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Unverified Commit 96fb441a authored by Daniel Hiltgen's avatar Daniel Hiltgen Committed by GitHub
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Merge pull request #1146 from dhiltgen/ext_server_cgo 

Add cgo implementation for llama.cpp
parents fabf2f34 495c06e4
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Showing with 1130 additions and 768 deletions
llm/llama.cpp/patches/0004-metal-add-missing-barriers-for-mul-mat-2699.patch deleted 100644 → 0
View file @ fabf2f34
From 14b1d7e6f720dee41ce5a826376df738096d9033 Mon Sep 17 00:00:00 2001
From: Shouzheng Liu <lshzh.hi@gmail.com>
Date: Tue, 22 Aug 2023 02:18:40 -0400
Subject: [PATCH] metal : add missing barriers for mul-mat (#2699)
---
ggml-metal.metal | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/ggml-metal.metal b/ggml-metal.metal
index 88d48f6..ce3541f 100644
--- a/ggml-metal.metal
+++ b/ggml-metal.metal
@@ -1850,6 +1850,7 @@ kernel void kernel_mul_mm(device const uchar * src0,
//load data and store to threadgroup memory
half4x4 temp_a;
dequantize_func(x, il, temp_a);
+ threadgroup_barrier(mem_flags::mem_threadgroup);
#pragma unroll(16)
for (int i = 0; i < 16; i++) {
*(sa + SG_MAT_SIZE * ((tiitg / THREAD_PER_ROW / 8) \
@@ -1895,14 +1896,14 @@ kernel void kernel_mul_mm(device const uchar * src0,
}
} else {
// block is smaller than 64x32, we should avoid writing data outside of the matrix
+ threadgroup_barrier(mem_flags::mem_threadgroup);
threadgroup float *temp_str = ((threadgroup float *)shared_memory) \
+ 32 * (sgitg&1) + (16 * (sgitg>>1)) * BLOCK_SIZE_M;
for (int i = 0; i < 8; i++) {
- threadgroup_barrier(mem_flags::mem_device);
simdgroup_store(c_res[i], temp_str + 8 * (i%4) + 8 * BLOCK_SIZE_M * (i/4), BLOCK_SIZE_M);
}
- threadgroup_barrier(mem_flags::mem_device);
+ threadgroup_barrier(mem_flags::mem_threadgroup);
device float *C = dst + BLOCK_SIZE_M * r0 + (BLOCK_SIZE_N * r1) * ne0 + im*ne1*ne0;
if (sgitg==0) {
for (int i = 0; i < n_rows; i++) {
--
2.41.0
llm/llama.cpp/patches/0005-ggml-support-CUDA-s-half-type-for-aarch64-1455-2670.patch deleted 100644 → 0
View file @ fabf2f34
From 1e3bc523d8053a77df3ac7126a84d0297ee97ef6 Mon Sep 17 00:00:00 2001
From: Kylin <56434533+KyL0N@users.noreply.github.com>
Date: Tue, 22 Aug 2023 15:14:23 +0800
Subject: [PATCH] ggml : support CUDA's half type for aarch64(#1455) (#2670)
* ggml: support CUDA's half type for aarch64(#1455)
support CUDA's half type for aarch64 in ggml_fp16_t definition
* ggml: use __CUDACC__ to recognise nvcc compiler
---
ggml.h | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/ggml.h b/ggml.h
index 544ad2d..0ec7ec5 100644
--- a/ggml.h
+++ b/ggml.h
@@ -259,8 +259,9 @@
extern "C" {
#endif
-#ifdef __ARM_NEON
- // we use the built-in 16-bit float type
+#if defined(__ARM_NEON) && defined(__CUDACC__)
+ typedef half ggml_fp16_t;
+#elif defined(__ARM_NEON)
typedef __fp16 ggml_fp16_t;
#else
typedef uint16_t ggml_fp16_t;
--
2.39.2 (Apple Git-143)
llm/llama.go
View file @ 96fb441a
package llm package llm
import ( import (
"bufio"
"bytes" "bytes"
"context" "context"
"embed" _ "embed"
"encoding/json"
"errors" "errors"
"fmt" "fmt"
"io" "io"
"io/fs" "io/fs"
"log"
"math/rand"
"net/http"
"os" "os"
"os/exec" "os/exec"
"path"
"path/filepath" "path/filepath"
"runtime"
"strconv"
"strings"
"sync" "sync"
"time" "time"
...@@ -55,109 +46,6 @@ number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws ...@@ -55,109 +46,6 @@ number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws
ws ::= ([ \t\n] ws)? ws ::= ([ \t\n] ws)?
` `
//go:embed llama.cpp/*/build/*/bin/*
var llamaCppEmbed embed.FS
type ModelRunner struct {
Type string // "gguf" or "ggml"
Path string // path to the model runner executable
Accelerated bool
}
func chooseRunners(workDir, runnerType string) []ModelRunner {
buildPath := path.Join("llama.cpp", runnerType, "build")
var runners []ModelRunner
// set the runners based on the OS
// IMPORTANT: the order of the runners in the array is the priority order
switch runtime.GOOS {
case "darwin":
if runtime.GOARCH == "arm64" {
runners = []ModelRunner{{Type: runnerType, Path: path.Join(buildPath, "metal", "bin", "ollama-runner")}}
} else {
runners = []ModelRunner{{Type: runnerType, Path: path.Join(buildPath, "cpu", "bin", "ollama-runner")}}
}
case "linux":
runners = []ModelRunner{
{Type: runnerType, Path: path.Join(buildPath, "cuda", "bin", "ollama-runner"), Accelerated: true},
{Type: runnerType, Path: path.Join(buildPath, "cpu", "bin", "ollama-runner")},
}
case "windows":
// TODO: select windows GPU runner here when available
runners = []ModelRunner{
{Type: runnerType, Path: path.Join(buildPath, "cuda", "bin", "Release", "ollama-runner.exe"), Accelerated: true},
{Type: runnerType, Path: path.Join(buildPath, "cpu", "bin", "Release", "ollama-runner.exe")},
}
default:
log.Printf("unknown OS, running on CPU: %s", runtime.GOOS)
runners = []ModelRunner{
{Type: runnerType, Path: path.Join(buildPath, "cpu", "bin", "ollama-runner")},
}
}
runnerAvailable := false // if no runner files are found in the embed, this flag will cause a fast fail
for _, r := range runners {
// find all the files in the runner's bin directory
files, err := fs.Glob(llamaCppEmbed, path.Join(path.Dir(r.Path), "*"))
if err != nil {
// this is expected, ollama may be compiled without all runners packed in
log.Printf("%s runner not found: %v", r.Path, err)
continue
}
for _, f := range files {
runnerAvailable = true
srcFile, err := llamaCppEmbed.Open(f)
if err != nil {
log.Fatalf("read llama runner %s: %v", f, err)
}
defer srcFile.Close()
// create the directory in case it does not exist, filepath.Dir() converts the file path to the OS's format
destPath := filepath.Join(workDir, filepath.Dir(f))
if err := os.MkdirAll(destPath, 0o755); err != nil {
log.Fatalf("create runner temp dir %s: %v", filepath.Dir(f), err)
}
// create the path to the destination file, filepath.Base() converts the file path to the OS's format
destFile := filepath.Join(destPath, filepath.Base(f))
_, err = os.Stat(destFile)
switch {
