Compare commits

...

65 Commits

Author SHA1 Message Date
Jeffrey Morgan
53da2c6965 llm: remove ambiguous comment when putting upper limit on predictions to avoid infinite generation (#5535) 2024-07-07 14:32:05 -04:00
Jeffrey Morgan
d8def1ff94 llm: allow gemma 2 to context shift (#5534) 2024-07-07 13:41:51 -04:00
Jeffrey Morgan
571dc61955 Update llama.cpp submodule to a8db2a9c (#5530) 2024-07-07 13:03:09 -04:00
Jeffrey Morgan
0e09c380fc llm: print caching notices in debug only (#5533) 2024-07-07 12:38:04 -04:00
Jeffrey Morgan
0ee87615c7 sched: don't error if paging to disk on Windows and macOS (#5523) 2024-07-06 22:01:52 -04:00
Jeffrey Morgan
f8241bfba3 gpu: report system free memory instead of 0 (#5521) 2024-07-06 19:35:04 -04:00
Jeffrey Morgan
4607c70641 llm: add -DBUILD_SHARED_LIBS=off to common cpu cmake flags (#5520) 2024-07-06 18:58:16 -04:00
jmorganca
c12f1c5b99 release: move mingw library cleanup to correct job 2024-07-06 16:12:29 -04:00
jmorganca
a08f20d910 release: remove unwanted mingw dll.a files 2024-07-06 15:21:15 -04:00
jmorganca
6cea036027 Revert "llm: only statically link libstdc++"
This reverts commit 5796bfc401.
2024-07-06 15:10:48 -04:00
jmorganca
5796bfc401 llm: only statically link libstdc++ 2024-07-06 14:06:20 -04:00
jmorganca
f1a379aa56 llm: statically link pthread and stdc++ dependencies in windows build 2024-07-06 12:54:02 -04:00
jmorganca
9ae146993e llm: add GGML_STATIC flag to windows static lib 2024-07-06 03:27:05 -04:00
Jeffrey Morgan
e0348d3fe8 llm: add COMMON_DARWIN_DEFS to arm static build (#5513) 2024-07-05 22:42:42 -04:00
Jeffrey Morgan
2cc854f8cb llm: fix missing dylibs by restoring old build behavior on Linux and macOS (#5511)
* Revert "fix cmake build (#5505)"

This reverts commit 4fd5f3526a.

* llm: fix missing dylibs by restoring old build behavior

* crlf -> lf
2024-07-05 21:48:31 -04:00
Jeffrey Morgan
5304b765b2 llm: put back old include dir (#5507)
* llm: put back old include dir

* llm: update link paths for old submodule commits
2024-07-05 19:34:21 -04:00
Jeffrey Morgan
4fd5f3526a fix cmake build (#5505) 2024-07-05 19:07:01 -04:00
Daniel Hiltgen
842f85f758 Merge pull request #5502 from dhiltgen/ci_fixes
Always go build in CI generate steps
2024-07-05 15:39:11 -07:00
Daniel Hiltgen
9d30f9f8b3 Always go build in CI generate steps
With the recent cgo changes, bugs can sneak through
if we don't make sure to `go build` all the permutations
2024-07-05 15:31:52 -07:00
Blake Mizerany
631cfd9e62 types/model: remove knowledge of digest (#5500)
This was leading to ambiguity and confusion in ollama.com, and is not
used anywhere in ollama at the moment. Once manifests are addressable by
digest, we can add this back in, and in a way that is more tailored to
the concept of addressing a manifest by digest.
2024-07-05 13:42:30 -07:00
Jeffrey Morgan
78fb33dd07 fix typo in cgo directives in llm.go (#5501) 2024-07-05 15:18:36 -04:00
Jeffrey Morgan
8f8e736b13 update llama.cpp submodule to d7fd29f (#5475) 2024-07-05 13:25:58 -04:00
Jeffrey Morgan
d89454de80 Use slot with cached prompt instead of least recently used (#5492)
* Use common prefix to select slot

* actually report `longest`
2024-07-05 12:32:47 -04:00
Daniel Hiltgen
af28b94533 Merge pull request #5469 from dhiltgen/prevent_system_oom
Prevent loading models larger than total memory
2024-07-05 08:22:20 -07:00
Jeffrey Morgan
e9188e971a Fix assert on small embedding inputs (#5491)
* Fix assert on small embedding inputs

* Update llm/patches/09-pooling.diff
2024-07-05 11:20:57 -04:00
Daniel Hiltgen
78eddfc068 Merge pull request #4412 from dhiltgen/win_docs
Document older win10 terminal problems
2024-07-05 08:18:22 -07:00
Daniel Hiltgen
02c24d3d01 Merge pull request #5466 from dhiltgen/fix_clip_unicode
Fix clip model loading with unicode paths
2024-07-05 08:16:58 -07:00
Daniel Hiltgen
52abc8acb7 Document older win10 terminal problems
We haven't found a workaround, so for now recommend updating.
2024-07-03 17:32:14 -07:00
Jeffrey Morgan
4d71c559b2 fix error detection by limiting model loading error parsing (#5472) 2024-07-03 20:04:30 -04:00
Anatoli Babenia
0d16eb310e fix: use envconfig.ModelsDir directly (#4821)
* Co-authored-by: Anatoli Babenia <anatoli@rainforce.org>

Co-authored-by: Maas Lalani <maas@lalani.dev>
2024-07-03 15:36:11 -07:00
Daniel Hiltgen
8072e205ff Merge pull request #5447 from dhiltgen/fix_keepalive
Only set default keep_alive on initial model load
2024-07-03 15:34:38 -07:00
Daniel Hiltgen
955f2a4e03 Only set default keep_alive on initial model load
This change fixes the handling of keep_alive so that if client
request omits the setting, we only set this on initial load.  Once
the model is loaded, if new requests leave this unset, we'll keep
whatever keep_alive was there.
2024-07-03 15:29:56 -07:00
Daniel Hiltgen
3c75113e37 Prevent loading models larger than total memory
Users may not realize the siny new model they're trying to load
fits on their disk, but can't load into system+GPU memory.  Today
we crash, but with this fix, we'll give them a better error message
before even trying to load it.
2024-07-03 14:47:42 -07:00
Daniel Hiltgen
ccd7785859 Merge pull request #5243 from dhiltgen/modelfile_use_mmap
Fix use_mmap for modefiles
2024-07-03 13:59:42 -07:00
royjhan
3b5a4a77f3 Return Correct Prompt Eval Count Regardless of Cache Prompt (#5371)
* openai compatibility

* Revert "openai compatibility"

This reverts commit d3f98a811e.

* remove erroneous subtraction of prompt cache
2024-07-03 13:46:23 -07:00
Daniel Hiltgen
daed0634a9 Merge pull request #5467 from dhiltgen/bogus_cpu_mac_error
Fix corner cases on tmp cleaner on mac
2024-07-03 13:39:36 -07:00
Daniel Hiltgen
0d4dd707bc Merge pull request #5465 from dhiltgen/better_cuda_logging
Better nvidia GPU discovery logging
2024-07-03 13:12:22 -07:00
Daniel Hiltgen
0e982bc1f4 Fix corner cases on tmp cleaner on mac
When ollama is running a long time, tmp cleaners can remove the
runners.  This tightens up a few corner cases on arm macs where
we failed with "server cpu not listed in available servers map[]"
2024-07-03 13:10:14 -07:00
Daniel Hiltgen
6298f49816 Fix clip model loading with unicode paths
On windows, if the model dir contained unicode characters
clip models would fail to load.  This fixes the file name
handling in clip.cpp to support utf16 on windows.
2024-07-03 12:46:36 -07:00
Daniel Hiltgen
ef757da2c9 Better nvidia GPU discovery logging
Refine the way we log GPU discovery to improve the non-debug
output, and report more actionable log messages when possible
to help users troubleshoot on their own.
2024-07-03 10:50:40 -07:00
Michael Yang
e5352297d9 Merge pull request #5448 from ollama/mxyng/fix-generate
use model template by default
2024-07-02 16:48:06 -07:00
Michael Yang
65a5040e09 fix generate template 2024-07-02 16:42:17 -07:00
royjhan
d626b99b54 OpenAI: v1/completions compatibility (#5209)
* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author

Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

* Test name

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Add Middleware for Chat and List

* Completions Endpoint

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* Rename function

* float types

* type cleanup

* cleaning

* more cleaning

* Extra test cases

* merge conflicts

* merge conflicts

* merge conflicts

* merge conflicts

* cleaning

* cleaning

---------

Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-02 16:01:45 -07:00
Michael Yang
dddb58a38b Merge pull request #5051 from ollama/mxyng/capabilities
add model capabilities
2024-07-02 14:26:07 -07:00
Michael Yang
400056e154 Merge pull request #5420 from ollama/mxyng/insecure-path
err on insecure path
2024-07-02 14:03:23 -07:00
Daniel Hiltgen
d2f19024d0 Merge pull request #5442 from dhiltgen/concurrency_docs
Add windows radeon concurrency note
2024-07-02 12:47:47 -07:00
Daniel Hiltgen
69c04eecc4 Add windows radeon concurreny note 2024-07-02 12:46:14 -07:00
royjhan
996bb1b85e OpenAI: /v1/models and /v1/models/{model} compatibility (#5007)
* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author

Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

* Test name

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Add Middleware for Chat and List

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* OpenAI: /v1/models/{model} compatibility (#5028)

* Retrieve Model

* OpenAI Delete Model

* Retrieve Middleware

* Remove Delete from Branch

* Update Test

* Middleware Test File

* Function name

* Cleanup

* Test Update

* Test Update

---------

Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-02 11:50:56 -07:00
Daniel Hiltgen
422dcc3856 Merge pull request #5439 from dhiltgen/fix_centos_7_build
Switch ARM64 container image base to rocky 8
2024-07-02 11:01:15 -07:00
Daniel Hiltgen
020bd60ab2 Switch amd container image base to rocky 8
The centos 7 arm mirrors have disappeared due to the EOL 2 days
ago, and the vault sed workaround which works for x86 doesn't work for arm.
2024-07-02 10:34:47 -07:00
Daniel Hiltgen
8e277b72bb Merge pull request #5438 from dhiltgen/fix_centos_7_build
Centos 7 EOL broke mirrors
2024-07-02 09:28:00 -07:00
Daniel Hiltgen
4f67b39d26 Centos 7 EOL broke mirrors
As of July 1st 2024: Could not resolve host: mirrorlist.centos.org
This is expected due to EOL dates.
2024-07-02 09:22:17 -07:00
Josh
2425281317 Merge pull request #5336 from ollama/jyan/from-errors
fix: trim spaces for FROM argument, don't trim inside of quotes
2024-07-01 16:32:46 -07:00
Josh
0403e9860e Merge pull request #5421 from ollama/jyan/ver
fix: add unsupported architecture message for linux/windows
2024-07-01 16:32:14 -07:00
Josh Yan
33a65e3ba3 error 2024-07-01 16:04:13 -07:00
Michael Yang
88bcd79bb9 err on insecure path 2024-07-01 15:55:59 -07:00
Josh Yan
7e571f95f0 trimspace test case 2024-07-01 11:07:48 -07:00
Michael Yang
da8e2a0447 use kvs to detect embedding models 2024-07-01 10:47:43 -07:00
Michael Yang
a30915bde1 add capabilities 2024-07-01 10:47:43 -07:00
Michael Yang
58e3fff311 rename templates to template 2024-07-01 10:40:54 -07:00
Michael Yang
3f0b309ad4 remove ManifestV2 2024-07-01 10:40:54 -07:00
Josh Yan
26e4e66faf updated parsefile test 2024-07-01 09:43:49 -07:00
Daniel Hiltgen
97c9e11768 Switch use_mmap to a pointer type
This uses nil as undefined for a cleaner implementation.
2024-07-01 08:44:59 -07:00
Josh Yan
9bd00041fa trim all params 2024-06-27 11:18:38 -07:00
Josh Yan
4e986a823c unquote, trimp space 2024-06-27 10:59:15 -07:00
80 changed files with 1820 additions and 947 deletions

View File

@@ -304,6 +304,11 @@ jobs:
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- name: remove unwanted mingw dll.a files
run: |
Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libpthread.dll.a" -File | Remove-Item -Force
Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libwinpthread.dll.a" -File | Remove-Item -Force
Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libstdc++.dll.a" -File | Remove-Item -Force
- uses: actions/setup-go@v5
with:
go-version-file: go.mod

View File

@@ -58,6 +58,7 @@ jobs:
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
@@ -79,6 +80,7 @@ jobs:
- run: go generate -x ./...
if: ${{ ! startsWith(matrix.os, 'windows-') }}
name: 'Unix Go Generate'
- run: go build .
- uses: actions/upload-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries

View File

@@ -70,12 +70,12 @@ RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
FROM --platform=linux/arm64 rockylinux:8 AS cpu-builder-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS

View File

@@ -159,49 +159,18 @@ type Options struct {
// Runner options which must be set when the model is loaded into memory
type Runner struct {
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap TriState `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
type TriState int
const (
TriStateUndefined TriState = -1
TriStateFalse TriState = 0
TriStateTrue TriState = 1
)
func (b *TriState) UnmarshalJSON(data []byte) error {
var v bool
if err := json.Unmarshal(data, &v); err != nil {
return err
}
if v {
*b = TriStateTrue
}
*b = TriStateFalse
return nil
}
func (b *TriState) MarshalJSON() ([]byte, error) {
if *b == TriStateUndefined {
return nil, nil
}
var v bool
if *b == TriStateTrue {
v = true
}
return json.Marshal(v)
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap *bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
// EmbeddingRequest is the request passed to [Client.Embeddings].
@@ -345,6 +314,13 @@ type ProcessModelResponse struct {
SizeVRAM int64 `json:"size_vram"`
}
type RetrieveModelResponse struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
OwnedBy string `json:"owned_by"`
}
type TokenResponse struct {
Token string `json:"token"`
}
@@ -437,19 +413,6 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
continue
}
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
if val {
field.SetInt(int64(TriStateTrue))
} else {
field.SetInt(int64(TriStateFalse))
}
continue
}
switch field.Kind() {
case reflect.Int:
switch t := val.(type) {
@@ -496,6 +459,17 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
field.Set(reflect.ValueOf(&val))
} else {
return fmt.Errorf("unknown type loading config params: %v %v", field.Kind(), field.Type())
}
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
@@ -538,7 +512,7 @@ func DefaultOptions() Options {
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: TriStateUndefined,
UseMMap: nil,
UseNUMA: false,
},
}
@@ -608,19 +582,6 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
} else {
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
if boolVal {
out[key] = TriStateTrue
} else {
out[key] = TriStateFalse
}
continue
}
switch field.Kind() {
case reflect.Float32:
floatVal, err := strconv.ParseFloat(vals[0], 32)
@@ -648,6 +609,17 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
case reflect.Slice:
// TODO: only string slices are supported right now
out[key] = vals
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
out[key] = &boolVal
} else {
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}
default:
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}

