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Switch back to subprocessing for llama.cpp

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This should resolve a number of memory leak and stability defects by allowing
us to isolate llama.cpp in a separate process and shutdown when idle, and
gracefully restart if it has problems.  This also serves as a first step to be
able to run multiple copies to support multiple models concurrently.
This commit is contained in:
Daniel Hiltgen 2024-03-14 10:24:13 -07:00
parent 3b6a9154dd
commit 58d95cc9bd
35 changed files with 1416 additions and 1910 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

42
.github/workflows/test.yaml vendored
View file

@ -56,10 +56,12 @@ jobs:
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
$gccpath=(get-command gcc).source | split-path -parent
& "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
cd $env:GITHUB_WORKSPACE
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$env:PATH"
$env:PATH="$gopath;$gccpath;$env:PATH"
echo $env:PATH
go generate -x ./...
if: ${{ startsWith(matrix.os, 'windows-') }}
name: "Windows Go Generate"
@ -69,7 +71,9 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: |
llm/build/**/bin/*
llm/build/**/*.a
generate-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
@ -100,7 +104,7 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: cuda-${{ matrix.cuda-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: llm/build/**/bin/*
generate-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
@ -131,7 +135,7 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: rocm-${{ matrix.rocm-version }}-libraries
path: llm/llama.cpp/build/**/lib/*
path: llm/build/**/lib/*
# ROCm generation step
generate-windows-rocm:
@ -244,17 +248,17 @@ jobs:
esac >>$GITHUB_ENV
shell: bash
- run: |
mkdir -p llm/llama.cpp/build/linux/$ARCH/stub/lib/
touch llm/llama.cpp/build/linux/$ARCH/stub/lib/stub.so
mkdir -p llm/build/linux/$ARCH/stub/bin/
touch llm/build/linux/$ARCH/stub/bin/stub.so
if: ${{ startsWith(matrix.os, 'ubuntu-') }}
- run: |
mkdir -p llm/llama.cpp/build/darwin/$ARCH/stub/lib/
touch llm/llama.cpp/build/darwin/$ARCH/stub/lib/stub.dylib
touch llm/llama.cpp/ggml-metal.metal
mkdir -p llm/build/darwin/$ARCH/stub/bin/
touch llm/build/darwin/$ARCH/stub/bin/stub.dylib
touch llm/ggml-metal.metal
if: ${{ startsWith(matrix.os, 'macos-') }}
- run: |
mkdir -p llm/llama.cpp/build/windows/$ARCH/stub/stub/lib/
touch llm/llama.cpp/build/windows/$ARCH/stub/stub/lib/stub.dll
mkdir -p llm/build/windows/$ARCH/stub/stub/bin/
touch llm/build/windows/$ARCH/stub/stub/bin/stub.dll
if: ${{ startsWith(matrix.os, 'windows-') }}
- uses: golangci/golangci-lint-action@v3
test:
@ -271,6 +275,7 @@ jobs:
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
OLLAMA_CPU_TARGET: "static"
steps:
- uses: actions/checkout@v4
with:
@ -287,18 +292,19 @@ jobs:
esac >>$GITHUB_ENV
shell: bash
- run: |
mkdir -p llm/llama.cpp/build/linux/$ARCH/stub/lib/
touch llm/llama.cpp/build/linux/$ARCH/stub/lib/stub.so
mkdir -p llm/build/linux/$ARCH/stub/bin/
touch llm//build/linux/$ARCH/stub/bin/stub.so
if: ${{ startsWith(matrix.os, 'ubuntu-') }}
- run: |
mkdir -p llm/llama.cpp/build/darwin/$ARCH/stub/lib/
touch llm/llama.cpp/build/darwin/$ARCH/stub/lib/stub.dylib
touch llm/llama.cpp/ggml-metal.metal
mkdir -p llm/build/darwin/$ARCH/stub/bin/
touch llm/build/darwin/$ARCH/stub/bin/stub.dylib
touch llm/ggml-metal.metal
if: ${{ startsWith(matrix.os, 'macos-') }}
- run: |
mkdir -p llm/llama.cpp/build/windows/$ARCH/stub/stub/lib/
touch llm/llama.cpp/build/windows/$ARCH/stub/stub/lib/stub.dll
mkdir -p llm/build/windows/$ARCH/stub/stub/bin/
touch llm/build/windows/$ARCH/stub/stub/bin/stub.dll
if: ${{ startsWith(matrix.os, 'windows-') }}
- run: go generate ./...
- run: go build
- run: go test -v ./...
- uses: actions/upload-artifact@v4

1
.gitignore vendored
View file

@ -11,3 +11,4 @@ ggml-metal.metal
.idea
test_data
*.crt
llm/build

25
Dockerfile
View file

@ -61,6 +61,8 @@ ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
@ -68,28 +70,33 @@ RUN OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
RUN OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-build-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/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
# Note, we only build the "base" CPU variant on arm since avx/avx2 are x86 features
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/arm64 cpu-builder-arm64 AS static-build-arm64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
# Intermediate stage used for ./scripts/build_linux.sh
FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=cuda-build-amd64 /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
COPY --from=static-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cuda-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/dist/deps/ ./dist/deps/
ARG GOFLAGS
ARG CGO_CFLAGS
@ -101,8 +108,8 @@ ENV CGO_ENABLED 1
ARG GOLANG_VERSION
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
COPY --from=cuda-build-arm64 /go/src/github.com/ollama/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
RUN mkdir -p /go/src/github.com/ollama/ollama/dist/deps/
COPY --from=static-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
COPY --from=cuda-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN go build -trimpath .

25
app/lifecycle/server.go
View file

@ -9,6 +9,7 @@ import (
"os"
"os/exec"
"path/filepath"
"syscall"
"time"
"github.com/ollama/ollama/api"
@ -83,6 +84,28 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
io.Copy(logFile, stderr) //nolint:errcheck
}()
// Re-wire context done behavior to attempt a graceful shutdown of the server
cmd.Cancel = func() error {
if cmd.Process != nil {
cmd.Process.Signal(os.Interrupt) //nolint:errcheck
tick := time.NewTicker(10 * time.Millisecond)
defer tick.Stop()
for {
select {
case <-tick.C:
// OS agnostic "is it still running"
if proc, err := os.FindProcess(int(cmd.Process.Pid)); err != nil || errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
return nil //nolint:nilerr
}
case <-time.After(5 * time.Second):
slog.Warn("graceful server shutdown timeout, killing", "pid", cmd.Process.Pid)
cmd.Process.Kill() //nolint:errcheck
}
}
}
return nil
}
// run the command and wait for it to finish
if err := cmd.Start(); err != nil {
return done, fmt.Errorf("failed to start server %w", err)
@ -105,7 +128,7 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
select {
case <-ctx.Done():
slog.Debug(fmt.Sprintf("server shutdown with exit code %d", code))
slog.Info(fmt.Sprintf("server shutdown with exit code %d", code))
done <- code
return
default:

17
gpu/amd_linux.go
View file

@ -100,6 +100,8 @@ func AMDGetGPUInfo(resp *GpuInfo) {
return
}
updateLibPath(libDir)
gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
if gfxOverride == "" {
supported, err := GetSupportedGFX(libDir)
@ -143,6 +145,21 @@ func AMDGetGPUInfo(resp *GpuInfo) {
}
}
func updateLibPath(libDir string) {
ldPaths := []string{}
if val, ok := os.LookupEnv("LD_LIBRARY_PATH"); ok {
ldPaths = strings.Split(val, ":")
}
for _, d := range ldPaths {
if d == libDir {
return
}
}
val := strings.Join(append(ldPaths, libDir), ":")
slog.Debug("updated lib path", "LD_LIBRARY_PATH", val)
os.Setenv("LD_LIBRARY_PATH", val)
}
// Walk the sysfs nodes for the available GPUs and gather information from them
// skipping over any devices in the skip map
func amdProcMemLookup(resp *GpuInfo, skip map[int]interface{}, ids []int) {

6
gpu/assets.go
View file

@ -11,6 +11,7 @@ import (
"strings"
"sync"
"syscall"
"time"
)
var (
@ -83,11 +84,16 @@ func Cleanup() {
tmpDir := filepath.Clean(filepath.Join(payloadsDir, ".."))
slog.Debug("cleaning up", "dir", tmpDir)
err := os.RemoveAll(tmpDir)
if err != nil {
// On windows, if we remove too quickly the llama.dll may still be in-use and fail to remove
time.Sleep(1000 * time.Millisecond)
err = os.RemoveAll(tmpDir)
if err != nil {
slog.Warn("failed to clean up", "dir", tmpDir, "err", err)
}
}
}
}
func UpdatePath(dir string) {
if runtime.GOOS == "windows" {

142
llm/dyn_ext_server.c
View file

@ -1,142 +0,0 @@
#include "dyn_ext_server.h"
#include <stdio.h>
#include <string.h>
#ifdef __linux__
#include <dlfcn.h>
#define LOAD_LIBRARY(lib, flags) dlopen(lib, flags)
#define LOAD_SYMBOL(handle, sym) dlsym(handle, sym)
#define LOAD_ERR() strdup(dlerror())
#define UNLOAD_LIBRARY(handle) dlclose(handle)
#elif _WIN32
#include <windows.h>
#define LOAD_LIBRARY(lib, flags) LoadLibrary(lib)
#define LOAD_SYMBOL(handle, sym) GetProcAddress(handle, sym)
#define UNLOAD_LIBRARY(handle) FreeLibrary(handle)
#define LOAD_ERR() ({\
LPSTR messageBuffer = NULL; \
size_t size = FormatMessageA(FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS, \
NULL, GetLastError(), MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT), (LPSTR)&messageBuffer, 0, NULL); \
char *resp = strdup(messageBuffer); \
LocalFree(messageBuffer); \
resp; \
})
#else
#include <dlfcn.h>
#define LOAD_LIBRARY(lib, flags) dlopen(lib, flags)
#define LOAD_SYMBOL(handle, sym) dlsym(handle, sym)
#define LOAD_ERR() strdup(dlerror())
#define UNLOAD_LIBRARY(handle) dlclose(handle)
#endif
void dyn_init(const char *libPath, struct dynamic_llama_server *s,
ext_server_resp_t *err) {
int i = 0;
struct lookup {
char *s;
void **p;
} l[] = {
{"llama_server_init", (void *)&s->llama_server_init},
{"llama_server_start", (void *)&s->llama_server_start},
{"llama_server_stop", (void *)&s->llama_server_stop},
{"llama_server_completion", (void *)&s->llama_server_completion},
{"llama_server_completion_next_result",
(void *)&s->llama_server_completion_next_result},
{"llama_server_completion_cancel",
(void *)&s->llama_server_completion_cancel},
{"llama_server_release_task_result",
(void *)&s->llama_server_release_task_result},
{"llama_server_tokenize", (void *)&s->llama_server_tokenize},
{"llama_server_detokenize", (void *)&s->llama_server_detokenize},
{"llama_server_embedding", (void *)&s->llama_server_embedding},
{"llama_server_release_json_resp",
(void *)&s->llama_server_release_json_resp},
{"", NULL},
};
printf("loading library %s\n", libPath);
s->handle = LOAD_LIBRARY(libPath, RTLD_LOCAL|RTLD_NOW);
if (!s->handle) {
err->id = -1;
char *msg = LOAD_ERR();
snprintf(err->msg, err->msg_len,
"Unable to load dynamic server library: %s", msg);
free(msg);
return;
}
for (i = 0; l[i].p != NULL; i++) {
*l[i].p = LOAD_SYMBOL(s->handle, l[i].s);
if (!l[i].p) {
UNLOAD_LIBRARY(s->handle);
err->id = -1;
char *msg = LOAD_ERR();
snprintf(err->msg, err->msg_len, "symbol lookup for %s failed: %s",
l[i].s, msg);
free(msg);
return;
}
}
}
inline void dyn_llama_server_init(struct dynamic_llama_server s,
ext_server_params_t *sparams,
ext_server_resp_t *err) {
s.llama_server_init(sparams, err);
}
inline void dyn_llama_server_start(struct dynamic_llama_server s) {
s.llama_server_start();
}
inline void dyn_llama_server_stop(struct dynamic_llama_server s) {
s.llama_server_stop();
}
inline void dyn_llama_server_completion(struct dynamic_llama_server s,
const char *json_req,
ext_server_resp_t *resp) {
s.llama_server_completion(json_req, resp);
}
inline void dyn_llama_server_completion_next_result(
struct dynamic_llama_server s, const int task_id,
ext_server_task_result_t *result) {
s.llama_server_completion_next_result(task_id, result);
}
inline void dyn_llama_server_completion_cancel(
struct dynamic_llama_server s, const int task_id, ext_server_resp_t *err) {
s.llama_server_completion_cancel(task_id, err);
}
inline void dyn_llama_server_release_task_result(
struct dynamic_llama_server s, ext_server_task_result_t *result) {
s.llama_server_release_task_result(result);
}
inline void dyn_llama_server_tokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_tokenize(json_req, json_resp, err);
}
inline void dyn_llama_server_detokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_detokenize(json_req, json_resp, err);
}
inline void dyn_llama_server_embedding(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err) {
s.llama_server_embedding(json_req, json_resp, err);
}
inline void dyn_llama_server_release_json_resp(
struct dynamic_llama_server s, char **json_resp) {
s.llama_server_release_json_resp(json_resp);
}