case errors.Is(err, os.ErrNotExist):
destFile, err := os.OpenFile(destFile, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
if err != nil {
log.Fatalf("write llama runner %s: %v", f, err)
}
defer destFile.Close()
if _, err := io.Copy(destFile, srcFile); err != nil {
log.Fatalf("copy llama runner %s: %v", f, err)
}
case err != nil:
log.Fatalf("stat llama runner %s: %v", f, err)
}
}
}
if !runnerAvailable {
log.Fatalf("%s runner not found", runnerType)
}
// return the runners to try in priority order
localRunnersByPriority := []ModelRunner{}
for _, r := range runners {
// clean the ModelRunner paths so that they match the OS we are running on
localRunnersByPriority = append(localRunnersByPriority, ModelRunner{
Type: r.Type,
Path: filepath.Clean(path.Join(workDir, r.Path)),
Accelerated: r.Accelerated,
})
}
return localRunnersByPriority
}
type llamaModel struct { type llamaModel struct {
hyperparameters llamaHyperparameters hyperparameters llamaHyperparameters
} }
...@@ -228,83 +116,12 @@ type ImageData struct { ...@@ -228,83 +116,12 @@ type ImageData struct {
ID int `json:"id"` ID int `json:"id"`
} }
type llama struct {
api.Options
ImageData []ImageData
Running
}
var ( var (
errNvidiaSMI = errors.New("warning: gpu support may not be enabled, check that you have installed GPU drivers: nvidia-smi command failed") errNvidiaSMI = errors.New("warning: gpu support may not be enabled, check that you have installed GPU drivers: nvidia-smi command failed")
errAvailableVRAM = errors.New("not enough VRAM available, falling back to CPU only") errAvailableVRAM = errors.New("not enough VRAM available, falling back to CPU only")
payloadMissing = fmt.Errorf("expected dynamic library payloads not included in this build of ollama")
) )
// CheckVRAM returns the free VRAM in bytes on Linux machines with NVIDIA GPUs
func CheckVRAM() (int64, error) {
cmd := exec.Command("nvidia-smi", "--query-gpu=memory.free", "--format=csv,noheader,nounits")
var stdout bytes.Buffer
cmd.Stdout = &stdout
err := cmd.Run()
if err != nil {
return 0, errNvidiaSMI
}
var freeMiB int64
scanner := bufio.NewScanner(&stdout)
for scanner.Scan() {
line := scanner.Text()
if strings.Contains(line, "[Insufficient Permissions]") {
return 0, fmt.Errorf("GPU support may not enabled, check you have installed GPU drivers and have the necessary permissions to run nvidia-smi")
}
vram, err := strconv.ParseInt(strings.TrimSpace(line), 10, 64)
if err != nil {
return 0, fmt.Errorf("failed to parse available VRAM: %v", err)
}
freeMiB += vram
}
freeBytes := freeMiB * 1024 * 1024
if freeBytes < 2*format.GigaByte {
log.Printf("less than 2 GB VRAM available")
return 0, errAvailableVRAM
}
return freeBytes, nil
}
func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
if opts.NumGPU != -1 {
return opts.NumGPU
}
if runtime.GOOS == "linux" || runtime.GOOS == "windows" {
freeBytes, err := CheckVRAM()
if err != nil {
if !errors.Is(err, errNvidiaSMI) {
log.Print(err.Error())
}
// nvidia driver not installed or no nvidia GPU found
return 0
}
/*
Calculate bytes per layer, this will roughly be the size of the model file divided by the number of layers.
We can store the model weights and the kv cache in vram,
to enable kv chache vram storage add two additional layers to the number of layers retrieved from the model file.
*/
bytesPerLayer := fileSizeBytes / numLayer
// 75% of the absolute max number of layers we can fit in available VRAM, off-loading too many layers to the GPU can cause OOM errors
layers := int(freeBytes/bytesPerLayer) * 3 / 4
log.Printf("%d MB VRAM available, loading up to %d GPU layers", freeBytes/(1024*1024), layers)
return layers
}
// default to enable metal on macOS
return 1
}
// StatusWriter is a writer that captures error messages from the llama runner process // StatusWriter is a writer that captures error messages from the llama runner process
type StatusWriter struct { type StatusWriter struct {
ErrCh chan error ErrCh chan error
...@@ -333,203 +150,6 @@ func (w *StatusWriter) Write(b []byte) (int, error) { ...@@ -333,203 +150,6 @@ func (w *StatusWriter) Write(b []byte) (int, error) {
return os.Stderr.Write(b) return os.Stderr.Write(b)
} }
func newLlama(model string, adapters, projectors []string, runners []ModelRunner, numLayers int64, opts api.Options) (*llama, error) {
fileInfo, err := os.Stat(model)
if err != nil {
return nil, err
}
if len(adapters) > 1 {
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
}
numGPU := NumGPU(numLayers, fileInfo.Size(), opts)
params := []string{
"--model", model,
"--ctx-size", fmt.Sprintf("%d", opts.NumCtx),
"--batch-size", fmt.Sprintf("%d", opts.NumBatch),
"--n-gpu-layers", fmt.Sprintf("%d", numGPU),
"--embedding",
}
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 opts.NumGQA > 0 {
params = append(params, "--gqa", fmt.Sprintf("%d", opts.NumGQA))
}
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")
}
var runnerErr error
// start the llama.cpp server with a retry in case the port is already in use
for _, runner := range runners {
if runner.Accelerated && numGPU == 0 {
log.Printf("skipping accelerated runner because num_gpu=0")
continue
}
if _, err := os.Stat(runner.Path); err != nil {
log.Printf("llama runner not found: %v", err)
continue
}
port := rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range
params := append(params, "--port", strconv.Itoa(port))
ctx, cancel := context.WithCancel(context.Background())
cmd := exec.CommandContext(
ctx,
runner.Path,
params...,
)
var libraryPaths []string
if libraryPath, ok := os.LookupEnv("LD_LIBRARY_PATH"); ok {
libraryPaths = append(libraryPaths, libraryPath)
}
libraryPaths = append(libraryPaths, filepath.Dir(runner.Path))
cmd.Env = append(os.Environ(), fmt.Sprintf("LD_LIBRARY_PATH=%s", strings.Join(libraryPaths, ":")))
cmd.Stdout = os.Stderr
statusWriter := NewStatusWriter()
cmd.Stderr = statusWriter
llm := &llama{Options: opts, Running: Running{Port: port, Cmd: cmd, Cancel: cancel, exitCh: make(chan error)}}
log.Print("starting llama runner")
if err := llm.Cmd.Start(); err != nil {
log.Printf("error starting the external llama runner: %v", err)
