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19 Commits

Author SHA1 Message Date
Patrick Devine
73a1e99f8a logging: add a new customer logger and trace method
This change addresses over logging with debug in the SPM tokenizer by
adding a trace level to slog.
2025-03-13 16:10:59 -07:00
Michael Yang
543240fb5f Merge pull request #9741 from ollama/mxyng/visionless
fix: error if image requested without vision model
2025-03-13 15:03:25 -07:00
Patrick Devine
4bed739259 add verbose mode to the show command (#9640)
Add metadata and tensor information to the show command to be able to
see more information about a model. This outputs the same data as
shown on the model details page on ollama.com
2025-03-13 14:24:27 -07:00
Patrick Devine
80c7ce381b fix: change default context size for gemma3 (#9744) 2025-03-13 13:59:19 -07:00
Michael Yang
ccfd41c4f0 Merge pull request #9742 from ollama/mxyng/engine-error-embeddings
fix: error on models that don't support embeddings
2025-03-13 13:12:33 -07:00
Michael Yang
3e102b7dad Update model/model.go
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2025-03-13 13:11:52 -07:00
Michael Yang
ec46f3286c engine: error on embeddings; not currently implemented 2025-03-13 11:40:55 -07:00
Michael Yang
5e2e0b46b1 fix: error if image requested without vision model 2025-03-13 10:52:09 -07:00
Michael Yang
45a13b1dec Merge pull request #9688 from Shane-XB-Qian/debug_mistype_lld
ollama-debug.c: correct mistype
2025-03-13 10:12:44 -07:00
Parth Sareen
5c0b663969 sample: separate softmax and temperature transforms (#9732) 2025-03-13 09:53:27 -07:00
shane.xb.qian
30d7a59ba8 ollama-debug.c: change 'ld' to 'PRIi64'
* macOS has different definition per info from @mxyng
2025-03-13 17:10:37 +08:00
ParthSareen
4aeb67ef4c sample: do all sorting in topK 2025-03-12 11:59:17 -07:00
ParthSareen
3ba91634c1 sample: simplify top_k=0 sorting 2025-03-12 11:59:17 -07:00
ParthSareen
1b7433b71e sample: use container/heap for top_k 2025-03-12 11:59:17 -07:00
Bruce MacDonald
a70820daa0 models/gemma3: remove final logit softcap (#9692)
Softcap isn't in the whitepaper/implementation for the language model so we should remove it. There is no discernible difference in output with it removed.
2025-03-12 10:17:57 -07:00
Shane-XB-Qian
6b45b1d6b4 cli: adding support ctrl-n/p like general cli (#9136)
Signed-off-by: shane.xb.qian <shane.qian@foxmail.com>
2025-03-12 08:51:56 -07:00
shane.xb.qian
85ab552028 ollama-debug.c: correct mistype
Signed-off-by: shane.xb.qian <shane.qian@foxmail.com>
2025-03-12 22:32:30 +08:00
frob
b3af953a55 cli: don't exit for invalid model during /load. (#9576)
Co-authored-by: Richard Lyons <frob@cloudstaff.com>
2025-03-11 23:42:53 -07:00
Michael
ad4e0bf3be Adding Gemma 3 to readme (#9671) 2025-03-12 07:39:25 +01:00
20 changed files with 439 additions and 291 deletions

View File

@@ -54,6 +54,10 @@ Here are some example models that can be downloaded:
| Model | Parameters | Size | Download |
| ------------------ | ---------- | ----- | -------------------------------- |
| Gemma 3 | 1B | 815MB | `ollama run gemma3:1b` |
| Gemma 3 | 4B | 3.3GB | `ollama run gemma3` |
| Gemma 3 | 12B | 8.1GB | `ollama run gemma3:12b` |
| Gemma 3 | 27B | 17GB | `ollama run gemma3:27b` |
| QwQ | 32B | 20GB | `ollama run qwq` |
| DeepSeek-R1 | 7B | 4.7GB | `ollama run deepseek-r1` |
| DeepSeek-R1 | 671B | 404GB | `ollama run deepseek-r1:671b` |
@@ -66,9 +70,6 @@ Here are some example models that can be downloaded:
| Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` |
| Phi 4 | 14B | 9.1GB | `ollama run phi4` |
| Phi 4 Mini | 3.8B | 2.5GB | `ollama run phi4-mini` |
| Gemma 2 | 2B | 1.6GB | `ollama run gemma2:2b` |
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |

View File

@@ -349,6 +349,7 @@ type ShowResponse struct {
Messages []Message `json:"messages,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
Tensors []Tensor `json:"tensors,omitempty"`
ModifiedAt time.Time `json:"modified_at,omitempty"`
}
@@ -467,6 +468,13 @@ type ModelDetails struct {
QuantizationLevel string `json:"quantization_level"`
}
// Tensor describes the metadata for a given tensor.
type Tensor struct {
Name string `json:"name"`
Type string `json:"type"`
Shape []uint64 `json:"shape"`
}
func (m *Metrics) Summary() {
if m.TotalDuration > 0 {
fmt.Fprintf(os.Stderr, "total duration: %v\n", m.TotalDuration)