388
llm/dyn_ext_server.go
View file

@ -1,388 +0,0 @@
package llm
/*
#cgo CFLAGS: -I${SRCDIR}/ext_server -I${SRCDIR}/llama.cpp -I${SRCDIR}/llama.cpp/common -I${SRCDIR}/llama.cpp/examples/server
#cgo CFLAGS: -DNDEBUG -DLLAMA_SERVER_LIBRARY=1 -D_XOPEN_SOURCE=600 -DACCELERATE_NEW_LAPACK -DACCELERATE_LAPACK_ILP64
#cgo CFLAGS: -Wmissing-noreturn -Wextra -Wcast-qual -Wno-unused-function -Wno-array-bounds
#cgo CPPFLAGS: -Ofast -Wextra -Wno-unused-function -Wno-unused-variable -Wno-deprecated-declarations
#cgo darwin CFLAGS: -D_DARWIN_C_SOURCE
#cgo darwin CPPFLAGS: -DGGML_USE_ACCELERATE
#cgo darwin CPPFLAGS: -DGGML_USE_METAL -DGGML_METAL_NDEBUG
#cgo darwin LDFLAGS: -lc++ -framework Accelerate
#cgo darwin LDFLAGS: -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
#cgo linux CFLAGS: -D_GNU_SOURCE
#cgo linux LDFLAGS: -lrt -ldl -lstdc++ -lm
#cgo linux windows LDFLAGS: -lpthread
#include <stdlib.h>
#include "dyn_ext_server.h"
*/
import "C"
import (
"bytes"
"context"
"encoding/json"
"fmt"
"log/slog"
"os"
"path/filepath"
"strings"
"sync"
"time"
"unsafe"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/gpu"
)
type dynExtServer struct {
s C.struct_dynamic_llama_server
options *api.Options
}
// Note: current implementation does not support concurrent instantiations
var mutex sync.Mutex
func newExtServerResp(len C.size_t) C.ext_server_resp_t {
var resp C.ext_server_resp_t
resp.msg_len = len
bytes := make([]byte, len)
resp.msg = (*C.char)(C.CBytes(bytes))
return resp
}
func freeExtServerResp(resp C.ext_server_resp_t) {
if resp.msg_len == 0 {
return
}
C.free(unsafe.Pointer(resp.msg))
}
func extServerResponseToErr(resp C.ext_server_resp_t) error {
return fmt.Errorf(C.GoString(resp.msg))
}
func newDynExtServer(library, model string, adapters, projectors []string, opts *api.Options) (LLM, error) {
if !mutex.TryLock() {
slog.Info("concurrent llm servers not yet supported, waiting for prior server to complete")
mutex.Lock()
}
gpu.UpdatePath(filepath.Dir(library))
libPath := C.CString(library)
defer C.free(unsafe.Pointer(libPath))
resp := newExtServerResp(512)
defer freeExtServerResp(resp)
var srv C.struct_dynamic_llama_server
C.dyn_init(libPath, &srv, &resp)
if resp.id < 0 {
mutex.Unlock()
return nil, fmt.Errorf("Unable to load dynamic library: %s", C.GoString(resp.msg))
}
llm := dynExtServer{
s: srv,
options: opts,
}
slog.Info(fmt.Sprintf("Loading Dynamic llm server: %s", library))
var sparams C.ext_server_params_t
sparams.model = C.CString(model)
defer C.free(unsafe.Pointer(sparams.model))
sparams.embedding = true
sparams.n_ctx = C.uint(opts.NumCtx)
sparams.n_batch = C.uint(opts.NumBatch)
sparams.n_gpu_layers = C.int(opts.NumGPU)
sparams.main_gpu = C.int(opts.MainGPU)
sparams.n_parallel = 1 // TODO - wire up concurrency
// Always use the value encoded in the model
sparams.rope_freq_base = 0.0
sparams.rope_freq_scale = 0.0
sparams.memory_f16 = C.bool(opts.F16KV)
sparams.use_mlock = C.bool(opts.UseMLock)
sparams.use_mmap = C.bool(opts.UseMMap)
if opts.UseNUMA {
sparams.numa = C.int(1)
} else {
sparams.numa = C.int(0)
}
sparams.lora_adapters = nil
for i := 0; i < len(adapters); i++ {
la := (*C.ext_server_lora_adapter_t)(C.malloc(C.sizeof_ext_server_lora_adapter_t))
defer C.free(unsafe.Pointer(la))
la.adapter = C.CString(adapters[i])
defer C.free(unsafe.Pointer(la.adapter))
la.scale = C.float(1.0) // TODO expose scale/weights up through ollama UX
la.next = nil
if i == 0 {
sparams.lora_adapters = la
} else {
tmp := sparams.lora_adapters
for ; tmp.next != nil; tmp = tmp.next {
}
tmp.next = la
}
}
if len(projectors) > 0 {
// TODO: applying multiple projectors is not supported by the llama.cpp server yet
sparams.mmproj = C.CString(projectors[0])
defer C.free(unsafe.Pointer(sparams.mmproj))
} else {
sparams.mmproj = nil
}
sparams.n_threads = C.uint(opts.NumThread)
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
sparams.verbose_logging = C.bool(true)
} else {
sparams.verbose_logging = C.bool(false)
}
slog.Info("Initializing llama server")
slog.Debug(fmt.Sprintf("server params: %+v", sparams))
initResp := newExtServerResp(512)
defer freeExtServerResp(initResp)
C.dyn_llama_server_init(llm.s, &sparams, &initResp)
if initResp.id < 0 {
mutex.Unlock()
err := extServerResponseToErr(initResp)
slog.Debug(fmt.Sprintf("failure during initialization: %s", err))
return nil, err
}
slog.Info("Starting llama main loop")
C.dyn_llama_server_start(llm.s)
return &llm, nil
}
func (llm *dynExtServer) Predict(ctx context.Context, predict PredictOpts, fn func(PredictResult)) error {
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
if len(predict.Images) > 0 {
slog.Info(fmt.Sprintf("loaded %d images", len(predict.Images)))
}
request := map[string]any{
"prompt": predict.Prompt,
"stream": true,
"n_predict": predict.Options.NumPredict,
"n_keep": predict.Options.NumKeep,
"temperature": predict.Options.Temperature,
"top_k": predict.Options.TopK,
"top_p": predict.Options.TopP,
"tfs_z": predict.Options.TFSZ,
"typical_p": predict.Options.TypicalP,
"repeat_last_n": predict.Options.RepeatLastN,
"repeat_penalty": predict.Options.RepeatPenalty,
"presence_penalty": predict.Options.PresencePenalty,
"frequency_penalty": predict.Options.FrequencyPenalty,
"mirostat": predict.Options.Mirostat,
"mirostat_tau": predict.Options.MirostatTau,
"mirostat_eta": predict.Options.MirostatEta,
"penalize_nl": predict.Options.PenalizeNewline,
"seed": predict.Options.Seed,
"stop": predict.Options.Stop,
"image_data": predict.Images,
"cache_prompt": true,
}
if predict.Format == "json" {
request["grammar"] = jsonGrammar
if !strings.Contains(strings.ToLower(predict.Prompt), "json") {
slog.Warn("Prompt does not specify that the LLM should response in JSON, but JSON format is expected. For best results specify that JSON is expected in the system prompt.")
}
}
retryDelay := 100 * time.Microsecond
for retries := 0; retries < maxRetries; retries++ {
if retries > 0 {
time.Sleep(retryDelay) // wait before retrying
retryDelay *= 2 // exponential backoff
}
// Handling JSON marshaling with special characters unescaped.
buffer := &bytes.Buffer{}
enc := json.NewEncoder(buffer)
enc.SetEscapeHTML(false)
if err := enc.Encode(request); err != nil {
return fmt.Errorf("failed to marshal data: %w", err)
}
req := C.CString(buffer.String())
defer C.free(unsafe.Pointer(req))
C.dyn_llama_server_completion(llm.s, req, &resp)
if resp.id < 0 {
return extServerResponseToErr(resp)
}
retryNeeded := false
// keep track of the last token generated, this is used to abort if the model starts looping
var lastToken string
var tokenRepeat int
out:
for {
select {
case <-ctx.Done():
return cancelCompletion(llm, resp)
default:
var result C.ext_server_task_result_t
C.dyn_llama_server_completion_next_result(llm.s, resp.id, &result)
json_resp := C.GoString(result.json_resp)
C.dyn_llama_server_release_task_result(llm.s, &result)
var p prediction
if err := json.Unmarshal([]byte(json_resp), &p); err != nil {
C.dyn_llama_server_completion_cancel(llm.s, resp.id, &resp)
if resp.id < 0 {
return fmt.Errorf("error unmarshaling llm prediction response: %w and cancel %s", err, C.GoString(resp.msg))
} else {
return fmt.Errorf("error unmarshaling llm prediction response: %w", err)
}
}
if bool(result.error) && strings.Contains(json_resp, "slot unavailable") {
retryNeeded = true
// task will already be canceled
break out
}
switch {
case strings.TrimSpace(p.Content) == lastToken:
tokenRepeat++
default:
lastToken = strings.TrimSpace(p.Content)
tokenRepeat = 0
}
// 30 picked as an arbitrary max token repeat limit, modify as needed
if tokenRepeat > 30 {
slog.Debug("prediction aborted, token repeat limit reached")
return cancelCompletion(llm, resp)
}
if p.Content != "" {
fn(PredictResult{
Content: p.Content,
})
}
if p.Stop || bool(result.stop) {
fn(PredictResult{
Done: true,
PromptEvalCount: p.Timings.PromptN,
PromptEvalDuration: parseDurationMs(p.Timings.PromptMS),
EvalCount: p.Timings.PredictedN,
EvalDuration: parseDurationMs(p.Timings.PredictedMS),
})
return nil
}
}
}
if !retryNeeded {
return nil // success
}
}
// should never reach here ideally
return fmt.Errorf("max retries exceeded")
}
func cancelCompletion(llm *dynExtServer, resp C.ext_server_resp_t) error {
C.dyn_llama_server_completion_cancel(llm.s, resp.id, &resp)
if resp.id < 0 {
return extServerResponseToErr(resp)
} else {
return nil
}
}
func (llm *dynExtServer) Encode(ctx context.Context, prompt string) ([]int, error) {
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("marshaling encode data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_tokenize(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return nil, extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var encoded TokenizeResponse
if err2 := json.Unmarshal([]byte(C.GoString(json_resp)), &encoded); err2 != nil {
return nil, fmt.Errorf("unmarshal encode response: %w", err2)
}
return encoded.Tokens, err
}
func (llm *dynExtServer) Decode(ctx context.Context, tokens []int) (string, error) {
if len(tokens) == 0 {
return "", nil
}
data, err := json.Marshal(DetokenizeRequest{Tokens: tokens})
if err != nil {
return "", fmt.Errorf("marshaling decode data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_detokenize(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return "", extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var decoded DetokenizeResponse
if err2 := json.Unmarshal([]byte(C.GoString(json_resp)), &decoded); err2 != nil {
return "", fmt.Errorf("unmarshal encode response: %w", err2)
}
return decoded.Content, err
}
func (llm *dynExtServer) Embedding(ctx context.Context, input string) ([]float64, error) {
data, err := json.Marshal(TokenizeRequest{Content: input})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
req := C.CString(string(data))
defer C.free(unsafe.Pointer(req))
var json_resp *C.char
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
C.dyn_llama_server_embedding(llm.s, req, &json_resp, &resp)
if resp.id < 0 {
return nil, extServerResponseToErr(resp)
}
defer C.dyn_llama_server_release_json_resp(llm.s, &json_resp)
var embedding EmbeddingResponse
if err := json.Unmarshal([]byte(C.GoString(json_resp)), &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}
return embedding.Embedding, nil
}
func (llm *dynExtServer) Close() {
C.dyn_llama_server_stop(llm.s)
mutex.Unlock()
}

74
llm/dyn_ext_server.h
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@ -1,74 +0,0 @@
#include <stdlib.h>
#include "ext_server.h"
#ifdef __cplusplus
extern "C" {
#endif
struct dynamic_llama_server {
void *handle;
void (*llama_server_init)(ext_server_params_t *sparams,
ext_server_resp_t *err);
void (*llama_server_start)();
void (*llama_server_stop)();
void (*llama_server_completion)(const char *json_req,
ext_server_resp_t *resp);
void (*llama_server_completion_next_result)(const int task_id,
ext_server_task_result_t *result);
void (*llama_server_completion_cancel)(const int task_id,
ext_server_resp_t *err);
void (*llama_server_release_task_result)(ext_server_task_result_t *result);
void (*llama_server_tokenize)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_detokenize)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_embedding)(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void (*llama_server_release_json_resp)(char **json_resp);
};
void dyn_init(const char *libPath, struct dynamic_llama_server *s,
ext_server_resp_t *err);
// No good way to call C function pointers from Go so inline the indirection
void dyn_llama_server_init(struct dynamic_llama_server s,
ext_server_params_t *sparams,
ext_server_resp_t *err);
void dyn_llama_server_start(struct dynamic_llama_server s);
void dyn_llama_server_stop(struct dynamic_llama_server s);
void dyn_llama_server_completion(struct dynamic_llama_server s,
const char *json_req,
ext_server_resp_t *resp);
void dyn_llama_server_completion_next_result(
struct dynamic_llama_server s, const int task_id,
ext_server_task_result_t *result);
void dyn_llama_server_completion_cancel(struct dynamic_llama_server s,
const int task_id,
ext_server_resp_t *err);
void dyn_llama_server_release_task_result(
struct dynamic_llama_server s, ext_server_task_result_t *result);
void dyn_llama_server_tokenize(struct dynamic_llama_server s,
const char *json_req, char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_detokenize(struct dynamic_llama_server s,
const char *json_req,
char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_embedding(struct dynamic_llama_server s,
const char *json_req, char **json_resp,
ext_server_resp_t *err);
void dyn_llama_server_release_json_resp(struct dynamic_llama_server s,
char **json_resp);
#ifdef __cplusplus
}
#endif