continue
}
// monitor the llama runner process and signal when it exits
go func() {
err := llm.Cmd.Wait()
// default to printing the exit message of the command process, it will probably just say 'exit staus 1'
errMsg := err.Error()
// try to set a better error message if llama runner logs captured an error
if statusWriter.LastErrMsg != "" {
errMsg = statusWriter.LastErrMsg
}
log.Println(errMsg)
// llm.Cmd.Wait() can only be called once, use this exit channel to signal that the process has exited
llm.exitOnce.Do(func() {
close(llm.exitCh)
})
}()
if err := waitForServer(llm); err != nil {
log.Printf("error starting llama runner: %v", err)
llm.Close()
// default the runnerErr to the error returned by the most recent llama runner process
runnerErr = err
// capture the error directly from the runner process, if any
select {
case runnerErr = <-statusWriter.ErrCh:
default:
// the runner process probably timed out
}
// try again
continue
}
// server started successfully
return llm, nil
}
if runnerErr != nil {
// this is the error returned from the llama runner process that failed most recently
return nil, runnerErr
}
return nil, fmt.Errorf("failed to start a llama runner")
}
func waitForServer(llm *llama) 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(200 * time.Millisecond)
defer ticker.Stop()
log.Print("waiting for llama runner to start responding")
for {
select {
case <-llm.exitCh:
// failed to start subprocess
return fmt.Errorf("llama runner process has terminated")
case <-ticker.C:
if time.Now().After(expiresAt) {
// timeout
return fmt.Errorf("timed out waiting for llama runner to start")
}
if err := llm.Ping(context.Background()); err == nil {
// success
log.Printf("llama runner started in %f seconds", time.Since(start).Seconds())
return nil
}
}
}
}
func (llm *llama) Close() {
// signal the sub-process to terminate
llm.Cancel()
// wait for the command to exit to prevent race conditions with the next run
<-llm.exitCh
if llm.StatusWriter != nil && llm.StatusWriter.LastErrMsg != "" {
log.Printf("llama runner stopped with error: %v", llm.StatusWriter.LastErrMsg)
} else {
log.Print("llama runner stopped successfully")
}
}
func (llm *llama) SetOptions(opts api.Options) {
llm.Options = opts
}
type prediction struct { type prediction struct {
Content string `json:"content"` Content string `json:"content"`
Model string `json:"model"` Model string `json:"model"`
...@@ -545,7 +165,8 @@ type prediction struct { ...@@ -545,7 +165,8 @@ type prediction struct {
} }
const maxBufferSize = 512 * format.KiloByte const maxBufferSize = 512 * format.KiloByte
const maxRetries = 6 const maxRetries = 3
const retryDelay = 1 * time.Second
type PredictOpts struct { type PredictOpts struct {
Prompt string Prompt string
...@@ -562,158 +183,6 @@ type PredictResult struct { ...@@ -562,158 +183,6 @@ type PredictResult struct {
EvalDuration time.Duration EvalDuration time.Duration
} }
// IsRetryable checks if the line matches a condition that can be retried
func isRetryable(line []byte) bool {
return bytes.Contains(line, []byte("slot unavailable"))
}
func (llm *llama) Predict(ctx context.Context, predict PredictOpts, fn func(PredictResult)) error {
imageData := llm.ImageData
if len(predict.Images) > 0 {
for cnt, i := range predict.Images {
imageData = append(imageData, ImageData{Data: i, ID: cnt})
}
}
log.Printf("loaded %d images", len(imageData))
request := map[string]any{
"prompt": predict.Prompt,
"stream": true,
"n_predict": llm.NumPredict,
"n_keep": llm.NumKeep,
"main_gpu": llm.MainGPU,
"temperature": llm.Temperature,
"top_k": llm.TopK,
"top_p": llm.TopP,
"tfs_z": llm.TFSZ,
"typical_p": llm.TypicalP,
"repeat_last_n": llm.RepeatLastN,
"repeat_penalty": llm.RepeatPenalty,
"presence_penalty": llm.PresencePenalty,
"frequency_penalty": llm.FrequencyPenalty,
"mirostat": llm.Mirostat,
"mirostat_tau": llm.MirostatTau,
"mirostat_eta": llm.MirostatEta,
"penalize_nl": llm.PenalizeNewline,
"seed": llm.Seed,
"stop": llm.Stop,
"image_data": imageData,
}
if predict.Format == "json" {
request["grammar"] = jsonGrammar
}
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", llm.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)
// increase the buffer size to avoid running out of space
buf := make([]byte, 0, maxBufferSize)
scanner.Buffer(buf, maxBufferSize)
retryNeeded := false
for scanner.Scan() {
select {
case <-ctx.Done():
// This handles the request cancellation
return ctx.Err()
default:
line := scanner.Bytes()
if len(line) == 0 {
continue
}
if isRetryable(line) {
retryNeeded = true
break
}
evt, ok := bytes.CutPrefix(line, []byte("data: "))
if !ok {
return fmt.Errorf("error parsing llm response stream: %s", line)
}
var p prediction
if err := json.Unmarshal(evt, &p); err != nil {
return fmt.Errorf("error unmarshaling llm prediction response: %v", err)
}
if p.Content != "" {
fn(PredictResult{
Content: p.Content,
})
}
if p.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 err := scanner.Err(); err != nil {
if strings.Contains(err.Error(), "unexpected EOF") {
// this means the llama runner subprocess crashed
llm.Close()
if llm.StatusWriter != nil && llm.StatusWriter.LastErrMsg != "" {
return fmt.Errorf("llama runner exited: %v", llm.StatusWriter.LastErrMsg)
}
return fmt.Errorf("llama runner exited, you may not have enough available memory to run this model")
}
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 TokenizeRequest struct { type TokenizeRequest struct {
Content string `json:"content"` Content string `json:"content"`
} }
...@@ -722,43 +191,6 @@ type TokenizeResponse struct { ...@@ -722,43 +191,6 @@ type TokenizeResponse struct {
Tokens []int `json:"tokens"` Tokens []int `json:"tokens"`
} }
func (llm *llama) Encode(ctx context.Context, prompt string) ([]int, error) {
endpoint := fmt.Sprintf("http://127.0.0.1:%d/tokenize", llm.Port)
data, err := json.Marshal(TokenizeRequest{Content: prompt})
if err != nil {
return nil, fmt.Errorf("marshaling encode data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, 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 { type DetokenizeRequest struct {
