mlxrunner: Enforce model context limit

Currently, context length is unbounded - the cache will keep
growing forever independent of the model's trained context
length. This caps it and enforces semantics similar to most
cloud services:
 - Long prompts will result in an error, not truncation.
 - Generation that exceeds the context will be stopped
This commit is contained in:
Jesse Gross
2026-02-25 15:07:09 -08:00
parent 18ab09b431
commit a16f96658b
13 changed files with 104 additions and 60 deletions

View File

@@ -71,6 +71,10 @@ type Model struct {
Template *template.Template
}
func (m *Model) IsMLX() bool {
return m.Config.ModelFormat == "safetensors"
}
// Capabilities returns the capabilities that the model supports
func (m *Model) Capabilities() []model.Capability {
capabilities := []model.Capability{}

View File

@@ -30,42 +30,44 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
lastMsgIdx := len(msgs) - 1
currMsgIdx := 0
// Start with all messages and remove from the front until it fits in context
for i := 0; i <= lastMsgIdx; i++ {
// Collect system messages from the portion we're about to skip
system = make([]api.Message, 0)
for j := range i {
if msgs[j].Role == "system" {
system = append(system, msgs[j])
if truncate {
// Start with all messages and remove from the front until it fits in context
for i := 0; i <= lastMsgIdx; i++ {
// Collect system messages from the portion we're about to skip
system = make([]api.Message, 0)
for j := range i {
if msgs[j].Role == "system" {
system = append(system, msgs[j])
}
}
}
p, err := renderPrompt(m, append(system, msgs[i:]...), tools, think)
if err != nil {
return "", nil, err
}
s, err := tokenize(ctx, p)
if err != nil {
return "", nil, err
}
ctxLen := len(s)
if m.ProjectorPaths != nil {
for _, msg := range msgs[i:] {
ctxLen += imageNumTokens * len(msg.Images)
p, err := renderPrompt(m, append(system, msgs[i:]...), tools, think)
if err != nil {
return "", nil, err
}
}
if !truncate || ctxLen <= opts.NumCtx {
currMsgIdx = i
break
}
s, err := tokenize(ctx, p)
if err != nil {
return "", nil, err
}
// Must always include at least the last message
if i == lastMsgIdx {
currMsgIdx = lastMsgIdx
break
ctxLen := len(s)
if m.ProjectorPaths != nil {
for _, msg := range msgs[i:] {
ctxLen += imageNumTokens * len(msg.Images)
}
}
if ctxLen <= opts.NumCtx {
currMsgIdx = i
break
}
// Must always include at least the last message
if i == lastMsgIdx {
currMsgIdx = lastMsgIdx
break
}
}
}

View File

@@ -484,7 +484,8 @@ func (s *Server) GenerateHandler(c *gin.Context) {
// the real chat handler, but doing this as a stopgap to get renderer
// support for generate
if values.Messages != nil && values.Suffix == "" && req.Template == "" {
prompt, images, err = chatPrompt(c.Request.Context(), m, r.Tokenize, opts, values.Messages, []api.Tool{}, req.Think, req.Truncate == nil || *req.Truncate)
genTruncate := (req.Truncate == nil || *req.Truncate) && !m.IsMLX()
prompt, images, err = chatPrompt(c.Request.Context(), m, r.Tokenize, opts, values.Messages, []api.Tool{}, req.Think, genTruncate)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
@@ -2217,6 +2218,9 @@ func (s *Server) ChatHandler(c *gin.Context) {
}
truncate := req.Truncate == nil || *req.Truncate
if m.IsMLX() {
truncate = false
}
prompt, images, err := chatPrompt(c.Request.Context(), m, r.Tokenize, opts, msgs, processedTools, req.Think, truncate)
if err != nil {
slog.Error("chat prompt error", "error", err)

View File

@@ -231,7 +231,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
}
// Check for experimental safetensors LLM models
if pending.model.Config.ModelFormat == "safetensors" {
if pending.model.IsMLX() {
if slices.Contains(pending.model.Config.Capabilities, "completion") {
// LLM model with safetensors format - use MLX runner
if s.loadMLX(pending) {
@@ -764,7 +764,7 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
defer cancel()
if !reflect.DeepEqual(runner.model.AdapterPaths, req.model.AdapterPaths) || // have the adapters changed?
!reflect.DeepEqual(runner.model.ProjectorPaths, req.model.ProjectorPaths) || // have the projectors changed?
!reflect.DeepEqual(optsExisting, optsNew) || // have the runner options changed?
(!runner.model.IsMLX() && !reflect.DeepEqual(optsExisting, optsNew)) || // have the runner options changed?
runner.llama.Ping(ctx) != nil {
return true
}

