mirror of
https://github.com/ollama/ollama.git
synced 2025-05-10 18:06:33 +02:00
This provides integration with the new Ollama engine
(5824541
next ollama runner (#7913)) and the rest of the Ollama
infrastructure such as the runner and Ollama server.
In addition, it also builds out the KV cache infrastructure to
support requirements of how Ollama runs models such as:
- Parallel processing
- Memory management for defragmentation and shifting
- Multi-modal modals
Both old and new engines continue to be supported. By default, only
the old engine is used. To enable the new engine:
Start the server with the OLLAMA_NEW_ENGINE environment variable set:
OLLAMA_NEW_ENGINE=1 ./ollama serve
Start a model that is supported by the Ollama engine. This one is Llama 3.1 8b Q4_K_M:
./ollama run jessegross/llama3.1
1124 lines
32 KiB
Go
1124 lines
32 KiB
Go
package llm
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import (
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"bufio"
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"bytes"
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"io"
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"log"
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"log/slog"
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"math/rand"
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"net"
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"net/http"
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"os"
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"os/exec"
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"path/filepath"
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"runtime"
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"strconv"
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"strings"
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"sync"
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"time"
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"golang.org/x/sync/semaphore"
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"github.com/ollama/ollama/api"
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"github.com/ollama/ollama/discover"
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"github.com/ollama/ollama/envconfig"
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"github.com/ollama/ollama/format"
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"github.com/ollama/ollama/fs/ggml"
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"github.com/ollama/ollama/llama"
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)
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type LlamaServer interface {
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Ping(ctx context.Context) error
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WaitUntilRunning(ctx context.Context) error
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Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error
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Embedding(ctx context.Context, input string) ([]float32, error)
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Tokenize(ctx context.Context, content string) ([]int, error)
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Detokenize(ctx context.Context, tokens []int) (string, error)
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Close() error
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EstimatedVRAM() uint64 // Total VRAM across all GPUs
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EstimatedTotal() uint64
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EstimatedVRAMByGPU(gpuID string) uint64
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}
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// llmServer is an instance of the llama.cpp server
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type llmServer struct {
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port int
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cmd *exec.Cmd
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done chan error // Channel to signal when the process exits
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status *StatusWriter
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options api.Options
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numParallel int
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modelPath string
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modelLock sync.Mutex // Temporary until we switch fully to Go server
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model *llama.Model // If non-nil, the runner is a new Go server
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estimate MemoryEstimate
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totalLayers uint64
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// gpuCount int
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gpus discover.GpuInfoList // Recorded just before the model loaded, free space will be incorrect
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loadDuration time.Duration // Record how long it took the model to load
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loadProgress float32
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sem *semaphore.Weighted
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}
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// LoadModel will load a model from disk. The model must be in the GGML format.
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//
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// It collects array values for arrays with a size less than or equal to
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// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
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// the maxArraySize is negative, all arrays are collected.
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func LoadModel(model string, maxArraySize int) (*ggml.GGML, error) {
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if _, err := os.Stat(model); err != nil {
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return nil, err
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}
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f, err := os.Open(model)
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if err != nil {
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return nil, err
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}
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defer f.Close()
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ggml, _, err := ggml.Decode(f, maxArraySize)
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return ggml, err
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}
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// NewLlamaServer will run a server for the given GPUs
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// The gpu list must be a single family.
