mirror of
https://github.com/ollama/ollama.git
synced 2026-07-07 16:21:53 +00:00
* broad lint fixes to sidestep CI scope glitch * runner: Remove CGO engines, use llama-server exclusively for GGML models Remove the vendored GGML and llama.cpp backend, CGO runner, Go model implementations, and sample. llama-server (built from upstream llama.cpp via FetchContent) is now the sole inference engine for GGUF-based models. (Safetensor based models continue to run on the new MLX engine.) This allows us to more rapidly pick up new capabilities and fixes from llama.cpp as they come out. On windows this now requires recent AMD driver versions to support ROCm v7 as llama.cpp currently does not support building against v6. * llama/compat: load Ollama-format GGUFs in llama-server Squashed from upstream/jmorganca/llama-compat on 2026-04-29. Source tip:0c33775d37. Original source commits: -25223160dllama/compat: add in-memory shim so llama-server can load Ollama-format GGUFs -7449b539allm,server: route Ollama-format gemma3 blobs through llama/compat -436f2e2b1llama/compat: make patch-apply idempotent -8c2c9d4c8llama/compat: extend gemma3 handler to cover 1B and 270M blobs -021389f7bllama/compat: shrink clip.cpp injection from 18 lines to 1 -61b367ec2llama/compat: shrink patch to pure call-site hooks (34 -> 20 lines) -36049361cllama/compat: simplify shim (gemma3-tested) -8fa664865llama/compat: add qwen35moe text handler -db0c74530llama/compat: add qwen35moe vision (clip) support -2a388da77llama/compat: split shared infra into a util TU -9a69a17dcllama/compat: document non-public API dependencies -d0f38a915llama/compat: add gpt-oss and lfm2 handlers -086071822llama/compat: add mistral3 text handler (vision TODO) -63bde9ff7llama/compat: add mistral3 vision (clip) support -3a57b89d5llama/compat: apply LLaMA RoPE permute to mistral3 vision Q/K -99cb87439llama/compat: add qwen35, gemma4, deepseek-ocr handlers -2c7850dballama/compat: add nemotron_h_moe handler (latent FFN + MTP skip) -9e3b54225llama/compat: add llama4 text + clip handlers -034fee349llama/compat: add gemma4 clip handler (gemma4v projector) -9945c5a93server: remove dhiltgen/* compat redirect table -5d4539101llama/compat: rewrite gemma4 tokenizer model to BPE -7e0765327llama/compat: add glm-ocr text handler + text-loader load-op hook -f1bd1a25allama/compat: add glm-ocr clip handler (glm4v projector) -4b5cf3420llama/compat: collapse text-loader hook back to one new patch line -eb4ecf4fcllama/compat: extend gemma4 clip handler to gemma4a (audio) -a23a5e76fllama/compat: fix gemma4a per-block norm tensor mapping -cd2dcaff4llama/compat: add embeddinggemma handler -1ce8a6b26llama/compat: add qwen3-vl + qwen2.5-vl handlers -fd98ffa1ellama/compat: add gemma3n + glm4moelite handlers -cc7bdf0bcllama/compat: handle null buft in maybe_load_tensor -0c33775d3llama/compat: disable mmap when load_op transforms text-side tensors * refine implementation * ci: fix windows MLX build * ci: fix windows llama-server build * ci: fix windows rocm build * ci: windows mlx tuning Shorten long-tail on build, and get OllamaSetup.exe back under 2g limit * ci: fix windows dependencies * win: fix dependency gathering * disable openmp * win: arm64 cross-compile build also DRY out CI steps * scheduler improvements * ci: improvements from #15982 * win: favor ninja for faster developer builds * win: fix build * win: fix arm64 cross-compile * win: avoid spaces in compiler path * misc discovery fixes, and bos handling * lint fixes * win: fix arm cross-compile build/CI bugs * llama.cpp update * win: handle multiple CRT dirs * vulkan: add windows iGPU detection * fix creation bugs for patched models, other refactoring work * tune batch size for better performance * ci and lint fixes * fix repeat_last_n bug * build: revamp build for better developer UX * amd, sampler, qwen3next fixes * version bump * fix mlx build * revamp GPU discovery Scanning the output of llama-server is turning out to be too error prone across llama.cpp updates, so this switches to a thin dynamic library load against the bundled GGML libraries so more details can be gathered from the API. * version bump * missing file * ci: fix cache miss on rocm build * refine vulkan dep handling * fix ps reporting bug on full GPU load * improve cmake wiring for customized local builds * version bump * docker build arg cleanup * improve windows exit error logs * fix community gemma4 support and ci flakes * fix mlx unit test * tighten up ps logic to avoid double counting fit log lines * version bump * fix ps view for full gpu layer offload * add MTP wiring for llama-server and create with GGUFs * pick best template by capabilities * version