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Author SHA1 Message Date
Roy Han
9357570d59 OpenAI Delete Endpoint 2024-06-14 16:28:22 -07:00
197 changed files with 2635 additions and 8502 deletions

View File

@@ -147,7 +147,7 @@ jobs:
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"
@@ -437,7 +437,6 @@ jobs:
env:
OLLAMA_SKIP_IMAGE_BUILD: '1'
PUSH: '1'
GH_TOKEN: ${{ github.token }}
steps:
- uses: actions/checkout@v4
- name: Set Version
@@ -461,20 +460,15 @@ jobs:
ls -lh dist/
(cd dist; sha256sum * > sha256sum.txt)
cat dist/sha256sum.txt
- name: Create or update Release
run: |
echo "Looking for existing release for ${{ env.RELEASE_VERSION }}"
OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${{ env.RELEASE_VERSION }}\") | .tagName")
if [ -n "$OLD_TAG" ]; then
echo "Updating release ${{ env.RELEASE_VERSION }} to point to new tag ${GITHUB_REF_NAME}"
gh release edit ${OLD_TAG} --tag ${GITHUB_REF_NAME}
else
echo "Creating new release ${{ env.RELEASE_VERSION }} pointing to tag ${GITHUB_REF_NAME}"
gh release create ${GITHUB_REF_NAME} \
--title ${{ env.RELEASE_VERSION }} \
--draft \
--generate-notes \
--prerelease
fi
echo "Uploading artifacts for tag ${GITHUB_REF_NAME}"
gh release upload ${GITHUB_REF_NAME} dist/* --clobber
- uses: ncipollo/release-action@v1
with:
name: ${{ env.RELEASE_VERSION }}
allowUpdates: true
artifacts: 'dist/*'
draft: true
prerelease: true
omitBodyDuringUpdate: true
generateReleaseNotes: true
omitDraftDuringUpdate: true
omitPrereleaseDuringUpdate: true
replacesArtifacts: true

View File

@@ -58,7 +58,6 @@ jobs:
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
@@ -80,7 +79,6 @@ 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
@@ -126,7 +124,7 @@ jobs:
strategy:
matrix:
rocm-version:
- '6.1.2'
- '6.0.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
@@ -169,7 +167,7 @@ jobs:
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"

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@@ -2,7 +2,7 @@ ARG GOLANG_VERSION=1.22.1
ARG CMAKE_VERSION=3.22.1
# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
ARG CUDA_VERSION=11.3.1
ARG ROCM_VERSION=6.1.2
ARG ROCM_VERSION=6.0.2
# Copy the minimal context we need to run the generate scripts
FROM scratch AS llm-code
@@ -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 rockylinux:8 AS cpu-builder-arm64
FROM --platform=linux/arm64 centos:7 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/gcc-toolset-10/root/usr/bin:$PATH
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS

View File

@@ -53,8 +53,8 @@ Here are some example models that can be downloaded:
| Llama 3 | 70B | 40GB | `ollama run llama3:70b` |
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
| Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` |
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
@@ -182,12 +182,6 @@ $ ollama run llama3 "Summarize this file: $(cat README.md)"
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
```
### Show model information
```
ollama show llama3
```
### List models on your computer
```
@@ -292,9 +286,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
- [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
- [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
- [AI Studio](https://github.com/MindWorkAI/AI-Studio)
### Terminal

View File

@@ -347,16 +347,7 @@ func (c *Client) Heartbeat(ctx context.Context) error {
return nil
}
// Embed generates embeddings from a model.
func (c *Client) Embed(ctx context.Context, req *EmbedRequest) (*EmbedResponse, error) {
var resp EmbedResponse
if err := c.do(ctx, http.MethodPost, "/api/embed", req, &resp); err != nil {
return nil, err
}
return &resp, nil
}
// Embeddings generates an embedding from a model.
// Embeddings generates embeddings from a model.
func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error) {
var resp EmbeddingResponse
if err := c.do(ctx, http.MethodPost, "/api/embeddings", req, &resp); err != nil {

View File

@@ -47,9 +47,6 @@ type GenerateRequest struct {
// Prompt is the textual prompt to send to the model.
Prompt string `json:"prompt"`
// Suffix is the text that comes after the inserted text.
Suffix string `json:"suffix"`
// System overrides the model's default system message/prompt.
System string `json:"system"`
@@ -100,9 +97,6 @@ type ChatRequest struct {
// followin the request.
KeepAlive *Duration `json:"keep_alive,omitempty"`
// Tools is an optional list of tools the model has access to.
Tools []Tool `json:"tools,omitempty"`
// Options lists model-specific options.
Options map[string]interface{} `json:"options"`
}
@@ -111,46 +105,9 @@ type ChatRequest struct {
// role ("system", "user", or "assistant"), the content and an optional list
// of images.
type Message struct {
Role string `json:"role"`
Content string `json:"content,omitempty"`
Images []ImageData `json:"images,omitempty"`
ToolCalls []ToolCall `json:"tool_calls,omitempty"`
}
type ToolCall struct {
Function struct {
Name string `json:"name"`
Arguments map[string]any `json:"arguments"`
} `json:"function"`
}
type Tool struct {
Type string `json:"type"`
Function struct {
Name string `json:"name"`
Description string `json:"description"`
Parameters struct {
Type string `json:"type"`
Required []string `json:"required"`
Properties map[string]struct {
Type string `json:"type"`
Description string `json:"description"`
Enum []string `json:"enum,omitempty"`
} `json:"properties"`
} `json:"parameters"`
} `json:"function"`
}
func (m *Message) UnmarshalJSON(b []byte) error {
type Alias Message
var a Alias
if err := json.Unmarshal(b, &a); err != nil {
return err
}
*m = Message(a)
m.Role = strings.ToLower(m.Role)
return nil
Role string `json:"role"`
Content string `json:"content"`
Images []ImageData `json:"images,omitempty"`
}
// ChatResponse is the response returned by [Client.Chat]. Its fields are
@@ -202,42 +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 *bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
// EmbedRequest is the request passed to [Client.Embed].
type EmbedRequest struct {
// Model is the model name.
Model string `json:"model"`
// Input is the input to embed.
Input any `json:"input"`
// KeepAlive controls how long the model will stay loaded in memory following
// this request.
KeepAlive *Duration `json:"keep_alive,omitempty"`
Truncate *bool `json:"truncate,omitempty"`
// Options lists model-specific options.
Options map[string]interface{} `json:"options"`
}
// EmbedResponse is the response from [Client.Embed].
type EmbedResponse struct {
Model string `json:"model"`
Embeddings [][]float32 `json:"embeddings"`
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].
@@ -286,12 +219,9 @@ type DeleteRequest struct {
// ShowRequest is the request passed to [Client.Show].
type ShowRequest struct {
Model string `json:"model"`
System string `json:"system"`
// Template is deprecated
Model string `json:"model"`
System string `json:"system"`
Template string `json:"template"`
Verbose bool `json:"verbose"`
Options map[string]interface{} `json:"options"`
@@ -301,16 +231,13 @@ type ShowRequest struct {
// ShowResponse is the response returned from [Client.Show].
type ShowResponse struct {
License string `json:"license,omitempty"`
Modelfile string `json:"modelfile,omitempty"`
Parameters string `json:"parameters,omitempty"`
Template string `json:"template,omitempty"`
System string `json:"system,omitempty"`
Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"`
ModifiedAt time.Time `json:"modified_at,omitempty"`
License string `json:"license,omitempty"`
Modelfile string `json:"modelfile,omitempty"`
Parameters string `json:"parameters,omitempty"`
Template string `json:"template,omitempty"`
System string `json:"system,omitempty"`
Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"`
}
// CopyRequest is the request passed to [Client.Copy].
@@ -383,13 +310,6 @@ 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"`
}
@@ -405,9 +325,6 @@ type GenerateResponse struct {
// Response is the textual response itself.
Response string `json:"response"`
// ToolCalls is the list of tools the model wants to call
ToolCalls []ToolCall `json:"tool_calls,omitempty"`
// Done specifies if the response is complete.
Done bool `json:"done"`
@@ -531,17 +448,6 @@ 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())
}
@@ -584,7 +490,7 @@ func DefaultOptions() Options {
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: nil,
UseMMap: true,
UseNUMA: false,
},
}
@@ -681,17 +587,6 @@ 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)
}

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@@ -2,7 +2,6 @@ package api
import (
"encoding/json"
"fmt"
"math"
"testing"
"time"
@@ -106,128 +105,3 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
})
}
}
func TestUseMmapParsingFromJSON(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req string
exp *bool
}{
{
name: "Undefined",
req: `{ }`,
exp: nil,
},
{
name: "True",
req: `{ "use_mmap": true }`,
exp: &tr,
},
{
name: "False",
req: `{ "use_mmap": false }`,
exp: &fa,
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
var oMap map[string]interface{}
err := json.Unmarshal([]byte(test.req), &oMap)
require.NoError(t, err)
opts := DefaultOptions()
err = opts.FromMap(oMap)
require.NoError(t, err)
assert.Equal(t, test.exp, opts.UseMMap)
})
}
}
func TestUseMmapFormatParams(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req map[string][]string
exp *bool
err error
}{
{
name: "True",
req: map[string][]string{
"use_mmap": {"true"},
},
exp: &tr,
err: nil,
},
{
name: "False",
req: map[string][]string{
"use_mmap": {"false"},
},
exp: &fa,
err: nil,
},
{
name: "Numeric True",
req: map[string][]string{
"use_mmap": {"1"},
},
exp: &tr,
err: nil,
},
{
name: "Numeric False",
req: map[string][]string{
"use_mmap": {"0"},
},
exp: &fa,
err: nil,
},
{
name: "invalid string",
req: map[string][]string{
"use_mmap": {"foo"},
},
exp: nil,
err: fmt.Errorf("invalid bool value [foo]"),
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
resp, err := FormatParams(test.req)
require.Equal(t, test.err, err)
respVal, ok := resp["use_mmap"]
if test.exp != nil {
assert.True(t, ok, "resp: %v", resp)
assert.Equal(t, *test.exp, *respVal.(*bool))
}
})
}
}
func TestMessage_UnmarshalJSON(t *testing.T) {
tests := []struct {
input string
expected string
}{
{`{"role": "USER", "content": "Hello!"}`, "user"},
{`{"role": "System", "content": "Initialization complete."}`, "system"},
{`{"role": "assistant", "content": "How can I help you?"}`, "assistant"},
{`{"role": "TOOl", "content": "Access granted."}`, "tool"},
}
for _, test := range tests {
var msg Message
if err := json.Unmarshal([]byte(test.input), &msg); err != nil {
t.Errorf("Unexpected error: %v", err)
}
if msg.Role != test.expected {
t.Errorf("role not lowercased: got %v, expected %v", msg.Role, test.expected)
}
}
}

View File

@@ -5,8 +5,6 @@ import (
"log/slog"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
)
@@ -26,7 +24,6 @@ func InitLogging() {
logFile = os.Stderr
// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
} else {
rotateLogs(AppLogFile)
logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
if err != nil {
slog.Error(fmt.Sprintf("failed to create server log %v", err))
@@ -49,32 +46,3 @@ func InitLogging() {
slog.Info("ollama app started")
}
func rotateLogs(logFile string) {
if _, err := os.Stat(logFile); os.IsNotExist(err) {
return
}
index := strings.LastIndex(logFile, ".")
pre := logFile[:index]
post := "." + logFile[index+1:]
for i := LogRotationCount; i > 0; i-- {
older := pre + "-" + strconv.Itoa(i) + post
newer := pre + "-" + strconv.Itoa(i-1) + post
if i == 1 {
newer = pre + post
}
if _, err := os.Stat(newer); err == nil {
if _, err := os.Stat(older); err == nil {
err := os.Remove(older)
if err != nil {
slog.Warn("Failed to remove older log", "older", older, "error", err)
continue
}
}
err := os.Rename(newer, older)
if err != nil {
slog.Warn("Failed to rotate log", "older", older, "newer", newer, "error", err)
}
}
}
}

View File

@@ -1,44 +0,0 @@
package lifecycle
import (
"os"
"path/filepath"
"strconv"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestRotateLogs(t *testing.T) {
logDir := t.TempDir()
logFile := filepath.Join(logDir, "testlog.log")
// No log exists
rotateLogs(logFile)
require.NoError(t, os.WriteFile(logFile, []byte("1"), 0644))
assert.FileExists(t, logFile)
// First rotation
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
// Should be a no-op without a new log
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
for i := 2; i <= LogRotationCount+1; i++ {
require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0644))
assert.FileExists(t, logFile)
rotateLogs(logFile)
assert.NoFileExists(t, logFile)
for j := 1; j < i; j++ {
assert.FileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(j)+".log"))
}
assert.NoFileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(i+1)+".log"))
}
}

View File

@@ -16,12 +16,11 @@ var (
AppDir = "/opt/Ollama"
AppDataDir = "/opt/Ollama"
// TODO - should there be a distinct log dir?
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
LogRotationCount = 5
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
)
func init() {

View File

@@ -54,7 +54,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
return nil, fmt.Errorf("failed to spawn server stderr pipe: %w", err)
}
rotateLogs(ServerLogFile)
// TODO - rotation
logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
if err != nil {
return nil, fmt.Errorf("failed to create server log: %w", err)

View File

@@ -88,15 +88,10 @@ DialogFontSize=12
[Files]
Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-{#ARCH}\*.dll"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-{#ARCH}\ollama_runners\*"; DestDir: "{app}\ollama_runners"; Flags: ignoreversion 64bit recursesubdirs
Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
#if DirExists("..\dist\windows-amd64\cuda")
Source: "..\dist\windows-amd64\cuda\*"; DestDir: "{app}\cuda\"; Flags: ignoreversion recursesubdirs
#endif
#if DirExists("..\dist\windows-amd64\oneapi")
Source: "..\dist\windows-amd64\oneapi\*"; DestDir: "{app}\oneapi\"; Flags: ignoreversion recursesubdirs
#endif
#if DirExists("..\dist\windows-amd64\rocm")
Source: "..\dist\windows-amd64\rocm\*"; DestDir: "{app}\rocm\"; Flags: ignoreversion recursesubdirs
#endif
@@ -127,10 +122,6 @@ Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\models"
Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\history"
; NOTE: if the user has a custom OLLAMA_MODELS it will be preserved
[InstallDelete]
Type: filesandordirs; Name: "{%TEMP}\ollama*"
Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
[Messages]
WizardReady=Ollama Windows Preview
ReadyLabel1=%nLet's get you up and running with your own large language models.

View File

@@ -162,6 +162,9 @@ func tempZipFiles(path string) (string, error) {
}
defer tempfile.Close()
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
detectContentType := func(path string) (string, error) {
f, err := os.Open(path)
if err != nil {
@@ -230,9 +233,6 @@ func tempZipFiles(path string) (string, error) {
files = append(files, tks...)
}
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
for _, file := range files {
f, err := os.Open(file)
if err != nil {
@@ -287,12 +287,38 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, er
}
func RunHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
name := args[0]
// check if the model exists on the server
show, err := client.Show(cmd.Context(), &api.ShowRequest{Name: name})
var statusError api.StatusError
switch {
case errors.As(err, &statusError) && statusError.StatusCode == http.StatusNotFound:
if err := PullHandler(cmd, []string{name}); err != nil {
return err
}
show, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
if err != nil {
return err
}
case err != nil:
return err
}
interactive := true
opts := runOptions{
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
MultiModal: slices.Contains(show.Details.Families, "clip"),
ParentModel: show.Details.ParentModel,
}
format, err := cmd.Flags().GetString("format")
@@ -336,38 +362,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
}
opts.WordWrap = !nowrap
// Fill out the rest of the options based on information about the
// model.
client, err := api.ClientFromEnvironment()
if err != nil {
return err
if !interactive {
return generate(cmd, opts)
}
name := args[0]
info, err := func() (*api.ShowResponse, error) {
showReq := &api.ShowRequest{Name: name}
info, err := client.Show(cmd.Context(), showReq)
var se api.StatusError
if errors.As(err, &se) && se.StatusCode == http.StatusNotFound {
if err := PullHandler(cmd, []string{name}); err != nil {
return nil, err
}
return client.Show(cmd.Context(), &api.ShowRequest{Name: name})
}
return info, err
}()
if err != nil {
return err
}
opts.MultiModal = slices.Contains(info.Details.Families, "clip")
opts.ParentModel = info.Details.ParentModel
opts.Messages = append(opts.Messages, info.Messages...)
if interactive {
return generateInteractive(cmd, opts)
}
return generate(cmd, opts)
return generateInteractive(cmd, opts)
}
func errFromUnknownKey(unknownKeyErr error) error {
@@ -580,6 +579,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
if len(args) != 1 {
return errors.New("missing model name")
}
license, errLicense := cmd.Flags().GetBool("license")
modelfile, errModelfile := cmd.Flags().GetBool("modelfile")
parameters, errParams := cmd.Flags().GetBool("parameters")
@@ -622,6 +625,8 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
if flagsSet > 1 {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
} else if flagsSet == 0 {
return errors.New("one of '--license', '--modelfile', '--parameters', '--system', or '--template' must be specified")
}
req := api.ShowRequest{Name: args[0]}
@@ -630,141 +635,22 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
if flagsSet == 1 {
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Println(resp.System)
case "template":
fmt.Println(resp.Template)
}
return nil
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Println(resp.System)
case "template":
fmt.Println(resp.Template)
}
showInfo(resp)
return nil
}
func showInfo(resp *api.ShowResponse) {
arch := resp.ModelInfo["general.architecture"].(string)
modelData := [][]string{
{"arch", arch},
{"parameters", resp.Details.ParameterSize},
{"quantization", resp.Details.QuantizationLevel},
{"context length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64))},
{"embedding length", fmt.Sprintf("%v", resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64))},
}
mainTableData := [][]string{
{"Model"},
{renderSubTable(modelData, false)},
}
if resp.ProjectorInfo != nil {
projectorData := [][]string{
{"arch", "clip"},
{"parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))},
}
if projectorType, ok := resp.ProjectorInfo["clip.projector_type"]; ok {
projectorData = append(projectorData, []string{"projector type", projectorType.(string)})
}
projectorData = append(projectorData,
[]string{"embedding length", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.embedding_length"].(float64))},
[]string{"projection dimensionality", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.projection_dim"].(float64))},
)
mainTableData = append(mainTableData,
[]string{"Projector"},
[]string{renderSubTable(projectorData, false)},
)
}
if resp.Parameters != "" {
mainTableData = append(mainTableData, []string{"Parameters"}, []string{formatParams(resp.Parameters)})
}
if resp.System != "" {
mainTableData = append(mainTableData, []string{"System"}, []string{renderSubTable(twoLines(resp.System), true)})
}
if resp.License != "" {
mainTableData = append(mainTableData, []string{"License"}, []string{renderSubTable(twoLines(resp.License), true)})
}
table := tablewriter.NewWriter(os.Stdout)
table.SetAutoWrapText(false)
table.SetBorder(false)
table.SetAlignment(tablewriter.ALIGN_LEFT)
for _, v := range mainTableData {
table.Append(v)
}
table.Render()
}
func renderSubTable(data [][]string, file bool) string {
var buf bytes.Buffer
table := tablewriter.NewWriter(&buf)
table.SetAutoWrapText(!file)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding("\t")
table.SetAlignment(tablewriter.ALIGN_LEFT)
for _, v := range data {
table.Append(v)
}
table.Render()
renderedTable := buf.String()
lines := strings.Split(renderedTable, "\n")
for i, line := range lines {
lines[i] = "\t" + line
}
return strings.Join(lines, "\n")
}
func twoLines(s string) [][]string {
lines := strings.Split(s, "\n")
res := [][]string{}
count := 0
for _, line := range lines {
line = strings.TrimSpace(line)
if line != "" {
count++
res = append(res, []string{line})
if count == 2 {
return res
}
}
}
return res
}
func formatParams(s string) string {
lines := strings.Split(s, "\n")
table := [][]string{}
for _, line := range lines {
table = append(table, strings.Fields(line))
}
return renderSubTable(table, false)
}
func CopyHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
@@ -843,6 +729,7 @@ type runOptions struct {
WordWrap bool
Format string
System string
Template string
Images []api.ImageData
Options map[string]interface{}
MultiModal bool
@@ -1036,6 +923,7 @@ func generate(cmd *cobra.Command, opts runOptions) error {
Images: opts.Images,
Format: opts.Format,
System: opts.System,
Template: opts.Template,
Options: opts.Options,
KeepAlive: opts.KeepAlive,
}

View File

@@ -27,43 +27,69 @@ const (
MultilineNone MultilineState = iota
MultilinePrompt
MultilineSystem
MultilineTemplate
)
func loadModel(cmd *cobra.Command, opts *runOptions) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
client, err := api.ClientFromEnvironment()
showReq := api.ShowRequest{Name: opts.Model}
showResp, err := client.Show(cmd.Context(), &showReq)
if err != nil {
return err
}
opts.MultiModal = slices.Contains(showResp.Details.Families, "clip")
opts.ParentModel = showResp.Details.ParentModel
chatReq := &api.ChatRequest{
Model: opts.Model,
KeepAlive: opts.KeepAlive,
if len(showResp.Messages) > 0 {
opts.Messages = append(opts.Messages, showResp.Messages...)
}
return client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
chatReq := &api.ChatRequest{
Model: opts.Model,
Messages: []api.Message{},
}
if opts.KeepAlive != nil {
chatReq.KeepAlive = opts.KeepAlive
}
err = client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
p.StopAndClear()
for _, msg := range opts.Messages {
switch msg.Role {
case "user":
fmt.Printf(">>> %s\n", msg.Content)
case "assistant":
state := &displayResponseState{}
displayResponse(msg.Content, opts.WordWrap, state)
fmt.Println()
fmt.Println()
if len(opts.Messages) > 0 {
for _, msg := range opts.Messages {
switch msg.Role {
case "user":
fmt.Printf(">>> %s\n", msg.Content)
case "assistant":
state := &displayResponseState{}
displayResponse(msg.Content, opts.WordWrap, state)
fmt.Println()
fmt.Println()
}
}
}
return nil
})
if err != nil {
return err
}
return nil
}
func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = make([]api.Message, 0)
err := loadModel(cmd, &opts)
if err != nil {
return err
@@ -93,6 +119,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Fprintln(os.Stderr, "Available Commands:")
fmt.Fprintln(os.Stderr, " /set parameter ... Set a parameter")
fmt.Fprintln(os.Stderr, " /set system <string> Set system message")
fmt.Fprintln(os.Stderr, " /set template <string> Set prompt template")
fmt.Fprintln(os.Stderr, " /set history Enable history")
fmt.Fprintln(os.Stderr, " /set nohistory Disable history")
fmt.Fprintln(os.Stderr, " /set wordwrap Enable wordwrap")
@@ -202,6 +229,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
fmt.Println("Set system message.")
sb.Reset()
case MultilineTemplate:
opts.Template = sb.String()
fmt.Println("Set prompt template.")
sb.Reset()
}
multiline = MultilineNone
@@ -320,13 +351,17 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
}
fmt.Printf("Set parameter '%s' to '%s'\n", args[2], strings.Join(params, ", "))
opts.Options[args[2]] = fp[args[2]]
case "system":
case "system", "template":
if len(args) < 3 {
usageSet()
continue
}
multiline = MultilineSystem
if args[1] == "system" {
multiline = MultilineSystem
} else if args[1] == "template" {
multiline = MultilineTemplate
}
line := strings.Join(args[2:], " ")
line, ok := strings.CutPrefix(line, `"""`)
@@ -346,17 +381,23 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
continue
}
opts.System = sb.String() // for display in modelfile
newMessage := api.Message{Role: "system", Content: sb.String()}
// Check if the slice is not empty and the last message is from 'system'
if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
// Replace the last message
opts.Messages[len(opts.Messages)-1] = newMessage
} else {
opts.Messages = append(opts.Messages, newMessage)
if args[1] == "system" {
opts.System = sb.String() // for display in modelfile
newMessage := api.Message{Role: "system", Content: sb.String()}
// Check if the slice is not empty and the last message is from 'system'
if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
// Replace the last message
opts.Messages[len(opts.Messages)-1] = newMessage
} else {
opts.Messages = append(opts.Messages, newMessage)
}
fmt.Println("Set system message.")
sb.Reset()
} else if args[1] == "template" {
opts.Template = sb.String()
fmt.Println("Set prompt template.")
sb.Reset()
}
fmt.Println("Set system message.")
sb.Reset()
sb.Reset()
continue
@@ -377,6 +418,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
req := &api.ShowRequest{
Name: opts.Model,
System: opts.System,
Template: opts.Template,
Options: opts.Options,
}
resp, err := client.Show(cmd.Context(), req)
@@ -387,7 +429,15 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
switch args[1] {
case "info":
showInfo(resp)
fmt.Println("Model details:")
if len(resp.Details.Families) > 0 {
fmt.Printf("Family %s\n", strings.Join(resp.Details.Families, ", "))
} else if resp.Details.Family != "" {
fmt.Printf("Family %s\n", resp.Details.Family)
}
fmt.Printf("Parameter Size %s\n", resp.Details.ParameterSize)
fmt.Printf("Quantization Level %s\n", resp.Details.QuantizationLevel)
fmt.Println("")
case "license":
if resp.License == "" {
fmt.Println("No license was specified for this model.")
@@ -420,9 +470,12 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Println("No system message was specified for this model.")
}
case "template":
if resp.Template != "" {
switch {
case opts.Template != "":
fmt.Println(opts.Template + "\n")
case resp.Template != "":
fmt.Println(resp.Template)
} else {
default:
fmt.Println("No prompt template was specified for this model.")
}
default:
@@ -516,6 +569,10 @@ func buildModelfile(opts runOptions) string {
fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
}
if opts.Template != "" {
fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
}
keys := make([]string, 0)
for k := range opts.Options {
keys = append(keys, k)

View File

@@ -59,6 +59,7 @@ func TestModelfileBuilder(t *testing.T) {
opts := runOptions{
Model: "hork",
System: "You are part horse and part shark, but all hork. Do horklike things",
Template: "This is a template.",
Messages: []api.Message{
{Role: "user", Content: "Hey there hork!"},
{Role: "assistant", Content: "Yes it is true, I am half horse, half shark."},
@@ -74,6 +75,7 @@ func TestModelfileBuilder(t *testing.T) {
mf := buildModelfile(opts)
expectedModelfile := `FROM {{.Model}}
SYSTEM """{{.System}}"""
TEMPLATE """{{.Template}}"""
PARAMETER penalize_newline false
PARAMETER seed 42
PARAMETER stop [hi there]
@@ -95,6 +97,7 @@ MESSAGE assistant """Yes it is true, I am half horse, half shark."""
mf = buildModelfile(opts)
expectedModelfile = `FROM {{.ParentModel}}
SYSTEM """{{.System}}"""
TEMPLATE """{{.Template}}"""
PARAMETER penalize_newline false
PARAMETER seed 42
PARAMETER stop [hi there]

View File

@@ -26,7 +26,7 @@ All durations are returned in nanoseconds.
### Streaming responses
Certain endpoints stream responses as JSON objects. Streaming can be disabled by providing `{"stream": false}` for these endpoints.
Certain endpoints stream responses as JSON objects and can optional return non-streamed responses.
## Generate a completion
@@ -777,12 +777,11 @@ A single JSON object will be returned.
POST /api/show
```
Show information about a model including details, modelfile, template, parameters, license, system prompt.
Show information about a model including details, modelfile, template, parameters, license, and system prompt.
### Parameters
- `name`: name of the model to show
- `verbose`: (optional) if set to `true`, returns full data for verbose response fields
### Examples
@@ -799,40 +798,14 @@ curl http://localhost:11434/api/show -d '{
```json
{
"modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llava:latest\n\nFROM /Users/matt/.ollama/models/blobs/sha256:200765e1283640ffbd013184bf496e261032fa75b99498a9613be4e94d63ad52\nTEMPLATE \"\"\"{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: \"\"\"\nPARAMETER num_ctx 4096\nPARAMETER stop \"\u003c/s\u003e\"\nPARAMETER stop \"USER:\"\nPARAMETER stop \"ASSISTANT:\"",
"parameters": "num_keep 24\nstop \"<|start_header_id|>\"\nstop \"<|end_header_id|>\"\nstop \"<|eot_id|>\"",
"template": "{{ 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|>",
"parameters": "num_ctx 4096\nstop \u003c/s\u003e\nstop USER:\nstop ASSISTANT:",
"template": "{{ .System }}\nUSER: {{ .Prompt }}\nASSISTANT: ",
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": [
"llama"
],
"parameter_size": "8.0B",
"families": ["llama", "clip"],
"parameter_size": "7B",
"quantization_level": "Q4_0"
},
"model_info": {
"general.architecture": "llama",
"general.file_type": 2,
"general.parameter_count": 8030261248,
"general.quantization_version": 2,
"llama.attention.head_count": 32,
"llama.attention.head_count_kv": 8,
"llama.attention.layer_norm_rms_epsilon": 0.00001,
"llama.block_count": 32,
"llama.context_length": 8192,
"llama.embedding_length": 4096,
"llama.feed_forward_length": 14336,
"llama.rope.dimension_count": 128,
"llama.rope.freq_base": 500000,
"llama.vocab_size": 128256,
"tokenizer.ggml.bos_token_id": 128000,
"tokenizer.ggml.eos_token_id": 128009,
"tokenizer.ggml.merges": [], // populates if `verbose=true`
"tokenizer.ggml.model": "gpt2",
"tokenizer.ggml.pre": "llama-bpe",
"tokenizer.ggml.token_type": [], // populates if `verbose=true`
"tokenizer.ggml.tokens": [] // populates if `verbose=true`
}
}
```

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="-DGGML_AVX=on -DGGML_AVX2=on -DGGML_F16C=on -DGGML_FMA=on" go generate ./...
OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
go build .
```
@@ -114,18 +114,15 @@ If you have Docker available, you can build linux binaries with `./scripts/build
### Windows
Note: The Windows build for Ollama is still under development.
Note: The windows build for Ollama is still under development.
First, install required tools:
Install required tools:
- MSVC toolchain - C/C++ and cmake as minimal requirements
- Go version 1.22 or higher
- MinGW (pick one variant) with GCC.
- [MinGW-w64](https://www.mingw-w64.org/)
- [MSYS2](https://www.msys2.org/)
- The `ThreadJob` Powershell module: `Install-Module -Name ThreadJob -Scope CurrentUser`
Then, build the `ollama` binary:
```powershell
$env:CGO_ENABLED="1"

View File

@@ -257,19 +257,3 @@ If you wish to override the `OLLAMA_KEEP_ALIVE` setting, use the `keep_alive` AP
## How do I manage the maximum number of requests the Ollama server can queue?
If too many requests are sent to the server, it will respond with a 503 error indicating the server is overloaded. You can adjust how many requests may be queue by setting `OLLAMA_MAX_QUEUE`.
## How does Ollama handle concurrent requests?
Ollama supports two levels of concurrent processing. If your system has sufficient available memory (system memory when using CPU inference, or VRAM for GPU inference) then multiple models can be loaded at the same time. For a given model, if there is sufficient available memory when the model is loaded, it is configured to allow parallel request processing.
If there is insufficient available memory to load a new model request while one or more models are already loaded, all new requests will be queued until the new model can be loaded. As prior models become idle, one or more will be unloaded to make room for the new model. Queued requests will be processed in order. When using GPU inference new models must be able to completely fit in VRAM to allow concurrent model loads.
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 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 v6.2 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

@@ -8,7 +8,7 @@ Check your compute compatibility to see if your card is supported:
| Compute Capability | Family | Cards |
| ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
| 9.0 | NVIDIA | `H100` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080 SUPER` `RTX 4080` `RTX 4070 Ti SUPER` `RTX 4070 Ti` `RTX 4070 SUPER` `RTX 4070` `RTX 4060 Ti` `RTX 4060` |
| 8.9 | GeForce RTX 40xx | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti` |
| | NVIDIA Professional | `L4` `L40` `RTX 6000` |
| 8.6 | GeForce RTX 30xx | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060` |
| | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2` |
@@ -18,7 +18,7 @@ Check your compute compatibility to see if your card is supported:
| | Quadro | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000` |
| 7.0 | NVIDIA | `TITAN V` `V100` `Quadro GV100` |
| 6.1 | NVIDIA TITAN | `TITAN Xp` `TITAN X` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050 Ti` `GTX 1050` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050` |
| | Quadro | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
| | Tesla | `P40` `P4` |
| 6.0 | NVIDIA | `Tesla P100` `Quadro GP100` |

View File

@@ -47,13 +47,19 @@ success
### Supported Quantizations
<details>
<summary>Legacy Quantization</summary>
- `Q4_0`
- `Q4_1`
- `Q5_0`
- `Q5_1`
- `Q8_0`
#### K-means Quantizations
</details>
<details>
<summary>K-means Quantization</summary>`
- `Q3_K_S`
- `Q3_K_M`
@@ -64,6 +70,11 @@ success
- `Q5_K_M`
- `Q6_K`
</details>
> [!NOTE]
> Activation-aware Weight Quantization (i.e. IQ) are not currently supported for automatic quantization however you can still import the quantized model into Ollama, see [Import GGUF](#import-gguf).
## Template Detection
> [!NOTE]

View File

@@ -27,11 +27,6 @@ chat_completion = client.chat.completions.create(
],
model='llama3',
)
completion = client.completions.create(
model="llama3",
prompt="Say this is a test"
)
```
### OpenAI JavaScript library
@@ -50,11 +45,6 @@ const chatCompletion = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'llama3',
})
const completion = await openai.completions.create({
model: "llama3",
prompt: "Say this is a test.",
})
```
### `curl`
@@ -75,13 +65,6 @@ curl http://localhost:11434/v1/chat/completions \
}
]
}'
curl http://localhost:11434/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "llama3",
"prompt": "Say this is a test"
}'
```
## Endpoints
@@ -119,71 +102,10 @@ curl http://localhost:11434/v1/completions \
- [ ] `user`
- [ ] `n`
### `/v1/completions`
#### Supported features
- [x] Completions
- [x] Streaming
- [x] JSON mode
- [x] Reproducible outputs
- [ ] Logprobs
#### Supported request fields
- [x] `model`
- [x] `prompt`
- [x] `frequency_penalty`
- [x] `presence_penalty`
- [x] `seed`
- [x] `stop`
- [x] `stream`
- [x] `temperature`
- [x] `top_p`
- [x] `max_tokens`
- [x] `suffix`
- [ ] `best_of`
- [ ] `echo`
- [ ] `logit_bias`
- [ ] `user`
- [ ] `n`
#### Notes
- `prompt` currently only accepts a string
### `/v1/completions`
#### Supported features
- [x] Completions
- [x] Streaming
- [x] JSON mode
- [x] Reproducible outputs
- [ ] Logprobs
#### Supported request fields
- [x] `model`
- [x] `prompt`
- [x] `frequency_penalty`
- [x] `presence_penalty`
- [x] `seed`
- [x] `stop`
- [x] `stream`
- [x] `temperature`
- [x] `top_p`
- [x] `max_tokens`
- [ ] `best_of`
- [ ] `echo`
- [ ] `suffix`
- [ ] `logit_bias`
- [ ] `user`
- [ ] `n`
#### Notes
- `prompt` currently only accepts a string
- Setting `seed` will always set `temperature` to `0`
- `finish_reason` will always be `stop`
- `usage.prompt_tokens` will be 0 for completions where prompt evaluation is cached
## Models