View File

@@ -18,6 +18,7 @@ import (
"os/signal"
"path/filepath"
"runtime"
"sort"
"strconv"
"strings"
"sync/atomic"
@@ -568,8 +569,9 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
parameters, errParams := cmd.Flags().GetBool("parameters")
system, errSystem := cmd.Flags().GetBool("system")
template, errTemplate := cmd.Flags().GetBool("template")
verbose, errVerbose := cmd.Flags().GetBool("verbose")
for _, boolErr := range []error{errLicense, errModelfile, errParams, errSystem, errTemplate} {
for _, boolErr := range []error{errLicense, errModelfile, errParams, errSystem, errTemplate, errVerbose} {
if boolErr != nil {
return errors.New("error retrieving flags")
}
@@ -607,7 +609,7 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
}
req := api.ShowRequest{Name: args[0]}
req := api.ShowRequest{Name: args[0], Verbose: verbose}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
@@ -630,10 +632,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return nil
}
return showInfo(resp, os.Stdout)
return showInfo(resp, verbose, os.Stdout)
}
func showInfo(resp *api.ShowResponse, w io.Writer) error {
func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
tableRender := func(header string, rows func() [][]string) {
fmt.Fprintln(w, " ", header)
table := tablewriter.NewWriter(w)
@@ -690,6 +692,45 @@ func showInfo(resp *api.ShowResponse, w io.Writer) error {
})
}
if resp.ModelInfo != nil && verbose {
tableRender("Metadata", func() (rows [][]string) {
keys := make([]string, 0, len(resp.ModelInfo))
for k := range resp.ModelInfo {
keys = append(keys, k)
}
sort.Strings(keys)
for _, k := range keys {
var v string
switch vData := resp.ModelInfo[k].(type) {
case string:
v = vData
case float64:
v = fmt.Sprintf("%g", vData)
case []any:
n := 3
if len(vData) < n {
n = len(vData)
}
v = fmt.Sprintf("%v", vData[:n])
default:
v = fmt.Sprintf("%T", vData)
}
rows = append(rows, []string{"", k, v})
}
return
})
}
if len(resp.Tensors) > 0 && verbose {
tableRender("Tensors", func() (rows [][]string) {
for _, t := range resp.Tensors {
rows = append(rows, []string{"", t.Name, t.Type, fmt.Sprint(t.Shape)})
}
return
})
}
head := func(s string, n int) (rows [][]string) {
scanner := bufio.NewScanner(strings.NewReader(s))
for scanner.Scan() && (len(rows) < n || n < 0) {
@@ -1196,6 +1237,7 @@ func NewCLI() *cobra.Command {
showCmd.Flags().Bool("parameters", false, "Show parameters of a model")
showCmd.Flags().Bool("template", false, "Show template of a model")
showCmd.Flags().Bool("system", false, "Show system message of a model")
showCmd.Flags().BoolP("verbose", "v", false, "Show detailed model information")
runCmd := &cobra.Command{
Use: "run MODEL [PROMPT]",

View File

@@ -27,7 +27,7 @@ func TestShowInfo(t *testing.T) {
ParameterSize: "7B",
QuantizationLevel: "FP16",
},
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}
@@ -57,7 +57,7 @@ func TestShowInfo(t *testing.T) {
ParameterSize: "7B",
QuantizationLevel: "FP16",
},
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}
@@ -68,6 +68,56 @@ func TestShowInfo(t *testing.T) {
embedding length 0
quantization FP16
`
if diff := cmp.Diff(expect, b.String()); diff != "" {
t.Errorf("unexpected output (-want +got):\n%s", diff)
}
})
t.Run("verbose model", func(t *testing.T) {
var b bytes.Buffer
if err := showInfo(&api.ShowResponse{
Details: api.ModelDetails{
Family: "test",
ParameterSize: "8B",
QuantizationLevel: "FP16",
},
Parameters: `
stop up`,
ModelInfo: map[string]any{
"general.architecture": "test",
"general.parameter_count": float64(8_000_000_000),
"test.context_length": float64(1000),
"test.embedding_length": float64(11434),
},
Tensors: []api.Tensor{
{Name: "blk.0.attn_k.weight", Type: "BF16", Shape: []uint64{42, 3117}},
{Name: "blk.0.attn_q.weight", Type: "FP16", Shape: []uint64{3117, 42}},
},
}, true, &b); err != nil {
t.Fatal(err)
}
expect := ` Model
architecture test
parameters 8B
context length 1000
embedding length 11434
quantization FP16
Parameters
stop up
Metadata
general.architecture test
general.parameter_count 8e+09
test.context_length 1000
test.embedding_length 11434
Tensors
blk.0.attn_k.weight BF16 [42 3117]
blk.0.attn_q.weight FP16 [3117 42]
`
if diff := cmp.Diff(expect, b.String()); diff != "" {
t.Errorf("unexpected output (-want +got):\n%s", diff)
@@ -89,7 +139,7 @@ func TestShowInfo(t *testing.T) {
stop you
stop up
temperature 99`,
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}
@@ -126,7 +176,7 @@ func TestShowInfo(t *testing.T) {
"clip.vision.embedding_length": float64(0),
"clip.vision.projection_dim": float64(0),
},
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}
@@ -159,7 +209,7 @@ func TestShowInfo(t *testing.T) {
Ahoy, matey!
Weigh anchor!
`,
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}
@@ -188,7 +238,7 @@ Weigh anchor!
QuantizationLevel: "FP16",
},
License: license,
}, &b); err != nil {
}, false, &b); err != nil {
t.Fatal(err)
}