Tokens []int `json:"tokens"` Tokens []int `json:"tokens"`
} }
...@@ -767,46 +199,6 @@ type DetokenizeResponse struct { ...@@ -767,46 +199,6 @@ type DetokenizeResponse struct {
Content string `json:"content"` Content string `json:"content"`
} }
func (llm *llama) Decode(ctx context.Context, tokens []int) (string, error) {
if len(tokens) == 0 {
return "", nil
}
endpoint := fmt.Sprintf("http://127.0.0.1:%d/detokenize", llm.Port)
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, endpoint, 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
}
type EmbeddingRequest struct { type EmbeddingRequest struct {
Content string `json:"content"` Content string `json:"content"`
} }
...@@ -815,51 +207,40 @@ type EmbeddingResponse struct { ...@@ -815,51 +207,40 @@ type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"` Embedding []float64 `json:"embedding"`
} }
func (llm *llama) Embedding(ctx context.Context, input string) ([]float64, error) { func extractDynamicLibs(workDir, glob string) ([]string, error) {
endpoint := fmt.Sprintf("http://127.0.0.1:%d/embedding", llm.Port) files, err := fs.Glob(libEmbed, glob)
data, err := json.Marshal(TokenizeRequest{Content: input}) if err != nil || len(files) == 0 {
if err != nil { return nil, payloadMissing
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
req, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, 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("POST embedding: %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)
} }
libs := make([]string, len(files))
if resp.StatusCode >= 400 { for i, file := range files {
log.Printf("llm encode error: %s", body) srcFile, err := libEmbed.Open(file)
return nil, fmt.Errorf("%s", body) if err != nil {
} return nil, fmt.Errorf("read payload %s: %v", file, err)
}
var embedding EmbeddingResponse defer srcFile.Close()
if err := json.Unmarshal(body, &embedding); err != nil { if err := os.MkdirAll(workDir, 0o755); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err) return nil, fmt.Errorf("create payload temp dir %s: %v", workDir, err)
} }
return embedding.Embedding, nil destFile := filepath.Join(workDir, filepath.Base(file))
} libs[i] = destFile
// Ping checks that the server subprocess is still running and responding to requests _, err = os.Stat(destFile)
func (llm *llama) Ping(ctx context.Context) error { switch {
resp, err := http.Head(fmt.Sprintf("http://127.0.0.1:%d", llm.Port)) case errors.Is(err, os.ErrNotExist):
if err != nil { destFile, err := os.OpenFile(destFile, os.O_WRONLY|os.O_CREATE|os.O_TRUNC, 0o755)
return fmt.Errorf("ping resp: %w", err) if err != nil {
} return nil, fmt.Errorf("write payload %s: %v", file, err)
if resp.StatusCode != http.StatusOK { }
return fmt.Errorf("unexpected ping status: %s", resp.Status) defer destFile.Close()
if _, err := io.Copy(destFile, srcFile); err != nil {
return nil, fmt.Errorf("copy payload %s: %v", file, err)
}
case err != nil:
return nil, fmt.Errorf("stat payload %s: %v", file, err)
}
} }
return nil return libs, nil
} }
llm/llm.go
View file @ 96fb441a
...@@ -11,6 +11,7 @@ import ( ...@@ -11,6 +11,7 @@ import (
"github.com/jmorganca/ollama/api" "github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/format" "github.com/jmorganca/ollama/format"
"github.com/jmorganca/ollama/gpu"
) )
type LLM interface { type LLM interface {
...@@ -18,11 +19,11 @@ type LLM interface { ...@@ -18,11 +19,11 @@ type LLM interface {
Embedding(context.Context, string) ([]float64, error) Embedding(context.Context, string) ([]float64, error)
Encode(context.Context, string) ([]int, error) Encode(context.Context, string) ([]int, error)
Decode(context.Context, []int) (string, error) Decode(context.Context, []int) (string, error)
SetOptions(api.Options)
Close() Close()
Ping(context.Context) error
} }
var AvailableShims = map[string]string{}
func New(workDir, model string, adapters, projectors []string, opts api.Options) (LLM, error) { func New(workDir, model string, adapters, projectors []string, opts api.Options) (LLM, error) {
if _, err := os.Stat(model); err != nil { if _, err := os.Stat(model); err != nil {
return nil, err return nil, err
...@@ -76,16 +77,27 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options) ...@@ -76,16 +77,27 @@ func New(workDir, model string, adapters, projectors []string, opts api.Options)
} }
} }
switch ggml.Name() { opts.NumGQA = 0
case "gguf": opts.RopeFrequencyBase = 0.0
// TODO: gguf will load these options automatically from the model binary opts.RopeFrequencyScale = 0.0
opts.NumGQA = 0 gpuInfo := gpu.GetGPUInfo()
opts.RopeFrequencyBase = 0.0 return newLlmServer(gpuInfo.Library, model, adapters, projectors, ggml.NumLayers(), opts)
opts.RopeFrequencyScale = 0.0 }
return newLlama(model, adapters, projectors, chooseRunners(workDir, "gguf"), ggml.NumLayers(), opts)
case "ggml", "ggmf", "ggjt", "ggla": // Give any native cgo implementations an opportunity to initialize
return newLlama(model, adapters, projectors, chooseRunners(workDir, "ggml"), ggml.NumLayers(), opts) func Init(workdir string) error {
default: return nativeInit(workdir)
return nil, fmt.Errorf("unknown ggml type: %s", ggml.ModelFamily()) }
func newLlmServer(library, model string, adapters, projectors []string, numLayers int64, opts api.Options) (extServer, error) {
if _, libPresent := AvailableShims[library]; libPresent && library != "default" {
srv, err := newDynamicShimExtServer(AvailableShims[library], model, adapters, projectors, numLayers, opts)
if err == nil {
return srv, nil
}
log.Printf("Failed to load dynamic library - falling back to CPU mode %s", err)
} }
return newDefaultExtServer(model, adapters, projectors, numLayers, opts)
} }
llm/shim_darwin.go 0 → 100644
View file @ 96fb441a
package llm
import (
"embed"
"fmt"
"log"
"os"
"github.com/jmorganca/ollama/api"
)
//go:embed llama.cpp/gguf/ggml-metal.metal
var libEmbed embed.FS
func newDynamicShimExtServer(library, model string, adapters, projectors []string, numLayers int64, opts api.Options) (extServer, error) {
// should never happen...
