diff --git a/go.mod b/go.mod index d94cfbf..531609a 100644 --- a/go.mod +++ b/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 diff --git a/go.sum b/go.sum index f95017b..73d273b 100644 --- a/go.sum +++ b/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/takara-ai/go-tokenizers v1.0.0/go.mod h1:2A7hN3gMtAARJ2V3sYyIzTDm+GNTudBX+CwUOyIVH2A= +github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c h1:pwb4kNSHb4K89ymCaN+5lPH/MwnfSVg4rzGDh4d+iy4= +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= diff --git a/rag/embedder.go b/rag/embedder.go index 386d508..396f04b 100644 --- a/rag/embedder.go +++ b/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 - dims int // 768, 512, 256, or 128 for Matryoshka + tokenizer *tokenizer.Tokenizer + dims int // embedding dimension (e.g., 768) + logger *slog.Logger } -func (e *ONNXEmbedder) EmbedSlice(texts []string) ([][]float32, error) { - // Batch processing - inputs := e.prepareBatch(texts) - outputs := make([][]float32, len(texts)) - - // Run batch inference (much faster) - err := e.session.Run(inputs, outputs) - return outputs, err -} - -func NewONNXEmbedder(modelPath string) (*ONNXEmbedder, error) { - // Load ONNX model +func NewONNXEmbedder(modelPath, tokenizerPath string, dims int, logger *slog.Logger) (*ONNXEmbedder, error) { + // Load tokenizer using sugarme/tokenizer + tok, err := pretrained.FromFile(tokenizerPath) + if err != nil { + return nil, fmt.Errorf("failed to load tokenizer: %w", err) + } + // Create ONNX session 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 - tokens := e.tokenizer.Encode(text, true) - // Prepare inputs - inputIDs := []int64{tokens.GetIds()} - attentionMask := []int64{tokens.GetAttentionMask()} - // Run inference - output := onnxruntime_go.NewEmptyTensor[float32]( - onnxruntime_go.NewShape(1, 768), - ) - err := e.session.Run( - map[string]any{ - "input_ids": inputIDs, - "attention_mask": attentionMask, + // 1. Tokenize + encoding, err := e.tokenizer.Encode(text, true) // true = add special tokens + if err != nil { + return nil, fmt.Errorf("tokenization failed: %w", err) + } + // Convert []int32 to []int64 for ONNX + inputIDs := make([]int64, len(encoding.GetIDs())) + for i, id := range encoding.GetIDs() { + inputIDs[i] = int64(id) + } + attentionMask := make([]int64, len(encoding.GetAttentionMask())) + for i, m := range encoding.GetAttentionMask() { + 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 }