package llm import ( "bufio" "bytes" "context" "encoding/json" "errors" "fmt" "io" "log" "log/slog" "math/rand" "net" "net/http" "os" "os/exec" "path/filepath" "runtime" "strconv" "strings" "time" "github.com/ollama/ollama/api" "github.com/ollama/ollama/format" "github.com/ollama/ollama/gpu" ) // LlamaServer is an instance of the llama.cpp server type LlamaServer struct { port int cmd *exec.Cmd done chan error // Channel to signal when the process exits status *StatusWriter options api.Options } func NewLlamaServer(model string, adapters, projectors []string, opts api.Options) (*LlamaServer, error) { f, err := os.Open(model) if err != nil { return nil, err } defer f.Close() ggml, _, err := DecodeGGML(f) if err != nil { return nil, err } if opts.NumCtx > int(ggml.KV().ContextLength()) { slog.Warn("requested context length is greater than model max context length", "requested", opts.NumCtx, "model", ggml.KV().ContextLength()) opts.NumCtx = int(ggml.KV().ContextLength()) } if opts.NumCtx < 4 { opts.NumCtx = 4 } memoryAvailable, _ := gpu.CheckVRAM() info := gpu.GetGPUInfo() memoryMinimum := info.MinimumMemory for _, projector := range projectors { memoryMinimum += projectorMemoryRequirements(projector) // multimodal models require at least 2048 context opts.NumCtx = max(opts.NumCtx, 2048) } // fp16 k,v = (1 (k) + 1 (v)) * sizeof(float16) * n_ctx * n_layer * n_embd / n_head * n_head_kv var kv uint64 = 2 * 2 * uint64(opts.NumCtx) * ggml.KV().BlockCount() * ggml.KV().EmbeddingLength() / ggml.KV().HeadCount() * ggml.KV().HeadCountKV() graphPartialOffload, graphFullOffload := ggml.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch))) if graphPartialOffload == 0 { graphPartialOffload = ggml.KV().GQA() * kv / 6 } if graphFullOffload == 0 { graphFullOffload = graphPartialOffload } graphFullOffload *= uint64(info.DeviceCount) graphPartialOffload *= uint64(info.DeviceCount) // memoryRequiredTotal represents the memory required for full GPU offloading (all layers) memoryRequiredTotal := memoryMinimum + graphFullOffload // memoryRequiredPartial represents the memory required for partial GPU offloading (n > 0, n < layers) memoryRequiredPartial := memoryMinimum + graphPartialOffload if info.Library != "metal" { if memoryRequiredPartial > memoryAvailable { info.Library = "cpu" } } var layerCount int layers := ggml.Tensors().Layers() for i := 0; i < int(ggml.KV().BlockCount()); i++ { memoryLayer := layers[fmt.Sprintf("blk.%d", i)].size() // KV is proportional to the number of layers memoryLayer += kv / ggml.KV().BlockCount() memoryRequiredTotal += memoryLayer if memoryAvailable > memoryRequiredPartial+memoryLayer { memoryRequiredPartial += memoryLayer layerCount++ } } var memoryLayerOutput uint64 for k, v := range layers { if !strings.HasPrefix(k, "blk.") { slog.Info("aaa", "name", k, "size", format.HumanBytes2(v.size())) memoryLayerOutput += v.size() } } memoryRequiredTotal += memoryLayerOutput if info.Library == "metal" && memoryRequiredTotal > info.TotalMemory { // disable partial offloading when model is greater than total system memory opts.NumGPU = 0 } else if memoryAvailable > memoryRequiredTotal { layerCount = int(ggml.KV().BlockCount()) + 1 memoryRequiredPartial = memoryRequiredTotal } if opts.NumGPU < 0 { opts.NumGPU = layerCount } memoryWeights := memoryRequiredTotal - memoryMinimum - graphFullOffload - kv slog.Info( "offload to gpu", slog.Group( "layers", // actual number of layers offloaded "real", opts.NumGPU, // estimated number of layers that can be offloaded "estimate", layerCount, ), slog.Group( "memory", // memory available for offloading "available", format.HumanBytes2(memoryAvailable), slog.Group( "required", // memory required for full offloading "full", format.HumanBytes2(memoryRequiredTotal), // memory required to offload layers.estimate layers "partial", format.HumanBytes2(memoryRequiredPartial), // memory of KV cache "kv", format.HumanBytes2(kv), ), slog.Group( "weights", // memory of the weights "total", format.HumanBytes2(memoryWeights), // memory of repeating layers "repeating", format.HumanBytes2(memoryWeights-memoryLayerOutput), // memory of non-repeating layers "nonrepeating", format.HumanBytes2(memoryLayerOutput), ), slog.Group( "graph", // memory of graph when fully offloaded "full", format.HumanBytes2(graphFullOffload), // memory