ollama/llm/server.go
2024-04-10 11:37:20 -07:00

850 lines
22 KiB
Go

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) {
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
}
memoryAvailable, _ := gpu.CheckVRAM()
info := gpu.GetGPUInfo()
memoryMinimum := info.MinimumMemory
for _, projector := range projectors {
memoryMinimum += 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
var kv uint64 = 2 * 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * ggml.KV().EmbeddingLength() / ggml.KV().HeadCount() * ggml.KV().HeadCountKV()
graphPartialOffload, graphFullOffload := ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)))
if graphPartialOffload == 0 {
graphPartialOffload = ggml.KV().GQA() * kv / 6
}
if graphFullOffload == 0 {
graphFullOffload = graphPartialOffload
}
// memoryRequiredTotal represents the memory required for full GPU offloading (all layers)
memoryRequiredTotal := memoryMinimum + graphFullOffload
// memoryRequiredPartial represents the memory required for partial GPU offloading (n > 0, n < layers)
memoryRequiredPartial := memoryMinimum + graphPartialOffload
if info.Library != "metal" {
if memoryRequiredPartial > memoryAvailable || slices.Contains(cpuOnlyFamilies, ggml.KV().Architecture()) {
info.Library = "cpu"
}
}
var layerCount int
layers := ggml.Tensors().Layers()
for i := 0; i < int(ggml.KV().BlockCount()); i++ {
memoryLayer := layers[fmt.Sprintf("%d", i)].size()
// KV is proportional to the number of layers
memoryLayer += kv / ggml.KV().BlockCount()
memoryRequiredTotal += memoryLayer
if memoryAvailable > memoryRequiredPartial+memoryLayer {
memoryRequiredPartial += memoryLayer
layerCount++
}
}
memoryLayerOutput := layers["output"].size()
memoryRequiredTotal += memoryLayerOutput
if memoryAvailable > memoryRequiredTotal {
layerCount = int(ggml.KV().BlockCount()) + 1
memoryRequiredPartial = memoryRequiredTotal
}
if opts.NumGPU < 0 {
opts.NumGPU = layerCount
}
slog.Info(
"offload to gpu",
"reallayers", opts.NumGPU,
"layers", layerCount,
"required", format.HumanBytes2(memoryRequiredTotal),
"used", format.HumanBytes2(memoryRequiredPartial),
"available", format.HumanBytes2(memoryAvailable),
"kv", format.HumanBytes2(kv),
"fulloffload", format.HumanBytes2(graphFullOffload),
"partialoffload", format.HumanBytes2(graphPartialOffload),
)
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 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) uint64 {
file, err := os.Open(filename)
if err != nil {
return 0
}
defer file.Close()
ggml, _, err := DecodeGGML(file)
if err != nil {
return 0
}
var mem uint64
for _, layer := range ggml.Tensors().Layers() {
mem += layer.size()
}
return mem
}
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()
// TODO we need to wire up a better way to detect hangs during model load and startup of the server
expiresAt := time.Now().Add(10 * 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
}