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Author SHA1 Message Date
Bruce MacDonald
04950140ec server: do not attempt to parse offset file as gguf
This logic was causing issues for me when importing a gguf that had some padding at the end of the file. The valid gguf would be read, but then it would try to read the offset as a different gguf file. This does not seem right.
2025-04-09 09:41:46 -07:00
8 changed files with 91 additions and 289 deletions

View File

@@ -104,8 +104,8 @@ COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12
FROM --platform=linux/arm64 scratch AS arm64
COPY --from=cuda-11 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_v11
COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12
COPY --from=jetpack-5 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_jetpack5
COPY --from=jetpack-6 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_jetpack6
COPY --from=jetpack-5 dist/lib/ollama/cuda_v11 lib/ollama/cuda_jetpack5
COPY --from=jetpack-6 dist/lib/ollama/cuda_v12 lib/ollama/cuda_jetpack6
FROM scratch AS rocm
COPY --from=rocm-6 dist/lib/ollama/rocm /lib/ollama/rocm

View File

@@ -163,7 +163,6 @@ func (t *ToolCallFunctionArguments) String() string {
type Tool struct {
Type string `json:"type"`
Items any `json:"items,omitempty"`
Function ToolFunction `json:"function"`
}
@@ -214,12 +213,9 @@ type ToolFunction struct {
Description string `json:"description"`
Parameters struct {
Type string `json:"type"`
Defs any `json:"$defs,omitempty"`
Items any `json:"items,omitempty"`
Required []string `json:"required"`
Properties map[string]struct {
Type PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
} `json:"properties"`