View File

@@ -22,7 +22,7 @@ docker logs <container-name>
If manually running `ollama serve` in a terminal, the logs will be on that terminal.
When you run Ollama on **Windows**, there are a few different locations. You can view them in the explorer window by hitting `<cmd>+R` and type in:
- `explorer %LOCALAPPDATA%\Ollama` to view logs. The most recent server logs will be in `server.log` and older logs will be in `server-#.log`
- `explorer %LOCALAPPDATA%\Ollama` to view logs
- `explorer %LOCALAPPDATA%\Programs\Ollama` to browse the binaries (The installer adds this to your user PATH)
- `explorer %HOMEPATH%\.ollama` to browse where models and configuration is stored
- `explorer %TEMP%` where temporary executable files are stored in one or more `ollama*` directories
@@ -70,18 +70,14 @@ 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/
## NVIDIA GPU Discovery
## Container fails to run on NVIDIA GPU
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.
Make sure you've set up the container runtime first as described in [docker.md](./docker.md)
### Linux NVIDIA Troubleshooting
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
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`
- 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`
- 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
@@ -89,8 +85,3 @@ Sometimes the Ollama can have difficulties initializing the GPU. When you check
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 22H2 or newer, Home or Pro
* Windows 10 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
@@ -39,8 +39,8 @@ server.
Ollama on Windows stores files in a few different locations. You can view them in
the explorer window by hitting `<cmd>+R` and type in:
- `explorer %LOCALAPPDATA%\Ollama` contains logs, and downloaded updates
- *app.log* contains most resent logs from the GUI application
- *server.log* contains the most recent server logs
- *app.log* contains logs from the GUI application
- *server.log* contains the server logs
- *upgrade.log* contains log output for upgrades
- `explorer %LOCALAPPDATA%\Programs\Ollama` contains the binaries (The installer adds this to your user PATH)
- `explorer %HOMEPATH%\.ollama` contains models and configuration

View File

@@ -4,14 +4,12 @@ import (
"errors"
"fmt"
"log/slog"
"math"
"net"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"time"
)
type OllamaHost struct {
@@ -36,17 +34,17 @@ var (
// Set via OLLAMA_HOST in the environment
Host *OllamaHost
// Set via OLLAMA_KEEP_ALIVE in the environment
KeepAlive time.Duration
KeepAlive string
// 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_MAX_VRAM in the environment
MaxVRAM uint64
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_MAX_VRAM in the environment
MaxVRAM uint64
// Set via OLLAMA_NOHISTORY in the environment
NoHistory bool
// Set via OLLAMA_NOPRUNE in the environment
@@ -55,23 +53,8 @@ var (
NumParallel int
// Set via OLLAMA_RUNNERS_DIR in the environment
RunnersDir string
// Set via OLLAMA_SCHED_SPREAD in the environment
SchedSpread bool
// Set via OLLAMA_TMPDIR in the environment
TmpDir string
// Set via OLLAMA_INTEL_GPU in the environment
IntelGpu bool
// Set via CUDA_VISIBLE_DEVICES in the environment
CudaVisibleDevices string
// Set via HIP_VISIBLE_DEVICES in the environment
HipVisibleDevices string
// Set via ROCR_VISIBLE_DEVICES in the environment
RocrVisibleDevices string
// Set via GPU_DEVICE_ORDINAL in the environment
GpuDeviceOrdinal string
// Set via HSA_OVERRIDE_GFX_VERSION in the environment
HsaOverrideGfxVersion string
)
type EnvVar struct {
@@ -81,33 +64,23 @@ type EnvVar struct {
}
func AsMap() map[string]EnvVar {
ret := map[string]EnvVar{
return map[string]EnvVar{
"OLLAMA_DEBUG": {"OLLAMA_DEBUG", Debug, "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
"OLLAMA_FLASH_ATTENTION": {"OLLAMA_FLASH_ATTENTION", FlashAttention, "Enabled flash attention"},
"OLLAMA_HOST": {"OLLAMA_HOST", Host, "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_KEEP_ALIVE": {"OLLAMA_KEEP_ALIVE", KeepAlive, "The duration that models stay loaded in memory (default \"5m\")"},
"OLLAMA_LLM_LIBRARY": {"OLLAMA_LLM_LIBRARY", LLMLibrary, "Set LLM library to bypass autodetection"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models per GPU"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models (default 1)"},
"OLLAMA_MAX_QUEUE": {"OLLAMA_MAX_QUEUE", MaxQueuedRequests, "Maximum number of queued requests"},
"OLLAMA_MAX_VRAM": {"OLLAMA_MAX_VRAM", MaxVRAM, "Maximum VRAM"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", ModelsDir, "The path to the models directory"},
"OLLAMA_NOHISTORY": {"OLLAMA_NOHISTORY", NoHistory, "Do not preserve readline history"},
"OLLAMA_NOPRUNE": {"OLLAMA_NOPRUNE", NoPrune, "Do not prune model blobs on startup"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests (default 1)"},
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", AllowOrigins, "A comma separated list of allowed origins"},
"OLLAMA_RUNNERS_DIR": {"OLLAMA_RUNNERS_DIR", RunnersDir, "Location for runners"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread, "Always schedule model across all GPUs"},
"OLLAMA_TMPDIR": {"OLLAMA_TMPDIR", TmpDir, "Location for temporary files"},
}
if runtime.GOOS != "darwin" {
ret["CUDA_VISIBLE_DEVICES"] = EnvVar{"CUDA_VISIBLE_DEVICES", CudaVisibleDevices, "Set which NVIDIA devices are visible"}
ret["HIP_VISIBLE_DEVICES"] = EnvVar{"HIP_VISIBLE_DEVICES", HipVisibleDevices, "Set which AMD devices are visible"}
ret["ROCR_VISIBLE_DEVICES"] = EnvVar{"ROCR_VISIBLE_DEVICES", RocrVisibleDevices, "Set which AMD devices are visible"}
ret["GPU_DEVICE_ORDINAL"] = EnvVar{"GPU_DEVICE_ORDINAL", GpuDeviceOrdinal, "Set which AMD devices are visible"}
ret["HSA_OVERRIDE_GFX_VERSION"] = EnvVar{"HSA_OVERRIDE_GFX_VERSION", HsaOverrideGfxVersion, "Override the gfx used for all detected AMD GPUs"}
ret["OLLAMA_INTEL_GPU"] = EnvVar{"OLLAMA_INTEL_GPU", IntelGpu, "Enable experimental Intel GPU detection"}
}
return ret
}
func Values() map[string]string {
@@ -131,10 +104,9 @@ func clean(key string) string {
func init() {
// default values
NumParallel = 0 // Autoselect
MaxRunners = 0 // Autoselect
NumParallel = 1
MaxRunners = 1
MaxQueuedRequests = 512
KeepAlive = 5 * time.Minute
LoadConfig()
}
@@ -208,8 +180,8 @@ func LoadConfig() {
if onp := clean("OLLAMA_NUM_PARALLEL"); onp != "" {
val, err := strconv.Atoi(onp)
if err != nil {
slog.Error("invalid setting, ignoring", "OLLAMA_NUM_PARALLEL", onp, "error", err)
if err != nil || val <= 0 {
slog.Error("invalid setting must be greater than zero", "OLLAMA_NUM_PARALLEL", onp, "error", err)
} else {
NumParallel = val
}
@@ -219,15 +191,6 @@ func LoadConfig() {
NoHistory = true
}
if spread := clean("OLLAMA_SCHED_SPREAD"); spread != "" {
s, err := strconv.ParseBool(spread)
if err == nil {
SchedSpread = s
} else {
SchedSpread = true
}
}
if noprune := clean("OLLAMA_NOPRUNE"); noprune != "" {
NoPrune = true
}
@@ -254,7 +217,7 @@ func LoadConfig() {
if maxRunners != "" {
m, err := strconv.Atoi(maxRunners)
if err != nil {
slog.Error("invalid setting, ignoring", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
slog.Error("invalid setting", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
} else {
MaxRunners = m
}
@@ -263,16 +226,13 @@ func LoadConfig() {
if onp := os.Getenv("OLLAMA_MAX_QUEUE"); onp != "" {
p, err := strconv.Atoi(onp)
if err != nil || p <= 0 {
slog.Error("invalid setting, ignoring", "OLLAMA_MAX_QUEUE", onp, "error", err)
slog.Error("invalid setting", "OLLAMA_MAX_QUEUE", onp, "error", err)
} else {
MaxQueuedRequests = p
}
}
ka := clean("OLLAMA_KEEP_ALIVE")
if ka != "" {
loadKeepAlive(ka)
}
KeepAlive = clean("OLLAMA_KEEP_ALIVE")
var err error
ModelsDir, err = getModelsDir()
@@ -284,16 +244,6 @@ func LoadConfig() {
if err != nil {
slog.Error("invalid setting", "OLLAMA_HOST", Host, "error", err, "using default port", Host.Port)
}
if set, err := strconv.ParseBool(clean("OLLAMA_INTEL_GPU")); err == nil {
IntelGpu = set
}
CudaVisibleDevices = clean("CUDA_VISIBLE_DEVICES")
HipVisibleDevices = clean("HIP_VISIBLE_DEVICES")
RocrVisibleDevices = clean("ROCR_VISIBLE_DEVICES")
GpuDeviceOrdinal = clean("GPU_DEVICE_ORDINAL")
HsaOverrideGfxVersion = clean("HSA_OVERRIDE_GFX_VERSION")
}
func getModelsDir() (string, error) {
@@ -350,24 +300,3 @@ 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

@@ -2,10 +2,8 @@ package envconfig
import (
"fmt"
"math"
"net"
"testing"
"time"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
@@ -25,21 +23,6 @@ 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) {

3
go.mod
View File

@@ -18,7 +18,6 @@ require (
require (
github.com/agnivade/levenshtein v1.1.1
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/google/go-cmp v0.6.0
github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
@@ -72,7 +71,7 @@ require (
golang.org/x/net v0.25.0 // indirect
golang.org/x/sys v0.20.0
golang.org/x/term v0.20.0
golang.org/x/text v0.15.0
golang.org/x/text v0.15.0 // indirect
google.golang.org/protobuf v1.34.1
gopkg.in/yaml.v3 v3.0.1 // indirect
)

View File

@@ -49,17 +49,9 @@ func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
}
func commonAMDValidateLibDir() (string, error) {
// Favor our bundled version
// Installer payload location if we're running the installed binary
exe, err := os.Executable()
if err == nil {
rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
if rocmLibUsable(rocmTargetDir) {
slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
return rocmTargetDir, nil
}
}
// We try to favor system paths first, so that we can wire up the subprocess to use
// the system version. Only use our bundled version if the system version doesn't work
// This gives users a more recovery options if versions have subtle problems at runtime
// Prefer explicit HIP env var
hipPath := os.Getenv("HIP_PATH")
@@ -95,5 +87,14 @@ func commonAMDValidateLibDir() (string, error) {
}
}
// Installer payload location if we're running the installed binary
exe, err := os.Executable()
if err == nil {
rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
if rocmLibUsable(rocmTargetDir) {
slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
return rocmTargetDir, nil
}
}
return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
}

View File

@@ -84,8 +84,9 @@ func (hl *HipLib) AMDDriverVersion() (driverMajor, driverMinor int, err error) {
}
slog.Debug("hipDriverGetVersion", "version", version)
driverMajor = version / 10000000
driverMinor = (version - (driverMajor * 10000000)) / 100000
// TODO - this isn't actually right, but the docs claim hipDriverGetVersion isn't accurate anyway...
driverMajor = version / 1000
driverMinor = (version - (driverMajor * 1000)) / 10
return driverMajor, driverMinor, nil
}

View File

@@ -13,7 +13,6 @@ import (
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
@@ -26,16 +25,7 @@ const (
// Prefix with the node dir
GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
// Direct Rendering Manager sysfs location
DRMDeviceDirGlob = "/sys/class/drm/card*/device"
DRMTotalMemoryFile = "mem_info_vram_total"
DRMUsedMemoryFile = "mem_info_vram_used"
// In hex; properties file is in decimal
DRMUniqueIDFile = "unique_id"
DRMVendorFile = "vendor"
DRMDeviceFile = "device"
GPUUsedMemoryFileGlob = "mem_banks/*/used_memory"
)
var (
@@ -45,8 +35,8 @@ var (
)
// Gather GPU information from the amdgpu driver if any supported GPUs are detected
func AMDGetGPUInfo() []RocmGPUInfo {
resp := []RocmGPUInfo{}
func AMDGetGPUInfo() []GpuInfo {
resp := []GpuInfo{}
if !AMDDetected() {
return resp
}
@@ -60,9 +50,9 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
var visibleDevices []string
hipVD := envconfig.HipVisibleDevices // zero based index only
rocrVD := envconfig.RocrVisibleDevices // zero based index or UUID, but consumer cards seem to not support UUID
gpuDO := envconfig.GpuDeviceOrdinal // zero based index
hipVD := os.Getenv("HIP_VISIBLE_DEVICES") // zero based index only
rocrVD := os.Getenv("ROCR_VISIBLE_DEVICES") // zero based index or UUID, but consumer cards seem to not support UUID
gpuDO := os.Getenv("GPU_DEVICE_ORDINAL") // zero based index
switch {
// TODO is this priorty order right?
case hipVD != "":
@@ -75,7 +65,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
visibleDevices = strings.Split(gpuDO, ",")
}
gfxOverride := envconfig.HsaOverrideGfxVersion
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
var supported []string
libDir := ""
@@ -100,7 +90,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
scanner := bufio.NewScanner(fp)
isCPU := false
var major, minor, patch uint64
var vendor, device, uniqueID uint64
var vendor, device uint64
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
// Note: we could also use "cpu_cores_count X" where X is greater than zero to detect CPUs
@@ -131,43 +121,30 @@ func AMDGetGPUInfo() []RocmGPUInfo {
} else if strings.HasPrefix(line, "vendor_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "vendor_id", line)
slog.Debug("malformed vendor_id", "vendor_id", line)
continue
}
vendor, err = strconv.ParseUint(ver[1], 10, 64)
vendor, err = strconv.ParseUint(ver[1], 10, 32)
if err != nil {
slog.Debug("malformed", "vendor_id", line, "error", err)
slog.Debug("malformed vendor_id" + line)
}
} else if strings.HasPrefix(line, "device_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "device_id", line)
slog.Debug("malformed device_id", "device_id", line)
continue
}
device, err = strconv.ParseUint(ver[1], 10, 64)
device, err = strconv.ParseUint(ver[1], 10, 32)
if err != nil {
slog.Debug("malformed", "device_id", line, "error", err)
}
} else if strings.HasPrefix(line, "unique_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "unique_id", line)
continue
}
uniqueID, err = strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Debug("malformed", "unique_id", line, "error", err)
slog.Debug("malformed device_id" + line)
}
}
// TODO - any other properties we want to extract and record?
// vendor_id + device_id -> pci lookup for "Name"
// Other metrics that may help us understand relative performance between multiple GPUs
}
// Note: while ./mem_banks/*/used_memory exists, it doesn't appear to take other VRAM consumers
// into consideration, so we instead map the device over to the DRM driver sysfs nodes which
// do reliably report VRAM usage.
if isCPU {
cpuCount++
continue
@@ -179,7 +156,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Shouldn't happen, but just in case...
if gpuID < 0 {
slog.Error("unexpected amdgpu sysfs data resulted in negative GPU ID, please set OLLAMA_DEBUG=1 and report an issue")
return nil
return []GpuInfo{}
}
if int(major) < RocmComputeMin {
@@ -190,68 +167,65 @@ func AMDGetGPUInfo() []RocmGPUInfo {
// Look up the memory for the current node
totalMemory := uint64(0)
usedMemory := uint64(0)
var usedFile string
mapping := []struct {
id uint64
filename string
}{
{vendor, DRMVendorFile},
{device, DRMDeviceFile},
{uniqueID, DRMUniqueIDFile}, // Not all devices will report this
propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUTotalMemoryFileGlob)
propFiles, err := filepath.Glob(propGlob)
if err != nil {
slog.Warn("error looking up total GPU memory", "glob", propGlob, "error", err)
}
slog.Debug("mapping amdgpu to drm sysfs nodes", "amdgpu", match, "vendor", vendor, "device", device, "unique_id", uniqueID)
// Map over to DRM location to find the total/free memory
drmMatches, _ := filepath.Glob(DRMDeviceDirGlob)
for _, devDir := range drmMatches {
matched := true
for _, m := range mapping {
if m.id == 0 {
// Null ID means it didn't populate, so we can't use it to match
continue
}
filename := filepath.Join(devDir, m.filename)
buf, err := os.ReadFile(filename)
if err != nil {
slog.Debug("failed to read sysfs node", "file", filename, "error", err)
matched = false
break
}
// values here are in hex, strip off the lead 0x and parse so we can compare the numeric (decimal) values in amdgpu
cmp, err := strconv.ParseUint(strings.TrimPrefix(strings.TrimSpace(string(buf)), "0x"), 16, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", filename, "error", err)
matched = false
break
}
if cmp != m.id {
matched = false
break
}
}
if !matched {
// 1 or more memory banks - sum the values of all of them
for _, propFile := range propFiles {
fp, err := os.Open(propFile)
if err != nil {
slog.Warn("failed to open sysfs node", "file", propFile, "erroir", err)
continue
}
// Found the matching DRM directory
slog.Debug("matched", "amdgpu", match, "drm", devDir)
totalFile := filepath.Join(devDir, DRMTotalMemoryFile)
buf, err := os.ReadFile(totalFile)
if err != nil {
slog.Debug("failed to read sysfs node", "file", totalFile, "error", err)
break
defer fp.Close()
scanner := bufio.NewScanner(fp)
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
if strings.HasPrefix(line, "size_in_bytes") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Warn("malformed " + line)
continue
}
bankSizeInBytes, err := strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Warn("malformed int " + line)
continue
}
totalMemory += bankSizeInBytes
}
}
totalMemory, err = strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
}
if totalMemory == 0 {
slog.Warn("amdgpu reports zero total memory", "gpu", gpuID)
continue
}
usedGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUUsedMemoryFileGlob)
usedFiles, err := filepath.Glob(usedGlob)
if err != nil {
slog.Warn("error looking up used GPU memory", "glob", usedGlob, "error", err)
continue
}
for _, usedFile := range usedFiles {
fp, err := os.Open(usedFile)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", totalFile, "error", err)
break
slog.Warn("failed to open sysfs node", "file", usedFile, "error", err)
continue
}
usedFile = filepath.Join(devDir, DRMUsedMemoryFile)
usedMemory, err = getFreeMemory(usedFile)
defer fp.Close()
data, err := io.ReadAll(fp)
if err != nil {
slog.Debug("failed to update used memory", "error", err)
slog.Warn("failed to read sysfs node", "file", usedFile, "error", err)
continue
}
break
used, err := strconv.ParseUint(strings.TrimSpace(string(data)), 10, 64)
if err != nil {
slog.Warn("malformed used memory", "data", string(data), "error", err)
continue
}
usedMemory += used
}
// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
@@ -267,21 +241,18 @@ func AMDGetGPUInfo() []RocmGPUInfo {
slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: (totalMemory - usedMemory),
},
ID: strconv.Itoa(gpuID),
Name: name,
Compute: fmt.Sprintf("gfx%d%x%x", major, minor, patch),
MinimumMemory: rocmMinimumMemory,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
gpuInfo := GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: (totalMemory - usedMemory),
},
usedFilepath: usedFile,
ID: fmt.Sprintf("%d", gpuID),
Name: name,
Compute: fmt.Sprintf("gfx%d%x%x", major, minor, patch),
MinimumMemory: rocmMinimumMemory,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
}
// If the user wants to filter to a subset of devices, filter out if we aren't a match
@@ -305,7 +276,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
libDir, err = AMDValidateLibDir()
if err != nil {
slog.Warn("unable to verify rocm library, will use cpu", "error", err)
return nil
return []GpuInfo{}
}
}
gpuInfo.DependencyPath = libDir
@@ -316,7 +287,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
supported, err = GetSupportedGFX(libDir)
if err != nil {
slog.Warn("failed to lookup supported GFX types, falling back to CPU mode", "error", err)
return nil
return []GpuInfo{}
}
slog.Debug("rocm supported GPUs", "types", supported)
}
@@ -333,11 +304,6 @@ func AMDGetGPUInfo() []RocmGPUInfo {
slog.Info("skipping rocm gfx compatibility check", "HSA_OVERRIDE_GFX_VERSION", gfxOverride)
}
// Check for env var workarounds
if name == "1002:687f" { // Vega RX 56
gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
}
// The GPU has passed all the verification steps and is supported
resp = append(resp, gpuInfo)
}
@@ -412,31 +378,3 @@ func AMDDriverVersion() (driverMajor, driverMinor int, err error) {
}
return driverMajor, driverMinor, nil
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
for i := range gpus {
usedMemory, err := getFreeMemory(gpus[i].usedFilepath)
if err != nil {
return err
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(gpus[i].TotalMemory-usedMemory))
gpus[i].FreeMemory = gpus[i].TotalMemory - usedMemory
}
return nil
}
func getFreeMemory(usedFile string) (uint64, error) {
buf, err := os.ReadFile(usedFile)
if err != nil {
return 0, fmt.Errorf("failed to read sysfs node %s %w", usedFile, err)
}
usedMemory, err := strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", usedFile, "error", err)
return 0, fmt.Errorf("failed to parse sysfs node %s %w", usedFile, err)
}
return usedMemory, nil
}

View File

@@ -7,10 +7,8 @@ import (
"os"
"path/filepath"
"slices"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
@@ -22,12 +20,12 @@ const (
var (
// Used to validate if the given ROCm lib is usable
ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // This is not sufficient to discern v5 vs v6
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\6.1\\bin"} // TODO glob?
ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // TODO - probably include more coverage of files here...
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\5.7\\bin"} // TODO glob?
)
func AMDGetGPUInfo() []RocmGPUInfo {
resp := []RocmGPUInfo{}
func AMDGetGPUInfo() []GpuInfo {
resp := []GpuInfo{}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
@@ -35,11 +33,12 @@ func AMDGetGPUInfo() []RocmGPUInfo {
}
defer hl.Release()
driverMajor, driverMinor, err := hl.AMDDriverVersion()
if err != nil {
// For now this is benign, but we may eventually need to fail compatibility checks
slog.Debug("error looking up amd driver version", "error", err)
}
// TODO - this reports incorrect version information, so omitting for now
// driverMajor, driverMinor, err := hl.AMDDriverVersion()
// if err != nil {
// // For now this is benign, but we may eventually need to fail compatibility checks
// slog.Debug("error looking up amd driver version", "error", err)
// }
// Note: the HIP library automatically handles subsetting to any HIP_VISIBLE_DEVICES the user specified
count := hl.HipGetDeviceCount()
@@ -53,7 +52,7 @@ func AMDGetGPUInfo() []RocmGPUInfo {
}
var supported []string
gfxOverride := envconfig.HsaOverrideGfxVersion
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
if gfxOverride == "" {
supported, err = GetSupportedGFX(libDir)
if err != nil {
@@ -114,27 +113,25 @@ func AMDGetGPUInfo() []RocmGPUInfo {
continue
}
// TODO revisit this once ROCm v6 is available on windows.
// v5.7 only reports VRAM used by this process, so it's completely wrong and unusable
slog.Debug("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
// Free memory reporting on Windows is not reliable until we bump to ROCm v6.2
UnreliableFreeMemory: true,
ID: strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
DependencyPath: libDir,
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
gpuInfo := GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
index: i,
ID: fmt.Sprintf("%d", i), // TODO this is probably wrong if we specify visible devices
DependencyPath: libDir,
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
// TODO - this information isn't accurate on windows, so don't report it until we find the right way to retrieve
// DriverMajor: driverMajor,
// DriverMinor: driverMinor,
}
resp = append(resp, gpuInfo)
@@ -162,30 +159,3 @@ func AMDValidateLibDir() (string, error) {
slog.Warn("amdgpu detected, but no compatible rocm library found. Please install ROCm")
return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
return nil
}
defer hl.Release()
for i := range gpus {
err := hl.HipSetDevice(gpus[i].index)
if err != nil {
return err
}
freeMemory, _, err := hl.HipMemGetInfo()
if err != nil {
slog.Warn("get mem info", "id", i, "error", err)
continue
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(freeMemory))
gpus[i].FreeMemory = freeMemory
}
return nil
}

View File

@@ -77,27 +77,20 @@ func cleanupTmpDirs() {
continue
}
raw, err := os.ReadFile(filepath.Join(d, "ollama.pid"))
if err == nil {
pid, err := strconv.Atoi(string(raw))
if err == nil {
if proc, err := os.FindProcess(pid); err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
// Another running ollama, ignore this tmpdir
continue
}
}
} else {
slog.Debug("failed to open ollama.pid", "path", d, "error", err)
}
err = os.RemoveAll(d)
if err != nil {
slog.Warn("failed to read ollama.pid", "path", d, "error", err)
// No pid, ignore this tmpdir
continue
}
pid, err := strconv.Atoi(string(raw))
if err != nil {
slog.Warn("failed to parse pid", "path", d, "error", err)
continue
}
proc, err := os.FindProcess(pid)
if err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
slog.Warn("found running ollama", "pid", pid, "path", d)
// Another running ollama, ignore this tmpdir
continue
}
if err := os.Remove(d); err != nil {
slog.Warn("unable to cleanup stale tmpdir", "path", d, "error", err)
slog.Debug("unable to cleanup stale tmpdir", "path", d, "error", err)
}
}
}

View File

@@ -1,16 +1,21 @@
package gpu
import (
"log/slog"
"golang.org/x/sys/cpu"
)
func GetCPUCapability() CPUCapability {
func GetCPUVariant() string {
if cpu.X86.HasAVX2 {
return CPUCapabilityAVX2
slog.Debug("CPU has AVX2")
return "avx2"
}
if cpu.X86.HasAVX {
return CPUCapabilityAVX
slog.Debug("CPU has AVX")
return "avx"
}
slog.Debug("CPU does not have vector extensions")
// else LCD
return CPUCapabilityNone
return ""
}