bump * ci: harden apt repos * remove unused cpu core discovery * adjust batch default logic to reduce OOMs * support larger tool calls * fix audio support, template show * qwen35 mtp patch support * flesh out dtypes * rocm deps * version bump * lint fix * block broken gfx1150 on windows * fix qwen3.5 moe mtp tensors in patch * mmproj oom fallback and vulkan on by default * qwen MTP compat fix * version bump * ci: fix WoA cross-compile * ci: workaround ui tool in cross-compile * version bump * win: enable OpenMP for CPU builds * build: improve developer UX * ci: windows path workaround for CPU build * win: fix WoA dependencies * win: fix large offset reads for mmproj patched loads * version bump * fix vulkan dup detection * add OLLAMA_IGPU_ENABLE and largely disable iGPUs by default * opt-in MTP, win large offset, integraton fixes * fix unit test scheduler interaction hang * fix multi-gpu filtering * version bump * review comments * fix thinking level * fix linux rocm ordering and granite 3.3 template * version bump * ci fix - non-shallow MLX checkout * bypass linux sysfs unit test on windows --------- Co-authored-by: jmorganca <jmorganca@gmail.com>
471 lines
13 KiB
Go
471 lines
13 KiB
Go
package imagegen
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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/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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"github.com/ollama/ollama/envconfig"
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"github.com/ollama/ollama/format"
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"github.com/ollama/ollama/llm"
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"github.com/ollama/ollama/ml"
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"github.com/ollama/ollama/x/imagegen/manifest"
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)
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// Server wraps an MLX runner subprocess to implement llm.LlamaServer.
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//
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// This implementation is compatible with Ollama's scheduler and can be loaded/unloaded
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// like any other model. It is used for image generation models.
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type Server struct {
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mu sync.Mutex
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cmd *exec.Cmd
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port int
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modelName string
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vramSize uint64
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done chan error
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client *http.Client
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lastErr string // Last stderr line for error reporting
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lastErrLock sync.Mutex
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}
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// NewServer prepares a new MLX runner server for image generation models.
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// The subprocess is not started until Load() is called.
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func NewServer(modelName string) (*Server, error) {
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// Validate platform support before attempting to start
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if err := CheckPlatformSupport(); err != nil {
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return nil, err
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}
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return &Server{
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modelName: modelName,
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done: make(chan error, 1),
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client: &http.Client{Timeout: 10 * time.Minute},
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}, nil
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}
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// ModelPath returns the path to the model.
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func (s *Server) ModelPath() string {
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return s.modelName
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}
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// Load checks whether the model fits in GPU memory and starts the subprocess.