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@@ -6,7 +6,6 @@ import (
"fmt"
"io"
"log/slog"
"reflect"
"slices"
"strings"
@@ -53,80 +52,32 @@ func (kv KV) EmbeddingLength() uint64 {
return uint64(kv.Uint("embedding_length"))
}
func (kv KV) HeadCounts() []uint64 {
return kv.UintOrArrayAsArray("attention.head_count", kv.BlockCount(), 1)
func (kv KV) HeadCount() uint64 {
return uint64(kv.Uint("attention.head_count"))
}
func (kv KV) HeadCountKVs() []uint64 {
return kv.UintOrArrayAsArray("attention.head_count_kv", kv.BlockCount(), 1)
func (kv KV) HeadCountKV() uint64 {
return uint64(kv.Uint("attention.head_count_kv", 1))
}
func (kv KV) EmbeddingHeadCount() []uint64 {
headCount := kv.HeadCounts()
embeddingHeadCount := make([]uint64, len(headCount))
for i, heads := range headCount {
if heads == 0 {
embeddingHeadCount[i] = 0
} else {
embeddingHeadCount[i] = kv.EmbeddingLength() / heads
}
func (kv KV) EmbeddingHeadCount() uint64 {
if heads := kv.HeadCount(); heads > 0 {
return kv.EmbeddingLength() / heads
}
return embeddingHeadCount
return 0
}
func (kv KV) FillArrayOrDefault(key string, defaultValue []uint64) []uint64 {
length := len(defaultValue)
if v, ok := keyValueUntyped(kv, key); ok {
switch v := v.(type) {
case uint32:
return FillArray(uint64(v), length)
case uint64:
return FillArray(v, length)
case int32:
return FillArray(uint64(v), length)
default:
slog.Warn("unsupported type", "key", key, "type", reflect.TypeOf(v))
}
}
return defaultValue
func (kv KV) EmbeddingHeadCountK() uint64 {
return uint64(kv.Uint("attention.key_length", uint32(kv.EmbeddingHeadCount())))
}
func (kv KV) EmbeddingHeadCountK() []uint64 {
return kv.FillArrayOrDefault("attention.key_length", kv.EmbeddingHeadCount())
func (kv KV) EmbeddingHeadCountV() uint64 {
return uint64(kv.Uint("attention.value_length", uint32(kv.EmbeddingHeadCount())))
}
func (kv KV) EmbeddingHeadCountV() []uint64 {
return kv.FillArrayOrDefault("attention.value_length", kv.EmbeddingHeadCount())
}
func (kv KV) GQAMax() uint64 {
heads := kv.HeadCounts()
headsKV := kv.HeadCountKVs()
if len(heads) != len(headsKV) {
slog.Warn("head count and head count kv are not the same length")
return 0
}
if len(heads) == 0 {
slog.Warn("head count is empty")
return 0
}
maxGQA := uint64(0)
for i := range heads {
head := heads[i]
headKV := headsKV[i]
if head == 0 || headKV == 0 {
return 0
}
gqa := head / headKV
if gqa > maxGQA {
maxGQA = gqa
}
}
return maxGQA
func (kv KV) GQA() uint64 {
return kv.HeadCount() / kv.HeadCountKV()
}
func (kv KV) ContextLength() uint64 {
@@ -153,41 +104,6 @@ func (kv KV) Bool(key string, defaultValue ...bool) bool {
return keyValue(kv, key, append(defaultValue, false)...)
}
func (kv KV) UintOrArrayAsArray(key string, n uint64, defaultSingleValue ...uint64) []uint64 {
var singleValue *uint64
if v, ok := keyValueUntyped(kv, key); ok {
switch v := v.(type) {
case *array:
switch v.values[0].(type) {
case int32, uint32, uint64:
values, ok := AsUint64Array(v.values)
if ok {
return values
}
default:
slog.Warn("unexpected array value type", "key", key, "type", reflect.TypeOf(v))
}
case uint32:
val := uint64(v)
singleValue = &val
case int32:
val := uint64(v)
singleValue = &val
}
}
if singleValue == nil {
slog.Warn("falling back to default")
singleValue = &defaultSingleValue[0]
}
values := make([]uint64, n)
for i := range values {
values[i] = *singleValue
}
return values
}
func (kv KV) Strings(key string, defaultValue ...[]string) []string {
