ollama/x/tokenizer/tokenizer_load.go
Daniel Hiltgen 9db4bdbad6
runner: Remove CGO engines, use llama-server exclusively for GGML models (#16031)
* broad lint fixes to sidestep CI scope glitch

* runner: Remove CGO engines, use llama-server exclusively for GGML models

Remove the vendored GGML and llama.cpp backend, CGO runner, Go model
implementations, and sample.  llama-server (built from upstream llama.cpp via
FetchContent) is now the sole inference engine for GGUF-based models.
(Safetensor based models continue to run on the new MLX engine.)  This allows
us to more rapidly pick up new capabilities and fixes from llama.cpp as they
come out.

On windows this now requires recent AMD driver versions to support ROCm v7 as
llama.cpp currently does not support building against v6.

* llama/compat: load Ollama-format GGUFs in llama-server

Squashed from upstream/jmorganca/llama-compat on 2026-04-29.
Source tip: 0c33775d37.

Original source commits:
- 25223160d llama/compat: add in-memory shim so llama-server can load Ollama-format GGUFs
- 7449b539a llm,server: route Ollama-format gemma3 blobs through llama/compat
- 436f2e2b1 llama/compat: make patch-apply idempotent
- 8c2c9d4c8 llama/compat: extend gemma3 handler to cover 1B and 270M blobs
- 021389f7b llama/compat: shrink clip.cpp injection from 18 lines to 1
- 61b367ec2 llama/compat: shrink patch to pure call-site hooks (34 -> 20 lines)
- 36049361c llama/compat: simplify shim (gemma3-tested)
- 8fa664865 llama/compat: add qwen35moe text handler
- db0c74530 llama/compat: add qwen35moe vision (clip) support
- 2a388da77 llama/compat: split shared infra into a util TU
- 9a69a17dc llama/compat: document non-public API dependencies
- d0f38a915 llama/compat: add gpt-oss and lfm2 handlers
- 086071822 llama/compat: add mistral3 text handler (vision TODO)
- 63bde9ff7 llama/compat: add mistral3 vision (clip) support
- 3a57b89d5 llama/compat: apply LLaMA RoPE permute to mistral3 vision Q/K
- 99cb87439 llama/compat: add qwen35, gemma4, deepseek-ocr handlers
- 2c7850dba llama/compat: add nemotron_h_moe handler (latent FFN + MTP skip)
- 9e3b54225 llama/compat: add llama4 text + clip handlers
- 034fee349 llama/compat: add gemma4 clip handler (gemma4v projector)
- 9945c5a93 server: remove dhiltgen/* compat redirect table
- 5d4539101 llama/compat: rewrite gemma4 tokenizer model to BPE
- 7e0765327 llama/compat: add glm-ocr text handler + text-loader load-op hook
- f1bd1a25a llama/compat: add glm-ocr clip handler (glm4v projector)
- 4b5cf3420 llama/compat: collapse text-loader hook back to one new patch line
- eb4ecf4fc llama/compat: extend gemma4 clip handler to gemma4a (audio)
- a23a5e76f llama/compat: fix gemma4a per-block norm tensor mapping
- cd2dcaff4 llama/compat: add embeddinggemma handler
- 1ce8a6b26 llama/compat: add qwen3-vl + qwen2.5-vl handlers
- fd98ffa1e llama/compat: add gemma3n + glm4moelite handlers
- cc7bdf0bc llama/compat: handle null buft in maybe_load_tensor
- 0c33775d3 llama/compat: disable mmap when load_op transforms text-side tensors

* refine implementation

* ci: fix windows MLX build

* ci: fix windows llama-server build

* ci: fix windows rocm build

* ci: windows mlx tuning

Shorten long-tail on build, and get OllamaSetup.exe back under 2g limit

* ci: fix windows dependencies

* win: fix dependency gathering

* disable openmp

* win: arm64 cross-compile build

also DRY out CI steps

* scheduler improvements

* ci: improvements from #15982

* win: favor ninja for faster developer builds

* win: fix build

* win: fix arm64 cross-compile

* win: avoid spaces in compiler path

* misc discovery fixes, and bos handling

* lint fixes

* win: fix arm cross-compile build/CI bugs

* llama.cpp update

* win: handle multiple CRT dirs

* vulkan: add windows iGPU detection

* fix creation bugs for patched models, other refactoring work

* tune batch size for better performance

* ci and lint fixes

* fix repeat_last_n bug

* build: revamp build for better developer UX

* amd, sampler, qwen3next fixes

* version bump

* fix mlx build

* revamp GPU discovery

Scanning the output of llama-server is turning out to be too error prone across
llama.cpp updates, so this switches to a thin dynamic library load against the
bundled GGML libraries so more details can be gathered from the API.

