Compare commits

..

9 Commits

Author SHA1 Message Date
Bruce MacDonald
d5a2849d1f cmd: set codex env vars on launch and handle zstd request bodies
The Codex runner was not setting OPENAI_BASE_URL or OPENAI_API_KEY, this prevents Codex from sending requests to api.openai.com instead of the local Ollama server. This mirrors the approach used by the Claude runner.

Codex v0.98.0 sends zstd-compressed request bodies to the /v1/responses endpoint. Add decompression support in ResponsesMiddleware with an 8MB max decompressed size limit to prevent resource exhaustion.
2026-02-06 10:42:18 -08:00
Parth Sareen
42e1d49fbe cmd: fix context limits for droid and add qwen3-coder-next ctx (#14112) 2026-02-05 22:29:53 -08:00
Michael Yang
814630ca60 Revert "move tokenizers to separate package (#13825)" (#14111) 2026-02-05 20:49:08 -08:00
Parth Sareen
87cf187774 cmd: set claude code env vars on launch (#14109)
Set ANTHROPIC_DEFAULT_OPUS_MODEL, ANTHROPIC_DEFAULT_SONNET_MODEL,
ANTHROPIC_DEFAULT_HAIKU_MODEL, and CLAUDE_CODE_SUBAGENT_MODEL when
launching Claude Code so all model tiers route through Ollama.
2026-02-05 19:04:53 -08:00
Michael Yang
6ddd8862cd chore: move x/mlxrunner into x/imagegen (#14100) 2026-02-05 18:25:56 -08:00
Michael Yang
f1373193dc move tokenizers to separate package (#13825) 2026-02-05 17:44:11 -08:00
Parth Sareen
8a4b77f9da cmd: set context limits for cloud models in opencode (#14107) 2026-02-05 16:36:46 -08:00
Parth Sareen
5f53fe7884 cmd: ollama launch improvements (#14099) 2026-02-05 15:08:17 -08:00
Bruce MacDonald
7ab4ca0e7f scripts: add macOS support to install.sh (#14060)
Allow installing Ollama on MacOS directly from the command line. This is in line with other CLI tools and results in a more streamlined experience when the user is looking to use the CLI specifically.
2026-02-05 14:59:01 -08:00
134 changed files with 3454 additions and 7247 deletions

22
.github/workflows/test-install.yaml vendored Normal file
View File

@@ -0,0 +1,22 @@
name: test-install
on:
pull_request:
paths:
- 'scripts/install.sh'
- '.github/workflows/test-install.yaml'
jobs:
test:
strategy:
matrix:
os: [ubuntu-latest, macos-latest]
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v4
- name: Run install script
run: sh ./scripts/install.sh
env:
OLLAMA_NO_START: 1 # do not start app
- name: Verify ollama is available
run: ollama --version

View File

@@ -182,7 +182,7 @@ option(MLX_ENGINE "Enable MLX backend" OFF)
if(MLX_ENGINE)
message(STATUS "Setting up MLX (this takes a while...)")
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/x/ml/backend/mlx)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/x/imagegen/mlx)
# Find CUDA toolkit if MLX is built with CUDA support
find_package(CUDAToolkit)
@@ -216,4 +216,4 @@ if(MLX_ENGINE)
COMPONENT MLX)
endif()
endif()
endif()
endif()