r := keyValue(kv, key, &array{})
s := make([]string, r.size)
@@ -225,24 +141,16 @@ func (kv KV) OllamaEngineRequired() bool {
}
func keyValue[T string | uint32 | uint64 | float32 | *array | bool](kv KV, key string, defaultValue ...T) T {
if val, ok := keyValueUntyped(kv, key); ok {
return val.(T)
}
slog.Warn("key not found", "key", key, "default", defaultValue[0])
return defaultValue[0]
}
func keyValueUntyped(kv KV, key string) (any, bool) {
if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
key = kv.Architecture() + "." + key
}
if val, ok := kv[key]; ok {
return val, true
return val.(T)
}
return nil, false
slog.Warn("key not found", "key", key, "default", defaultValue[0])
return defaultValue[0]
}
type Tensors struct {
@@ -510,22 +418,12 @@ func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType string) (kv []uint64, partialOffload, fullOffload uint64) {
embedding := f.KV().EmbeddingLength()
heads := f.KV().HeadCounts()
headsKV := f.KV().HeadCountKVs()
heads := f.KV().HeadCount()
headsKV := f.KV().HeadCountKV()
vocab := uint64(f.KV()["tokenizer.ggml.tokens"].(*array).size)
embeddingHeads := f.KV().EmbeddingHeadCount()
maxEmbeddingHeads, ok := MaxValue(embeddingHeads)
if !ok {
maxEmbeddingHeads = 1
slog.Warn("failed to get max embedding heads")
}
embeddingHeadsK := f.KV().EmbeddingHeadCountK()
maxEmbeddingHeadsK, ok := MaxValue(embeddingHeadsK)
if !ok {
maxEmbeddingHeadsK = 1
slog.Warn("failed to get max embedding headsK")
}
embeddingHeadsV := f.KV().EmbeddingHeadCountV()
layers := f.Tensors().GroupLayers()
@@ -533,30 +431,19 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
bytesPerElement := kvCacheBytesPerElement(kvCacheType)
kv = make([]uint64, f.KV().BlockCount())
for i := range kv {
kv[i] = uint64(float64(context*(embeddingHeadsK[i]+embeddingHeadsV[i])*headsKV[i]) * bytesPerElement)
}
maxHeads, ok := MaxValue(heads)
if !ok {
maxHeads = 1
slog.Warn("failed to get max heads")
}
maxHeadsKV, ok := MaxValue(headsKV)
if !ok {
maxHeadsKV = 1
slog.Warn("failed to get max headsKV")
kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
}
switch f.KV().Architecture() {
case "llama":
fullOffload = max(
4*batch*(1+4*embedding+context*(1+maxHeads)),
4*batch*(1+4*embedding+context*(1+heads)),
4*batch*(embedding+vocab),
)
partialOffload = 4 * batch * embedding
partialOffload += max(
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*maxHeads+maxEmbeddingHeads*maxHeadsKV),
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embeddingHeads*headsKV),
4*batch*(embedding+vocab)+embedding*vocab*105/128,
)
@@ -564,16 +451,16 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
// mixtral 8x22b
ff := uint64(f.KV()["llama.feed_forward_length"].(uint32))
partialOffload = max(
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+maxHeadsKV+embedding+context+maxEmbeddingHeads*maxHeadsKV),
4*(context*batch*maxHeads+context*maxEmbeddingHeads*maxHeadsKV+batch*1024+maxEmbeddingHeads*maxHeadsKV*batch),
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embeddingHeads*headsKV),
4*(context*batch*heads+context*embeddingHeads*headsKV+batch*1024+embeddingHeads*headsKV*batch),
)
} else if ffnGateWeight, ok := layers["blk.0"]["ffn_gate.0.weight"]; ok {
// mixtral 8x7b
ffnGateWeight1 := ffnGateWeight.Shape[1]
fullOffload = 4 * batch * (2 + 3*embedding + context*(1+maxHeads) + 2*maxHeadsKV + ffnGateWeight1)
fullOffload = 4 * batch * (2 + 3*embedding + context*(1+heads) + 2*headsKV + ffnGateWeight1)