return nil, fmt.Errorf("Dynamic library loading not supported on Mac")
}
func nativeInit(workdir string) error {
_, err := extractDynamicLibs(workdir, "llama.cpp/gguf/ggml-metal.metal")
if err != nil {
if err == payloadMissing {
// TODO perhaps consider this a hard failure on arm macs?
log.Printf("ggml-meta.metal payload missing")
return nil
}
return err
}
os.Setenv("GGML_METAL_PATH_RESOURCES", workdir)
return nil
}
llm/shim_ext_server.go 0 → 100644
View file @ 96fb441a
//go:build !darwin
package llm
/*
#include <stdlib.h>
#include "dynamic_shim.h"
*/
import "C"
import (
"context"
"embed"
"errors"
"fmt"
"io/fs"
"log"
"os"
"path/filepath"
"strings"
"sync"
"unsafe"
"github.com/jmorganca/ollama/api"
)
//go:embed llama.cpp/gguf/build/lib/*
var libEmbed embed.FS
var RocmShimMissing = fmt.Errorf("ROCm shim library not included in this build of ollama. Radeon GPUs are not supported")
type shimExtServer struct {
s C.struct_dynamic_llama_server
options api.Options
}
// Note: current implementation does not support concurrent instantiations
var shimMutex sync.Mutex
var llm *shimExtServer
func (llm *shimExtServer) llama_server_init(sparams *C.ext_server_params_t, err *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_init(llm.s, sparams, err)
}
func (llm *shimExtServer) llama_server_start() {
C.dynamic_shim_llama_server_start(llm.s)
}
func (llm *shimExtServer) llama_server_stop() {
C.dynamic_shim_llama_server_stop(llm.s)
}
func (llm *shimExtServer) llama_server_completion(json_req *C.char, resp *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_completion(llm.s, json_req, resp)
}
func (llm *shimExtServer) llama_server_completion_next_result(task_id C.int, resp *C.ext_server_task_result_t) {
C.dynamic_shim_llama_server_completion_next_result(llm.s, task_id, resp)
}
func (llm *shimExtServer) llama_server_completion_cancel(task_id C.int, err *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_completion_cancel(llm.s, task_id, err)
}
func (llm *shimExtServer) llama_server_release_task_result(result *C.ext_server_task_result_t) {
C.dynamic_shim_llama_server_release_task_result(llm.s, result)
}
func (llm *shimExtServer) llama_server_tokenize(json_req *C.char, json_resp **C.char, err *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_tokenize(llm.s, json_req, json_resp, err)
}
func (llm *shimExtServer) llama_server_detokenize(json_req *C.char, json_resp **C.char, err *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_detokenize(llm.s, json_req, json_resp, err)
}
func (llm *shimExtServer) llama_server_embedding(json_req *C.char, json_resp **C.char, err *C.ext_server_resp_t) {
C.dynamic_shim_llama_server_embedding(llm.s, json_req, json_resp, err)
}
func (llm *shimExtServer) llama_server_release_json_resp(json_resp **C.char) {
C.dynamic_shim_llama_server_release_json_resp(llm.s, json_resp)
}
func newDynamicShimExtServer(library, model string, adapters, projectors []string, numLayers int64, opts api.Options) (extServer, error) {
shimMutex.Lock()
defer shimMutex.Unlock()
libPath := C.CString(library)
defer C.free(unsafe.Pointer(libPath))
resp := newExtServerResp(128)
defer freeExtServerResp(resp)
var srv C.struct_dynamic_llama_server
C.dynamic_shim_init(libPath, &srv, &resp)
if resp.id < 0 {
return nil, fmt.Errorf("Unable to load dynamic library: %s", C.GoString(resp.msg))
}
llm = &shimExtServer{
s: srv,
options: opts,
}
log.Printf("Loading Dynamic Shim llm server: %s", library)
return newExtServer(llm, model, adapters, projectors, numLayers, opts)
}
func (llm *shimExtServer) Predict(ctx context.Context, pred PredictOpts, fn func(PredictResult)) error {
return predict(llm, llm.options, ctx, pred, fn)
}
func (llm *shimExtServer) Encode(ctx context.Context, prompt string) ([]int, error) {
return encode(llm, ctx, prompt)
}
func (llm *shimExtServer) Decode(ctx context.Context, tokens []int) (string, error) {
return decode(llm, ctx, tokens)
}
func (llm *shimExtServer) Embedding(ctx context.Context, input string) ([]float64, error) {
return embedding(llm, ctx, input)
}
func (llm *shimExtServer) Close() {
close(llm)
}
func nativeInit(workdir string) error {
libs, err := extractDynamicLibs(workdir, "llama.cpp/gguf/build/lib/*server*")
if err != nil {
if err == payloadMissing {
log.Printf("%s", payloadMissing)
return nil
}
return err
}
for _, lib := range libs {
libName := strings.Split(strings.TrimPrefix(filepath.Base(lib), "lib"), ".")[0]
AvailableShims[libName] = lib
}
// Only check ROCm access if we have the dynamic lib loaded
if _, rocmPresent := AvailableShims["rocm_server"]; rocmPresent {
// 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) {
log.Fatalf("Radeon card detected, but permissions not set up properly. Either run ollama as root, or add you user account to the render group.")
return err
} 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
}
scripts/build_darwin.sh
View file @ 96fb441a
...@@ -9,7 +9,7 @@ mkdir -p dist ...@@ -9,7 +9,7 @@ mkdir -p dist
for TARGETARCH in arm64 amd64; do for TARGETARCH in arm64 amd64; do
GOOS=darwin GOARCH=$TARGETARCH go generate ./... GOOS=darwin GOARCH=$TARGETARCH go generate ./...