25
llm/ext_server/CMakeLists.txt vendored
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@ -1,21 +1,14 @@
set(TARGET ext_server)
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 ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
add_library(${TARGET} SHARED ext_server.cpp ../llama.cpp/llama.cpp)
else()
add_library(${TARGET} STATIC ext_server.cpp ../llama.cpp/llama.cpp)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
target_compile_features(${TARGET} PRIVATE cxx_std_11)
target_compile_definitions(${TARGET} PUBLIC LLAMA_SERVER_LIBRARY=1)
target_link_libraries(${TARGET} PRIVATE ggml llava common )
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_compile_definitions(${TARGET} PRIVATE SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>)
install(TARGETS ext_server LIBRARY)
if (CUDAToolkit_FOUND)
target_include_directories(${TARGET} PRIVATE ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES})
if (WIN32)
target_link_libraries(${TARGET} PRIVATE nvml)
endif()
endif()

18
llm/ext_server/README.md vendored
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@ -1,18 +0,0 @@
# Extern C Server
This directory contains a thin facade we layer on top of the Llama.cpp server to
expose `extern C` interfaces to access the functionality through direct API
calls in-process. The llama.cpp code uses compile time macros to configure GPU
type along with other settings. During the `go generate ./...` execution, the
build will generate one or more copies of the llama.cpp `extern C` server based
on what GPU libraries are detected to support multiple GPU types as well as CPU
only support. The Ollama go build then embeds these different servers to support
different GPUs and settings at runtime.
If you are making changes to the code in this directory, make sure to disable
caching during your go build to ensure you pick up your changes. A typical
iteration cycle from the top of the source tree looks like:
```
go generate ./... && go build -a .
```

377
llm/ext_server/ext_server.cpp vendored
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@ -1,377 +0,0 @@
#include "ext_server.h"
#include <atomic>
// Necessary evil since the server types are not defined in a header
#include "server.cpp"
// Low level API access to verify GPU access
#if defined(GGML_USE_CUBLAS)
#if defined(GGML_USE_HIPBLAS)
#include <hip/hip_runtime.h>
#include <hipblas/hipblas.h>
#include <hip/hip_fp16.h>
#ifdef __HIP_PLATFORM_AMD__
// for rocblas_initialize()
#include "rocblas/rocblas.h"
#endif // __HIP_PLATFORM_AMD__
#define cudaGetDevice hipGetDevice
#define cudaError_t hipError_t
#define cudaSuccess hipSuccess
#define cudaGetErrorString hipGetErrorString
#else
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cuda_fp16.h>
#endif // defined(GGML_USE_HIPBLAS)
#endif // GGML_USE_CUBLAS
// Expose the llama server as a callable extern "C" API
llama_server_context *llama = NULL;
std::thread ext_server_thread;
bool shutting_down = false;
std::atomic_int recv_counter;
// RAII wrapper for tracking in-flight recv calls
class atomicRecv {
public:
atomicRecv(std::atomic<int> &atomic) : atomic(atomic) {
++this->atomic;
}
~atomicRecv() {
--this->atomic;
}
private:
std::atomic<int> &atomic;
};
void llama_server_init(ext_server_params *sparams, ext_server_resp_t *err) {
recv_counter = 0;
assert(err != NULL && sparams != NULL);
log_set_target(stderr);
if (!sparams->verbose_logging) {
server_verbose = true;
log_disable();
}
LOG_TEE("system info: %s\n", llama_print_system_info());
err->id = 0;
err->msg[0] = '\0';
try {
llama = new llama_server_context;
gpt_params params;
params.n_ctx = sparams->n_ctx;
params.n_batch = sparams->n_batch;
if (sparams->n_threads > 0) {
params.n_threads = sparams->n_threads;
}
params.n_parallel = sparams->n_parallel;
params.rope_freq_base = sparams->rope_freq_base;
params.rope_freq_scale = sparams->rope_freq_scale;
if (sparams->memory_f16) {
params.cache_type_k = "f16";
params.cache_type_v = "f16";
} else {
params.cache_type_k = "f32";
params.cache_type_v = "f32";
}
params.n_gpu_layers = sparams->n_gpu_layers;
params.main_gpu = sparams->main_gpu;
params.use_mlock = sparams->use_mlock;
params.use_mmap = sparams->use_mmap;
params.numa = (ggml_numa_strategy)sparams->numa;
params.embedding = sparams->embedding;
if (sparams->model != NULL) {
params.model = sparams->model;
}
if (sparams->lora_adapters != NULL) {
for (ext_server_lora_adapter *la = sparams->lora_adapters; la != NULL;
la = la->next) {
params.lora_adapter.push_back(std::make_tuple(la->adapter, la->scale));
}
params.use_mmap = false;
}
if (sparams->mmproj != NULL) {
params.mmproj = std::string(sparams->mmproj);
}
#if defined(GGML_USE_CUBLAS)
// Before attempting to init the backend which will assert on error, verify the CUDA/ROCM GPU is accessible
LOG_TEE("Performing pre-initialization of GPU\n");
int id;
cudaError_t cudaErr = cudaGetDevice(&id);
if (cudaErr != cudaSuccess) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unable to init GPU: %s", cudaGetErrorString(cudaErr));
return;
}
#endif
llama_backend_init();
llama_numa_init(params.numa);
if (!llama->load_model(params)) {
// an error occurred that was not thrown
err->id = -1;
snprintf(err->msg, err->msg_len, "error loading model %s", params.model.c_str());
return;
}
llama->initialize();
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len,
"Unknown exception initializing llama server");
}
}
void llama_server_start() {
assert(llama != NULL);
// TODO mutex to protect thread creation
ext_server_thread = std::thread([&]() {
try {
LOG_TEE("llama server main loop starting\n");
ggml_time_init();
llama->queue_tasks.on_new_task(std::bind(
&llama_server_context::process_single_task, llama, std::placeholders::_1));
llama->queue_tasks.on_finish_multitask(std::bind(
&llama_server_context::on_finish_multitask, llama, std::placeholders::_1));
llama->queue_tasks.on_run_slots(std::bind(
&llama_server_context::update_slots, llama));
llama->queue_results.on_multitask_update(std::bind(
&llama_server_queue::update_multitask,
&llama->queue_tasks,
std::placeholders::_1,
std::placeholders::_2,
std::placeholders::_3
));
llama->queue_tasks.start_loop();
} catch (std::exception &e) {
LOG_TEE("caught exception in llama server main loop: %s\n", e.what());
} catch (...) {
LOG_TEE("caught unknown exception in llama server main loop\n");
}
LOG_TEE("\nllama server shutting down\n");
llama_backend_free();
});
}
void llama_server_stop() {
assert(llama != NULL);
// Shutdown any in-flight requests and block incoming requests.
LOG_TEE("\ninitiating shutdown - draining remaining tasks...\n");
shutting_down = true;
while (recv_counter.load() > 0) {
std::this_thread::sleep_for(std::chrono::milliseconds(50));
}
// This may take a while for any pending tasks to drain
// TODO - consider a timeout to cancel tasks if it's taking too long
llama->queue_tasks.terminate();
ext_server_thread.join();
delete llama;
llama = NULL;
LOG_TEE("llama server shutdown complete\n");
shutting_down = false;
}
void llama_server_completion(const char *json_req, ext_server_resp_t *resp) {
assert(llama != NULL && json_req != NULL && resp != NULL);
resp->id = -1;
resp->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
json data = json::parse(json_req);
resp->id = llama->queue_tasks.get_new_id();
llama->queue_results.add_waiting_task_id(resp->id);
llama->request_completion(resp->id, data, false, false, -1);
} catch (std::exception &e) {
snprintf(resp->msg, resp->msg_len, "exception %s", e.what());
} catch (...) {
snprintf(resp->msg, resp->msg_len, "Unknown exception during completion");
}
}
void llama_server_completion_next_result(const int task_id,
ext_server_task_result_t *resp) {
assert(llama != NULL && resp != NULL);
resp->id = -1;
resp->stop = false;
resp->error = false;
resp->json_resp = NULL;
std::string result_json;
try {
atomicRecv ar(recv_counter);
task_result result = llama->queue_results.recv(task_id);
result_json =
result.result_json.dump(-1, ' ', false, json::error_handler_t::replace);
resp->id = result.id;
resp->stop = result.stop;
resp->error = result.error;
if (result.error) {
LOG_TEE("next result cancel on error\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting tak ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (result.stop) {
LOG_TEE("next result cancel on stop\n");
llama->request_cancel(task_id);
LOG_TEE("next result removing waiting task ID: %d\n", task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} else if (shutting_down) {
LOG_TEE("aborting completion due to shutdown %d\n", task_id);
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
resp->stop = true;
}
} catch (std::exception &e) {
resp->error = true;
resp->id = -1;
result_json = "{\"error\":\"exception " + std::string(e.what()) + "\"}";
LOG_TEE("llama server completion exception %s\n", e.what());
} catch (...) {
resp->error = true;
resp->id = -1;
result_json = "{\"error\":\"Unknown exception during completion\"}";
LOG_TEE("llama server completion unknown exception\n");
}
const std::string::size_type size = result_json.size() + 1;
resp->json_resp = new char[size];
snprintf(resp->json_resp, size, "%s", result_json.c_str());
}
void llama_server_release_task_result(ext_server_task_result_t *result) {
if (result == NULL || result->json_resp == NULL) {
return;
}
delete[] result->json_resp;
}
void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err) {
assert(llama != NULL && err != NULL);
err->id = 0;
err->msg[0] = '\0';
try {
llama->request_cancel(task_id);
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len,
"Unknown exception completion cancel in llama server");
}
}
void llama_server_tokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::vector<llama_token> tokens;
if (body.count("content") != 0) {
tokens = llama->tokenize(body["content"], false);
}
const json data = format_tokenizer_response(tokens);
std::string result_json = data.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during tokenize");
}
}
void llama_server_release_json_resp(char **json_resp) {
if (json_resp == NULL || *json_resp == NULL) {
return;
}
delete[] *json_resp;
}
void llama_server_detokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
std::string content;
if (body.count("tokens") != 0) {
const std::vector<llama_token> tokens = body["tokens"];
content = tokens_to_str(llama->ctx, tokens.cbegin(), tokens.cend());
}
const json data = format_detokenized_response(content);
std::string result_json = data.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during detokenize");
}
}
void llama_server_embedding(const char *json_req, char **json_resp,
ext_server_resp_t *err) {
assert(llama != NULL && json_req != NULL && json_resp != NULL && err != NULL);
*json_resp = NULL;
err->id = 0;
err->msg[0] = '\0';
try {
if (shutting_down) {
throw std::runtime_error("server shutting down");
}
const json body = json::parse(json_req);
json prompt;
if (body.count("content") != 0) {
prompt = body["content"];
} else {
prompt = "";
}
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}}, false, true, -1);
atomicRecv ar(recv_counter);
task_result result = llama->queue_results.recv(task_id);
std::string result_json = result.result_json.dump();
const std::string::size_type size = result_json.size() + 1;
*json_resp = new char[size];
snprintf(*json_resp, size, "%s", result_json.c_str());
llama->queue_results.remove_waiting_task_id(task_id);
} catch (std::exception &e) {
err->id = -1;
snprintf(err->msg, err->msg_len, "exception %s", e.what());
} catch (...) {
err->id = -1;
snprintf(err->msg, err->msg_len, "Unknown exception during embedding");
}
}