partialOffload = max(
4*batch*(3+maxEmbeddingHeads*maxHeadsKV+embedding+context*(1+maxHeads)+ffnGateWeight1)+(embedding*embedding+3*embedding*maxHeadsKV*ffnGateWeight1)*9/16,
4*batch*(1+2*embedding+context*(1+maxHeads))+embedding*(6*context*maxHeadsKV/maxHeads+embedding*9/16),
4*batch*(3+embeddingHeads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
4*batch*(1+2*embedding+context*(1+heads))+embedding*(6*context*headsKV/heads+embedding*9/16),
)
}
case "mllama":
@@ -582,7 +469,7 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
crossAttentionLayers := f.KV().Uints("attention.cross_attention_layers")
for i := range kv {
if slices.Contains(crossAttentionLayers, uint32(i)) {
kv[i] = headsKV[i] * (embeddingHeadsK[i] + embeddingHeadsV[i]) *
kv[i] = headsKV * (embeddingHeadsK + embeddingHeadsV) *
4 * // sizeof(float32)
visionTokens *
tiles
@@ -590,7 +477,7 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
}
fullOffload = max(
4*batch*(2+3*embedding+maxEmbeddingHeadsK*maxHeads+context*(1+maxHeads)),
4*batch*(2+3*embedding+embeddingHeadsK*heads+context*(1+heads)),
// vocab graph
4*batch*(embedding+vocab),
)
@@ -604,23 +491,23 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
partialOffload = max(
4*(batch*
(2*embedding+1+context*(1+maxHeads)+maxEmbeddingHeadsK*maxHeads)+
(2*embedding+1+context*(1+heads)+embeddingHeadsK*heads)+
ropeFreqsCount+
maxEmbeddingHeadsK*context*maxHeadsKV),
embeddingHeadsK*context*headsKV),
// vocab graph
4*batch*(embedding+vocab)+embedding*vocab*105/128,
)
case "gemma", "gemma2", "gemma3":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(2+context+context*maxHeads+2*embedding+2*maxEmbeddingHeadsK*maxHeads),
4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
)
partialOffload = max(
4*embedding*batch+embedding*vocab*105/128+4*vocab*batch,
4*batch*(2*embedding+1+2*maxEmbeddingHeadsK*maxHeads+context+context*maxHeads)+
4*maxEmbeddingHeadsK*context*8+
embedding*embedding*maxEmbeddingHeadsK*maxHeads*9/16,
4*batch*(2*embedding+1+2*embeddingHeadsK*heads+context+context*heads)+
4*embeddingHeadsK*context*8+
embedding*embeddingHeadsK*heads*9/16,
)
// Gemma2 also has sliding window attention but we only have an optimized implementation in the Ollama
@@ -632,42 +519,42 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
// Every 6th layer is a global layer, which is the full context size that has already been set. The other
// layers are the smaller local (sliding) layers.
if (i+1)%gemma3GlobalCacheCount != 0 {
kv[i] = uint64(float64(slidingWindow*(embeddingHeadsK[i]+embeddingHeadsV[i])*headsKV[i]) * bytesPerElement)
kv[i] = uint64(float64(slidingWindow*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
}
}
}
case "command-r":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(2+4*embedding+context*(1+maxHeads)),
4*batch*(2+4*embedding+context*(1+heads)),
)
partialOffload = max(
4*batch*(embedding+vocab)+embedding*vocab*105/128,
4*batch*(1+2*embedding+context*(1+maxHeads))+4*embedding*context+embedding*embedding*9/16,
4*batch*(1+2*embedding+context*(1+heads))+4*embedding*context+embedding*embedding*9/16,
)
case "qwen2":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(1+2*embedding+context+context*maxHeads),
4*batch*(1+2*embedding+context+context*heads),
)
partialOffload = max(
4*batch*(embedding+vocab)+embedding*vocab*105/128,
4*(batch*(1+2*embedding+context*(1+maxHeads))+embedding*(1+context)),
4*(batch*(1+2*embedding+context*(1+heads))+embedding*(1+context)),