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func (s *Server) Load(ctx context.Context, _ ml.SystemInfo, gpus []ml.DeviceInfo, requireFull bool) ([]ml.DeviceID, error) {
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// Estimate VRAM based on tensor size from manifest
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if modelManifest, err := manifest.LoadManifest(s.modelName); err == nil {
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s.vramSize = uint64(modelManifest.TotalTensorSize())
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} else {
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s.vramSize = 8 * 1024 * 1024 * 1024
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}
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if len(gpus) > 0 {
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available := gpus[0].FreeMemory
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overhead := gpus[0].MinimumMemory() + envconfig.GpuOverhead()
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if available > overhead {
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available -= overhead
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} else {
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available = 0
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}
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if s.vramSize > available {
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if requireFull {
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return nil, llm.ErrLoadRequiredFull
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}
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return nil, fmt.Errorf("model requires %s but only %s are available (after %s overhead)", format.HumanBytes2(s.vramSize), format.HumanBytes2(available), format.HumanBytes2(overhead))
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}
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}
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// Find a free port
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port := 0
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if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
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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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port = rand.Intn(65535-49152) + 49152
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}
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s.port = port
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// Get the current executable path (we use the same binary with runner subcommand)
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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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if eval, err := filepath.EvalSymlinks(exe); err == nil {
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exe = eval
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}
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// Spawn subprocess: ollama runner --imagegen-engine --model <path> --port <port>
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cmd := exec.Command(exe, "runner", "--imagegen-engine", "--model", s.modelName, "--port", strconv.Itoa(port))
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cmd.Env = os.Environ()
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configureMLXSubprocessEnv(cmd, ml.LibraryPaths(gpus))
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s.cmd = cmd
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// Forward subprocess stdout/stderr to server logs
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stdout, _ := cmd.StdoutPipe()
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stderr, _ := cmd.StderrPipe()
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go func() {
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scanner := bufio.NewScanner(stdout)
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for scanner.Scan() {
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slog.Info("mlx-runner", "msg", scanner.Text())
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}
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}()
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go func() {
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scanner := bufio.NewScanner(stderr)
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for scanner.Scan() {
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line := scanner.Text()
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slog.Warn("mlx-runner", "msg", line)
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s.lastErrLock.Lock()
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s.lastErr = line
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s.lastErrLock.Unlock()
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}
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}()
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slog.Info("starting mlx runner subprocess", "model", s.modelName, "port", s.port)
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if err := cmd.Start(); err != nil {
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return nil, fmt.Errorf("failed to start mlx runner: %w", err)
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}
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// Reap subprocess when it exits
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go func() {
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err := cmd.Wait()
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s.done <- err
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}()
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return nil, nil
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}
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// Ping checks if the subprocess is healthy.
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func (s *Server) Ping(ctx context.Context) error {
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url := fmt.Sprintf("http://127.0.0.1:%d/health", s.port)
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req, err := http.NewRequestWithContext(ctx, "GET", url, nil)
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if err != nil {
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return err
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}
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resp, err := s.client.Do(req)
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if err != nil {
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return err
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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return fmt.Errorf("health check failed: %d", resp.StatusCode)
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}
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return nil
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}
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func mlxLibraryPathEnv() string {
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switch runtime.GOOS {
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case "windows":
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return "PATH"
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case "darwin":
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return "DYLD_LIBRARY_PATH"
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default:
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return "LD_LIBRARY_PATH"
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}
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}
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func configureMLXSubprocessEnv(cmd *exec.Cmd, libraryPaths []string) {
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if len(libraryPaths) == 0 {
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return
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}
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// Search order for the imagegen runner is:
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// 1. bundled lib/ollama root
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// 2. backend-specific library dirs selected during GPU discovery
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// 3. any existing caller-provided library path values
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pathEnv := mlxLibraryPathEnv()
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pathEnvPaths := append([]string{}, libraryPaths...)
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if existingPath, ok := os.LookupEnv(pathEnv); ok {
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pathEnvPaths = append(pathEnvPaths, filepath.SplitList(existingPath)...)
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}
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setSubprocessEnv(cmd, pathEnv, strings.Join(pathEnvPaths, string(filepath.ListSeparator)))
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slog.Debug("mlx subprocess library path", pathEnv, strings.Join(pathEnvPaths, string(filepath.ListSeparator)))
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ollamaLibraryPaths := append([]string{}, libraryPaths...)
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if existingPath, ok := os.LookupEnv("OLLAMA_LIBRARY_PATH"); ok {
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ollamaLibraryPaths = append(ollamaLibraryPaths, filepath.SplitList(existingPath)...)
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}
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setSubprocessEnv(cmd, "OLLAMA_LIBRARY_PATH", strings.Join(ollamaLibraryPaths, string(filepath.ListSeparator)))
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slog.Debug("mlx subprocess library path", "OLLAMA_LIBRARY_PATH", strings.Join(ollamaLibraryPaths, string(filepath.ListSeparator)))
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}
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func setSubprocessEnv(cmd *exec.Cmd, key, value string) {
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for i := range cmd.Env {
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name, _, ok := strings.Cut(cmd.Env[i], "=")
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if ok && strings.EqualFold(name, key) {
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cmd.Env[i] = key + "=" + value
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return
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}
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}
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cmd.Env = append(cmd.Env, key+"="+value)
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}
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// getLastErr returns the last stderr line.