of graph when not fully offloaded "partial", format.HumanBytes2(graphPartialOffload), ), ), ) if len(adapters) > 1 { return nil, errors.New("ollama supports only one lora adapter, but multiple were provided") } availableServers := availableServers() servers := serversForGpu(info) demandLib := os.Getenv("OLLAMA_LLM_LIBRARY") if demandLib != "" { serverPath := availableServers[demandLib] if serverPath == "" { slog.Info(fmt.Sprintf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib)) } else { slog.Info("user override", "OLLAMA_LLM_LIBRARY", demandLib, "path", serverPath) servers = []string{demandLib} } } if len(servers) == 0 { return nil, fmt.Errorf("no servers found for %v", info) } params := []string{ "--model", model, "--ctx-size", fmt.Sprintf("%d", opts.NumCtx), "--batch-size", fmt.Sprintf("%d", opts.NumBatch), "--embedding", } if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" { params = append(params, "--log-format", "json") } else { params = append(params, "--log-disable") } if opts.NumGPU >= 0 { params = append(params, "--n-gpu-layers", fmt.Sprintf("%d", opts.NumGPU)) } if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" { params = append(params, "--verbose") } if opts.MainGPU > 0 { params = append(params, "--main-gpu", fmt.Sprintf("%d", opts.MainGPU)) } if len(adapters) > 0 { // TODO: applying multiple adapters is not supported by the llama.cpp server yet params = append(params, "--lora", adapters[0]) } if len(projectors) > 0 { // TODO: applying multiple projectors is not supported by the llama.cpp server yet params = append(params, "--mmproj", projectors[0]) } if opts.NumThread > 0 { params = append(params, "--threads", fmt.Sprintf("%d", opts.NumThread)) } if !opts.F16KV { params = append(params, "--memory-f32") } if opts.UseMLock { params = append(params, "--mlock") } if !opts.UseMMap { params = append(params, "--no-mmap") } if opts.UseNUMA { params = append(params, "--numa") } // Loop through potential servers var finalErr error for i := 0; i < len(servers); i++ { dir := availableServers[servers[i]] // Find an availableServers port, retry on each iterration in case the failure was a port conflict race port := 0 if a, err := net.ResolveTCPAddr("tcp", "localhost:0"); err == nil { var l *net.TCPListener if l, err = net.ListenTCP("tcp", a); err == nil { port = l.Addr().(*net.TCPAddr).Port l.Close() } } if port == 0 { slog.Debug("ResolveTCPAddr failed ", "error", err) port = rand.Intn(65535-49152) + 49152 // get a random port in the ephemeral range } finalParams := append(params, "--port", strconv.Itoa(port)) pathEnv := "LD_LIBRARY_PATH" if runtime.GOOS == "windows" { pathEnv = "PATH" } // append the server directory to LD_LIBRARY_PATH/PATH libraryPaths := []string{dir} if libraryPath, ok := os.LookupEnv(pathEnv); ok { // Append our runner directory to the path // This will favor system libraries over our bundled library dependencies libraryPaths = append(filepath.SplitList(libraryPath), libraryPaths...) } server := filepath.Join(dir, "ollama_llama_server") if runtime.GOOS == "windows" { server = server + ".exe" } s := &LlamaServer{ port: port, cmd: exec.Command(server, finalParams...), status: NewStatusWriter(os.Stderr), options: opts, } libEnv := fmt.Sprintf("%s=%s", pathEnv, strings.Join(libraryPaths, string(filepath.ListSeparator))) slog.Debug(libEnv) s.cmd.Env = append(os.Environ(), libEnv) s.cmd.Stdout = os.Stdout s.cmd.Stderr = s.status slog.Info("starting llama server", "cmd", s.cmd.String()) if err = s.cmd.Start(); err != nil { msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } err = fmt.Errorf("error starting the external llama server: %v %s", err, msg) finalErr = err continue } // reap subprocess when it exits go func() { // Exit status managed via getServerStatus _ = s.cmd.Wait() }() return s, nil } slog.Error("unable to load any llama server", "error", finalErr) return nil, finalErr } func projectorMemoryRequirements(filename string) uint64 { file, err := os.Open(filename) if err != nil { return 0 } defer file.Close() ggml, _, err := DecodeGGML(file) if err != nil { return 0 } var mem uint64 for _, layer := range ggml.Tensors().Layers() { mem += layer.size() } return mem } type ServerStatus int const ( // iota is reset to 0 ServerStatusReady ServerStatus = iota ServerStatusNoSlotsAvaialble