* version bump

* missing file

* ci: fix cache miss on rocm build

* refine vulkan dep handling

* fix ps reporting bug on full GPU load

* improve cmake wiring for customized local builds

* version bump

* docker build arg cleanup

* improve windows exit error logs

* fix community gemma4 support and ci flakes

* fix mlx unit test

* tighten up ps logic to avoid double counting fit log lines

* version bump

* fix ps view for full gpu layer offload

* add MTP wiring for llama-server and create with GGUFs

* pick best template by capabilities

* version bump

* ci: harden apt repos

* remove unused cpu core discovery

* adjust batch default logic to reduce OOMs

* support larger tool calls

* fix audio support, template show

* qwen35 mtp patch support

* flesh out dtypes

* rocm deps

* version bump

* lint fix

* block broken gfx1150 on windows

* fix qwen3.5 moe mtp tensors in patch

* mmproj oom fallback and vulkan on by default

* qwen MTP compat fix

* version bump

* ci: fix WoA cross-compile

* ci: workaround ui tool in cross-compile

* version bump

* win: enable OpenMP for CPU builds

* build: improve developer UX

* ci: windows path workaround for CPU build

* win: fix WoA dependencies

* win: fix large offset reads for mmproj patched loads

* version bump

* fix vulkan dup detection

* add OLLAMA_IGPU_ENABLE and largely disable iGPUs by default

* opt-in MTP, win large offset, integraton fixes

* fix unit test scheduler interaction hang

* fix multi-gpu filtering

* version bump

* review comments

* fix thinking level

* fix linux rocm ordering and granite 3.3 template

* version bump

* ci fix - non-shallow MLX checkout

* bypass linux sysfs unit test on windows

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>
2026-05-29 13:35:47 -07:00