View File

@@ -518,24 +518,26 @@ func mapStopReason(reason string, hasToolCalls bool) string {
// StreamConverter manages state for converting Ollama streaming responses to Anthropic format
type StreamConverter struct {
ID string
Model string
firstWrite bool
contentIndex int
inputTokens int
outputTokens int
thinkingStarted bool
thinkingDone bool
textStarted bool
toolCallsSent map[string]bool
ID string
Model string
firstWrite bool
contentIndex int
inputTokens int
outputTokens int
estimatedInputTokens int // Estimated tokens from request (used when actual metrics are 0)
thinkingStarted bool
thinkingDone bool
textStarted bool
toolCallsSent map[string]bool
}
func NewStreamConverter(id, model string) *StreamConverter {
func NewStreamConverter(id, model string, estimatedInputTokens int) *StreamConverter {
return &StreamConverter{
ID: id,
Model: model,
firstWrite: true,
toolCallsSent: make(map[string]bool),
ID: id,
Model: model,
firstWrite: true,
estimatedInputTokens: estimatedInputTokens,
toolCallsSent: make(map[string]bool),
}
}
@@ -551,7 +553,11 @@ func (c *StreamConverter) Process(r api.ChatResponse) []StreamEvent {
if c.firstWrite {
c.firstWrite = false
// Use actual metrics if available, otherwise use estimate
c.inputTokens = r.Metrics.PromptEvalCount
if c.inputTokens == 0 && c.estimatedInputTokens > 0 {
c.inputTokens = c.estimatedInputTokens
}
events = append(events, StreamEvent{
Event: "message_start",
@@ -779,3 +785,123 @@ func mapToArgs(m map[string]any) api.ToolCallFunctionArguments {
}
return args
}
// CountTokensRequest represents an Anthropic count_tokens request
type CountTokensRequest struct {
Model string `json:"model"`
Messages []MessageParam `json:"messages"`
System any `json:"system,omitempty"`
Tools []Tool `json:"tools,omitempty"`
Thinking *ThinkingConfig `json:"thinking,omitempty"`
}
// EstimateInputTokens estimates input tokens from a MessagesRequest (reuses CountTokensRequest logic)
func EstimateInputTokens(req MessagesRequest) int {
return estimateTokens(CountTokensRequest{
Model: req.Model,
Messages: req.Messages,
System: req.System,
Tools: req.Tools,
Thinking: req.Thinking,
})
}
// CountTokensResponse represents an Anthropic count_tokens response
type CountTokensResponse struct {
InputTokens int `json:"input_tokens"`
}
// estimateTokens returns a rough estimate of tokens (len/4).
// TODO: Replace with actual tokenization via Tokenize API for accuracy.
// Current len/4 heuristic is a rough approximation (~4 chars/token average).
func estimateTokens(req CountTokensRequest) int {
var totalLen int
// Count system prompt
if req.System != nil {
totalLen += countAnyContent(req.System)
}
// Count messages
for _, msg := range req.Messages {
// Count role (always present)
totalLen += len(msg.Role)
// Count content
contentLen := countAnyContent(msg.Content)
totalLen += contentLen
}
for _, tool := range req.Tools {
totalLen += len(tool.Name) + len(tool.Description) + len(tool.InputSchema)
}
// Return len/4 as rough token estimate, minimum 1 if there's any content
tokens := totalLen / 4
if tokens == 0 && (len(req.Messages) > 0 || req.System != nil) {
tokens = 1
}
return tokens
}
func countAnyContent(content any) int {
if content == nil {
return 0
}
switch c := content.(type) {
case string:
return len(c)
case []any:
total := 0
for _, block := range c {
total += countContentBlock(block)
}
return total
default:
if data, err := json.Marshal(content); err == nil {
return len(data)
}
return 0
}
}
func countContentBlock(block any) int {
blockMap, ok := block.(map[string]any)
if !ok {
if s, ok := block.(string); ok {
return len(s)
}
return 0
}
total := 0
blockType, _ := blockMap["type"].(string)
if text, ok := blockMap["text"].(string); ok {
total += len(text)
}
if thinking, ok := blockMap["thinking"].(string); ok {
total += len(thinking)
}
if blockType == "tool_use" {
if data, err := json.Marshal(blockMap); err == nil {
total += len(data)
}
}
if blockType == "tool_result" {
if data, err := json.Marshal(blockMap); err == nil {
total += len(data)
}
}
if source, ok := blockMap["source"].(map[string]any); ok {
if data, ok := source["data"].(string); ok {
total += len(data)
}
}
return total
}