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func NewLlamaServer(gpus discover.GpuInfoList, model string, f *ggml.GGML, adapters, projectors []string, opts api.Options, numParallel int) (LlamaServer, error) {
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systemInfo := discover.GetSystemInfo()
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systemTotalMemory := systemInfo.System.TotalMemory
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systemFreeMemory := systemInfo.System.FreeMemory
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systemSwapFreeMemory := systemInfo.System.FreeSwap
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slog.Info("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
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// If the user wants zero GPU layers, reset the gpu list to be CPU/system ram info
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if opts.NumGPU == 0 {
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gpus = discover.GetCPUInfo()
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}
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estimate := EstimateGPULayers(gpus, f, projectors, opts)
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if len(gpus) > 1 || gpus[0].Library != "cpu" {
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switch {
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case gpus[0].Library == "metal" && estimate.VRAMSize > systemTotalMemory:
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// disable partial offloading when model is greater than total system memory as this
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// can lead to locking up the system
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opts.NumGPU = 0
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case gpus[0].Library != "metal" && estimate.Layers == 0:
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// Don't bother loading into the GPU if no layers can fit
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gpus = discover.GetCPUInfo()
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case opts.NumGPU < 0 && estimate.Layers > 0 && gpus[0].Library != "cpu":
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opts.NumGPU = estimate.Layers
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}
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}
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// On linux and windows, over-allocating CPU memory will almost always result in an error
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// Darwin has fully dynamic swap so has no direct concept of free swap space
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if runtime.GOOS != "darwin" {
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systemMemoryRequired := estimate.TotalSize - estimate.VRAMSize
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available := systemFreeMemory + systemSwapFreeMemory
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if systemMemoryRequired > available {
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slog.Warn("model request too large for system", "requested", format.HumanBytes2(systemMemoryRequired), "available", available, "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "swap", format.HumanBytes2(systemSwapFreeMemory))
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return nil, fmt.Errorf("model requires more system memory (%s) than is available (%s)", format.HumanBytes2(systemMemoryRequired), format.HumanBytes2(available))
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}
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}
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slog.Info("offload", "", estimate)
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params := []string{
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"--model", model,
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"--ctx-size", strconv.Itoa(opts.NumCtx),
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"--batch-size", strconv.Itoa(opts.NumBatch),
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}
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if opts.NumGPU >= 0 {
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params = append(params, "--n-gpu-layers", strconv.Itoa(opts.NumGPU))
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}
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if envconfig.Debug() {
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params = append(params, "--verbose")
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}
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if opts.MainGPU > 0 {
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params = append(params, "--main-gpu", strconv.Itoa(opts.MainGPU))
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}
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if len(adapters) > 0 {
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for _, adapter := range adapters {
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params = append(params, "--lora", adapter)
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}
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}
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if len(projectors) > 0 {
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// TODO: applying multiple projectors is not supported by the llama.cpp server yet
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params = append(params, "--mmproj", projectors[0])
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}
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defaultThreads := systemInfo.GetOptimalThreadCount()
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if opts.NumThread > 0 {
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params = append(params, "--threads", strconv.Itoa(opts.NumThread))
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} else if defaultThreads > 0 {
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params = append(params, "--threads", strconv.Itoa(defaultThreads))
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}
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fa := envconfig.FlashAttention()
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if fa && !gpus.FlashAttentionSupported() {
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slog.Warn("flash attention enabled but not supported by gpu")
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fa = false
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}
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if fa && !f.SupportsFlashAttention() {
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slog.Warn("flash attention enabled but not supported by model")
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fa = false
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}
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kvct := strings.ToLower(envconfig.KvCacheType())
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if fa {
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slog.Info("enabling flash attention")
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params = append(params, "--flash-attn")
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// Flash Attention also supports kv cache quantization
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// Enable if the requested and kv cache type is supported by the model
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if kvct != "" && f.SupportsKVCacheType(kvct) {
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params = append(params, "--kv-cache-type", kvct)
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} else {
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slog.Warn("kv cache type not supported by model", "type", kvct)
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}
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} else if kvct != "" && kvct != "f16" {
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slog.Warn("quantized kv cache requested but flash attention disabled", "type", kvct)
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}
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// mmap has issues with partial offloading on metal
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for _, g := range gpus {
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if g.Library == "metal" &&