ServerStatusLoadingModel ServerStatusNotResponding ServerStatusError ) type ServerStatusResp struct { Status string `json:"status"` SlotsIdle int `json:"slots_idle"` SlotsProcessing int `json:"slots_processing"` Error string `json:"error"` } func (s *LlamaServer) getServerStatus(ctx context.Context) (ServerStatus, error) { // Fail fast if its exited if s.cmd.ProcessState != nil { msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } return ServerStatusError, fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg) } req, err := http.NewRequestWithContext(ctx, http.MethodGet, fmt.Sprintf("http://127.0.0.1:%d/health", s.port), nil) if err != nil { return ServerStatusError, fmt.Errorf("error creating GET request: %v", err) } req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { if errors.Is(err, context.DeadlineExceeded) { return ServerStatusNotResponding, fmt.Errorf("server not responding") } return ServerStatusError, fmt.Errorf("health resp: %w", err) } defer resp.Body.Close() body, err := io.ReadAll(resp.Body) if err != nil { return ServerStatusError, fmt.Errorf("read health request: %w", err) } var status ServerStatusResp if err := json.Unmarshal(body, &status); err != nil { return ServerStatusError, fmt.Errorf("health unmarshal encode response: %w", err) } switch status.Status { case "ok": return ServerStatusReady, nil case "no slot available": return ServerStatusNoSlotsAvaialble, nil case "loading model": return ServerStatusLoadingModel, nil default: return ServerStatusError, fmt.Errorf("server error: %+v", status) } } func (s *LlamaServer) Ping(ctx context.Context) error { _, err := s.getServerStatus(ctx) if err != nil { slog.Debug("server unhealthy", "error", err) return err } return nil } func (s *LlamaServer) WaitUntilRunning() error { start := time.Now() // TODO we need to wire up a better way to detect hangs during model load and startup of the server expiresAt := time.Now().Add(10 * time.Minute) // be generous with timeout, large models can take a while to load ticker := time.NewTicker(50 * time.Millisecond) defer ticker.Stop() slog.Info("waiting for llama runner to start responding") var lastStatus ServerStatus = -1 for { select { case err := <-s.done: msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } return fmt.Errorf("llama runner process has terminated: %v %s", err, msg) case <-ticker.C: if time.Now().After(expiresAt) { // timeout msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } return fmt.Errorf("timed out waiting for llama runner to start: %s", msg) } if s.cmd.ProcessState != nil { msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } return fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg) } ctx, cancel := context.WithTimeout(context.Background(), 200*time.Millisecond) defer cancel() status, err := s.getServerStatus(ctx) if err != nil && lastStatus != status { slog.Debug("server not yet available", "error", err) lastStatus = status continue } switch status { case ServerStatusLoadingModel: // TODO - this state never seems to happen with the current server.cpp code (bug?) // it doesn't respond to the health endpoint until after the model is loaded slog.Debug("loading model") case ServerStatusReady: slog.Debug(fmt.Sprintf("llama runner started in %f seconds", time.Since(start).Seconds())) return nil } } } } const jsonGrammar = ` root ::= object value ::= object | array | string | number | ("true" | "false" | "null") ws object ::= "{" ws ( string ":" ws value ("," ws string ":" ws value)* )? "}" ws array ::= "[" ws ( value ("," ws value)* )? "]" ws string ::= "\"" ( [^"\\] | "\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) # escapes )* "\"" ws number ::= ("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? ws # Optional space: by convention, applied in this grammar after literal chars when allowed ws ::= ([ \t\n] ws)? ` const maxBufferSize = 512 * format.KiloByte const maxRetries = 3 type ImageData struct { Data []byte `json:"data"` ID int `json:"id"` } type completion struct { Content string `json:"content"` Model string `json:"model"` Prompt string `json:"prompt"` Stop bool `json:"stop"` Timings struct { PredictedN int `json:"predicted_n"` PredictedMS float64 `json:"predicted_ms"` PromptN int `json:"prompt_n"` PromptMS float64 `json:"prompt_ms"` } } type CompletionRequest