95
llm/ext_server/ext_server.h vendored
View file

@ -1,95 +0,0 @@
#if defined(LLAMA_SERVER_LIBRARY)
#ifndef LLAMA_SERVER_H
#define LLAMA_SERVER_H
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#include <stdio.h>
int __main(int argc, char **argv);
// This exposes extern C entrypoints into the llama_server
// To enable the server compile with LLAMA_SERVER_LIBRARY
#ifdef __cplusplus
extern "C" {
#endif
typedef struct ext_server_resp {
int id; // < 0 on error
size_t msg_len; // caller must allocate msg and set msg_len
char *msg;
} ext_server_resp_t;
// Allocated and freed by caller
typedef struct ext_server_lora_adapter {
char *adapter;
float scale;
struct ext_server_lora_adapter *next;
} ext_server_lora_adapter_t;
// Allocated and freed by caller
typedef struct ext_server_params {
char *model;
uint32_t n_ctx; // token context window, 0 = from model
uint32_t n_batch; // prompt processing maximum batch size
uint32_t n_threads; // number of threads to use for generation
int32_t n_parallel; // number of parallel sequences to decodewra
float rope_freq_base; // RoPE base frequency, 0 = from model
float rope_freq_scale; // RoPE frequency scaling factor, 0 = from model
bool memory_f16; // use f16 instead of f32 for memory kv
int32_t n_gpu_layers; // number of layers to store in VRAM (-1 - use default)
int32_t main_gpu; // the GPU that is used for scratch and small tensors
bool use_mlock; // force system to keep model in RAM
bool use_mmap; // use mmap if possible
int numa; // attempt optimizations that help on some NUMA systems
bool embedding; // get only sentence embedding
ext_server_lora_adapter_t *lora_adapters;
char *mmproj;
bool verbose_logging; // Enable verbose logging of the server
} ext_server_params_t;
typedef struct ext_server_task_result {
int id;
bool stop;
bool error;
char *json_resp; // null terminated, memory managed by ext_server
} ext_server_task_result_t;
// Initialize the server once per process
// err->id = 0 for success and err->msg[0] = NULL
// err->id != 0 for failure, and err->msg contains error message
void llama_server_init(ext_server_params_t *sparams, ext_server_resp_t *err);
// Run the main loop, called once per init
void llama_server_start();
// Stop the main loop and free up resources allocated in init and start. Init
// must be called again to reuse
void llama_server_stop();
// json_req null terminated string, memory managed by caller
// resp->id >= 0 on success (task ID)
// resp->id < 0 on error, and resp->msg contains error message
void llama_server_completion(const char *json_req, ext_server_resp_t *resp);
// Caller must call llama_server_release_task_result to free resp->json_resp
void llama_server_completion_next_result(const int task_id,
ext_server_task_result_t *result);
void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err);
void llama_server_release_task_result(ext_server_task_result_t *result);
// Caller must call llama_server_releaes_json_resp to free json_resp if err.id <
// 0
void llama_server_tokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_detokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_embedding(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_release_json_resp(char **json_resp);
#ifdef __cplusplus
}
#endif
#endif
#endif // LLAMA_SERVER_LIBRARY

2
llm/ext_server/server.cpp vendored
View file

@ -2768,7 +2768,7 @@ inline void signal_handler(int signal) {
shutdown_handler(signal);
}
int _main(int argc, char **argv)
int main(int argc, char **argv)
{
#if SERVER_VERBOSE != 1
log_disable();

27
llm/generate/gen_common.sh
View file

@ -14,7 +14,7 @@ init_vars() {
LLAMACPP_DIR=../llama.cpp
CMAKE_DEFS=""
CMAKE_TARGETS="--target ext_server"
CMAKE_TARGETS="--target ollama_llama_server"
if echo "${CGO_CFLAGS}" | grep -- '-g' >/dev/null; then
CMAKE_DEFS="-DCMAKE_BUILD_TYPE=RelWithDebInfo -DCMAKE_VERBOSE_MAKEFILE=on -DLLAMA_GPROF=on -DLLAMA_SERVER_VERBOSE=on ${CMAKE_DEFS}"
else
@ -81,26 +81,23 @@ apply_patches() {
build() {
cmake -S ${LLAMACPP_DIR} -B ${BUILD_DIR} ${CMAKE_DEFS}
cmake --build ${BUILD_DIR} ${CMAKE_TARGETS} -j8
mkdir -p ${BUILD_DIR}/lib/
ls ${BUILD_DIR}
g++ -fPIC -g -shared -o ${BUILD_DIR}/lib/libext_server.${LIB_EXT} \
${GCC_ARCH} \
${WHOLE_ARCHIVE} ${BUILD_DIR}/ext_server/libext_server.a ${NO_WHOLE_ARCHIVE} \
${BUILD_DIR}/common/libcommon.a \
${BUILD_DIR}/libllama.a \
-Wl,-rpath,\$ORIGIN \
-lpthread -ldl -lm \
${EXTRA_LIBS}
}
compress_libs() {
compress() {
echo "Compressing payloads to reduce overall binary size..."
pids=""
rm -rf ${BUILD_DIR}/lib/*.${LIB_EXT}*.gz
for lib in ${BUILD_DIR}/lib/*.${LIB_EXT}* ; do
gzip -n --best -f ${lib} &
rm -rf ${BUILD_DIR}/bin/*.gz
for f in ${BUILD_DIR}/bin/* ; do
gzip -n --best -f ${f} &
pids+=" $!"
done
# check for lib directory
if [ -d ${BUILD_DIR}/lib ]; then
for f in ${BUILD_DIR}/lib/* ; do
gzip -n --best -f ${f} &
pids+=" $!"
done
fi
echo
for pid in ${pids}; do
wait $pid

47
llm/generate/gen_darwin.sh
View file

@ -18,21 +18,31 @@ sign() {
fi
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -DCMAKE_SYSTEM_NAME=Darwin"
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.0 -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} -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} -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
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu"
BUILD_DIR="../build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
#
# ~2011 CPU Dynamic library with more capabilities turned on to optimize performance
@ -40,11 +50,11 @@ case "${GOARCH}" in
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
#
# ~2013 CPU Dynamic library
@ -52,20 +62,30 @@ case "${GOARCH}" in
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/cpu_avx2/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
;;
"arm64")
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_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
init_vars
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/darwin/${ARCH}/metal"
BUILD_DIR="../build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
build
sign ${LLAMACPP_DIR}/build/darwin/${ARCH}/metal/lib/libext_server.dylib
compress_libs
sign ${BUILD_DIR}/lib/libext_server.dylib
compress
;;
*)
echo "GOARCH must be set"
@ -75,3 +95,4 @@ case "${GOARCH}" in
esac
cleanup
echo "go generate completed. LLM runners: $(cd ${BUILD_DIR}/..; echo *)"

63
llm/generate/gen_linux.sh
View file

@ -57,16 +57,31 @@ init_vars
git_module_setup
apply_patches
init_vars
if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "static" ]; then
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}_static"
echo "Building static library"
build
fi
# Users building from source can tune the exact flags we pass to cmake for configuring
# llama.cpp, and we'll build only 1 CPU variant in that case as the default.
if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
init_vars
echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building custom CPU"
build
compress_libs
compress
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
@ -83,11 +98,12 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
compress_libs
compress
fi
if [ "${ARCH}" == "x86_64" ]; then
@ -101,10 +117,10 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
compress_libs
compress
fi
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx2" ]; then
@ -114,10 +130,10 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cpu_avx2"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
compress_libs
compress
fi
fi
fi
@ -157,7 +173,7 @@ if [ -d "${CUDA_LIB_DIR}" ]; then
ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_CUDA_F16=off"
fi
CMAKE_DEFS="-DLLAMA_CUBLAS=on -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/cuda${CUDA_VARIANT}"
BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
EXTRA_LIBS="-L${CUDA_LIB_DIR} -lcudart -lcublas -lcublasLt -lcuda"
build
@ -165,20 +181,20 @@ if [ -d "${CUDA_LIB_DIR}" ]; then
#
# TODO - in the future we may shift to packaging these separately and conditionally
# downloading them in the install script.
DEPS="$(ldd ${BUILD_DIR}/lib/libext_server.so )"
DEPS="$(ldd ${BUILD_DIR}/bin/ollama_llama_server )"
for lib in libcudart.so libcublas.so libcublasLt.so ; do
DEP=$(echo "${DEPS}" | grep ${lib} | cut -f1 -d' ' | xargs || true)
if [ -n "${DEP}" -a -e "${CUDA_LIB_DIR}/${DEP}" ]; then
cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/lib/"
cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/bin/"
elif [ -e "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" ]; then
cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/lib/"
cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/bin/"
elif [ -e "${CUDART_LIB_DIR}/${lib}" ]; then
cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/lib/"
cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/bin/"
else
cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/lib/"
cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/bin/"
fi
done
compress_libs
compress
fi
@ -201,23 +217,24 @@ if [ -d "${ROCM_PATH}" ]; then
fi
init_vars
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/${ARCH}/rocm${ROCM_VARIANT}"
BUILD_DIR="../build/linux/${ARCH}/rocm${ROCM_VARIANT}"
EXTRA_LIBS="-L${ROCM_PATH}/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ -Wl,-rpath,\$ORIGIN/../../rocm/ -lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu"
build
# Record the ROCM dependencies
rm -f "${BUILD_DIR}/lib/deps.txt"
touch "${BUILD_DIR}/lib/deps.txt"
for dep in $(ldd "${BUILD_DIR}/lib/libext_server.so" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e rocm -e amdgpu -e libtinfo ); do
echo "${dep}" >> "${BUILD_DIR}/lib/deps.txt"
rm -f "${BUILD_DIR}/bin/deps.txt"
touch "${BUILD_DIR}/bin/deps.txt"
for dep in $(ldd "${BUILD_DIR}/bin/ollama_llama_server" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e rocm -e amdgpu -e libtinfo ); do
echo "${dep}" >> "${BUILD_DIR}/bin/deps.txt"
done
# bomb out if for some reason we didn't get a few deps
if [ $(cat "${BUILD_DIR}/lib/deps.txt" | wc -l ) -lt 8 ] ; then
cat "${BUILD_DIR}/lib/deps.txt"
if [ $(cat "${BUILD_DIR}/bin/deps.txt" | wc -l ) -lt 8 ] ; then
cat "${BUILD_DIR}/bin/deps.txt"
echo "ERROR: deps file short"
exit 1
fi
compress_libs
compress
fi
cleanup
echo "go generate completed. LLM runners: $(cd ${BUILD_DIR}/..; echo *)"

98
llm/generate/gen_windows.ps1
View file

@ -33,7 +33,7 @@ function init_vars {
"-DBUILD_SHARED_LIBS=on",
"-DLLAMA_NATIVE=off"
)
$script:cmakeTargets = @("ext_server")
$script:cmakeTargets = @("ollama_llama_server")
$script:ARCH = "amd64" # arm not yet supported.
if ($env:CGO_CFLAGS -contains "-g") {
$script:cmakeDefs += @("-DCMAKE_VERBOSE_MAKEFILE=on", "-DLLAMA_SERVER_VERBOSE=on", "-DCMAKE_BUILD_TYPE=RelWithDebInfo")
@ -97,16 +97,14 @@ function apply_patches {
}
# Checkout each file
Set-Location -Path ${script:llamacppDir}
foreach ($file in $filePaths) {
git checkout $file
git -C "${script:llamacppDir}" checkout $file
}
}
# Apply each patch
foreach ($patch in $patches) {
Set-Location -Path ${script:llamacppDir}
git apply $patch.FullName
git -C "${script:llamacppDir}" apply $patch.FullName
}
}
@ -115,41 +113,41 @@ function build {
& cmake --version
& cmake -S "${script:llamacppDir}" -B $script:buildDir $script:cmakeDefs
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
write-host "building with: cmake --build $script:buildDir --config $script:config ($script:cmakeTargets | ForEach-Object { "--target", $_ })"
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($LASTEXITCODE)}
}
function install {
rm -ea 0 -recurse -force -path "${script:buildDir}/lib"
md "${script:buildDir}/lib" -ea 0 > $null
cp "${script:buildDir}/bin/${script:config}/ext_server.dll" "${script:buildDir}/lib"
cp "${script:buildDir}/bin/${script:config}/llama.dll" "${script:buildDir}/lib"
# Display the dll dependencies in the build log
if ($script:DUMPBIN -ne $null) {
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/${script:config}/ext_server.dll" | select-string ".dll"
# Rearrange output to be consistent between different generators
if ($null -ne ${script:config} -And (test-path -path "${script:buildDir}/bin/${script:config}" ) ) {
mv -force "${script:buildDir}/bin/${script:config}/*" "${script:buildDir}/bin/"
remove-item "${script:buildDir}/bin/${script:config}"
}
}
function sign {
if ("${env:KEY_CONTAINER}") {
write-host "Signing ${script:buildDir}/lib/*.dll"
foreach ($file in (get-childitem "${script:buildDir}/lib/*.dll")){
& "${script:SignTool}" sign /v /debug /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
write-host "Signing ${script:buildDir}/bin/*.exe ${script:buildDir}/bin/*.dll"
foreach ($file in @(get-childitem "${script:buildDir}/bin/*.exe") + @(get-childitem "${script:buildDir}/bin/*.dll")){
& "${script:SignTool}" sign /v /fd sha256 /t http://timestamp.digicert.com /f "${script:OLLAMA_CERT}" `
/csp "Google Cloud KMS Provider" /kc "${env:KEY_CONTAINER}" $file
if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
}
}
}
function compress_libs {
function compress {
if ($script:GZIP -eq $null) {
write-host "gzip not installed, not compressing files"
return
}
write-host "Compressing binaries..."
$binaries = dir "${script:buildDir}/bin/*.exe"
foreach ($file in $binaries) {
& "$script:GZIP" --best -f $file
}
write-host "Compressing dlls..."
$libs = dir "${script:buildDir}/lib/*.dll"
foreach ($file in $libs) {
$binaries = dir "${script:buildDir}/bin/*.dll"
foreach ($file in $dlls) {
& "$script:GZIP" --best -f $file
}
}
@ -164,14 +162,11 @@ function cleanup {
}
# Checkout each file
Set-Location -Path ${script:llamacppDir}
foreach ($file in $filePaths) {
git checkout $file
git -C "${script:llamacppDir}" checkout $file
}
git -C "${script:llamacppDir}" checkout CMakeLists.txt
}
Set-Location "${script:llamacppDir}/"
git checkout CMakeLists.txt
}
init_vars
@ -179,7 +174,6 @@ git_module_setup
apply_patches
# -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
@ -187,32 +181,46 @@ $script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
if ($null -eq ${env:OLLAMA_SKIP_CPU_GENERATE}) {
# GCC build for direct linking into the Go binary
init_vars
$script:cmakeTargets = @("llama", "ggml")
$script:cmakeDefs = @(
"-G", "MinGW Makefiles"
"-DBUILD_SHARED_LIBS=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
# remaining llama.cpp builds use MSVC
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu"
$script:buildDir="../build/windows/${script:ARCH}/cpu"
write-host "Building LCD CPU"
build
install
sign
compress_libs
compress
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx"
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
write-host "Building AVX CPU"
build
install
sign
compress_libs
compress
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cpu_avx2"
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
write-host "Building AVX2 CPU"
build
install
sign
compress_libs
compress
} else {
write-host "Skipping CPU generation step as requested"
}
@ -225,13 +233,11 @@ if ($null -ne $script:CUDA_LIB_DIR) {
$script:CUDA_VARIANT="_"+$script:CUDA_VERSION
}
init_vars
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:buildDir="../build/windows/${script:ARCH}/cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @("-A", "x64", "-DLLAMA_CUBLAS=ON", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR", "-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}")
write-host "Building CUDA"
build
install
sign
compress_libs
compress
}
if ($null -ne $env:HIP_PATH) {
@ -241,7 +247,7 @@ if ($null -ne $env:HIP_PATH) {
}
init_vars
$script:buildDir="${script:llamacppDir}/build/windows/${script:ARCH}/rocm$script:ROCM_VARIANT"
$script:buildDir="../build/windows/${script:ARCH}/rocm$script:ROCM_VARIANT"
$script:cmakeDefs += @(
"-G", "Ninja",
"-DCMAKE_C_COMPILER=clang.exe",
@ -264,13 +270,13 @@ if ($null -ne $env:HIP_PATH) {
build
# Ninja doesn't prefix with config name
${script:config}=""
install
if ($null -ne $script:DUMPBIN) {
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/${script:config}/ext_server.dll" | select-string ".dll"
& "$script:DUMPBIN" /dependents "${script:buildDir}/bin/ollama_llama_server.exe" | select-string ".dll"
}
sign
compress_libs
compress
}
cleanup
write-host "`ngo generate completed. LLM runners: $(get-childitem -path ${script:SRC_DIR}\llm\llama.cpp\build\windows\${script:ARCH})"
write-host "`ngo generate completed. LLM runners: $(get-childitem -path ${script:SRC_DIR}\llm\build\windows\${script:ARCH})"