View File

@@ -108,25 +108,27 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
}
func TestUseMmapParsingFromJSON(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req string
exp TriState
exp *bool
}{
{
name: "Undefined",
req: `{ }`,
exp: TriStateUndefined,
exp: nil,
},
{
name: "True",
req: `{ "use_mmap": true }`,
exp: TriStateTrue,
exp: &tr,
},
{
name: "False",
req: `{ "use_mmap": false }`,
exp: TriStateFalse,
exp: &fa,
},
}
@@ -144,50 +146,52 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
}
func TestUseMmapFormatParams(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req map[string][]string
exp TriState
exp *bool
err error
}{
{
name: "True",
req: map[string][]string{
"use_mmap": []string{"true"},
"use_mmap": {"true"},
},
exp: TriStateTrue,
exp: &tr,
err: nil,
},
{
name: "False",
req: map[string][]string{
"use_mmap": []string{"false"},
"use_mmap": {"false"},
},
exp: TriStateFalse,
exp: &fa,
err: nil,
},
{
name: "Numeric True",
req: map[string][]string{
"use_mmap": []string{"1"},
"use_mmap": {"1"},
},
exp: TriStateTrue,
exp: &tr,
err: nil,
},
{
name: "Numeric False",
req: map[string][]string{
"use_mmap": []string{"0"},
"use_mmap": {"0"},
},
exp: TriStateFalse,
exp: &fa,
err: nil,
},
{
name: "invalid string",
req: map[string][]string{
"use_mmap": []string{"foo"},
"use_mmap": {"foo"},
},
exp: TriStateUndefined,
exp: nil,
err: fmt.Errorf("invalid bool value [foo]"),
},
}
@@ -195,11 +199,11 @@ func TestUseMmapFormatParams(t *testing.T) {
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
resp, err := FormatParams(test.req)
require.Equal(t, err, test.err)
require.Equal(t, test.err, err)
respVal, ok := resp["use_mmap"]
if test.exp != TriStateUndefined {
if test.exp != nil {
assert.True(t, ok, "resp: %v", resp)
assert.Equal(t, test.exp, respVal)
assert.Equal(t, *test.exp, *respVal.(*bool))
}
})
}

View File

@@ -104,7 +104,7 @@ like to use. For example, to compile an optimized binary for an Intel i9-9880H,
you might use:
```
OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
OLLAMA_CUSTOM_CPU_DEFS="-DGGML_AVX=on -DGGML_AVX2=on -DGGML_F16C=on -DGGML_FMA=on" go generate ./...
go build .
```

View File

@@ -266,8 +266,10 @@ If there is insufficient available memory to load a new model request while one
Parallel request processing for a given model results in increasing the context size by the number of parallel requests. For example, a 2K context with 4 parallel requests will result in an 8K context and additional memory allocation.
The following server settings may be used to adjust how Ollama handles concurrent requests:
The following server settings may be used to adjust how Ollama handles concurrent requests on most platforms:
- `OLLAMA_MAX_LOADED_MODELS` - The maximum number of models that can be loaded concurrently provided they fit in available memory. The default is 3 * the number of GPUs or 3 for CPU inference.
- `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time. The default will auto-select either 4 or 1 based on available memory.
- `OLLAMA_MAX_QUEUE` - The maximum number of requests Ollama will queue when busy before rejecting additional requests. The default is 512
Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting. Once ROCm v6 is available, Windows Radeon will follow the defaults above. You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.