View File

@@ -195,6 +195,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = []api.Message{}
fmt.Printf("Loading model '%s'\n", opts.Model)
if err := loadOrUnloadModel(cmd, &opts); err != nil {
if strings.Contains(err.Error(), "not found") {
fmt.Printf("error: %v\n", err)
continue
}
return err
}
continue
@@ -343,7 +347,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
switch args[1] {
case "info":
_ = showInfo(resp, os.Stderr)
_ = showInfo(resp, false, os.Stderr)
case "license":
if resp.License == "" {
fmt.Println("No license was specified for this model.")

View File

@@ -87,7 +87,7 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
kv["gemma3.embedding_length"] = p.HiddenSize
kv["gemma3.feed_forward_length"] = p.IntermediateSize
default:
kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 8192)
kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 131072)
kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
kv["gemma3.feed_forward_length"] = p.TextModel.IntermediateSize
kv["gemma3.attention.sliding_window"] = p.TextModel.SlidingWindow

View File

@@ -327,6 +327,10 @@ func (t Tensor) Size() uint64 {
return t.parameters() * t.typeSize() / t.blockSize()
}
func (t Tensor) Type() string {
return fileType(t.Kind).String()
}
type container interface {
Name() string
Decode(io.ReadSeeker) (model, error)

40
logging/log.go Normal file
View File

@@ -0,0 +1,40 @@
package logging
import (
"context"
"log/slog"
"os"
)
const LevelTrace slog.Level = slog.LevelDebug - 4
type Logger struct {
logger *slog.Logger
}
func NewLogger() *Logger {
handler := slog.NewTextHandler(os.Stdout, nil)
return &Logger{
logger: slog.New(handler),
}
}
func (l *Logger) Trace(msg string, args ...any) {
l.logger.Log(context.Background(), LevelTrace, msg, args...)
}
func (l *Logger) Debug(msg string, args ...any) {
l.logger.Debug(msg, args...)
}
func (l *Logger) Info(msg string, args ...any) {
l.logger.Info(msg, args...)
}
func (l *Logger) Warn(msg string, args ...any) {
l.logger.Warn(msg, args...)
}
func (l *Logger) Error(msg string, args ...any) {
l.logger.Error(msg, args...)
}

View File

@@ -1,4 +1,5 @@
#include <string.h>
#include <inttypes.h>
#include "ollama-debug.h"
@@ -24,7 +25,7 @@ static void print_tensor(const void *tensor, void (*cb)(const void *, int),
fprintf(stderr, "[");
for (int i = 0; i < dims[0]; i++) {
if (i >= nitems && i < dims[0] - nitems) {
fprintf(stderr, "... (%lld more), ", dims[0] - 2 * nitems);
fprintf(stderr, "... (%" PRIi64 " more), ", dims[0] - 2 * nitems);
int skip = dims[0] - 2 * nitems;
if (ndims > 1) {
stride += mul(dims + 1, ndims - 1) * skip;
@@ -67,7 +68,7 @@ static void print_tensor_i32(const void *tensor, int i) {
}
static void ollama_debug_tensor(const struct ggml_tensor *tensor, bool verbose, const char *prefix, int indent) {
fprintf(stderr, "%s%s %s (%s): [%lld %lld %lld %lld]\n", prefix, tensor->name,
fprintf(stderr, "%s%s %s (%s): [%" PRIi64 " %" PRIi64 " %" PRIi64 " %" PRIi64 "]\n", prefix, tensor->name,
ggml_op_name(tensor->op), ggml_type_name(tensor->type), tensor->ne[0],
tensor->ne[1], tensor->ne[2], tensor->ne[3]);

View File

@@ -22,6 +22,8 @@ import (
"github.com/ollama/ollama/model/input"
)
var ErrNoVisionModel = errors.New("this model is missing data required for image input")
// Model implements a specific model architecture, defining the forward pass and any model-specific configuration
type Model interface {
Forward(ml.Context, input.Options) (ml.Tensor, error)

View File

@@ -84,6 +84,10 @@ func New(c ml.Config) (model.Model, error) {
}
func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
if len(m.VisionModel.Layers) == 0 {
return nil, model.ErrNoVisionModel
}
image, _, err := image.Decode(bytes.NewReader(multimodalData))
if err != nil {
return nil, err