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uint64(opts.NumGPU) > 0 &&
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uint64(opts.NumGPU) < f.KV().BlockCount()+1 {
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opts.UseMMap = new(bool)
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*opts.UseMMap = false
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}
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}
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// Windows CUDA should not use mmap for best performance
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// Linux with a model larger than free space, mmap leads to thrashing
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// For CPU loads we want the memory to be allocated, not FS cache
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if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == nil) ||
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(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == nil) ||
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(gpus[0].Library == "cpu" && opts.UseMMap == nil) ||
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(opts.UseMMap != nil && !*opts.UseMMap) {
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params = append(params, "--no-mmap")
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}
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if opts.UseMLock {
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params = append(params, "--mlock")
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}
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// TODO - NUMA support currently doesn't work properly
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params = append(params, "--parallel", strconv.Itoa(numParallel))
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if estimate.TensorSplit != "" {
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params = append(params, "--tensor-split", estimate.TensorSplit)
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}
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if envconfig.MultiUserCache() {
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params = append(params, "--multiuser-cache")
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}
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libs := make(map[string]string)
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if entries, err := os.ReadDir(discover.LibOllamaPath); err == nil {
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for _, entry := range entries {
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libs[entry.Name()] = filepath.Join(discover.LibOllamaPath, entry.Name())
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}
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}
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lib := gpus[0].RunnerName()
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requested := envconfig.LLMLibrary()
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if libs[requested] != "" {
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slog.Info("using requested gpu library", "requested", requested)
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lib = requested
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}
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var compatible []string
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for k := range libs {
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// exact match first
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if k == lib {
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compatible = append([]string{k}, compatible...)
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continue
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}
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// then match the family (e.g. 'cuda')
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if strings.Split(k, "_")[0] == strings.Split(lib, "_")[0] {
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compatible = append(compatible, k)
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}
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}
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slog.Debug("compatible gpu libraries", "compatible", compatible)
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// iterate through compatible GPU libraries such as 'cuda_v12', 'cuda_v11', 'rocm', etc.
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// adding each library's respective path to the LD_LIBRARY_PATH, until finally running
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// without any LD_LIBRARY_PATH flags
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for {
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port := 0
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if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
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var l *net.TCPListener
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if l, err = net.ListenTCP("tcp", a); err == nil {
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port = l.Addr().(*net.TCPAddr).Port
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l.Close()
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}
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}
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if port == 0 {
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slog.Debug("ResolveTCPAddr failed, using random port")
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port = rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range
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}
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finalParams := []string{"runner"}
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if envconfig.NewEngine() {
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finalParams = append(finalParams, "--ollama-engine")
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}
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finalParams = append(finalParams, params...)
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finalParams = append(finalParams, "--port", strconv.Itoa(port))
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var pathEnv string
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switch runtime.GOOS {
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case "windows":
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pathEnv = "PATH"
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case "darwin":
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pathEnv = "DYLD_LIBRARY_PATH"
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default:
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pathEnv = "LD_LIBRARY_PATH"
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}
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var libraryPaths []string
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if libraryPath, ok := os.LookupEnv(pathEnv); ok {
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libraryPaths = append(libraryPaths, filepath.SplitList(libraryPath)...)
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}
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if len(compatible) > 0 {
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c := compatible[0]
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if libpath, ok := libs[c]; ok {
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slog.Debug("adding gpu library", "path", libpath)
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libraryPaths = append(libraryPaths, libpath)
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}
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}
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// Note: we always put the dependency path first
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// since this was the exact version we compiled/linked against
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if gpus[0].DependencyPath != nil {
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slog.Debug("adding gpu dependency paths", "paths", gpus[0].DependencyPath)
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// assume gpus from the same library have the same dependency path
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libraryPaths = append(gpus[0].DependencyPath, libraryPaths...)