457 lines
13 KiB
Go

package tokenizer
import (
"encoding/json"
"fmt"
"regexp"
"sort"
"strings"
)
// TokenizerConfig holds optional configuration data that can be passed to LoadFromBytesWithConfig.
type TokenizerConfig struct {
TokenizerConfigJSON []byte // tokenizer_config.json content
GenerationConfigJSON []byte // generation_config.json content
SpecialTokensMapJSON []byte // special_tokens_map.json content
ConfigJSON []byte // config.json content
}
// LoadFromBytes loads a tokenizer from tokenizer.json bytes.
// This is useful when loading from blob storage where the file content is already in memory.
// Note: This won't load special token config from companion files. Use LoadFromBytesWithConfig
// to provide tokenizer_config.json data for proper PAD/EOS token loading.
func LoadFromBytes(data []byte) (*Tokenizer, error) {
return loadFromTokenizerJSON(data)
}
// LoadFromBytesWithConfig loads a tokenizer from tokenizer.json bytes with additional config files.
// This is useful when loading from blob storage where companion config files are also blobs.
func LoadFromBytesWithConfig(data []byte, config *TokenizerConfig) (*Tokenizer, error) {
t, err := loadFromTokenizerJSON(data)
if err != nil {
return nil, err
}
if config == nil {
return t, nil
}
// Apply special token configs from provided data
loadSpecialTokenConfigFromBytes(t, config)
return t, nil
}
// loadFromTokenizerJSON parses tokenizer.json content from bytes.
func loadFromTokenizerJSON(data []byte) (*Tokenizer, error) {
var raw struct {
Model struct {
Type string `json:"type"` // "BPE"
Vocab map[string]int32 `json:"vocab"`
Merges json.RawMessage `json:"merges"` // Can be []string or [][]string (BPE only)
} `json:"model"`
PreTokenizer json.RawMessage `json:"pre_tokenizer"`
Decoder json.RawMessage `json:"decoder"`
AddedTokens []struct {
ID int32 `json:"id"`
Content string `json:"content"`
Special bool `json:"special"`
} `json:"added_tokens"`
}
if err := json.Unmarshal(data, &raw); err != nil {
return nil, fmt.Errorf("failed to parse tokenizer: %w", err)
}
// Covers SentencePiece and BPE models
if raw.Model.Type != "BPE" {
return nil, fmt.Errorf("unsupported tokenizer type: %s", raw.Model.Type)
}
// Parse merges - can be []string (Llama) or [][]string (GPT-OSS).
var mergesStrings []string
if raw.Model.Merges != nil {
var mergesArrays [][]string
if err := json.Unmarshal(raw.Model.Merges, &mergesStrings); err != nil {
// Try array of arrays format
if err := json.Unmarshal(raw.Model.Merges, &mergesArrays); err != nil {
return nil, fmt.Errorf("failed to parse merges: %w", err)
}
// Convert [][]string to []string
mergesStrings = make([]string, len(mergesArrays))
for i, pair := range mergesArrays {
if len(pair) != 2 {
return nil, fmt.Errorf("failed to parse merges: expected merge pair of length 2, got %d", len(pair))
}
mergesStrings[i] = pair[0] + " " + pair[1]
}
}
}
// Build tokenizer
t := &Tokenizer{
vocab: &Vocabulary{
Values: make([]string, len(raw.Model.Vocab)),
Reverse: raw.Model.Vocab,
Merges: make(map[string]int, len(mergesStrings)),
BOS: -1,
PAD: -1,
},
specialTokens: make(map[string]int32),
}
// Build values array
for token, id := range raw.Model.Vocab {
if int(id) >= len(t.vocab.Values) {
newValues := make([]string, id+1)
copy(newValues, t.vocab.Values)
t.vocab.Values = newValues
}
t.vocab.Values[id] = token
}
// Build merges map
for i, merge := range mergesStrings {
t.vocab.Merges[merge] = i
}
// Add all added_tokens to vocabulary and special tokens map.
// HuggingFace treats ALL added_tokens as special for tokenization purposes -
// they bypass BPE and get their own token ID. The "special" flag just indicates
// if it's a "truly special" token like BOS/EOS/PAD, but for tokenization we need
// to treat all added_tokens as special to match HuggingFace behavior.
for _, tok := range raw.AddedTokens {
if int(tok.ID) >= len(t.vocab.Values) {
newValues := make([]string, tok.ID+1)
copy(newValues, t.vocab.Values)
t.vocab.Values = newValues
}
t.vocab.Values[tok.ID] = tok.Content
t.specialTokens[tok.Content] = tok.ID // Add ALL added_tokens to special tokens
}
// Precompute byte token IDs for <0xNN> fallback
initByteTokens(t)
// Determine tokenizer type
switch {
case detectSentencePiece(raw.Decoder):
t.typ = TokenizerSentencePiece