View File

@@ -15,7 +15,6 @@ type TextOptions struct {
attnKeyLen, attnValLen int
eps, ropeScale float32
ropeLocalBase, ropeGlobalBase float32
finalLogitSoftcap float32
largeModelScaling bool
}
@@ -57,16 +56,15 @@ func newTextModel(c ml.Config) *TextModel {
),
Layers: make([]TextLayer, numBlocks),
TextOptions: &TextOptions{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")),
attnKeyLen: int(c.Uint("attention.key_length", 256)),
attnValLen: int(c.Uint("attention.value_length", 256)),
eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06),
ropeLocalBase: c.Float("rope.local.freq_base", 10000.0),
ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
ropeScale: c.Float("rope.freq_scale", 1.0),
finalLogitSoftcap: c.Float("final_logit_softcapping", 30.0),
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")),
attnKeyLen: int(c.Uint("attention.key_length", 256)),
attnValLen: int(c.Uint("attention.value_length", 256)),
eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06),
ropeLocalBase: c.Float("rope.local.freq_base", 10000.0),
ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
ropeScale: c.Float("rope.freq_scale", 1.0),
},
}
@@ -245,10 +243,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
}
hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
hiddenState = m.Output.Forward(ctx, hiddenState)
// final logit softcap
hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.TextOptions.finalLogitSoftcap))
hiddenState = hiddenState.Tanh(ctx)
return hiddenState.Scale(ctx, float64(m.TextOptions.finalLogitSoftcap))
return m.Output.Forward(ctx, hiddenState)
}

View File

@@ -63,6 +63,10 @@ func New(c ml.Config) (model.Model, error) {
}
func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
if len(m.VisionModel.Transformer.Layers) == 0 || len(m.GlobalTransformer.Layers) == 0 {
return nil, model.ErrNoVisionModel
}
image, _, err := image.Decode(bytes.NewReader(multimodalData))
if err != nil {
return nil, err

View File

@@ -2,15 +2,18 @@ package model
import (
"iter"
"log/slog"
"strings"
"github.com/dlclark/regexp2"
queue "github.com/emirpasic/gods/v2/queues/priorityqueue"
"github.com/ollama/ollama/logging"
)
const spmWhitespaceSep = "▁"
var log = logging.NewLogger()
func replaceWhitespaceBySeperator(s string) string {
return strings.ReplaceAll(s, " ", spmWhitespaceSep)
}
@@ -24,7 +27,7 @@ type SentencePieceModel struct {
var _ TextProcessor = (*SentencePieceModel)(nil)
func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
slog.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
log.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
counter := map[int]int{}
var maxTokenLen int
@@ -38,7 +41,7 @@ func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
}
}
slog.Debug("Token counts", "normal", counter[TOKEN_TYPE_NORMAL], "unknown", counter[TOKEN_TYPE_UNKNOWN], "control", counter[TOKEN_TYPE_CONTROL],
log.Debug("Token counts", "normal", counter[TOKEN_TYPE_NORMAL], "unknown", counter[TOKEN_TYPE_UNKNOWN], "control", counter[TOKEN_TYPE_CONTROL],
"user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE],
"max token len", maxTokenLen)
@@ -91,7 +94,7 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
fragments = append(fragments[:i], append(middle, fragments[i+1:]...)...)
}
}
slog.Debug("fragments", "frags", fragments)
log.Trace("fragments", "frags", fragments)
var ids []int32
for _, frag := range fragments {
@@ -129,7 +132,7 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
}
}
slog.Debug("tokenizer", "merges", merges)
log.Trace("tokenizer", "merges", merges)
pairwise := func(a, b int) *candidate {
if a < 0 || b >= len(runes) {
@@ -156,7 +159,7 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
pqv := pq.Values()
for _, v := range pqv {
e := v.(*candidate)
slog.Debug("candidate", "candidate", e)
log.Trace("candidate", "candidate", e)
}
for !pq.Empty() {
@@ -164,7 +167,7 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
pair := v.(*candidate)
left, right := merges[pair.a], merges[pair.b]
slog.Debug("pair", "left", left, "right", right)
log.Trace("pair", "left", left, "right", right)
if len(left.runes) == 0 || len(right.runes) == 0 {
continue
}
@@ -189,14 +192,14 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
}
}
slog.Debug("merges", "merges", merges)
log.Trace("merges", "merges", merges)
for _, merge := range merges {
if len(merge.runes) > 0 {
if id := spm.vocab.Encode(string(merge.runes)); id >= 0 {
ids = append(ids, id)
} else {
slog.Debug("missing token", "token", string(merge.runes))
log.Error("missing token", "token", string(merge.runes))
}
}
}
@@ -206,19 +209,19 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
if addSpecial && len(ids) > 0 {
if spm.vocab.AddBOS {
if ids[0] == spm.vocab.BOS {
slog.Warn("adding bos token to prompt which already has it", "id", spm.vocab.BOS)
log.Warn("adding bos token to prompt which already has it", "id", spm.vocab.BOS)
}
slog.Debug("adding bos token to prompt", "id", spm.vocab.BOS)
log.Debug("adding bos token to prompt", "id", spm.vocab.BOS)
ids = append([]int32{spm.vocab.BOS}, ids...)
}
if spm.vocab.AddEOS {
if ids[len(ids)-1] == spm.vocab.EOS {
slog.Warn("adding eos token to prompt which already has it", "id", spm.vocab.EOS)
log.Warn("adding eos token to prompt which already has it", "id", spm.vocab.EOS)
}
slog.Debug("adding eos token to prompt", "id", spm.vocab.EOS)
log.Debug("adding eos token to prompt", "id", spm.vocab.EOS)
ids = append(ids, spm.vocab.EOS)
}
}
@@ -241,6 +244,6 @@ func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
}
}
slog.Debug("decoded", "ids", ids, "text", sb.String())
log.Debug("decoded", "ids", ids, "text", sb.String())
return sb.String(), nil
}