)
case "phi2":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(1+4*embedding+context+context*maxHeads),
4*batch*(1+4*embedding+context+context*heads),
)
partialOffload = max(
4*batch*(2*embedding+vocab)+embedding*vocab*105/128,
4*batch*(2+3*embedding+context+context*maxHeads),
4*batch*(2+3*embedding+context+context*heads),
)
case "stablelm":
fullOffload = 4 * batch * (context*(1+maxHeads) + 3*embedding + 2)
fullOffload = 4 * batch * (context*(1+heads) + 3*embedding + 2)
partialOffload = max(
4*batch*(vocab+2*embedding),
fullOffload,
@@ -675,12 +562,12 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
case "deepseek2":
fullOffload = max(
4*batch*(3*embedding+vocab),
4*batch*(3*embedding+2+context*(1+maxHeadsKV)+2*maxEmbeddingHeadsK*maxHeadsKV),
4*batch*(3*embedding+2+context*(1+headsKV)+2*embeddingHeadsK*headsKV),
)
partialOffload = max(
4*batch*(3*embedding+vocab)+embedding*vocab*105/128,
4*batch*(2*embedding+1+2*maxEmbeddingHeadsK*maxHeadsKV+context+context*maxHeadsKV)+4*maxEmbeddingHeadsK*context*maxHeadsKV+embedding*embedding*maxEmbeddingHeadsK*maxHeadsKV*9/16,
4*batch*(2*embedding+1+2*embeddingHeadsK*headsKV+context+context*headsKV)+4*embeddingHeadsK*context*headsKV+embedding*embeddingHeadsK*headsKV*9/16,
)
case "chatglm":
fullOffload = 4 * batch * (embedding + vocab)
@@ -691,8 +578,8 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
4*batch*(2+
2*embedding+
context+
context*maxHeads+
maxEmbeddingHeadsK*maxHeads+
context*heads+
embeddingHeadsK*heads+
qkvBias.Shape[0]),
)
@@ -700,11 +587,11 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
partialOffload,
4*batch*(1+
2*embedding+
maxEmbeddingHeadsK*maxHeads+
embeddingHeadsK*heads+
context+
context*maxHeads)+
4*maxEmbeddingHeadsK*context+
4*context*maxEmbeddingHeadsK+
context*heads)+
4*embeddingHeadsK*context+
4*context*embeddingHeadsK+
4*qkvBias.Shape[0],
)
}
@@ -776,15 +663,9 @@ func (f GGML) SupportsFlashAttention() bool {
}
// Check head counts match and are non-zero
headCount := f.KV().HeadCounts()
embeddingHeadCountK := f.KV().EmbeddingHeadCountK()
embeddingHeadCountV := f.KV().EmbeddingHeadCountV()
for i := range headCount {
if embeddingHeadCountK[i] != embeddingHeadCountV[i] {
return false
}
}
return true
headCountK := f.KV().EmbeddingHeadCountK()
headCountV := f.KV().EmbeddingHeadCountV()
return headCountK != 0 && headCountV != 0 && headCountK == headCountV
}
// kvCacheBytesPerElement returns the number of bytes per element for a given KV cache type
@@ -798,54 +679,3 @@ func kvCacheBytesPerElement(cacheType string) float64 {
return 2 // f16 (default)
}
}
func AsUint64Array(v []any) ([]uint64, bool) {
switch v[0].(type) {
case uint32:
values := make([]uint64, len(v))
for i, v := range v {
values[i] = uint64(v.(uint32))
}
return values, true
case uint64:
values := make([]uint64, len(v))
for i, v := range v {
values[i] = v.(uint64)
}
return values, true
case int32:
values := make([]uint64, len(v))
for i, val := range v {
val := val.(int32)
if val < 0 {
slog.Warn("negative value in int32 array", "value", val)
return nil, false
}
values[i] = uint64(val)
}
return values, true
}
return nil, false
}
func MaxValue(values []uint64) (uint64, bool) {
if len(values) == 0 {
return 0, false
}
max := values[0]
for _, v := range values {
if v > max {
max = v
}
}
return max, true
}
func FillArray[T any](value T, n int) []T {
values := make([]T, n)
for i := range values {
values[i] = value
}
return values
}