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}
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// finally, add the root library path
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libraryPaths = append(libraryPaths, discover.LibOllamaPath)
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exe, err := os.Executable()
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if err != nil {
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return nil, fmt.Errorf("unable to lookup executable path: %w", err)
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}
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exe, err = filepath.EvalSymlinks(exe)
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if err != nil {
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return nil, fmt.Errorf("unable to evaluate symlinks for executable path: %w", err)
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}
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// TODO - once fully switched to the Go runner, load the model here for tokenize/detokenize cgo access
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s := &llmServer{
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port: port,
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cmd: exec.Command(exe, finalParams...),
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status: NewStatusWriter(os.Stderr),
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options: opts,
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modelPath: model,
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estimate: estimate,
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numParallel: numParallel,
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sem: semaphore.NewWeighted(int64(numParallel)),
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totalLayers: f.KV().BlockCount() + 1,
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gpus: gpus,
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done: make(chan error, 1),
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}
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s.cmd.Env = os.Environ()
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s.cmd.Stdout = os.Stdout
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s.cmd.Stderr = s.status
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s.cmd.SysProcAttr = LlamaServerSysProcAttr
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envWorkarounds := [][2]string{}
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for _, gpu := range gpus {
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envWorkarounds = append(envWorkarounds, gpu.EnvWorkarounds...)
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}
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visibleDevicesEnv, visibleDevicesEnvVal := gpus.GetVisibleDevicesEnv()
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pathEnvVal := strings.Join(libraryPaths, string(filepath.ListSeparator))
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// Update or add the path and visible devices variable with our adjusted version
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pathNeeded := true
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devicesNeeded := visibleDevicesEnv != ""
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for i := range s.cmd.Env {
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cmp := strings.SplitN(s.cmd.Env[i], "=", 2)
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if strings.EqualFold(cmp[0], pathEnv) {
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s.cmd.Env[i] = pathEnv + "=" + pathEnvVal
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pathNeeded = false
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} else if devicesNeeded && strings.EqualFold(cmp[0], visibleDevicesEnv) {
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s.cmd.Env[i] = visibleDevicesEnv + "=" + visibleDevicesEnvVal
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devicesNeeded = false
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} else if len(envWorkarounds) != 0 {
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for _, kv := range envWorkarounds {
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if strings.EqualFold(cmp[0], kv[0]) {
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s.cmd.Env[i] = kv[0] + "=" + kv[1]
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}
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}
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}
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}
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if pathNeeded {
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s.cmd.Env = append(s.cmd.Env, pathEnv+"="+pathEnvVal)
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}
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if devicesNeeded {
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s.cmd.Env = append(s.cmd.Env, visibleDevicesEnv+"="+visibleDevicesEnvVal)
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}
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slog.Info("starting llama server", "cmd", s.cmd.String())
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if envconfig.Debug() {
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filteredEnv := []string{}
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for _, ev := range s.cmd.Env {
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if strings.HasPrefix(ev, "CUDA_") ||
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strings.HasPrefix(ev, "ROCR_") ||
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strings.HasPrefix(ev, "ROCM_") ||