GOOS=darwin GOARCH=$TARGETARCH go build -o dist/ollama-darwin-$TARGETARCH CGO_ENABLED=1 GOOS=darwin GOARCH=$TARGETARCH go build -o dist/ollama-darwin-$TARGETARCH
rm -rf llm/llama.cpp/*/build rm -rf llm/llama.cpp/*/build
done done
......
scripts/build_linux.sh
View file @ 96fb441a
...@@ -7,8 +7,8 @@ export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version ...@@ -7,8 +7,8 @@ export GOFLAGS="'-ldflags=-w -s \"-X=github.com/jmorganca/ollama/version.Version
mkdir -p dist mkdir -p dist
for TARGETARCH in arm64 amd64; do for TARGETARCH in amd64 arm64; do
docker buildx build --load --platform=linux/$TARGETARCH --build-arg=VERSION --build-arg=GOFLAGS -f Dockerfile.build -t builder:$TARGETARCH . docker buildx build --load --progress=plain --platform=linux/$TARGETARCH --build-arg=VERSION --build-arg=GOFLAGS -f Dockerfile.build -t builder:$TARGETARCH .
docker create --platform linux/$TARGETARCH --name builder-$TARGETARCH builder:$TARGETARCH docker create --platform linux/$TARGETARCH --name builder-$TARGETARCH builder:$TARGETARCH
docker cp builder-$TARGETARCH:/go/src/github.com/jmorganca/ollama/ollama ./dist/ollama-linux-$TARGETARCH docker cp builder-$TARGETARCH:/go/src/github.com/jmorganca/ollama/ollama ./dist/ollama-linux-$TARGETARCH
docker rm builder-$TARGETARCH docker rm builder-$TARGETARCH
......
scripts/build_remote.py 0 → 100755
View file @ 96fb441a
#!/usr/bin/env python3
import subprocess
import sys
from urllib.parse import urlparse
from git import Repo
# Helper script to be able to build on remote repos using git to push local changes
# (e.g. particularly helpful to target a remote windows build system)
#
# Typical windows remote git config looks like this:
#
#[remote "windows-pa"]
# url = jdoe@desktop-foo:C:/Users/Jdoe/code/ollama
# fetch = +refs/heads/*:refs/remotes/windows-pa/*
# uploadpack = powershell git upload-pack
# receivepack = powershell git receive-pack
#
# TODO - add argpare and make this more configurable
# - force flag becomes optional
# - generate, build or test ...
# Note: remote repo will need this run once:
# git config --local receive.denyCurrentBranch updateInstead
repo = Repo(".")
# On linux, add links in /usr/local/bin to the go binaries to avoid needing this
# GoCmd = "/usr/local/go/bin/go"
GoCmd = "go"
if repo.is_dirty():
print("Tree is dirty. Commit your changes before running this script")
sys.exit(1)
if len(sys.argv) != 2:
print("Please specify the remote name: " + ', '.join([r.name for r in repo.remotes]))
sys.exit(1)
remote_name = sys.argv[1]
remote = {r.name: r for r in repo.remotes}[remote_name]
raw_url = list(remote.urls)[0]
url = urlparse(raw_url)
# Windows urls don't quite parse properly
if url.scheme == "" and url.netloc == "":
url = urlparse("ssh://" + raw_url)
print("URL: " + str(url))
netloc = url.netloc.split(":")[0]
path = url.path
branch_name = repo.active_branch.name
print("Force pushing content to remote...")
# Use with care given the force push
remote.push(force=True).raise_if_error()
print("Ensuring correct branch checked out on remote via ssh...")
subprocess.check_call(['ssh', netloc, 'cd', path, ';', 'git', 'checkout', branch_name])
# TODO - add some hardening to try to figure out how to set up the path properly
# subprocess.check_call(['ssh', netloc, 'cd', path, ';', 'env'])
# TODO - or consider paramiko maybe
print("Performing generate")
subprocess.check_call(['ssh', netloc, 'cd', path, ';', GoCmd, 'generate', './...'])
print("Building")
subprocess.check_call(['ssh', netloc, 'cd', path, ';', GoCmd, 'build', '.'])
scripts/setup_integration_tests.sh 0 → 100755
View file @ 96fb441a
#!/bin/bash
# This script sets up integration tests which run the full stack to verify
# inference locally
set -e
set -o pipefail
REPO=$(dirname $0)/../
export OLLAMA_MODELS=${REPO}/test_data/models
REGISTRY_SCHEME=https
REGISTRY=registry.ollama.ai
TEST_MODELS=("library/orca-mini:latest" "library/llava:7b")
ACCEPT_HEADER="Accept: application/vnd.docker.distribution.manifest.v2+json"
for model in ${TEST_MODELS[@]}; do
TEST_MODEL=$(echo ${model} | cut -f1 -d:)
TEST_MODEL_TAG=$(echo ${model} | cut -f2 -d:)
mkdir -p ${OLLAMA_MODELS}/manifests/${REGISTRY}/${TEST_MODEL}/
mkdir -p ${OLLAMA_MODELS}/blobs/
echo "Pulling manifest for ${TEST_MODEL}:${TEST_MODEL_TAG}"
curl -s --header "${ACCEPT_HEADER}" \
-o ${OLLAMA_MODELS}/manifests/${REGISTRY}/${TEST_MODEL}/${TEST_MODEL_TAG} \
${REGISTRY_SCHEME}://${REGISTRY}/v2/${TEST_MODEL}/manifests/${TEST_MODEL_TAG}
CFG_HASH=$(cat ${OLLAMA_MODELS}/manifests/${REGISTRY}/${TEST_MODEL}/${TEST_MODEL_TAG} | jq -r ".config.digest")
echo "Pulling config blob ${CFG_HASH}"
curl -L -C - --header "${ACCEPT_HEADER}" \
-o ${OLLAMA_MODELS}/blobs/${CFG_HASH} \
${REGISTRY_SCHEME}://${REGISTRY}/v2/${TEST_MODEL}/blobs/${CFG_HASH}
for LAYER in $(cat ${OLLAMA_MODELS}/manifests/${REGISTRY}/${TEST_MODEL}/${TEST_MODEL_TAG} | jq -r ".layers[].digest" ) ; do
echo "Pulling blob ${LAYER}"
curl -L -C - --header "${ACCEPT_HEADER}" \
-o ${OLLAMA_MODELS}/blobs/${LAYER} \
${REGISTRY_SCHEME}://${REGISTRY}/v2/${TEST_MODEL}/blobs/${LAYER}
done
done
server/images.go
View file @ 96fb441a
...@@ -418,6 +418,31 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars ...@@ -418,6 +418,31 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars
return err return err
} }
// if the model is not in gguf format, pull the base model to try and get it in gguf format
if fromConfig.ModelFormat != "gguf" {
fn(api.ProgressResponse{Status: "updating base model"})
parent, err := GetModel(c.Args)
if err != nil {
return err
}
if err := PullModel(ctx, parent.OriginalModel, &RegistryOptions{}, fn); err != nil {
log.Printf("error pulling model: %v", err)
}
// Reset the file pointer to the beginning of the file
_, err = fromConfigFile.Seek(0, 0)
if err != nil {
return fmt.Errorf("update from config after pull: %w", err)
}
if err := json.NewDecoder(fromConfigFile).Decode(&fromConfig); err != nil {
return err
}
}
// if the model is still not in gguf format, error out
if fromConfig.ModelFormat != "gguf" {
return fmt.Errorf("%s is not in gguf format, this base model is not compatible with this version of ollama", c.Args)
}
config.SetModelFormat(fromConfig.ModelFormat) config.SetModelFormat(fromConfig.ModelFormat)
config.SetModelFamily(append(fromConfig.ModelFamilies, fromConfig.ModelFamily)...) config.SetModelFamily(append(fromConfig.ModelFamilies, fromConfig.ModelFamily)...)