View File

@@ -116,19 +116,9 @@ func (i *Instance) Readline() (string, error) {
switch r {
case KeyUp:
if i.History.Pos > 0 {
if i.History.Pos == i.History.Size() {
currentLineBuf = []rune(buf.String())
}
buf.Replace([]rune(i.History.Prev()))
}
i.historyPrev(buf, &currentLineBuf)
case KeyDown:
if i.History.Pos < i.History.Size() {
buf.Replace([]rune(i.History.Next()))
if i.History.Pos == i.History.Size() {
buf.Replace(currentLineBuf)
}
}
i.historyNext(buf, &currentLineBuf)
case KeyLeft:
buf.MoveLeft()
case KeyRight:
@@ -185,6 +175,10 @@ func (i *Instance) Readline() (string, error) {
esc = true
case CharInterrupt:
return "", ErrInterrupt
case CharPrev:
i.historyPrev(buf, &currentLineBuf)
case CharNext:
i.historyNext(buf, &currentLineBuf)
case CharLineStart:
buf.MoveToStart()
case CharLineEnd:
@@ -246,6 +240,24 @@ func (i *Instance) HistoryDisable() {
i.History.Enabled = false
}
func (i *Instance) historyPrev(buf *Buffer, currentLineBuf *[]rune) {
if i.History.Pos > 0 {
if i.History.Pos == i.History.Size() {
*currentLineBuf = []rune(buf.String())
}
buf.Replace([]rune(i.History.Prev()))
}
}
func (i *Instance) historyNext(buf *Buffer, currentLineBuf *[]rune) {
if i.History.Pos < i.History.Size() {
buf.Replace([]rune(i.History.Next()))
if i.History.Pos == i.History.Size() {
buf.Replace(*currentLineBuf)
}
}
}
func NewTerminal() (*Terminal, error) {
fd := os.Stdin.Fd()
termios, err := SetRawMode(fd)

View File

@@ -691,65 +691,6 @@ type EmbeddingResponse struct {
Embedding []float32 `json:"embedding"`
}
func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
var req EmbeddingRequest
if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
http.Error(w, fmt.Sprintf("bad request: %s", err), http.StatusBadRequest)
return
}
w.Header().Set("Content-Type", "application/json")
slog.Debug("embedding request", "content", req.Content)
seq, err := s.NewSequence(req.Content, nil, NewSequenceParams{embedding: true})
if err != nil {
http.Error(w, fmt.Sprintf("Failed to create new sequence: %v", err), http.StatusInternalServerError)
return
}
// Ensure there is a place to put the sequence, released when removed from s.seqs
if err := s.seqsSem.Acquire(r.Context(), 1); err != nil {
if errors.Is(err, context.Canceled) {
slog.Info("aborting embeddings request due to client closing the connection")
} else {
slog.Error("Failed to acquire semaphore", "error", err)
}
return
}
s.mu.Lock()
found := false
for i, sq := range s.seqs {
if sq == nil {
seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
if err != nil {
s.mu.Unlock()
http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
return
}
s.seqs[i] = seq
s.cond.Signal()
found = true
break
}
}
s.mu.Unlock()
if !found {
http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
return
}
embedding := <-seq.embedding
if err := json.NewEncoder(w).Encode(&EmbeddingResponse{
Embedding: embedding,
}); err != nil {
http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
}
}
type HealthResponse struct {
Status string `json:"status"`
Progress float32 `json:"progress"`
@@ -927,9 +868,13 @@ func Execute(args []string) error {
defer listener.Close()
mux := http.NewServeMux()
mux.HandleFunc("/embedding", server.embeddings)
mux.HandleFunc("/completion", server.completion)
mux.HandleFunc("/health", server.health)
// TODO: support embeddings
mux.HandleFunc("POST /embedding", func(w http.ResponseWriter, r *http.Request) {
http.Error(w, "this model does not support embeddings", http.StatusNotImplemented)
})
mux.HandleFunc("POST /completion", server.completion)
mux.HandleFunc("GET /health", server.health)
httpServer := http.Server{
Handler: mux,