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func (s *Server) getLastErr() string {
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s.lastErrLock.Lock()
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defer s.lastErrLock.Unlock()
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return s.lastErr
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}
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// WaitUntilRunning waits for the subprocess to be ready.
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func (s *Server) WaitUntilRunning(ctx context.Context) error {
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timeout := time.After(envconfig.LoadTimeout())
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ticker := time.NewTicker(100 * time.Millisecond)
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defer ticker.Stop()
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for {
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select {
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case err := <-s.done:
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errMsg := s.getLastErr()
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if errMsg != "" {
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return fmt.Errorf("mlx runner failed: %s (exit: %v)", errMsg, err)
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}
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return fmt.Errorf("mlx runner exited unexpectedly: %w", err)
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case <-timeout:
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errMsg := s.getLastErr()
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if errMsg != "" {
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return fmt.Errorf("timeout waiting for mlx runner: %s", errMsg)
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}
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return errors.New("timeout waiting for mlx runner to start")
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case <-ticker.C:
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if err := s.Ping(ctx); err == nil {
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slog.Info("mlx runner is ready", "port", s.port)
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return nil
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}
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}
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}
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}
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// Completion handles both text and image generation requests.
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func (s *Server) Completion(ctx context.Context, req llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
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seed := req.Seed
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if seed == 0 {
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seed = time.Now().UnixNano()
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}
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// Extract raw image bytes from the request media.
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var images [][]byte
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for _, media := range req.Media {
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images = append(images, media.Data)
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}
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// Build request for subprocess
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creq := Request{
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Prompt: req.Prompt,
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Width: req.Width,
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Height: req.Height,
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Steps: int(req.Steps),
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Seed: seed,
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Images: images,
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}
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// Pass LLM options if present
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if req.Options != nil {
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creq.Options = &RequestOptions{
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NumPredict: req.Options.NumPredict,
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Temperature: float64(req.Options.Temperature),
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TopP: float64(req.Options.TopP),
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TopK: req.Options.TopK,
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Stop: req.Options.Stop,
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}
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}
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body, err := json.Marshal(creq)
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if err != nil {
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return err
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}
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url := fmt.Sprintf("http://127.0.0.1:%d/completion", s.port)
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httpReq, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(body))
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if err != nil {
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return err
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}
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httpReq.Header.Set("Content-Type", "application/json")
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resp, err := s.client.Do(httpReq)
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if err != nil {
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return err
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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body, _ := io.ReadAll(resp.Body)
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return fmt.Errorf("%s", strings.TrimSpace(string(body)))
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}
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scanner := bufio.NewScanner(resp.Body)
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scanner.Buffer(make([]byte, 1024*1024), 16*1024*1024) // 16MB max
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for scanner.Scan() {
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// Parse subprocess response
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var raw struct {
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Image string `json:"image,omitempty"`
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Content string `json:"content,omitempty"`
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Done bool `json:"done"`
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Step int `json:"step,omitempty"`
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Total int `json:"total,omitempty"`
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StopReason string `json:"stop_reason,omitempty"`
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PromptEvalCount int `json:"prompt_eval_count,omitempty"`
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PromptEvalDuration int `json:"prompt_eval_duration,omitempty"`
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EvalCount int `json:"eval_count,omitempty"`
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EvalDuration int `json:"eval_duration,omitempty"`
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}
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if err := json.Unmarshal(scanner.Bytes(), &raw); err != nil {