View File

@@ -24,37 +24,19 @@ import (
"github.com/ollama/ollama/format"
)
type cudaHandles struct {
type handles struct {
deviceCount int
cudart *C.cudart_handle_t
nvcuda *C.nvcuda_handle_t
nvml *C.nvml_handle_t
}
type oneapiHandles struct {
oneapi *C.oneapi_handle_t
deviceCount int
}
const (
cudaMinimumMemory = 457 * format.MebiByte
rocmMinimumMemory = 457 * format.MebiByte
// TODO OneAPI minimum memory
)
var (
gpuMutex sync.Mutex
bootstrapped bool
cpuCapability CPUCapability
cpus []CPUInfo
cudaGPUs []CudaGPUInfo
nvcudaLibPath string
cudartLibPath string
oneapiLibPath string
nvmlLibPath string
rocmGPUs []RocmGPUInfo
oneapiGPUs []OneapiGPUInfo
)
var gpuMutex sync.Mutex
// With our current CUDA compile flags, older than 5.0 will not work properly
var CudaComputeMin = [2]C.int{5, 0}
@@ -64,113 +46,113 @@ var RocmComputeMin = 9
// TODO find a better way to detect iGPU instead of minimum memory
const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
var CudartLinuxGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var CudartWindowsGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
var NvcudaLinuxGlobs = []string{
"/usr/local/cuda*/targets/*/lib/libcuda.so*",
"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
"/usr/lib/*-linux-gnu/libcuda.so*",
"/usr/lib/wsl/lib/libcuda.so*",
"/usr/lib/wsl/drivers/*/libcuda.so*",
"/opt/cuda/lib*/libcuda.so*",
"/usr/local/cuda/lib*/libcuda.so*",
"/usr/lib*/libcuda.so*",
"/usr/local/lib*/libcuda.so*",
}
var NvcudaWindowsGlobs = []string{
"c:\\windows\\system*\\nvcuda.dll",
}
var OneapiWindowsGlobs = []string{
"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
}
var OneapiLinuxGlobs = []string{
"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
"/usr/lib*/libze_intel_gpu.so*",
}
// Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
// Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
var CudaTegra string = os.Getenv("JETSON_JETPACK")
// Note: gpuMutex must already be held
func initCudaHandles() *cudaHandles {
func initGPUHandles() *handles {
// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
cHandles := &cudaHandles{}
// Short Circuit if we already know which library to use
if nvmlLibPath != "" {
cHandles.nvml, _ = LoadNVMLMgmt([]string{nvmlLibPath})
return cHandles
}
if nvcudaLibPath != "" {
cHandles.deviceCount, cHandles.nvcuda, _ = LoadNVCUDAMgmt([]string{nvcudaLibPath})
return cHandles
}
if cudartLibPath != "" {
cHandles.deviceCount, cHandles.cudart, _ = LoadCUDARTMgmt([]string{cudartLibPath})
return cHandles
}
slog.Debug("searching for GPU discovery libraries for NVIDIA")
gpuHandles := &handles{}
var cudartMgmtName string
var cudartMgmtPatterns []string
var nvcudaMgmtName string
var nvcudaMgmtPatterns []string
// Aligned with driver, we can't carry as payloads
nvcudaMgmtPatterns := NvcudaGlobs
if runtime.GOOS == "windows" {
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", CudartMgmtName)}
}
tmpDir, _ := PayloadsDir()
if tmpDir != "" {
// TODO - add "payloads" for subprocess
cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", CudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartGlobs...)
if len(NvmlGlobs) > 0 {
nvmlLibPaths := FindGPULibs(NvmlMgmtName, NvmlGlobs)
if len(nvmlLibPaths) > 0 {
nvml, libPath := LoadNVMLMgmt(nvmlLibPaths)
if nvml != nil {
slog.Debug("nvidia-ml loaded", "library", libPath)
cHandles.nvml = nvml
nvmlLibPath = libPath
}
switch runtime.GOOS {
case "windows":
cudartMgmtName = "cudart64_*.dll"
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
// Aligned with driver, we can't carry as payloads
nvcudaMgmtName = "nvcuda.dll"
nvcudaMgmtPatterns = NvcudaWindowsGlobs
case "linux":
cudartMgmtName = "libcudart.so*"
if tmpDir != "" {
// TODO - add "payloads" for subprocess
cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
// Aligned with driver, we can't carry as payloads
nvcudaMgmtName = "libcuda.so*"
nvcudaMgmtPatterns = NvcudaLinuxGlobs
default:
return gpuHandles
}
nvcudaLibPaths := FindGPULibs(NvcudaMgmtName, nvcudaMgmtPatterns)
slog.Debug("Detecting GPUs")
nvcudaLibPaths := FindGPULibs(nvcudaMgmtName, nvcudaMgmtPatterns)
if len(nvcudaLibPaths) > 0 {
deviceCount, nvcuda, libPath := LoadNVCUDAMgmt(nvcudaLibPaths)
if nvcuda != nil {
slog.Debug("detected GPUs", "count", deviceCount, "library", libPath)
cHandles.nvcuda = nvcuda
cHandles.deviceCount = deviceCount
nvcudaLibPath = libPath
return cHandles
gpuHandles.nvcuda = nvcuda
gpuHandles.deviceCount = deviceCount
return gpuHandles
}
}
cudartLibPaths := FindGPULibs(CudartMgmtName, cudartMgmtPatterns)
cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
if len(cudartLibPaths) > 0 {
deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths)
if cudart != nil {
slog.Debug("detected GPUs", "library", libPath, "count", deviceCount)
cHandles.cudart = cudart
cHandles.deviceCount = deviceCount
cudartLibPath = libPath
return cHandles
gpuHandles.cudart = cudart
gpuHandles.deviceCount = deviceCount
return gpuHandles
}
}
return cHandles
}
// Note: gpuMutex must already be held
func initOneAPIHandles() *oneapiHandles {
oHandles := &oneapiHandles{}
// Short Circuit if we already know which library to use
if oneapiLibPath != "" {
oHandles.deviceCount, oHandles.oneapi, _ = LoadOneapiMgmt([]string{oneapiLibPath})
return oHandles
}
oneapiLibPaths := FindGPULibs(OneapiMgmtName, OneapiGlobs)
if len(oneapiLibPaths) > 0 {
oHandles.deviceCount, oHandles.oneapi, oneapiLibPath = LoadOneapiMgmt(oneapiLibPaths)
}
return oHandles
}
func GetCPUInfo() GpuInfoList {
gpuMutex.Lock()
if !bootstrapped {
gpuMutex.Unlock()
GetGPUInfo()
} else {
gpuMutex.Unlock()
}
return GpuInfoList{cpus[0].GpuInfo}
return gpuHandles
}
func GetGPUInfo() GpuInfoList {
@@ -178,288 +160,112 @@ func GetGPUInfo() GpuInfoList {
// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
gpuMutex.Lock()
defer gpuMutex.Unlock()
needRefresh := true
var cHandles *cudaHandles
var oHandles *oneapiHandles
gpuHandles := initGPUHandles()
defer func() {
if cHandles != nil {
if cHandles.cudart != nil {
C.cudart_release(*cHandles.cudart)
}
if cHandles.nvcuda != nil {
C.nvcuda_release(*cHandles.nvcuda)
}
if cHandles.nvml != nil {
C.nvml_release(*cHandles.nvml)
}
if gpuHandles.cudart != nil {
C.cudart_release(*gpuHandles.cudart)
}
if oHandles != nil {
if oHandles.oneapi != nil {
// TODO - is this needed?
C.oneapi_release(*oHandles.oneapi)
}
if gpuHandles.nvcuda != nil {
C.nvcuda_release(*gpuHandles.nvcuda)
}
}()
if !bootstrapped {
slog.Info("looking for compatible GPUs")
needRefresh = false
cpuCapability = GetCPUCapability()
var memInfo C.mem_info_t
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
}
cpus = []CPUInfo{CPUInfo{
GpuInfo: GpuInfo{
memInfo: mem,
Library: "cpu",
Variant: cpuCapability,
ID: "0",
},
}}
// Fallback to CPU mode if we're lacking required vector extensions on x86
if cpuCapability < GPURunnerCPUCapability && runtime.GOARCH == "amd64" {
slog.Warn("CPU does not have minimum vector extensions, GPU inference disabled", "required", GPURunnerCPUCapability, "detected", cpuCapability)
bootstrapped = true
// No need to do any GPU discovery, since we can't run on them
return GpuInfoList{cpus[0].GpuInfo}
}
// On windows we bundle the nvidia library one level above the runner dir
depPath := ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "cuda")
}
// Load ALL libraries
cHandles = initCudaHandles()
// NVIDIA
for i := range cHandles.deviceCount {
if cHandles.cudart != nil || cHandles.nvcuda != nil {
gpuInfo := CudaGPUInfo{
GpuInfo: GpuInfo{
Library: "cuda",
},
index: i,
}
var driverMajor int
var driverMinor int
if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
} else {
C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
driverMajor = int(cHandles.nvcuda.driver_major)
driverMinor = int(cHandles.nvcuda.driver_minor)
}
if memInfo.err != nil {
slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
continue
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DependencyPath = depPath
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor
// query the management library as well so we can record any skew between the two
// which represents overhead on the GPU we must set aside on subsequent updates
if cHandles.nvml != nil {
C.nvml_get_free(*cHandles.nvml, C.int(gpuInfo.index), &memInfo.free, &memInfo.total, &memInfo.used)
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
} else {
if memInfo.free != 0 && uint64(memInfo.free) > gpuInfo.FreeMemory {
gpuInfo.OSOverhead = uint64(memInfo.free) - gpuInfo.FreeMemory
slog.Info("detected OS VRAM overhead",
"id", gpuInfo.ID,
"library", gpuInfo.Library,
"compute", gpuInfo.Compute,
"driver", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor),
"name", gpuInfo.Name,
"overhead", format.HumanBytes2(gpuInfo.OSOverhead),
)
}
}
}
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
cudaGPUs = append(cudaGPUs, gpuInfo)
}
}
// Intel
if envconfig.IntelGpu {
oHandles = initOneAPIHandles()
// On windows we bundle the oneapi library one level above the runner dir
depPath = ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Join(filepath.Dir(envconfig.RunnersDir), "oneapi")
}
for d := range oHandles.oneapi.num_drivers {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with driver count", "count", int(oHandles.oneapi.num_drivers))
continue
}
devCount := C.oneapi_get_device_count(*oHandles.oneapi, C.int(d))
for i := range devCount {
gpuInfo := OneapiGPUInfo{
GpuInfo: GpuInfo{
Library: "oneapi",
},
driverIndex: int(d),
gpuIndex: int(i),
}
// TODO - split bootstrapping from updating free memory
C.oneapi_check_vram(*oHandles.oneapi, C.int(d), i, &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DependencyPath = depPath
oneapiGPUs = append(oneapiGPUs, gpuInfo)
}
}
}
rocmGPUs = AMDGetGPUInfo()
bootstrapped = true
if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
slog.Info("no compatible GPUs were discovered")
}
// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
cpuVariant := GetCPUVariant()
if cpuVariant == "" && runtime.GOARCH == "amd64" {
slog.Warn("CPU does not have AVX or AVX2, disabling GPU support.")
}
// For detected GPUs, load library if not loaded
// On windows we bundle the nvidia library one level above the runner dir
depPath := ""
if runtime.GOOS == "windows" && envconfig.RunnersDir != "" {
depPath = filepath.Dir(envconfig.RunnersDir)
}
// Refresh free memory usage
if needRefresh {
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
} else {
slog.Debug("updating system memory data",
slog.Group(
"before",
"total", format.HumanBytes2(cpus[0].TotalMemory),
"free", format.HumanBytes2(cpus[0].FreeMemory),
"free_swap", format.HumanBytes2(cpus[0].FreeSwap),
),
slog.Group(
"now",
"total", format.HumanBytes2(mem.TotalMemory),
"free", format.HumanBytes2(mem.FreeMemory),
"free_swap", format.HumanBytes2(mem.FreeSwap),
),
)
cpus[0].FreeMemory = mem.FreeMemory
cpus[0].FreeSwap = mem.FreeSwap
}
var memInfo C.mem_info_t
resp := []GpuInfo{}
var memInfo C.mem_info_t
if cHandles == nil && len(cudaGPUs) > 0 {
cHandles = initCudaHandles()
// NVIDIA first
for i := range gpuHandles.deviceCount {
// TODO once we support CPU compilation variants of GPU libraries refine this...
if cpuVariant == "" && runtime.GOARCH == "amd64" {
continue
}
for i, gpu := range cudaGPUs {
if cHandles.nvml != nil {
C.nvml_get_free(*cHandles.nvml, C.int(gpu.index), &memInfo.free, &memInfo.total, &memInfo.used)
} else if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(gpu.index), &memInfo)
} else if cHandles.nvcuda != nil {
C.nvcuda_get_free(*cHandles.nvcuda, C.int(gpu.index), &memInfo.free, &memInfo.total)
memInfo.used = memInfo.total - memInfo.free
if gpuHandles.cudart != nil || gpuHandles.nvcuda != nil {
gpuInfo := GpuInfo{
Library: "cuda",
}
var driverMajor int
var driverMinor int
if gpuHandles.cudart != nil {
C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo)
} else {
// shouldn't happen
slog.Warn("no valid cuda library loaded to refresh vram usage")
break
C.nvcuda_check_vram(*gpuHandles.nvcuda, C.int(i), &memInfo)
driverMajor = int(gpuHandles.nvcuda.driver_major)
driverMinor = int(gpuHandles.nvcuda.driver_minor)
}
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
if memInfo.free == 0 {
slog.Warn("error looking up nvidia GPU memory")
if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
continue
}
if cHandles.nvml != nil && gpu.OSOverhead > 0 {
// When using the management library update based on recorded overhead
memInfo.free -= C.uint64_t(gpu.OSOverhead)
}
slog.Debug("updating cuda memory data",
"gpu", gpu.ID,
"name", gpu.Name,
"overhead", format.HumanBytes2(gpu.OSOverhead),
slog.Group(
"before",
"total", format.HumanBytes2(gpu.TotalMemory),
"free", format.HumanBytes2(gpu.FreeMemory),
),
slog.Group(
"now",
"total", format.HumanBytes2(uint64(memInfo.total)),
"free", format.HumanBytes2(uint64(memInfo.free)),
"used", format.HumanBytes2(uint64(memInfo.used)),
),
)
cudaGPUs[i].FreeMemory = uint64(memInfo.free)
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DependencyPath = depPath
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor
if oHandles == nil && len(oneapiGPUs) > 0 {
oHandles = initOneAPIHandles()
}
for i, gpu := range oneapiGPUs {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with device count", "count", oHandles.deviceCount)
continue
}
C.oneapi_check_vram(*oHandles.oneapi, C.int(gpu.driverIndex), C.int(gpu.gpuIndex), &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
oneapiGPUs[i].FreeMemory = uint64(memInfo.free)
}
err = RocmGPUInfoList(rocmGPUs).RefreshFreeMemory()
if err != nil {
slog.Debug("problem refreshing ROCm free memory", "error", err)
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
resp = append(resp, gpuInfo)
}
}
resp := []GpuInfo{}
for _, gpu := range cudaGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range rocmGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range oneapiGPUs {
resp = append(resp, gpu.GpuInfo)
}
// Then AMD
resp = append(resp, AMDGetGPUInfo()...)
if len(resp) == 0 {
resp = append(resp, cpus[0].GpuInfo)
C.cpu_check_ram(&memInfo)
if memInfo.err != nil {
slog.Info("error looking up CPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
return resp
}
gpuInfo := GpuInfo{
Library: "cpu",
Variant: cpuVariant,
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
resp = append(resp, gpuInfo)
}
return resp
}
func GetCPUMem() (memInfo, error) {
var ret memInfo
var info C.mem_info_t
C.cpu_check_ram(&info)
if info.err != nil {
defer C.free(unsafe.Pointer(info.err))
return ret, fmt.Errorf(C.GoString(info.err))
}
ret.FreeMemory = uint64(info.free)
ret.TotalMemory = uint64(info.total)
return ret, nil
}
func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
var ldPaths []string
@@ -547,23 +353,7 @@ 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 {
// 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)
}
}
slog.Debug("Unable to load nvcuda", "library", libPath, "error", C.GoString(resp.err))
C.free(unsafe.Pointer(resp.err))
} else {
return int(resp.num_devices), &resp.ch, libPath
@@ -572,26 +362,8 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
return 0, nil, ""
}
func LoadNVMLMgmt(nvmlLibPaths []string) (*C.nvml_handle_t, string) {
var resp C.nvml_init_resp_t
resp.ch.verbose = getVerboseState()
for _, libPath := range nvmlLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.nvml_init(lib, &resp)
if resp.err != nil {
slog.Info(fmt.Sprintf("Unable to load NVML management library %s: %s", libPath, C.GoString(resp.err)))
C.free(unsafe.Pointer(resp.err))
} else {
return &resp.ch, libPath
}
}
return nil, ""
}
func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
var resp C.oneapi_init_resp_t
num_devices := 0
resp.oh.verbose = getVerboseState()
for _, libPath := range oneapiLibPaths {
lib := C.CString(libPath)
@@ -601,10 +373,7 @@ func LoadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string) {
slog.Debug("Unable to load oneAPI management library", "library", libPath, "error", C.GoString(resp.err))
C.free(unsafe.Pointer(resp.err))
} else {
for i := range resp.oh.num_drivers {
num_devices += int(C.oneapi_get_device_count(resp.oh, C.int(i)))
}
return num_devices, &resp.oh, libPath
return int(resp.num_devices), &resp.oh, libPath
}
}
return 0, nil, ""

View File

@@ -24,7 +24,7 @@ func GetGPUInfo() GpuInfoList {
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
Variant: GetCPUVariant(),
memInfo: mem,
},
}
@@ -42,22 +42,10 @@ func GetGPUInfo() GpuInfoList {
return []GpuInfo{info}
}
func GetCPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
memInfo: mem,
},
}
}
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),
FreeMemory: uint64(C.getFreeMemory()),
// FreeSwap omitted as Darwin uses dynamic paging
FreeMemory: 0,
}, nil
}

View File

@@ -47,7 +47,6 @@ typedef struct mem_info {
char gpu_name[GPU_NAME_LEN];
uint64_t total;
uint64_t free;
uint64_t used;
// Compute Capability
int major;
@@ -63,7 +62,6 @@ void cpu_check_ram(mem_info_t *resp);
#include "gpu_info_cudart.h"
#include "gpu_info_nvcuda.h"
#include "gpu_info_nvml.h"
#include "gpu_info_oneapi.h"
#endif // __GPU_INFO_H__

45
gpu/gpu_info_cpu.c Normal file
View File

@@ -0,0 +1,45 @@
#include "gpu_info.h"
// Fallbacks for CPU mode
#ifdef _WIN32
#include <sysinfoapi.h>
void cpu_check_ram(mem_info_t *resp) {
resp->err = NULL;
MEMORYSTATUSEX info;
info.dwLength = sizeof(info);
if (GlobalMemoryStatusEx(&info) != 0) {
resp->total = info.ullTotalPhys;
resp->free = info.ullAvailPhys;
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
} else {
resp->err = LOAD_ERR();
}
return;
}
#elif __linux__
#include <errno.h>
#include <string.h>
#include <sys/sysinfo.h>
void cpu_check_ram(mem_info_t *resp) {
struct sysinfo info;
resp->err = NULL;
if (sysinfo(&info) != 0) {
resp->err = strdup(strerror(errno));
} else {
resp->total = info.totalram * info.mem_unit;
resp->free = info.freeram * info.mem_unit;
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
}
return;
}
#elif __APPLE__
// TODO consider an Apple implementation that does something useful
// mem_info_t cpu_check_ram() {
// mem_info_t resp = {0, 0, NULL};
// return resp;
// }
#else
#error "Unsupported platform"
#endif

View File

@@ -40,7 +40,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
if (!l[i].p) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
@@ -94,7 +94,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
}
void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
void cudart_check_vram(cudart_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
cudartMemory_t memInfo = {0,0,0};
cudartReturn_t ret;
@@ -166,11 +166,9 @@ void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
resp->total = memInfo.total;
resp->free = memInfo.free;
resp->used = memInfo.used;
LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
}

View File

@@ -140,8 +140,7 @@ typedef struct cudart_init_resp {
} cudart_init_resp_t;
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
void cudart_bootstrap(cudart_handle_t ch, int device_id, mem_info_t *resp);
// TODO - if we keep this library longer term, add cudart_get_free
void cudart_check_vram(cudart_handle_t ch, int device_id, mem_info_t *resp);
void cudart_release(cudart_handle_t ch);
#endif // __GPU_INFO_CUDART_H__

View File

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

View File

@@ -1,5 +1,4 @@
#import <Foundation/Foundation.h>
#import <mach/mach.h>
// go:build darwin
#include "gpu_info_darwin.h"
uint64_t getRecommendedMaxVRAM() {
@@ -9,27 +8,6 @@ uint64_t getRecommendedMaxVRAM() {
return result;
}
// getPhysicalMemory returns the total physical memory in bytes
uint64_t getPhysicalMemory() {
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;
return [[NSProcessInfo processInfo] physicalMemory];
}

View File

@@ -7,7 +7,6 @@ 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;
@@ -39,13 +38,12 @@ 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;
}
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
if (!*l[i].p) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
@@ -54,7 +52,6 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
}
@@ -64,9 +61,12 @@ 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;
snprintf(buf, buflen, "cuda driver library init failure: %d", ret);
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);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
@@ -91,13 +91,12 @@ 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;
}
}
const int buflen = 256;
void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
void nvcuda_check_vram(nvcuda_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
nvcudaMemory_t memInfo = {0,0};
CUresult ret;
@@ -107,13 +106,13 @@ 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("cuda driver library handle isn't initialized");
resp->err = strdup("nvcuda handle isn't initialized");
return;
}
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "cuda driver library device failed to initialize");
snprintf(buf, buflen, "nvcuda device failed to initialize");
resp->err = strdup(buf);
return;
}
@@ -169,14 +168,14 @@ 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, "cuda driver library failed to get device context %d", ret);
snprintf(buf, buflen, "nvcuda failed to get primary device context %d", ret);
resp->err = strdup(buf);
return;
}
ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "cuda driver library device memory info lookup failure %d", ret);
snprintf(buf, buflen, "nvcuda device memory info lookup failure %d", ret);
resp->err = strdup(buf);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
@@ -194,47 +193,12 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total) {
CUresult ret;
CUcontext ctx = NULL;
CUdevice device = -1;
*free = 0;
*total = 0;
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library device failed to initialize");
return;
}
// 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, "cuda driver library failed to get device context %d", ret);
return;
}
ret = (*h.cuMemGetInfo_v2)(free, total);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library device memory info lookup failure %d", ret);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
}
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library failed to release device context %d", ret);
LOG(1, "nvcuda failed to release primary device context %d", ret);
}
}
void nvcuda_release(nvcuda_handle_t h) {
LOG(h.verbose, "releasing cuda driver library\n");
LOG(h.verbose, "releasing nvcuda library\n");
UNLOAD_LIBRARY(h.handle);
// TODO and other context release logic?
h.handle = NULL;

View File

@@ -7,12 +7,9 @@
typedef enum cudaError_enum {
CUDA_SUCCESS = 0,
CUDA_ERROR_INVALID_VALUE = 1,
CUDA_ERROR_OUT_OF_MEMORY = 2,
CUDA_ERROR_MEMORY_ALLOCATION = 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;
@@ -67,12 +64,10 @@ 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);
void nvcuda_bootstrap(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
void nvcuda_get_free(nvcuda_handle_t ch, int device_id, uint64_t *free, uint64_t *total);
void nvcuda_check_vram(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
void nvcuda_release(nvcuda_handle_t ch);
#endif // __GPU_INFO_NVCUDA_H__

View File

@@ -1,104 +0,0 @@
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_nvml.h"
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
{"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
{"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
nvml_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
resp->ch.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.nvmlInit_v2)();
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "nvml vram init failure: %d", ret);
resp->err = strdup(buf);
return;
}
}
void nvml_get_free(nvml_handle_t h, int device_id, uint64_t *free, uint64_t *total, uint64_t *used) {
nvmlDevice_t device;
nvmlMemory_t memInfo = {0};
nvmlReturn_t ret;
ret = (*h.nvmlDeviceGetHandleByIndex)(device_id, &device);
if (ret != NVML_SUCCESS) {
LOG(1, "unable to get device handle %d: %d", device_id, ret);
*free = 0;
return;
}
ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
if (ret != NVML_SUCCESS) {
LOG(1, "device memory info lookup failure %d: %d", device_id, ret);
*free = 0;
return;
}
*free = memInfo.free;
*total = memInfo.total;
*used = memInfo.used;
}
void nvml_release(nvml_handle_t h) {
LOG(h.verbose, "releasing nvml library\n");
nvmlReturn_t ret;
ret = (*h.nvmlShutdown)();
if (ret != NVML_SUCCESS) {
LOG(1, "error during nvmlShutdown %d", ret);
}
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__

View File

@@ -1,48 +0,0 @@
#ifndef __APPLE__
#ifndef __GPU_INFO_NVML_H__
#define __GPU_INFO_NVML_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum nvmlReturn_enum {
NVML_SUCCESS = 0,
// Other values omitted for now...
} nvmlReturn_t;
typedef void *nvmlDevice_t; // Opaque is sufficient
typedef struct nvmlMemory_st {
unsigned long long total;
unsigned long long free;
unsigned long long used;
} nvmlMemory_t;
typedef enum nvmlBrandType_enum
{
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct nvml_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
} nvml_handle_t;
typedef struct nvml_init_resp {
char *err; // If err is non-null handle is invalid
nvml_handle_t ch;
} nvml_init_resp_t;
typedef struct nvml_compute_capability {
char *err;
int major;
int minor;
} nvml_compute_capability_t;
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
void nvml_get_free(nvml_handle_t ch, int device_id, uint64_t *free, uint64_t *total, uint64_t *used);
void nvml_release(nvml_handle_t ch);
#endif // __GPU_INFO_NVML_H__
#endif // __APPLE__

View File

@@ -4,17 +4,15 @@
#include <string.h>
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp)
{
ze_result_t ret;
resp->err = NULL;
resp->oh.devices = NULL;
resp->oh.num_devices = NULL;
resp->oh.drivers = NULL;
resp->oh.num_drivers = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d;
struct lookup {
int i;
struct lookup
{
char *s;
void **p;
} l[] = {
@@ -30,7 +28,8 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
};
resp->oh.handle = LOAD_LIBRARY(oneapi_lib_path, RTLD_LAZY);
if (!resp->oh.handle) {
if (!resp->oh.handle)
{
char *msg = LOAD_ERR();
snprintf(buf, buflen,
"Unable to load %s library to query for Intel GPUs: %s\n",
@@ -45,12 +44,14 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
"wiring Level-Zero management library functions in %s\n",
oneapi_lib_path);
for (i = 0; l[i].s != NULL; i++) {
for (i = 0; l[i].s != NULL; i++)
{
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->oh.handle, l[i].s);
if (!*(l[i].p)) {
if (!l[i].p)
{
resp->oh.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->oh.verbose, "dlerr: %s\n", msg);
@@ -62,70 +63,23 @@ void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
}
}
LOG(resp->oh.verbose, "calling zesInit\n");
ret = (*resp->oh.zesInit)(0);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesInit err: %x\n", ret);
snprintf(buf, buflen, "oneapi vram init failure: %x", ret);
if (ret != ZE_RESULT_SUCCESS)
{
LOG(resp->oh.verbose, "zesInit err: %d\n", ret);
UNLOAD_LIBRARY(resp->oh.handle);
resp->oh.handle = NULL;
snprintf(buf, buflen, "oneapi vram init failure: %d", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "calling zesDriverGet\n");
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "oneapi driver count: %d\n", resp->oh.num_drivers);
resp->oh.drivers = malloc(resp->oh.num_drivers * sizeof(zes_driver_handle_t));
resp->oh.num_devices = malloc(resp->oh.num_drivers * sizeof(uint32_t));
memset(&resp->oh.num_devices[0], 0, resp->oh.num_drivers * sizeof(uint32_t));
resp->oh.devices =
malloc(resp->oh.num_drivers * sizeof(zes_device_handle_t *));
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, &resp->oh.drivers[0]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
for (d = 0; d < resp->oh.num_drivers; d++) {
LOG(resp->oh.verbose, "calling zesDeviceGet count %d: %p\n", d, resp->oh.drivers[d]);
ret = (*resp->oh.zesDeviceGet)(resp->oh.drivers[d],
&resp->oh.num_devices[d], NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
resp->oh.devices[d] =
malloc(resp->oh.num_devices[d] * sizeof(zes_device_handle_t));
ret = (*resp->oh.zesDeviceGet)(
resp->oh.drivers[d], &resp->oh.num_devices[d], resp->oh.devices[d]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
}
(*resp->oh.zesDriverGet)(&resp->num_devices, NULL);
return;
}
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp) {
void oneapi_check_vram(oneapi_handle_t h, mem_info_t *resp)
{
ze_result_t ret;
resp->err = NULL;
uint64_t totalMem = 0;
@@ -134,126 +88,127 @@ void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
char buf[buflen + 1];
int i, d, m;
if (h.handle == NULL) {
if (h.handle == NULL)
{
resp->err = strdup("Level-Zero handle not initialized");
return;
}
if (driver > h.num_drivers || device > h.num_devices[driver]) {
resp->err = strdup("driver of device index out of bounds");
uint32_t driversCount = 0;
ret = (*h.zesDriverGet)(&driversCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get driver count: %d", ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero drivers\n", driversCount);
zes_driver_handle_t *allDrivers =
malloc(driversCount * sizeof(zes_driver_handle_t));
(*h.zesDriverGet)(&driversCount, allDrivers);
resp->total = 0;
resp->free = 0;
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(h.devices[driver][device], &props);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
return;
}
snprintf(&resp->gpu_name[0], GPU_NAME_LEN, "%s", props.modelName);
// TODO this needs to map to ONEAPI_DEVICE_SELECTOR syntax
// (this is probably wrong...)
// TODO - the driver isn't included - what if there are multiple drivers?
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", device);
if (h.verbose) {
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d:%d] oneAPI device name: %s\n", driver, device,
props.modelName);
LOG(h.verbose, "[%d:%d] oneAPI brand: %s\n", driver, device,
props.brandName);
LOG(h.verbose, "[%d:%d] oneAPI vendor: %s\n", driver, device,
props.vendorName);
LOG(h.verbose, "[%d:%d] oneAPI S/N: %s\n", driver, device,
props.serialNumber);
LOG(h.verbose, "[%d:%d] oneAPI board number: %s\n", driver, device,
props.boardNumber);
}
// TODO
// Compute Capability equivalent in resp->major, resp->minor, resp->patch
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount,
NULL);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to enumerate Level-Zero memory modules: %x",
ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount, mems);
for (m = 0; m < memCount; m++) {
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get memory state: %x", ret);
for (d = 0; d < driversCount; d++)
{
uint32_t deviceCount = 0;
ret = (*h.zesDeviceGet)(allDrivers[d], &deviceCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
free(mems);
free(allDrivers);
return;
}
resp->total += state.size;
resp->free += state.free;
}
LOG(h.verbose, "discovered %d Level-Zero devices\n", deviceCount);
free(mems);
}
zes_device_handle_t *devices =
malloc(deviceCount * sizeof(zes_device_handle_t));
(*h.zesDeviceGet)(allDrivers[d], &deviceCount, devices);
void oneapi_release(oneapi_handle_t h) {
int d;
LOG(h.verbose, "releasing oneapi library\n");
for (d = 0; d < h.num_drivers; d++) {
if (h.devices != NULL && h.devices[d] != NULL) {
free(h.devices[d]);
for (i = 0; i < deviceCount; i++)
{
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(devices[i], &props);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
return;
}
if (h.verbose)
{
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d] oneAPI device name: %s\n", i,
props.modelName);
LOG(h.verbose, "[%d] oneAPI brand: %s\n", i,
props.brandName);
LOG(h.verbose, "[%d] oneAPI vendor: %s\n", i,
props.vendorName);
LOG(h.verbose, "[%d] oneAPI S/N: %s\n", i,
props.serialNumber);
LOG(h.verbose, "[%d] oneAPI board number: %s\n", i,
props.boardNumber);
}
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, NULL);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen,
"unable to enumerate Level-Zero memory modules: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(devices[i], &memCount, mems);
for (m = 0; m < memCount; m++)
{
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS)
{
snprintf(buf, buflen, "unable to get memory state: %d", ret);
resp->err = strdup(buf);
free(allDrivers);
free(devices);
free(mems);
return;
}
resp->total += state.size;
resp->free += state.free;
}
free(mems);
}
}
if (h.devices != NULL) {
free(h.devices);
h.devices = NULL;
}
if (h.num_devices != NULL) {
free(h.num_devices);
h.num_devices = NULL;
}
if (h.drivers != NULL) {
free(h.drivers);
h.drivers = NULL;
}
h.num_drivers = 0;
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
int oneapi_get_device_count(oneapi_handle_t h, int driver) {
if (h.handle == NULL || h.num_devices == NULL) {
return 0;
free(devices);
}
if (driver > h.num_drivers) {
return 0;
}
return (int)h.num_devices[driver];
free(allDrivers);
}
#endif // __APPLE__