View File

@@ -65,6 +65,7 @@ curl http://localhost:11434/v1/chat/completions \
}
]
}'
```
## Endpoints

View File

@@ -70,14 +70,18 @@ curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.29" sh
If your system is configured with the "noexec" flag where Ollama stores its temporary executable files, you can specify an alternate location by setting OLLAMA_TMPDIR to a location writable by the user ollama runs as. For example OLLAMA_TMPDIR=/usr/share/ollama/
## Container fails to run on NVIDIA GPU
## NVIDIA GPU Discovery
Make sure you've set up the container runtime first as described in [docker.md](./docker.md)
When Ollama starts up, it takes inventory of the GPUs present in the system to determine compatibility and how much VRAM is available. Sometimes this discovery can fail to find your GPUs. In general, running the latest driver will yield the best results.
Sometimes the container runtime can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
### Linux NVIDIA Troubleshooting
- Is the container runtime working? Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
- Is the uvm driver not loaded? `sudo nvidia-modprobe -u`
If you are using a container to run Ollama, make sure you've set up the container runtime first as described in [docker.md](./docker.md)
Sometimes the Ollama can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
- If you are using a container, is the container runtime working? Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
- Is the uvm driver loaded? `sudo nvidia-modprobe -u`
- Try reloading the nvidia_uvm driver - `sudo rmmod nvidia_uvm` then `sudo modprobe nvidia_uvm`
- Try rebooting
- Make sure you're running the latest nvidia drivers
@@ -85,3 +89,8 @@ Sometimes the container runtime can have difficulties initializing the GPU. When
If none of those resolve the problem, gather additional information and file an issue:
- Set `CUDA_ERROR_LEVEL=50` and try again to get more diagnostic logs
- Check dmesg for any errors `sudo dmesg | grep -i nvrm` and `sudo dmesg | grep -i nvidia`
## Windows Terminal Errors
Older versions of Windows 10 (e.g., 21H1) are known to have a bug where the standard terminal program does not display control characters correctly. This can result in a long string of strings like `←[?25h←[?25l` being displayed, sometimes erroring with `The parameter is incorrect` To resolve this problem, please update to Win 10 22H1 or newer.

View File

@@ -19,7 +19,7 @@ Logs will often be helpful in diagnosing the problem (see
## System Requirements
* Windows 10 or newer, Home or Pro
* Windows 10 22H2 or newer, Home or Pro
* NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
* AMD Radeon Driver https://www.amd.com/en/support if you have a Radeon card

View File

@@ -4,12 +4,14 @@ import (
"errors"
"fmt"
"log/slog"
"math"
"net"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"time"
)
type OllamaHost struct {
@@ -34,17 +36,17 @@ var (
// Set via OLLAMA_HOST in the environment
Host *OllamaHost
// Set via OLLAMA_KEEP_ALIVE in the environment
KeepAlive string
KeepAlive time.Duration
// Set via OLLAMA_LLM_LIBRARY in the environment
LLMLibrary string
// Set via OLLAMA_MAX_LOADED_MODELS in the environment
MaxRunners int
// Set via OLLAMA_MAX_QUEUE in the environment
MaxQueuedRequests int
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_MAX_VRAM in the environment
MaxVRAM uint64
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_NOHISTORY in the environment
NoHistory bool
// Set via OLLAMA_NOPRUNE in the environment
@@ -132,6 +134,7 @@ func init() {
NumParallel = 0 // Autoselect
MaxRunners = 0 // Autoselect
MaxQueuedRequests = 512
KeepAlive = 5 * time.Minute
LoadConfig()
}
@@ -266,7 +269,10 @@ func LoadConfig() {
}
}
KeepAlive = clean("OLLAMA_KEEP_ALIVE")
ka := clean("OLLAMA_KEEP_ALIVE")
if ka != "" {
loadKeepAlive(ka)
}
var err error
ModelsDir, err = getModelsDir()
@@ -344,3 +350,24 @@ func getOllamaHost() (*OllamaHost, error) {
Port: port,
}, nil
}
func loadKeepAlive(ka string) {
v, err := strconv.Atoi(ka)
if err != nil {
d, err := time.ParseDuration(ka)
if err == nil {
if d < 0 {
KeepAlive = time.Duration(math.MaxInt64)
} else {
KeepAlive = d
}
}
} else {
d := time.Duration(v) * time.Second
if d < 0 {
KeepAlive = time.Duration(math.MaxInt64)
} else {
KeepAlive = d
}
}
}

View File

@@ -2,8 +2,10 @@ package envconfig
import (
"fmt"
"math"
"net"
"testing"
"time"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
@@ -23,6 +25,21 @@ func TestConfig(t *testing.T) {
t.Setenv("OLLAMA_FLASH_ATTENTION", "1")
LoadConfig()
require.True(t, FlashAttention)
t.Setenv("OLLAMA_KEEP_ALIVE", "")
LoadConfig()
require.Equal(t, 5*time.Minute, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "3")
LoadConfig()
require.Equal(t, 3*time.Second, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "1h")
LoadConfig()
require.Equal(t, 1*time.Hour, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "-1s")
LoadConfig()
require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "-1")
LoadConfig()
require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
}
func TestClientFromEnvironment(t *testing.T) {

View File

@@ -202,7 +202,7 @@ func GetGPUInfo() GpuInfoList {
}()
if !bootstrapped {
slog.Debug("Detecting GPUs")
slog.Info("looking for compatible GPUs")
needRefresh = false
cpuCapability = GetCPUCapability()
var memInfo C.mem_info_t
@@ -320,6 +320,9 @@ func GetGPUInfo() GpuInfoList {
rocmGPUs = AMDGetGPUInfo()
bootstrapped = true
if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
slog.Info("no compatible GPUs were discovered")
}
}
// For detected GPUs, load library if not loaded
@@ -514,7 +517,23 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
defer C.free(unsafe.Pointer(lib))
C.nvcuda_init(lib, &resp)
if resp.err != nil {
slog.Debug("Unable to load nvcuda", "library", libPath, "error", C.GoString(resp.err))
// Decide what log level based on the type of error message to help users understand why
msg := C.GoString(resp.err)
switch resp.cudaErr {
case C.CUDA_ERROR_INSUFFICIENT_DRIVER, C.CUDA_ERROR_SYSTEM_DRIVER_MISMATCH:
slog.Warn("version mismatch between driver and cuda driver library - reboot or upgrade may be required", "library", libPath, "error", msg)
case C.CUDA_ERROR_NO_DEVICE:
slog.Info("no nvidia devices detected", "library", libPath)
case C.CUDA_ERROR_UNKNOWN:
slog.Warn("unknown error initializing cuda driver library", "library", libPath, "error", msg)
slog.Warn("see https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for more information")
default:
if strings.Contains(msg, "wrong ELF class") {
slog.Debug("skipping 32bit library", "library", libPath)
} else {
slog.Info("unable to load cuda driver library", "library", libPath, "error", msg)
}
}
C.free(unsafe.Pointer(resp.err))
} else {
return int(resp.num_devices), &resp.ch, libPath

View File

@@ -56,7 +56,7 @@ func GetCPUInfo() GpuInfoList {
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),
FreeMemory: 0,
FreeMemory: uint64(C.getFreeMemory()),
}, nil
}

View File

@@ -2,3 +2,4 @@
#include <stdint.h>
uint64_t getRecommendedMaxVRAM();
uint64_t getPhysicalMemory();
uint64_t getFreeMemory();

View File

@@ -1,4 +1,5 @@
// go:build darwin
#import <Foundation/Foundation.h>
#import <mach/mach.h>
#include "gpu_info_darwin.h"
uint64_t getRecommendedMaxVRAM() {
@@ -8,6 +9,27 @@ uint64_t getRecommendedMaxVRAM() {
return result;
}
// getPhysicalMemory returns the total physical memory in bytes
uint64_t getPhysicalMemory() {
return [[NSProcessInfo processInfo] physicalMemory];
return [NSProcessInfo processInfo].physicalMemory;
}
// getFreeMemory returns the total free memory in bytes, including inactive
// memory that can be reclaimed by the system.
uint64_t getFreeMemory() {
mach_port_t host_port = mach_host_self();
mach_msg_type_number_t host_size = sizeof(vm_statistics64_data_t) / sizeof(integer_t);
vm_size_t pagesize;
vm_statistics64_data_t vm_stat;
host_page_size(host_port, &pagesize);
if (host_statistics64(host_port, HOST_VM_INFO64, (host_info64_t)&vm_stat, &host_size) != KERN_SUCCESS) {
return 0;
}
uint64_t free_memory = (uint64_t)vm_stat.free_count * pagesize;
free_memory += (uint64_t)vm_stat.speculative_count * pagesize;
free_memory += (uint64_t)vm_stat.inactive_count * pagesize;
return free_memory;
}

View File

@@ -7,6 +7,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
CUresult ret;
resp->err = NULL;
resp->num_devices = 0;
resp->cudaErr = CUDA_SUCCESS;
const int buflen = 256;
char buf[buflen + 1];
int i;
@@ -38,6 +39,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
nvcuda_lib_path, msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
@@ -52,6 +54,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
}
@@ -61,12 +64,9 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
resp->err = strdup("your nvidia driver is too old or missing. If you have a CUDA GPU please upgrade to run ollama");
return;
}
snprintf(buf, buflen, "nvcuda init failure: %d", ret);
snprintf(buf, buflen, "cuda driver library init failure: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
@@ -91,6 +91,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
resp->ch.handle = NULL;
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
}
@@ -106,13 +107,13 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
CUuuid uuid = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
if (h.handle == NULL) {
resp->err = strdup("nvcuda handle isn't initialized");
resp->err = strdup("cuda driver library handle isn't initialized");
return;
}
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda device failed to initialize");
snprintf(buf, buflen, "cuda driver library device failed to initialize");
resp->err = strdup(buf);
return;
}
@@ -168,14 +169,14 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda failed to get device context %d", ret);
snprintf(buf, buflen, "cuda driver library failed to get device context %d", ret);
resp->err = strdup(buf);
return;
}
ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda device memory info lookup failure %d", ret);
snprintf(buf, buflen, "cuda driver library device memory info lookup failure %d", ret);
resp->err = strdup(buf);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
@@ -193,7 +194,7 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
@@ -206,7 +207,7 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device failed to initialize");
LOG(1, "cuda driver library device failed to initialize");
return;
}
@@ -214,13 +215,13 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to get device context %d", ret);
LOG(1, "cuda driver library failed to get device context %d", ret);
return;
}
ret = (*h.cuMemGetInfo_v2)(free, total);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device memory info lookup failure %d", ret);
LOG(1, "cuda driver library device memory info lookup failure %d", ret);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
@@ -228,12 +229,12 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
void nvcuda_release(nvcuda_handle_t h) {
LOG(h.verbose, "releasing nvcuda library\n");
LOG(h.verbose, "releasing cuda driver library\n");
UNLOAD_LIBRARY(h.handle);
// TODO and other context release logic?
h.handle = NULL;

View File

@@ -7,9 +7,12 @@
typedef enum cudaError_enum {
CUDA_SUCCESS = 0,
CUDA_ERROR_INVALID_VALUE = 1,
CUDA_ERROR_MEMORY_ALLOCATION = 2,
CUDA_ERROR_OUT_OF_MEMORY = 2,
CUDA_ERROR_NOT_INITIALIZED = 3,
CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
CUDA_ERROR_NO_DEVICE = 100,
CUDA_ERROR_SYSTEM_DRIVER_MISMATCH = 803,
CUDA_ERROR_UNKNOWN = 999,
// Other values omitted for now...
} CUresult;
@@ -64,6 +67,7 @@ typedef struct nvcuda_init_resp {
char *err; // If err is non-null handle is invalid
nvcuda_handle_t ch;
int num_devices;
CUresult cudaErr;
} nvcuda_init_resp_t;
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);

View File

@@ -1,14 +1,13 @@
set(TARGET ollama_llama_server)
option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
install(TARGETS ${TARGET} RUNTIME)
target_compile_definitions(${TARGET} PRIVATE
SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
)
target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
set(TARGET ollama_llama_server)
option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
install(TARGETS ${TARGET} RUNTIME)
target_compile_definitions(${TARGET} PRIVATE
SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
)
target_link_libraries(${TARGET} PRIVATE ggml llama common llava ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
target_compile_features(${TARGET} PRIVATE cxx_std_11)

View File

@@ -1382,12 +1382,50 @@ struct llama_server_context
}
}
std::string common_prefix(const std::string& str1, const std::string& str2) {
auto mismatch_pair = std::mismatch(str1.begin(), str1.end(), str2.begin());
return std::string(str1.begin(), mismatch_pair.first);
}
// Find the slot that has the greatest common prefix
server_slot *prefix_slot(const json &prompt) {
if (!prompt.is_string()) {
return nullptr;
}
std::string prompt_str = prompt.get<std::string>();
server_slot *slot = nullptr;
size_t longest = 0;
for (server_slot &s : slots) {
if (s.available() && s.prompt.is_string()) {
std::string s_prompt = s.prompt.get<std::string>();
std::string prefix = common_prefix(s_prompt, prompt_str);
if (prefix.size() > longest) {
slot = &s;
longest = prefix.size();
}
}
}
if (!slot) {
return get_slot(-1);
}
LOG_DEBUG("slot with common prefix found", {{
"slot_id", slot->id,
"characters", longest
}});
return slot;
}
void process_single_task(task_server& task)
{
switch (task.type)
{
case TASK_TYPE_COMPLETION: {
server_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
server_slot *slot = prefix_slot(task.data["prompt"]);
if (slot == nullptr)
{
// if no slot is available, we defer this task for processing later
@@ -1650,22 +1688,8 @@ struct llama_server_context
}
slot.params.n_keep = std::min(slot.n_ctx - 4, slot.params.n_keep);
char buf[256];
llama_model_meta_val_str(model, "general.architecture", buf, 256);
bool gemma2 = strcmp(buf, "gemma2") == 0;
int32_t truncate_at = slot.n_ctx;
// truncate at 2/3 of the context length for gemma2 models
// as they do not support context shifts (from the sliding window implementation).
// this way, prompts that almost fit the context length can still generate a full
// response without a sudden stop from hitting the context limit
if (gemma2) {
truncate_at = 2 * slot.n_ctx / 3;
}
// if input prompt is too big, truncate it, if group attention self-extend is disabled
if (slot.ga_n == 1 && slot.n_prompt_tokens >= truncate_at)
if (slot.ga_n == 1 && slot.n_prompt_tokens >= slot.n_ctx)
{
const int n_left = slot.n_ctx - slot.params.n_keep;
const int n_shift = n_left / 2;
@@ -1693,19 +1717,6 @@ struct llama_server_context
GGML_ASSERT(slot.n_prompt_tokens < slot.n_ctx);
}
// Models with sliding window attention do not work with context shifts, so
// limit their prediction to the context length
if (gemma2) {
int32_t limit = slot.n_ctx - slot.n_prompt_tokens;
slot.n_predict = limit;
slot.params.n_predict = limit;
LOG_INFO("model does not support sliding window, limiting generation", {
{"n_ctx", slot.n_ctx},
{"n_prompt_tokens", slot.n_prompt_tokens},
{"n_predict", slot.n_predict}
});
}
if (!slot.params.cache_prompt)
{
llama_sampling_reset(slot.ctx_sampling);
@@ -1732,7 +1743,7 @@ struct llama_server_context
slot.n_past -= 1;
}
slot.n_prompt_tokens_processed = slot.n_prompt_tokens - slot.n_past;
slot.n_prompt_tokens_processed = slot.n_prompt_tokens;
if (slot.ga_n != 1)
{

View File

@@ -18,16 +18,16 @@ sign() {
fi
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_OPENMP=off"
COMMON_DARWIN_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DGGML_METAL_EMBED_LIBRARY=on -DGGML_OPENMP=off"
case "${GOARCH}" in
"amd64")
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_NATIVE=off"
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DGGML_METAL=off -DGGML_NATIVE=off"
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_BLAS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_BLAS=off -DGGML_ACCELERATE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
@@ -37,7 +37,7 @@ case "${GOARCH}" in
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
@@ -49,7 +49,7 @@ case "${GOARCH}" in
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
@@ -61,7 +61,7 @@ case "${GOARCH}" in
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=on -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
@@ -75,14 +75,14 @@ case "${GOARCH}" in
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_BLAS=off -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
if [ -z "$OLLAMA_SKIP_METAL_GENERATE" ]; then
init_vars
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
build

View File

@@ -51,7 +51,7 @@ if [ -z "${CUDACXX}" ]; then
export CUDACXX=$(command -v nvcc)
fi
fi
COMMON_CMAKE_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off"
COMMON_CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off"
source $(dirname $0)/gen_common.sh
init_vars
git_module_setup
@@ -64,7 +64,7 @@ if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ];
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off ${CMAKE_DEFS}"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DGGML_NATIVE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}_static"