View File

@@ -149,7 +149,7 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
}
if graphPartialOffload == 0 {
graphPartialOffload = f.KV().GQAMax() * kvTotal / 6
graphPartialOffload = f.KV().GQA() * kvTotal / 6
}
if graphFullOffload == 0 {
graphFullOffload = graphPartialOffload

View File

@@ -281,12 +281,9 @@ func TestChatMiddleware(t *testing.T) {
Description: "Get the current weather",
Parameters: struct {
Type string `json:"type"`
Defs any `json:"$defs,omitempty"`
Items any `json:"items,omitempty"`
Required []string `json:"required"`
Properties map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
} `json:"properties"`
@@ -295,7 +292,6 @@ func TestChatMiddleware(t *testing.T) {
Required: []string{"location"},
Properties: map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
}{

View File

@@ -497,43 +497,37 @@ func ggufLayers(digest string, fn func(resp api.ProgressResponse)) ([]*layerGGML
return nil, err
}
var offset int64
for offset < stat.Size() {
f, n, err := ggml.Decode(blob, 0)
if errors.Is(err, io.EOF) {
break
} else if err != nil {
f, n, err := ggml.Decode(blob, 0)
if err != nil {
return nil, err
}
mediatype := "application/vnd.ollama.image.model"
if f.KV().Kind() == "adapter" {
mediatype = "application/vnd.ollama.image.adapter"
} else if _, ok := f.KV()[fmt.Sprintf("%s.vision.block_count", f.KV().Architecture())]; ok || f.KV().Kind() == "projector" {
mediatype = "application/vnd.ollama.image.projector"
}
var layer Layer
if digest != "" && n == stat.Size() {
layer, err = NewLayerFromLayer(digest, mediatype, blob.Name())
if err != nil {
slog.Debug("could not create new layer from layer", "error", err)
return nil, err
}
mediatype := "application/vnd.ollama.image.model"
if f.KV().Kind() == "adapter" {
mediatype = "application/vnd.ollama.image.adapter"
} else if _, ok := f.KV()[fmt.Sprintf("%s.vision.block_count", f.KV().Architecture())]; ok || f.KV().Kind() == "projector" {
mediatype = "application/vnd.ollama.image.projector"
}
var layer Layer
if digest != "" && n == stat.Size() && offset == 0 {
layer, err = NewLayerFromLayer(digest, mediatype, blob.Name())
if err != nil {
slog.Debug("could not create new layer from layer", "error", err)
return nil, err
}
}
// Fallback to creating layer from file copy (either NewLayerFromLayer failed, or digest empty/n != stat.Size())
if layer.Digest == "" {
layer, err = NewLayer(io.NewSectionReader(blob, offset, n), mediatype)
if err != nil {
return nil, err
}
}
layers = append(layers, &layerGGML{layer, f})
offset = n
}
// Fallback to creating layer from file copy (either NewLayerFromLayer failed, or digest empty/n != stat.Size())
if layer.Digest == "" {
layer, err = NewLayer(io.NewSectionReader(blob, 0, n), mediatype)
if err != nil {
return nil, err
}
}
layers = append(layers, &layerGGML{layer, f})
return detectChatTemplate(layers)
}

View File

@@ -370,12 +370,9 @@ func TestGenerateChat(t *testing.T) {
Description: "Get the current weather",
Parameters: struct {
Type string `json:"type"`
Defs any `json:"$defs,omitempty"`
Items any `json:"items,omitempty"`
Required []string `json:"required"`
Properties map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
} `json:"properties"`
@@ -384,7 +381,6 @@ func TestGenerateChat(t *testing.T) {
Required: []string{"location"},
Properties: map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
}{
@@ -471,12 +467,9 @@ func TestGenerateChat(t *testing.T) {
Description: "Get the current weather",
Parameters: struct {
Type string `json:"type"`
Defs any `json:"$defs,omitempty"`
Items any `json:"items,omitempty"`
Required []string `json:"required"`
Properties map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
} `json:"properties"`
@@ -485,7 +478,6 @@ func TestGenerateChat(t *testing.T) {
Required: []string{"location"},
Properties: map[string]struct {
Type api.PropertyType `json:"type"`
Items any `json:"items,omitempty"`
Description string `json:"description"`
Enum []any `json:"enum,omitempty"`
}{

View File

@@ -667,19 +667,13 @@ func (runner *runnerRef) waitForVRAMRecovery() chan any {
return finished
}
type ByDurationAndName []*runnerRef
type ByDuration []*runnerRef
func (a ByDurationAndName) Len() int { return len(a) }
func (a ByDurationAndName) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByDurationAndName) Less(i, j int) bool {
// Primary sort by session duration (uint64 to handle negatives)
d1 := uint64(a[i].sessionDuration)
d2 := uint64(a[j].sessionDuration)
if d1 != d2 {
return d1 < d2
}
// Secondary sort by model path lex order
return a[i].modelPath < a[j].modelPath
func (a ByDuration) Len() int { return len(a) }
func (a ByDuration) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByDuration) Less(i, j int) bool {
// uint64 to turn negative time (never unload) to largest
return uint64(a[i].sessionDuration) < uint64(a[j].sessionDuration)
}
// TODO - future consideration to pick runners based on size
@@ -781,7 +775,7 @@ func (s *Scheduler) findRunnerToUnload() *runnerRef {
// In the future we can enhance the algorithm to be smarter about picking the optimal runner to unload
// e.g., if we have multiple options, will one make room for the request?
sort.Sort(ByDurationAndName(runnerList))
sort.Sort(ByDuration(runnerList))
// First try to find a runner that's already idle
for _, runner := range runnerList {