2
llm/generate/generate_darwin.go
View file

@ -1,3 +1,3 @@
package generate
//go:generate sh ./gen_darwin.sh
//go:generate bash ./gen_darwin.sh

100
llm/llama.go
View file

@ -1,100 +0,0 @@
package llm
import (
_ "embed"
"fmt"
"time"
"github.com/ollama/ollama/api"
)
const jsonGrammar = `
root ::= object
value ::= object | array | string | number | ("true" | "false" | "null") ws
object ::=
"{" ws (
string ":" ws value
("," ws string ":" ws value)*
)? "}" ws
array ::=
"[" ws (
value
("," ws value)*
)? "]" ws
string ::=
"\"" (
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
# Optional space: by convention, applied in this grammar after literal chars when allowed
ws ::= ([ \t\n] ws)?
`
type ImageData struct {
Data []byte `json:"data"`
ID int `json:"id"`
}
var payloadMissing = fmt.Errorf("expected dynamic library payloads not included in this build of ollama")
type prediction struct {
Content string `json:"content"`
Model string `json:"model"`
Prompt string `json:"prompt"`
Stop bool `json:"stop"`
Timings struct {
PredictedN int `json:"predicted_n"`
PredictedMS float64 `json:"predicted_ms"`
PromptN int `json:"prompt_n"`
PromptMS float64 `json:"prompt_ms"`
}
}
const maxRetries = 3
type PredictOpts struct {
Prompt string
Format string
Images []ImageData
Options api.Options
}
type PredictResult struct {
Content string
Done bool
PromptEvalCount int
PromptEvalDuration time.Duration
EvalCount int
EvalDuration time.Duration
}
type TokenizeRequest struct {
Content string `json:"content"`
}
type TokenizeResponse struct {
Tokens []int `json:"tokens"`
}
type DetokenizeRequest struct {
Tokens []int `json:"tokens"`
}
type DetokenizeResponse struct {
Content string `json:"content"`
}
type EmbeddingRequest struct {
Content string `json:"content"`
}
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}

190
llm/llm.go
View file

@ -1,183 +1,15 @@
package llm
import (
"context"
"fmt"
"log/slog"
"os"
"slices"
"strings"
// #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 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 "llama.h"
import "C"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/gpu"
)
type LLM interface {
Predict(context.Context, PredictOpts, func(PredictResult)) error
Embedding(context.Context, string) ([]float64, error)
Encode(context.Context, string) ([]int, error)
Decode(context.Context, []int) (string, error)
Close()
}
var cpuOnlyFamilies = []string{
"mamba",
}
func New(model string, adapters, projectors []string, opts *api.Options) (LLM, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
f, err := os.Open(model)
if err != nil {
return nil, err
}
defer f.Close()
ggml, _, err := DecodeGGML(f)
if err != nil {
return nil, err
}
if opts.NumCtx > int(ggml.KV().ContextLength()) {
slog.Warn("requested context length is greater than model max context length", "requested", opts.NumCtx, "model", ggml.KV().ContextLength())
opts.NumCtx = int(ggml.KV().ContextLength())
}
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
availableMemory, _ := gpu.CheckVRAM()
info := gpu.GetGPUInfo()
usedMemory := info.MinimumMemory
for _, projector := range projectors {
usedMemory += projectorMemoryRequirements(projector)
// multimodal models require at least 2048 context
opts.NumCtx = max(opts.NumCtx, 2048)
}
// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
kv := 2 * 2 * int64(opts.NumCtx) * int64(ggml.KV().BlockCount()) * int64(ggml.KV().EmbeddingLength()) / int64(ggml.KV().HeadCount()) * int64(ggml.KV().HeadCountKV())
// this amount is the overhead + tensors in memory
// TODO: get this from the llama.cpp's graph calculations instead of
// estimating it's 1/6 * kv_cache_size * num_gqa
graph := int64(ggml.KV().GQA()) * kv / 6
usedMemory += graph
if usedMemory > availableMemory || slices.Contains(cpuOnlyFamilies, ggml.KV().Architecture()) {
info.Library = "cpu"
}
requiredMemory := usedMemory
var layers int
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
layerMemory := ggml.LayerSize(fmt.Sprintf("blk.%d.", i)) + kv/int64(ggml.KV().BlockCount())
requiredMemory += layerMemory
if availableMemory > usedMemory+layerMemory && (opts.NumGPU < 0 || layers < opts.NumGPU) {
usedMemory += layerMemory
layers++
}
}
memOutputLayer := ggml.LayerSize("output.")
requiredMemory += memOutputLayer
// only offload output layer if all repeating layers are offloaded
if layers >= int(ggml.KV().BlockCount()) && availableMemory > usedMemory+memOutputLayer {
usedMemory += memOutputLayer
layers++
}
slog.Info(
"offload to gpu",
"layers", layers,
"required", format.HumanBytes2(requiredMemory),
"used", format.HumanBytes2(usedMemory),
"available", format.HumanBytes2(availableMemory),
"kv", format.HumanBytes2(kv),
"graph", format.HumanBytes2(graph),
)
if opts.NumGPU < 0 && info.Library != "cpu" {
opts.NumGPU = layers
}
return newLlmServer(info, model, adapters, projectors, opts)
}
func projectorMemoryRequirements(filename string) int64 {
file, err := os.Open(filename)
if err != nil {
return 0
}
defer file.Close()
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
prefixes := make(map[string]struct{})
for _, layer := range ggml.Tensors() {
parts := strings.Split(layer.Name, ".")
prefixes[strings.Join(parts[:2], ".")] = struct{}{}
}
var ask int64
for prefix := range prefixes {
ask += ggml.LayerSize(prefix)
}
return ask
}
// Give any native cgo implementations an opportunity to initialize
func Init() error {
return nativeInit()
}
func newLlmServer(gpuInfo gpu.GpuInfo, model string, adapters, projectors []string, opts *api.Options) (LLM, error) {
dynLibs := getDynLibs(gpuInfo)
// Check to see if the user has requested a specific library instead of auto-detecting
demandLib := os.Getenv("OLLAMA_LLM_LIBRARY")
if demandLib != "" {
libPath := availableDynLibs[demandLib]
if libPath == "" {
slog.Info(fmt.Sprintf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib))
} else {
slog.Info(fmt.Sprintf("Loading OLLAMA_LLM_LIBRARY=%s", demandLib))
dynLibs = []string{libPath}
}
}
// We stage into a temp directory, and if we've been idle for a while, it may have been reaped
_, err := os.Stat(dynLibs[0])
if err != nil {
slog.Info(fmt.Sprintf("%s has disappeared, reloading libraries", dynLibs[0]))
err = nativeInit()
if err != nil {
return nil, err
}
}
err2 := fmt.Errorf("unable to locate suitable llm library")
for _, dynLib := range dynLibs {
srv, err := newDynExtServer(dynLib, model, adapters, projectors, opts)
if err == nil {
return srv, nil
}
slog.Warn(fmt.Sprintf("Failed to load dynamic library %s %s", dynLib, err))
err2 = err
}
return nil, err2
// SystemInfo is an unused example of calling llama.cpp functions using CGo
func SystemInfo() string {
return C.GoString(C.llama_print_system_info())
}

2
llm/payload_linux.go → llm/llm_darwin_amd64.go
View file

@ -4,5 +4,5 @@ import (
"embed"
)
//go:embed llama.cpp/build/linux/*/*/lib/*
//go:embed build/darwin/x86_64/*/bin/*
var libEmbed embed.FS

2
llm/payload_windows.go → llm/llm_darwin_arm64.go
View file

@ -4,5 +4,5 @@ import (
"embed"
)
//go:embed llama.cpp/build/windows/*/*/lib/*.dll*
//go:embed build/darwin/arm64/*/bin/*
var libEmbed embed.FS

6
llm/llm_linux.go Normal file
View file

@ -0,0 +1,6 @@
package llm
import "embed"
//go:embed build/linux/*/*/bin/*
var libEmbed embed.FS

6
llm/llm_windows.go Normal file
View file

@ -0,0 +1,6 @@
package llm
import "embed"
//go:embed build/windows/*/*/bin/*
var libEmbed embed.FS