echo "Building static library"
build
@@ -77,29 +77,29 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
init_vars
echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building custom CPU"
build
compress
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# Note: the following seem to yield slower results than AVX2 - ymmv
# -DLLAMA_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
# -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_OPENMP=off"
COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off"
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
@@ -116,7 +116,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
@@ -129,7 +129,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
@@ -170,15 +170,15 @@ if [ -z "${OLLAMA_SKIP_CUDA_GENERATE}" -a -d "${CUDA_LIB_DIR}" ]; then
#
# CUDA compute < 6.0 lacks proper FP16 support on ARM.
# Disabling has minimal performance effect while maintaining compatibility.
ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_CUDA_F16=off"
ARM64_DEFS="-DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_CUDA_F16=off"
fi
# Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
if [ -n "${OLLAMA_CUSTOM_CUDA_DEFS}" ]; then
echo "OLLAMA_CUSTOM_CUDA_DEFS=\"${OLLAMA_CUSTOM_CUDA_DEFS}\""
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
echo "Building custom CUDA GPU"
else
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DGGML_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} -DCMAKE_LIBRARY_PATH=/usr/local/cuda/compat"
fi
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
@@ -216,7 +216,7 @@ if [ -z "${OLLAMA_SKIP_ONEAPI_GENERATE}" -a -d "${ONEAPI_ROOT}" ]; then
init_vars
source ${ONEAPI_ROOT}/setvars.sh --force # set up environment variables for oneAPI
CC=icx
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL=ON -DLLAMA_SYCL_F16=OFF"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF"
BUILD_DIR="../build/linux/${ARCH}/oneapi"
EXTRA_LIBS="-fsycl -Wl,-rpath,${ONEAPI_ROOT}/compiler/latest/lib,-rpath,${ONEAPI_ROOT}/mkl/latest/lib,-rpath,${ONEAPI_ROOT}/tbb/latest/lib,-rpath,${ONEAPI_ROOT}/compiler/latest/opt/oclfpga/linux64/lib -lOpenCL -lmkl_core -lmkl_sycl_blas -lmkl_intel_ilp64 -lmkl_tbb_thread -ltbb"
DEBUG_FLAGS="" # icx compiles with -O0 if we pass -g, so we must remove it
@@ -254,7 +254,7 @@ if [ -z "${OLLAMA_SKIP_ROCM_GENERATE}" -a -d "${ROCM_PATH}" ]; then
ROCM_VARIANT=_v$(ls ${ROCM_PATH}/lib/librocblas.so.*.*.????? | cut -f5 -d. || true)
fi
init_vars
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
# Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
if [ -n "${OLLAMA_CUSTOM_ROCM_DEFS}" ]; then
echo "OLLAMA_CUSTOM_ROCM_DEFS=\"${OLLAMA_CUSTOM_ROCM_DEFS}\""

View File

@@ -39,8 +39,8 @@ function init_vars {
}
$script:cmakeDefs = @(
"-DBUILD_SHARED_LIBS=on",
"-DLLAMA_NATIVE=off",
"-DLLAMA_OPENMP=off"
"-DGGML_NATIVE=off",
"-DGGML_OPENMP=off"
)
$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
$script:ARCH = $Env:PROCESSOR_ARCHITECTURE.ToLower()
@@ -182,9 +182,9 @@ function cleanup {
}
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
function build_static() {
@@ -204,13 +204,13 @@ function build_static() {
"-DCMAKE_C_COMPILER=gcc.exe",
"-DCMAKE_CXX_COMPILER=g++.exe",
"-DBUILD_SHARED_LIBS=off",
"-DLLAMA_NATIVE=off",
"-DLLAMA_AVX=off",
"-DLLAMA_AVX2=off",
"-DLLAMA_AVX512=off",
"-DLLAMA_F16C=off",
"-DLLAMA_FMA=off",
"-DLLAMA_OPENMP=off")
"-DGGML_NATIVE=off",
"-DGGML_AVX=off",
"-DGGML_AVX2=off",
"-DGGML_AVX512=off",
"-DGGML_F16C=off",
"-DGGML_FMA=off",
"-DGGML_OPENMP=off")
$script:buildDir="../build/windows/${script:ARCH}_static"
write-host "Building static library"
build
@@ -224,7 +224,7 @@ function build_cpu($gen_arch) {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu"))) {
# remaining llama.cpp builds use MSVC
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DGGML_AVX=off", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu"
$script:distDir="$script:DIST_BASE\cpu"
write-host "Building LCD CPU"
@@ -239,7 +239,7 @@ function build_cpu($gen_arch) {
function build_cpu_avx() {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx"))) {
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
$script:distDir="$script:DIST_BASE\cpu_avx"
write-host "Building AVX CPU"
@@ -254,7 +254,7 @@ function build_cpu_avx() {
function build_cpu_avx2() {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx2"))) {
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=on", "-DGGML_AVX512=off", "-DGGML_FMA=on", "-DGGML_F16C=on") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
$script:distDir="$script:DIST_BASE\cpu_avx2"
write-host "Building AVX2 CPU"
@@ -279,9 +279,9 @@ function build_cuda() {
$script:distDir="$script:DIST_BASE\cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @(
"-A", "x64",
"-DLLAMA_CUDA=ON",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DGGML_CUDA=ON",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR",
"-DCMAKE_CUDA_FLAGS=-t8",
"-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}"
@@ -319,7 +319,7 @@ function build_oneapi() {
$script:distDir ="$script:DIST_BASE\oneapi$script:ONEAPI_VARIANT"
$script:cmakeDefs += @(
"-G", "MinGW Makefiles",
"-DLLAMA_SYCL=ON",
"-DGGML_SYCL=ON",
"-DCMAKE_C_COMPILER=icx",
"-DCMAKE_CXX_COMPILER=icx",
"-DCMAKE_BUILD_TYPE=Release"
@@ -365,10 +365,10 @@ function build_rocm() {
"-G", "Ninja",
"-DCMAKE_C_COMPILER=clang.exe",
"-DCMAKE_CXX_COMPILER=clang++.exe",
"-DLLAMA_HIPBLAS=on",
"-DGGML_HIPBLAS=on",
"-DHIP_PLATFORM=amd",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DCMAKE_POSITION_INDEPENDENT_CODE=on",
"-DAMDGPU_TARGETS=$(amdGPUs)",
"-DGPU_TARGETS=$(amdGPUs)"

View File

@@ -1,12 +1,13 @@
package llm
// #cgo CFLAGS: -Illama.cpp
// #cgo darwin,arm64 LDFLAGS: ${SRCDIR}/build/darwin/arm64_static/libllama.a -lstdc++
// #cgo darwin,amd64 LDFLAGS: ${SRCDIR}/build/darwin/x86_64_static/libllama.a -lstdc++
// #cgo windows,amd64 LDFLAGS: ${SRCDIR}/build/windows/amd64_static/libllama.a -static -lstdc++
// #cgo windows,arm64 LDFLAGS: ${SRCDIR}/build/windows/arm64_static/libllama.a -static -lstdc++
// #cgo linux,amd64 LDFLAGS: ${SRCDIR}/build/linux/x86_64_static/libllama.a -lstdc++
// #cgo linux,arm64 LDFLAGS: ${SRCDIR}/build/linux/arm64_static/libllama.a -lstdc++
// #cgo CFLAGS: -Illama.cpp -Illama.cpp/include -Illama.cpp/ggml/include
// #cgo LDFLAGS: -lllama -lggml -lstdc++ -lpthread
// #cgo darwin,arm64 LDFLAGS: -L${SRCDIR}/build/darwin/arm64_static -L${SRCDIR}/build/darwin/arm64_static/src -L${SRCDIR}/build/darwin/arm64_static/ggml/src -framework Accelerate -framework Metal
// #cgo darwin,amd64 LDFLAGS: -L${SRCDIR}/build/darwin/x86_64_static -L${SRCDIR}/build/darwin/x86_64_static/src -L${SRCDIR}/build/darwin/x86_64_static/ggml/src
// #cgo windows,amd64 LDFLAGS: -L${SRCDIR}/build/windows/amd64_static -L${SRCDIR}/build/windows/amd64_static/src -L${SRCDIR}/build/windows/amd64_static/ggml/src
// #cgo windows,arm64 LDFLAGS: -L${SRCDIR}/build/windows/arm64_static -L${SRCDIR}/build/windows/arm64_static/src -L${SRCDIR}/build/windows/arm64_static/ggml/src
// #cgo linux,amd64 LDFLAGS: -L${SRCDIR}/build/linux/x86_64_static -L${SRCDIR}/build/linux/x86_64_static/src -L${SRCDIR}/build/linux/x86_64_static/ggml/src
// #cgo linux,arm64 LDFLAGS: -L${SRCDIR}/build/linux/arm64_static -L${SRCDIR}/build/linux/arm64_static/src -L${SRCDIR}/build/linux/arm64_static/ggml/src
// #include <stdlib.h>
// #include "llama.h"
import "C"

View File

@@ -1,8 +1,8 @@
diff --git a/common/common.cpp b/common/common.cpp
index 73ff0e85..6adb1a92 100644
index 2c05a4d4..927f0e3d 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2447,6 +2447,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
@@ -2093,6 +2093,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
mparams.use_mmap = params.use_mmap;
mparams.use_mlock = params.use_mlock;
mparams.check_tensors = params.check_tensors;
@@ -12,10 +12,10 @@ index 73ff0e85..6adb1a92 100644
mparams.kv_overrides = NULL;
} else {
diff --git a/common/common.h b/common/common.h
index 58ed72f4..0bb2605e 100644
index 65c0ef81..ebca2c77 100644
--- a/common/common.h
+++ b/common/common.h
@@ -180,6 +180,13 @@ struct gpt_params {
@@ -184,6 +184,13 @@ struct gpt_params {
std::string mmproj = ""; // path to multimodal projector
std::vector<std::string> image; // path to image file(s)
@@ -26,6 +26,6 @@ index 58ed72f4..0bb2605e 100644
+ // context pointer passed to the progress callback
+ void * progress_callback_user_data;
+
// server params
int32_t port = 8080; // server listens on this network port
int32_t timeout_read = 600; // http read timeout in seconds
// embedding
bool embedding = false; // get only sentence embedding
int32_t embd_normalize = 2; // normalisation for embendings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)

View File

@@ -1,17 +1,8 @@
From 544a2d2e646d39e878d87dfbb3398a356bc560ab Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 23 May 2024 11:18:45 -0700
Subject: [PATCH] throw exception on load errors
---
llama.cpp | 25 ++++++++++++++++---------
1 file changed, 16 insertions(+), 9 deletions(-)
diff --git a/llama.cpp b/llama.cpp
index 15c66077..8ba90b6a 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -6346,7 +6346,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
diff --git a/src/llama.cpp b/src/llama.cpp
index 73f52435..58a00fb1 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -7241,7 +7241,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
}
} catch (const std::exception & err) {
LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
@@ -20,7 +11,7 @@ index 15c66077..8ba90b6a 100644
}
return 0;
@@ -15600,16 +15600,23 @@ struct llama_model * llama_load_model_from_file(
@@ -17564,16 +17564,23 @@ struct llama_model * llama_load_model_from_file(
}
model->rpc_servers.push_back(servers);
}
@@ -52,6 +43,3 @@ index 15c66077..8ba90b6a 100644
}
return model;
--
2.45.1

View File

@@ -1,7 +1,7 @@
diff --git a/ggml-metal.m b/ggml-metal.m
diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m
index 0207b787..b5e9884b 100644
--- a/ggml-metal.m
+++ b/ggml-metal.m
--- a/ggml/src/ggml-metal.m
+++ b/ggml/src/ggml-metal.m
@@ -1396,27 +1396,23 @@ static enum ggml_status ggml_metal_graph_compute(
// to the matrix-vector kernel
int ne11_mm_min = 1;

View File

@@ -1,11 +1,11 @@
diff --git a/llama.cpp b/llama.cpp
index 61948751..4b72a293 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -4824,16 +4824,7 @@ static void llm_load_vocab(
// for now, only BPE models have pre-tokenizers
diff --git a/src/llama.cpp b/src/llama.cpp
index 2b9ace28..172640e2 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5357,16 +5357,7 @@ static void llm_load_vocab(
if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
vocab.tokenizer_add_space_prefix = false;
vocab.tokenizer_clean_spaces = true;
- if (tokenizer_pre.empty()) {
- LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
- LLAMA_LOG_WARN("%s: \n", __func__);
@@ -20,13 +20,13 @@ index 61948751..4b72a293 100644
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
} else if (
tokenizer_pre == "llama3" ||
@@ -4888,7 +4879,8 @@ static void llm_load_vocab(
tokenizer_pre == "poro-chat") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
@@ -5439,7 +5430,8 @@ static void llm_load_vocab(
tokenizer_pre == "jais") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
} else {
- throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
+ LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
+ vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
}
} else {
} else if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;

View File

@@ -1,7 +1,7 @@
diff --git a/llama.cpp b/llama.cpp
diff --git a/src/llama.cpp b/src/llama.cpp
index 40d2ec2c..f34eb79a 100644
--- a/llama.cpp
+++ b/llama.cpp
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -6943,7 +6943,7 @@ static struct ggml_tensor * llm_build_kqv(
struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
cb(kq, "kq", il);

View File

@@ -0,0 +1,45 @@
diff --git a/src/llama.cpp b/src/llama.cpp
index 1fe2b9f7..a43312a7 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -13689,7 +13689,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
const auto n_embd = hparams.n_embd;
// TODO: use a per-batch flag for logits presence instead
- const bool has_logits = !cparams.embeddings;
+ const bool has_logits = cparams.causal_attn;
const bool has_embd = lctx.is_encoding || (cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE));
const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
@@ -13959,17 +13959,25 @@ static int llama_decode_internal(
// no output
res = nullptr;
embd = nullptr;
- } else if (cparams.embeddings) {
- res = nullptr; // do not extract logits for embedding case
- embd = gf->nodes[gf->n_nodes - 1];
- if (strcmp(embd->name, "result_embd_pooled") != 0) {
- embd = gf->nodes[gf->n_nodes - 2];
+ }
+
+ if (cparams.embeddings) {
+ for (int i = gf->n_nodes - 1; i >= 0; --i) {
+ embd = gf->nodes[i];
+ if (strcmp(embd->name, "result_embd_pooled") == 0) {
+ break;
+ }
}
GGML_ASSERT(strcmp(embd->name, "result_embd_pooled") == 0 && "missing embeddings tensor");
- } else {
+ } else {
embd = nullptr; // do not extract embeddings when not needed
GGML_ASSERT(strcmp(res->name, "result_output") == 0 && "missing result_output tensor");
}
+
+ if (!cparams.causal_attn) {
+ res = nullptr; // do not extract logits when not needed
+ }
+
// LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
ggml_backend_sched_alloc_graph(lctx.sched, gf);

View File

@@ -1,305 +0,0 @@
From 5cadb45f39d001ffbad95b690d6cf0abcb4a6d96 Mon Sep 17 00:00:00 2001
From: Ollama maintainers <hello@ollama.com>
Date: Wed, 26 Jun 2024 16:18:09 -0700
Subject: [PATCH] Architecture support
---
llama.cpp | 194 +++++++++++++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 193 insertions(+), 1 deletion(-)
diff --git a/llama.cpp b/llama.cpp
index 61948751..3b4196f5 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -217,6 +217,7 @@ enum llm_arch {
LLM_ARCH_INTERNLM2,
LLM_ARCH_MINICPM,
LLM_ARCH_GEMMA,
+ LLM_ARCH_GEMMA2,
LLM_ARCH_STARCODER2,
LLM_ARCH_MAMBA,
LLM_ARCH_XVERSE,
@@ -255,6 +256,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_INTERNLM2, "internlm2" },
{ LLM_ARCH_MINICPM, "minicpm" },
{ LLM_ARCH_GEMMA, "gemma" },
+ { LLM_ARCH_GEMMA2, "gemma2" },
{ LLM_ARCH_STARCODER2, "starcoder2" },
{ LLM_ARCH_MAMBA, "mamba" },
{ LLM_ARCH_XVERSE, "xverse" },
@@ -464,10 +466,12 @@ enum llm_tensor {
LLM_TENSOR_ATTN_NORM,
LLM_TENSOR_ATTN_NORM_2,
LLM_TENSOR_ATTN_OUT_NORM,
+ LLM_TENSOR_ATTN_POST_NORM,
LLM_TENSOR_ATTN_ROT_EMBD,
LLM_TENSOR_FFN_GATE_INP,
LLM_TENSOR_FFN_GATE_INP_SHEXP,
LLM_TENSOR_FFN_NORM,
+ LLM_TENSOR_FFN_POST_NORM,
LLM_TENSOR_FFN_GATE,
LLM_TENSOR_FFN_DOWN,
LLM_TENSOR_FFN_UP,
@@ -960,6 +964,24 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
},
},
+ {
+ LLM_ARCH_GEMMA2,
+ {
+ { LLM_TENSOR_TOKEN_EMBD, "token_embd" },
+ { LLM_TENSOR_OUTPUT_NORM, "output_norm" },
+ { LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
+ { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },
+ { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },
+ { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },
+ { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },
+ { LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" },
+ { LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
+ { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },
+ { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },
+ { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
+ { LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" },
+ },
+ },
{
LLM_ARCH_STARCODER2,
{
@@ -1941,6 +1963,8 @@ enum e_model {
MODEL_8x22B,
MODEL_16x12B,
MODEL_10B_128x3_66B,
+ MODEL_9B,
+ MODEL_27B,
};
static const size_t kiB = 1024;
@@ -2114,6 +2138,7 @@ struct llama_layer {
struct ggml_tensor * attn_out_norm_b;
struct ggml_tensor * attn_q_a_norm;
struct ggml_tensor * attn_kv_a_norm;
+ struct ggml_tensor * attn_post_norm;
// attention
struct ggml_tensor * wq;
@@ -2136,6 +2161,7 @@ struct llama_layer {
// normalization
struct ggml_tensor * ffn_norm;
struct ggml_tensor * ffn_norm_b;
+ struct ggml_tensor * ffn_post_norm;
struct ggml_tensor * layer_out_norm;
struct ggml_tensor * layer_out_norm_b;
struct ggml_tensor * ffn_norm_exps;
@@ -4529,6 +4555,16 @@ static void llm_load_hparams(
}
} break;
case LLM_ARCH_GEMMA:
+ {
+ ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+ switch (hparams.n_layer) {
+ case 18: model.type = e_model::MODEL_9B; break;
+ case 28: model.type = e_model::MODEL_27B; break;
+ default: model.type = e_model::MODEL_UNKNOWN;
+ }
+ } break;
+ case LLM_ARCH_GEMMA2:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -6305,6 +6341,40 @@ static bool llm_load_tensors(
layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
}
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+ // output
+ model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+ model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
+
+ const int64_t n_ff = hparams.n_ff;
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+ const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