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strings.HasPrefix(ev, "HIP_") ||
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strings.HasPrefix(ev, "GPU_") ||
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strings.HasPrefix(ev, "HSA_") ||
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strings.HasPrefix(ev, "GGML_") ||
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strings.HasPrefix(ev, "PATH=") ||
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strings.HasPrefix(ev, "LD_LIBRARY_PATH=") ||
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strings.HasPrefix(ev, "DYLD_LIBRARY_PATH=") {
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filteredEnv = append(filteredEnv, ev)
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}
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}
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// Log at debug as the environment is inherited and might contain sensitive information
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slog.Debug("subprocess", "environment", filteredEnv)
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}
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if err = s.cmd.Start(); err != nil {
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var msg string
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if s.status != nil && s.status.LastErrMsg != "" {
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msg = s.status.LastErrMsg
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}
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err := fmt.Errorf("error starting runner: %v %s", err, msg)
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if len(compatible) == 0 {
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return nil, err
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}
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slog.Warn("unable to start runner with compatible gpu", "error", err, "compatible", compatible)
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compatible = compatible[1:]
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continue
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}
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// reap subprocess when it exits
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go func() {
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err := s.cmd.Wait()
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// Favor a more detailed message over the process exit status
|
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if err != nil && s.status != nil && s.status.LastErrMsg != "" {
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slog.Error("llama runner terminated", "error", err)
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if strings.Contains(s.status.LastErrMsg, "unknown model") {
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s.status.LastErrMsg = "this model is not supported by your version of Ollama. You may need to upgrade"
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}
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s.done <- errors.New(s.status.LastErrMsg)
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} else {
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s.done <- err
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}
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}()
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return s, nil
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}
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}
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type ServerStatus int
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|
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const ( // iota is reset to 0
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ServerStatusReady ServerStatus = iota
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ServerStatusNoSlotsAvailable
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ServerStatusLoadingModel
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ServerStatusNotResponding
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ServerStatusError
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)
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func (s ServerStatus) ToString() string {
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switch s {
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case ServerStatusReady:
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return "llm server ready"
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case ServerStatusNoSlotsAvailable:
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return "llm busy - no slots available"
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case ServerStatusLoadingModel:
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return "llm server loading model"
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case ServerStatusNotResponding:
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return "llm server not responding"
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default:
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return "llm server error"
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}
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}
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|
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type ServerStatusResp struct {
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Status string `json:"status"`
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SlotsIdle int `json:"slots_idle"`
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SlotsProcessing int `json:"slots_processing"`
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Error string `json:"error"`