211
llm/payload.go Normal file
View file

@ -0,0 +1,211 @@
package llm
import (
"compress/gzip"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"strings"
"golang.org/x/exp/slices"
"golang.org/x/sync/errgroup"
"github.com/ollama/ollama/gpu"
)
var errPayloadMissing = fmt.Errorf("expected payloads not included in this build of ollama")
func Init() error {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
return err
}
slog.Info("extracting embedded files", "dir", payloadsDir)
binGlob := "build/*/*/*/bin/*"
// extract server libraries
err = extractFiles(payloadsDir, binGlob)
if err != nil {
return fmt.Errorf("extract binaries: %v", err)
}
var variants []string
for v := range availableServers() {
variants = append(variants, v)
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
slog.Debug("Override detection logic by setting OLLAMA_LLM_LIBRARY")
return nil
}
// binary names may contain an optional variant separated by '_'
// For example, "ollama_rocm_v6" and "ollama_rocm_v5" or "ollama_cpu" and "ollama_cpu_avx2"
// Any library without a variant is the lowest common denominator
func availableServers() map[string]string {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
slog.Error("payload lookup error", "error", err)
return nil
}
// glob payloadsDir for files that start with ollama_
pattern := filepath.Join(payloadsDir, "*")
files, err := filepath.Glob(pattern)
if err != nil {
slog.Debug("could not glob", "pattern", pattern, "error", err)
return nil
}
servers := make(map[string]string)
for _, file := range files {
slog.Debug("availableServers : found", "file", file)
servers[filepath.Base(file)] = file
}
return servers
}
// serversForGpu returns a list of compatible servers give the provided GPU
// info, ordered by performance. assumes Init() has been called
// TODO - switch to metadata based mapping
func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := availableServers()
requested := info.Library
if info.Variant != "" {
requested += "_" + info.Variant
}
servers := []string{}
// exact match first
for a := range availableServers {
if a == requested {
servers = []string{a}
if a == "metal" {
return servers
}
break
}
}
alt := []string{}
// Then for GPUs load alternates and sort the list for consistent load ordering
if info.Library != "cpu" {
for a := range availableServers {
if info.Library == strings.Split(a, "_")[0] && a != requested {
alt = append(alt, a)
}
}
slices.Sort(alt)
servers = append(servers, alt...)
}
// 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")
}
}
if len(servers) == 0 {
servers = []string{"cpu"}
}
return servers
}
// extract extracts the embedded files to the target directory
func extractFiles(targetDir string, glob string) error {
files, err := fs.Glob(libEmbed, glob)
if err != nil || len(files) == 0 {
return errPayloadMissing
}
if err := os.MkdirAll(targetDir, 0o755); err != nil {
return fmt.Errorf("extractFiles could not mkdir %s: %v", targetDir, err)
}
g := new(errgroup.Group)
// build/$OS/$GOARCH/$VARIANT/{bin,lib}/$FILE
for _, file := range files {
filename := file
variant := filepath.Base(filepath.Dir(filepath.Dir(filename)))
slog.Debug("extracting", "variant", variant, "file", filename)
g.Go(func() error {
srcf, err := libEmbed.Open(filename)
if err != nil {
return err
}
defer srcf.Close()
src := io.Reader(srcf)
if strings.HasSuffix(filename, ".gz") {
src, err = gzip.NewReader(src)
if err != nil {
return fmt.Errorf("decompress payload %s: %v", filename, err)
}
filename = strings.TrimSuffix(filename, ".gz")
}
variantDir := filepath.Join(targetDir, variant)
if err := os.MkdirAll(variantDir, 0o755); err != nil {
return fmt.Errorf("extractFiles could not mkdir %s: %v", variantDir, err)
}
base := filepath.Base(filename)
destFilename := filepath.Join(variantDir, base)
_, err = os.Stat(destFilename)
switch {
case errors.Is(err, os.ErrNotExist):
destFile, err := os.OpenFile(destFilename, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("write payload %s: %v", filename, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, src); err != nil {
return fmt.Errorf("copy payload %s: %v", filename, err)
}
case err != nil:
return fmt.Errorf("stat payload %s: %v", filename, err)
}
return nil
})
}
err = g.Wait()
if err != nil {
// If we fail to extract, the payload dir is unusable, so cleanup whatever we extracted
gpu.Cleanup()
return err
}
return nil
}

233
llm/payload_common.go
View file

@ -1,233 +0,0 @@
package llm
import (
"compress/gzip"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"runtime"
"strings"
"sync"
"golang.org/x/exp/slices"
"golang.org/x/sync/errgroup"
"github.com/ollama/ollama/gpu"
)
// Libraries names may contain an optional variant separated by '_'
// For example, "rocm_v6" and "rocm_v5" or "cpu" and "cpu_avx2"
// Any library without a variant is the lowest common denominator
var availableDynLibs = map[string]string{}
const pathComponentCount = 7
// getDynLibs returns an ordered list of LLM libraries to try, starting with the best
func getDynLibs(gpuInfo gpu.GpuInfo) []string {
// Short circuit if we know we're using the default built-in (darwin only)
if gpuInfo.Library == "default" {
return []string{"default"}
}
// TODO - temporary until we have multiple CPU variations for Darwin
// Short circuit on darwin with metal only
if len(availableDynLibs) == 1 {
if _, onlyMetal := availableDynLibs["metal"]; onlyMetal {
return []string{availableDynLibs["metal"]}
}
}
exactMatch := ""
dynLibs := []string{}
altDynLibs := []string{}
requested := gpuInfo.Library
if gpuInfo.Variant != "" {
requested += "_" + gpuInfo.Variant
}
// Try to find an exact match
for cmp := range availableDynLibs {
if requested == cmp {
exactMatch = cmp
dynLibs = []string{availableDynLibs[cmp]}
break
}
}
// Then for GPUs load alternates and sort the list for consistent load ordering
if gpuInfo.Library != "cpu" {
for cmp := range availableDynLibs {
if gpuInfo.Library == strings.Split(cmp, "_")[0] && cmp != exactMatch {
altDynLibs = append(altDynLibs, cmp)
}
}
slices.Sort(altDynLibs)
for _, altDynLib := range altDynLibs {
dynLibs = append(dynLibs, availableDynLibs[altDynLib])
}
}
// Load up the best CPU variant if not primary requested
if gpuInfo.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 availableDynLibs {
if cmp == "cpu_"+variant {
dynLibs = append(dynLibs, availableDynLibs[cmp])
break
}
}
} else {
dynLibs = append(dynLibs, availableDynLibs["cpu"])
}
}
// Finally, if we didn't find any matches, LCD CPU FTW
if len(dynLibs) == 0 {
dynLibs = []string{availableDynLibs["cpu"]}
}
slog.Debug(fmt.Sprintf("ordered list of LLM libraries to try %v", dynLibs))
return dynLibs
}
func rocmDynLibPresent() bool {
for dynLibName := range availableDynLibs {
if strings.HasPrefix(dynLibName, "rocm") {
return true
}
}
return false
}
func nativeInit() error {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
return err
}
slog.Info(fmt.Sprintf("Extracting dynamic libraries to %s ...", payloadsDir))
libs, err := extractDynamicLibs(payloadsDir, "llama.cpp/build/*/*/*/lib/*")
if err != nil {
if errors.Is(err, payloadMissing) {
slog.Info(fmt.Sprintf("%s", payloadMissing))
return nil
}
return err
}
for _, lib := range libs {
// The last dir component is the variant name
variant := filepath.Base(filepath.Dir(lib))
availableDynLibs[variant] = lib
}
if err := verifyDriverAccess(); err != nil {
return err
}
// Report which dynamic libraries we have loaded to assist troubleshooting
variants := make([]string, len(availableDynLibs))
i := 0
for variant := range availableDynLibs {
variants[i] = variant
i++
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
slog.Debug("Override detection logic by setting OLLAMA_LLM_LIBRARY")
return nil
}
func extractDynamicLibs(payloadsDir, glob string) ([]string, error) {
files, err := fs.Glob(libEmbed, glob)
if err != nil || len(files) == 0 {
return nil, payloadMissing
}
var mu sync.Mutex
var libs []string
var g errgroup.Group
for _, file := range files {
pathComps := strings.Split(file, "/")
if len(pathComps) != pathComponentCount {
slog.Error(fmt.Sprintf("unexpected payload components: %v", pathComps))
continue
}
file := file
g.Go(func() error {
// llama.cpp/build/$OS/$GOARCH/$VARIANT/lib/$LIBRARY
// Include the variant in the path to avoid conflicts between multiple server libs
targetDir := filepath.Join(payloadsDir, pathComps[pathComponentCount-3])
srcFile, err := libEmbed.Open(file)
if err != nil {
return fmt.Errorf("read payload %s: %v", file, err)
}
defer srcFile.Close()
if err := os.MkdirAll(targetDir, 0o755); err != nil {
return fmt.Errorf("create payload lib dir %s: %v", payloadsDir, err)
}
src := io.Reader(srcFile)
filename := file
if strings.HasSuffix(file, ".gz") {
src, err = gzip.NewReader(src)
if err != nil {
return fmt.Errorf("decompress payload %s: %v", file, err)
}
filename = strings.TrimSuffix(filename, ".gz")
}
destFile := filepath.Join(targetDir, filepath.Base(filename))
if strings.Contains(destFile, "server") {
mu.Lock()
libs = append(libs, destFile)
mu.Unlock()
}
destFp, err := os.OpenFile(destFile, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
return fmt.Errorf("write payload %s: %v", file, err)
}
defer destFp.Close()
if _, err := io.Copy(destFp, src); err != nil {
return fmt.Errorf("copy payload %s: %v", file, err)
}
return nil
})
}
err = g.Wait()
if err != nil {
// If we fail to extract, the payload dir is unusable, so cleanup whatever we extracted
gpu.Cleanup()
return nil, err
}
return libs, nil
}
func verifyDriverAccess() error {
if runtime.GOOS != "linux" {
return nil
}
// Only check ROCm access if we have the dynamic lib loaded
if rocmDynLibPresent() {
// Verify we have permissions - either running as root, or we have group access to the driver
fd, err := os.OpenFile("/dev/kfd", os.O_RDWR, 0666)
if err != nil {
if errors.Is(err, fs.ErrPermission) {
return fmt.Errorf("Radeon card detected, but permissions not set up properly. Either run ollama as root, or add you user account to the render group.")
} else if errors.Is(err, fs.ErrNotExist) {
// expected behavior without a radeon card
return nil
}
return fmt.Errorf("failed to check permission on /dev/kfd: %w", err)
}
fd.Close()
}
return nil
}

8
llm/payload_darwin_amd64.go
View file

@ -1,8 +0,0 @@
package llm
import (
"embed"
)
//go:embed llama.cpp/build/darwin/x86_64/*/lib/*.dylib*
var libEmbed embed.FS

8
llm/payload_darwin_arm64.go
View file

@ -1,8 +0,0 @@
package llm
import (
"embed"
)
//go:embed llama.cpp/ggml-metal.metal llama.cpp/build/darwin/arm64/*/lib/*.dylib*
var libEmbed embed.FS

58
llm/payload_test.go
View file

@ -1,58 +0,0 @@
package llm
import (
"testing"
"github.com/ollama/ollama/gpu"
"github.com/stretchr/testify/assert"
)
func TestGetDynLibs(t *testing.T) {
availableDynLibs = map[string]string{
"cpu": "X_cpu",
}
assert.Equal(t, false, rocmDynLibPresent())
res := getDynLibs(gpu.GpuInfo{Library: "cpu"})
assert.Len(t, res, 1)
assert.Equal(t, availableDynLibs["cpu"], res[0])
variant := gpu.GetCPUVariant()
if variant != "" {
variant = "_" + variant
}
availableDynLibs = map[string]string{
"rocm_v5": "X_rocm_v5",
"rocm_v6": "X_rocm_v6",
"cpu" + variant: "X_cpu",
}
assert.Equal(t, true, rocmDynLibPresent())
res = getDynLibs(gpu.GpuInfo{Library: "rocm"})
assert.Len(t, res, 3)
assert.Equal(t, availableDynLibs["rocm_v5"], res[0])
assert.Equal(t, availableDynLibs["rocm_v6"], res[1])
assert.Equal(t, availableDynLibs["cpu"+variant], res[2])
res = getDynLibs(gpu.GpuInfo{Library: "rocm", Variant: "v6"})
assert.Len(t, res, 3)
assert.Equal(t, availableDynLibs["rocm_v6"], res[0])
assert.Equal(t, availableDynLibs["rocm_v5"], res[1])
assert.Equal(t, availableDynLibs["cpu"+variant], res[2])
res = getDynLibs(gpu.GpuInfo{Library: "cuda"})
assert.Len(t, res, 1)
assert.Equal(t, availableDynLibs["cpu"+variant], res[0])
res = getDynLibs(gpu.GpuInfo{Library: "default"})
assert.Len(t, res, 1)
assert.Equal(t, "default", res[0])
availableDynLibs = map[string]string{
"rocm": "X_rocm_v5",
"cpu" + variant: "X_cpu",
}
assert.Equal(t, true, rocmDynLibPresent())
res = getDynLibs(gpu.GpuInfo{Library: "rocm", Variant: "v6"})
assert.Len(t, res, 2)
assert.Equal(t, availableDynLibs["rocm"], res[0])
assert.Equal(t, availableDynLibs["cpu"+variant], res[1])
}