+ const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
+
+ for (uint32_t i = 0; i < n_layer; ++i) {
+ ggml_context * ctx_layer = ctx_for_layer(i);
+ ggml_context * ctx_split = ctx_for_layer_split(i);
+
+ auto & layer = model.layers[i];
+
+ layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+ layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+ layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_k_gqa});
+ layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_v_gqa});
+ layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+ layer.attn_post_norm = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
+
+ layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+ layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
+ layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff});
+ layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
+ layer.ffn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd});
+ }
+ } break;
case LLM_ARCH_STARCODER2:
{
model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
@@ -10614,6 +10684,123 @@ struct llm_build_context {
return gf;
}
+ struct ggml_cgraph * build_gemma2() {
+ struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+
+ struct ggml_tensor * cur;
+ struct ggml_tensor * inpL;
+
+ inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+ inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
+ cb(inpL, "inp_scaled", -1);
+
+ // inp_pos - contains the positions
+ struct ggml_tensor * inp_pos = build_inp_pos();
+
+ // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+ struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+ for (int il = 0; il < n_layer; ++il) {
+ // norm
+ cur = llm_build_norm(ctx0, inpL, hparams,
+ model.layers[il].attn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_norm", il);
+
+ // self-attention
+ {
+ // compute Q and K and RoPE them
+ struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+ cb(Qcur, "Qcur", il);
+
+ struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+ cb(Kcur, "Kcur", il);
+
+ struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+ cb(Vcur, "Vcur", il);
+
+ Qcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Qcur, "Qcur", il);
+
+ Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
+ cb(Qcur, "Qcur_scaled", il);
+
+ Kcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Kcur, "Kcur", il);
+
+ cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+ model.layers[il].wo, NULL,
+ Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
+ }
+
+ if (il == n_layer - 1) {
+ // skip computing output for unused tokens
+ struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+ cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+ inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].attn_post_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_post_norm", il);
+
+ struct ggml_tensor * sa_out = ggml_add(ctx0, cur, inpL);
+ cb(sa_out, "sa_out", il);
+
+ cur = llm_build_norm(ctx0, sa_out, hparams,
+ model.layers[il].ffn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "ffn_norm", il);
+
+ // feed-forward network
+ {
+ cur = llm_build_ffn(ctx0, cur,
+ model.layers[il].ffn_up, NULL,
+ model.layers[il].ffn_gate, NULL,
+ model.layers[il].ffn_down, NULL,
+ NULL,
+ LLM_FFN_GELU, LLM_FFN_PAR, cb, il);
+ cb(cur, "ffn_out", il);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].ffn_post_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "ffn_post_norm", -1);
+
+ cur = ggml_add(ctx0, cur, sa_out);
+ cb(cur, "l_out", il);
+
+ // input for next layer
+ inpL = cur;
+ }
+
+ cur = inpL;
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.output_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "result_norm", -1);
+
+ // lm_head
+ cur = ggml_mul_mat(ctx0, model.output, cur);
+ cb(cur, "result_output", -1);
+
+ ggml_build_forward_expand(gf, cur);
+
+ return gf;
+ }
+
struct ggml_cgraph * build_starcoder2() {
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
@@ -11847,6 +12034,10 @@ static struct ggml_cgraph * llama_build_graph(
{
result = llm.build_gemma();
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ result = llm.build_gemma2();
+ } break;
case LLM_ARCH_STARCODER2:
{
result = llm.build_starcoder2();
@@ -16671,6 +16862,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
case LLM_ARCH_PHI2:
case LLM_ARCH_PHI3:
case LLM_ARCH_GEMMA:
+ case LLM_ARCH_GEMMA2:
case LLM_ARCH_STARCODER2:
case LLM_ARCH_GPTNEOX:
return LLAMA_ROPE_TYPE_NEOX;
@@ -18551,7 +18743,7 @@ static int32_t llama_chat_apply_template_internal(
if (add_ass) {
ss << "<s>assistant\n";
}
- } else if (tmpl == "gemma" || tmpl.find("<start_of_turn>") != std::string::npos) {
+ } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl.find("<start_of_turn>") != std::string::npos) {
// google/gemma-7b-it
std::string system_prompt = "";
for (auto message : chat) {
--
2.45.2

View File

@@ -0,0 +1,42 @@
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index 95fbe3d0..5a02a6ec 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -32,6 +33,14 @@
#include <cinttypes>
#include <limits>
+#if defined(_WIN32)
+#define WIN32_LEAN_AND_MEAN
+#ifndef NOMINMAX
+ #define NOMINMAX
+#endif
+#include <windows.h>
+#endif
+
//#define CLIP_DEBUG_FUNCTIONS
// RGB uint8 image
@@ -1055,7 +1064,22 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
return nullptr;
}
+#ifdef _WIN32
+ int wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, NULL, 0);
+ if (!wlen) {
+ return NULL;
+ }
+ wchar_t * wbuf = (wchar_t *) malloc(wlen * sizeof(wchar_t));
+ wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, wbuf, wlen);
+ if (!wlen) {
+ free(wbuf);
+ return NULL;
+ }
+ auto fin = std::ifstream(wbuf, std::ios::binary);
+ free(wbuf);
+#else
auto fin = std::ifstream(fname, std::ios::binary);
+#endif
if (!fin) {
LOG_TEE("cannot open model file for loading tensors\n");
clip_free(new_clip);

View File

@@ -0,0 +1,60 @@
diff --git a/src/llama.cpp b/src/llama.cpp
index 721b8f4e..cfe7ac40 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -8420,14 +8420,14 @@ struct llm_build_context {
}
struct ggml_tensor * build_inp_mean() {
- lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, n_tokens);
+ lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, cparams.n_seq_max);
cb(lctx.inp_mean, "inp_mean", -1);
ggml_set_input(lctx.inp_mean);
return lctx.inp_mean;
}
struct ggml_tensor * build_inp_cls() {
- lctx.inp_cls = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_tokens);
+ lctx.inp_cls = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, cparams.n_seq_max);
cb(lctx.inp_cls, "inp_cls", -1);
ggml_set_input(lctx.inp_cls);
return lctx.inp_cls;
@@ -13847,19 +13847,16 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_mean->buffer));
float * data = (float *) lctx.inp_mean->data;
- memset(lctx.inp_mean->data, 0, n_tokens * n_tokens * ggml_element_size(lctx.inp_mean));
+ memset(lctx.inp_mean->data, 0, n_tokens * cparams.n_seq_max * ggml_element_size(lctx.inp_mean));
std::vector<uint64_t> sum(n_tokens, 0);
for (int i = 0; i < n_tokens; ++i) {
const llama_seq_id seq_id = batch.seq_id[i][0];
-
- GGML_ASSERT(seq_id < n_tokens && "seq_id cannot be larger than n_tokens with pooling_type == MEAN");
-
sum[seq_id] += 1;
}
- std::vector<float> div(n_tokens, 0.0f);
- for (int i = 0; i < n_tokens; ++i) {
+ std::vector<float> div(cparams.n_seq_max, 0.0f);
+ for (uint32_t i = 0; i < cparams.n_seq_max; ++i) {
const uint64_t s = sum[i];
if (s > 0) {
div[i] = 1.0f/float(s);
@@ -13879,14 +13876,11 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_cls->buffer));
uint32_t * data = (uint32_t *) lctx.inp_cls->data;
- memset(lctx.inp_cls->data, 0, n_tokens * ggml_element_size(lctx.inp_cls));
+ memset(lctx.inp_cls->data, 0, cparams.n_seq_max * ggml_element_size(lctx.inp_cls));
for (int i = 0; i < n_tokens; ++i) {
const llama_seq_id seq_id = batch.seq_id[i][0];
const llama_pos pos = batch.pos[i];
-
- GGML_ASSERT(seq_id < n_tokens && "seq_id cannot be larger than n_tokens with pooling_type == CLS");
-
if (pos == 0) {
data[seq_id] = i;
}

View File

@@ -38,7 +38,7 @@ func Init() error {
}
var variants []string
for v := range availableServers() {
for v := range getAvailableServers() {
variants = append(variants, v)
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
@@ -50,7 +50,7 @@ func Init() error {
// binary names may contain an optional variant separated by '_'
// For example, "ollama_rocm_v6" and "ollama_rocm_v5" or "ollama_cpu" and "ollama_cpu_avx2"
// Any library without a variant is the lowest common denominator
func availableServers() map[string]string {
func getAvailableServers() map[string]string {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
slog.Error("payload lookup error", "error", err)
@@ -80,7 +80,7 @@ func availableServers() map[string]string {
// TODO - switch to metadata based mapping
func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := availableServers()
availableServers := getAvailableServers()
requested := info.Library
if info.Variant != gpu.CPUCapabilityNone {
requested += "_" + info.Variant.String()
@@ -115,27 +115,29 @@ func serversForGpu(info gpu.GpuInfo) []string {
servers = append(servers, alt...)
}
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUCapability()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
servers = append(servers, cmp)
break
if !(runtime.GOOS == "darwin" && runtime.GOARCH == "arm64") {
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUCapability()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
servers = append(servers, cmp)
break
}
}
} else {
servers = append(servers, "cpu")
}
} else {
servers = append(servers, "cpu")
}
}
if len(servers) == 0 {
servers = []string{"cpu"}
if len(servers) == 0 {
servers = []string{"cpu"}
}
}
return servers
@@ -147,7 +149,7 @@ func serverForCpu() string {
return "metal"
}
variant := gpu.GetCPUCapability()
availableServers := availableServers()
availableServers := getAvailableServers()
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {

View File

@@ -131,7 +131,20 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
}
availableServers := availableServers()
availableServers := getAvailableServers()
if len(availableServers) == 0 {
if runtime.GOOS != "windows" {
slog.Warn("llama server binary disappeared, reinitializing payloads")
err = Init()
if err != nil {
slog.Warn("failed to reinitialize payloads", "error", err)
return nil, err
}
availableServers = getAvailableServers()
} else {
return nil, finalErr
}
}
var servers []string
if cpuRunner != "" {
servers = []string{cpuRunner}
@@ -208,7 +221,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
if g.Library == "metal" &&
uint64(opts.NumGPU) > 0 &&
uint64(opts.NumGPU) < ggml.KV().BlockCount()+1 {
opts.UseMMap = api.TriStateFalse
opts.UseMMap = new(bool)
*opts.UseMMap = false
}
}
@@ -219,10 +233,10 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
// Windows CUDA should not use mmap for best performance
// Linux with a model larger than free space, mmap leads to thrashing
// For CPU loads we want the memory to be allocated, not FS cache
if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == api.TriStateUndefined) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == api.TriStateUndefined) ||
(gpus[0].Library == "cpu" && opts.UseMMap == api.TriStateUndefined) ||
opts.UseMMap == api.TriStateFalse {
if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == nil) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == nil) ||
(gpus[0].Library == "cpu" && opts.UseMMap == nil) ||
(opts.UseMMap != nil && !*opts.UseMMap) {
params = append(params, "--no-mmap")
}
@@ -560,6 +574,9 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
if strings.Contains(msg, "unknown model") {
return fmt.Errorf("this model is not supported by your version of Ollama. You may need to upgrade")
}
return fmt.Errorf("llama runner process has terminated: %v %s", err, msg)
default:
}
@@ -682,10 +699,9 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
}
defer s.sem.Release(1)
// only allow maximum 10 "context shifts" to avoid infinite generation
// put an upper limit on num_predict to avoid the model running on forever
if req.Options.NumPredict < 0 || req.Options.NumPredict > 10*s.options.NumCtx {
req.Options.NumPredict = 10 * s.options.NumCtx
slog.Debug("setting token limit to 10x num_ctx", "num_ctx", s.options.NumCtx, "num_predict", req.Options.NumPredict)
}
request := map[string]any{

View File

@@ -25,6 +25,7 @@ var errorPrefixes = []string{
"CUDA error",
"cudaMalloc failed",
"\"ERR\"",
"error loading model",
}
func (w *StatusWriter) Write(b []byte) (int, error) {

View File

@@ -12,6 +12,7 @@ import (
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/types/model"
)
type Error struct {
@@ -42,6 +43,12 @@ type ChunkChoice struct {
FinishReason *string `json:"finish_reason"`
}
type CompleteChunkChoice struct {
Text string `json:"text"`
Index int `json:"index"`
FinishReason *string `json:"finish_reason"`
}
type Usage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
@@ -85,6 +92,51 @@ type ChatCompletionChunk struct {
Choices []ChunkChoice `json:"choices"`
}
// TODO (https://github.com/ollama/ollama/issues/5259): support []string, []int and [][]int
type CompletionRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt"`
FrequencyPenalty float32 `json:"frequency_penalty"`
MaxTokens *int `json:"max_tokens"`
PresencePenalty float32 `json:"presence_penalty"`
Seed *int `json:"seed"`
Stop any `json:"stop"`
Stream bool `json:"stream"`
Temperature *float32 `json:"temperature"`
TopP float32 `json:"top_p"`
}
type Completion struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
Choices []CompleteChunkChoice `json:"choices"`
Usage Usage `json:"usage,omitempty"`
}
type CompletionChunk struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Choices []CompleteChunkChoice `json:"choices"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
}
type Model struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
OwnedBy string `json:"owned_by"`
}
type ListCompletion struct {
Object string `json:"object"`
Data []Model `json:"data"`
}
func NewError(code int, message string) ErrorResponse {
var etype string
switch code {
@@ -145,7 +197,79 @@ func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
}
}
func fromRequest(r ChatCompletionRequest) api.ChatRequest {
func toCompletion(id string, r api.GenerateResponse) Completion {
return Completion{
Id: id,
Object: "text_completion",
Created: r.CreatedAt.Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []CompleteChunkChoice{{
Text: r.Response,
Index: 0,
FinishReason: func(reason string) *string {
if len(reason) > 0 {
return &reason
}
return nil
}(r.DoneReason),
}},
Usage: Usage{
// TODO: ollama returns 0 for prompt eval if the prompt was cached, but openai returns the actual count
PromptTokens: r.PromptEvalCount,
CompletionTokens: r.EvalCount,
TotalTokens: r.PromptEvalCount + r.EvalCount,
},
}
}
func toCompleteChunk(id string, r api.GenerateResponse) CompletionChunk {
return CompletionChunk{
Id: id,
Object: "text_completion",
Created: time.Now().Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []CompleteChunkChoice{{
Text: r.Response,
Index: 0,
FinishReason: func(reason string) *string {
if len(reason) > 0 {
return &reason
}
return nil
}(r.DoneReason),
}},
}
}
func toListCompletion(r api.ListResponse) ListCompletion {
var data []Model
for _, m := range r.Models {
data = append(data, Model{
Id: m.Name,
Object: "model",
Created: m.ModifiedAt.Unix(),
OwnedBy: model.ParseName(m.Name).Namespace,
})
}
return ListCompletion{
Object: "list",
Data: data,
}
}
func toModel(r api.ShowResponse, m string) Model {
return Model{
Id: m,
Object: "model",
Created: r.ModifiedAt.Unix(),
OwnedBy: model.ParseName(m).Namespace,
}
}
func fromChatRequest(r ChatCompletionRequest) api.ChatRequest {
var messages []api.Message
for _, msg := range r.Messages {
messages = append(messages, api.Message{Role: msg.Role, Content: msg.Content})
@@ -156,7 +280,7 @@ func fromRequest(r ChatCompletionRequest) api.ChatRequest {
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []interface{}:
case []any:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
@@ -208,13 +332,78 @@ func fromRequest(r ChatCompletionRequest) api.ChatRequest {
}
}
type writer struct {
stream bool
id string
func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
options := make(map[string]any)
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []string:
options["stop"] = stop
default:
if r.Stop != nil {
return api.GenerateRequest{}, fmt.Errorf("invalid type for 'stop' field: %T", r.Stop)
}
}
if r.MaxTokens != nil {
options["num_predict"] = *r.MaxTokens
}
if r.Temperature != nil {
options["temperature"] = *r.Temperature * 2.0
} else {
options["temperature"] = 1.0
}
if r.Seed != nil {
options["seed"] = *r.Seed
}
options["frequency_penalty"] = r.FrequencyPenalty * 2.0
options["presence_penalty"] = r.PresencePenalty * 2.0
if r.TopP != 0.0 {
options["top_p"] = r.TopP
} else {
options["top_p"] = 1.0
}
return api.GenerateRequest{
Model: r.Model,
Prompt: r.Prompt,
Options: options,
Stream: &r.Stream,
}, nil
}
type BaseWriter struct {
gin.ResponseWriter
}
func (w *writer) writeError(code int, data []byte) (int, error) {