View File

@@ -8,7 +8,6 @@ import (
"fmt"
"io"
"log/slog"
"math"
"math/rand"
"net"
"net/http"
@@ -30,15 +29,16 @@ import (
// Client wraps an MLX runner subprocess to implement llm.LlamaServer for LLM models.
type Client struct {
port int
modelName string
memory atomic.Uint64
done chan error
client *http.Client
lastErr string
lastErrLock sync.Mutex
mu sync.Mutex
cmd *exec.Cmd
port int
modelName string
contextLength atomic.Int64
memory atomic.Uint64
done chan error
client *http.Client
lastErr string
lastErrLock sync.Mutex
mu sync.Mutex
cmd *exec.Cmd
}
// NewClient spawns a new MLX runner subprocess for LLM models and waits until it's ready.
@@ -297,7 +297,7 @@ func (c *Client) Completion(ctx context.Context, req llm.CompletionRequest, fn f
}
func (c *Client) ContextLength() int {
return math.MaxInt
return int(c.contextLength.Load())
}
// Detokenize implements llm.LlamaServer.
@@ -351,9 +351,10 @@ func (c *Client) Pid() int {
}
type statusResponse struct {
Status int
Progress int
Memory uint64
Status int
Progress int
ContextLength int
Memory uint64
}
// Ping implements llm.LlamaServer.
@@ -376,7 +377,10 @@ func (c *Client) Ping(ctx context.Context) error {
if err := json.NewDecoder(resp.Body).Decode(&status); err != nil {
return err
}
c.contextLength.Store(int64(status.ContextLength))
c.memory.Store(status.Memory)
return nil
}

View File

@@ -20,6 +20,7 @@ type Model interface {
Unembed(x *mlx.Array) *mlx.Array
NumLayers() int
Tokenizer() *tokenizer.Tokenizer
MaxContextLength() int
// LoadWeights receives all tensors loaded from the manifest and assigns
// them to model fields. Model-specific logic (MLA absorption, expert

View File

@@ -6,9 +6,12 @@ import (
"bytes"
"context"
"errors"
"fmt"
"log/slog"
"net/http"
"time"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/x/mlxrunner/mlx"
)
@@ -51,9 +54,23 @@ func (r *Runner) TextGenerationPipeline(request Request) error {
return errors.New("empty prompt")
}
if len(inputs) >= r.contextLength {
return api.StatusError{
StatusCode: http.StatusBadRequest,
ErrorMessage: fmt.Sprintf("input length (%d tokens) exceeds the model's maximum context length (%d tokens)", len(inputs), r.contextLength),
}
}
// Cap generation to stay within the model's context length
maxGenerate := r.contextLength - len(inputs)
if request.Options.MaxTokens <= 0 {
request.Options.MaxTokens = maxGenerate
} else {
request.Options.MaxTokens = min(request.Options.MaxTokens, maxGenerate)
}
session := r.cache.begin(r.Model, inputs)
defer session.close()
caches := session.caches
tokens := session.remaining

View File

@@ -45,10 +45,11 @@ type TextCompletionsRequest struct {
}
type Runner struct {
Model base.Model
Tokenizer *tokenizer.Tokenizer
Requests chan Request
cache kvCache
Model base.Model
Tokenizer *tokenizer.Tokenizer
Requests chan Request
cache kvCache
contextLength int
}
func (r *Runner) Load(modelName string) error {
@@ -77,6 +78,7 @@ func (r *Runner) Load(modelName string) error {
r.Model = m
r.Tokenizer = m.Tokenizer()
r.contextLength = m.MaxContextLength()
return nil
}

View File

@@ -51,9 +51,10 @@ func Execute(args []string) error {
mux := http.NewServeMux()
mux.HandleFunc("GET /v1/status", func(w http.ResponseWriter, r *http.Request) {
if err := json.NewEncoder(w).Encode(statusResponse{
Status: 0,
Progress: 100,
Memory: uint64(mlx.ActiveMemory() + mlx.CacheMemory()),
Status: 0,
Progress: 100,
ContextLength: runner.contextLength,
Memory: uint64(mlx.ActiveMemory() + mlx.CacheMemory()),
}); err != nil {
slog.Error("Failed to encode response", "error", err)
http.Error(w, "Internal Server Error", http.StatusInternalServerError)
@@ -88,9 +89,6 @@ func Execute(args []string) error {
}
request.Options.MaxTokens = cmp.Or(request.Options.MaxTokens, request.Options.NumPredict)
if request.Options.MaxTokens < 1 {
request.Options.MaxTokens = 16 << 10
}
request.Pipeline = runner.TextGenerationPipeline
request.Sampler = sample.New(

View File

@@ -430,6 +430,10 @@ func (m *Model) NumLayers() int {
return len(m.Layers)
}
func (m *Model) MaxContextLength() int {
return int(m.MaxPositionEmbeddings)
}
func (m *Model) Tokenizer() *tokenizer.Tokenizer {
return m.tok
}

View File

@@ -733,7 +733,7 @@ func (m *Model) Unembed(x *mlx.Array) *mlx.Array {
func (m *Model) NumLayers() int { return len(m.Layers) }
// MaxContextLength returns the maximum context length
func (m *Model) MaxContextLength() int32 { return m.MaxPositionEmbeddings }
func (m *Model) MaxContextLength() int { return int(m.MaxPositionEmbeddings) }
// VocabSize returns the vocabulary size
func (m *Model) VocabSize() int32 { return m.Config.VocabSize }

View File

@@ -262,6 +262,10 @@ func (m *Model) NumLayers() int {
return len(m.Layers)
}
func (m *Model) MaxContextLength() int {
return int(m.MaxPositionEmbeddings)
}
func (m *Model) Tokenizer() *tokenizer.Tokenizer {
return m.tok
}

View File

@@ -279,6 +279,10 @@ func (m *Model) NumLayers() int {
return len(m.Layers)
}
func (m *Model) MaxContextLength() int {
return int(m.MaxPositionEmbeddings)
}
func (m *Model) Tokenizer() *tokenizer.Tokenizer {
return m.tok
}