View File

@@ -9,7 +9,8 @@
#define ZE_BIT(_i) (1 << _i)
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum ze_result_t {
typedef enum ze_result_t
{
ZE_RESULT_SUCCESS = 0,
// Other values omitted for now...
} ze_result_t;
@@ -19,11 +20,13 @@ typedef struct _zes_driver_handle_t *zes_driver_handle_t;
typedef struct _zes_device_handle_t *zes_device_handle_t;
typedef struct _zes_mem_handle_t *zes_mem_handle_t;
typedef enum _ze_structure_type_t {
typedef enum _ze_structure_type_t
{
ZE_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_structure_type_t;
typedef enum _zes_structure_type_t {
typedef enum _zes_structure_type_t
{
ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES = 0x1,
ZES_STRUCTURE_TYPE_MEM_PROPERTIES = 0xb,
ZES_STRUCTURE_TYPE_MEM_STATE = 0x1e,
@@ -31,29 +34,35 @@ typedef enum _zes_structure_type_t {
ZES_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_structure_type_t;
typedef enum _zes_mem_type_t {
typedef enum _zes_mem_type_t
{
ZES_MEM_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_mem_type_t;
typedef enum _zes_mem_loc_t {
typedef enum _zes_mem_loc_t
{
ZES_MEM_LOC_SYSTEM = 0,
ZES_MEM_LOC_DEVICE = 1,
ZES_MEM_LOC_FORCE_UINT32 = 0x7fffffff
} zes_mem_loc_t;
typedef enum _zes_mem_health_t {
typedef enum _zes_mem_health_t
{
ZES_MEM_HEALTH_FORCE_UINT32 = 0x7fffffff
} zes_mem_health_t;
typedef struct _ze_device_uuid_t {
typedef struct _ze_device_uuid_t
{
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} ze_device_uuid_t;
typedef struct _zes_uuid_t {
typedef struct _zes_uuid_t
{
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} zes_uuid_t;
typedef enum _ze_device_type_t {
typedef enum _ze_device_type_t
{
ZE_DEVICE_TYPE_GPU = 1,
ZE_DEVICE_TYPE_CPU = 2,
ZE_DEVICE_TYPE_FPGA = 3,
@@ -62,7 +71,8 @@ typedef enum _ze_device_type_t {
ZE_DEVICE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_device_type_t;
typedef enum _zes_device_type_t {
typedef enum _zes_device_type_t
{
ZES_DEVICE_TYPE_GPU = 1,
ZES_DEVICE_TYPE_CPU = 2,
ZES_DEVICE_TYPE_FPGA = 3,
@@ -72,7 +82,8 @@ typedef enum _zes_device_type_t {
} zes_device_type_t;
typedef uint32_t ze_device_property_flags_t;
typedef enum _ze_device_property_flag_t {
typedef enum _ze_device_property_flag_t
{
ZE_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZE_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZE_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -81,7 +92,8 @@ typedef enum _ze_device_property_flag_t {
} ze_device_property_flag_t;
typedef uint32_t zes_device_property_flags_t;
typedef enum _zes_device_property_flag_t {
typedef enum _zes_device_property_flag_t
{
ZES_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZES_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZES_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
@@ -89,7 +101,8 @@ typedef enum _zes_device_property_flag_t {
ZES_DEVICE_PROPERTY_FLAG_FORCE_UINT32 = 0x7fffffff
} zes_device_property_flag_t;
typedef struct _ze_device_properties_t {
typedef struct _ze_device_properties_t
{
ze_structure_type_t stype;
void *pNext;
ze_device_type_t type;
@@ -113,7 +126,8 @@ typedef struct _ze_device_properties_t {
char name[ZE_MAX_DEVICE_NAME];
} ze_device_properties_t;
typedef struct _zes_device_properties_t {
typedef struct _zes_device_properties_t
{
zes_structure_type_t stype;
void *pNext;
ze_device_properties_t core;
@@ -126,7 +140,8 @@ typedef struct _zes_device_properties_t {
char driverVersion[ZES_STRING_PROPERTY_SIZE];
} zes_device_properties_t;
typedef struct _zes_device_ext_properties_t {
typedef struct _zes_device_ext_properties_t
{
zes_structure_type_t stype;
void *pNext;
zes_uuid_t uuid;
@@ -134,7 +149,8 @@ typedef struct _zes_device_ext_properties_t {
zes_device_property_flags_t flags;
} zes_device_ext_properties_t;
typedef struct _zes_mem_properties_t {
typedef struct _zes_mem_properties_t
{
zes_structure_type_t stype;
void *pNext;
zes_mem_type_t type;
@@ -146,7 +162,8 @@ typedef struct _zes_mem_properties_t {
int32_t numChannels;
} zes_mem_properties_t;
typedef struct _zes_mem_state_t {
typedef struct _zes_mem_state_t
{
zes_structure_type_t stype;
const void *pNext;
zes_mem_health_t health;
@@ -154,19 +171,10 @@ typedef struct _zes_mem_state_t {
uint64_t size;
} zes_mem_state_t;
typedef struct oneapi_handle {
typedef struct oneapi_handle
{
void *handle;
uint16_t verbose;
uint32_t num_drivers;
zes_driver_handle_t *drivers;
uint32_t *num_devices;
zes_device_handle_t **devices;
// TODO Driver major, minor information
// int driver_major;
// int driver_minor;
ze_result_t (*zesInit)(int);
ze_result_t (*zesDriverGet)(uint32_t *pCount, zes_driver_handle_t *phDrivers);
ze_result_t (*zesDeviceGet)(zes_driver_handle_t hDriver, uint32_t *pCount,
@@ -183,21 +191,21 @@ typedef struct oneapi_handle {
} oneapi_handle_t;
typedef struct oneapi_init_resp {
typedef struct oneapi_init_resp
{
char *err; // If err is non-null handle is invalid
int num_devices;
oneapi_handle_t oh;
} oneapi_init_resp_t;
typedef struct oneapi_version_resp {
typedef struct oneapi_version_resp
{
ze_result_t status;
char *str; // Contains version or error string if status != 0
} oneapi_version_resp_t;
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp);
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp);
void oneapi_release(oneapi_handle_t h);
int oneapi_get_device_count(oneapi_handle_t h, int driver);
void oneapi_check_vram(oneapi_handle_t rh, mem_info_t *resp);
#endif // __GPU_INFO_INTEL_H__
#endif // __APPLE__

View File

@@ -1,90 +0,0 @@
package gpu
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/ollama/ollama/format"
)
var CudartGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var NvmlGlobs = []string{}
var NvcudaGlobs = []string{
"/usr/local/cuda*/targets/*/lib/libcuda.so*",
"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
"/usr/lib/*-linux-gnu/libcuda.so*",
"/usr/lib/wsl/lib/libcuda.so*",
"/usr/lib/wsl/drivers/*/libcuda.so*",
"/opt/cuda/lib*/libcuda.so*",
"/usr/local/cuda/lib*/libcuda.so*",
"/usr/lib*/libcuda.so*",
"/usr/local/lib*/libcuda.so*",
}
var OneapiGlobs = []string{
"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
"/usr/lib*/libze_intel_gpu.so*",
}
var CudartMgmtName = "libcudart.so*"
var NvcudaMgmtName = "libcuda.so*"
var NvmlMgmtName = "" // not currently wired on linux
var OneapiMgmtName = "libze_intel_gpu.so"
func GetCPUMem() (memInfo, error) {
var mem memInfo
var total, available, free, buffers, cached, freeSwap uint64
f, err := os.Open("/proc/meminfo")
if err != nil {
return mem, err
}
defer f.Close()
s := bufio.NewScanner(f)
for s.Scan() {
line := s.Text()
switch {
case strings.HasPrefix(line, "MemTotal:"):
_, err = fmt.Sscanf(line, "MemTotal:%d", &total)
case strings.HasPrefix(line, "MemAvailable:"):
_, err = fmt.Sscanf(line, "MemAvailable:%d", &available)
case strings.HasPrefix(line, "MemFree:"):
_, err = fmt.Sscanf(line, "MemFree:%d", &free)
case strings.HasPrefix(line, "Buffers:"):
_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
case strings.HasPrefix(line, "Cached:"):
_, err = fmt.Sscanf(line, "Cached:%d", &cached)
case strings.HasPrefix(line, "SwapFree:"):
_, err = fmt.Sscanf(line, "SwapFree:%d", &freeSwap)
default:
continue
}
if err != nil {
return mem, err
}
}
mem.TotalMemory = total * format.KibiByte
mem.FreeSwap = freeSwap * format.KibiByte
if available > 0 {
mem.FreeMemory = available * format.KibiByte
} else {
mem.FreeMemory = (free + buffers + cached) * format.KibiByte
}
return mem, nil
}

View File

@@ -1,55 +0,0 @@
package gpu
import (
"fmt"
"syscall"
"unsafe"
)
type MEMORYSTATUSEX struct {
length uint32
MemoryLoad uint32
TotalPhys uint64
AvailPhys uint64
TotalPageFile uint64
AvailPageFile uint64
TotalVirtual uint64
AvailVirtual uint64
AvailExtendedVirtual uint64
}
var (
k32 = syscall.NewLazyDLL("kernel32.dll")
globalMemoryStatusExProc = k32.NewProc("GlobalMemoryStatusEx")
sizeofMemoryStatusEx = uint32(unsafe.Sizeof(MEMORYSTATUSEX{}))
)
var CudartGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
var NvmlGlobs = []string{
"c:\\Windows\\System32\\nvml.dll",
}
var NvcudaGlobs = []string{
"c:\\windows\\system*\\nvcuda.dll",
}
var OneapiGlobs = []string{
"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
}
var CudartMgmtName = "cudart64_*.dll"
var NvcudaMgmtName = "nvcuda.dll"
var NvmlMgmtName = "nvml.dll"
var OneapiMgmtName = "ze_intel_gpu64.dll"
func GetCPUMem() (memInfo, error) {
memStatus := MEMORYSTATUSEX{length: sizeofMemoryStatusEx}
r1, _, err := globalMemoryStatusExProc.Call(uintptr(unsafe.Pointer(&memStatus)))
if r1 == 0 {
return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
}
return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys, FreeSwap: memStatus.AvailPageFile}, nil
}

View File

@@ -10,7 +10,6 @@ import (
type memInfo struct {
TotalMemory uint64 `json:"total_memory,omitempty"`
FreeMemory uint64 `json:"free_memory,omitempty"`
FreeSwap uint64 `json:"free_swap,omitempty"`
}
// Beginning of an `ollama info` command
@@ -19,7 +18,7 @@ type GpuInfo struct {
Library string `json:"library,omitempty"`
// Optional variant to select (e.g. versions, cpu feature flags)
Variant CPUCapability `json:"variant"`
Variant string `json:"variant,omitempty"`
// MinimumMemory represents the minimum memory required to use the GPU
MinimumMemory uint64 `json:"-"`
@@ -27,14 +26,6 @@ type GpuInfo struct {
// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
DependencyPath string `json:"lib_path,omitempty"`
// Extra environment variables specific to the GPU as list of [key,value]
EnvWorkarounds [][2]string `json:"envs,omitempty"`
// Set to true if we can NOT reliably discover FreeMemory. A value of true indicates
// the FreeMemory is best effort, and may over or under report actual memory usage
// False indicates FreeMemory can generally be trusted on this GPU
UnreliableFreeMemory bool
// GPU information
ID string `json:"gpu_id"` // string to use for selection of this specific GPU
Name string `json:"name"` // user friendly name if available
@@ -47,31 +38,6 @@ type GpuInfo struct {
// TODO other performance capability info to help in scheduling decisions
}
type CPUInfo struct {
GpuInfo
}
type CudaGPUInfo struct {
GpuInfo
OSOverhead uint64 // Memory overhead between the driver library and management library
index int //nolint:unused,nolintlint
}
type CudaGPUInfoList []CudaGPUInfo
type RocmGPUInfo struct {
GpuInfo
usedFilepath string //nolint:unused,nolintlint
index int //nolint:unused,nolintlint
}
type RocmGPUInfoList []RocmGPUInfo
type OneapiGPUInfo struct {
GpuInfo
driverIndex int //nolint:unused,nolintlint
gpuIndex int //nolint:unused,nolintlint
}
type OneapiGPUInfoList []OneapiGPUInfo
type GpuInfoList []GpuInfo
// Split up the set of gpu info's by Library and variant
@@ -81,8 +47,8 @@ func (l GpuInfoList) ByLibrary() []GpuInfoList {
for _, info := range l {
found := false
requested := info.Library
if info.Variant != CPUCapabilityNone {
requested += "_" + info.Variant.String()
if info.Variant != "" {
requested += "_" + info.Variant
}
for i, lib := range libs {
if lib == requested {
@@ -120,26 +86,3 @@ type ByFreeMemory []GpuInfo
func (a ByFreeMemory) Len() int { return len(a) }
func (a ByFreeMemory) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByFreeMemory) Less(i, j int) bool { return a[i].FreeMemory < a[j].FreeMemory }
type CPUCapability uint32
// Override at build time when building base GPU runners
var GPURunnerCPUCapability = CPUCapabilityAVX
const (
CPUCapabilityNone CPUCapability = iota
CPUCapabilityAVX
CPUCapabilityAVX2
// TODO AVX512
)
func (c CPUCapability) String() string {
switch c {
case CPUCapabilityAVX:
return "avx"
case CPUCapabilityAVX2:
return "avx2"
default:
return "no vector extensions"
}
}

View File

@@ -19,19 +19,17 @@ func TestMultiModelConcurrency(t *testing.T) {
var (
req = [2]api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "tinydolphin",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "tinydolphin",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
@@ -40,64 +38,42 @@ func TestMultiModelConcurrency(t *testing.T) {
}
resp = [2][]string{
[]string{"sunlight"},
[]string{"england", "english", "massachusetts", "pilgrims", "british"},
[]string{"england", "english", "massachusetts", "pilgrims"},
}
)
var wg sync.WaitGroup
wg.Add(len(req))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*240)
ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
for i := 0; i < len(req); i++ {
require.NoError(t, PullIfMissing(ctx, client, req[i].Model))
}
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
DoGenerate(ctx, t, client, req[i], resp[i], 60*time.Second, 10*time.Second)
GenerateTestHelper(ctx, t, req[i], resp[i])
}(i)
}
wg.Wait()
}
func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
req, resp := GenerateRequests()
reqLimit := len(req)
iterLimit := 5
vram := os.Getenv("OLLAMA_MAX_VRAM")
if vram != "" {
max, err := strconv.ParseUint(vram, 10, 64)
require.NoError(t, err)
// Don't hammer on small VRAM cards...
if max < 4*1024*1024*1024 {
reqLimit = min(reqLimit, 2)
iterLimit = 2
}
}
ctx, cancel := context.WithTimeout(context.Background(), 9*time.Minute)
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute) // GTX 750 2G card takes ~9 minutes
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
req, resp := GenerateRequests()
// Get the server running (if applicable) warm the model up with a single initial request
DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 10*time.Second)
DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 5*time.Second)
var wg sync.WaitGroup
wg.Add(reqLimit)
for i := 0; i < reqLimit; i++ {
wg.Add(len(req))
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
for j := 0; j < iterLimit; j++ {
for j := 0; j < 5; j++ {
slog.Info("Starting", "req", i, "iter", j)
// On slower GPUs it can take a while to process the concurrent requests
// On slower GPUs it can take a while to process the 4 concurrent requests
// so we allow a much longer initial timeout
DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 20*time.Second)
DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
}
}(i)
}
@@ -245,23 +221,5 @@ func TestMultiModelStress(t *testing.T) {
}
}(i)
}
go func() {
for {
time.Sleep(2 * time.Second)
select {
case <-ctx.Done():
return
default:
models, err := client.ListRunning(ctx)
if err != nil {
slog.Warn("failed to list running models", "error", err)
continue
}
for _, m := range models.Models {
slog.Info("loaded model snapshot", "model", m)
}
}
}
}()
wg.Wait()
}

View File

@@ -11,8 +11,7 @@ import (
)
func TestContextExhaustion(t *testing.T) {
// Longer needed for small footprint GPUs
ctx, cancel := context.WithTimeout(context.Background(), 6*time.Minute)
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute) // TODO maybe shorter?
defer cancel()
// Set up the test data
req := api.GenerateRequest{

View File

@@ -1,152 +0,0 @@
//go:build integration
package integration
import (
"context"
"testing"
"time"
"github.com/ollama/ollama/api"
)
func TestAllMiniLMEmbed(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
req := api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
}
res, err := embedTestHelper(ctx, t, req)
if err != nil {
t.Fatalf("error: %v", err)
}
if len(res.Embeddings) != 1 {
t.Fatalf("expected 1 embedding, got %d", len(res.Embeddings))
}
if len(res.Embeddings[0]) != 384 {
t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
}
if res.Embeddings[0][0] != 0.010071031 {
t.Fatalf("expected 0.010071031, got %f", res.Embeddings[0][0])
}
}
func TestAllMiniLMBatchEmbed(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
req := api.EmbedRequest{
Model: "all-minilm",
Input: []string{"why is the sky blue?", "why is the grass green?"},
}
res, err := embedTestHelper(ctx, t, req)
if err != nil {
t.Fatalf("error: %v", err)
}
if len(res.Embeddings) != 2 {
t.Fatalf("expected 2 embeddings, got %d", len(res.Embeddings))
}
if len(res.Embeddings[0]) != 384 {
t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
}
if res.Embeddings[0][0] != 0.010071031 || res.Embeddings[1][0] != -0.009802706 {
t.Fatalf("expected 0.010071031 and -0.009802706, got %f and %f", res.Embeddings[0][0], res.Embeddings[1][0])
}
}
func TestAllMiniLmEmbedTruncate(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
truncTrue, truncFalse := true, false
type testReq struct {
Name string
Request api.EmbedRequest
}
reqs := []testReq{
{
Name: "Target Truncation",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why",
},
},
{
Name: "Default Truncate",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Options: map[string]any{"num_ctx": 1},
},
},
{
Name: "Explicit Truncate",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncTrue,
Options: map[string]any{"num_ctx": 1},
},
},
}
res := make(map[string]*api.EmbedResponse)
for _, req := range reqs {
response, err := embedTestHelper(ctx, t, req.Request)
if err != nil {
t.Fatalf("error: %v", err)
}
res[req.Name] = response
}
if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
t.Fatal("expected default request to truncate correctly")
}
if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
t.Fatal("expected default request and truncate true request to be the same")
}
// check that truncate set to false returns an error if context length is exceeded
_, err := embedTestHelper(ctx, t, api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncFalse,
Options: map[string]any{"num_ctx": 1},
})
if err == nil {
t.Fatal("expected error, got nil")
}
}
func embedTestHelper(ctx context.Context, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("failed to pull model %s: %v", req.Model, err)
}
response, err := client.Embed(ctx, &req)
if err != nil {
return nil, err
}
return response, nil
}

View File

@@ -32,11 +32,7 @@ func TestIntegrationMultimodal(t *testing.T) {
resp := "the ollam"
ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
require.NoError(t, PullIfMissing(ctx, client, req.Model))
// llava models on CPU can be quite slow to start,
DoGenerate(ctx, t, client, req, []string{resp}, 120*time.Second, 30*time.Second)
GenerateTestHelper(ctx, t, req, []string{resp})
}
const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb

View File

@@ -140,7 +140,7 @@ func PullIfMissing(ctx context.Context, client *api.Client, modelName string) er
showCtx, cancel := context.WithDeadlineCause(
ctx,
time.Now().Add(10*time.Second),
time.Now().Add(5*time.Second),
fmt.Errorf("show for existing model %s took too long", modelName),
)
defer cancel()
@@ -287,46 +287,41 @@ func DoGenerate(ctx context.Context, t *testing.T, client *api.Client, genReq ap
func GenerateRequests() ([]api.GenerateRequest, [][]string) {
return []api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "why is the color of dirt brown?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "why is the color of dirt brown?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the origin of independence day?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the origin of independence day?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "orca-mini",
Prompt: "what is the composition of air?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Model: "orca-mini",
Prompt: "what is the composition of air?",
Stream: &stream,
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
@@ -336,7 +331,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
[][]string{
[]string{"sunlight"},
[]string{"soil", "organic", "earth", "black", "tan"},
[]string{"england", "english", "massachusetts", "pilgrims", "british"},
[]string{"england", "english", "massachusetts", "pilgrims"},
[]string{"fourth", "july", "declaration", "independence"},
[]string{"nitrogen", "oxygen", "carbon", "dioxide"},
}

View File

@@ -1,13 +1,14 @@
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()
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()
target_compile_features(${TARGET} PRIVATE cxx_std_11)

View File

@@ -56,6 +56,7 @@ struct server_params {
std::string hostname = "127.0.0.1";
std::vector<std::string> api_keys;
std::string public_path = "examples/server/public";
std::string chat_template = "";
int32_t port = 8080;
int32_t read_timeout = 600;
int32_t write_timeout = 600;
@@ -426,6 +427,16 @@ struct llama_server_context
return true;
}
void validate_model_chat_template(server_params & sparams) {
llama_chat_message chat[] = {{"user", "test"}};
std::vector<char> buf(1);
int res = llama_chat_apply_template(model, nullptr, chat, 1, true, buf.data(), buf.size());
if (res < 0) {
LOG_ERROR("The chat template comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses", {});
sparams.chat_template = "chatml";
}
}
void initialize() {
// create slots
all_slots_are_idle = true;
@@ -1382,50 +1393,12 @@ 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 = prefix_slot(task.data["prompt"]);
server_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
if (slot == nullptr)
{
// if no slot is available, we defer this task for processing later
@@ -1692,23 +1665,22 @@ struct llama_server_context
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;
const int n_erase = slot.n_prompt_tokens - slot.params.n_keep - n_shift;
const int n_block_size = n_left / 2;
const int erased_blocks = (slot.n_prompt_tokens - slot.params.n_keep - n_block_size) / n_block_size;
std::vector<llama_token> new_tokens(
prompt_tokens.begin(),
prompt_tokens.begin() + slot.params.n_keep);
new_tokens.insert(
new_tokens.end(),
prompt_tokens.begin() + slot.params.n_keep + n_erase,
prompt_tokens.begin() + slot.params.n_keep + erased_blocks * n_block_size,
prompt_tokens.end());
LOG_INFO("input truncated", {
{"n_ctx", slot.n_ctx},
{"n_keep", slot.params.n_keep},
{"n_left", n_left},
{"n_shift", n_shift},
{"n_erase", n_erase},
LOG_VERBOSE("input truncated", {
{"n_ctx", slot.n_ctx},
{"n_keep", slot.params.n_keep},
{"n_left", n_left},
{"new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend())},
});
slot.truncated = true;
prompt_tokens = new_tokens;
@@ -1743,7 +1715,7 @@ struct llama_server_context
slot.n_past -= 1;
}
slot.n_prompt_tokens_processed = slot.n_prompt_tokens;
slot.n_prompt_tokens_processed = slot.n_prompt_tokens - slot.n_past;
if (slot.ga_n != 1)
{
@@ -2363,9 +2335,9 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#ifndef GGML_USE_CUDA
fprintf(stderr, "warning: llama.cpp was compiled without CUDA. Setting the split mode has no effect.\n");
#endif // GGML_USE_CUDA
#ifndef GGML_USE_CUBLAS
fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. Setting the split mode has no effect.\n");
#endif // GGML_USE_CUBLAS
}
else if (arg == "--tensor-split" || arg == "-ts")
{
@@ -2374,7 +2346,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
std::string arg_next = argv[i];
// split string by , and /
@@ -2395,8 +2367,8 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
}
}
#else
LOG_WARNING("llama.cpp was compiled without CUDA. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUDA
LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--main-gpu" || arg == "-mg")
{
@@ -2405,7 +2377,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
#if defined(GGML_USE_CUDA) || defined(GGML_USE_SYCL)
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_SYCL)
params.main_gpu = std::stoi(argv[i]);
#else
LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.", {});
@@ -2563,6 +2535,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams, g
invalid_param = true;
break;
}
sparams.chat_template = argv[i];
}
else if (arg == "--override-kv")
{
@@ -3035,6 +3008,11 @@ int main(int argc, char **argv) {
}
const auto model_meta = llama.model_meta();
if (sparams.chat_template.empty()) { // custom chat template is not supplied
// check if the template comes with the model is supported by us
llama.validate_model_chat_template(sparams);
}
// Middleware for API key validation
auto validate_api_key = [&sparams](const httplib::Request &req, httplib::Response &res) -> bool {
// If API key is not set, skip validation
@@ -3188,33 +3166,26 @@ int main(int argc, char **argv) {
prompt = "";
}
if (prompt.size() == 1) {
prompt = prompt[0];
json image_data;
if (body.count("image_data") != 0) {
image_data = body["image_data"];
}
else
{
image_data = "";
}
// create and queue the task
json responses;
{
const int id_task = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(id_task);
llama.request_completion(id_task, {{"prompt", prompt}}, true, -1);
const int task_id = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(task_id);
llama.request_completion(task_id, { {"prompt", prompt}, { "n_predict", 0}, {"image_data", image_data} }, true, -1);
// get the result
task_result result = llama.queue_results.recv(id_task);
llama.queue_results.remove_waiting_task_id(id_task);
if (result.error) {
return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
}
// get the result
task_result result = llama.queue_results.recv(task_id);
llama.queue_results.remove_waiting_task_id(task_id);
responses = result.result_json.value("results", std::vector<json>{result.result_json});
json embeddings = json::array();
for (auto & elem : responses) {
embeddings.push_back(elem.at("embedding"));
}
// send the result
json embedding_res = json{{"embedding", embeddings}};
return res.set_content(embedding_res.dump(), "application/json; charset=utf-8");
}
// send the result
return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
});
// GG: if I put the main loop inside a thread, it crashes on the first request when build in Debug!?

View File

@@ -18,16 +18,16 @@ sign() {
fi
}
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"
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"
case "${GOARCH}" in
"amd64")
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DGGML_METAL=off -DGGML_NATIVE=off"
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_NATIVE=off"
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_BLAS=off -DGGML_ACCELERATE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_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} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_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} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_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} -DGGML_ACCELERATE=on -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_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="${COMMON_DARWIN_DEFS} -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${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 ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
if [ -z "$OLLAMA_SKIP_METAL_GENERATE" ]; then
init_vars
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${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="-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"
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"
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 -DGGML_NATIVE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off ${CMAKE_DEFS}"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=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} -DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -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
# -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
# -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
# Note: the following seem to yield slower results than AVX2 - ymmv
# -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake
# -DLLAMA_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off"
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=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} -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_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} -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_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} -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_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="-DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_CUDA_F16=off"
ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_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="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
echo "Building custom CUDA GPU"
else
CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
fi
CMAKE_DEFS="${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} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL=ON -DLLAMA_SYCL_F16=OFF"
BUILD_DIR="../build/linux/${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} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DLLAMA_CUDA_NO_PEER_COPY=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
# Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
if [ -n "${OLLAMA_CUSTOM_ROCM_DEFS}" ]; then
echo "OLLAMA_CUSTOM_ROCM_DEFS=\"${OLLAMA_CUSTOM_ROCM_DEFS}\""

View File

@@ -6,9 +6,18 @@ function amdGPUs {
if ($env:AMDGPU_TARGETS) {
return $env:AMDGPU_TARGETS
}
# Current supported rocblas list from ROCm v6.1.2 on windows
# TODO - load from some common data file for linux + windows build consistency
$GPU_LIST = @(
"gfx900"
"gfx906:xnack-"
"gfx908:xnack-"
"gfx90a:xnack+"
"gfx90a:xnack-"
"gfx940"
"gfx941"
"gfx942"
"gfx1010"
"gfx1012"
"gfx1030"
"gfx1100"
"gfx1101"
@@ -30,8 +39,7 @@ function init_vars {
}
$script:cmakeDefs = @(
"-DBUILD_SHARED_LIBS=on",
"-DGGML_NATIVE=off",
"-DGGML_OPENMP=off"
"-DLLAMA_NATIVE=off"
)
$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
$script:ARCH = $Env:PROCESSOR_ARCHITECTURE.ToLower()
@@ -114,13 +122,8 @@ function build {
& cmake --version
& cmake -S "${script:llamacppDir}" -B $script:buildDir $script:cmakeDefs
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
if ($cmakeDefs -contains "-G") {
$extra=@("-j8")
} else {
$extra= @("--", "/p:CL_MPcount=8")
}
write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ }) $extra"
& cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ }) $extra
write-host "building with: cmake --build $script:buildDir --config $script:config $($script:cmakeTargets | ForEach-Object { `"--target`", $_ })"
& cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
# Rearrange output to be consistent between different generators
if ($null -ne ${script:config} -And (test-path -path "${script:buildDir}/bin/${script:config}" ) ) {
@@ -173,9 +176,9 @@ function cleanup {
}
# -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
# -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
function build_static() {
@@ -195,13 +198,12 @@ function build_static() {
"-DCMAKE_C_COMPILER=gcc.exe",
"-DCMAKE_CXX_COMPILER=g++.exe",
"-DBUILD_SHARED_LIBS=off",
"-DGGML_NATIVE=off",
"-DGGML_AVX=off",
"-DGGML_AVX2=off",
"-DGGML_AVX512=off",
"-DGGML_F16C=off",
"-DGGML_FMA=off",
"-DGGML_OPENMP=off")
"-DLLAMA_NATIVE=off",
"-DLLAMA_AVX=off",
"-DLLAMA_AVX2=off",
"-DLLAMA_AVX512=off",
"-DLLAMA_F16C=off",
"-DLLAMA_FMA=off")
$script:buildDir="../build/windows/${script:ARCH}_static"
write-host "Building static library"
build
@@ -215,7 +217,7 @@ 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, "-DGGML_AVX=off", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu"
$script:distDir="$script:DIST_BASE\cpu"
write-host "Building LCD CPU"
@@ -230,7 +232,7 @@ 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", "-DGGML_AVX=on", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
$script:distDir="$script:DIST_BASE\cpu_avx"
write-host "Building AVX CPU"
@@ -245,7 +247,7 @@ 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", "-DGGML_AVX=on", "-DGGML_AVX2=on", "-DGGML_AVX512=off", "-DGGML_FMA=on", "-DGGML_F16C=on") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
$script:distDir="$script:DIST_BASE\cpu_avx2"
write-host "Building AVX2 CPU"
@@ -268,15 +270,7 @@ function build_cuda() {
init_vars
$script:buildDir="../build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:distDir="$script:DIST_BASE\cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @(
"-A", "x64",
"-DGGML_CUDA=ON",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR",
"-DCMAKE_CUDA_FLAGS=-t8",
"-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}"
)
$script:cmakeDefs += @("-A", "x64", "-DLLAMA_CUDA=ON", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
if ($null -ne $env:OLLAMA_CUSTOM_CUDA_DEFS) {
write-host "OLLAMA_CUSTOM_CUDA_DEFS=`"${env:OLLAMA_CUSTOM_CUDA_DEFS}`""
$script:cmakeDefs +=@("${env:OLLAMA_CUSTOM_CUDA_DEFS}")
@@ -286,12 +280,10 @@ function build_cuda() {
sign
install
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\" -ea 0 > $null
write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\cuda\"
write-host "copying CUDA dependencies to ${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cudart64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cublas64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
cp "${script:CUDA_LIB_DIR}\cublasLt64_*.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\"
} else {
write-host "Skipping CUDA generation step"
}
@@ -310,7 +302,7 @@ function build_oneapi() {
$script:distDir ="$script:DIST_BASE\oneapi$script:ONEAPI_VARIANT"
$script:cmakeDefs += @(
"-G", "MinGW Makefiles",
"-DGGML_SYCL=ON",
"-DLLAMA_SYCL=ON",
"-DCMAKE_C_COMPILER=icx",
"-DCMAKE_CXX_COMPILER=icx",
"-DCMAKE_BUILD_TYPE=Release"
@@ -325,18 +317,16 @@ function build_oneapi() {
sign
install
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\" -ea 0 > $null
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\oneapi\"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libirngmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\libmmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_level_zero.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_unified_runtime.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\pi_win_proxy_loader.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\svml_dispmd.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\compiler\latest\bin\sycl7.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_core.2.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_sycl_blas.4.dll" "${script:distDir}"
cp "${env:ONEAPI_ROOT}\mkl\latest\bin\mkl_tbb_thread.2.dll" "${script:distDir}"
} else {
Write-Host "Skipping oneAPI generation step"
}
@@ -356,11 +346,10 @@ function build_rocm() {
"-G", "Ninja",
"-DCMAKE_C_COMPILER=clang.exe",
"-DCMAKE_CXX_COMPILER=clang++.exe",
"-DGGML_HIPBLAS=on",
"-DLLAMA_CUDA_NO_PEER_COPY=on",
"-DLLAMA_HIPBLAS=on",
"-DHIP_PLATFORM=amd",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DCMAKE_POSITION_INDEPENDENT_CODE=on",
"-DAMDGPU_TARGETS=$(amdGPUs)",
"-DGPU_TARGETS=$(amdGPUs)"
@@ -386,6 +375,7 @@ function build_rocm() {
sign
install
# Assumes v5.7, may need adjustments for v6
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\rocblas\library\" -ea 0 > $null
cp "${env:HIP_PATH}\bin\hipblas.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"