View File

@@ -84,14 +84,11 @@ func (s *Sampler) sample(tokens []token) (token, error) {
return greedy(tokens), nil
}
if s.topK > 0 {
tokens = topK(tokens, s.topK)
} else {
sortLogits(tokens)
}
// topK also sorts the tokens in descending order of logits
tokens = topK(tokens, s.topK)
// token logit values are updated to probabilities
tokens = temperature(tokens, s.temperature)
tokens = softmax(tokens)
tokens = topP(tokens, s.topP)
tokens = minP(tokens, s.minP)

View File

@@ -1,12 +1,42 @@
package sample
import (
"container/heap"
"math"
"slices"
)
// temperature applies scaling and softmax to the logits
// tokenHeap implements heap.Interface and holds tokens as a min-heap to track k largest elements
type tokenHeap []token
func (h tokenHeap) Len() int { return len(h) }
func (h tokenHeap) Less(i, j int) bool { return h[i].value < h[j].value }
func (h tokenHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *tokenHeap) Push(x any) {
*h = append(*h, x.(token))
}
func (h *tokenHeap) Pop() any {
old := *h
n := len(old)
x := old[n-1]
*h = old[0 : n-1]
return x
}
// temperature applies scaling to the logits
func temperature(ts []token, temp float32) []token {
// Ensure temperature clipping near 0 to avoid numerical instability
temp = max(temp, 1e-7)
for i := range ts {
ts[i].value = ts[i].value / temp
}
return ts
}
// softmax applies normalization to the logits
func softmax(ts []token) []token {
// Find max logit for numerical stability
maxLogit := float32(math.Inf(-1))
for _, t := range ts {
@@ -15,15 +45,14 @@ func temperature(ts []token, temp float32) []token {
}
}
// Apply temperature and compute exp(x - max)
temp = max(temp, 1e-7)
// Compute exp(x - max)
var sum float32
for i, v := range ts {
ts[i].value = float32(math.Exp(float64((v.value - maxLogit) / temp)))
ts[i].value = float32(math.Exp(float64(v.value - maxLogit)))
sum += ts[i].value
}
// Normalize
// exp(x - max) / sum(exp(x - max))
for i := range ts {
ts[i].value /= sum
}
@@ -31,62 +60,42 @@ func temperature(ts []token, temp float32) []token {
return ts
}
// siftDown maintains a min-heap property by recursively moving larger elements down the heap.
//
// The heap is represented as an array where for any node at index i:
// - Left child is at index 2i + 1
// - Right child is at index 2i + 2
// - Parent is at index (i-1)/2
//
// The function compares a node with its children and:
// 1. Finds the smallest value between the node and its children
// 2. If the node is not the smallest, swaps it with its smallest child
// 3. Continues this process down the affected path until the min-heap property is restored
func siftDown(data []token, start, end int) {
root := start
for {
child := 2*root + 1
if child >= end {
break
}
// Find smaller child (we want min heap)
if child+1 < end && data[child+1].value < data[child].value {
child++
}
// Exit if root is already smaller than children
if data[root].value <= data[child].value {
break
}
// Swap with smaller child and continue
data[root], data[child] = data[child], data[root]
root = child
}
}
// topK limits the number of tokens considered to the k highest logits
func topK(ts []token, k int) []token {
if k >= len(ts) {
if k >= len(ts) || k <= 0 {
slices.SortFunc(ts, func(a, b token) int {
switch {
case a.value < b.value:
return 1
case a.value > b.value:
return -1
default:
return 0
}
})
return ts
}
// Heapify + siftDown - O(nlog(k))
// Build min-heap of first k elements
heap := ts[:k]
for i := k/2 - 1; i >= 0; i-- {
siftDown(heap, i, k)
}
// Process remaining elements - if larger than heap root, replace root
// Initialize min-heap with first k elements
h := make(tokenHeap, k)
copy(h, ts[:k])
heap.Init(&h)
// Process remaining elements
for i := k; i < len(ts); i++ {
if ts[i].value > heap[0].value {
heap[0] = ts[i]
siftDown(heap, 0, k)
if ts[i].value > h[0].value {
heap.Pop(&h)
heap.Push(&h, ts[i])
}
}
slices.Reverse(heap)
// Convert heap to sorted slice in descending order
result := make([]token, len(h))
for i := k - 1; i >= 0; i-- {
result[i] = heap.Pop(&h).(token)
}
ts = heap
return ts
return result
}
// topP limits tokens to those with cumulative probability p
@@ -134,62 +143,3 @@ func minP(ts []token, p float32) []token {
ts = validTokens
return ts
}
// TODO(parthsareen): possibly replace with simpler implementation https://github.com/ollama/ollama/issues/9584
// sortLogits sorts implementation to sort tokens by logits using counting sort
// counting sort is faster than built-in sort for this use case
func sortLogits(tokens []token) {
if len(tokens) <= 1 {
return
}
// Find max/min in a single pass
minLogit, maxLogit := tokens[0].value, tokens[0].value
for _, t := range tokens[1:] {
if t.value < minLogit {
minLogit = t.value
} else if t.value > maxLogit {
maxLogit = t.value
}
}
// Calculate scaling to map to uint32 range
logitRange := maxLogit - minLogit
if logitRange < 1e-6 {
return // All values effectively equal
}
// Count frequencies directly from tokens
const maxInt = (1 << 24) - 1 // Use 24 bits for good granularity
var counts [256]int // For first byte
// First pass: count frequencies
for _, t := range tokens {
// Map to [0, maxInt] range
score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
counts[score>>16]++
}
// Calculate offsets
var offset int
for i := range counts {
count := counts[i]
counts[i] = offset
offset += count
}
// Second pass: place elements in correct position
output := make([]token, len(tokens))
// Track current positions
countsCopy := counts
for i, t := range tokens {
score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
pos := countsCopy[score>>16]
countsCopy[score>>16]++
output[len(tokens)-1-pos] = tokens[i]
}
copy(tokens, output)
}