type ChatWriter struct {
stream bool
id string
BaseWriter
}
type CompleteWriter struct {
stream bool
id string
BaseWriter
}
type ListWriter struct {
BaseWriter
}
type RetrieveWriter struct {
BaseWriter
model string
}
func (w *BaseWriter) writeError(code int, data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
@@ -230,7 +419,7 @@ func (w *writer) writeError(code int, data []byte) (int, error) {
return len(data), nil
}
func (w *writer) writeResponse(data []byte) (int, error) {
func (w *ChatWriter) writeResponse(data []byte) (int, error) {
var chatResponse api.ChatResponse
err := json.Unmarshal(data, &chatResponse)
if err != nil {
@@ -270,7 +459,7 @@ func (w *writer) writeResponse(data []byte) (int, error) {
return len(data), nil
}
func (w *writer) Write(data []byte) (int, error) {
func (w *ChatWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
@@ -279,7 +468,176 @@ func (w *writer) Write(data []byte) (int, error) {
return w.writeResponse(data)
}
func Middleware() gin.HandlerFunc {
func (w *CompleteWriter) writeResponse(data []byte) (int, error) {
var generateResponse api.GenerateResponse
err := json.Unmarshal(data, &generateResponse)
if err != nil {
return 0, err
}
// completion chunk
if w.stream {
d, err := json.Marshal(toCompleteChunk(w.id, generateResponse))
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "text/event-stream")
_, err = w.ResponseWriter.Write([]byte(fmt.Sprintf("data: %s\n\n", d)))
if err != nil {
return 0, err
}
if generateResponse.Done {
_, err = w.ResponseWriter.Write([]byte("data: [DONE]\n\n"))
if err != nil {
return 0, err
}
}
return len(data), nil
}
// completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toCompletion(w.id, generateResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *CompleteWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func (w *ListWriter) writeResponse(data []byte) (int, error) {
var listResponse api.ListResponse
err := json.Unmarshal(data, &listResponse)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toListCompletion(listResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *ListWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func (w *RetrieveWriter) writeResponse(data []byte) (int, error) {
var showResponse api.ShowResponse
err := json.Unmarshal(data, &showResponse)
if err != nil {
return 0, err
}
// retrieve completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toModel(showResponse, w.model))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *RetrieveWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func ListMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
w := &ListWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
}
c.Writer = w
c.Next()
}
}
func RetrieveMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(api.ShowRequest{Name: c.Param("model")}); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
// response writer
w := &RetrieveWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
model: c.Param("model"),
}
c.Writer = w
c.Next()
}
}
func CompletionsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req CompletionRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
var b bytes.Buffer
genReq, err := fromCompleteRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if err := json.NewEncoder(&b).Encode(genReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &CompleteWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: fmt.Sprintf("cmpl-%d", rand.Intn(999)),
}
c.Writer = w
c.Next()
}
}
func ChatMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req ChatCompletionRequest
err := c.ShouldBindJSON(&req)
@@ -294,17 +652,17 @@ func Middleware() gin.HandlerFunc {
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(fromRequest(req)); err != nil {
if err := json.NewEncoder(&b).Encode(fromChatRequest(req)); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &writer{
ResponseWriter: c.Writer,
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
w := &ChatWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
}
c.Writer = w

298
openai/openai_test.go Normal file
View File

@@ -0,0 +1,298 @@
package openai
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
"net/http/httptest"
"strings"
"testing"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/stretchr/testify/assert"
)
func TestMiddleware(t *testing.T) {
type testCase struct {
Name string
Method string
Path string
TestPath string
Handler func() gin.HandlerFunc
Endpoint func(c *gin.Context)
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, resp *httptest.ResponseRecorder)
}
testCases := []testCase{
{
Name: "chat handler",
Method: http.MethodPost,
Path: "/api/chat",
TestPath: "/api/chat",
Handler: ChatMiddleware,
Endpoint: func(c *gin.Context) {
var chatReq api.ChatRequest
if err := c.ShouldBindJSON(&chatReq); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request"})
return
}
userMessage := chatReq.Messages[0].Content
var assistantMessage string
switch userMessage {
case "Hello":
assistantMessage = "Hello!"
default:
assistantMessage = "I'm not sure how to respond to that."
}
c.JSON(http.StatusOK, api.ChatResponse{
Message: api.Message{
Role: "assistant",
Content: assistantMessage,
},
})
},
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{{Role: "user", Content: "Hello"}},
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
assert.Equal(t, http.StatusOK, resp.Code)
var chatResp ChatCompletion
if err := json.NewDecoder(resp.Body).Decode(&chatResp); err != nil {
t.Fatal(err)
}
if chatResp.Object != "chat.completion" {
t.Fatalf("expected chat.completion, got %s", chatResp.Object)
}
if chatResp.Choices[0].Message.Content != "Hello!" {
t.Fatalf("expected Hello!, got %s", chatResp.Choices[0].Message.Content)
}
},
},
{
Name: "completions handler",
Method: http.MethodPost,
Path: "/api/generate",
TestPath: "/api/generate",
Handler: CompletionsMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusOK, api.GenerateResponse{
Response: "Hello!",
})
},
Setup: func(t *testing.T, req *http.Request) {
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
assert.Equal(t, http.StatusOK, resp.Code)
var completionResp Completion
if err := json.NewDecoder(resp.Body).Decode(&completionResp); err != nil {
t.Fatal(err)
}
if completionResp.Object != "text_completion" {
t.Fatalf("expected text_completion, got %s", completionResp.Object)
}
if completionResp.Choices[0].Text != "Hello!" {
t.Fatalf("expected Hello!, got %s", completionResp.Choices[0].Text)
}
},
},
{
Name: "completions handler with params",
Method: http.MethodPost,
Path: "/api/generate",
TestPath: "/api/generate",
Handler: CompletionsMiddleware,
Endpoint: func(c *gin.Context) {
var generateReq api.GenerateRequest
if err := c.ShouldBindJSON(&generateReq); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request"})
return
}
temperature := generateReq.Options["temperature"].(float64)
var assistantMessage string
switch temperature {
case 1.6:
assistantMessage = "Received temperature of 1.6"
default:
assistantMessage = fmt.Sprintf("Received temperature of %f", temperature)
}
c.JSON(http.StatusOK, api.GenerateResponse{
Response: assistantMessage,
})
},
Setup: func(t *testing.T, req *http.Request) {
temp := float32(0.8)
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
Temperature: &temp,
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
assert.Equal(t, http.StatusOK, resp.Code)
var completionResp Completion
if err := json.NewDecoder(resp.Body).Decode(&completionResp); err != nil {
t.Fatal(err)
}
if completionResp.Object != "text_completion" {
t.Fatalf("expected text_completion, got %s", completionResp.Object)
}
if completionResp.Choices[0].Text != "Received temperature of 1.6" {
t.Fatalf("expected Received temperature of 1.6, got %s", completionResp.Choices[0].Text)
}
},
},
{
Name: "completions handler with error",
Method: http.MethodPost,
Path: "/api/generate",
TestPath: "/api/generate",
Handler: CompletionsMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request"})
},
Setup: func(t *testing.T, req *http.Request) {
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusBadRequest {
t.Fatalf("expected 400, got %d", resp.Code)
}
if !strings.Contains(resp.Body.String(), `"invalid request"`) {
t.Fatalf("error was not forwarded")
}
},
},
{
Name: "list handler",
Method: http.MethodGet,
Path: "/api/tags",
TestPath: "/api/tags",
Handler: ListMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusOK, api.ListResponse{
Models: []api.ListModelResponse{
{
Name: "Test Model",
},
},
})
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
assert.Equal(t, http.StatusOK, resp.Code)
var listResp ListCompletion
if err := json.NewDecoder(resp.Body).Decode(&listResp); err != nil {
t.Fatal(err)
}
if listResp.Object != "list" {
t.Fatalf("expected list, got %s", listResp.Object)
}
if len(listResp.Data) != 1 {
t.Fatalf("expected 1, got %d", len(listResp.Data))
}
if listResp.Data[0].Id != "Test Model" {
t.Fatalf("expected Test Model, got %s", listResp.Data[0].Id)
}
},
},
{
Name: "retrieve model",
Method: http.MethodGet,
Path: "/api/show/:model",
TestPath: "/api/show/test-model",
Handler: RetrieveMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusOK, api.ShowResponse{
ModifiedAt: time.Date(2024, 6, 17, 13, 45, 0, 0, time.UTC),
})
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
var retrieveResp Model
if err := json.NewDecoder(resp.Body).Decode(&retrieveResp); err != nil {
t.Fatal(err)
}
if retrieveResp.Object != "model" {
t.Fatalf("Expected object to be model, got %s", retrieveResp.Object)
}
if retrieveResp.Id != "test-model" {
t.Fatalf("Expected id to be test-model, got %s", retrieveResp.Id)
}
},
},
}
gin.SetMode(gin.TestMode)
router := gin.New()
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
router = gin.New()
router.Use(tc.Handler())
router.Handle(tc.Method, tc.Path, tc.Endpoint)
req, _ := http.NewRequest(tc.Method, tc.TestPath, nil)
if tc.Setup != nil {
tc.Setup(t, req)
}
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
tc.Expected(t, resp)
})
}
}

View File

@@ -124,7 +124,7 @@ func ParseFile(r io.Reader) (*File, error) {
case stateComment, stateNil:
// pass
case stateValue:
s, ok := unquote(b.String())
s, ok := unquote(strings.TrimSpace(b.String()))
if !ok || isSpace(r) {
if _, err := b.WriteRune(r); err != nil {
return nil, err
@@ -158,7 +158,7 @@ func ParseFile(r io.Reader) (*File, error) {
case stateComment, stateNil:
// pass; nothing to flush
case stateValue:
s, ok := unquote(b.String())
s, ok := unquote(strings.TrimSpace(b.String()))
if !ok {
return nil, io.ErrUnexpectedEOF
}

View File

@@ -22,7 +22,13 @@ ADAPTER adapter1
LICENSE MIT
PARAMETER param1 value1
PARAMETER param2 value2
TEMPLATE template1
TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ .Response }}<|eot_id|>"""
`
reader := strings.NewReader(input)
@@ -36,7 +42,40 @@ TEMPLATE template1
{Name: "license", Args: "MIT"},
{Name: "param1", Args: "value1"},
{Name: "param2", Args: "value2"},
{Name: "template", Args: "template1"},
{Name: "template", Args: "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>"},
}
assert.Equal(t, expectedCommands, modelfile.Commands)
}
func TestParseFileTrimSpace(t *testing.T) {
input := `
FROM " model 1"
ADAPTER adapter3
LICENSE "MIT "
PARAMETER param1 value1
PARAMETER param2 value2
TEMPLATE """ {{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ .Response }}<|eot_id|> """
`
reader := strings.NewReader(input)
modelfile, err := ParseFile(reader)
require.NoError(t, err)
expectedCommands := []Command{
{Name: "model", Args: " model 1"},
{Name: "adapter", Args: "adapter3"},
{Name: "license", Args: "MIT "},
{Name: "param1", Args: "value1"},
{Name: "param2", Args: "value2"},
{Name: "template", Args: " {{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|> "},
}
assert.Equal(t, expectedCommands, modelfile.Commands)
@@ -48,6 +87,26 @@ func TestParseFileFrom(t *testing.T) {
expected []Command
err error
}{
{
"FROM \"FOO BAR \"",
[]Command{{Name: "model", Args: "FOO BAR "}},
nil,
},
{
"FROM \"FOO BAR\"\nPARAMETER param1 value1",
[]Command{{Name: "model", Args: "FOO BAR"}, {Name: "param1", Args: "value1"}},
nil,
},
{
"FROM FOOO BAR ",
[]Command{{Name: "model", Args: "FOOO BAR"}},
nil,
},
{
"FROM /what/is/the path ",
[]Command{{Name: "model", Args: "/what/is/the path"}},
nil,
},
{
"FROM foo",
[]Command{{Name: "model", Args: "foo"}},
@@ -86,6 +145,11 @@ func TestParseFileFrom(t *testing.T) {
[]Command{{Name: "param1", Args: "value1"}, {Name: "model", Args: "foo"}},
nil,
},
{
"PARAMETER what the \nFROM lemons make lemonade ",
[]Command{{Name: "what", Args: "the"}, {Name: "model", Args: "lemons make lemonade"}},
nil,
},
}
for _, c := range cases {
@@ -399,7 +463,7 @@ func TestParseFileParameters(t *testing.T) {
"mirostat_eta 1.0": {"mirostat_eta", "1.0"},
"penalize_newline true": {"penalize_newline", "true"},
"stop ### User:": {"stop", "### User:"},
"stop ### User: ": {"stop", "### User: "},
"stop ### User: ": {"stop", "### User:"},
"stop \"### User:\"": {"stop", "### User:"},
"stop \"### User: \"": {"stop", "### User: "},
"stop \"\"\"### User:\"\"\"": {"stop", "### User:"},

View File

@@ -6,10 +6,21 @@ set -ex
MACHINE=$(uname -m)
if grep -i "centos" /etc/system-release >/dev/null; then
# As of 7/1/2024 mirrorlist.centos.org has been taken offline, so adjust accordingly
sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
# Centos 7 derivatives have too old of a git version to run our generate script
# uninstall and ignore failures
yum remove -y git
yum -y install epel-release centos-release-scl
# The release packages reinstate the mirrors, undo that again
sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
yum -y install dnf
if [ "${MACHINE}" = "x86_64" ]; then
yum -y install https://repo.ius.io/ius-release-el7.rpm

View File

@@ -28,11 +28,16 @@ import (
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/errtypes"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
)
type Capability string
const CapabilityCompletion = Capability("completion")
type registryOptions struct {
Insecure bool
Username string
@@ -48,16 +53,43 @@ type Model struct {
ParentModel string
AdapterPaths []string
ProjectorPaths []string
Template string
System string
License []string
Digest string
Options map[string]interface{}
Messages []Message
Template *template.Template
}
func (m *Model) IsEmbedding() bool {
return slices.Contains(m.Config.ModelFamilies, "bert") || slices.Contains(m.Config.ModelFamilies, "nomic-bert")
func (m *Model) Has(caps ...Capability) bool {
for _, cap := range caps {
switch cap {
case CapabilityCompletion:
f, err := os.Open(m.ModelPath)
if err != nil {
slog.Error("couldn't open model file", "error", err)
continue
}
defer f.Close()
// TODO(mxyng): decode the GGML into model to avoid doing this multiple times
ggml, _, err := llm.DecodeGGML(f, 0)
if err != nil {
slog.Error("couldn't decode ggml", "error", err)
continue
}
if _, ok := ggml.KV()[fmt.Sprintf("%s.pooling_type", ggml.KV().Architecture())]; ok {
return false
}
default:
slog.Error("unknown capability", "capability", cap)
return false
}
}
return true
}
func (m *Model) String() string {
@@ -82,10 +114,10 @@ func (m *Model) String() string {
})
}
if m.Template != "" {
if m.Template != nil {
modelfile.Commands = append(modelfile.Commands, parser.Command{
Name: "template",
Args: m.Template,
Args: m.Template.String(),
})
}
@@ -135,13 +167,6 @@ type Message struct {
Content string `json:"content"`
}
type ManifestV2 struct {
SchemaVersion int `json:"schemaVersion"`
MediaType string `json:"mediaType"`
Config *Layer `json:"config"`
Layers []*Layer `json:"layers"`
}
type ConfigV2 struct {
ModelFormat string `json:"model_format"`
ModelFamily string `json:"model_family"`
@@ -160,7 +185,7 @@ type RootFS struct {
DiffIDs []string `json:"diff_ids"`
}
func GetManifest(mp ModelPath) (*ManifestV2, string, error) {
func GetManifest(mp ModelPath) (*Manifest, string, error) {
fp, err := mp.GetManifestPath()
if err != nil {
return nil, "", err
@@ -170,7 +195,7 @@ func GetManifest(mp ModelPath) (*ManifestV2, string, error) {
return nil, "", err
}
var manifest *ManifestV2
var manifest *Manifest
bts, err := os.ReadFile(fp)
if err != nil {
@@ -198,8 +223,7 @@ func GetModel(name string) (*Model, error) {
Name: mp.GetFullTagname(),
ShortName: mp.GetShortTagname(),
Digest: digest,
Template: "{{ .Prompt }}",
License: []string{},
Template: template.DefaultTemplate,
}
filename, err := GetBlobsPath(manifest.Config.Digest)
@@ -235,13 +259,17 @@ func GetModel(name string) (*Model, error) {
model.AdapterPaths = append(model.AdapterPaths, filename)
case "application/vnd.ollama.image.projector":
model.ProjectorPaths = append(model.ProjectorPaths, filename)
case "application/vnd.ollama.image.template":
case "application/vnd.ollama.image.prompt",
"application/vnd.ollama.image.template":
bts, err := os.ReadFile(filename)
if err != nil {
return nil, err
}
model.Template = string(bts)
model.Template, err = template.Parse(string(bts))
if err != nil {
return nil, err
}
case "application/vnd.ollama.image.system":
bts, err := os.ReadFile(filename)
if err != nil {
@@ -249,13 +277,6 @@ func GetModel(name string) (*Model, error) {
}
model.System = string(bts)