default:
t.typ = TokenizerBPE
}
// Parse and compile pretokenizer pattern (BPE only - SentencePiece doesn't use pretokenizer)
if t.typ == TokenizerBPE {
pattern := extractPretokenizer(raw.PreTokenizer)
if pattern == "" {
pattern = `'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`
}
re, err := regexp.Compile(rewritePatternForRE2(pattern))
if err != nil {
return nil, fmt.Errorf("failed to compile pretokenizer regex %q: %w", pattern, err)
}
t.pretokenizer = re
}
cacheSortedSpecialTokens(t)
return t, nil
}
func cacheSortedSpecialTokens(t *Tokenizer) {
if len(t.specialTokens) == 0 {
t.sortedSpecialTokens = nil
return
}
tokens := make([]string, 0, len(t.specialTokens))
for tok := range t.specialTokens {
tokens = append(tokens, tok)
}
sort.Slice(tokens, func(i, j int) bool {
return len(tokens[i]) > len(tokens[j])
})
t.sortedSpecialTokens = tokens
}
type specialTokenConfigData struct {
tokenizerConfigJSON []byte
generationConfigJSON []byte
specialTokensMapJSON []byte
configJSON []byte
}
func applySpecialTokenConfig(t *Tokenizer, config specialTokenConfigData) {
parseTokenIDs := func(v interface{}) []int32 {
switch val := v.(type) {
case float64:
return []int32{int32(val)}
case []interface{}:
ids := make([]int32, 0, len(val))
for _, id := range val {
if f, ok := id.(float64); ok {
ids = append(ids, int32(f))
}
}
return ids
}
return nil
}
// Priority 1: generation_config.json
if len(config.generationConfigJSON) > 0 {
var genConfig struct {
EOSTokenID interface{} `json:"eos_token_id"`
BOSTokenID interface{} `json:"bos_token_id"`
}
if err := json.Unmarshal(config.generationConfigJSON, &genConfig); err == nil {
if ids := parseTokenIDs(genConfig.EOSTokenID); len(ids) > 0 {
t.vocab.EOS = ids
}
if ids := parseTokenIDs(genConfig.BOSTokenID); len(ids) > 0 {
t.vocab.BOS = ids[0]
}
}
}
// Priority 2: config.json
if len(config.configJSON) > 0 && (len(t.vocab.EOS) == 0 || t.vocab.BOS < 0) {
var modelConfig struct {
EOSTokenID interface{} `json:"eos_token_id"`
BOSTokenID interface{} `json:"bos_token_id"`
}
if err := json.Unmarshal(config.configJSON, &modelConfig); err == nil {
if len(t.vocab.EOS) == 0 {
if ids := parseTokenIDs(modelConfig.EOSTokenID); len(ids) > 0 {
t.vocab.EOS = ids
}
}
if t.vocab.BOS < 0 {
if ids := parseTokenIDs(modelConfig.BOSTokenID); len(ids) > 0 {
t.vocab.BOS = ids[0]
}
}
}
}
// Priority 3: tokenizer_config.json
if len(config.tokenizerConfigJSON) > 0 {
var tokConfig struct {
BOSToken interface{} `json:"bos_token"`
EOSToken interface{} `json:"eos_token"`
PADToken interface{} `json:"pad_token"`
AddBOSToken *bool `json:"add_bos_token"`
AddEOSToken *bool `json:"add_eos_token"`
}
if err := json.Unmarshal(config.tokenizerConfigJSON, &tokConfig); err == nil {
if t.vocab.BOS < 0 {
if bosStr := extractTokenString(tokConfig.BOSToken); bosStr != "" {
if id, ok := t.specialTokens[bosStr]; ok {
t.vocab.BOS = id
}
}
}
if len(t.vocab.EOS) == 0 {
if eosStr := extractTokenString(tokConfig.EOSToken); eosStr != "" {
if id, ok := t.specialTokens[eosStr]; ok {
t.vocab.EOS = []int32{id}
}
}
}
if t.vocab.PAD < 0 {
if padStr := extractTokenString(tokConfig.PADToken); padStr != "" {
if id, ok := t.specialTokens[padStr]; ok {
t.vocab.PAD = id
}
}
}
if tokConfig.AddBOSToken != nil {
t.vocab.AddBOS = *tokConfig.AddBOSToken
}
if tokConfig.AddEOSToken != nil {
t.vocab.AddEOS = *tokConfig.AddEOSToken
}
}
}
// Priority 4: special_tokens_map.json
if len(config.specialTokensMapJSON) > 0 {
var tokensMap map[string]interface{}
if err := json.Unmarshal(config.specialTokensMapJSON, &tokensMap); err == nil {
if t.vocab.BOS < 0 {
if bosStr := extractTokenString(tokensMap["bos_token"]); bosStr != "" {
if id, ok := t.specialTokens[bosStr]; ok {
t.vocab.BOS = id
}
}
}
if len(t.vocab.EOS) == 0 {
if eosStr := extractTokenString(tokensMap["eos_token"]); eosStr != "" {
if id, ok := t.specialTokens[eosStr]; ok {
t.vocab.EOS = []int32{id}
}
}
}
if t.vocab.PAD < 0 {
if padStr := extractTokenString(tokensMap["pad_token"]); padStr != "" {
if id, ok := t.specialTokens[padStr]; ok {
t.vocab.PAD = id
}
}
}
}
}
}
// extractTokenString extracts the token string from various formats used in HuggingFace configs.
// Tokens can be represented as:
// - string: "token"
// - object: {"content": "token", ...}