View File

@@ -53,7 +53,7 @@ func (llm *ggla) Tensors() Tensors {
return llm.tensors
}
func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
func (llm *ggla) decode(rs io.ReadSeeker) error {
var r uint32
if err := binary.Read(rs, binary.LittleEndian, &r); err != nil {
return err
@@ -69,18 +69,9 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
for {
var dims uint32
if err := binary.Read(rs, binary.LittleEndian, &dims); err != nil {
if errors.Is(err, io.EOF) {
return nil
}
return err
}
defer func() {
if errors.Is(retErr, io.EOF) {
retErr = io.ErrUnexpectedEOF
}
}()
var namesize uint32
if err := binary.Read(rs, binary.LittleEndian, &namesize); err != nil {
return err
@@ -117,7 +108,7 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
return err
}
if _, err := rs.Seek((offset+31)&-32-offset, io.SeekCurrent); err != nil {
if _, err := rs.Seek((offset+31)&-32, io.SeekStart); err != nil {
return err
}

View File

@@ -6,8 +6,6 @@ import (
"fmt"
"io"
"strings"
"github.com/ollama/ollama/util/bufioutil"
)
type GGML struct {
@@ -71,30 +69,6 @@ func (kv KV) HeadCountKV() uint64 {
return 1
}
func (kv KV) EmbeddingHeadCount() uint64 {
if heads := kv.HeadCount(); heads > 0 {
return kv.EmbeddingLength() / kv.HeadCount()
}
return 0
}
func (kv KV) EmbeddingHeadCountK() uint64 {
if k := kv.u64(fmt.Sprintf("%s.attention.key_length", kv.Architecture())); k > 0 {
return k
}
return kv.EmbeddingHeadCount()
}
func (kv KV) EmbeddingHeadCountV() uint64 {
if v := kv.u64(fmt.Sprintf("%s.attention.value_length", kv.Architecture())); v > 0 {
return v
}
return kv.EmbeddingHeadCount()
}
func (kv KV) GQA() uint64 {
return kv.HeadCount() / kv.HeadCountKV()
}
@@ -280,18 +254,7 @@ func DetectGGMLType(b []byte) string {
}
}
// DecodeGGML decodes a GGML model from the given reader.
//
// It collects array values for arrays with a size less than or equal to
// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected.
func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
if maxArraySize == 0 {
maxArraySize = 1024
}
rs = bufioutil.NewBufferedSeeker(rs, 32<<10)
func DecodeGGML(rs io.ReadSeeker) (*GGML, int64, error) {
var magic uint32
if err := binary.Read(rs, binary.LittleEndian, &magic); err != nil {
return nil, 0, err
@@ -304,15 +267,17 @@ func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
case FILE_MAGIC_GGLA:
c = &containerGGLA{}
case FILE_MAGIC_GGUF_LE:
c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize}
c = &containerGGUF{ByteOrder: binary.LittleEndian}
case FILE_MAGIC_GGUF_BE:
c = &containerGGUF{ByteOrder: binary.BigEndian, maxArraySize: maxArraySize}
c = &containerGGUF{ByteOrder: binary.BigEndian}
default:
return nil, 0, errors.New("invalid file magic")
}
model, err := c.Decode(rs)
if err != nil {
if errors.Is(err, io.EOF) {
// noop
} else if err != nil {
return nil, 0, err
}
@@ -332,10 +297,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
embedding := llm.KV().EmbeddingLength()
heads := llm.KV().HeadCount()
headsKV := llm.KV().HeadCountKV()
vocab := uint64(llm.KV()["tokenizer.ggml.tokens"].(*array).size)
embeddingHeads := llm.KV().EmbeddingHeadCount()
embeddingHeadsK := llm.KV().EmbeddingHeadCountK()
vocab := uint64(len(llm.KV()["tokenizer.ggml.tokens"].([]any)))
layers := llm.Tensors().Layers()
@@ -345,8 +307,7 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
partialOffload = 4 * batch * embedding
partialOffload += max(
// 4*batch*(4+6*embedding+context*(2*heads)+llm.KV().GQA()),
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embeddingHeads*headsKV),
4*batch*(1+embedding+max(context, embedding))+embedding*embedding*9/16+4*context*(batch*heads+embedding/heads*headsKV),
4*batch*(embedding+vocab)+embedding*vocab*105/128,
)
@@ -354,30 +315,21 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
// mixtral 8x22b
ff := uint64(llm.KV()["llama.feed_forward_length"].(uint32))
partialOffload = max(
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embeddingHeads*headsKV),
4*(context*batch*heads+context*embeddingHeads*headsKV+batch*1024+embeddingHeads*headsKV*batch),
3*ffnGateExpsWeight.Size()+4*batch*(2*ff+headsKV+embedding+context+embedding/heads*headsKV),
4*(context*batch*heads+context*embedding/heads*headsKV+batch*1024+embedding/heads*headsKV*batch),
)
} else if ffnGateWeight, ok := layers["blk.0"]["ffn_gate.0.weight"]; ok {
// mixtral 8x7b
ffnGateWeight1 := ffnGateWeight.Shape[1]
fullOffload = 4 * batch * (2 + 3*embedding + context*(1+heads) + 2*headsKV + ffnGateWeight1)
partialOffload = max(
4*batch*(3+embeddingHeads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
4*batch*(3+embedding/heads*headsKV+embedding+context*(1+heads)+ffnGateWeight1)+(embedding*embedding+3*embedding*headsKV*ffnGateWeight1)*9/16,
4*batch*(1+2*embedding+context*(1+heads))+embedding*(6*context*headsKV/heads+embedding*9/16),
)
}
case "gemma", "gemma2":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
)
partialOffload = max(
4*embedding*batch+embedding*vocab*105/128+4*vocab*batch,
4*batch*(2*embedding+1+2*embeddingHeadsK*heads+context+context*heads)+
4*embeddingHeadsK*context*8+
embedding*embeddingHeadsK*heads*9/16,
)
case "gemma":
fullOffload = 4 * batch * (embedding + vocab)
partialOffload = 4*batch*(2*embedding+vocab+1) + embedding*vocab*105/128
case "command-r":
fullOffload = max(
4*batch*(embedding+vocab),
@@ -414,42 +366,6 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
4*batch*(vocab+2*embedding),
fullOffload,
)
case "deepseek2":
fullOffload = max(
4*batch*(3*embedding+vocab),
4*batch*(3*embedding+2+context*(1+headsKV)+2*embeddingHeadsK*headsKV),
)
partialOffload = max(
4*batch*(3*embedding+vocab)+embedding*vocab*105/128,
4*batch*(2*embedding+1+2*embeddingHeadsK*headsKV+context+context*headsKV)+4*embeddingHeadsK*context*headsKV+embedding*embeddingHeadsK*headsKV*9/16,
)
case "chatglm":
fullOffload = 4 * batch * (embedding + vocab)
partialOffload = 4*batch*(embedding+vocab) + embedding*vocab*105/128
if qkvBias, ok := layers["blk.0"]["attn_qkv.bias"]; ok {
fullOffload = max(
fullOffload,
4*batch*(2+
2*embedding+
context+
context*heads+
embeddingHeadsK*heads+
qkvBias.Shape[0]),
)
partialOffload = max(
partialOffload,
4*batch*(1+
2*embedding+
embeddingHeadsK*heads+
context+
context*heads)+
4*embeddingHeadsK*context+
4*context*embeddingHeadsK+
4*qkvBias.Shape[0],
)
}
}
return

View File

@@ -1 +0,0 @@
package llm

View File

@@ -3,10 +3,11 @@ package llm
import (
"bytes"
"encoding/binary"
"encoding/json"
"fmt"
"io"
"strings"
"log/slog"
)
type containerGGUF struct {
@@ -28,12 +29,6 @@ type containerGGUF struct {
NumTensor uint64
NumKV uint64
}
maxArraySize int
}
func (c *containerGGUF) canCollectArray(size int) bool {
return c.maxArraySize < 0 || size <= c.maxArraySize
}
func (c *containerGGUF) Name() string {
@@ -59,6 +54,7 @@ func (c *containerGGUF) Decode(rs io.ReadSeeker) (model, error) {
}
model := newGGUF(c)
slog.Debug(fmt.Sprintf("model = %#v", model))
if err := model.Decode(rs); err != nil {
return nil, err
}
@@ -89,8 +85,6 @@ type gguf struct {
tensors []*Tensor
parameters uint64
scratch [16 << 10]byte
}
func newGGUF(container *containerGGUF) *gguf {
@@ -187,34 +181,34 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
}
// decode tensors
for range llm.numTensor() {
for i := 0; uint64(i) < llm.numTensor(); i++ {
name, err := readGGUFString(llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor name: %w", err)
return err
}
// dims is the number of dimensions in the tensor
dims, err := readGGUF[uint32](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor dimensions: %w", err)
return err
}
shape := [4]uint64{1, 1, 1, 1}
for i := 0; uint32(i) < dims; i++ {
shape[i], err = readGGUF[uint64](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor shape: %w", err)
return err
}
}
kind, err := readGGUF[uint32](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor kind: %w", err)
return err
}
offset, err := readGGUF[uint64](llm, rs)
if err != nil {
return fmt.Errorf("failed to read tensor offset: %w", err)
return err
}
tensor := Tensor{
@@ -236,19 +230,24 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
alignment = 32
}
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return err
}
padding := llm.padding(offset, int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return err
}
for _, tensor := range llm.tensors {
offset, err := rs.Seek(0, io.SeekCurrent)
if err != nil {
return fmt.Errorf("failed to get current offset: %w", err)
}
padding := llm.padding(offset, int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return fmt.Errorf("failed to seek to init padding: %w", err)
}
if _, err := rs.Seek(int64(tensor.Size()), io.SeekCurrent); err != nil {
return fmt.Errorf("failed to seek to tensor: %w", err)
return err
}
padding := llm.padding(int64(tensor.Size()), int64(alignment))
if _, err := rs.Seek(padding, io.SeekCurrent); err != nil {
return err
}
}
@@ -286,48 +285,22 @@ func readGGUFV1String(llm *gguf, r io.Reader) (string, error) {
return b.String(), nil
}
func discardGGUFString(llm *gguf, r io.Reader) error {
buf := llm.scratch[:8]
_, err := io.ReadFull(r, buf)
if err != nil {
return err
}
size := int(llm.ByteOrder.Uint64(buf))
for size > 0 {
n, err := r.Read(llm.scratch[:min(size, cap(llm.scratch))])
if err != nil {
return err
}
size -= n
}
return nil
}
func readGGUFString(llm *gguf, r io.Reader) (string, error) {
if llm.Version == 1 {
return readGGUFV1String(llm, r)
}
buf := llm.scratch[:8]
_, err := io.ReadFull(r, buf)
if err != nil {
var length uint64
if err := binary.Read(r, llm.ByteOrder, &length); err != nil {
return "", err
}
length := int(llm.ByteOrder.Uint64(buf))
if length > len(llm.scratch) {
buf = make([]byte, length)
} else {
buf = llm.scratch[:length]
}
clear(buf)
_, err = io.ReadFull(r, buf)
if err != nil {
var b bytes.Buffer
if _, err := io.CopyN(&b, r, int64(length)); err != nil {
return "", err
}
return string(buf), nil
return b.String(), nil
}
func writeGGUFString(llm *gguf, w io.Writer, s string) error {
@@ -343,16 +316,7 @@ func writeGGUFString(llm *gguf, w io.Writer, s string) error {
return err
}
type array struct {
size int
values []any
}
func (a *array) MarshalJSON() ([]byte, error) {
return json.Marshal(a.values)
}
func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
func readGGUFV1Array(llm *gguf, r io.Reader) (a []any, err error) {
t, err := readGGUF[uint32](llm, r)
if err != nil {
return nil, err
@@ -363,12 +327,7 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
a := &array{size: int(n)}
if llm.canCollectArray(int(n)) {
a.values = make([]any, 0, int(n))
}
for i := range n {
for i := 0; uint32(i) < n; i++ {
var e any
switch t {
case ggufTypeUint8:
@@ -402,15 +361,13 @@ func readGGUFV1Array(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
if a.values != nil {
a.values[i] = e
}
a = append(a, e)
}
return a, nil
return
}
func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
func readGGUFArray(llm *gguf, r io.Reader) (a []any, err error) {
if llm.Version == 1 {
return readGGUFV1Array(llm, r)
}
@@ -425,12 +382,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
a := &array{size: int(n)}
if llm.canCollectArray(int(n)) {
a.values = make([]any, int(n))
}
for i := range n {
for i := 0; uint64(i) < n; i++ {
var e any
switch t {
case ggufTypeUint8:
@@ -456,11 +408,7 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
case ggufTypeBool:
e, err = readGGUF[bool](llm, r)
case ggufTypeString:
if a.values != nil {
e, err = readGGUFString(llm, r)
} else {
err = discardGGUFString(llm, r)
}
e, err = readGGUFString(llm, r)
default:
return nil, fmt.Errorf("invalid array type: %d", t)
}
@@ -468,12 +416,10 @@ func readGGUFArray(llm *gguf, r io.Reader) (*array, error) {
return nil, err
}
if a.values != nil {
a.values[i] = e
}
a = append(a, e)
}
return a, nil
return
}
func writeGGUFArray[S ~[]E, E any](llm *gguf, w io.Writer, t uint32, s S) error {
@@ -537,7 +483,6 @@ var ggufKVOrder = map[string][]string{
"tokenizer.ggml.add_bos_token",
"tokenizer.ggml.add_eos_token",
"tokenizer.chat_template",
"bert.pooling_type",
},
}

View File

@@ -1,13 +1,12 @@
package llm
// #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: -static-libstdc++ -static-libgcc -static -L${SRCDIR}/build/windows/amd64_static -L${SRCDIR}/build/windows/amd64_static/src -L${SRCDIR}/build/windows/amd64_static/ggml/src
// #cgo windows,arm64 LDFLAGS: -static-libstdc++ -static-libgcc -static -L${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
// #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++
// #include <stdlib.h>
// #include "llama.h"
import "C"
@@ -33,7 +32,7 @@ func Quantize(infile, outfile string, ftype fileType) error {
params.ftype = ftype.Value()
if rc := C.llama_model_quantize(cinfile, coutfile, &params); rc != 0 {
return fmt.Errorf("failed to quantize model. This model architecture may not be supported, or you may need to upgrade Ollama to the latest version")
return fmt.Errorf("llama_model_quantize: %d", rc)
}
return nil

View File

@@ -3,10 +3,9 @@ package llm
import (
"fmt"
"log/slog"
"strconv"
"strings"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/gpu"
)
@@ -17,8 +16,7 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
var estimatedVRAM uint64
for _, gpus := range allGpus.ByLibrary() {
var layerCount int
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
layerCount, estimatedVRAM, _ = EstimateGPULayers(gpus, ggml, projectors, opts)
if opts.NumGPU < 0 {
if layerCount > 0 && layerCount >= int(ggml.KV().BlockCount()+1) {
return true, estimatedVRAM
@@ -32,76 +30,24 @@ func PredictServerFit(allGpus gpu.GpuInfoList, ggml *GGML, adapters, projectors
return false, estimatedVRAM
}
type MemoryEstimate struct {
// How many layers we predict we can load
Layers int
// The size of the graph which occupies the main GPU
Graph uint64
// How much VRAM will be allocated given the number of layers we predict
VRAMSize uint64
// The total size of the model if loaded into VRAM. If all layers are loaded, VRAMSize == TotalSize
TotalSize uint64
// For multi-GPU scenarios, this provides the tensor split parameter
TensorSplit string
// For multi-GPU scenarios, this is the size in bytes per GPU
GPUSizes []uint64
// internal fields for logging purposes
inferenceLibrary string
layersRequested int
layersModel int
availableList []string
kv uint64
allocationsList []string
memoryWeights uint64
memoryLayerOutput uint64
graphFullOffload uint64
graphPartialOffload uint64
}
// Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
// The GPUs provided must all be the same Library
func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) MemoryEstimate {
// Graph size for a partial offload, applies to all GPUs
var graphPartialOffload uint64
// Graph size when all layers are offloaded, applies to all GPUs
var graphFullOffload uint64
// Final graph offload once we know full or partial
var graphOffload uint64
// Projectors loaded into GPU0 only
var projectorSize uint64
// Conditional output size on GPU 0
var memoryLayerOutput uint64
// The sizes of a layer
var layerSize uint64
// The sum of all the layer sizes (just for logging)
var memoryWeights uint64
// True if all the layers are loaded
var fullyLoaded bool
// Overflow that didn't fit into the GPU
var overflow uint64
availableList := make([]string, len(gpus))
for i, gpu := range gpus {
availableList[i] = format.HumanBytes2(gpu.FreeMemory)
func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts api.Options) (int, uint64, uint64) {
var memoryAvailable uint64
for _, info := range gpus {
memoryAvailable += info.FreeMemory
}
slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", availableList)
if envconfig.MaxVRAM > 0 {
memoryAvailable = envconfig.MaxVRAM
}
slog.Debug("evaluating", "library", gpus[0].Library, "gpu_count", len(gpus), "available", format.HumanBytes2(memoryAvailable))
// TODO - this is probably wrong, first GPU vs secondaries will have different overheads
memoryMinimum := gpus[0].MinimumMemory
for _, projector := range projectors {
projectorSize += projectorMemoryRequirements(projector)
memoryMinimum += projectorMemoryRequirements(projector)
// multimodal models require at least 2048 context
opts.NumCtx = max(opts.NumCtx, 2048)
@@ -110,246 +56,127 @@ func EstimateGPULayers(gpus []gpu.GpuInfo, ggml *GGML, projectors []string, opts
layers := ggml.Tensors().Layers()
// add one layer worth of memory as a buffer
if blk0, ok := layers["blk.0"]; ok {
layerSize = blk0.size()
} else {
slog.Warn("model missing blk.0 layer size")
memoryMinimum += blk0.size()
}
// fp16 k,v = sizeof(float16) * n_ctx * n_layer * (n_embd_head_k + n_embd_head_v) * n_head_kv
var kv uint64 = 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * (ggml.KV().EmbeddingHeadCountK() + ggml.KV().EmbeddingHeadCountV()) * ggml.KV().HeadCountKV()
// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
var kv uint64 = 2 * 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * ggml.KV().EmbeddingLength() / ggml.KV().HeadCount() * ggml.KV().HeadCountKV()
// KV is proportional to the number of layers
layerSize += kv / ggml.KV().BlockCount()
graphPartialOffload, graphFullOffload = ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
graphPartialOffload, graphFullOffload := ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
if graphPartialOffload == 0 {
graphPartialOffload = ggml.KV().GQA() * kv / 6
}
if graphFullOffload == 0 {
graphFullOffload = graphPartialOffload
}
graphFullOffload *= uint64(len(gpus))
graphPartialOffload *= uint64(len(gpus))
// on metal there's no partial offload overhead
if gpus[0].Library == "metal" {
graphPartialOffload = graphFullOffload
} else if len(gpus) > 1 {
// multigpu should always use the partial graph size
graphFullOffload = graphPartialOffload
}
// memoryRequiredTotal represents the memory required for full GPU offloading (all layers)
memoryRequiredTotal := memoryMinimum + graphFullOffload
// memoryRequiredPartial represents the memory required for partial GPU offloading (n > 0, n < layers)
memoryRequiredPartial := memoryMinimum + graphPartialOffload
var memoryLayerOutput uint64
if layer, ok := layers["output_norm"]; ok {
memoryLayerOutput += layer.size()
}
if layer, ok := layers["output"]; ok {
memoryLayerOutput += layer.size()
} else if layer, ok := layers["token_embd"]; ok {
memoryLayerOutput += layer.size()
}
// Output layer handled at the end if we have space
gpuZeroOverhead := projectorSize
if gpus[0].Library == "metal" && opts.UseMMap {
// memory is preallocated for output tensors
memoryRequiredTotal += memoryLayerOutput
memoryRequiredPartial += memoryLayerOutput
}
// Reduce set of GPUs to only those that have sufficient space to fit overhead and at least one layer
var layerCount int
layerCounts := make([]int, len(gpus))
gpuAllocations := make([]uint64, len(gpus))
type gs struct {
i int
g *gpu.GpuInfo
}
gpusWithSpace := []gs{}
for i := range gpus {
var gzo uint64
if len(gpusWithSpace) == 0 {
gzo = gpuZeroOverhead
}
// Only include GPUs that can fit the graph, gpu minimum, the layer buffer and at least more layer
if gpus[i].FreeMemory < gzo+max(graphPartialOffload, graphFullOffload)+gpus[i].MinimumMemory+2*layerSize {
slog.Debug("gpu has too little memory to allocate any layers", "gpu", gpus[i])
continue
}
gpusWithSpace = append(gpusWithSpace, gs{i, &gpus[i]})
gpuAllocations[i] += gpus[i].MinimumMemory + layerSize // We hold off on graph until we know partial vs. full
}
var gpuZeroID int
if len(gpusWithSpace) > 0 {
gpuZeroID = gpusWithSpace[0].i
gpuAllocations[gpuZeroID] += gpuZeroOverhead
}
// For all the layers, find where they can fit on the GPU(s)
for i := range int(ggml.KV().BlockCount()) {
// Some models have inconsistent layer sizes
if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
layerSize = blk.size()
layerSize += kv / ggml.KV().BlockCount()
}
memoryWeights += layerSize
memoryLayer := blk.size()
if opts.NumGPU >= 0 && layerCount >= opts.NumGPU {
// Stop allocating on GPU(s) once we hit the users target NumGPU
continue
}
// KV is proportional to the number of layers
memoryLayer += kv / ggml.KV().BlockCount()
// distribute the layers across the GPU(s) that have space
for j := len(gpusWithSpace); j > 0; j-- {
g := gpusWithSpace[i%j]
used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
if g.g.FreeMemory > used+layerSize {
gpuAllocations[g.i] += layerSize
layerCounts[g.i]++
memoryRequiredTotal += memoryLayer
if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredPartial+memoryLayer) {
memoryRequiredPartial += memoryLayer
layerCount++
break
} else {
gpusWithSpace = append(gpusWithSpace[:i%j], gpusWithSpace[i%j+1:]...)
}
}
}
if layerCount >= int(ggml.KV().BlockCount()) {
fullyLoaded = true
} else {
for i := layerCount; i < int(ggml.KV().BlockCount()); i++ {
overflow += layerSize
}
if gpus[0].Library != "metal" || !opts.UseMMap {
// memory was not preallocated for output tensors
memoryRequiredTotal += memoryLayerOutput
}
// Determine if we need to consider output then find where it fits
if memoryLayerOutput > 0 && (opts.NumGPU < 0 || layerCount < opts.NumGPU) {
for j := len(gpusWithSpace); j > 0; j-- {
g := gpusWithSpace[layerCount%j]
used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
if g.g.FreeMemory > used+memoryLayerOutput {
gpuAllocations[g.i] += memoryLayerOutput
layerCounts[g.i]++
layerCount++
break
}
}
if layerCount < int(ggml.KV().BlockCount())+1 {
fullyLoaded = false
overflow += memoryLayerOutput
}
if (opts.NumGPU >= 0 && layerCount+1 <= opts.NumGPU) || (opts.NumGPU < 0 && memoryAvailable > memoryRequiredTotal) {
layerCount = int(ggml.KV().BlockCount()) + 1
memoryRequiredPartial = memoryRequiredTotal
}
// Add the applicable (full or partial) graph allocations
for i := range gpus {
if layerCounts[i] <= 0 {
continue
}
if fullyLoaded {
gpuAllocations[i] += graphFullOffload
} else {
gpuAllocations[i] += graphPartialOffload
}
}
if fullyLoaded {
graphOffload = graphFullOffload
} else {
graphOffload = graphPartialOffload
}
memoryWeights := memoryRequiredTotal - memoryMinimum - graphFullOffload - kv
// Summaries for the log
var memoryRequiredPartial, memoryRequiredTotal uint64
for i := range gpuAllocations {
memoryRequiredPartial += gpuAllocations[i]
}
memoryRequiredTotal = memoryRequiredPartial + overflow
tensorSplit := ""
if len(gpus) > 1 {
splits := make([]string, len(gpus))
for i, count := range layerCounts {
splits[i] = strconv.Itoa(count)
}
tensorSplit = strings.Join(splits, ",")
}
allocationsList := []string{}
for _, a := range gpuAllocations {
allocationsList = append(allocationsList, format.HumanBytes2(a))
}
estimate := MemoryEstimate{
TotalSize: memoryRequiredTotal,
Layers: 0,
Graph: 0,
VRAMSize: 0,
GPUSizes: []uint64{},
inferenceLibrary: gpus[0].Library,
layersRequested: opts.NumGPU,
layersModel: int(ggml.KV().BlockCount()) + 1,
availableList: availableList,
kv: kv,
allocationsList: allocationsList,
memoryWeights: memoryWeights,
memoryLayerOutput: memoryLayerOutput,
graphFullOffload: graphFullOffload,
graphPartialOffload: graphPartialOffload,
}
if gpus[0].Library == "cpu" {
return estimate
}
if layerCount == 0 {
slog.Debug("insufficient VRAM to load any model layers")
return estimate
}
estimate.Layers = layerCount
estimate.Graph = graphOffload
estimate.VRAMSize = memoryRequiredPartial
estimate.TotalSize = memoryRequiredTotal
estimate.TensorSplit = tensorSplit
estimate.GPUSizes = gpuAllocations
return estimate
}
func (m MemoryEstimate) log() {
slog.Info(
"offload to "+m.inferenceLibrary,
"offload to gpu",
slog.Group(
"layers",
// requested number of layers to offload
"requested", m.layersRequested,
// The number of layers the model has (including output)
"model", m.layersModel,
"requested", opts.NumGPU,
// estimated number of layers that can be offloaded
"offload", m.Layers,
// multi-gpu split for tensors
"split", m.TensorSplit,
"real", layerCount,
),
slog.Group(
"memory",
// memory available by GPU for offloading
"available", m.availableList,
// memory available for offloading
"available", format.HumanBytes2(memoryAvailable),
slog.Group(
"required",
// memory required for full offloading
"full", format.HumanBytes2(m.TotalSize),
"full", format.HumanBytes2(memoryRequiredTotal),
// memory required to offload layers.estimate layers
"partial", format.HumanBytes2(m.VRAMSize),
"partial", format.HumanBytes2(memoryRequiredPartial),
// memory of KV cache
"kv", format.HumanBytes2(m.kv),
// Allocations across the GPUs
"allocations", m.allocationsList,
"kv", format.HumanBytes2(kv),
),
slog.Group(
"weights",
// memory of the weights
"total", format.HumanBytes2(m.memoryWeights),
"total", format.HumanBytes2(memoryWeights),
// memory of repeating layers
"repeating", format.HumanBytes2(m.memoryWeights-m.memoryLayerOutput),
"repeating", format.HumanBytes2(memoryWeights-memoryLayerOutput),
// memory of non-repeating layers
"nonrepeating", format.HumanBytes2(m.memoryLayerOutput),
"nonrepeating", format.HumanBytes2(memoryLayerOutput),
),
slog.Group(
"graph",
// memory of graph when fully offloaded
"full", format.HumanBytes2(m.graphFullOffload),
"full", format.HumanBytes2(graphFullOffload),
// memory of graph when not fully offloaded
"partial", format.HumanBytes2(m.graphPartialOffload),
"partial", format.HumanBytes2(graphPartialOffload),
),
),
)
if gpus[0].Library == "cpu" {
return 0, 0, memoryRequiredTotal
}
if memoryRequiredPartial > memoryAvailable {
slog.Debug("insufficient VRAM to load any model layers")
return 0, 0, memoryRequiredTotal
}
return layerCount, memoryRequiredPartial, memoryRequiredTotal
}

View File

@@ -1,130 +0,0 @@
package llm
import (
"bytes"
"encoding/binary"
"fmt"
"os"
"testing"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/gpu"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestEstimateGPULayers(t *testing.T) {
envconfig.Debug = true
modelName := "dummy"
f, err := os.CreateTemp(t.TempDir(), modelName)
require.NoError(t, err)
defer f.Close()
gguf := NewGGUFV3(binary.LittleEndian)
inputLayerCount := 5
tensors := []Tensor{
{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.1.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.2.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.3.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "blk.4.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
}
assert.Len(t, tensors, inputLayerCount+1)
err = gguf.Encode(f, KV{
"general.architecture": "llama",
"general.name": "name",
"llama.context_length": uint32(32),
"llama.embedding_length": uint32(4096),
"llama.block_count": uint32(inputLayerCount),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(32),
"tokenizer.ggml.tokens": []string{" "},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, tensors)
require.NoError(t, err)
ggml, err := LoadModel(f.Name(), 0)
if err != nil {
t.Fatal(err)
}
// Simple CPU scenario
gpus := []gpu.GpuInfo{
{
Library: "cpu",
},
}
projectors := []string{}
opts := api.DefaultOptions()
t.Run("cpu", func(t *testing.T) {
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
assert.Equal(t, 0, estimate.Layers)
assert.Equal(t, uint64(0), estimate.Graph)
})
// derived from the dummy ggml file above
graphPartialOffload := uint64(202377216)
graphFullOffload := uint64(171968512)
layerSize := uint64(33554436)
projectorSize := uint64(0)
memoryLayerOutput := uint64(4)
// Dual CUDA scenario with assymetry
gpuMinimumMemory := uint64(2048)
gpus = []gpu.GpuInfo{
{
Library: "cuda",
MinimumMemory: gpuMinimumMemory,
},
{
Library: "cuda",
MinimumMemory: gpuMinimumMemory,
},
}
// Nested array: GPU0 layer space, GPU1 layer space, expected gpu0, expected gpu1
for i, s := range []struct {
layer0, layer1 uint64
expect0, expect1 uint64
}{
{1, 1, 1, 1},
{2, 1, 2, 1},
{2, 2, 2, 2},
{1, 2, 1, 2},
{3, 3, 3, 3},
{4, 4, 3, 3},
{6, 6, 3, 3},
{0, 3, 0, 3},
} {
t.Run(fmt.Sprintf("%v", s), func(t *testing.T) {
gpus[0].FreeMemory = 0
gpus[1].FreeMemory = 0
gpus[0].FreeMemory += projectorSize
if s.layer0 > 0 {
gpus[0].FreeMemory += memoryLayerOutput
} else {
gpus[1].FreeMemory += memoryLayerOutput
}
gpus[0].FreeMemory += gpuMinimumMemory + layerSize + s.layer0*layerSize + 1
gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
assert.Equal(t, int(s.expect0+s.expect1), estimate.Layers, "scenario %d: %v", i, s)
assert.Equal(t, fmt.Sprintf("%d,%d", s.expect0, s.expect1), estimate.TensorSplit, "scenario %d: %v", i, s)
var layerSums uint64
for _, b := range estimate.GPUSizes {
layerSums += b
}
if estimate.Layers < inputLayerCount+1 {
assert.Less(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
assert.Equal(t, estimate.VRAMSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
} else {
assert.Equal(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
assert.Equal(t, estimate.TotalSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
}
})
}
}