854
llm/server.go Normal file
View file

@ -0,0 +1,854 @@
package llm
import (
"bufio"
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"log"
"log/slog"
"math/rand"
"net"
"net/http"
"os"
"os/exec"
"path/filepath"
"runtime"
"slices"
"strconv"
"strings"
"time"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/gpu"
)
// LlamaServer is an instance of the llama.cpp server
type LlamaServer struct {
port int
cmd *exec.Cmd
done chan error // Channel to signal when the process exits
status *StatusWriter
options *api.Options
}
var cpuOnlyFamilies = []string{
"mamba",
}
func NewLlamaServer(model string, adapters, projectors []string, opts *api.Options) (*LlamaServer, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
f, err := os.Open(model)
if err != nil {
return nil, err
}
defer f.Close()
ggml, _, err := DecodeGGML(f)
if err != nil {
return nil, err
}
if opts.NumCtx > int(ggml.KV().ContextLength()) {
slog.Warn("requested context length is greater than model max context length", "requested", opts.NumCtx, "model", ggml.KV().ContextLength())
opts.NumCtx = int(ggml.KV().ContextLength())
}
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
availableMemory, _ := gpu.CheckVRAM()
info := gpu.GetGPUInfo()
usedMemory := info.MinimumMemory
for _, projector := range projectors {
usedMemory += projectorMemoryRequirements(projector)
// multimodal models require at least 2048 context
opts.NumCtx = max(opts.NumCtx, 2048)
}
// fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv
kv := 2 * 2 * int64(opts.NumCtx) * int64(ggml.KV().BlockCount()) * int64(ggml.KV().EmbeddingLength()) / int64(ggml.KV().HeadCount()) * int64(ggml.KV().HeadCountKV())
// this amount is the overhead + tensors in memory
// TODO: get this from the llama.cpp's graph calculations instead of
// estimating it's 1/6 * kv_cache_size * num_gqa
graph := int64(ggml.KV().GQA()) * kv / 6
usedMemory += graph
if usedMemory > availableMemory || slices.Contains(cpuOnlyFamilies, ggml.KV().Architecture()) {
info.Library = "cpu"
}
requiredMemory := usedMemory
var layers int
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
layerMemory := ggml.LayerSize(fmt.Sprintf("blk.%d.", i)) + kv/int64(ggml.KV().BlockCount())
requiredMemory += layerMemory
if availableMemory > usedMemory+layerMemory && (opts.NumGPU < 0 || layers < opts.NumGPU) {
usedMemory += layerMemory
layers++
}
}
memOutputLayer := ggml.LayerSize("output.")
requiredMemory += memOutputLayer
// only offload output layer if all repeating layers are offloaded
if layers >= int(ggml.KV().BlockCount()) && availableMemory > usedMemory+memOutputLayer {
usedMemory += memOutputLayer
layers++
}
slog.Info(
"offload to gpu",
"layers", layers,
"required", format.HumanBytes2(requiredMemory),
"used", format.HumanBytes2(usedMemory),
"available", format.HumanBytes2(availableMemory),
"kv", format.HumanBytes2(kv),
"graph", format.HumanBytes2(graph),
)
if opts.NumGPU < 0 && info.Library != "cpu" {
opts.NumGPU = layers
}
if len(adapters) > 1 {
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
}
availableServers := availableServers()
servers := serversForGpu(info)
demandLib := os.Getenv("OLLAMA_LLM_LIBRARY")
if demandLib != "" {
serverPath := availableServers[demandLib]
if serverPath == "" {
slog.Info(fmt.Sprintf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib))
} else {
slog.Info("user override", "OLLAMA_LLM_LIBRARY", demandLib, "path", serverPath)
servers = []string{demandLib}
}
}
if len(servers) == 0 {
return nil, fmt.Errorf("no servers found for %v", info)
}
params := []string{
"--model", model,
"--ctx-size", fmt.Sprintf("%d", opts.NumCtx),
"--batch-size", fmt.Sprintf("%d", opts.NumBatch),
"--embedding",
}
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
params = append(params, "--log-format", "json")
} else {
params = append(params, "--log-disable")
}
if opts.NumGPU > 0 {
params = append(params, "--n-gpu-layers", fmt.Sprintf("%d", opts.NumGPU))
}
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
params = append(params, "--verbose")
}
if opts.MainGPU > 0 {
params = append(params, "--main-gpu", fmt.Sprintf("%d", opts.MainGPU))
}
if opts.RopeFrequencyBase > 0 {
params = append(params, "--rope-freq-base", fmt.Sprintf("%f", opts.RopeFrequencyBase))
}
if opts.RopeFrequencyScale > 0 {
params = append(params, "--rope-freq-scale", fmt.Sprintf("%f", opts.RopeFrequencyScale))
}
if len(adapters) > 0 {
// TODO: applying multiple adapters is not supported by the llama.cpp server yet
params = append(params, "--lora", adapters[0])
}
if len(projectors) > 0 {
// TODO: applying multiple projectors is not supported by the llama.cpp server yet
params = append(params, "--mmproj", projectors[0])
}
if opts.NumThread > 0 {
params = append(params, "--threads", fmt.Sprintf("%d", opts.NumThread))
}
if !opts.F16KV {
params = append(params, "--memory-f32")
}
if opts.UseMLock {
params = append(params, "--mlock")
}
if !opts.UseMMap {
params = append(params, "--no-mmap")
}
if opts.UseNUMA {
params = append(params, "--numa")
}
// Loop through potential servers
var finalErr error
for i := 0; i < len(servers); i++ {
dir := availableServers[servers[i]]
// Find an availableServers port, retry on each iterration in case the failure was a port conflict race
port := 0
if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
var l *net.TCPListener
if l, err = net.ListenTCP("tcp", a); err == nil {
port = l.Addr().(*net.TCPAddr).Port
l.Close()
}
}
if port == 0 {
slog.Debug("ResolveTCPAddr failed ", "error", err)
port = rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range
}
finalParams := append(params, "--port", strconv.Itoa(port))
pathEnv := "LD_LIBRARY_PATH"
if runtime.GOOS == "windows" {
pathEnv = "PATH"
}
// append 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
// This will favor system libraries over our bundled library dependencies
libraryPaths = append(filepath.SplitList(libraryPath), libraryPaths...)
}
server := filepath.Join(dir, "ollama_llama_server")
if runtime.GOOS == "windows" {
server = server + ".exe"
}
s := &LlamaServer{
port: port,
cmd: exec.Command(server, finalParams...),
status: NewStatusWriter(os.Stderr),
options: opts,
}
libEnv := fmt.Sprintf("%s=%s", pathEnv, strings.Join(libraryPaths, string(filepath.ListSeparator)))
slog.Debug(libEnv)
s.cmd.Env = append(os.Environ(), libEnv)
s.cmd.Stdout = os.Stdout
s.cmd.Stderr = s.status
slog.Info("starting llama server", "cmd", s.cmd.String())
if err = s.cmd.Start(); err != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
err = fmt.Errorf("error starting the external llama server: %v %s", err, msg)
finalErr = err
continue
}
// reap subprocess when it exits
go func() {
// Exit status managed via getServerStatus
_ = s.cmd.Wait()
}()
if err = s.waitUntilRunning(); err != nil {
slog.Error("error starting llama server", "server", servers[i], "error", err)
s.Close()
finalErr = err
continue
}
return s, nil
}
slog.Error("unable to load any llama server", "error", finalErr)
return nil, finalErr
}
func projectorMemoryRequirements(filename string) int64 {
file, err := os.Open(filename)
if err != nil {
return 0
}
defer file.Close()
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
prefixes := make(map[string]struct{})
for _, layer := range ggml.Tensors() {
parts := strings.Split(layer.Name, ".")
prefixes[strings.Join(parts[:2], ".")] = struct{}{}
}
var ask int64
for prefix := range prefixes {
ask += ggml.LayerSize(prefix)
}
return ask
}
type ServerStatus int
const ( // iota is reset to 0
ServerStatusReady ServerStatus = iota
ServerStatusNoSlotsAvaialble
ServerStatusLoadingModel
ServerStatusNotResponding
ServerStatusError
)
type ServerStatusResp struct {
Status string `json:"status"`
SlotsIdle int `json:"slots_idle"`
SlotsProcessing int `json:"slots_processing"`
Error string `json:"error"`
}
func (s *LlamaServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
// Fail fast if its exited
if s.cmd.ProcessState != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return ServerStatusError, fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
}
req, err := http.NewRequestWithContext(ctx, http.MethodGet, fmt.Sprintf("http://127.0.0.1:%d/health", s.port), nil)
if err != nil {
return ServerStatusError, fmt.Errorf("error creating GET request: %v", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
if errors.Is(err, context.DeadlineExceeded) {
return ServerStatusNotResponding, fmt.Errorf("server not responding")
}
return ServerStatusError, fmt.Errorf("health resp: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return ServerStatusError, fmt.Errorf("read health request: %w", err)
}
var status ServerStatusResp
if err := json.Unmarshal(body, &status); err != nil {
return ServerStatusError, fmt.Errorf("health unmarshal encode response: %w", err)
}
switch status.Status {
case "ok":
return ServerStatusReady, nil
case "no slot available":
return ServerStatusNoSlotsAvaialble, nil
case "loading model":
return ServerStatusLoadingModel, nil
default:
return ServerStatusError, fmt.Errorf("server error: %+v", status)
}
}
func (s *LlamaServer) Ping(ctx context.Context) error {
_, err := s.getServerStatus(ctx)
if err != nil {
slog.Debug("server unhealthy", "error", err)
return err
}
return nil
}
func (s *LlamaServer) waitUntilRunning() error {
start := time.Now()
expiresAt := time.Now().Add(3 * time.Minute) // be generous with timeout, large models can take a while to load
ticker := time.NewTicker(50 * time.Millisecond)
defer ticker.Stop()
slog.Info("waiting for llama runner to start responding")
var lastStatus ServerStatus = -1
for {
select {
case err := <-s.done:
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("llama runner process has terminated: %v %s", err, msg)
case <-ticker.C:
if time.Now().After(expiresAt) {
// timeout
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("timed out waiting for llama runner to start: %s", msg)
}
if s.cmd.ProcessState != nil {
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
}
ctx, cancel := context.WithTimeout(context.Background(), 200*time.Millisecond)
defer cancel()
status, err := s.getServerStatus(ctx)
if err != nil && lastStatus != status {
slog.Debug("server not yet available", "error", err)
lastStatus = status
continue
}
switch status {
case ServerStatusLoadingModel:
// TODO - this state never seems to happen with the current server.cpp code (bug?)
// it doesn't respond to the health endpoint until after the model is loaded
slog.Debug("loading model")
case ServerStatusReady:
slog.Debug(fmt.Sprintf("llama runner started in %f seconds", time.Since(start).Seconds()))
return nil
}
}
}
}
const jsonGrammar = `
root ::= object
value ::= object | array | string | number | ("true" | "false" | "null") ws
object ::=
"{" ws (
string ":" ws value
("," ws string ":" ws value)*
)? "}" ws
array ::=
"[" ws (
value
("," ws value)*
)? "]" ws
string ::=
"\"" (
[^"\\] |
"\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes
)* "\"" ws
number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
# Optional space: by convention, applied in this grammar after literal chars when allowed
ws ::= ([ \t\n] ws)?
`
const maxBufferSize = 512 * format.KiloByte
const maxRetries = 3
type ImageData struct {
Data []byte `json:"data"`
ID int `json:"id"`
}
type completion struct {
Content string `json:"content"`
Model string `json:"model"`
Prompt string `json:"prompt"`
Stop bool `json:"stop"`
Timings struct {
PredictedN int `json:"predicted_n"`
PredictedMS float64 `json:"predicted_ms"`
PromptN int `json:"prompt_n"`
PromptMS float64 `json:"prompt_ms"`
}
}
type CompletionRequest struct {
Prompt string
Format string
Images []ImageData
Options api.Options
}
type CompletionResponse struct {
Content string
Done bool
PromptEvalCount int
PromptEvalDuration time.Duration
EvalCount int
EvalDuration time.Duration
}
func (s *LlamaServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
request := map[string]any{
"prompt": req.Prompt,
"stream": true,
"n_predict": req.Options.NumPredict,
"n_keep": req.Options.NumKeep,
"main_gpu": req.Options.MainGPU,
"temperature": req.Options.Temperature,
"top_k": req.Options.TopK,
"top_p": req.Options.TopP,
"tfs_z": req.Options.TFSZ,
"typical_p": req.Options.TypicalP,
"repeat_last_n": req.Options.RepeatLastN,
"repeat_penalty": req.Options.RepeatPenalty,
"presence_penalty": req.Options.PresencePenalty,
"frequency_penalty": req.Options.FrequencyPenalty,
"mirostat": req.Options.Mirostat,
"mirostat_tau": req.Options.MirostatTau,
"mirostat_eta": req.Options.MirostatEta,
"penalize_nl": req.Options.PenalizeNewline,
"seed": req.Options.Seed,
"stop": req.Options.Stop,
"image_data": req.Images,
"cache_prompt": true,
}
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return err
} else if status != ServerStatusReady {
return fmt.Errorf("unexpected server status: %d", status)
}
if req.Format == "json" {
request["grammar"] = jsonGrammar
if !strings.Contains(strings.ToLower(req.Prompt), "json") {
slog.Warn("Prompt does not specify that the LLM should response in JSON, but JSON format is expected. For best results specify that JSON is expected in the system prompt.")
}
}
retryDelay := 100 * time.Microsecond
for retries := 0; retries < maxRetries; retries++ {
if retries > 0 {
time.Sleep(retryDelay) // wait before retrying
retryDelay *= 2 // exponential backoff
}
// Handling JSON marshaling with special characters unescaped.
buffer := &bytes.Buffer{}
enc := json.NewEncoder(buffer)
enc.SetEscapeHTML(false)
if err := enc.Encode(request); err != nil {
return fmt.Errorf("failed to marshal data: %v", err)
}
endpoint := fmt.Sprintf("http://127.0.0.1:%d/completion", s.port)
req, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, buffer)
if err != nil {
return fmt.Errorf("error creating POST request: %v", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return fmt.Errorf("POST predict: %v", err)
}
defer resp.Body.Close()
if resp.StatusCode >= 400 {
bodyBytes, err := io.ReadAll(resp.Body)
if err != nil {
return fmt.Errorf("failed reading llm error response: %w", err)
}
log.Printf("llm predict error: %s", bodyBytes)
return fmt.Errorf("%s", bodyBytes)
}
scanner := bufio.NewScanner(resp.Body)
buf := make([]byte, 0, maxBufferSize)
scanner.Buffer(buf, maxBufferSize)
retryNeeded := false
// keep track of the last token generated, this is used to abort if the model starts looping
var lastToken string
var tokenRepeat int
for scanner.Scan() {
select {
case <-ctx.Done():
// This handles the request cancellation
return ctx.Err()
default:
line := scanner.Bytes()
if len(line) == 0 {
continue
}
// try again on slot unavailable
if bytes.Contains(line, []byte("slot unavailable")) {
retryNeeded = true
break
}
evt, ok := bytes.CutPrefix(line, []byte("data: "))
if !ok {
return fmt.Errorf("error parsing llm response stream: %s", line)
}
var c completion
if err := json.Unmarshal(evt, &c); err != nil {
return fmt.Errorf("error unmarshaling llm prediction response: %v", err)
}
switch {
case strings.TrimSpace(c.Content) == lastToken:
tokenRepeat++
default:
lastToken = strings.TrimSpace(c.Content)
tokenRepeat = 0
}
// 30 picked as an arbitrary max token repeat limit, modify as needed
if tokenRepeat > 30 {
slog.Debug("prediction aborted, token repeat limit reached")
return ctx.Err()
}
if c.Content != "" {
fn(CompletionResponse{
Content: c.Content,
})
}
if c.Stop {
fn(CompletionResponse{
Done: true,
PromptEvalCount: c.Timings.PromptN,
PromptEvalDuration: parseDurationMs(c.Timings.PromptMS),
EvalCount: c.Timings.PredictedN,
EvalDuration: parseDurationMs(c.Timings.PredictedMS),
})
return nil
}
}
}
if err := scanner.Err(); err != nil {
if strings.Contains(err.Error(), "unexpected EOF") {
s.Close()
msg := ""
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
return fmt.Errorf("an unknown error was encountered while running the model %s", msg)
}
return fmt.Errorf("error reading llm response: %v", err)
}
if !retryNeeded {
return nil // success
}
}
// should never reach here ideally
return fmt.Errorf("max retries exceeded")
}
type EmbeddingRequest struct {
Content string `json:"content"`
}
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}
func (s *LlamaServer) Embedding(ctx context.Context, prompt string) ([]float64, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return nil, err
} else if status != ServerStatusReady {
return nil, fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/embedding", s.port), bytes.NewBuffer(data))
if err != nil {
return nil, fmt.Errorf("error creating embed request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("do embedding request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("error reading embed response: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm encode error: %s", body)
return nil, fmt.Errorf("%s", body)
}
var embedding EmbeddingResponse
if err := json.Unmarshal(body, &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}
return embedding.Embedding, nil
}
type TokenizeRequest struct {
Content string `json:"content"`
}
type TokenizeResponse struct {
Tokens []int `json:"tokens"`
}
func (s *LlamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return nil, err
} else if status != ServerStatusReady {
return nil, fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(TokenizeRequest{Content: content})
if err != nil {
return nil, fmt.Errorf("marshaling encode data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/tokenize", s.port), bytes.NewBuffer(data))
if err != nil {
return nil, fmt.Errorf("encode request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("do encode request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("read encode request: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm encode error: %s", body)
return nil, fmt.Errorf("%s", body)
}
var encoded TokenizeResponse
if err := json.Unmarshal(body, &encoded); err != nil {
return nil, fmt.Errorf("unmarshal encode response: %w", err)
}
return encoded.Tokens, nil
}
type DetokenizeRequest struct {
Tokens []int `json:"tokens"`
}
type DetokenizeResponse struct {
Content string `json:"content"`
}
func (s *LlamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
// Make sure the server is ready
status, err := s.getServerStatus(ctx)
if err != nil {
return "", err
} else if status != ServerStatusReady {
return "", fmt.Errorf("unexpected server status: %d", status)
}
data, err := json.Marshal(DetokenizeRequest{Tokens: tokens})
if err != nil {
return "", fmt.Errorf("marshaling decode data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/detokenize", s.port), bytes.NewBuffer(data))
if err != nil {
return "", fmt.Errorf("decode request: %w", err)
}
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return "", fmt.Errorf("do decode request: %w", err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return "", fmt.Errorf("read decode request: %w", err)
}
if resp.StatusCode >= 400 {
log.Printf("llm decode error: %s", body)
return "", fmt.Errorf("%s", body)
}
var decoded DetokenizeResponse
if err := json.Unmarshal(body, &decoded); err != nil {
return "", fmt.Errorf("unmarshal encode response: %w", err)
}
return decoded.Content, nil
}
func (s *LlamaServer) Close() error {
if s.cmd != nil {
slog.Debug("stopping llama server")
return s.cmd.Process.Kill()
}
return nil
}
func parseDurationMs(ms float64) time.Duration {
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
return dur
}