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slog.Debug("mlx response parse error", "error", err, "line", string(scanner.Bytes()))
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continue
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}
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// Log stop reason when generation completes
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if raw.Done && raw.StopReason != "" {
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slog.Info("mlx generation completed", "stop_reason", raw.StopReason)
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}
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// Convert to llm.CompletionResponse
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cresp := llm.CompletionResponse{
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Content: raw.Content,
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Done: raw.Done,
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Step: raw.Step,
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TotalSteps: raw.Total,
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Image: raw.Image,
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PromptEvalCount: raw.PromptEvalCount,
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PromptEvalDuration: time.Duration(raw.PromptEvalDuration),
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EvalCount: raw.EvalCount,
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EvalDuration: time.Duration(raw.EvalDuration),
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}
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fn(cresp)
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if cresp.Done {
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return nil
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}
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}
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// Scanner exited without receiving Done - connection was likely closed
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scanErr := scanner.Err()
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if scanErr != nil {
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slog.Error("mlx scanner error", "error", scanErr)
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} else {
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slog.Warn("mlx scanner EOF without Done response - subprocess may have crashed")
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}
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// Check if subprocess is still alive
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if s.HasExited() {
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slog.Error("mlx subprocess has exited unexpectedly")
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if errMsg := s.getLastErr(); errMsg != "" {
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return fmt.Errorf("mlx runner closed response before completion: %s", errMsg)
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}
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}
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if scanErr != nil {
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return scanErr
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}
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return errors.New("mlx runner closed response before completion")
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}
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func (s *Server) Chat(ctx context.Context, req llm.ChatRequest, fn func(llm.ChatResponse)) error {
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return errors.New("image generation runner does not support native chat")
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}
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func (s *Server) ApplyChatTemplate(ctx context.Context, req llm.ChatRequest) (string, error) {
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return "", errors.New("image generation runner does not support native chat templates")
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}
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// Close terminates the subprocess.
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func (s *Server) Close() error {
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s.mu.Lock()
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defer s.mu.Unlock()
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if s.cmd != nil && s.cmd.Process != nil {
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slog.Info("stopping mlx runner subprocess", "pid", s.cmd.Process.Pid)
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s.cmd.Process.Signal(os.Interrupt)
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// Wait briefly for graceful shutdown
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select {
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case <-s.done:
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case <-time.After(5 * time.Second):
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s.cmd.Process.Kill()
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}
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s.cmd = nil
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}
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return nil
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}
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// MemorySize returns the total and VRAM memory usage.
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func (s *Server) MemorySize() (total, vram uint64) {
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return s.vramSize, s.vramSize
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}
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// VRAMByGPU returns VRAM usage for a specific GPU.
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func (s *Server) VRAMByGPU(id ml.DeviceID) uint64 {
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return s.vramSize
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}
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// ContextLength returns the context length (not applicable for image generation).
|
|
func (s *Server) ContextLength() int {
|
|
return 0
|
|
}
|
|
|
|
// Embedding returns embeddings for the input.
|
|
func (s *Server) Embedding(ctx context.Context, input string) ([]float32, int, error) {
|
|
return nil, 0, errors.New("embeddings not supported for MLX models")
|
|
}
|
|
|
|
// Tokenize tokenizes the input content.
|
|
func (s *Server) Tokenize(ctx context.Context, content string) ([]int, error) {
|
|
return nil, errors.New("tokenization not supported for image generation models")
|
|
}
|
|
|
|
// Detokenize converts tokens back to text.
|
|
func (s *Server) Detokenize(ctx context.Context, tokens []int) (string, error) {
|
|
return "", errors.New("detokenization not supported for MLX models")
|
|
}
|
|
|
|
// Pid returns the process ID of the subprocess.
|
|
func (s *Server) Pid() int {
|
|
s.mu.Lock()
|
|
defer s.mu.Unlock()
|
|
if s.cmd != nil && s.cmd.Process != nil {
|
|
return s.cmd.Process.Pid
|
|
}
|
|
return -1
|
|
}
|
|
|
|
// GetPort returns the port the subprocess is listening on.
|
|
func (s *Server) GetPort() int {
|
|
return s.port
|
|
}
|
|
|
|
// GetDeviceInfos returns device information.
|
|
func (s *Server) GetDeviceInfos(ctx context.Context) []ml.DeviceInfo {
|
|
return nil
|
|
}
|
|
|
|
// HasExited returns whether the subprocess has exited.
|
|
func (s *Server) HasExited() bool {
|
|
select {
|
|
case <-s.done:
|
|
return true
|
|
default:
|
|
return false
|
|
}
|
|
}
|
|
|
|
// Ensure Server implements llm.LlamaServer
|
|
var _ llm.LlamaServer = (*Server)(nil)
|