View File

@@ -1,8 +1,8 @@
diff --git a/common/common.cpp b/common/common.cpp
index 2c05a4d4..927f0e3d 100644
index ba1ecf0e..cead57cc 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2093,6 +2093,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
@@ -1836,6 +1836,8 @@ 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;
@@ -12,20 +12,20 @@ index 2c05a4d4..927f0e3d 100644
mparams.kv_overrides = NULL;
} else {
diff --git a/common/common.h b/common/common.h
index 65c0ef81..ebca2c77 100644
index d80344f2..71e84834 100644
--- a/common/common.h
+++ b/common/common.h
@@ -184,6 +184,13 @@ struct gpt_params {
@@ -174,6 +174,13 @@ struct gpt_params {
// multimodal models (see examples/llava)
std::string mmproj = ""; // path to multimodal projector
std::vector<std::string> image; // path to image file(s)
+
+ // Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
+ // If the provided progress_callback returns true, model loading continues.
+ // If it returns false, model loading is immediately aborted.
+ llama_progress_callback progress_callback = NULL;
+ // context pointer passed to the progress callback
+ void * progress_callback_user_data;
+
// 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)
};
void gpt_params_handle_model_default(gpt_params & params);

View File

@@ -1,8 +1,17 @@
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
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
}
} catch (const std::exception & err) {
LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
@@ -11,7 +20,7 @@ index 73f52435..58a00fb1 100644
}
return 0;
@@ -17564,16 +17564,23 @@ struct llama_model * llama_load_model_from_file(
@@ -15600,16 +15600,23 @@ struct llama_model * llama_load_model_from_file(
}
model->rpc_servers.push_back(servers);
}
@@ -43,3 +52,6 @@ index 73f52435..58a00fb1 100644
}
return model;
--
2.45.1

View File

@@ -1,7 +1,7 @@
diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m
diff --git a/ggml-metal.m b/ggml-metal.m
index 0207b787..b5e9884b 100644
--- a/ggml/src/ggml-metal.m
+++ b/ggml/src/ggml-metal.m
--- a/ggml-metal.m
+++ b/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/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(
diff --git a/llama.cpp b/llama.cpp
index 40d2ec2c..74f3ee9c 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -4642,16 +4642,7 @@ static void llm_load_vocab(
// for now, only BPE models have pre-tokenizers
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__);
@@ -15,18 +15,18 @@ index 2b9ace28..172640e2 100644
- LLAMA_LOG_WARN("%s: ************************************ \n", __func__);
- LLAMA_LOG_WARN("%s: \n", __func__);
- vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
- } else if (tokenizer_pre == "default") {
+ if (tokenizer_pre == "default") {
- } else if (
+ if (
tokenizer_pre == "default") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
} else if (
tokenizer_pre == "llama3" ||
@@ -5439,7 +5430,8 @@ static void llm_load_vocab(
tokenizer_pre == "jais") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
@@ -4703,7 +4694,8 @@ static void llm_load_vocab(
tokenizer_pre == "smaug-bpe") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_SMAUG;
} 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 if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
} else {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;

View File

@@ -1,7 +1,7 @@
diff --git a/src/llama.cpp b/src/llama.cpp
diff --git a/llama.cpp b/llama.cpp
index 40d2ec2c..f34eb79a 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
--- a/llama.cpp
+++ b/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

@@ -1,45 +0,0 @@
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

@@ -1,42 +0,0 @@
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

@@ -1,60 +0,0 @@
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 getAvailableServers() {
for v := range availableServers() {
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 getAvailableServers() map[string]string {
func availableServers() map[string]string {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
slog.Error("payload lookup error", "error", err)
@@ -58,7 +58,7 @@ func getAvailableServers() map[string]string {
}
// glob payloadsDir for files that start with ollama_
pattern := filepath.Join(payloadsDir, "*", "ollama_*")
pattern := filepath.Join(payloadsDir, "*")
files, err := filepath.Glob(pattern)
if err != nil {
@@ -69,7 +69,7 @@ func getAvailableServers() map[string]string {
servers := make(map[string]string)
for _, file := range files {
slog.Debug("availableServers : found", "file", file)
servers[filepath.Base(filepath.Dir(file))] = filepath.Dir(file)
servers[filepath.Base(file)] = file
}
return servers
@@ -80,10 +80,10 @@ func getAvailableServers() map[string]string {
// TODO - switch to metadata based mapping
func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := getAvailableServers()
availableServers := availableServers()
requested := info.Library
if info.Variant != gpu.CPUCapabilityNone {
requested += "_" + info.Variant.String()
if info.Variant != "" {
requested += "_" + info.Variant
}
servers := []string{}
@@ -115,29 +115,27 @@ func serversForGpu(info gpu.GpuInfo) []string {
servers = append(servers, alt...)
}
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
}
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUVariant()
// 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 != "" {
for cmp := range availableServers {
if cmp == "cpu_"+variant {
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
@@ -148,11 +146,11 @@ func serverForCpu() string {
if runtime.GOOS == "darwin" && runtime.GOARCH == "arm64" {
return "metal"
}
variant := gpu.GetCPUCapability()
availableServers := getAvailableServers()
if variant != gpu.CPUCapabilityNone {
variant := gpu.GetCPUVariant()
availableServers := availableServers()
if variant != "" {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
if cmp == "cpu_"+variant {
return cmp
}
}

View File

@@ -33,13 +33,12 @@ type LlamaServer interface {
Ping(ctx context.Context) error
WaitUntilRunning(ctx context.Context) error
Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error
Embed(ctx context.Context, input []string) ([][]float32, error)
Embedding(ctx context.Context, prompt string) ([]float64, error)
Tokenize(ctx context.Context, content string) ([]int, error)
Detokenize(ctx context.Context, tokens []int) (string, error)
Close() error
EstimatedVRAM() uint64 // Total VRAM across all GPUs
EstimatedVRAM() uint64
EstimatedTotal() uint64
EstimatedVRAMByGPU(gpuID string) uint64
}
// llmServer is an instance of the llama.cpp server
@@ -50,22 +49,18 @@ type llmServer struct {
status *StatusWriter
options api.Options
estimate MemoryEstimate
totalLayers uint64
// gpuCount int
gpus gpu.GpuInfoList // Recorded just before the model loaded, free space will be incorrect
loadDuration time.Duration // Record how long it took the model to load
loadProgress float32
// TODO - this should be broken down by GPU
estimatedVRAM uint64 // Estimated usage of VRAM by the loaded model
estimatedTotal uint64 // Total size of model
totalLayers uint64
gpuCount int
loadDuration time.Duration // Record how long it took the model to load
loadProgress float32
sem *semaphore.Weighted
}
// LoadModel will load a model from disk. The model must be in the GGML format.
//
// It collects array values for arrays with a size less than or equal to
// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected.
func LoadModel(model string, maxArraySize int) (*GGML, error) {
func LoadModel(model string) (*GGML, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
@@ -76,66 +71,52 @@ func LoadModel(model string, maxArraySize int) (*GGML, error) {
}
defer f.Close()
ggml, _, err := DecodeGGML(f, maxArraySize)
ggml, _, err := DecodeGGML(f)
return ggml, err
}
// NewLlamaServer will run a server for the given GPUs
// The gpu list must be a single family.
func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options, numParallel int) (LlamaServer, error) {
func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options) (LlamaServer, error) {
var err error
var cpuRunner string
var estimate MemoryEstimate
var systemTotalMemory uint64
var systemFreeMemory uint64
var systemSwapFreeMemory uint64
var estimatedVRAM uint64
var estimatedTotal uint64
var systemMemory uint64
gpuCount := len(gpus)
if (len(gpus) == 1 && gpus[0].Library == "cpu") || opts.NumGPU == 0 {
// TODO evaluate system memory to see if we should block the load, or force an unload of another CPU runner
systemMemInfo, err := gpu.GetCPUMem()
if err != nil {
slog.Error("failed to lookup system memory", "error", err)
} else {
systemTotalMemory = systemMemInfo.TotalMemory
systemFreeMemory = systemMemInfo.FreeMemory
systemSwapFreeMemory = systemMemInfo.FreeSwap
slog.Debug("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
}
// If the user wants zero GPU layers, reset the gpu list to be CPU/system ram info
if opts.NumGPU == 0 {
gpus = gpu.GetCPUInfo()
}
if len(gpus) == 1 && gpus[0].Library == "cpu" {
cpuRunner = serverForCpu()
estimate = EstimateGPULayers(gpus, ggml, projectors, opts)
gpuCount = 0
_, _, estimatedTotal = EstimateGPULayers(gpus, ggml, projectors, opts)
} else {
estimate = EstimateGPULayers(gpus, ggml, projectors, opts)
if gpus[0].Library == "metal" {
memInfo, err := gpu.GetCPUMem()
if err != nil {
slog.Error("failed to lookup system memory", "error", err)
} else {
systemMemory = memInfo.TotalMemory
slog.Debug("system memory", "total", format.HumanBytes2(systemMemory))
}
}
var layers int
layers, estimatedVRAM, estimatedTotal = EstimateGPULayers(gpus, ggml, projectors, opts)
switch {
case gpus[0].Library == "metal" && estimate.VRAMSize > systemTotalMemory:
case gpus[0].Library == "metal" && estimatedVRAM > systemMemory:
// disable partial offloading when model is greater than total system memory as this
// can lead to locking up the system
opts.NumGPU = 0
case gpus[0].Library != "metal" && estimate.Layers == 0:
case gpus[0].Library != "metal" && layers == 0:
// Don't bother loading into the GPU if no layers can fit
cpuRunner = serverForCpu()
gpus = gpu.GetCPUInfo()
case opts.NumGPU < 0 && estimate.Layers > 0 && gpus[0].Library != "cpu":
opts.NumGPU = estimate.Layers
gpuCount = 0
case opts.NumGPU < 0 && layers > 0 && gpus[0].Library != "cpu":
opts.NumGPU = layers
}
}
// On linux, over-allocating CPU memory will almost always result in an error
if runtime.GOOS == "linux" {
systemMemoryRequired := estimate.TotalSize - estimate.VRAMSize
available := systemFreeMemory + systemSwapFreeMemory
if systemMemoryRequired > available {
slog.Warn("model request too large for system", "requested", format.HumanBytes2(systemMemoryRequired), "available", available, "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "swap", format.HumanBytes2(systemSwapFreeMemory))
return nil, fmt.Errorf("model requires more system memory (%s) than is available (%s)", format.HumanBytes2(systemMemoryRequired), format.HumanBytes2(available))
}
}
estimate.log()
// Loop through potential servers
finalErr := errors.New("no suitable llama servers found")
@@ -143,20 +124,7 @@ 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 := 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
}
}
availableServers := availableServers()
var servers []string
if cpuRunner != "" {
servers = []string{cpuRunner}
@@ -233,8 +201,7 @@ 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 = new(bool)
*opts.UseMMap = false
opts.UseMMap = false
}
}
@@ -242,13 +209,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--flash-attn")
}
// 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 == nil) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == nil) ||
(gpus[0].Library == "cpu" && opts.UseMMap == nil) ||
(opts.UseMMap != nil && !*opts.UseMMap) {
if !opts.UseMMap {
params = append(params, "--no-mmap")
}
@@ -260,12 +221,17 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--numa")
}
params = append(params, "--parallel", fmt.Sprintf("%d", numParallel))
numParallel := envconfig.NumParallel
if estimate.TensorSplit != "" {
params = append(params, "--tensor-split", estimate.TensorSplit)
// TODO (jmorganca): multimodal models don't support parallel yet
// see https://github.com/ollama/ollama/issues/4165
if len(projectors) > 0 {
numParallel = 1
slog.Warn("multimodal models don't support parallel requests yet")
}
params = append(params, "--parallel", fmt.Sprintf("%d", numParallel))
for i := range len(servers) {
dir := availableServers[servers[i]]
if dir == "" {
@@ -276,7 +242,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
}
if strings.HasPrefix(servers[i], "cpu") {
gpus = gpu.GetCPUInfo()
// TODO if we tried a gpu runner first, and it failed, record the error and bubble that back up
gpuCount = 0
}
// Find an availableServers port, retry on each iteration in case the failure was a port conflict race
@@ -298,8 +265,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
if runtime.GOOS == "windows" {
pathEnv = "PATH"
}
// prepend the server directory to LD_LIBRARY_PATH/PATH and the parent dir for common dependencies
libraryPaths := []string{dir, filepath.Dir(dir)}
// prepend the server directory to LD_LIBRARY_PATH/PATH
libraryPaths := []string{dir}
if libraryPath, ok := os.LookupEnv(pathEnv); ok {
// Append our runner directory to the path
@@ -332,25 +299,22 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
}
s := &llmServer{
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
estimate: estimate,
sem: semaphore.NewWeighted(int64(numParallel)),
totalLayers: ggml.KV().BlockCount() + 1,
gpus: gpus,
done: make(chan error, 1),
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
estimatedVRAM: estimatedVRAM,
estimatedTotal: estimatedTotal,
sem: semaphore.NewWeighted(int64(numParallel)),
totalLayers: ggml.KV().BlockCount() + 1,
gpuCount: gpuCount,
done: make(chan error, 1),
}
s.cmd.Env = os.Environ()
s.cmd.Stdout = os.Stdout
s.cmd.Stderr = s.status
envWorkarounds := [][2]string{}
for _, gpu := range gpus {
envWorkarounds = append(envWorkarounds, gpu.EnvWorkarounds...)
}
visibleDevicesEnv, visibleDevicesEnvVal := gpus.GetVisibleDevicesEnv()
pathEnvVal := strings.Join(libraryPaths, string(filepath.ListSeparator))
@@ -365,12 +329,6 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
} else if devicesNeeded && strings.EqualFold(cmp[0], visibleDevicesEnv) {
s.cmd.Env[i] = visibleDevicesEnv + "=" + visibleDevicesEnvVal
devicesNeeded = false
} else if len(envWorkarounds) != 0 {
for _, kv := range envWorkarounds {
if strings.EqualFold(cmp[0], kv[0]) {
s.cmd.Env[i] = kv[0] + "=" + kv[1]
}
}
}
}
if pathNeeded {
@@ -432,7 +390,7 @@ func projectorMemoryRequirements(filename string) uint64 {
}
defer file.Close()
ggml, _, err := DecodeGGML(file, 0)
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
@@ -582,9 +540,6 @@ 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:
}
@@ -687,7 +642,7 @@ type CompletionRequest struct {
Prompt string
Format string
Images []ImageData
Options *api.Options
Options api.Options
}
type CompletionResponse struct {
@@ -707,9 +662,10 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
}
defer s.sem.Release(1)
// put an upper limit on num_predict to avoid the model running on forever
// only allow maximum 10 "context shifts" to avoid infinite generation
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{
@@ -867,15 +823,15 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
return nil
}
type EmbedRequest struct {
Content []string `json:"content"`
type EmbeddingRequest struct {
Content string `json:"content"`
}
type EmbedResponse struct {
Embedding [][]float32 `json:"embedding"`
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}
func (s *llmServer) Embed(ctx context.Context, input []string) ([][]float32, error) {
func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, error) {
if err := s.sem.Acquire(ctx, 1); err != nil {
slog.Error("Failed to acquire semaphore", "error", err)
return nil, err
@@ -890,7 +846,7 @@ func (s *llmServer) Embed(ctx context.Context, input []string) ([][]float32, err
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
}
data, err := json.Marshal(EmbedRequest{Content: input})
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
@@ -917,7 +873,7 @@ func (s *llmServer) Embed(ctx context.Context, input []string) ([][]float32, err
return nil, fmt.Errorf("%s", body)
}
var embedding EmbedResponse
var embedding EmbeddingResponse
if err := json.Unmarshal(body, &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}
@@ -1048,20 +1004,11 @@ func (s *llmServer) Close() error {
}
func (s *llmServer) EstimatedVRAM() uint64 {
return s.estimate.VRAMSize
return s.estimatedVRAM
}
func (s *llmServer) EstimatedTotal() uint64 {
return s.estimate.TotalSize
}
func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
for i, gpu := range s.gpus {
if gpu.ID == gpuID {
return s.estimate.GPUSizes[i]
}
}
return 0
return s.estimatedTotal
}
func parseDurationMs(ms float64) time.Duration {

View File

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

View File

@@ -3,18 +3,15 @@ package openai
import (
"bytes"
"encoding/base64"
"encoding/json"
"fmt"
"io"
"math/rand"
"net/http"
"strings"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/types/model"
)
type Error struct {
@@ -30,7 +27,7 @@ type ErrorResponse struct {
type Message struct {
Role string `json:"role"`
Content any `json:"content"`
Content string `json:"content"`
}
type Choice struct {
@@ -45,12 +42,6 @@ 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"`
@@ -61,11 +52,6 @@ type ResponseFormat struct {
Type string `json:"type"`
}
type EmbedRequest struct {
Input any `json:"input"`
Model string `json:"model"`
}
type ChatCompletionRequest struct {
Model string `json:"model"`
Messages []Message `json:"messages"`
@@ -99,63 +85,6 @@ 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 Embedding struct {
Object string `json:"object"`
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
}
type ListCompletion struct {
Object string `json:"object"`
Data []Model `json:"data"`
}
type EmbeddingList struct {
Object string `json:"object"`
Data []Embedding `json:"data"`
Model string `json:"model"`
}
func NewError(code int, message string) ErrorResponse {
var etype string
switch code {
@@ -216,159 +145,10 @@ func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
}
}
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 toEmbeddingList(model string, r api.EmbedResponse) EmbeddingList {
if r.Embeddings != nil {
var data []Embedding
for i, e := range r.Embeddings {
data = append(data, Embedding{
Object: "embedding",
Embedding: e,
Index: i,
})
}
return EmbeddingList{
Object: "list",
Data: data,
Model: model,
}
}
return EmbeddingList{}
}
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, error) {
func fromRequest(r ChatCompletionRequest) api.ChatRequest {
var messages []api.Message
for _, msg := range r.Messages {
switch content := msg.Content.(type) {
case string:
messages = append(messages, api.Message{Role: msg.Role, Content: content})
case []any:
message := api.Message{Role: msg.Role}
for _, c := range content {
data, ok := c.(map[string]any)
if !ok {
return nil, fmt.Errorf("invalid message format")
}
switch data["type"] {
case "text":
text, ok := data["text"].(string)
if !ok {
return nil, fmt.Errorf("invalid message format")
}
message.Content = text
case "image_url":
var url string
if urlMap, ok := data["image_url"].(map[string]any); ok {
if url, ok = urlMap["url"].(string); !ok {
return nil, fmt.Errorf("invalid message format")
}
} else {
if url, ok = data["image_url"].(string); !ok {
return nil, fmt.Errorf("invalid message format")
}
}
types := []string{"jpeg", "jpg", "png"}
valid := false
for _, t := range types {
prefix := "data:image/" + t + ";base64,"
if strings.HasPrefix(url, prefix) {
url = strings.TrimPrefix(url, prefix)
valid = true
break
}
}
if !valid {
return nil, fmt.Errorf("invalid image input")
}
img, err := base64.StdEncoding.DecodeString(url)
if err != nil {
return nil, fmt.Errorf("invalid message format")
}
message.Images = append(message.Images, img)
default:
return nil, fmt.Errorf("invalid message format")
}
}
messages = append(messages, message)
default:
return nil, fmt.Errorf("invalid message content type: %T", content)
}
messages = append(messages, api.Message{Role: msg.Role, Content: msg.Content})
}
options := make(map[string]interface{})
@@ -376,7 +156,7 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []any:
case []interface{}:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
@@ -398,6 +178,9 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
if r.Seed != nil {
options["seed"] = *r.Seed
// temperature=0 is required for reproducible outputs
options["temperature"] = 0.0
}
if r.FrequencyPenalty != nil {
@@ -419,96 +202,45 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
format = "json"
}
return &api.ChatRequest{
return api.ChatRequest{
Model: r.Model,
Messages: messages,
Format: format,
Options: options,
Stream: &r.Stream,
}, nil
}
}
func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
options := make(map[string]any)
type DeleteCompletion struct {
Id string `json:"id"`
Object string `json:"object"`
Deleted bool `json:"deleted"`
}
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []any:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
stops = append(stops, str)
} else {
return api.GenerateRequest{}, fmt.Errorf("invalid type for 'stop' field: %T", s)
}
}
options["stop"] = stops
func toDeleteCompletion(model string) DeleteCompletion {
return DeleteCompletion{
Id: model,
Object: "model",
Deleted: true,
}
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
}
type ChatWriter struct {
stream bool
id string
BaseWriter
}
type CompleteWriter struct {
stream bool
id string
BaseWriter
}
type ListWriter struct {
BaseWriter
}
type RetrieveWriter struct {
type DeleteWriter struct {
BaseWriter
model string
}
type EmbedWriter struct {
BaseWriter
model string
type writer struct {
stream bool
id string
gin.ResponseWriter
}
func (w *BaseWriter) writeError(code int, data []byte) (int, error) {
func (w *writer) writeError(code int, data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
@@ -524,7 +256,7 @@ func (w *BaseWriter) writeError(code int, data []byte) (int, error) {
return len(data), nil
}
func (w *ChatWriter) writeResponse(data []byte) (int, error) {
func (w *writer) writeResponse(data []byte) (int, error) {
var chatResponse api.ChatResponse
err := json.Unmarshal(data, &chatResponse)
if err != nil {
@@ -564,7 +296,7 @@ func (w *ChatWriter) writeResponse(data []byte) (int, error) {
return len(data), nil
}
func (w *ChatWriter) Write(data []byte) (int, error) {
func (w *writer) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
@@ -573,244 +305,7 @@ func (w *ChatWriter) Write(data []byte) (int, error) {
return w.writeResponse(data)
}
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 (w *EmbedWriter) writeResponse(data []byte) (int, error) {
var embedResponse api.EmbedResponse
err := json.Unmarshal(data, &embedResponse)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toEmbeddingList(w.model, embedResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *EmbedWriter) 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 EmbeddingsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req EmbedRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if req.Input == "" {
req.Input = []string{""}
}
if req.Input == nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, "invalid input"))
return
}
if v, ok := req.Input.([]any); ok && len(v) == 0 {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, "invalid input"))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input}); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &EmbedWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
model: req.Model,
}
c.Writer = w
c.Next()
}
}
func ChatMiddleware() gin.HandlerFunc {
func Middleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req ChatCompletionRequest
err := c.ShouldBindJSON(&req)
@@ -825,23 +320,17 @@ func ChatMiddleware() gin.HandlerFunc {
}
var b bytes.Buffer
chatReq, err := fromChatRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
}
if err := json.NewEncoder(&b).Encode(chatReq); err != nil {
if err := json.NewEncoder(&b).Encode(fromRequest(req)); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &ChatWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
w := &writer{
ResponseWriter: c.Writer,
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
}
c.Writer = w
@@ -849,3 +338,69 @@ func ChatMiddleware() gin.HandlerFunc {
c.Next()
}
}
func (w *DeleteWriter) writeError(code int, data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(NewError(http.StatusInternalServerError, serr.Error()))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *DeleteWriter) writeResponse(data []byte) (int, error) {
// delete completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err := json.NewEncoder(w.ResponseWriter).Encode(toDeleteCompletion(w.model))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *DeleteWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func DeleteMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(api.DeleteRequest{Model: c.Param("model")}); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
// response writer
w := &DeleteWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
model: c.Param("model"),
}
c.Writer = w
c.Next()
// If the status code is OK, write the DeleteCompletion response
if c.Writer.Status() == http.StatusOK {
_, err := w.writeResponse(nil)
if err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
}
}
}
}

View File

@@ -1,392 +0,0 @@
package openai
import (
"bytes"
"encoding/base64"
"encoding/json"
"io"
"net/http"
"net/http/httptest"
"strings"
"testing"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/stretchr/testify/assert"
)
const prefix = `data:image/jpeg;base64,`
const image = `iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=`
const imageURL = prefix + image
func TestMiddlewareRequests(t *testing.T) {
type testCase struct {
Name string
Method string
Path string
Handler func() gin.HandlerFunc
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, req *http.Request)
}
var capturedRequest *http.Request
captureRequestMiddleware := func() gin.HandlerFunc {
return func(c *gin.Context) {
bodyBytes, _ := io.ReadAll(c.Request.Body)
c.Request.Body = io.NopCloser(bytes.NewReader(bodyBytes))
capturedRequest = c.Request
c.Next()
}
}
testCases := []testCase{
{
Name: "chat handler",
Method: http.MethodPost,
Path: "/api/chat",
Handler: ChatMiddleware,
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, req *http.Request) {
var chatReq api.ChatRequest
if err := json.NewDecoder(req.Body).Decode(&chatReq); err != nil {
t.Fatal(err)
}
if chatReq.Messages[0].Role != "user" {
t.Fatalf("expected 'user', got %s", chatReq.Messages[0].Role)
}
if chatReq.Messages[0].Content != "Hello" {
t.Fatalf("expected 'Hello', got %s", chatReq.Messages[0].Content)
}
},
},
{
Name: "completions handler",
Method: http.MethodPost,
Path: "/api/generate",
Handler: CompletionsMiddleware,
Setup: func(t *testing.T, req *http.Request) {
temp := float32(0.8)
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
Temperature: &temp,
Stop: []string{"\n", "stop"},
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, req *http.Request) {
var genReq api.GenerateRequest
if err := json.NewDecoder(req.Body).Decode(&genReq); err != nil {
t.Fatal(err)
}
if genReq.Prompt != "Hello" {
t.Fatalf("expected 'Hello', got %s", genReq.Prompt)
}
if genReq.Options["temperature"] != 1.6 {
t.Fatalf("expected 1.6, got %f", genReq.Options["temperature"])
}
stopTokens, ok := genReq.Options["stop"].([]any)
if !ok {
t.Fatalf("expected stop tokens to be a list")
}
if stopTokens[0] != "\n" || stopTokens[1] != "stop" {
t.Fatalf("expected ['\\n', 'stop'], got %v", stopTokens)
}
},
},
{
Name: "chat handler with image content",
Method: http.MethodPost,
Path: "/api/chat",
Handler: ChatMiddleware,
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{
{
Role: "user", Content: []map[string]any{
{"type": "text", "text": "Hello"},
{"type": "image_url", "image_url": map[string]string{"url": imageURL}},
},
},
},
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, req *http.Request) {
var chatReq api.ChatRequest
if err := json.NewDecoder(req.Body).Decode(&chatReq); err != nil {
t.Fatal(err)
}
if chatReq.Messages[0].Role != "user" {
t.Fatalf("expected 'user', got %s", chatReq.Messages[0].Role)
}
if chatReq.Messages[0].Content != "Hello" {
t.Fatalf("expected 'Hello', got %s", chatReq.Messages[0].Content)
}
img, _ := base64.StdEncoding.DecodeString(imageURL[len(prefix):])
if !bytes.Equal(chatReq.Messages[0].Images[0], img) {
t.Fatalf("expected image encoding, got %s", chatReq.Messages[0].Images[0])
}
},
},
{
Name: "embed handler single input",
Method: http.MethodPost,
Path: "/api/embed",
Handler: EmbeddingsMiddleware,
Setup: func(t *testing.T, req *http.Request) {
body := EmbedRequest{
Input: "Hello",
Model: "test-model",
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, req *http.Request) {
var embedReq api.EmbedRequest
if err := json.NewDecoder(req.Body).Decode(&embedReq); err != nil {
t.Fatal(err)
}
if embedReq.Input != "Hello" {
t.Fatalf("expected 'Hello', got %s", embedReq.Input)
}
if embedReq.Model != "test-model" {
t.Fatalf("expected 'test-model', got %s", embedReq.Model)
}
},
},
{
Name: "embed handler batch input",
Method: http.MethodPost,
Path: "/api/embed",
Handler: EmbeddingsMiddleware,
Setup: func(t *testing.T, req *http.Request) {
body := EmbedRequest{
Input: []string{"Hello", "World"},
Model: "test-model",
}
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
},
Expected: func(t *testing.T, req *http.Request) {
var embedReq api.EmbedRequest
if err := json.NewDecoder(req.Body).Decode(&embedReq); err != nil {
t.Fatal(err)
}
input, ok := embedReq.Input.([]any)
if !ok {
t.Fatalf("expected input to be a list")
}
if input[0].(string) != "Hello" {
t.Fatalf("expected 'Hello', got %s", input[0])
}
if input[1].(string) != "World" {
t.Fatalf("expected 'World', got %s", input[1])
}
if embedReq.Model != "test-model" {
t.Fatalf("expected 'test-model', got %s", embedReq.Model)
}
},
},
}
gin.SetMode(gin.TestMode)
router := gin.New()
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
router = gin.New()
router.Use(captureRequestMiddleware())
router.Use(tc.Handler())
router.Handle(tc.Method, tc.Path, endpoint)
req, _ := http.NewRequest(tc.Method, tc.Path, nil)
if tc.Setup != nil {
tc.Setup(t, req)
}
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
tc.Expected(t, capturedRequest)
})
}
}
func TestMiddlewareResponses(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: "completions handler error forwarding",
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(strings.TrimSpace(b.String()))
s, ok := unquote(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(strings.TrimSpace(b.String()))
s, ok := unquote(b.String())
if !ok {
return nil, io.ErrUnexpectedEOF
}

View File

@@ -22,13 +22,7 @@ ADAPTER adapter1
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|>"""
TEMPLATE template1
`
reader := strings.NewReader(input)
@@ -42,40 +36,7 @@ TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>
{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)
}
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|> "},
{Name: "template", Args: "template1"},
}
assert.Equal(t, expectedCommands, modelfile.Commands)
@@ -87,26 +48,6 @@ 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"}},
@@ -145,11 +86,6 @@ 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 {
@@ -463,7 +399,7 @@ 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