42
llm/status.go Normal file
View file

@ -0,0 +1,42 @@
package llm
import (
"bytes"
"os"
)
// StatusWriter is a writer that captures error messages from the llama runner process
type StatusWriter struct {
LastErrMsg string
out *os.File
}
func NewStatusWriter(out *os.File) *StatusWriter {
return &StatusWriter{
out: out,
}
}
// TODO - regex matching to detect errors like
// libcublasLt.so.11: cannot open shared object file: No such file or directory
var errorPrefixes = []string{
"error:",
"CUDA error",
"cudaMalloc failed",
"\"ERR\"",
}
func (w *StatusWriter) Write(b []byte) (int, error) {
var errMsg string
for _, prefix := range errorPrefixes {
if _, after, ok := bytes.Cut(b, []byte(prefix)); ok {
errMsg = prefix + string(bytes.TrimSpace(after))
}
}
if errMsg != "" {
w.LastErrMsg = errMsg
}
return w.out.Write(b)
}

15
llm/utils.go
View file

@ -1,15 +0,0 @@
package llm
import (
"fmt"
"time"
)
func parseDurationMs(ms float64) time.Duration {
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
return dur
}

82
server/routes.go
View file

@ -56,12 +56,13 @@ func init() {
var loaded struct {
mu sync.Mutex
runner llm.LLM
llama *llm.LlamaServer
expireAt time.Time
expireTimer *time.Timer
*Model
model string
adapters []string
projectors []string
*api.Options
}
@ -69,21 +70,28 @@ var defaultSessionDuration = 5 * time.Minute
// load a model into memory if it is not already loaded, it is up to the caller to lock loaded.mu before calling this function
func load(c *gin.Context, model *Model, opts *api.Options, sessionDuration time.Duration) error {
needLoad := loaded.runner == nil || // is there a model loaded?
loaded.ModelPath != model.ModelPath || // has the base model changed?
!reflect.DeepEqual(loaded.AdapterPaths, model.AdapterPaths) || // have the adapters changed?
!reflect.DeepEqual(loaded.Options.Runner, opts.Runner) // have the runner options changed?
ctx, cancel := context.WithTimeout(c, 10*time.Second)
defer cancel()
needLoad := loaded.llama == nil || // is there a model loaded?
loaded.model != model.ModelPath || // has the base model changed?
!reflect.DeepEqual(loaded.adapters, model.AdapterPaths) || // have the adapters changed?
!reflect.DeepEqual(loaded.projectors, model.ProjectorPaths) || // have the adapters changed?
!reflect.DeepEqual(loaded.Options.Runner, opts.Runner) || // have the runner options changed?
loaded.llama.Ping(ctx) != nil
if needLoad {
if loaded.runner != nil {
if loaded.llama != nil {
slog.Info("changing loaded model")
loaded.runner.Close()
loaded.runner = nil
loaded.Model = nil
loaded.llama.Close()
loaded.llama = nil
loaded.model = ""
loaded.adapters = nil
loaded.projectors = nil
loaded.Options = nil
}
llmRunner, err := llm.New(model.ModelPath, model.AdapterPaths, model.ProjectorPaths, opts)
llama, err := llm.NewLlamaServer(model.ModelPath, model.AdapterPaths, model.ProjectorPaths, 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
@ -95,28 +103,26 @@ func load(c *gin.Context, model *Model, opts *api.Options, sessionDuration time.
return err
}
loaded.Model = model
loaded.runner = llmRunner
loaded.model = model.ModelPath
loaded.adapters = model.AdapterPaths
loaded.projectors = model.ProjectorPaths
loaded.llama = llama
loaded.Options = opts
}
loaded.expireAt = time.Now().Add(sessionDuration)
if loaded.expireTimer == nil {
loaded.expireTimer = time.AfterFunc(sessionDuration, func() {
loaded.mu.Lock()
defer loaded.mu.Unlock()
if time.Now().Before(loaded.expireAt) {
return
if loaded.llama != nil {
loaded.llama.Close()
}
if loaded.runner != nil {
loaded.runner.Close()
}
loaded.runner = nil
loaded.Model = nil
loaded.llama = nil
loaded.model = ""
loaded.adapters = nil
loaded.projectors = nil
loaded.Options = nil
})
}
@ -265,7 +271,7 @@ func GenerateHandler(c *gin.Context) {
sb.Reset()
if req.Context != nil {
prev, err := loaded.runner.Decode(c.Request.Context(), req.Context)
prev, err := loaded.llama.Detokenize(c.Request.Context(), req.Context)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@ -286,9 +292,8 @@ func GenerateHandler(c *gin.Context) {
go func() {
defer close(ch)
fn := func(r llm.PredictResult) {
fn := func(r llm.CompletionResponse) {
// Update model expiration
loaded.expireAt = time.Now().Add(sessionDuration)
loaded.expireTimer.Reset(sessionDuration)
// Build up the full response
@ -322,7 +327,7 @@ func GenerateHandler(c *gin.Context) {
}
// TODO (jmorganca): encode() should not strip special tokens
tokens, err := loaded.runner.Encode(c.Request.Context(), p)
tokens, err := loaded.llama.Tokenize(c.Request.Context(), p)
if err != nil {
ch <- gin.H{"error": err.Error()}
return
@ -344,13 +349,13 @@ func GenerateHandler(c *gin.Context) {
}
// Start prediction
predictReq := llm.PredictOpts{
req := llm.CompletionRequest{
Prompt: prompt,
Format: req.Format,
Images: images,
Options: opts,
}
if err := loaded.runner.Predict(c.Request.Context(), predictReq, fn); err != nil {
if err := loaded.llama.Completion(c.Request.Context(), req, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
@ -471,7 +476,7 @@ func EmbeddingsHandler(c *gin.Context) {
return
}
embedding, err := loaded.runner.Embedding(c.Request.Context(), req.Prompt)
embedding, err := loaded.llama.Embedding(c.Request.Context(), req.Prompt)
if err != nil {
slog.Info(fmt.Sprintf("embedding generation failed: %v", err))
c.JSON(http.StatusInternalServerError, gin.H{"error": "failed to generate embedding"})
@ -1123,8 +1128,8 @@ func Serve(ln net.Listener) error {
signal.Notify(signals, syscall.SIGINT, syscall.SIGTERM)
go func() {
<-signals
if loaded.runner != nil {
loaded.runner.Close()
if loaded.llama != nil {
loaded.llama.Close()
}
gpu.Cleanup()
os.Exit(0)
@ -1196,7 +1201,7 @@ func streamResponse(c *gin.Context, ch chan any) {
// ChatPrompt builds up a prompt from a series of messages for the currently `loaded` model
func chatPrompt(ctx context.Context, template string, messages []api.Message, numCtx int) (string, error) {
encode := func(s string) ([]int, error) {
return loaded.runner.Encode(ctx, s)
return loaded.llama.Tokenize(ctx, s)
}
prompt, err := ChatPrompt(template, messages, numCtx, encode)
@ -1326,9 +1331,8 @@ func ChatHandler(c *gin.Context) {
go func() {
defer close(ch)
fn := func(r llm.PredictResult) {
fn := func(r llm.CompletionResponse) {
// Update model expiration
loaded.expireAt = time.Now().Add(sessionDuration)
loaded.expireTimer.Reset(sessionDuration)
resp := api.ChatResponse{
@ -1352,14 +1356,12 @@ func ChatHandler(c *gin.Context) {
ch <- resp
}
// Start prediction
predictReq := llm.PredictOpts{
if err := loaded.llama.Completion(c.Request.Context(), llm.CompletionRequest{
Prompt: prompt,
Format: req.Format,
Images: images,
Options: opts,
}
if err := loaded.runner.Predict(c.Request.Context(), predictReq, fn); err != nil {
}, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()

27
server/routes_test.go
View file

@ -17,7 +17,6 @@ import (
"github.com/stretchr/testify/assert"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/version"
)
@ -211,7 +210,7 @@ func Test_Routes(t *testing.T) {
},
}
s := Server{}
s := &Server{}
router := s.GenerateRoutes()
httpSrv := httptest.NewServer(router)
@ -242,27 +241,3 @@ func Test_Routes(t *testing.T) {
}
}
type MockLLM struct {
encoding []int
}
func (llm *MockLLM) Predict(ctx context.Context, pred llm.PredictOpts, fn func(llm.PredictResult)) error {
return nil
}
func (llm *MockLLM) Encode(ctx context.Context, prompt string) ([]int, error) {
return llm.encoding, nil
}
func (llm *MockLLM) Decode(ctx context.Context, tokens []int) (string, error) {
return "", nil
}
func (llm *MockLLM) Embedding(ctx context.Context, input string) ([]float64, error) {
return []float64{}, nil
}
func (llm *MockLLM) Close() {
// do nothing
}