View File

@@ -6,80 +6,155 @@ import (
"testing"
)
// Helper to convert float64 slice to logit slice
func toTokens(values []float64) []token {
// Helper to convert float32 slice to logit slice
func toTokens(values []float32) []token {
tokens := make([]token, len(values))
for i, v := range values {
tokens[i] = token{
id: int32(i),
value: float32(v),
value: v,
}
}
return tokens
}
// Helper to compare logit slices
func compareLogits(t *testing.T, name string, want []float64, got []token) {
func compareLogits(t *testing.T, name string, want []float32, got []token) {
t.Helper()
if len(want) != len(got) {
t.Errorf("%s: length mismatch: want %d, got %d", name, len(want), len(got))
return
}
for i := range want {
if math.Abs(float64(got[i].value)-want[i]) > 1e-6 {
if math.Abs(float64(got[i].value-want[i])) > 1e-6 {
t.Errorf("%s: index %d: want %f, got %f", name, i, want[i], got[i].value)
}
}
}
func TestTemperatureAndSoftmax(t *testing.T) {
input := []float64{1, 4, -2, 0}
func TestTemperature(t *testing.T) {
input := []float32{1.0, 4.0, -2.0, 0.0}
got := temperature(toTokens(input), 0.5)
want := []float32{2.0, 8.0, -4.0, 0.0}
compareLogits(t, "temperature(0.5)", want, got)
// Check probabilities sum to 1
var sum float32
for _, token := range got {
sum += token.value
}
if math.Abs(float64(sum)-1.0) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
got = temperature(toTokens(input), 1.0)
want = []float32{1.0, 4.0, -2.0, 0.0}
compareLogits(t, "temperature(1)", want, got)
got = temperature(toTokens(input), 0.0)
want = []float32{1e7, 4e7, -2e7, 0.0}
compareLogits(t, "temperature(0)", want, got)
}
func TestSoftmax(t *testing.T) {
tests := []struct {
name string
input []float32
expected []float32
}{
{
name: "correctness softmax",
input: []float32{1, -2, 3, 0},
expected: []float32{0.113550, 0.005653, 0.839024, 0.041773},
},
{
name: "normal distribution",
input: []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367},
},
{
name: "single value",
input: []float32{1.0},
},
{
name: "identical values",
input: []float32{0.9, 0.9, 0.9},
},
{
name: "large values",
input: []float32{1000.0, 2000.0, 3000.0},
},
{
name: "small values",
input: []float32{1e-6, 2e-6, 3e-6},
},
{
name: "negative values",
input: []float32{-1.0, -2.0, -3.0},
},
{
name: "mixed values",
input: []float32{-100.0, 0.0, 100.0},
},
}
got = temperature(toTokens(input), 1)
// Check probabilities sum to 1
sum = 0.0
for _, token := range got {
sum += token.value
}
if math.Abs(float64(sum)-1.0) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := softmax(toTokens(tt.input))
if tt.expected != nil {
compareLogits(t, tt.name, tt.expected, got)
return
}
// Check probabilities sum to 1
var sum float32
for _, token := range got {
sum += token.value
if token.value < 0 || token.value > 1 {
t.Errorf("probability out of range [0,1]: got %f", token.value)
}
}
if math.Abs(float64(sum-1.0)) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
}
})
}
}
func TestTopK(t *testing.T) {
input := []float64{-3, -2, -1, 0, 1, 2, 4}
input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
// Test k=3
got := topK(toTokens(input), 3)
if len(got) != 3 {
t.Errorf("topK(3): wrong length: want 3, got %d", len(got))
// Test k=5
got := topK(toTokens(input), 5)
if len(got) != 5 {
t.Errorf("topK(5): wrong length: want 5, got %d", len(got))
}
// Should keep highest 3 values: 4, 2, 1
want := []float64{4, 2, 1}
// Should keep highest 3 values in descending order
want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154}
compareLogits(t, "topK(3)", want, got)
// Test k > len
got = topK(toTokens(input), 10)
compareLogits(t, "topK(10)", input, got)
got = topK(toTokens(input), 20)
if len(got) != len(input) {
t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(got))
}
// Test k=-1
input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
got = topK(toTokens(input), -1)
if len(got) != len(input) {
t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
}
compareLogits(t, "topK(-1)", want, got)
// Test k=0
input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
got = topK(toTokens(input), 0)
if len(got) != len(input) {
t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
}
compareLogits(t, "topK(-1)", want, got)
}
func TestTopP(t *testing.T) {
input := []float64{-3, -2, -1, 0, 1, 2, 4}
input := []float32{-3, -2, -1, 0, 1, 2, 4}
tokens := toTokens(input)
// First apply temperature and softmax to get probabilities
tokens = temperature(tokens, 1)
sortLogits(tokens)
tokens = softmax(tokens)
tokens = topK(tokens, 20)
// Then apply topP
got := topP(tokens, 0.95)
@@ -92,11 +167,11 @@ func TestTopP(t *testing.T) {
}
func TestMinP(t *testing.T) {
input := []float64{-3, -2, -1, 0, 1, 2, 4, 3}
input := []float32{-3, -2, -1, 0, 1, 2, 4, 3}
tokens := toTokens(input)
// First apply temperature and softmax
tokens = temperature(tokens, 1)
tokens = softmax(tokens)
// Then apply minP
got := minP(tokens, 0.2)
@@ -108,10 +183,10 @@ func TestMinP(t *testing.T) {
}
func TestSortLogits(t *testing.T) {
input := []float64{3, 1, 4, 2, -1, 0, -2}
input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
tokens := toTokens(input)
sortLogits(tokens)
tokens = topK(tokens, 20)
for i := 1; i < len(tokens); i++ {
if tokens[i].value > tokens[i-1].value {
@@ -120,7 +195,7 @@ func TestSortLogits(t *testing.T) {
}
}
want := []float64{4, 3, 2, 1, 0, -1, -2}
want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
compareLogits(t, "sortLogits", want, tokens)
}
@@ -144,6 +219,14 @@ func BenchmarkTransforms(b *testing.B) {
}
})
b.Run("Softmax", func(b *testing.B) {
b.ResetTimer()
for b.Loop() {
copy(tokensCopy, tokens)
softmax(tokensCopy)
}
})
b.Run("TopK", func(b *testing.B) {
b.ResetTimer()
for b.Loop() {
@@ -172,7 +255,7 @@ func BenchmarkTransforms(b *testing.B) {
b.ResetTimer()
for b.Loop() {
copy(tokensCopy, tokens)
sortLogits(tokensCopy)
topK(tokensCopy, 200000)
}
})
}

