github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c h1:pwb4kNSHb4K89ymCaN+5lPH/MwnfSVg4rzGDh4d+iy4=
-github.com/takara-ai/go-tokenizers v1.0.0/go.mod h1:2A7hN3gMtAARJ2V3sYyIzTDm+GNTudBX+CwUOyIVH2A=
+github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c/go.mod h1:2gwkXLWbDGUQWeL3RtpCmcY4mzCtU13kb9UsAg9xMaw=
+github.com/sugarme/tokenizer v0.3.0 h1:FE8DYbNSz/kSbgEo9l/RjgYHkIJYEdskumitFQBE9FE=
+github.com/sugarme/tokenizer v0.3.0/go.mod h1:VJ+DLK5ZEZwzvODOWwY0cw+B1dabTd3nCB5HuFCItCc=
 github.com/yalue/onnxruntime_go v1.27.0 h1:c1YSgDNtpf0WGtxj3YeRIb8VC5LmM1J+Ve3uHdteC1U=
 github.com/yalue/onnxruntime_go v1.27.0/go.mod h1:b4X26A8pekNb1ACJ58wAXgNKeUCGEAQ9dmACut9Sm/4=
 github.com/yuin/goldmark v1.4.13 h1:fVcFKWvrslecOb/tg+Cc05dkeYx540o0FuFt3nUVDoE=

rag/embedder.go

@@ -10,8 +10,8 @@ import (
 	"log/slog"
 	"net/http"
 
-	"github.com/takara-ai/go-tokenizers/tokenizers"
+	"github.com/sugarme/tokenizer"
-
+	"github.com/sugarme/tokenizer/pretrained"
 	"github.com/yalue/onnxruntime_go"
 )
 
@@ -141,59 +141,168 @@ func (a *APIEmbedder) EmbedSlice(lines []string) ([][]float32, error) {
 // 1. Loading ONNX models locally
 // 2. Using a Go ONNX runtime (like gorgonia/onnx or similar)
 // 3. Converting text to embeddings without external API calls
-
 type ONNXEmbedder struct {
 	session   *onnxruntime_go.DynamicAdvancedSession
-	tokenizer *tokenizers.Tokenizer
+	tokenizer *tokenizer.Tokenizer
-	dims      int // 768, 512, 256, or 128 for Matryoshka
+	dims      int // embedding dimension (e.g., 768)
+	logger    *slog.Logger
 }
 
-func (e *ONNXEmbedder) EmbedSlice(texts []string) ([][]float32, error) {
+func NewONNXEmbedder(modelPath, tokenizerPath string, dims int, logger *slog.Logger) (*ONNXEmbedder, error) {
-	// Batch processing
+	// Load tokenizer using sugarme/tokenizer
-	inputs := e.prepareBatch(texts)
+	tok, err := pretrained.FromFile(tokenizerPath)
-	outputs := make([][]float32, len(texts))
+	if err != nil {
-
+		return nil, fmt.Errorf("failed to load tokenizer: %w", err)
-	// Run batch inference (much faster)
+	}
-	err := e.session.Run(inputs, outputs)
+	// Create ONNX session
-	return outputs, err
-}
-
-func NewONNXEmbedder(modelPath string) (*ONNXEmbedder, error) {
-	// Load ONNX model
 	session, err := onnxruntime_go.NewDynamicAdvancedSession(
 		modelPath, // onnx/embedgemma/model_q4.onnx
 		[]string{"input_ids", "attention_mask"},
 		[]string{"sentence_embedding"},
-		nil,
+		nil, // optional options
 	)
 	if err != nil {
-		return nil, err
+		return nil, fmt.Errorf("failed to create ONNX session: %w", err)
 	}
-	// Load tokenizer (from Hugging Face)
-	tokenizer, err := tokenizers.FromFile("./tokenizer.json")
 	return &ONNXEmbedder{
 		session:   session,
-		tokenizer: tokenizer,
+		tokenizer: tok,
+		dims:      dims,
+		logger:    logger,
 	}, nil
 }
 