config.SetModelType(fromConfig.ModelType) config.SetModelType(fromConfig.ModelType)
...@@ -456,15 +481,21 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars ...@@ -456,15 +481,21 @@ func CreateModel(ctx context.Context, name, modelFileDir string, commands []pars
defer bin.Close() defer bin.Close()
var offset int64 var offset int64
CREATE:
for { for {
fn(api.ProgressResponse{Status: "creating model layer"}) fn(api.ProgressResponse{Status: "creating model layer"})
bin.Seek(offset, io.SeekStart) bin.Seek(offset, io.SeekStart)
ggml, err := llm.DecodeGGML(bin) ggml, err := llm.DecodeGGML(bin)
if errors.Is(err, io.EOF) { if err != nil {
break switch {
} else if err != nil { case errors.Is(err, io.EOF):
return err break CREATE
case errors.Is(err, llm.ErrUnsupportedFormat):
return fmt.Errorf("model binary specified in FROM field is not a valid gguf format model, %w", err)
default:
return err
}
} }
config.SetModelFormat(ggml.Name()) config.SetModelFormat(ggml.Name())
......
server/llm_image_test.go 0 → 100644
View file @ 96fb441a
package server
import (
"context"
"encoding/base64"
"log"
"os"
"strings"
"testing"
"time"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llm"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestIntegrationMultimodal(t *testing.T) {
SkipIFNoTestData(t)
image, err := base64.StdEncoding.DecodeString(imageEncoding)
require.NoError(t, err)
req := api.GenerateRequest{
Model: "llava:7b",
Prompt: "what does the text in this image say?",
Options: map[string]interface{}{},
Images: []api.ImageData{
image,
},
}
resp := "the ollamas"
workDir, err := os.MkdirTemp("", "ollama")
require.NoError(t, err)
defer os.RemoveAll(workDir)
require.NoError(t, llm.Init(workDir))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
defer cancel()
opts := api.DefaultOptions()
opts.Seed = 42
opts.Temperature = 0.0
model, llmRunner := PrepareModelForPrompts(t, req.Model, opts)
defer llmRunner.Close()
response := OneShotPromptResponse(t, ctx, req, model, llmRunner)
log.Print(response)
assert.Contains(t, strings.ToLower(response), resp)
}
const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb
AAUAAAABAAAAUgEoAAMAAAABAAIAAIdpAAQAAAABAAAAWgAAAAAAAABIAAAAAQAAAEgAAAABAAOgAQADAAAAAQABAACgAgAEAAAAAQAAANKgAwAEAAAAAQAA
AHgAAAAAXdsepgAAAAlwSFlzAAALEwAACxMBAJqcGAAAAVlpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6
bWV0YS8iIHg6eG1wdGs9IlhNUCBDb3JlIDYuMC4wIj4KICAgPHJkZjpSREYgeG1sbnM6cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1z
eW50YXgtbnMjIj4KICAgICAgPHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9IiIKICAgICAgICAgICAgeG1sbnM6dGlmZj0iaHR0cDovL25zLmFkb2JlLmNv
bS90aWZmLzEuMC8iPgogICAgICAgICA8dGlmZjpPcmllbnRhdGlvbj4xPC90aWZmOk9yaWVudGF0aW9uPgogICAgICA8L3JkZjpEZXNjcmlwdGlvbj4KICAg
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server/llm_test.go 0 → 100644
View file @ 96fb441a
package server
import (
"context"
"os"
"strings"
"sync"
"testing"
"time"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llm"
)
// TODO - this would ideally be in the llm package, but that would require some refactoring of interfaces in the server
// package to avoid circular dependencies
// WARNING - these tests will fail on mac if you don't manually copy ggml-metal.metal to this dir (./server)
//
// TODO - Fix this ^^
var (
req = [2]api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "tell me a short story about agi?",
Options: map[string]interface{}{},
}, {
Model: "orca-mini",
Prompt: "what is the origin of the us thanksgiving holiday?",
Options: map[string]interface{}{},
},
}
resp = [2]string{
"once upon a time",
"united states thanksgiving",
}
)
func TestIntegrationSimpleOrcaMini(t *testing.T) {
SkipIFNoTestData(t)
workDir, err := os.MkdirTemp("", "ollama")
require.NoError(t, err)
defer os.RemoveAll(workDir)
require.NoError(t, llm.Init(workDir))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
defer cancel()
opts := api.DefaultOptions()
opts.Seed = 42
opts.Temperature = 0.0
model, llmRunner := PrepareModelForPrompts(t, req[0].Model, opts)
defer llmRunner.Close()
response := OneShotPromptResponse(t, ctx, req[0], model, llmRunner)
assert.Contains(t, strings.ToLower(response), resp[0])
}
// TODO
// The server always loads a new runner and closes the old one, which forces serial execution
// At present this test case fails with concurrency problems. Eventually we should try to
// get true concurrency working with n_parallel support in the backend
func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
SkipIFNoTestData(t)
t.Skip("concurrent prediction on single runner not currently supported")
workDir, err := os.MkdirTemp("", "ollama")
require.NoError(t, err)
defer os.RemoveAll(workDir)
require.NoError(t, llm.Init(workDir))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
defer cancel()
opts := api.DefaultOptions()
opts.Seed = 42
opts.Temperature = 0.0
var wg sync.WaitGroup
wg.Add(len(req))
model, llmRunner := PrepareModelForPrompts(t, req[0].Model, opts)
defer llmRunner.Close()
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
response := OneShotPromptResponse(t, ctx, req[i], model, llmRunner)
t.Logf("Prompt: %s\nResponse: %s", req[0].Prompt, response)
assert.Contains(t, strings.ToLower(response), resp[i], "error in thread %d (%s)", i, req[i].Prompt)
}(i)
}
wg.Wait()
}
func TestIntegrationConcurrentRunnersOrcaMini(t *testing.T) {
SkipIFNoTestData(t)
workDir, err := os.MkdirTemp("", "ollama")
require.NoError(t, err)
defer os.RemoveAll(workDir)
require.NoError(t, llm.Init(workDir))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
defer cancel()
opts := api.DefaultOptions()
opts.Seed = 42
opts.Temperature = 0.0
var wg sync.WaitGroup
wg.Add(len(req))
t.Logf("Running %d concurrently", len(req))
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
model, llmRunner := PrepareModelForPrompts(t, req[0].Model, opts)
defer llmRunner.Close()
response := OneShotPromptResponse(t, ctx, req[i], model, llmRunner)
t.Logf("Prompt: %s\nResponse: %s", req[0].Prompt, response)
assert.Contains(t, strings.ToLower(response), resp[i], "error in thread %d (%s)", i, req[i].Prompt)
}(i)
}
wg.Wait()
}
// TODO - create a parallel test with 2 different models once we support concurrency
server/llm_utils_test.go 0 → 100644
View file @ 96fb441a
package server
import (
"context"
"errors"
"os"
"path"
"runtime"
"testing"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llm"
"github.com/stretchr/testify/require"
)
func SkipIFNoTestData(t *testing.T) {
modelDir := getModelDir()
if _, err := os.Stat(modelDir); errors.Is(err, os.ErrNotExist) {
t.Skipf("%s does not exist - skipping integration tests", modelDir)
}
}
func getModelDir() string {
_, filename, _, _ := runtime.Caller(0)
return path.Dir(path.Dir(filename) + "/../test_data/models/.")