struct { Prompt string Format string Images []ImageData Options api.Options } type CompletionResponse struct { Content string Done bool PromptEvalCount int PromptEvalDuration time.Duration EvalCount int EvalDuration time.Duration } func (s *LlamaServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error { request := map[string]any{ "prompt": req.Prompt, "stream": true, "n_predict": req.Options.NumPredict, "n_keep": req.Options.NumKeep, "main_gpu": req.Options.MainGPU, "temperature": req.Options.Temperature, "top_k": req.Options.TopK, "top_p": req.Options.TopP, "tfs_z": req.Options.TFSZ, "typical_p": req.Options.TypicalP, "repeat_last_n": req.Options.RepeatLastN, "repeat_penalty": req.Options.RepeatPenalty, "presence_penalty": req.Options.PresencePenalty, "frequency_penalty": req.Options.FrequencyPenalty, "mirostat": req.Options.Mirostat, "mirostat_tau": req.Options.MirostatTau, "mirostat_eta": req.Options.MirostatEta, "penalize_nl": req.Options.PenalizeNewline, "seed": req.Options.Seed, "stop": req.Options.Stop, "image_data": req.Images, "cache_prompt": true, } // Make sure the server is ready status, err := s.getServerStatus(ctx) if err != nil { return err } else if status != ServerStatusReady { return fmt.Errorf("unexpected server status: %d", status) } if req.Format == "json" { request["grammar"] = jsonGrammar if !strings.Contains(strings.ToLower(req.Prompt), "json") { slog.Warn("Prompt does not specify that the LLM should response in JSON, but JSON format is expected. For best results specify that JSON is expected in the system prompt.") } } retryDelay := 100 * time.Microsecond for retries := 0; retries < maxRetries; retries++ { if retries > 0 { time.Sleep(retryDelay) // wait before retrying retryDelay *= 2 // exponential backoff } // Handling JSON marshaling with special characters unescaped. buffer := &bytes.Buffer{} enc := json.NewEncoder(buffer) enc.SetEscapeHTML(false) if err := enc.Encode(request); err != nil { return fmt.Errorf("failed to marshal data: %v", err) } endpoint := fmt.Sprintf("http://127.0.0.1:%d/completion", s.port) req, err := http.NewRequestWithContext(ctx, http.MethodPost, endpoint, buffer) if err != nil { return fmt.Errorf("error creating POST request: %v", err) } req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { return fmt.Errorf("POST predict: %v", err) } defer resp.Body.Close() if resp.StatusCode >= 400 { bodyBytes, err := io.ReadAll(resp.Body) if err != nil { return fmt.Errorf("failed reading llm error response: %w", err) } log.Printf("llm predict error: %s", bodyBytes) return fmt.Errorf("%s", bodyBytes) } scanner := bufio.NewScanner(resp.Body) buf := make([]byte, 0, maxBufferSize) scanner.Buffer(buf, maxBufferSize) retryNeeded := false // keep track of the last token generated, this is used to abort if the model starts looping var lastToken string var tokenRepeat int for scanner.Scan() { select { case <-ctx.Done(): // This handles the request cancellation return ctx.Err() default: line := scanner.Bytes() if len(line) == 0 { continue } // try again on slot unavailable if bytes.Contains(line, []byte("slot unavailable")) { retryNeeded = true break } evt, ok := bytes.CutPrefix(line, []byte("data: ")) if !ok { return fmt.Errorf("error parsing llm response stream: %s", line) } var c completion if err := json.Unmarshal(evt, &c); err != nil { return fmt.Errorf("error unmarshaling llm prediction response: %v", err) } switch { case strings.TrimSpace(c.Content) == lastToken: tokenRepeat++ default: lastToken = strings.TrimSpace(c.Content) tokenRepeat = 0 } // 30 picked as an arbitrary max token repeat limit, modify as needed if tokenRepeat > 30 { slog.Debug("prediction aborted, token repeat limit reached") return ctx.Err() } if c.Content != "" { fn(CompletionResponse{ Content: c.Content, }) } if c.Stop { fn(CompletionResponse{ Done: true, PromptEvalCount: c.Timings.PromptN, PromptEvalDuration: parseDurationMs(c.Timings.PromptMS), EvalCount: c.Timings.PredictedN, EvalDuration: parseDurationMs(c.Timings.PredictedMS), }) return nil } } } if err := scanner.Err(); err != nil { if strings.Contains(err.Error(), "unexpected EOF") { s.Close() msg := "" if s.status != nil && s.status.LastErrMsg != "" { msg = s.status.LastErrMsg } return fmt.Errorf("an unknown error was encountered while running the model %s", msg) } return fmt.Errorf("error reading llm response: %v", err) } if !retryNeeded { return nil // success } } // should never reach here ideally return fmt.Errorf("max retries exceeded") } type EmbeddingRequest struct { Content string `json:"content"` } type EmbeddingResponse struct { Embedding []float64 `json:"embedding"` } func (s *LlamaServer) Embedding(ctx context.Context, prompt string) ([]float64, error) { // Make sure the server is ready status, err := s.getServerStatus(ctx) if err != nil { return nil, err } else if status != ServerStatusReady { return nil, fmt.Errorf("unexpected server status: %d", status) } data, err := json.Marshal(TokenizeRequest{Content: prompt}) if err != nil { return nil, fmt.Errorf("error marshaling embed data: %w", err) } req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/embedding", s.port), bytes.NewBuffer(data)) if err != nil { return nil, fmt.Errorf("error creating embed request: %w", err) } req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { return nil, fmt.Errorf("do embedding request: %w", err) } defer resp.Body.Close() body, err := io.ReadAll(resp.Body) if err != nil { return nil, fmt.Errorf("error reading embed response: %w", err) } if resp.StatusCode >= 400 { log.Printf("llm encode error: %s", body) return nil, fmt.Errorf("%s", body) } var embedding EmbeddingResponse if err := json.Unmarshal(body, &embedding); err != nil { return nil, fmt.Errorf("unmarshal tokenize response: %w", err) } return embedding.Embedding, nil } type TokenizeRequest struct { Content string `json:"content"` } type TokenizeResponse struct { Tokens []int `json:"tokens"` } func (s *LlamaServer) Tokenize(ctx context.Context, content string) ([]int, error) { // Make sure the server is ready status, err := s.getServerStatus(ctx) if err != nil { return nil, err } else if status != ServerStatusReady { return nil, fmt.Errorf("unexpected server status: %d", status) } data, err := json.Marshal(TokenizeRequest{Content: content}) if err != nil { return nil, fmt.Errorf("marshaling encode data: %w", err) } req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/tokenize", s.port), bytes.NewBuffer(data)) if err != nil { return nil, fmt.Errorf("encode request: %w", err) } req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { return nil, fmt.Errorf("do encode request: %w", err) } defer resp.Body.Close() body, err := io.ReadAll(resp.Body) if err != nil { return nil, fmt.Errorf("read encode request: %w", err) } if resp.StatusCode >= 400 { log.Printf("llm encode error: %s", body) return nil, fmt.Errorf("%s", body) } var encoded TokenizeResponse if err := json.Unmarshal(body, &encoded); err != nil { return nil, fmt.Errorf("unmarshal encode response: %w", err) } return encoded.Tokens, nil } type DetokenizeRequest struct { Tokens []int `json:"tokens"` } type DetokenizeResponse struct { Content string `json:"content"` } func (s *LlamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) { // Make sure the server is ready status, err := s.getServerStatus(ctx) if err != nil { return "", err } else if status != ServerStatusReady { return "", fmt.Errorf("unexpected server status: %d", status) } data, err := json.Marshal(DetokenizeRequest{Tokens: tokens}) if err != nil { return "", fmt.Errorf("marshaling decode data: %w", err) } req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/detokenize", s.port), bytes.NewBuffer(data)) if err != nil { return "", fmt.Errorf("decode request: %w", err) } req.Header.Set("Content-Type", "application/json") resp, err := http.DefaultClient.Do(req) if err != nil { return "", fmt.Errorf("do decode request: %w", err) } defer resp.Body.Close() body, err := io.ReadAll(resp.Body) if err != nil { return "", fmt.Errorf("read decode request: %w", err) } if resp.StatusCode >= 400 { log.Printf("llm decode error: %s", body) return "", fmt.Errorf("%s", body) } var decoded DetokenizeResponse if err := json.Unmarshal(body, &decoded); err != nil { return "", fmt.Errorf("unmarshal encode response: %w", err) } return decoded.Content, nil } func (s *LlamaServer) Close() error { if s.cmd != nil { slog.Debug("stopping llama server") return s.cmd.Process.Kill() } return nil } func parseDurationMs(ms float64) time.Duration { dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms)) if err != nil { panic(err) } return dur }