case "application/vnd.ollama.image.prompt":
bts, err := os.ReadFile(filename)
if err != nil {
return nil, err
}
model.Template = string(bts)
case "application/vnd.ollama.image.params":
params, err := os.Open(filename)
if err != nil {
@@ -822,7 +843,7 @@ func PushModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn func(api.ProgressResponse)) error {
mp := ParseModelPath(name)
var manifest *ManifestV2
var manifest *Manifest
var err error
var noprune string
@@ -929,7 +950,7 @@ func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
return nil
}
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*ManifestV2, error) {
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*Manifest, error) {
requestURL := mp.BaseURL().JoinPath("v2", mp.GetNamespaceRepository(), "manifests", mp.Tag)
headers := make(http.Header)
@@ -940,7 +961,7 @@ func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptio
}
defer resp.Body.Close()
var m *ManifestV2
var m *Manifest
if err := json.NewDecoder(resp.Body).Decode(&m); err != nil {
return nil, err
}

View File

@@ -14,7 +14,10 @@ import (
)
type Manifest struct {
ManifestV2
SchemaVersion int `json:"schemaVersion"`
MediaType string `json:"mediaType"`
Config *Layer `json:"config"`
Layers []*Layer `json:"layers"`
filepath string
fi os.FileInfo
@@ -66,7 +69,7 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
p := filepath.Join(manifests, n.Filepath())
var m ManifestV2
var m Manifest
f, err := os.Open(p)
if err != nil {
return nil, err
@@ -83,12 +86,11 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
return nil, err
}
return &Manifest{
ManifestV2: m,
filepath: p,
fi: fi,
digest: fmt.Sprintf("%x", sha256sum.Sum(nil)),
}, nil
m.filepath = p
m.fi = fi
m.digest = fmt.Sprintf("%x", sha256sum.Sum(nil))
return &m, nil
}
func WriteManifest(name model.Name, config *Layer, layers []*Layer) error {
@@ -108,7 +110,7 @@ func WriteManifest(name model.Name, config *Layer, layers []*Layer) error {
}
defer f.Close()
m := ManifestV2{
m := Manifest{
SchemaVersion: 2,
MediaType: "application/vnd.docker.distribution.manifest.v2+json",
Config: config,

View File

@@ -25,7 +25,7 @@ func createManifest(t *testing.T, path, name string) {
}
defer f.Close()
if err := json.NewEncoder(f).Encode(ManifestV2{}); err != nil {
if err := json.NewEncoder(f).Encode(Manifest{}); err != nil {
t.Fatal(err)
}
}

View File

@@ -11,12 +11,11 @@ import (
"net/http"
"os"
"path/filepath"
"strings"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/convert"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/templates"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/model"
)
@@ -91,12 +90,11 @@ func extractFromZipFile(p string, file *os.File, fn func(api.ProgressResponse))
fn(api.ProgressResponse{Status: "unpacking model metadata"})
for _, f := range r.File {
n := filepath.Join(p, f.Name)
if !strings.HasPrefix(n, p) {
slog.Warn("skipped extracting file outside of context", "name", f.Name)
continue
if !filepath.IsLocal(f.Name) {
return fmt.Errorf("%w: %s", zip.ErrInsecurePath, f.Name)
}
n := filepath.Join(p, f.Name)
if err := os.MkdirAll(filepath.Dir(n), 0o750); err != nil {
return err
}
@@ -258,7 +256,7 @@ func parseFromFile(ctx context.Context, file *os.File, digest string, fn func(ap
func detectChatTemplate(layers []*layerGGML) ([]*layerGGML, error) {
for _, layer := range layers {
if s := layer.GGML.KV().ChatTemplate(); s != "" {
if t, err := templates.NamedTemplate(s); err != nil {
if t, err := template.Named(s); err != nil {
slog.Debug("template detection", "error", err)
} else {
tmpl, err := NewLayer(t.Reader(), "application/vnd.ollama.image.template")

View File

@@ -3,10 +3,12 @@ package server
import (
"archive/zip"
"bytes"
"errors"
"io"
"os"
"path/filepath"
"slices"
"strings"
"testing"
"github.com/ollama/ollama/api"
@@ -39,13 +41,31 @@ func TestExtractFromZipFile(t *testing.T) {
cases := []struct {
name string
expect []string
err error
}{
{
name: "good",
expect: []string{"good"},
},
{
name: filepath.Join("..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "bad"),
name: strings.Join([]string{"path", "..", "to", "good"}, string(os.PathSeparator)),
expect: []string{filepath.Join("to", "good")},
},
{
name: strings.Join([]string{"path", "..", "to", "..", "good"}, string(os.PathSeparator)),
expect: []string{"good"},
},
{
name: strings.Join([]string{"path", "to", "..", "..", "good"}, string(os.PathSeparator)),
expect: []string{"good"},
},
{
name: strings.Join([]string{"..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "bad"}, string(os.PathSeparator)),
err: zip.ErrInsecurePath,
},
{
name: strings.Join([]string{"path", "..", "..", "to", "bad"}, string(os.PathSeparator)),
err: zip.ErrInsecurePath,
},
}
@@ -55,7 +75,7 @@ func TestExtractFromZipFile(t *testing.T) {
defer f.Close()
tempDir := t.TempDir()
if err := extractFromZipFile(tempDir, f, func(api.ProgressResponse) {}); err != nil {
if err := extractFromZipFile(tempDir, f, func(api.ProgressResponse) {}); !errors.Is(err, tt.err) {
t.Fatal(err)
}

View File

@@ -103,18 +103,9 @@ func (mp ModelPath) GetShortTagname() string {
return fmt.Sprintf("%s/%s/%s:%s", mp.Registry, mp.Namespace, mp.Repository, mp.Tag)
}
// modelsDir returns the value of the OLLAMA_MODELS environment variable or the user's home directory if OLLAMA_MODELS is not set.
// The models directory is where Ollama stores its model files and manifests.
func modelsDir() (string, error) {
return envconfig.ModelsDir, nil
}
// GetManifestPath returns the path to the manifest file for the given model path, it is up to the caller to create the directory if it does not exist.
func (mp ModelPath) GetManifestPath() (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
return filepath.Join(dir, "manifests", mp.Registry, mp.Namespace, mp.Repository, mp.Tag), nil
}
@@ -127,10 +118,7 @@ func (mp ModelPath) BaseURL() *url.URL {
}
func GetManifestPath() (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
path := filepath.Join(dir, "manifests")
if err := os.MkdirAll(path, 0o755); err != nil {
@@ -141,10 +129,7 @@ func GetManifestPath() (string, error) {
}
func GetBlobsPath(digest string) (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
// only accept actual sha256 digests
pattern := "^sha256[:-][0-9a-fA-F]{64}$"

View File

@@ -4,10 +4,11 @@ import (
"fmt"
"log/slog"
"strings"
"text/template"
"text/template/parse"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
// isResponseNode checks if the node contains .Response
@@ -53,13 +54,8 @@ func formatTemplateForResponse(tmpl *template.Template, generate bool) {
// Prompt renders a prompt from a template. If generate is set to true,
// the response and parts of the template following it are not rendered
func Prompt(tmpl, system, prompt, response string, generate bool) (string, error) {
parsed, err := template.New("").Option("missingkey=zero").Parse(tmpl)
if err != nil {
return "", err
}
formatTemplateForResponse(parsed, generate)
func Prompt(tmpl *template.Template, system, prompt, response string, generate bool) (string, error) {
formatTemplateForResponse(tmpl, generate)
vars := map[string]any{
"System": system,
@@ -68,14 +64,14 @@ func Prompt(tmpl, system, prompt, response string, generate bool) (string, error
}
var sb strings.Builder
if err := parsed.Execute(&sb, vars); err != nil {
if err := tmpl.Execute(&sb, vars); err != nil {
return "", err
}
return sb.String(), nil
}
func countTokens(tmpl string, system string, prompt string, response string, encode func(string) ([]int, error)) (int, error) {
func countTokens(tmpl *template.Template, system string, prompt string, response string, encode func(string) ([]int, error)) (int, error) {
rendered, err := Prompt(tmpl, system, prompt, response, false)
if err != nil {
return 0, err
@@ -91,7 +87,7 @@ func countTokens(tmpl string, system string, prompt string, response string, enc
}
// ChatPrompt builds up a prompt from a series of messages, truncating based on context window size
func ChatPrompt(tmpl string, messages []api.Message, window int, encode func(string) ([]int, error)) (string, error) {
func ChatPrompt(tmpl *template.Template, messages []api.Message, window int, encode func(string) ([]int, error)) (string, error) {
type prompt struct {
System string
Prompt string

View File

@@ -5,6 +5,7 @@ import (
"testing"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
func TestPrompt(t *testing.T) {
@@ -61,7 +62,12 @@ func TestPrompt(t *testing.T) {
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := Prompt(tc.template, tc.system, tc.prompt, tc.response, tc.generate)
tmpl, err := template.Parse(tc.template)
if err != nil {
t.Fatal(err)
}
got, err := Prompt(tmpl, tc.system, tc.prompt, tc.response, tc.generate)
if err != nil {
t.Errorf("error = %v", err)
}
@@ -192,7 +198,12 @@ func TestChatPrompt(t *testing.T) {
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := ChatPrompt(tc.template, tc.messages, tc.window, encode)
tmpl, err := template.Parse(tc.template)
if err != nil {
t.Fatal(err)
}
got, err := ChatPrompt(tmpl, tc.messages, tc.window, encode)
if err != nil {
t.Errorf("error = %v", err)
}

View File

@@ -9,7 +9,6 @@ import (
"io"
"io/fs"
"log/slog"
"math"
"net"
"net/http"
"net/netip"
@@ -17,7 +16,6 @@ import (
"os/signal"
"path/filepath"
"slices"
"strconv"
"strings"
"syscall"
"time"
@@ -31,6 +29,7 @@ import (
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/openai"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/errtypes"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
@@ -55,8 +54,6 @@ func init() {
gin.SetMode(mode)
}
var defaultSessionDuration = 5 * time.Minute
func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options, error) {
opts := api.DefaultOptions()
if err := opts.FromMap(model.Options); err != nil {
@@ -121,8 +118,8 @@ func (s *Server) GenerateHandler(c *gin.Context) {
return
}
if model.IsEmbedding() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support generate"})
if !model.Has(CapabilityCompletion) {
c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%s does not support generate", req.Model)})
return
}
@@ -132,14 +129,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, req.KeepAlive)
var runner *runnerRef
select {
case runner = <-rCh:
@@ -161,6 +151,12 @@ func (s *Server) GenerateHandler(c *gin.Context) {
return
}
tmpl, err := template.Parse(req.Template)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
checkpointLoaded := time.Now()
var prompt string
@@ -169,7 +165,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
prompt = req.Prompt
case req.Prompt != "":
if req.Template == "" {
req.Template = model.Template
tmpl = model.Template
}
if req.System == "" {
@@ -187,7 +183,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
sb.WriteString(req.Prompt)
p, err := Prompt(req.Template, req.System, sb.String(), "", true)
p, err := Prompt(tmpl, req.System, sb.String(), "", true)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@@ -242,7 +238,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
resp.LoadDuration = checkpointLoaded.Sub(checkpointStart)
if !req.Raw {
p, err := Prompt(req.Template, req.System, req.Prompt, generated.String(), false)
p, err := Prompt(tmpl, req.System, req.Prompt, generated.String(), false)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@@ -313,32 +309,6 @@ func (s *Server) GenerateHandler(c *gin.Context) {
streamResponse(c, ch)
}
func getDefaultSessionDuration() time.Duration {
if envconfig.KeepAlive != "" {
v, err := strconv.Atoi(envconfig.KeepAlive)
if err != nil {
d, err := time.ParseDuration(envconfig.KeepAlive)
if err != nil {
return defaultSessionDuration
}
if d < 0 {
return time.Duration(math.MaxInt64)
}
return d
}
d := time.Duration(v) * time.Second
if d < 0 {
return time.Duration(math.MaxInt64)
}
return d
}
return defaultSessionDuration
}
func (s *Server) EmbeddingsHandler(c *gin.Context) {
var req api.EmbeddingRequest
err := c.ShouldBindJSON(&req)
@@ -373,14 +343,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, req.KeepAlive)
var runner *runnerRef
select {
case runner = <-rCh:
@@ -680,7 +643,10 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
}
if req.Template != "" {
m.Template = req.Template
m.Template, err = template.Parse(req.Template)
if err != nil {
return nil, err
}
}
msgs := make([]api.Message, 0)
@@ -701,7 +667,7 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
resp := &api.ShowResponse{
License: strings.Join(m.License, "\n"),
System: m.System,
Template: m.Template,
Template: m.Template.String(),
Details: modelDetails,
Messages: msgs,
ModifiedAt: manifest.fi.ModTime(),
@@ -1039,7 +1005,10 @@ func (s *Server) GenerateRoutes() http.Handler {
r.GET("/api/ps", s.ProcessHandler)
// Compatibility endpoints
r.POST("/v1/chat/completions", openai.Middleware(), s.ChatHandler)
r.POST("/v1/chat/completions", openai.ChatMiddleware(), s.ChatHandler)
r.POST("/v1/completions", openai.CompletionsMiddleware(), s.GenerateHandler)
r.GET("/v1/models", openai.ListMiddleware(), s.ListModelsHandler)
r.GET("/v1/models/:model", openai.RetrieveMiddleware(), s.ShowModelHandler)
for _, method := range []string{http.MethodGet, http.MethodHead} {
r.Handle(method, "/", func(c *gin.Context) {
@@ -1246,7 +1215,7 @@ func (s *Server) ProcessHandler(c *gin.Context) {
}
// ChatPrompt builds up a prompt from a series of messages for the currently `loaded` model
func chatPrompt(ctx context.Context, runner *runnerRef, template string, messages []api.Message, numCtx int) (string, error) {
func chatPrompt(ctx context.Context, runner *runnerRef, template *template.Template, messages []api.Message, numCtx int) (string, error) {
encode := func(s string) ([]int, error) {
return runner.llama.Tokenize(ctx, s)
}
@@ -1294,8 +1263,8 @@ func (s *Server) ChatHandler(c *gin.Context) {
return
}
if model.IsEmbedding() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support chat"})
if !model.Has(CapabilityCompletion) {
c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%s does not support chat", req.Model)})
return
}
@@ -1305,14 +1274,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, req.KeepAlive)
var runner *runnerRef
select {
case runner = <-rCh:

View File

@@ -20,6 +20,7 @@ import (
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/openai"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
@@ -105,6 +106,24 @@ func Test_Routes(t *testing.T) {
assert.Empty(t, len(modelList.Models))
},
},
{
Name: "openai empty list",
Method: http.MethodGet,
Path: "/v1/models",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var modelList openai.ListCompletion
err = json.Unmarshal(body, &modelList)
require.NoError(t, err)
assert.Equal(t, "list", modelList.Object)
assert.Empty(t, modelList.Data)
},
},
{
Name: "Tags Handler (yes tags)",
Method: http.MethodGet,
@@ -128,6 +147,25 @@ func Test_Routes(t *testing.T) {
assert.Equal(t, "test-model:latest", modelList.Models[0].Name)
},
},
{
Name: "openai list models with tags",
Method: http.MethodGet,
Path: "/v1/models",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var modelList openai.ListCompletion
err = json.Unmarshal(body, &modelList)
require.NoError(t, err)
assert.Len(t, modelList.Data, 1)
assert.Equal(t, "test-model:latest", modelList.Data[0].Id)
assert.Equal(t, "library", modelList.Data[0].OwnedBy)
},
},
{
Name: "Create Model Handler",
Method: http.MethodPost,
@@ -216,6 +254,24 @@ func Test_Routes(t *testing.T) {
assert.InDelta(t, 0, showResp.ModelInfo["general.parameter_count"], 1e-9, "Parameter count should be 0")
},
},
{
Name: "openai retrieve model handler",
Method: http.MethodGet,
Path: "/v1/models/show-model",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var retrieveResp api.RetrieveModelResponse
err = json.Unmarshal(body, &retrieveResp)
require.NoError(t, err)
assert.Equal(t, "show-model", retrieveResp.Id)
assert.Equal(t, "library", retrieveResp.OwnedBy)
},
},
}
t.Setenv("OLLAMA_MODELS", t.TempDir())

View File

@@ -24,7 +24,7 @@ type LlmRequest struct {
model *Model
opts api.Options
origNumCtx int // Track the initial ctx request
sessionDuration time.Duration
sessionDuration *api.Duration
successCh chan *runnerRef
errCh chan error
schedAttempts uint
@@ -75,7 +75,7 @@ func InitScheduler(ctx context.Context) *Scheduler {
}
// context must be canceled to decrement ref count and release the runner
func (s *Scheduler) GetRunner(c context.Context, model *Model, opts api.Options, sessionDuration time.Duration) (chan *runnerRef, chan error) {
func (s *Scheduler) GetRunner(c context.Context, model *Model, opts api.Options, sessionDuration *api.Duration) (chan *runnerRef, chan error) {
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
@@ -139,6 +139,11 @@ func (s *Scheduler) processPending(ctx context.Context) {
}
for {
cpus := s.getCpuFn()
var systemMem gpu.GpuInfo
if len(cpus) > 0 {
systemMem = cpus[0]
}
var runnerToExpire *runnerRef
s.loadedMu.Lock()
runner := s.loaded[pending.model.ModelPath]
@@ -192,6 +197,38 @@ func (s *Scheduler) processPending(ctx context.Context) {
break
}
estimate := llm.EstimateGPULayers(gpus, ggml, pending.model.ProjectorPaths, pending.opts)
maxSize := systemMem.FreeMemory
// Add available GPU memory to the total pool
// macOS hardware has unified memory so don't double count