}
func PrepareModelForPrompts(t *testing.T, modelName string, opts api.Options) (*Model, llm.LLM) {
modelDir := getModelDir()
os.Setenv("OLLAMA_MODELS", modelDir)
model, err := GetModel(modelName)
require.NoError(t, err, "GetModel ")
err = opts.FromMap(model.Options)
require.NoError(t, err, "opts from model ")
runner, err := llm.New("unused", model.ModelPath, model.AdapterPaths, model.ProjectorPaths, opts)
require.NoError(t, err, "llm.New failed")
return model, runner
}
func OneShotPromptResponse(t *testing.T, ctx context.Context, req api.GenerateRequest, model *Model, runner llm.LLM) string {
prompt, err := model.Prompt(PromptVars{
System: req.System,
Prompt: req.Prompt,
First: len(req.Context) == 0,
})
require.NoError(t, err, "prompt generation failed")
success := make(chan bool, 1)
response := ""
cb := func(r llm.PredictResult) {
if !r.Done {
response += r.Content
} else {
success <- true
}
}
predictReq := llm.PredictOpts{
Prompt: prompt,
Format: req.Format,
Images: req.Images,
}
err = runner.Predict(ctx, predictReq, cb)
require.NoError(t, err, "predict call failed")
select {
case <-ctx.Done():
t.Errorf("failed to complete before timeout: \n%s", response)
return ""
case <-success:
return response
}
}
server/routes.go
View file @ 96fb441a
...@@ -25,6 +25,7 @@ import ( ...@@ -25,6 +25,7 @@ import (
"github.com/gin-gonic/gin" "github.com/gin-gonic/gin"
"github.com/jmorganca/ollama/api" "github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/gpu"
"github.com/jmorganca/ollama/llm" "github.com/jmorganca/ollama/llm"
"github.com/jmorganca/ollama/parser" "github.com/jmorganca/ollama/parser"
"github.com/jmorganca/ollama/version" "github.com/jmorganca/ollama/version"
...@@ -81,20 +82,6 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess ...@@ -81,20 +82,6 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess
return nil, err return nil, err
} }
ctx := c.Request.Context()
// check if the loaded model is still running in a subprocess, in case something unexpected happened
if loaded.runner != nil {
if err := loaded.runner.Ping(ctx); err != nil {
log.Print("loaded llm process not responding, closing now")
// the subprocess is no longer running, so close it
loaded.runner.Close()
loaded.runner = nil
loaded.Model = nil
loaded.Options = nil
}
}
needLoad := loaded.runner == nil || // is there a model loaded? needLoad := loaded.runner == nil || // is there a model loaded?
loaded.ModelPath != model.ModelPath || // has the base model changed? loaded.ModelPath != model.ModelPath || // has the base model changed?
!reflect.DeepEqual(loaded.AdapterPaths, model.AdapterPaths) || // have the adapters changed? !reflect.DeepEqual(loaded.AdapterPaths, model.AdapterPaths) || // have the adapters changed?
...@@ -114,7 +101,7 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess ...@@ -114,7 +101,7 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess
// some older models are not compatible with newer versions of llama.cpp // some older models are not compatible with newer versions of llama.cpp
// show a generalized compatibility error until there is a better way to // show a generalized compatibility error until there is a better way to
// check for model compatibility // check for model compatibility
if strings.Contains(err.Error(), "failed to load model") { if errors.Is(llm.ErrUnsupportedFormat, err) || strings.Contains(err.Error(), "failed to load model") {
err = fmt.Errorf("%v: this model may be incompatible with your version of Ollama. If you previously pulled this model, try updating it by running `ollama pull %s`", err, model.ShortName) err = fmt.Errorf("%v: this model may be incompatible with your version of Ollama. If you previously pulled this model, try updating it by running `ollama pull %s`", err, model.ShortName)
} }
...@@ -126,10 +113,6 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess ...@@ -126,10 +113,6 @@ func load(c *gin.Context, modelName string, reqOpts map[string]interface{}, sess
loaded.Options = &opts loaded.Options = &opts
} }
// update options for the loaded llm
// TODO(mxyng): this isn't thread safe, but it should be fine for now
loaded.runner.SetOptions(opts)
loaded.expireAt = time.Now().Add(sessionDuration) loaded.expireAt = time.Now().Add(sessionDuration)
if loaded.expireTimer == nil { if loaded.expireTimer == nil {
...@@ -909,9 +892,12 @@ func Serve(ln net.Listener) error { ...@@ -909,9 +892,12 @@ func Serve(ln net.Listener) error {
os.Exit(0) os.Exit(0)
}() }()
if runtime.GOOS == "linux" { if err := llm.Init(s.WorkDir); err != nil {
return fmt.Errorf("unable to initialize llm library %w", err)
}
if runtime.GOOS == "linux" { // TODO - windows too
// check compatibility to log warnings // check compatibility to log warnings
if _, err := llm.CheckVRAM(); err != nil { if _, err := gpu.CheckVRAM(); err != nil {
log.Print(err.Error()) log.Print(err.Error())
} }
} }
......
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