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Progress float32 `json:"progress"`
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}
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|
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func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
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// Fail fast if its exited
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if s.cmd.ProcessState != nil {
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msg := ""
|
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if s.status != nil && s.status.LastErrMsg != "" {
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msg = s.status.LastErrMsg
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}
|
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if s.cmd.ProcessState.ExitCode() == -1 {
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// Most likely a signal killed it, log some more details to try to help troubleshoot
|
|
slog.Warn("llama runner process no longer running", "sys", s.cmd.ProcessState.Sys(), "string", s.cmd.ProcessState.String())
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}
|
|
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, errors.New("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 ServerStatusNoSlotsAvailable, nil
|
|
case "loading model":
|
|
s.loadProgress = status.Progress
|
|
return ServerStatusLoadingModel, nil
|
|
default:
|
|
return ServerStatusError, fmt.Errorf("server error: %+v", status)
|
|
}
|
|
}
|
|
|
|
// getServerStatusRetry will retry if ServerStatusNoSlotsAvailable is received
|
|
func (s *llmServer) getServerStatusRetry(ctx context.Context) (ServerStatus, error) {
|
|
var retries int
|
|
for {
|
|
status, err := s.getServerStatus(ctx)
|
|
if err != nil {
|
|
return status, err
|
|
}
|
|
|
|
if status == ServerStatusNoSlotsAvailable {
|
|
if retries >= 10 {
|
|
return status, fmt.Errorf("no slots available after %d retries", retries)
|
|
}
|
|
|
|
time.Sleep(5 * time.Millisecond)
|
|
retries++
|
|
continue
|
|
}
|
|
|
|
return status, nil
|
|
}
|
|
}
|
|
|
|
func (s *llmServer) Ping(ctx context.Context) error {
|
|
_, err := s.getServerStatus(ctx)
|
|
if err != nil {
|
|
slog.Debug("server unhealthy", "error", err)
|
|
return err
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
|
|
start := time.Now()
|
|
stallDuration := envconfig.LoadTimeout() // If no progress happens
|
|
stallTimer := time.Now().Add(stallDuration) // give up if we stall
|
|
|
|
slog.Info("waiting for llama runner to start responding")
|
|
var lastStatus ServerStatus = -1
|
|
fullyLoaded := false
|
|
|
|
for {
|
|
select {
|
|
case <-ctx.Done():
|
|
slog.Warn("client connection closed before server finished loading, aborting load")
|
|
return fmt.Errorf("timed out waiting for llama runner to start: %w", ctx.Err())
|
|
case err := <-s.done:
|
|
return fmt.Errorf("llama runner process has terminated: %w", err)
|
|
default:
|
|
}
|
|
if time.Now().After(stallTimer) {
|
|
// timeout
|
|
msg := ""
|
|
if s.status != nil && s.status.LastErrMsg != "" {
|
|
msg = s.status.LastErrMsg
|
|
}
|
|
return fmt.Errorf("timed out waiting for llama runner to start - progress %0.2f - %s", s.loadProgress, 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(ctx, 200*time.Millisecond)
|
|
defer cancel()
|
|
priorProgress := s.loadProgress
|
|
status, _ := s.getServerStatus(ctx)
|
|
if lastStatus != status && status != ServerStatusReady {
|
|
// Only log on status changes
|
|
slog.Info("waiting for server to become available", "status", status.ToString())
|
|
}
|
|
switch status {
|
|
case ServerStatusReady:
|
|
s.loadDuration = time.Since(start)
|
|
slog.Info(fmt.Sprintf("llama runner started in %0.2f seconds", s.loadDuration.Seconds()))
|
|
return nil
|
|
default:
|
|
lastStatus = status
|
|
// Reset the timer as long as we're making forward progress on the load
|
|
if priorProgress != s.loadProgress {
|
|
slog.Debug(fmt.Sprintf("model load progress %0.2f", s.loadProgress))
|
|
stallTimer = time.Now().Add(stallDuration)
|
|
} else if !fullyLoaded && int(s.loadProgress*100.0) >= 100 {
|
|
slog.Debug("model load completed, waiting for server to become available", "status", status.ToString())
|
|
stallTimer = time.Now().Add(stallDuration)
|
|
fullyLoaded = true
|
|
}
|
|
time.Sleep(time.Millisecond * 250)
|
|
continue
|
|
}
|
|
}
|
|
}
|
|
|
|
var grammarJSON = `
|
|
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 ::=
|
|
"\"" (
|
|
[^"\\\x7F\x00-\x1F] |
|
|
"\\" (["\\/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
|
|
|
|
type ImageData struct {
|
|
Data []byte `json:"data"`
|
|
ID int `json:"id"`
|
|
AspectRatioID int `json:"aspect_ratio_id"`
|
|
}
|
|
|
|
type completion struct {
|
|
Content string `json:"content"`
|
|
Model string `json:"model"`
|
|
Prompt string `json:"prompt"`
|
|
Stop bool `json:"stop"`
|
|
StoppedLimit bool `json:"stopped_limit"`
|
|
|
|
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 json.RawMessage
|
|
Images []ImageData
|
|
Options *api.Options
|
|
}
|
|
|
|
type CompletionResponse struct {
|
|
Content string
|
|
DoneReason string
|
|
Done bool
|
|
PromptEvalCount int
|
|
PromptEvalDuration time.Duration
|
|
EvalCount int
|
|
EvalDuration time.Duration
|
|
}
|
|
|
|
func (s *llmServer) 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,
|
|
"min_p": req.Options.MinP,
|
|
"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,
|
|
"seed": req.Options.Seed,
|
|
"stop": req.Options.Stop,
|
|
"image_data": req.Images,
|
|
"cache_prompt": true,
|
|
}
|
|
|
|
if len(req.Format) > 0 {
|
|
switch string(req.Format) {
|
|
case `null`, `""`:
|
|
// Field was set, but "missing" a value. We accept
|
|
// these as "not set".