 func (e *ONNXEmbedder) Embed(text string) ([]float32, error) {
-	// Tokenize
+	// 1. Tokenize
-	tokens := e.tokenizer.Encode(text, true)
+	encoding, err := e.tokenizer.Encode(text, true) // true = add special tokens
-	// Prepare inputs
+	if err != nil {
-	inputIDs := []int64{tokens.GetIds()}
+		return nil, fmt.Errorf("tokenization failed: %w", err)
-	attentionMask := []int64{tokens.GetAttentionMask()}
+	}
-	// Run inference
+	// Convert []int32 to []int64 for ONNX
-	output := onnxruntime_go.NewEmptyTensor[float32](
+	inputIDs := make([]int64, len(encoding.GetIDs()))
-		onnxruntime_go.NewShape(1, 768),
+	for i, id := range encoding.GetIDs() {
-	)
+		inputIDs[i] = int64(id)
-	err := e.session.Run(
+	}
-		map[string]any{
+	attentionMask := make([]int64, len(encoding.GetAttentionMask()))
-			"input_ids":      inputIDs,
+	for i, m := range encoding.GetAttentionMask() {
-			"attention_mask": attentionMask,
+		attentionMask[i] = int64(m)
+	}
+	// 2. Create input tensors (shape: [1, seq_len])
+	seqLen := int64(len(inputIDs))
+	inputIDsTensor, err := onnxruntime_go.NewTensor(onnxruntime_go.NewShape(1, seqLen), inputIDs)
+	if err != nil {
+		return nil, fmt.Errorf("failed to create input_ids tensor: %w", err)
+	}
+	defer inputIDsTensor.Destroy()
+	maskTensor, err := onnxruntime_go.NewTensor(onnxruntime_go.NewShape(1, seqLen), attentionMask)
+	if err != nil {
+		return nil, fmt.Errorf("failed to create attention_mask tensor: %w", err)
+	}
+	defer maskTensor.Destroy()
+	// 3. Create output tensor (shape: [1, dims])
+	outputTensor, err := onnxruntime_go.NewEmptyTensor[float32](onnxruntime_go.NewShape(1, int64(e.dims)))
+	if err != nil {
+		return nil, fmt.Errorf("failed to create output tensor: %w", err)
+	}
+	defer outputTensor.Destroy()
+	// 4. Run inference
+	err = e.session.Run(
+		map[string]*onnxruntime_go.Tensor{
+			"input_ids":      inputIDsTensor,
+			"attention_mask": maskTensor,
 		},
 		[]string{"sentence_embedding"},
-		[]any{&output},
+		[]*onnxruntime_go.Tensor{outputTensor},
 	)
-	return output.GetData(), nil
+	if err != nil {
+		return nil, fmt.Errorf("inference failed: %w", err)
+	}
+	// 5. Extract data
+	outputData := outputTensor.GetData()
+	// outputTensor is owned by us, but GetData returns a slice that remains valid until Destroy.
+	// We need to copy if we want to keep it after Destroy (we defer Destroy, so copy now).
+	embedding := make([]float32, len(outputData))
+	copy(embedding, outputData)
+	return embedding, nil
+}
+
+// EmbedSlice (batch) – to be implemented properly
+func (e *ONNXEmbedder) EmbedSlice(texts []string) ([][]float32, error) {
+	if len(texts) == 0 {
+		return nil, nil
+	}
+	// 1. Tokenize all texts and find max length for padding
+	encodings := make([]*tokenizer.Encoding, len(texts))
+	maxLen := 0
+	for i, txt := range texts {
+		enc, err := e.tokenizer.Encode(txt, true)
+		if err != nil {
+			return nil, fmt.Errorf("tokenization failed at index %d: %w", i, err)
+		}
+		encodings[i] = enc
+		if l := len(enc.GetIDs()); l > maxLen {
+			maxLen = l
+		}
+	}
+	// 2. Build padded input_ids and attention_mask (shape: [batch, maxLen])
+	batchSize := len(texts)
+	inputIDs := make([]int64, batchSize*maxLen)
+	attentionMask := make([]int64, batchSize*maxLen)
+	for i, enc := range encodings {
+		ids := enc.GetIDs()
+		mask := enc.GetAttentionMask()
+		offset := i * maxLen
+		// copy actual tokens
+		for j := 0; j < len(ids); j++ {
+			inputIDs[offset+j] = int64(ids[j])
+			attentionMask[offset+j] = int64(mask[j])
+		}
+		// remaining positions (padding) are already zero-initialized
+	}
+	// 3. Create tensors
+	inputIDsTensor, err := onnxruntime_go.NewTensor(
+		onnxruntime_go.NewShape(int64(batchSize), int64(maxLen)),
+		inputIDs,
+	)
+	if err != nil {
+		return nil, err
+	}
+	defer inputIDsTensor.Destroy()
+	maskTensor, err := onnxruntime_go.NewTensor(
+		onnxruntime_go.NewShape(int64(batchSize), int64(maxLen)),
+		attentionMask,
+	)
+	if err != nil {
+		return nil, err
+	}
+	defer maskTensor.Destroy()
+	outputTensor, err := onnxruntime_go.NewEmptyTensor[float32](
+		onnxruntime_go.NewShape(int64(batchSize), int64(e.dims)),
+	)
+	if err != nil {
+		return nil, err
+	}
+	defer outputTensor.Destroy()
+	// 4. Run
+	err = e.session.Run(
+		map[string]*onnxruntime_go.Tensor{
+			"input_ids":      inputIDsTensor,
+			"attention_mask": maskTensor,
+		},
+		[]string{"sentence_embedding"},
+		[]*onnxruntime_go.Tensor{outputTensor},
+	)
+	if err != nil {
+		return nil, err
+	}
+	// 5. Extract batch results
+	outputData := outputTensor.GetData()
+	embeddings := make([][]float32, batchSize)
+	for i := 0; i < batchSize; i++ {
+		start := i * e.dims
+		emb := make([]float32, e.dims)
+		copy(emb, outputData[start:start+e.dims])
+		embeddings[i] = emb
+	}
+	return embeddings, nil
 }