View File

@@ -435,7 +435,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
return
}
kvData, err := getKVData(m.ModelPath, false)
kvData, _, err := getModelData(m.ModelPath, false)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@@ -483,8 +483,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
}
if err := g.Wait(); err != nil {
slog.Error("embedding generation failed", "error", err)
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Errorf("failed to generate embeddings: %v", err)})
c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": strings.TrimSpace(err.Error())})
return
}
@@ -545,8 +544,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
embedding, err := r.Embedding(c.Request.Context(), req.Prompt)
if err != nil {
slog.Info(fmt.Sprintf("embedding generation failed: %v", err))
c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Errorf("failed to generate embedding: %v", err)})
c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": strings.TrimSpace(err.Error())})
return
}
@@ -850,16 +848,23 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
fmt.Fprint(&sb, m.String())
resp.Modelfile = sb.String()
kvData, err := getKVData(m.ModelPath, req.Verbose)
kvData, tensors, err := getModelData(m.ModelPath, req.Verbose)
if err != nil {
return nil, err
}
delete(kvData, "general.name")
delete(kvData, "tokenizer.chat_template")
resp.ModelInfo = kvData
tensorData := make([]api.Tensor, len(tensors.Items()))
for cnt, t := range tensors.Items() {
tensorData[cnt] = api.Tensor{Name: t.Name, Type: t.Type(), Shape: t.Shape}
}
resp.Tensors = tensorData
if len(m.ProjectorPaths) > 0 {
projectorData, err := getKVData(m.ProjectorPaths[0], req.Verbose)
projectorData, _, err := getModelData(m.ProjectorPaths[0], req.Verbose)
if err != nil {
return nil, err
}
@@ -869,17 +874,17 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
return resp, nil
}
func getKVData(digest string, verbose bool) (ggml.KV, error) {
func getModelData(digest string, verbose bool) (ggml.KV, ggml.Tensors, error) {
maxArraySize := 0
if verbose {
maxArraySize = -1
}
kvData, err := llm.LoadModel(digest, maxArraySize)
data, err := llm.LoadModel(digest, maxArraySize)
if err != nil {
return nil, err
return nil, ggml.Tensors{}, err
}
kv := kvData.KV()
kv := data.KV()
if !verbose {
for k := range kv {
@@ -889,7 +894,7 @@ func getKVData(digest string, verbose bool) (ggml.KV, error) {
}
}
return kv, nil
return kv, data.Tensors(), nil
}
func (s *Server) ListHandler(c *gin.Context) {