|
|
break
|
|
case `"json"`:
|
|
request["grammar"] = grammarJSON
|
|
default:
|
|
if req.Format[0] != '{' {
|
|
return fmt.Errorf("invalid format: %q; expected \"json\" or a valid JSON Schema object", req.Format)
|
|
}
|
|
|
|
// User provided a JSON schema
|
|
g := llama.SchemaToGrammar(req.Format)
|
|
if g == nil {
|
|
return fmt.Errorf("invalid JSON schema in format")
|
|
}
|
|
request["grammar"] = string(g)
|
|
}
|
|
}
|
|
|
|
if err := s.sem.Acquire(ctx, 1); err != nil {
|
|
if errors.Is(err, context.Canceled) {
|
|
slog.Info("aborting completion request due to client closing the connection")
|
|
} else {
|
|
slog.Error("Failed to acquire semaphore", "error", err)
|
|
}
|
|
return err
|
|
}
|
|
defer s.sem.Release(1)
|
|
|
|
// put an upper limit on num_predict to avoid the model running on forever
|
|
if req.Options.NumPredict < 0 || req.Options.NumPredict > 10*s.options.NumCtx {
|
|
req.Options.NumPredict = 10 * s.options.NumCtx
|
|
}
|
|
|
|
// Make sure the server is ready
|
|
status, err := s.getServerStatusRetry(ctx)
|
|
if err != nil {
|
|
return err
|
|
} else if status != ServerStatusReady {
|
|
return fmt.Errorf("unexpected server status: %s", status.ToString())
|
|
}
|
|
|
|
// 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)
|
|
serverReq, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, buffer)
|
|
if err != nil {
|
|
return fmt.Errorf("error creating POST request: %v", err)
|
|
}
|
|
serverReq.Header.Set("Content-Type", "application/json")
|
|
|
|
res, err := http.DefaultClient.Do(serverReq)
|
|
if err != nil {
|
|
return fmt.Errorf("POST predict: %v", err)
|
|
}
|
|
defer res.Body.Close()
|
|
|
|
if res.StatusCode >= 400 {
|
|
bodyBytes, err := io.ReadAll(res.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(res.Body)
|
|
buf := make([]byte, 0, maxBufferSize)
|
|
scanner.Buffer(buf, maxBufferSize)
|
|
|
|
// 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
|
|
}
|
|
|
|
// slog.Debug("got line", "line", string(line))
|
|
evt, ok := bytes.CutPrefix(line, []byte("data: "))
|
|
if !ok {
|
|
evt = line
|
|
}
|
|
|
|
var c completion
|
|
if err := json.Unmarshal(evt, &c); err != nil {
|
|
return fmt.Errorf("error unmarshalling 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 {
|
|
doneReason := "stop"
|
|
if c.StoppedLimit {
|
|
doneReason = "length"
|
|
}
|
|
|
|
fn(CompletionResponse{
|
|
Done: true,
|
|
DoneReason: doneReason,
|
|
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") || strings.Contains(err.Error(), "forcibly closed") {
|
|
s.Close()
|
|
var msg string
|
|
if s.status != nil && s.status.LastErrMsg != "" {
|
|
msg = s.status.LastErrMsg
|
|
} else {
|
|
msg = err.Error()
|
|
}
|
|
return fmt.Errorf("an error was encountered while running the model: %s", msg)
|
|
}
|
|
|
|
return fmt.Errorf("error reading llm response: %v", err)
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
type EmbeddingRequest struct {
|
|
Content string `json:"content"`
|
|
}
|
|
|
|
type EmbeddingResponse struct {
|
|
Embedding []float32 `json:"embedding"`
|
|
}
|
|
|
|
func (s *llmServer) Embedding(ctx context.Context, input string) ([]float32, error) {
|
|
if err := s.sem.Acquire(ctx, 1); err != nil {
|
|
if errors.Is(err, context.Canceled) {
|
|
slog.Info("aborting embedding request due to client closing the connection")
|
|
} else {
|
|
slog.Error("Failed to acquire semaphore", "error", err)
|
|
}
|
|
return nil, err
|
|
}
|
|
defer s.sem.Release(1)
|
|
|
|
// Make sure the server is ready
|
|
status, err := s.getServerStatusRetry(ctx)
|
|
if err != nil {
|
|
return nil, err
|
|
} else if status != ServerStatusReady {
|
|
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
|
|
}
|
|
|
|
data, err := json.Marshal(EmbeddingRequest{Content: input})
|
|
if err != nil {
|
|
return nil, fmt.Errorf("error marshaling embed data: %w", err)
|
|
}
|
|
|
|
r, 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)