if runtime.GOOS != "darwin" {
for _, gpu := range gpus {
if gpu.Library == "cpu" {
continue
}
if loadedCount == 0 {
// If no other models are loaded, set the limit based on what's available
maxSize += gpu.FreeMemory
} else {
// Other models could be unloaded, favor total memory for limit
maxSize += gpu.TotalMemory
}
}
}
// Block attempting to load a model larger than system memory + GPU memory
if estimate.TotalSize > maxSize {
slog.Warn("model request too large for system", "requested", format.HumanBytes2(estimate.TotalSize), "system", format.HumanBytes2(maxSize))
// Linux will crash if over-allocating memory - return an error to the user.
// TODO (jmorganca): add reasonable upper limits for darwin and windows as well
if runtime.GOOS == "linux" {
pending.errCh <- fmt.Errorf("requested model (%s) is too large for this system (%s)", format.HumanBytes2(estimate.TotalSize), format.HumanBytes2(maxSize))
break
}
}
// Evaluate if the model will fit in the available system memory, or if we should unload a model first
if len(gpus) == 1 && gpus[0].Library == "cpu" {
// simplifying assumption of defaultParallel when in CPU mode
@@ -389,7 +426,9 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
runner.expireTimer.Stop()
runner.expireTimer = nil
}
runner.sessionDuration = pending.sessionDuration
if pending.sessionDuration != nil {
runner.sessionDuration = pending.sessionDuration.Duration
}
pending.successCh <- runner
go func() {
<-pending.ctx.Done()
@@ -402,6 +441,10 @@ func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList,
if numParallel < 1 {
numParallel = 1
}
sessionDuration := envconfig.KeepAlive
if req.sessionDuration != nil {
sessionDuration = req.sessionDuration.Duration
}
llama, err := s.newServerFn(gpus, req.model.ModelPath, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, numParallel)
if err != nil {
// some older models are not compatible with newer versions of llama.cpp
@@ -419,7 +462,7 @@ func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList,
modelPath: req.model.ModelPath,
llama: llama,
Options: &req.opts,
sessionDuration: req.sessionDuration,
sessionDuration: sessionDuration,
gpus: gpus,
estimatedVRAM: llama.EstimatedVRAM(),
estimatedTotal: llama.EstimatedTotal(),

View File

@@ -44,7 +44,7 @@ func TestLoad(t *testing.T) {
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
sessionDuration: 2,
sessionDuration: &api.Duration{Duration: 2 * time.Second},
}
// Fail to load model first
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
@@ -142,7 +142,7 @@ func newScenario(t *testing.T, ctx context.Context, modelName string, estimatedV
ctx: scenario.ctx,
model: model,
opts: api.DefaultOptions(),
sessionDuration: 5 * time.Millisecond,
sessionDuration: &api.Duration{Duration: 5 * time.Millisecond},
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
}
@@ -156,18 +156,18 @@ func TestRequests(t *testing.T) {
// Same model, same request
scenario1a := newScenario(t, ctx, "ollama-model-1", 10)
scenario1a.req.sessionDuration = 5 * time.Millisecond
scenario1a.req.sessionDuration = &api.Duration{Duration: 5 * time.Millisecond}
scenario1b := newScenario(t, ctx, "ollama-model-1", 11)
scenario1b.req.model = scenario1a.req.model
scenario1b.ggml = scenario1a.ggml
scenario1b.req.sessionDuration = 0
scenario1b.req.sessionDuration = &api.Duration{Duration: 0}
// simple reload of same model
scenario2a := newScenario(t, ctx, "ollama-model-1", 20)
tmpModel := *scenario1a.req.model
scenario2a.req.model = &tmpModel
scenario2a.ggml = scenario1a.ggml
scenario2a.req.sessionDuration = 5 * time.Millisecond
scenario2a.req.sessionDuration = &api.Duration{Duration: 5 * time.Millisecond}
// Multiple loaded models
scenario3a := newScenario(t, ctx, "ollama-model-3a", 1*format.GigaByte)
@@ -199,6 +199,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario1a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1a.req.errCh)
case err := <-scenario1a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -212,6 +214,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario1a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1b.req.errCh)
case err := <-scenario1b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -230,6 +234,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario2a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario2a.req.errCh)
case err := <-scenario2a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -246,6 +252,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario3a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3a.req.errCh)
case err := <-scenario3a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -262,6 +270,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario3b.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3b.req.errCh)
case err := <-scenario3b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -278,6 +288,8 @@ func TestRequests(t *testing.T) {
require.Equal(t, resp.llama, scenario3c.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3c.req.errCh)
case err := <-scenario3c.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
@@ -318,11 +330,11 @@ func TestGetRunner(t *testing.T) {
defer done()
scenario1a := newScenario(t, ctx, "ollama-model-1a", 10)
scenario1a.req.sessionDuration = 0
scenario1a.req.sessionDuration = &api.Duration{Duration: 0}
scenario1b := newScenario(t, ctx, "ollama-model-1b", 10)
scenario1b.req.sessionDuration = 0
scenario1b.req.sessionDuration = &api.Duration{Duration: 0}
scenario1c := newScenario(t, ctx, "ollama-model-1c", 10)
scenario1c.req.sessionDuration = 0
scenario1c.req.sessionDuration = &api.Duration{Duration: 0}
envconfig.MaxQueuedRequests = 1
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
@@ -402,7 +414,7 @@ func TestPrematureExpired(t *testing.T) {
case <-ctx.Done():
t.Fatal("timeout")
}
time.Sleep(scenario1a.req.sessionDuration)
time.Sleep(scenario1a.req.sessionDuration.Duration)
scenario1a.ctxDone()
time.Sleep(20 * time.Millisecond)
require.LessOrEqual(t, len(s.finishedReqCh), 1)
@@ -423,7 +435,7 @@ func TestUseLoadedRunner(t *testing.T) {
ctx: ctx,
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
sessionDuration: 2,
sessionDuration: &api.Duration{Duration: 2},
}
finished := make(chan *LlmRequest)
llm1 := &mockLlm{estimatedVRAMByGPU: map[string]uint64{}}
@@ -614,7 +626,7 @@ func TestAlreadyCanceled(t *testing.T) {
dctx, done2 := context.WithCancel(ctx)
done2()
scenario1a := newScenario(t, dctx, "ollama-model-1", 10)
scenario1a.req.sessionDuration = 0
scenario1a.req.sessionDuration = &api.Duration{Duration: 0}
s := InitScheduler(ctx)
slog.Info("scenario1a")
s.pendingReqCh <- scenario1a.req

158
template/template.go Normal file
View File

@@ -0,0 +1,158 @@
package template
import (
"bytes"
"embed"
"encoding/json"
"errors"
"io"
"math"
"slices"
"strings"
"sync"
"text/template"
"text/template/parse"
"github.com/agnivade/levenshtein"
"golang.org/x/exp/maps"
)
//go:embed index.json
var indexBytes []byte
//go:embed *.gotmpl
var templatesFS embed.FS
var templatesOnce = sync.OnceValues(func() ([]*named, error) {
var templates []*named
if err := json.Unmarshal(indexBytes, &templates); err != nil {
return nil, err
}
for _, t := range templates {
bts, err := templatesFS.ReadFile(t.Name + ".gotmpl")
if err != nil {
return nil, err
}
// normalize line endings
t.Bytes = bytes.ReplaceAll(bts, []byte("\r\n"), []byte("\n"))
}
return templates, nil
})
type named struct {
Name string `json:"name"`
Template string `json:"template"`
Bytes []byte
}
func (t named) Reader() io.Reader {
return bytes.NewReader(t.Bytes)
}
func Named(s string) (*named, error) {
templates, err := templatesOnce()
if err != nil {
return nil, err
}
var template *named
score := math.MaxInt
for _, t := range templates {
if s := levenshtein.ComputeDistance(s, t.Template); s < score {
score = s
template = t
}
}
if score < 100 {
return template, nil
}
return nil, errors.New("no matching template found")
}
type Template struct {
*template.Template
raw string
}
func (t *Template) String() string {
return t.raw
}
var DefaultTemplate, _ = Parse("{{ .Prompt }}")
func Parse(s string) (*Template, error) {
t, err := template.New("").Option("missingkey=zero").Parse(s)
if err != nil {
return nil, err
}
return &Template{Template: t, raw: s}, nil
}
func (t *Template) Vars() []string {
var vars []string
for _, n := range t.Tree.Root.Nodes {
vars = append(vars, parseNode(n)...)
}
set := make(map[string]struct{})
for _, n := range vars {
set[strings.ToLower(n)] = struct{}{}
}
vars = maps.Keys(set)
slices.Sort(vars)
return vars
}
func parseNode(n parse.Node) []string {
switch n := n.(type) {
case *parse.ActionNode:
return parseNode(n.Pipe)
case *parse.IfNode:
names := parseNode(n.Pipe)
names = append(names, parseNode(n.List)...)
if n.ElseList != nil {
names = append(names, parseNode(n.ElseList)...)
}
return names
case *parse.RangeNode:
names := parseNode(n.Pipe)
names = append(names, parseNode(n.List)...)
if n.ElseList != nil {
names = append(names, parseNode(n.ElseList)...)
}
return names
case *parse.WithNode:
names := parseNode(n.Pipe)
names = append(names, parseNode(n.List)...)
if n.ElseList != nil {
names = append(names, parseNode(n.ElseList)...)
}
return names
case *parse.PipeNode:
var names []string
for _, c := range n.Cmds {
for _, a := range c.Args {
names = append(names, parseNode(a)...)
}
}
return names
case *parse.ListNode:
var names []string
for _, n := range n.Nodes {
names = append(names, parseNode(n)...)
}
return names
case *parse.FieldNode:
return n.Ident
}
return nil
}

89
template/template_test.go Normal file
View File

@@ -0,0 +1,89 @@
package template
import (
"bufio"
"bytes"
"encoding/json"
"io"
"os"
"path/filepath"
"slices"
"testing"
"text/template"
"github.com/ollama/ollama/llm"
)
func TestNamed(t *testing.T) {
f, err := os.Open(filepath.Join("testdata", "templates.jsonl"))
if err != nil {
t.Fatal(err)
}
defer f.Close()
scanner := bufio.NewScanner(f)
for scanner.Scan() {
var ss map[string]string
if err := json.Unmarshal(scanner.Bytes(), &ss); err != nil {
t.Fatal(err)
}
for k, v := range ss {
t.Run(k, func(t *testing.T) {
kv := llm.KV{"tokenizer.chat_template": v}
s := kv.ChatTemplate()
r, err := Named(s)
if err != nil {
t.Fatal(err)
}
if r.Name != k {
t.Errorf("expected %q, got %q", k, r.Name)
}
var b bytes.Buffer
if _, err := io.Copy(&b, r.Reader()); err != nil {
t.Fatal(err)
}
tmpl, err := template.New(s).Parse(b.String())
if err != nil {
t.Fatal(err)
}
if tmpl.Tree.Root.String() == "" {
t.Errorf("empty %s template", k)
}
})
}
}
}
func TestParse(t *testing.T) {
cases := []struct {
template string
vars []string
}{
{"{{ .Prompt }}", []string{"prompt"}},
{"{{ .System }} {{ .Prompt }}", []string{"prompt", "system"}},
{"{{ .System }} {{ .Prompt }} {{ .Response }}", []string{"prompt", "response", "system"}},
{"{{ with .Tools }}{{ . }}{{ end }} {{ .System }} {{ .Prompt }}", []string{"prompt", "system", "tools"}},
{"{{ range .Messages }}{{ .Role }} {{ .Content }}{{ end }}", []string{"content", "messages", "role"}},
{"{{ range .Messages }}{{ if eq .Role \"system\" }}SYSTEM: {{ .Content }}{{ else if eq .Role \"user\" }}USER: {{ .Content }}{{ else if eq .Role \"assistant\" }}ASSISTANT: {{ .Content }}{{ end }}{{ end }}", []string{"content", "messages", "role"}},
{"{{ .Prompt }} {{ .Suffix }}", []string{"prompt", "suffix"}},
}
for _, tt := range cases {
t.Run("", func(t *testing.T) {
tmpl, err := Parse(tt.template)
if err != nil {
t.Fatal(err)
}
vars := tmpl.Vars()
if !slices.Equal(tt.vars, vars) {
t.Errorf("expected %v, got %v", tt.vars, vars)
}
})
}
}

View File

@@ -1,70 +0,0 @@
package templates
import (
"bytes"
"embed"
"encoding/json"
"errors"
"io"
"math"
"sync"
"github.com/agnivade/levenshtein"
)
//go:embed index.json
var indexBytes []byte
//go:embed *.gotmpl
var templatesFS embed.FS
var templatesOnce = sync.OnceValues(func() ([]*Template, error) {
var templates []*Template
if err := json.Unmarshal(indexBytes, &templates); err != nil {
return nil, err
}
for _, t := range templates {
bts, err := templatesFS.ReadFile(t.Name + ".gotmpl")
if err != nil {
return nil, err
}
// normalize line endings
t.Bytes = bytes.ReplaceAll(bts, []byte("\r\n"), []byte("\n"))
}
return templates, nil
})
type Template struct {
Name string `json:"name"`
Template string `json:"template"`
Bytes []byte
}
func (t Template) Reader() io.Reader {
return bytes.NewReader(t.Bytes)
}
func NamedTemplate(s string) (*Template, error) {
templates, err := templatesOnce()
if err != nil {
return nil, err
}
var template *Template
score := math.MaxInt
for _, t := range templates {
if s := levenshtein.ComputeDistance(s, t.Template); s < score {
score = s
template = t
}
}
if score < 100 {
return template, nil
}
return nil, errors.New("no matching template found")
}

View File

@@ -1,59 +0,0 @@
package templates
import (
"bufio"
"bytes"
"encoding/json"
"io"
"os"
"path/filepath"
"testing"
"text/template"
"github.com/ollama/ollama/llm"
)
func TestKVChatTemplate(t *testing.T) {
f, err := os.Open(filepath.Join("testdata", "templates.jsonl"))
if err != nil {
t.Fatal(err)
}
defer f.Close()
scanner := bufio.NewScanner(f)
for scanner.Scan() {
var ss map[string]string
if err := json.Unmarshal(scanner.Bytes(), &ss); err != nil {
t.Fatal(err)
}
for k, v := range ss {
t.Run(k, func(t *testing.T) {
kv := llm.KV{"tokenizer.chat_template": v}
s := kv.ChatTemplate()
r, err := NamedTemplate(s)
if err != nil {
t.Fatal(err)
}
if r.Name != k {
t.Errorf("expected %q, got %q", k, r.Name)
}
var b bytes.Buffer
if _, err := io.Copy(&b, r.Reader()); err != nil {
t.Fatal(err)
}
tmpl, err := template.New(s).Parse(b.String())
if err != nil {
t.Fatal(err)
}
if tmpl.Tree.Root.String() == "" {
t.Errorf("empty %s template", k)
}
})
}
}
}

View File

@@ -91,7 +91,6 @@ type Name struct {
Namespace string
Model string
Tag string
RawDigest string
}
// ParseName parses and assembles a Name from a name string. The
@@ -143,11 +142,6 @@ func ParseNameBare(s string) Name {
var n Name
var promised bool
s, n.RawDigest, promised = cutLast(s, "@")
if promised && n.RawDigest == "" {
n.RawDigest = MissingPart
}
// "/" is an illegal tag character, so we can use it to split the host
if strings.LastIndex(s, ":") > strings.LastIndex(s, "/") {
s, n.Tag, _ = cutPromised(s, ":")
@@ -222,10 +216,6 @@ func (n Name) String() string {
b.WriteByte(':')
b.WriteString(n.Tag)
}
if n.RawDigest != "" {
b.WriteByte('@')
b.WriteString(n.RawDigest)
}
return b.String()
}
@@ -250,16 +240,18 @@ func (n Name) DisplayShortest() string {
return sb.String()
}
func IsValidNamespace(namespace string) bool {
return isValidPart(kindNamespace, namespace)
// IsValidNamespace reports whether the provided string is a valid
// namespace.
func IsValidNamespace(s string) bool {
return isValidPart(kindNamespace, s)
}
// IsValid reports whether all parts of the name are present and valid. The
// digest is a special case, and is checked for validity only if present.
//
// Note: The digest check has been removed as is planned to be added back in
// at a later time.
func (n Name) IsValid() bool {
if n.RawDigest != "" && !isValidPart(kindDigest, n.RawDigest) {
return false
}
return n.IsFullyQualified()
}

View File

@@ -122,21 +122,6 @@ func TestParseNameParts(t *testing.T) {
},
wantFilepath: filepath.Join(part350, part80, part80, part80),
},
{
in: "@digest",
want: Name{
RawDigest: "digest",
},
wantValidDigest: false,
},
{
in: "model@sha256:123",
want: Name{
Model: "model",
RawDigest: "sha256:123",
},
wantValidDigest: true,
},
}
for _, tt := range cases {
@@ -160,22 +145,18 @@ var testCases = map[string]bool{ // name -> valid
"_why/_the/_lucky:_stiff": true,
// minimal
"h/n/m:t@d": true,
"h/n/m:t": true,
"host/namespace/model:tag": true,
"host/namespace/model": false,
"namespace/model": false,
"model": false,
"@sha256-1000000000000000000000000000000000000000000000000000000000000000": false,
"model@sha256-1000000000000000000000000000000000000000000000000000000000000000": false,
"model@sha256:1000000000000000000000000000000000000000000000000000000000000000": false,
// long (but valid)
part80 + "/" + part80 + "/" + part80 + ":" + part80: true,
part350 + "/" + part80 + "/" + part80 + ":" + part80: true,
"h/nn/mm:t@sha256-1000000000000000000000000000000000000000000000000000000000000000": true, // bare minimum part sizes
"h/nn/mm:t@sha256:1000000000000000000000000000000000000000000000000000000000000000": true, // bare minimum part sizes
"h/nn/mm:t": true, // bare minimum part sizes
// unqualified
"m": false,
@@ -196,11 +177,10 @@ var testCases = map[string]bool{ // name -> valid
"@": false,
// not starting with alphanum
"-hh/nn/mm:tt@dd": false,
"hh/-nn/mm:tt@dd": false,
"hh/nn/-mm:tt@dd": false,
"hh/nn/mm:-tt@dd": false,
"hh/nn/mm:tt@-dd": false,
"-hh/nn/mm:tt": false,
"hh/-nn/mm:tt": false,
"hh/nn/-mm:tt": false,
"hh/nn/mm:-tt": false,
// hosts
"host:https/namespace/model:tag": true,
@@ -334,7 +314,7 @@ func FuzzName(f *testing.F) {
f.Fuzz(func(t *testing.T, s string) {
n := ParseNameBare(s)
if n.IsValid() {
parts := [...]string{n.Host, n.Namespace, n.Model, n.Tag, n.RawDigest}
parts := [...]string{n.Host, n.Namespace, n.Model, n.Tag}
for _, part := range parts {
if part == ".." {
t.Errorf("unexpected .. as valid part")