@@ -103,22 +103,19 @@ function buildApp() {
function gatherDependencies() {
write-host "Gathering runtime dependencies"
cd "${script:SRC_DIR}"
md "${script:DEPS_DIR}\ollama_runners" -ea 0 > $null
md "${script:DEPS_DIR}" -ea 0 > $null
# TODO - this varies based on host build system and MSVC version - drive from dumpbin output
# currently works for Win11 + MSVC 2019 + Cuda V11
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\msvcp140*.dll" "${script:DEPS_DIR}\ollama_runners\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140.dll" "${script:DEPS_DIR}\ollama_runners\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140_1.dll" "${script:DEPS_DIR}\ollama_runners\"
foreach ($part in $("runtime", "stdio", "filesystem", "math", "convert", "heap", "string", "time", "locale", "environment")) {
cp "$env:VCToolsRedistDir\..\..\..\Tools\Llvm\x64\bin\api-ms-win-crt-${part}*.dll" "${script:DEPS_DIR}\ollama_runners\"
}
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\msvcp140.dll" "${script:DEPS_DIR}\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140.dll" "${script:DEPS_DIR}\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140_1.dll" "${script:DEPS_DIR}\"
cp "${script:SRC_DIR}\app\ollama_welcome.ps1" "${script:SRC_DIR}\dist\"
if ("${env:KEY_CONTAINER}") {
write-host "about to sign"
foreach ($file in (get-childitem "${script:DEPS_DIR}\cuda\cu*.dll") + @("${script:SRC_DIR}\dist\ollama_welcome.ps1")){
foreach ($file in (get-childitem "${script:DEPS_DIR}/cu*.dll") + @("${script:SRC_DIR}\dist\ollama_welcome.ps1")){
write-host "signing $file"
& "${script:SignTool}" sign /v /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
/csp "Google Cloud KMS Provider" /kc ${env:KEY_CONTAINER} $file

View File

@@ -159,8 +159,8 @@ check_gpu() {
esac ;;
lshw)
case $2 in
nvidia) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[10DE\]' || return 1 ;;
amdgpu) available lshw && $SUDO lshw -c display -numeric -disable network | grep -q 'vendor: .* \[1002\]' || return 1 ;;
nvidia) available lshw && $SUDO lshw -c display -numeric | grep -q 'vendor: .* \[10DE\]' || return 1 ;;
amdgpu) available lshw && $SUDO lshw -c display -numeric | grep -q 'vendor: .* \[1002\]' || return 1 ;;
esac ;;
nvidia-smi) available nvidia-smi || return 1 ;;
esac
@@ -279,7 +279,7 @@ if ! check_gpu nvidia-smi || [ -z "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\
case $OS_NAME in
centos|rhel) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -d '.' -f 1) ;;
rocky) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -c1) ;;
fedora) [ $OS_VERSION -lt '39' ] && install_cuda_driver_yum $OS_NAME $OS_VERSION || install_cuda_driver_yum $OS_NAME '39';;
fedora) [ $OS_VERSION -lt '37' ] && install_cuda_driver_yum $OS_NAME $OS_VERSION || install_cuda_driver_yum $OS_NAME '37';;
amzn) install_cuda_driver_yum 'fedora' '37' ;;
debian) install_cuda_driver_apt $OS_NAME $OS_VERSION ;;
ubuntu) install_cuda_driver_apt $OS_NAME $(echo $OS_VERSION | sed 's/\.//') ;;

View File

@@ -6,21 +6,10 @@ 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

@@ -28,27 +28,11 @@ 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"
)
var (
errCapabilities = errors.New("does not support")
errCapabilityCompletion = errors.New("completion")
errCapabilityTools = errors.New("tools")
errCapabilityInsert = errors.New("insert")
)
type Capability string
const (
CapabilityCompletion = Capability("completion")
CapabilityTools = Capability("tools")
CapabilityInsert = Capability("insert")
)
type registryOptions struct {
Insecure bool
Username string
@@ -64,59 +48,16 @@ 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
}
// CheckCapabilities checks if the model has the specified capabilities returning an error describing
// any missing or unknown capabilities
func (m *Model) CheckCapabilities(caps ...Capability) error {
var errs []error
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 {
errs = append(errs, errCapabilityCompletion)
}
case CapabilityTools:
if !slices.Contains(m.Template.Vars(), "tools") {
errs = append(errs, errCapabilityTools)
}
case CapabilityInsert:
vars := m.Template.Vars()
if !slices.Contains(vars, "suffix") {
errs = append(errs, errCapabilityInsert)
}
default:
slog.Error("unknown capability", "capability", cap)
return fmt.Errorf("unknown capability: %s", cap)
}
}
if err := errors.Join(errs...); err != nil {
return fmt.Errorf("%w %w", errCapabilities, errors.Join(errs...))
}
return nil
func (m *Model) IsEmbedding() bool {
return slices.Contains(m.Config.ModelFamilies, "bert") || slices.Contains(m.Config.ModelFamilies, "nomic-bert")
}
func (m *Model) String() string {
@@ -141,10 +82,10 @@ func (m *Model) String() string {
})
}
if m.Template != nil {
if m.Template != "" {
modelfile.Commands = append(modelfile.Commands, parser.Command{
Name: "template",
Args: m.Template.String(),
Args: m.Template,
})
}
@@ -194,6 +135,13 @@ 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"`
@@ -212,7 +160,7 @@ type RootFS struct {
DiffIDs []string `json:"diff_ids"`
}
func GetManifest(mp ModelPath) (*Manifest, string, error) {
func GetManifest(mp ModelPath) (*ManifestV2, string, error) {
fp, err := mp.GetManifestPath()
if err != nil {
return nil, "", err
@@ -222,7 +170,7 @@ func GetManifest(mp ModelPath) (*Manifest, string, error) {
return nil, "", err
}
var manifest *Manifest
var manifest *ManifestV2
bts, err := os.ReadFile(fp)
if err != nil {
@@ -250,7 +198,8 @@ func GetModel(name string) (*Model, error) {
Name: mp.GetFullTagname(),
ShortName: mp.GetShortTagname(),
Digest: digest,
Template: template.DefaultTemplate,
Template: "{{ .Prompt }}",
License: []string{},
}
filename, err := GetBlobsPath(manifest.Config.Digest)
@@ -286,17 +235,13 @@ 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.prompt",
"application/vnd.ollama.image.template":
case "application/vnd.ollama.image.template":
bts, err := os.ReadFile(filename)
if err != nil {
return nil, err
}
model.Template, err = template.Parse(string(bts))
if err != nil {
return nil, err
}
model.Template = string(bts)
case "application/vnd.ollama.image.system":
bts, err := os.ReadFile(filename)
if err != nil {
@@ -304,6 +249,13 @@ 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 {
@@ -462,22 +414,17 @@ func CreateModel(ctx context.Context, name model.Name, modelFileDir, quantizatio
return err
}
layer, err := NewLayer(temp, baseLayer.MediaType)
layers, err := parseFromFile(ctx, temp, "", fn)
if err != nil {
return err
}
if _, err := temp.Seek(0, io.SeekStart); err != nil {
return err
if len(layers) != 1 {
return errors.New("quantization failed")
}
ggml, _, err := llm.DecodeGGML(temp, 0)
if err != nil {
return err
}
baseLayer.Layer = layer
baseLayer.GGML = ggml
baseLayer.Layer = layers[0].Layer
baseLayer.GGML = layers[0].GGML
}
}
@@ -870,7 +817,7 @@ 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 *Manifest
var manifest *ManifestV2
var err error
var noprune string
@@ -977,7 +924,7 @@ func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
return nil
}
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*Manifest, error) {
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*ManifestV2, error) {
requestURL := mp.BaseURL().JoinPath("v2", mp.GetNamespaceRepository(), "manifests", mp.Tag)
headers := make(http.Header)
@@ -988,7 +935,7 @@ func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptio
}
defer resp.Body.Close()
var m *Manifest
var m *ManifestV2
if err := json.NewDecoder(resp.Body).Decode(&m); err != nil {
return nil, err
}

View File

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

View File

@@ -4,7 +4,6 @@ import (
"archive/zip"
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
@@ -12,14 +11,11 @@ import (
"net/http"
"os"
"path/filepath"
"slices"
"strings"
"text/template/parse"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/convert"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/templates"
"github.com/ollama/ollama/types/model"
)
@@ -67,7 +63,7 @@ func parseFromModel(ctx context.Context, name model.Name, fn func(api.ProgressRe
}
defer blob.Close()
ggml, _, err := llm.DecodeGGML(blob, 0)
ggml, _, err := llm.DecodeGGML(blob)
if err != nil {
return nil, err
}
@@ -81,79 +77,62 @@ func parseFromModel(ctx context.Context, name model.Name, fn func(api.ProgressRe
return layers, nil
}
func extractFromZipFile(p string, file *os.File, fn func(api.ProgressResponse)) error {
func parseFromZipFile(_ context.Context, file *os.File, digest string, fn func(api.ProgressResponse)) (layers []*layerGGML, err error) {
stat, err := file.Stat()
if err != nil {
return err
return nil, err
}
r, err := zip.NewReader(file, stat.Size())
if err != nil {
return err
return nil, err
}
tempdir, err := os.MkdirTemp(filepath.Dir(file.Name()), "")
if err != nil {
return nil, err
}
defer os.RemoveAll(tempdir)
fn(api.ProgressResponse{Status: "unpacking model metadata"})
for _, f := range r.File {
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
}
// TODO(mxyng): this should not write out all files to disk
outfile, err := os.Create(n)
outfile, err := os.Create(filepath.Join(tempdir, f.Name))
if err != nil {
return err
return nil, err
}
defer outfile.Close()
infile, err := f.Open()
if err != nil {
return err
return nil, err
}
defer infile.Close()
if _, err = io.Copy(outfile, infile); err != nil {
return err
return nil, err
}
if err := outfile.Close(); err != nil {
return err
return nil, err
}
if err := infile.Close(); err != nil {
return err
return nil, err
}
}
return nil
}
func parseFromZipFile(_ context.Context, file *os.File, digest string, fn func(api.ProgressResponse)) (layers []*layerGGML, err error) {
tempDir, err := os.MkdirTemp(filepath.Dir(file.Name()), "")
if err != nil {
return nil, err
}
defer os.RemoveAll(tempDir)
if err := extractFromZipFile(tempDir, file, fn); err != nil {
return nil, err
}
mf, err := convert.GetModelFormat(tempDir)
mf, err := convert.GetModelFormat(tempdir)
if err != nil {
return nil, err
}
params, err := mf.GetParams(tempDir)
params, err := mf.GetParams(tempdir)
if err != nil {
return nil, err
}
mArch, err := mf.GetModelArch("", tempDir, params)
mArch, err := mf.GetModelArch("", tempdir, params)
if err != nil {
return nil, err
}
@@ -171,7 +150,7 @@ func parseFromZipFile(_ context.Context, file *os.File, digest string, fn func(a
// TODO(mxyng): this should write directly into a layer
// e.g. NewLayer(arch.Reader(), "application/vnd.ollama.image.model")
temp, err := os.CreateTemp(tempDir, "fp16")
temp, err := os.CreateTemp(tempdir, "fp16")
if err != nil {
return nil, err
}
@@ -197,7 +176,7 @@ func parseFromZipFile(_ context.Context, file *os.File, digest string, fn func(a
}
defer bin.Close()
ggml, _, err := llm.DecodeGGML(bin, 0)
ggml, _, err := llm.DecodeGGML(bin)
if err != nil {
return nil, err
}
@@ -231,7 +210,7 @@ func parseFromFile(ctx context.Context, file *os.File, digest string, fn func(ap
var offset int64
for offset < stat.Size() {
ggml, n, err := llm.DecodeGGML(file, 0)
ggml, n, err := llm.DecodeGGML(file)
if errors.Is(err, io.EOF) {
break
} else if err != nil {
@@ -260,7 +239,7 @@ 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 := template.Named(s); err != nil {
if t, err := templates.NamedTemplate(s); err != nil {
slog.Debug("template detection", "error", err)
} else {
tmpl, err := NewLayer(t.Reader(), "application/vnd.ollama.image.template")
@@ -293,87 +272,3 @@ func detectContentType(r io.Reader) (string, error) {
return "unknown", nil
}
// parseToolCalls attempts to parse a JSON string into a slice of ToolCalls.
// mxyng: this only really works if the input contains tool calls in some JSON format
func (m *Model) parseToolCalls(s string) ([]api.ToolCall, bool) {
// create a subtree from the node that ranges over .ToolCalls
tmpl := m.Template.Subtree(func(n parse.Node) bool {
if t, ok := n.(*parse.RangeNode); ok {
return slices.Contains(template.Identifiers(t.Pipe), "ToolCalls")
}
return false
})
if tmpl == nil {
return nil, false
}
var b bytes.Buffer
if err := tmpl.Execute(&b, map[string][]map[string]any{
"ToolCalls": {
{
"Function": map[string]any{
"Name": "@@name@@",
"Arguments": "@@arguments@@",
},
},
},
}); err != nil {
return nil, false
}
var kv map[string]string
// execute the subtree with placeholders to identify the keys
// trim any commands that might exist in the template
if err := json.Unmarshal(bytes.TrimSuffix(b.Bytes(), []byte(",")), &kv); err != nil {
return nil, false
}
// find the keys that correspond to the name and arguments fields
var name, arguments string
for k, v := range kv {
switch v {
case "@@name@@":
name = k
case "@@arguments@@":
arguments = k
}
}
var objs []map[string]any
for offset := 0; offset < len(s); {
if err := json.NewDecoder(strings.NewReader(s[offset:])).Decode(&objs); errors.Is(err, io.EOF) {
break
} else if syntax := &(json.SyntaxError{}); errors.As(err, &syntax) {
// skip over any syntax errors
offset += int(syntax.Offset)
} else if unmarshalType := &(json.UnmarshalTypeError{}); errors.As(err, &unmarshalType) {
// skip over any unmarshalable types
offset += int(unmarshalType.Offset)
} else if err != nil {
return nil, false
} else {
// break when an object is decoded
break
}
}
var toolCalls []api.ToolCall
for _, kv := range objs {
var call api.ToolCall
for k, v := range kv {
switch k {
case name:
call.Function.Name = v.(string)
case arguments:
call.Function.Arguments = v.(map[string]any)
}
}
toolCalls = append(toolCalls, call)
}
return toolCalls, len(toolCalls) > 0
}

View File

@@ -1,236 +0,0 @@
package server
import (
"archive/zip"
"bytes"
"encoding/json"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"slices"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
func createZipFile(t *testing.T, name string) *os.File {
t.Helper()
f, err := os.CreateTemp(t.TempDir(), "")
if err != nil {
t.Fatal(err)
}
zf := zip.NewWriter(f)
defer zf.Close()
zh, err := zf.CreateHeader(&zip.FileHeader{Name: name})
if err != nil {
t.Fatal(err)
}
if _, err := io.Copy(zh, bytes.NewReader([]byte(""))); err != nil {
t.Fatal(err)
}
return f
}
func TestExtractFromZipFile(t *testing.T) {
cases := []struct {
name string
expect []string
err error
}{
{
name: "good",
expect: []string{"good"},
},
{
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,
},
}
for _, tt := range cases {
t.Run(tt.name, func(t *testing.T) {
f := createZipFile(t, tt.name)
defer f.Close()
tempDir := t.TempDir()
if err := extractFromZipFile(tempDir, f, func(api.ProgressResponse) {}); !errors.Is(err, tt.err) {
t.Fatal(err)
}
var matches []string
if err := filepath.Walk(tempDir, func(p string, fi os.FileInfo, err error) error {
if err != nil {
return err
}
if !fi.IsDir() {
matches = append(matches, p)
}
return nil
}); err != nil {
t.Fatal(err)
}
var actual []string
for _, match := range matches {
rel, err := filepath.Rel(tempDir, match)
if err != nil {
t.Error(err)
}
actual = append(actual, rel)
}
if !slices.Equal(actual, tt.expect) {
t.Fatalf("expected %d files, got %d", len(tt.expect), len(matches))
}
})
}
}
type function struct {
Name string `json:"name"`
Arguments map[string]any `json:"arguments"`
}
func readFile(t *testing.T, base, name string) *bytes.Buffer {
t.Helper()
bts, err := os.ReadFile(filepath.Join(base, name))
if err != nil {
t.Fatal(err)
}
return bytes.NewBuffer(bts)
}
func TestExecuteWithTools(t *testing.T) {
p := filepath.Join("testdata", "tools")
cases := []struct {
model string
output string
ok bool
}{
{"mistral", `[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"mistral", `[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]
The temperature in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.`, true},
{"mistral", `I'm not aware of that information. However, I can suggest searching for the weather using the "get_current_weather" function:
[{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"mistral", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
{"command-r-plus", "Action: ```json" + `
[
{
"tool_name": "get_current_weather",
"parameters": {
"format": "fahrenheit",
"location": "San Francisco, CA"
}
},
{
"tool_name": "get_current_weather",
"parameters": {
"format": "celsius",
"location": "Toronto, Canada"
}
}
]
` + "```", true},
{"command-r-plus", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
{"firefunction", ` functools[{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"firefunction", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
}
var tools []api.Tool
if err := json.Unmarshal(readFile(t, p, "tools.json").Bytes(), &tools); err != nil {
t.Fatal(err)
}
var messages []api.Message
if err := json.Unmarshal(readFile(t, p, "messages.json").Bytes(), &messages); err != nil {
t.Fatal(err)
}
calls := []api.ToolCall{
{
Function: function{
Name: "get_current_weather",
Arguments: map[string]any{
"format": "fahrenheit",
"location": "San Francisco, CA",
},
},
},
{
Function: function{
Name: "get_current_weather",
Arguments: map[string]any{
"format": "celsius",
"location": "Toronto, Canada",
},
},
},
}
for _, tt := range cases {
t.Run(tt.model, func(t *testing.T) {
tmpl, err := template.Parse(readFile(t, p, fmt.Sprintf("%s.gotmpl", tt.model)).String())
if err != nil {
t.Fatal(err)
}
t.Run("template", func(t *testing.T) {
var actual bytes.Buffer
if err := tmpl.Execute(&actual, template.Values{Tools: tools, Messages: messages}); err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(actual.String(), readFile(t, p, fmt.Sprintf("%s.out", tt.model)).String()); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("parse", func(t *testing.T) {
m := &Model{Template: tmpl}
actual, ok := m.parseToolCalls(tt.output)
if ok != tt.ok {
t.Fatalf("expected %t, got %t", tt.ok, ok)
}
if tt.ok {
if diff := cmp.Diff(actual, calls); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
}
})
})
}
}

View File

@@ -103,9 +103,18 @@ 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 := envconfig.ModelsDir
dir, err := modelsDir()
if err != nil {
return "", err
}
return filepath.Join(dir, "manifests", mp.Registry, mp.Namespace, mp.Repository, mp.Tag), nil
}
@@ -118,7 +127,10 @@ func (mp ModelPath) BaseURL() *url.URL {
}
func GetManifestPath() (string, error) {
dir := envconfig.ModelsDir
dir, err := modelsDir()
if err != nil {
return "", err
}
path := filepath.Join(dir, "manifests")
if err := os.MkdirAll(path, 0o755); err != nil {
@@ -129,7 +141,10 @@ func GetManifestPath() (string, error) {
}
func GetBlobsPath(digest string) (string, error) {
dir := envconfig.ModelsDir
dir, err := modelsDir()
if err != nil {
return "", err
}
// only accept actual sha256 digests
pattern := "^sha256[:-][0-9a-fA-F]{64}$"

View File

@@ -1,74 +1,221 @@
package server
import (
"bytes"
"context"
"fmt"
"log/slog"
"strings"
"text/template"
"text/template/parse"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/template"
)
type tokenizeFunc func(context.Context, string) ([]int, error)
// chatPrompt accepts a list of messages and returns the prompt and images that should be used for the next chat turn.
// chatPrompt truncates any messages that exceed the context window of the model, making sure to always include 1) the
// latest message and 2) system messages
func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.Options, msgs []api.Message, tools []api.Tool) (prompt string, images []llm.ImageData, _ error) {
var system []api.Message
// always include the last message
n := len(msgs) - 1
// in reverse, find all messages that fit into context window
for i := n - 1; i >= 0; i-- {
system = make([]api.Message, 0)
for j := range i {
if msgs[j].Role == "system" {
system = append(system, msgs[j])
// isResponseNode checks if the node contains .Response
func isResponseNode(node *parse.ActionNode) bool {
for _, cmd := range node.Pipe.Cmds {
for _, arg := range cmd.Args {
if fieldNode, ok := arg.(*parse.FieldNode); ok && len(fieldNode.Ident) > 0 {
if fieldNode.Ident[0] == "Response" {
return true
}
}
}
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools}); err != nil {
return "", nil, err
}
s, err := tokenize(ctx, b.String())
if err != nil {
return "", nil, err
}
c := len(s)
if m.ProjectorPaths != nil {
for _, m := range msgs[i:] {
// images are represented as 768 sized embeddings
// TODO: get embedding length from project metadata
c += 768 * len(m.Images)
}
}
if c > opts.NumCtx {
slog.Debug("truncating input messages which exceed context length", "truncated", len(msgs[i:]))
break
} else {
n = i
}
}
// truncate any messages that do not fit into the context window
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[n:]...), Tools: tools}); err != nil {
return "", nil, err
}
for _, m := range msgs[n:] {
for _, i := range m.Images {
images = append(images, llm.ImageData{
ID: len(images),
Data: i,
})
}
}
return b.String(), images, nil
return false
}
// formatTemplateForResponse formats the template AST to:
// 1. remove all nodes after the first .Response (if generate=true)
// 2. add a .Response node to the end if it doesn't exist
// TODO(jmorganca): this should recursively cut the template before the first .Response
func formatTemplateForResponse(tmpl *template.Template, generate bool) {
var found bool
for i, node := range tmpl.Tree.Root.Nodes {
if actionNode, ok := node.(*parse.ActionNode); ok {
if isResponseNode(actionNode) {
found = true
if generate {
tmpl.Tree.Root.Nodes = tmpl.Tree.Root.Nodes[:i+1]
break
}
}
}
}
if !found {
// add the response node if it doesn't exist
responseFieldNode := &parse.FieldNode{NodeType: parse.NodeField, Ident: []string{"Response"}}
responsePipeNode := &parse.PipeNode{NodeType: parse.NodePipe, Cmds: []*parse.CommandNode{{NodeType: parse.NodeCommand, Args: []parse.Node{responseFieldNode}}}}
responseActionNode := &parse.ActionNode{NodeType: parse.NodeAction, Pipe: responsePipeNode}
tmpl.Tree.Root.Nodes = append(tmpl.Tree.Root.Nodes, responseActionNode)
}
}
// 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)
vars := map[string]any{
"System": system,
"Prompt": prompt,
"Response": response,
}
var sb strings.Builder
if err := parsed.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) {
rendered, err := Prompt(tmpl, system, prompt, response, false)
if err != nil {
return 0, err
}
tokens, err := encode(rendered)
if err != nil {
slog.Error("failed to encode prompt", "err", err)
return 0, err
}
return len(tokens), err
}
// 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) {
type prompt struct {
System string
Prompt string
Response string
images []int
tokens int
}
var p prompt
// iterate through messages to build up {system,user,response} prompts
var imgId int
var prompts []prompt
for _, msg := range messages {
switch strings.ToLower(msg.Role) {
case "system":
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.System = msg.Content
case "user":
if p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
var sb strings.Builder
for range msg.Images {
fmt.Fprintf(&sb, "[img-%d] ", imgId)
p.images = append(p.images, imgId)
imgId += 1
}
sb.WriteString(msg.Content)
p.Prompt = sb.String()
case "assistant":
if p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.Response = msg.Content
default:
return "", fmt.Errorf("invalid role: %s, role must be one of [system, user, assistant]", msg.Role)
}
}
// add final prompt
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
}
// calculate token lengths for each prompt, estimating 768 tokens per images
for i, p := range prompts {
tokens, err := countTokens(tmpl, p.System, p.Prompt, p.Response, encode)
if err != nil {
return "", err
}
prompts[i].tokens = tokens + len(prompts[i].images)*768
}
// truncate images and prompts starting from the beginning of the list
// until either one prompt remains or the total tokens fits the context window
// TODO (jmorganca): this doesn't account for the context window room required for the response
for {
var required int
for _, p := range prompts {
required += p.tokens
}
required += 1 // for bos token
if required <= window {
slog.Debug("prompt now fits in context window", "required", required, "window", window)
break
}
prompt := &prompts[0]
if len(prompt.images) > 1 {
img := prompt.images[0]
slog.Debug("prompt longer than context window, removing image", "id", img, "required", required, "window", window)
prompt.images = prompt.images[1:]
prompt.Prompt = strings.Replace(prompt.Prompt, fmt.Sprintf(" [img-%d]", img), "", 1)
prompt.tokens -= 768
continue
}
if len(prompts) > 1 {
slog.Debug("required tokens longer than context window, removing first prompt", "prompt", prompts[0].tokens, "required", required, "window", window)
system := prompt.System
prompts = prompts[1:]
if system != "" && prompts[0].System == "" {
prompts[0].System = system
tokens, err := countTokens(tmpl, prompts[0].System, prompts[0].Prompt, prompts[0].Response, encode)
if err != nil {
return "", err
}
prompts[0].tokens = tokens + len(prompts[0].images)*768
}
continue
}
// stop truncating if there's only one prompt left
break
}
var sb strings.Builder
for i, p := range prompts {
// last prompt should leave the response unrendered (for completion)
rendered, err := Prompt(tmpl, p.System, p.Prompt, p.Response, i == len(prompts)-1)
if err != nil {
return "", err
}
sb.WriteString(rendered)
}
return sb.String(), nil
}

View File

@@ -1,209 +1,204 @@
package server
import (
"bytes"
"context"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
func TestChatPrompt(t *testing.T) {
type expect struct {
prompt string
images [][]byte
}
cases := []struct {
name string
limit int
msgs []api.Message
expect
func TestPrompt(t *testing.T) {
tests := []struct {
name string
template string
system string
prompt string
response string
generate bool
want string
}{
{
name: "messages",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry! I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
},
name: "simple prompt",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "truncate messages",
limit: 1,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "A test. And a thumping good one at that, I'd wager. ",
},
name: "implicit response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]I don't know.",
},
{
name: "truncate messages with image",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("something")}},
},
expect: expect{
prompt: "[img-0] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
},
},
name: "response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST] I don't know.",
},
{
name: "truncate messages with images",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "[img-0] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("somethingelse"),
},
},
name: "cut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
generate: true,
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.",
},
{
name: "messages with images",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "[img-0] You're a test, Harry! I-I'm a what? [img-1] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
},
{
name: "message with image tag",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry! [img]", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "You're a test, Harry! [img-0] I-I'm a what? [img-1] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
},
{
name: "messages with interleaved images",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "user", Images: []api.ImageData{[]byte("something")}},
{Role: "user", Images: []api.ImageData{[]byte("somethingelse")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry!\n\n[img-0]\n\n[img-1] I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
},
{
name: "truncate message with interleaved images",
limit: 1024,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "user", Images: []api.ImageData{[]byte("something")}},
{Role: "user", Images: []api.ImageData{[]byte("somethingelse")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "[img-0] I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("somethingelse"),
},
},
},
{
name: "message with system prompt",
limit: 2048,
msgs: []api.Message{
{Role: "system", Content: "You are the Test Who Lived."},
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You are the Test Who Lived. You're a test, Harry! I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
},
},
{
name: "out of order system",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "system", Content: "You are the Test Who Lived."},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry! I-I'm a what? You are the Test Who Lived. A test. And a thumping good one at that, I'd wager. ",
},
name: "nocut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.</assistant>",
},
}
tmpl, err := template.Parse(`
{{- if .System }}{{ .System }} {{ end }}
{{- if .Prompt }}{{ .Prompt }} {{ end }}
{{- if .Response }}{{ .Response }} {{ end }}`)
if err != nil {
t.Fatal(err)
}
for _, tt := range cases {
t.Run(tt.name, func(t *testing.T) {
model := Model{Template: tmpl, ProjectorPaths: []string{"vision"}}
opts := api.Options{Runner: api.Runner{NumCtx: tt.limit}}
prompt, images, err := chatPrompt(context.TODO(), &model, mockRunner{}.Tokenize, &opts, tt.msgs, nil)
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)
if err != nil {
t.Fatal(err)
t.Errorf("error = %v", err)
}
if diff := cmp.Diff(prompt, tt.prompt); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
if len(images) != len(tt.images) {
t.Fatalf("expected %d images, got %d", len(tt.images), len(images))
}
for i := range images {
if images[i].ID != i {
t.Errorf("expected ID %d, got %d", i, images[i].ID)
}
if !bytes.Equal(images[i].Data, tt.images[i]) {
t.Errorf("expected %q, got %q", tt.images[i], images[i])
}
if got != tc.want {
t.Errorf("got = %v, want %v", got, tc.want)
}
})
}
}
func TestChatPrompt(t *testing.T) {
tests := []struct {
name string
template string
messages []api.Message
window int
want string
}{
{
name: "simple prompt",
template: "[INST] {{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "user", Content: "Hello"},
},
window: 1024,
want: "[INST] Hello [/INST]",
},
{
name: "with system message",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]",
},
{
name: "with response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST] I am?",
},
{
name: "with implicit response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]I am?",
},
{
name: "with conversation",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "What are the potion ingredients?"},
{Role: "assistant", Content: "sugar"},
{Role: "user", Content: "Anything else?"},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> What are the potion ingredients? [/INST] sugar [INST] Anything else? [/INST] ",
},
{
name: "with truncation",
template: "{{ .System }} {{ .Prompt }} {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
{Role: "user", Content: "Why is the sky blue?"},
{Role: "assistant", Content: "The sky is blue from rayleigh scattering"},
},
window: 10,
want: "You are a Wizard. Why is the sky blue? The sky is blue from rayleigh scattering",
},
{
name: "images",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("base64")}},
},
window: 1024,
want: "You are a Wizard. [img-0] Hello",
},
{
name: "images truncated",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("img1"), []byte("img2")}},
},
window: 1024,
want: "You are a Wizard. [img-0] [img-1] Hello",
},
{
name: "empty list",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{},
window: 1024,
want: "",
},
{
name: "empty prompt",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "user", Content: ""},
},
window: 1024,
want: "",
},
}
encode := func(s string) ([]int, error) {
words := strings.Fields(s)
return make([]int, len(words)), nil
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := ChatPrompt(tc.template, tc.messages, tc.window, encode)
if err != nil {
t.Errorf("error = %v", err)
}
if got != tc.want {
t.Errorf("got: %q, want: %q", got, tc.want)
}
})
}

File diff suppressed because it is too large Load Diff

View File

@@ -85,8 +85,6 @@ func checkFileExists(t *testing.T, p string, expect []string) {
}
func TestCreateFromBin(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -113,8 +111,6 @@ func TestCreateFromBin(t *testing.T) {
}
func TestCreateFromModel(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -156,8 +152,6 @@ func TestCreateFromModel(t *testing.T) {
}
func TestCreateRemovesLayers(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -205,8 +199,6 @@ func TestCreateRemovesLayers(t *testing.T) {
}
func TestCreateUnsetsSystem(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -263,8 +255,6 @@ func TestCreateUnsetsSystem(t *testing.T) {
}
func TestCreateMergeParameters(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -368,8 +358,6 @@ func TestCreateMergeParameters(t *testing.T) {
}
func TestCreateReplacesMessages(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -446,8 +434,6 @@ func TestCreateReplacesMessages(t *testing.T) {
}
func TestCreateTemplateSystem(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -494,8 +480,6 @@ func TestCreateTemplateSystem(t *testing.T) {
}
func TestCreateLicenses(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -542,8 +526,6 @@ func TestCreateLicenses(t *testing.T) {
}
func TestCreateDetectTemplate(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -563,9 +545,9 @@ func TestCreateDetectTemplate(t *testing.T) {
}
checkFileExists(t, filepath.Join(p, "blobs", "*"), []string{
filepath.Join(p, "blobs", "sha256-2f8e594e6f34b1b4d36a246628eeb3365ce442303d656f1fcc69e821722acea0"),
filepath.Join(p, "blobs", "sha256-542b217f179c7825eeb5bca3c77d2b75ed05bafbd3451d9188891a60a85337c6"),
filepath.Join(p, "blobs", "sha256-553c4a3f747b3d22a4946875f1cc8ed011c2930d83f864a0c7265f9ec0a20413"),
filepath.Join(p, "blobs", "sha256-c608dc615584cd20d9d830363dabf8a4783ae5d34245c3d8c115edb3bc7b28e4"),
filepath.Join(p, "blobs", "sha256-f836ee110db21567f826332e4cedd746c06d10664fd5a9ea3659e3683a944510"),
})
})