|
|
}
|
|
r.Header.Set("Content-Type", "application/json")
|
|
|
|
resp, err := http.DefaultClient.Do(r)
|
|
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 embedding error: %s", body)
|
|
return nil, fmt.Errorf("%s", body)
|
|
}
|
|
|
|
var e EmbeddingResponse
|
|
if err := json.Unmarshal(body, &e); err != nil {
|
|
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
|
|
}
|
|
|
|
return e.Embedding, nil
|
|
}
|
|
|
|
type TokenizeRequest struct {
|
|
Content string `json:"content"`
|
|
}
|
|
|
|
type TokenizeResponse struct {
|
|
Tokens []int `json:"tokens"`
|
|
}
|
|
|
|
func (s *llmServer) Tokenize(ctx context.Context, content string) ([]int, error) {
|
|
s.modelLock.Lock()
|
|
defer s.modelLock.Unlock()
|
|
if s.model != nil {
|
|
return s.model.Tokenize(content, false, true)
|
|
}
|
|
|
|
// Make sure the server is ready
|
|
status, err := s.getServerStatus(ctx)
|
|
if err != nil {
|
|
return nil, err
|
|
} else if status != ServerStatusReady && status != ServerStatusNoSlotsAvailable {
|
|
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
|
|
}
|
|
|
|
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()
|
|
if resp.StatusCode == http.StatusNotFound {
|
|
if s.model == nil {
|
|
slog.Debug("new runner detected, loading model for cgo tokenization")
|
|
m, err := llama.LoadModelFromFile(s.modelPath, llama.ModelParams{VocabOnly: true})
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
s.model = m
|
|
}
|
|
return s.model.Tokenize(content, false, true)
|
|
}
|
|
|
|
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 *llmServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
|
|
s.modelLock.Lock()
|
|
defer s.modelLock.Unlock()
|
|
if s.model != nil {
|
|
var resp string
|
|
for _, token := range tokens {
|
|
resp += s.model.TokenToPiece(token)
|
|
}
|
|
return resp, nil
|
|
}
|
|
// Make sure the server is ready
|
|
status, err := s.getServerStatus(ctx)
|
|
if err != nil {
|
|
return "", err
|
|
} else if status != ServerStatusReady && status != ServerStatusNoSlotsAvailable {
|
|
return "", fmt.Errorf("unexpected server status: %s", status.ToString())
|
|
}
|
|
|
|
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()
|
|
if resp.StatusCode == http.StatusNotFound {
|
|
if s.model == nil {
|
|
slog.Debug("new runner detected, loading model for cgo tokenization")
|
|
m, err := llama.LoadModelFromFile(s.modelPath, llama.ModelParams{VocabOnly: true})
|
|
if err != nil {
|
|
return "", err
|
|
}
|
|
s.model = m
|
|
}
|
|
var resp string
|
|
for _, token := range tokens {
|
|
resp += s.model.TokenToPiece(token)
|
|
}
|
|
return resp, nil
|
|
}
|
|
|
|
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 *llmServer) Close() error {
|
|
s.modelLock.Lock()
|
|
if s.model != nil {
|
|
llama.FreeModel(s.model)
|
|
s.model = nil
|
|
}
|
|
s.modelLock.Unlock()
|
|
|
|
if s.cmd != nil {
|
|
slog.Debug("stopping llama server")
|
|
if err := s.cmd.Process.Kill(); err != nil {
|
|
return err
|
|
}
|
|
// if ProcessState is already populated, Wait already completed, no need to wait again
|
|
if s.cmd.ProcessState == nil {
|
|
slog.Debug("waiting for llama server to exit")
|
|
<-s.done
|
|
}
|
|
|
|
slog.Debug("llama server stopped")
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
func (s *llmServer) EstimatedVRAM() uint64 {
|
|
return s.estimate.VRAMSize
|
|
}
|
|
|
|
func (s *llmServer) EstimatedTotal() uint64 {
|
|
return s.estimate.TotalSize
|
|
}
|
|
|
|
func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
|
|
for i, gpu := range s.gpus {
|
|
if gpu.ID == gpuID {
|
|
if i < len(s.estimate.GPUSizes) {
|
|
return s.estimate.GPUSizes[i]
|
|
}
|
|
}
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func parseDurationMs(ms float64) time.Duration {
|
|
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
|
|
if err != nil {
|
|
panic(err)
|
|
}
|
|
|
|
return dur
|
|
}
|