func extractTokenString(v interface{}) string {
if v == nil {
return ""
}
// Direct string
if s, ok := v.(string); ok {
return s
}
// Object with content field
if m, ok := v.(map[string]interface{}); ok {
if content, ok := m["content"].(string); ok {
return content
}
}
return ""
}
// rewritePatternForRE2 rewrites HuggingFace pretokenizer regex patterns to be
// compatible with Go's regexp package (RE2). HuggingFace patterns use PCRE features:
// - (?!\S) negative lookahead - RE2 doesn't support this
// - (?i:...) inline case-insensitive groups - RE2 doesn't support this
//
// We replace \s+(?!\S)|\s+ with \s+ and fix whitespace boundaries in encodeWithRegex().
// The lookahead version splits "a b" into ["a", " ", " b"] (space prepended to word).
// Simple \s+ would give ["a", " ", "b"]. We post-process to match Python's behavior.
func rewritePatternForRE2(pattern string) string {
// Replace lookahead pattern with simple \s+ - we fix boundaries in encodeWithRegex()
pattern = strings.ReplaceAll(pattern, `\s+(?!\S)|\s+`, `\s+`)
// Handle the pattern when it appears with a ? suffix (optional contractions in GPT-4o style)
// IMPORTANT: Must be done before the non-optional version to avoid partial replacement
pattern = strings.ReplaceAll(pattern,
`(?i:'s|'t|'re|'ve|'m|'ll|'d)?`,
`(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])?`)
// Expand case-insensitive contraction pattern to explicit alternations
// (?i:'s|'t|'re|'ve|'m|'ll|'d) -> '[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD]
pattern = strings.ReplaceAll(pattern,
`(?i:'s|'t|'re|'ve|'m|'ll|'d)`,
`(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])`)
return pattern
}
// loadSpecialTokenConfigFromBytes loads special token configuration from byte slices.
func loadSpecialTokenConfigFromBytes(t *Tokenizer, config *TokenizerConfig) {
applySpecialTokenConfig(t, specialTokenConfigData{
tokenizerConfigJSON: config.TokenizerConfigJSON,
generationConfigJSON: config.GenerationConfigJSON,
specialTokensMapJSON: config.SpecialTokensMapJSON,
configJSON: config.ConfigJSON,
})
}
// detectSentencePiece checks if the decoder uses SentencePiece-style (▁ for spaces)
// vs GPT-2 byte-level encoding
func detectSentencePiece(data json.RawMessage) bool {
if data == nil {
return false
}
// Check for Sequence decoder with Replace step (SentencePiece style)
var seq struct {
Type string `json:"type"`
Decoders []struct {
Type string `json:"type"`
Pattern struct {
String string `json:"String"`
} `json:"pattern"`
} `json:"decoders"`
}
if err := json.Unmarshal(data, &seq); err == nil {
if seq.Type == "Sequence" {
for _, dec := range seq.Decoders {
// Look for Replace decoder that converts ▁ to space
if dec.Type == "Replace" && dec.Pattern.String == "▁" {
return true
}
}
}
}
// Check for direct ByteLevel decoder (GPT-2 style)
var simple struct {
Type string `json:"type"`
}
if err := json.Unmarshal(data, &simple); err == nil {
if simple.Type == "ByteLevel" {
return false
}
}
return false
}
// initByteTokens precomputes byte token IDs for <0xNN> fallback encoding
func initByteTokens(t *Tokenizer) {
for i := range t.vocab.byteTokens {
t.vocab.byteTokens[i] = -1
}
for b := range 256 {
token := fmt.Sprintf("<0x%02X>", b)
if id, ok := t.vocab.Reverse[token]; ok {
t.vocab.byteTokens[b] = id
}
}
}
// extractPretokenizer extracts the regex pattern from the pre_tokenizer config
func extractPretokenizer(data json.RawMessage) string {
if data == nil {
return ""
}
// Try to parse as a single Split pretokenizer
var single struct {
Type string `json:"type"`
Pattern struct {
Regex string `json:"Regex"`
} `json:"pattern"`
}
if err := json.Unmarshal(data, &single); err == nil && single.Pattern.Regex != "" {
return single.Pattern.Regex
}
// Try to parse as Sequence of pretokenizers - use first Split pattern
var seq struct {
Type string `json:"type"`
Pretokenizers []struct {
Type string `json:"type"`
Pattern struct {
Regex string `json:"Regex"`
} `json:"pattern"`
} `json:"pretokenizers"`
}
if err := json.Unmarshal(data, &seq); err == nil && seq.Type == "Sequence" {
for _, pt := range seq.Pretokenizers {
if pt.Type == "Split" && pt.Pattern.Regex != "" {
if _, err := regexp.Compile(rewritePatternForRE2(pt.Pattern.Regex)); err == nil {
return pt.Pattern.Regex
}
}
}
}
return ""
}