View File

@@ -8,15 +8,12 @@ import (
"path/filepath"
"testing"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/types/model"
)
func TestDelete(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -80,8 +77,6 @@ func TestDelete(t *testing.T) {
}
func TestDeleteDuplicateLayers(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
var s Server

View File

@@ -1,712 +0,0 @@
package server
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"testing"
"time"
"github.com/gin-gonic/gin"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/gpu"
"github.com/ollama/ollama/llm"
)
type mockRunner struct {
llm.LlamaServer
// CompletionRequest is only valid until the next call to Completion
llm.CompletionRequest
llm.CompletionResponse
}
func (m *mockRunner) Completion(_ context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
m.CompletionRequest = r
fn(m.CompletionResponse)
return nil
}
func (mockRunner) Tokenize(_ context.Context, s string) (tokens []int, err error) {
for range strings.Fields(s) {
tokens = append(tokens, len(tokens))
}
return
}
func newMockServer(mock *mockRunner) func(gpu.GpuInfoList, string, *llm.GGML, []string, []string, api.Options, int) (llm.LlamaServer, error) {
return func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, projectors, system []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
return mock, nil
}
}
func TestGenerateChat(t *testing.T) {
gin.SetMode(gin.TestMode)
mock := mockRunner{
CompletionResponse: llm.CompletionResponse{
Done: true,
DoneReason: "stop",
PromptEvalCount: 1,
PromptEvalDuration: 1,
EvalCount: 1,
EvalDuration: 1,
},
}
s := Server{
sched: &Scheduler{
pendingReqCh: make(chan *LlmRequest, 1),
finishedReqCh: make(chan *LlmRequest, 1),
expiredCh: make(chan *runnerRef, 1),
unloadedCh: make(chan any, 1),
loaded: make(map[string]*runnerRef),
newServerFn: newMockServer(&mock),
getGpuFn: gpu.GetGPUInfo,
getCpuFn: gpu.GetCPUInfo,
reschedDelay: 250 * time.Millisecond,
loadFn: func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
// add 10ms delay to simulate loading
time.Sleep(10 * time.Millisecond)
req.successCh <- &runnerRef{
llama: &mock,
}
},
},
}
go s.sched.Run(context.TODO())
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test",
Modelfile: fmt.Sprintf(`FROM %s
TEMPLATE """
{{- if .System }}System: {{ .System }} {{ end }}
{{- if .Prompt }}User: {{ .Prompt }} {{ end }}
{{- if .Response }}Assistant: {{ .Response }} {{ end }}"""
`, createBinFile(t, llm.KV{
"general.architecture": "llama",
"llama.block_count": uint32(1),
"llama.context_length": uint32(8192),
"llama.embedding_length": uint32(4096),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(8),
"tokenizer.ggml.tokens": []string{""},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []llm.Tensor{
{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("missing body", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, nil)
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing model", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities chat", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "bert",
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, llm.KV{
"general.architecture": "bert",
"bert.pooling_type": uint32(0),
}, []llm.Tensor{})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "bert",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"\"bert\" does not support chat"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("load model", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
var actual api.ChatResponse
if err := json.NewDecoder(w.Body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != "test" {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done true, got false")
}
if actual.DoneReason != "load" {
t.Errorf("expected done reason load, got %s", actual.DoneReason)
}
})
checkChatResponse := func(t *testing.T, body io.Reader, model, content string) {
t.Helper()
var actual api.ChatResponse
if err := json.NewDecoder(body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != model {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done false, got true")
}
if actual.DoneReason != "stop" {
t.Errorf("expected done reason stop, got %s", actual.DoneReason)
}
if diff := cmp.Diff(actual.Message, api.Message{
Role: "assistant",
Content: content,
}); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
if actual.PromptEvalCount == 0 {
t.Errorf("expected prompt eval count > 0, got 0")
}
if actual.PromptEvalDuration == 0 {
t.Errorf("expected prompt eval duration > 0, got 0")
}
if actual.EvalCount == 0 {
t.Errorf("expected eval count > 0, got 0")
}
if actual.EvalDuration == 0 {
t.Errorf("expected eval duration > 0, got 0")
}
if actual.LoadDuration == 0 {
t.Errorf("expected load duration > 0, got 0")
}
if actual.TotalDuration == 0 {
t.Errorf("expected total duration > 0, got 0")
}
}
mock.CompletionResponse.Content = "Hi!"
t.Run("messages", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test", "Hi!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-system",
Modelfile: "FROM test\nSYSTEM You are a helpful assistant.",
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("messages with model system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Hi!")
})
mock.CompletionResponse.Content = "Abra kadabra!"
t.Run("messages with system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "system", Content: "You can perform magic tricks."},
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You can perform magic tricks. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Abra kadabra!")
})
t.Run("messages with interleaved system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
{Role: "assistant", Content: "I can help you with that."},
{Role: "system", Content: "You can perform magic tricks."},
{Role: "user", Content: "Help me write tests."},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! Assistant: I can help you with that. System: You can perform magic tricks. User: Help me write tests. "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Abra kadabra!")
})
}
func TestGenerate(t *testing.T) {
gin.SetMode(gin.TestMode)
mock := mockRunner{
CompletionResponse: llm.CompletionResponse{
Done: true,
DoneReason: "stop",
PromptEvalCount: 1,
PromptEvalDuration: 1,
EvalCount: 1,
EvalDuration: 1,
},
}
s := Server{
sched: &Scheduler{
pendingReqCh: make(chan *LlmRequest, 1),
finishedReqCh: make(chan *LlmRequest, 1),
expiredCh: make(chan *runnerRef, 1),
unloadedCh: make(chan any, 1),
loaded: make(map[string]*runnerRef),
newServerFn: newMockServer(&mock),
getGpuFn: gpu.GetGPUInfo,
getCpuFn: gpu.GetCPUInfo,
reschedDelay: 250 * time.Millisecond,
loadFn: func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
req.successCh <- &runnerRef{
llama: &mock,
}
},
},
}
go s.sched.Run(context.TODO())
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test",
Modelfile: fmt.Sprintf(`FROM %s
TEMPLATE """
{{- if .System }}System: {{ .System }} {{ end }}
{{- if .Prompt }}User: {{ .Prompt }} {{ end }}
{{- if .Response }}Assistant: {{ .Response }} {{ end }}"""
`, createBinFile(t, llm.KV{
"general.architecture": "llama",
"llama.block_count": uint32(1),
"llama.context_length": uint32(8192),
"llama.embedding_length": uint32(4096),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(8),
"tokenizer.ggml.tokens": []string{""},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []llm.Tensor{
{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("missing body", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, nil)
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing model", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities generate", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "bert",
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, llm.KV{
"general.architecture": "bert",
"bert.pooling_type": uint32(0),
}, []llm.Tensor{})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "bert",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"\"bert\" does not support generate"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
Prompt: "def add(",
Suffix: " return c",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"test does not support insert"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("load model", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
var actual api.GenerateResponse
if err := json.NewDecoder(w.Body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != "test" {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done true, got false")
}
if actual.DoneReason != "load" {
t.Errorf("expected done reason load, got %s", actual.DoneReason)
}
})
checkGenerateResponse := func(t *testing.T, body io.Reader, model, content string) {
t.Helper()
var actual api.GenerateResponse
if err := json.NewDecoder(body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != model {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done false, got true")
}
if actual.DoneReason != "stop" {
t.Errorf("expected done reason stop, got %s", actual.DoneReason)
}
if actual.Response != content {
t.Errorf("expected response %s, got %s", content, actual.Response)
}
if actual.Context == nil {
t.Errorf("expected context not nil")
}
if actual.PromptEvalCount == 0 {
t.Errorf("expected prompt eval count > 0, got 0")
}
if actual.PromptEvalDuration == 0 {
t.Errorf("expected prompt eval duration > 0, got 0")
}
if actual.EvalCount == 0 {
t.Errorf("expected eval count > 0, got 0")
}
if actual.EvalDuration == 0 {
t.Errorf("expected eval duration > 0, got 0")
}
if actual.LoadDuration == 0 {
t.Errorf("expected load duration > 0, got 0")
}
if actual.TotalDuration == 0 {
t.Errorf("expected total duration > 0, got 0")
}
}
mock.CompletionResponse.Content = "Hi!"
t.Run("prompt", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
Prompt: "Hello!",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test", "Hi!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-system",
Modelfile: "FROM test\nSYSTEM You are a helpful assistant.",
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("prompt with model system", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Hello!",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Hi!")
})
mock.CompletionResponse.Content = "Abra kadabra!"
t.Run("prompt with system", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Hello!",
System: "You can perform magic tricks.",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You can perform magic tricks. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Abra kadabra!")
})
t.Run("prompt with template", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Help me write tests.",
System: "You can perform magic tricks.",
Template: `{{- if .System }}{{ .System }} {{ end }}
{{- if .Prompt }}### USER {{ .Prompt }} {{ end }}
{{- if .Response }}### ASSISTANT {{ .Response }} {{ end }}`,
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "You can perform magic tricks. ### USER Help me write tests. "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Abra kadabra!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-suffix",
Modelfile: `FROM test
TEMPLATE """{{- if .Suffix }}<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
{{- else }}{{ .Prompt }}
{{- end }}"""`,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("prompt with suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-suffix",
Prompt: "def add(",
Suffix: " return c",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "<PRE> def add( <SUF> return c <MID>"); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("prompt without suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-suffix",
Prompt: "def add(",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "def add("); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("raw", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Help me write tests.",
Raw: true,
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "Help me write tests."); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
}

View File

@@ -7,14 +7,11 @@ import (
"slices"
"testing"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
)
func TestList(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("OLLAMA_MODELS", t.TempDir())
envconfig.LoadConfig()

View File

@@ -7,7 +7,6 @@ import (
"encoding/json"
"fmt"
"io"
"math"
"net/http"
"net/http/httptest"
"os"
@@ -20,8 +19,6 @@ 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"
@@ -107,24 +104,6 @@ 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,
@@ -148,25 +127,6 @@ 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,
@@ -252,96 +212,6 @@ func Test_Routes(t *testing.T) {
"top_p 0.9",
}
assert.Equal(t, expectedParams, params)
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)
},
},
{
Name: "Embed Handler Empty Input",
Method: http.MethodPost,
Path: "/api/embed",
Setup: func(t *testing.T, req *http.Request) {
embedReq := api.EmbedRequest{
Model: "t-bone",
Input: "",
}
jsonData, err := json.Marshal(embedReq)
require.NoError(t, err)
req.Body = io.NopCloser(bytes.NewReader(jsonData))
},
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
if contentType != "application/json; charset=utf-8" {
t.Fatalf("expected content type application/json; charset=utf-8, got %s", contentType)
}
body, err := io.ReadAll(resp.Body)
if err != nil {
t.Fatal(err)
}
var embedResp api.EmbedResponse
err = json.Unmarshal(body, &embedResp)
if err != nil {
t.Fatal(err)
}
if embedResp.Model != "t-bone" {
t.Fatalf("expected model t-bone, got %s", embedResp.Model)
}
if embedResp.Embeddings == nil {
t.Fatalf("expected embeddings to not be nil, got %v", embedResp.Embeddings)
}
if len(embedResp.Embeddings) != 0 {
t.Fatalf("expected embeddings to be empty, got %v", embedResp.Embeddings)
}
},
},
{
Name: "Embed Handler Invalid Input",
Method: http.MethodPost,
Path: "/api/embed",
Setup: func(t *testing.T, req *http.Request) {
embedReq := api.EmbedRequest{
Model: "t-bone",
Input: 2,
}
jsonData, err := json.Marshal(embedReq)
require.NoError(t, err)
req.Body = io.NopCloser(bytes.NewReader(jsonData))
},
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
if contentType != "application/json; charset=utf-8" {
t.Fatalf("expected content type application/json; charset=utf-8, got %s", contentType)
}
_, err := io.ReadAll(resp.Body)
if err != nil {
t.Fatal(err)
}
if resp.StatusCode != http.StatusBadRequest {
t.Fatalf("expected status code 400, got %d", resp.StatusCode)
}
},
},
}
@@ -455,75 +325,3 @@ func TestCase(t *testing.T) {
})
}
}
func TestShow(t *testing.T) {
t.Setenv("OLLAMA_MODELS", t.TempDir())
envconfig.LoadConfig()
var s Server
createRequest(t, s.CreateModelHandler, api.CreateRequest{
Name: "show-model",
Modelfile: fmt.Sprintf(
"FROM %s\nFROM %s",
createBinFile(t, llm.KV{"general.architecture": "test"}, nil),
createBinFile(t, llm.KV{"general.architecture": "clip"}, nil),
),
})
w := createRequest(t, s.ShowModelHandler, api.ShowRequest{
Name: "show-model",
})
if w.Code != http.StatusOK {
t.Fatalf("expected status code 200, actual %d", w.Code)
}
var resp api.ShowResponse
if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
t.Fatal(err)
}
if resp.ModelInfo["general.architecture"] != "test" {
t.Fatal("Expected model architecture to be 'test', but got", resp.ModelInfo["general.architecture"])
}
if resp.ProjectorInfo["general.architecture"] != "clip" {
t.Fatal("Expected projector architecture to be 'clip', but got", resp.ProjectorInfo["general.architecture"])
}
}
func TestNormalize(t *testing.T) {
type testCase struct {
input []float32
}
testCases := []testCase{
{input: []float32{1}},
{input: []float32{0, 1, 2, 3}},
{input: []float32{0.1, 0.2, 0.3}},
{input: []float32{-0.1, 0.2, 0.3, -0.4}},
{input: []float32{0, 0, 0}},
}
isNormalized := func(vec []float32) (res bool) {
sum := 0.0
for _, v := range vec {
sum += float64(v * v)
}
if math.Abs(sum-1) > 1e-6 {
return sum == 0
} else {
return true
}
}
for _, tc := range testCases {
t.Run("", func(t *testing.T) {
normalized := normalize(tc.input)
if !isNormalized(normalized) {
t.Errorf("Vector %v is not normalized", tc.input)
}
})
}
}

View File

@@ -7,6 +7,7 @@ import (
"log/slog"
"reflect"
"runtime"
"slices"
"sort"
"strings"
"sync"
@@ -23,11 +24,9 @@ type LlmRequest struct {
ctx context.Context //nolint:containedctx
model *Model
opts api.Options
origNumCtx int // Track the initial ctx request
sessionDuration *api.Duration
sessionDuration time.Duration
successCh chan *runnerRef
errCh chan error
schedAttempts uint
}
type Scheduler struct {
@@ -39,23 +38,11 @@ type Scheduler struct {
loaded map[string]*runnerRef
loadedMu sync.Mutex
loadFn func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int)
newServerFn func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error)
getGpuFn func() gpu.GpuInfoList
getCpuFn func() gpu.GpuInfoList
reschedDelay time.Duration
loadFn func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList)
newServerFn func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options) (llm.LlamaServer, error)
getGpuFn func() gpu.GpuInfoList
}
// Default automatic value for number of models we allow per GPU
// Model will still need to fit in VRAM, but loading many small models
// on a large GPU can cause stalling
var defaultModelsPerGPU = 3
// Default automatic value for parallel setting
// Model will still need to fit in VRAM. If this setting wont fit
// we'll back off down to 1 to try to get it to fit
var defaultParallel = 4
var ErrMaxQueue = fmt.Errorf("server busy, please try again. maximum pending requests exceeded")
func InitScheduler(ctx context.Context) *Scheduler {
@@ -67,19 +54,20 @@ func InitScheduler(ctx context.Context) *Scheduler {
loaded: make(map[string]*runnerRef),
newServerFn: llm.NewLlamaServer,
getGpuFn: gpu.GetGPUInfo,
getCpuFn: gpu.GetCPUInfo,
reschedDelay: 250 * time.Millisecond,
}
sched.loadFn = sched.load
return sched
}
// 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 *api.Duration) (chan *runnerRef, chan error) {
func (s *Scheduler) GetRunner(c context.Context, model *Model, opts api.Options, sessionDuration time.Duration) (chan *runnerRef, chan error) {
// allocate a large enough kv cache for all parallel requests
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
opts.NumCtx *= envconfig.NumParallel
req := &LlmRequest{
ctx: c,
model: model,
@@ -117,22 +105,11 @@ func (s *Scheduler) processPending(ctx context.Context) {
return
case pending := <-s.pendingReqCh:
// Block other requests until we get this pending request running
pending.schedAttempts++
if pending.origNumCtx == 0 {
pending.origNumCtx = pending.opts.NumCtx
}
if pending.ctx.Err() != nil {
slog.Debug("pending request cancelled or timed out, skipping scheduling")
continue
}
numParallel := envconfig.NumParallel
// TODO (jmorganca): multimodal models don't support parallel yet
// see https://github.com/ollama/ollama/issues/4165
if len(pending.model.ProjectorPaths) > 0 && numParallel != 1 {
numParallel = 1
slog.Warn("multimodal models don't support parallel requests yet")
}
for {
var runnerToExpire *runnerRef
@@ -154,110 +131,44 @@ func (s *Scheduler) processPending(ctx context.Context) {
} else {
// Either no models are loaded or below envconfig.MaxRunners
// Get a refreshed GPU list
var gpus gpu.GpuInfoList
if pending.opts.NumGPU == 0 {
gpus = s.getCpuFn()
} else {
gpus = s.getGpuFn()
}
if envconfig.MaxRunners <= 0 {
// No user specified MaxRunners, so figure out what automatic setting to use
// If all GPUs have reliable free memory reporting, defaultModelsPerGPU * the number of GPUs
// if any GPU has unreliable free memory reporting, 1x the number of GPUs
allReliable := true
for _, gpu := range gpus {
if gpu.UnreliableFreeMemory {
allReliable = false
break
}
}
if allReliable {
envconfig.MaxRunners = defaultModelsPerGPU * len(gpus)
slog.Debug("updating default concurrency", "OLLAMA_MAX_LOADED_MODELS", envconfig.MaxRunners, "gpu_count", len(gpus))
} else {
slog.Info("one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency")
envconfig.MaxRunners = len(gpus)
}
}
gpus := s.getGpuFn()
// Load model for fitting
ggml, err := llm.LoadModel(pending.model.ModelPath, 0)
ggml, err := llm.LoadModel(pending.model.ModelPath)
if err != nil {
pending.errCh <- err
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
if numParallel <= 0 {
numParallel = defaultParallel
}
pending.opts.NumCtx = pending.origNumCtx * numParallel
if loadedCount == 0 {
slog.Debug("cpu mode with first model, loading")
s.loadFn(pending, ggml, gpus, numParallel)
break
}
runnerToExpire = s.maybeFindCPURunnerToUnload(pending, ggml, gpus)
if runnerToExpire == nil {
slog.Debug("cpu mode with available system memory or first model, loading")
s.loadFn(pending, ggml, gpus, numParallel)
break
}
// else we need to expire a runner
} else if loadedCount == 0 {
// No models loaded. Load the model but prefer the best fit.
slog.Debug("loading first model", "model", pending.model.ModelPath)
g := pickBestFitGPUs(pending, ggml, gpus, &numParallel)
if g != nil {
gpus = g
}
s.loadFn(pending, ggml, gpus, numParallel)
// If we're CPU only mode, just limit by envconfig.MaxRunners above
// TODO handle system memory exhaustion
if (len(gpus) == 1 && gpus[0].Library == "cpu") || pending.opts.NumGPU == 0 {
slog.Debug("cpu mode with existing models, loading")
s.loadFn(pending, ggml, gpus)
break
}
if runnerToExpire == nil {
// More than one loaded model, so we have to see if the
// new one fits
//
// We want to avoid loading on any GPUs that have other
// models still loading on them to avoid potential races
// with VRAM consumption ramping up during load
availGpus := s.filterGPUsWithoutLoadingModels(gpus)
// Update free memory from currently loaded models
s.updateFreeSpace(availGpus)
fitGpus := pickBestFitGPUs(pending, ggml, availGpus, &numParallel)
if fitGpus != nil {
slog.Debug("new model fits with existing models, loading")
s.loadFn(pending, ggml, fitGpus, numParallel)
break
// No models loaded. Load the model but prefer the best fit.
if loadedCount == 0 {
slog.Debug("loading first model", "model", pending.model.ModelPath)
g := pickBestFitGPUs(pending, ggml, gpus)
if g != nil {
gpus = g
}
// We couldn't find a set of GPUs to fully load the new
// model. If no other models are loading (both GPU lists
// are the same) then we need to unload another model to
// make room
if len(availGpus) < len(gpus) {
// There are other requests pending, and this one
// needs more time, so put it on the back of the
// queue so that we might satisfy other pending
// requests that aren't blocked
go func() {
// Process in a go routine to avoid deadlocking
// the scheduler if our queue is full
slog.Debug("delaying scheduling while other models finish loading", "attempts", pending.schedAttempts, "model", pending.model.ModelPath)
time.Sleep(s.reschedDelay)
s.pendingReqCh <- pending
}()
break
}
runnerToExpire = s.findRunnerToUnload()
s.loadFn(pending, ggml, gpus)
break
}
// More than one loaded model, so we have to see if the new one fits
// Update free memory from currently loaded models
s.updateFreeSpace(gpus)
gpus = pickBestFitGPUs(pending, ggml, gpus)
if gpus != nil {
slog.Debug("new model fits with existing models, loading")
s.loadFn(pending, ggml, gpus)
break
}
runnerToExpire = s.findRunnerToUnload()
}
if runnerToExpire == nil {
@@ -386,9 +297,7 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
runner.expireTimer.Stop()
runner.expireTimer = nil
}
if pending.sessionDuration != nil {
runner.sessionDuration = pending.sessionDuration.Duration
}
runner.sessionDuration = pending.sessionDuration
pending.successCh <- runner
go func() {
<-pending.ctx.Done()
@@ -397,15 +306,8 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
}()
}
func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
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)
func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) {
llama, err := s.newServerFn(gpus, req.model.ModelPath, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts)
if err != nil {
// some older models are not compatible with newer versions of llama.cpp
// show a generalized compatibility error until there is a better way to
@@ -422,14 +324,13 @@ func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList,
modelPath: req.model.ModelPath,
llama: llama,
Options: &req.opts,
sessionDuration: sessionDuration,
sessionDuration: req.sessionDuration,
gpus: gpus,
estimatedVRAM: llama.EstimatedVRAM(),
estimatedTotal: llama.EstimatedTotal(),
loading: true,
refCount: 1,
}
runner.numParallel = numParallel
runner.refMu.Lock()
s.loadedMu.Lock()
@@ -467,9 +368,17 @@ func (s *Scheduler) updateFreeSpace(allGpus gpu.GpuInfoList) {
s.loadedMu.Lock()
for _, r := range s.loaded {
r.refMu.Lock()
gpuIDs := make([]string, 0, len(r.gpus))
if r.llama != nil {
// TODO this should be broken down by GPU instead of assuming uniform spread
estimatedVRAMPerGPU := r.llama.EstimatedVRAM() / uint64(len(r.gpus))
for _, gpu := range r.gpus {
gpuIDs = append(gpuIDs, gpu.ID)
}
for _, gpu := range allGpus {
predMap[predKey{gpu.Library, gpu.ID}] += r.llama.EstimatedVRAMByGPU(gpu.ID)
if slices.Contains(gpuIDs, gpu.ID) {
predMap[predKey{gpu.Library, gpu.ID}] += estimatedVRAMPerGPU
}
}
} else {
slog.Warn("unexpected nil runner reference, memory prediction may be incorrect")
@@ -492,36 +401,11 @@ func (s *Scheduler) updateFreeSpace(allGpus gpu.GpuInfoList) {
// after we start our first runner, then we'll never acount for that, so picking the smallest free value seems prudent.
allGpus[i].FreeMemory = allGpus[i].TotalMemory - p
}
slog.Info("updated VRAM based on existing loaded models", "gpu", allGpus[i].ID, "library", allGpus[i].Library, "total", format.HumanBytes2(allGpus[i].TotalMemory), "available", format.HumanBytes2(allGpus[i].FreeMemory))
slog.Info("updated VRAM", "gpu", allGpus[i].ID, "library", allGpus[i].Library, "total", format.HumanBytes2(allGpus[i].TotalMemory), "available", format.HumanBytes2(allGpus[i].FreeMemory))
}
}
}
// While models are loading the VRAM consumption numbers will be indeterminate, so we have
// to avoid scheduling another model on the same GPU(s) that haven't stabilized.
// This routine returns the set of GPUs that do not have an active loading model.
// If all GPUs have loading models, an empty list will be returned (not a single CPU entry)
func (s *Scheduler) filterGPUsWithoutLoadingModels(allGpus gpu.GpuInfoList) gpu.GpuInfoList {
ret := append(gpu.GpuInfoList{}, allGpus...)
s.loadedMu.Lock()
defer s.loadedMu.Unlock()
for _, runner := range s.loaded {
if runner.loading {
slog.Debug("overlapping loads detected", "gpus", runner.gpus, "model", runner.modelPath)
for _, busyGPU := range runner.gpus {
for i := range ret {
if ret[i].ID == busyGPU.ID {
ret = append(ret[:i], ret[i+1:]...)
break
}
}
}
}
}
return ret
}
// TODO consolidate sched_types.go
type runnerRef struct {
refMu sync.Mutex
// refCond sync.Cond // Signaled on transition from 1 -> 0 refCount
@@ -538,9 +422,8 @@ type runnerRef struct {
expireTimer *time.Timer
expiresAt time.Time
model *Model
modelPath string
numParallel int
model *Model
modelPath string
*api.Options
}
@@ -581,9 +464,6 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
optsNew.NumGPU = -1
}
// Normalize the NumCtx for parallelism
optsExisting.NumCtx = optsExisting.NumCtx / runner.numParallel
ctx, cancel := context.WithTimeout(ctx, timeout)
defer cancel()
if !reflect.DeepEqual(runner.model.AdapterPaths, req.model.AdapterPaths) || // have the adapters changed?
@@ -607,11 +487,8 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
func (runner *runnerRef) waitForVRAMRecovery() chan interface{} {
finished := make(chan interface{}, 1)
// CPU or Metal don't need checking, so no waiting required
// windows can page VRAM, only cuda currently can report accurate used vram usage
if len(runner.gpus) == 0 ||
(len(runner.gpus) == 1 && (runner.gpus[0].Library == "cpu" || runner.gpus[0].Library == "metal")) ||
(runtime.GOOS == "windows" && runner.gpus[0].Library != "cuda") {
// CPU or Metal don't need checking, so no waiting required, windows can page VRAM, and the APIs we query tend to be optimistic on free space
if (len(runner.gpus) == 1 && (runner.gpus[0].Library == "cpu" || runner.gpus[0].Library == "metal")) || runtime.GOOS == "windows" {
finished <- struct{}{}
return finished
}
@@ -631,7 +508,7 @@ func (runner *runnerRef) waitForVRAMRecovery() chan interface{} {
for {
<-ticker.C
if time.Now().After(expiresAt) {
slog.Warn("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds(), "model", runner.modelPath)
slog.Warn("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds())
finished <- struct{}{}
}
@@ -644,7 +521,7 @@ func (runner *runnerRef) waitForVRAMRecovery() chan interface{} {
}
// If we're within ~80% of the estimated memory usage recovered, bail out
if float32(freeMemoryNow-freeMemoryBefore) > float32(runner.estimatedVRAM)*0.8 {
slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()), "model", runner.modelPath)
slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()))
finished <- struct{}{}
return
}
@@ -670,39 +547,21 @@ func (a ByDuration) Less(i, j int) bool {
// pickBestFitGPUs will try to find the optimal placement of the model in the available GPUs where the model fully fits
// If the model can not be fit fully within the available GPU(s) nil is returned
// If numParallel is <= 0, this will attempt try to optimize parallism based on available VRAM, and adjust
// opts.NumCtx accordingly
func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel *int) gpu.GpuInfoList {
func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) gpu.GpuInfoList {
var estimatedVRAM uint64
var numParallelToTry []int
if *numParallel <= 0 {
// If no specific parallel setting was provided, try larger then smaller, always end with 1
numParallelToTry = append(numParallelToTry, defaultParallel, 1)
} else {
numParallelToTry = []int{*numParallel}
}
for _, gl := range gpus.ByLibrary() {
var ok bool
sgl := append(make(gpu.GpuInfoList, 0, len(gl)), gl...)
// TODO - potentially sort by performance capability, existing models loaded, etc.
// TODO - Eliminate any GPUs that already have envconfig.MaxRunners loaded on them
// Note: at present, this will favor more VRAM over faster GPU speed in mixed setups
sort.Sort(sort.Reverse(gpu.ByFreeMemory(sgl)))
// First attempt to fit the model into a single GPU
for _, p := range numParallelToTry {
req.opts.NumCtx = req.origNumCtx * p
if !envconfig.SchedSpread {
for _, g := range sgl {
if ok, estimatedVRAM = llm.PredictServerFit([]gpu.GpuInfo{g}, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Info("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "parallel", p, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
*numParallel = p
return []gpu.GpuInfo{g}
}
}
for _, g := range sgl {
if ok, estimatedVRAM = llm.PredictServerFit([]gpu.GpuInfo{g}, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Debug("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
return []gpu.GpuInfo{g}
}
}
@@ -711,13 +570,9 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numP
// - try subsets of GPUs instead of just falling back to 1 or all in a family
// Now try all the GPUs
for _, p := range numParallelToTry {
req.opts.NumCtx = req.origNumCtx * p
if ok, estimatedVRAM = llm.PredictServerFit(sgl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Info("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "parallel", p, "required", format.HumanBytes2(estimatedVRAM))
*numParallel = p
return sgl
}
if ok, estimatedVRAM = llm.PredictServerFit(sgl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Debug("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "required", format.HumanBytes2(estimatedVRAM))
return sgl
}
}
return nil
@@ -731,10 +586,6 @@ func (s *Scheduler) findRunnerToUnload() *runnerRef {
runnerList = append(runnerList, r)
}
s.loadedMu.Unlock()
if len(runnerList) == 0 {
slog.Debug("no loaded runner to unload")
return nil
}
// In the future we can enhance the algorithm to be smarter about picking the optimal runner to unload
// e.g., if we have multiple options, will one make room for the request?
@@ -765,18 +616,3 @@ func (s *Scheduler) unloadAllRunners() {
}
}
}
// If other runners are loaded, make sure the pending request will fit in system memory
// If not, pick a runner to unload, else return nil and the request can be loaded
func (s *Scheduler) maybeFindCPURunnerToUnload(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) *runnerRef {
slog.Debug("evaluating if CPU model load will fit in available system memory")
estimate := llm.EstimateGPULayers(gpus, ggml, req.model.ProjectorPaths, req.opts)
if estimate.TotalSize <= gpus[0].FreeMemory {
slog.Debug("cpu inference mode, model fits in available system memory", "model", format.HumanBytes2(estimate.TotalSize), "available", format.HumanBytes2(gpus[0].FreeMemory))
return nil
}
// TODO - optimization: try to find CPU only runners first, or partial offloads with enough in system memory to make room
return s.findRunnerToUnload()
}

Some files were not shown because too many files have changed in this diff Show More