View File

@@ -321,8 +321,6 @@ func TestFromMessagesRequest_WithThinking(t *testing.T) {
}
}
// TestFromMessagesRequest_ThinkingOnlyBlock verifies that messages containing only
// a thinking block (no text, images, or tool calls) are preserved and not dropped.
func TestFromMessagesRequest_ThinkingOnlyBlock(t *testing.T) {
req := MessagesRequest{
Model: "test-model",
@@ -605,7 +603,7 @@ func TestGenerateMessageID(t *testing.T) {
}
func TestStreamConverter_Basic(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
// First chunk
resp1 := api.ChatResponse{
@@ -678,7 +676,7 @@ func TestStreamConverter_Basic(t *testing.T) {
}
func TestStreamConverter_WithToolCalls(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -731,7 +729,7 @@ func TestStreamConverter_WithToolCalls(t *testing.T) {
func TestStreamConverter_ToolCallWithUnmarshalableArgs(t *testing.T) {
// Test that unmarshalable arguments (like channels) are handled gracefully
// and don't cause a panic or corrupt stream
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
// Create a channel which cannot be JSON marshaled
unmarshalable := make(chan int)
@@ -778,7 +776,7 @@ func TestStreamConverter_ToolCallWithUnmarshalableArgs(t *testing.T) {
func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
// Test that valid tool calls still work when mixed with invalid ones
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
unmarshalable := make(chan int)
badArgs := api.NewToolCallFunctionArguments()
@@ -842,10 +840,6 @@ func TestStreamConverter_MultipleToolCallsWithMixedValidity(t *testing.T) {
}
}
// TestContentBlockJSON_EmptyFieldsPresent verifies that empty text and thinking fields
// are serialized in JSON output. The Anthropic SDK requires these fields to be present
// (even when empty) in content_block_start events to properly accumulate streaming deltas.
// Without these fields, the SDK throws: "TypeError: unsupported operand type(s) for +=: 'NoneType' and 'str'"
func TestContentBlockJSON_EmptyFieldsPresent(t *testing.T) {
tests := []struct {
name string
@@ -899,11 +893,9 @@ func TestContentBlockJSON_EmptyFieldsPresent(t *testing.T) {
}
}
// TestStreamConverter_ContentBlockStartIncludesEmptyFields verifies that content_block_start
// events include the required empty fields for SDK compatibility.
func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
t.Run("text block start includes empty text", func(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -937,7 +929,7 @@ func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
})
t.Run("thinking block start includes empty thinking", func(t *testing.T) {
conv := NewStreamConverter("msg_123", "test-model")
conv := NewStreamConverter("msg_123", "test-model", 0)
resp := api.ChatResponse{
Model: "test-model",
@@ -969,3 +961,105 @@ func TestStreamConverter_ContentBlockStartIncludesEmptyFields(t *testing.T) {
}
})
}
func TestEstimateTokens_SimpleMessage(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: "Hello, world!"},
},
}
tokens := estimateTokens(req)
// "user" (4) + "Hello, world!" (13) = 17 chars / 4 = 4 tokens
if tokens < 1 {
t.Errorf("expected at least 1 token, got %d", tokens)
}
// Sanity check: shouldn't be wildly off
if tokens > 10 {
t.Errorf("expected fewer than 10 tokens for short message, got %d", tokens)
}
}
func TestEstimateTokens_WithSystemPrompt(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
System: "You are a helpful assistant.",
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
},
}
tokens := estimateTokens(req)
// System prompt adds to count
if tokens < 5 {
t.Errorf("expected at least 5 tokens with system prompt, got %d", tokens)
}
}
func TestEstimateTokens_WithTools(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: "What's the weather?"},
},
Tools: []Tool{
{
Name: "get_weather",
Description: "Get the current weather for a location",
InputSchema: json.RawMessage(`{"type":"object","properties":{"location":{"type":"string"}}}`),
},
},
}
tokens := estimateTokens(req)
// Tools add significant content
if tokens < 10 {
t.Errorf("expected at least 10 tokens with tools, got %d", tokens)
}
}
func TestEstimateTokens_WithThinking(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{
{Role: "user", Content: "Hello"},
{
Role: "assistant",
Content: []any{
map[string]any{
"type": "thinking",
"thinking": "Let me think about this carefully...",
},
map[string]any{
"type": "text",
"text": "Here is my response.",
},
},
},
},
}
tokens := estimateTokens(req)
// Thinking content should be counted
if tokens < 10 {
t.Errorf("expected at least 10 tokens with thinking content, got %d", tokens)
}
}
func TestEstimateTokens_EmptyContent(t *testing.T) {
req := CountTokensRequest{
Model: "test-model",
Messages: []MessageParam{},
}
tokens := estimateTokens(req)
if tokens != 0 {
t.Errorf("expected 0 tokens for empty content, got %d", tokens)
}
}

View File

@@ -466,3 +466,25 @@ func (c *Client) Whoami(ctx context.Context) (*UserResponse, error) {
}
return &resp, nil
}
// AliasRequest is the request body for creating or updating a model alias.
type AliasRequest struct {
Alias string `json:"alias"`
Target string `json:"target"`
PrefixMatching bool `json:"prefix_matching,omitempty"`
}
// SetAliasExperimental creates or updates a model alias via the experimental aliases API.
func (c *Client) SetAliasExperimental(ctx context.Context, req *AliasRequest) error {
return c.do(ctx, http.MethodPost, "/api/experimental/aliases", req, nil)
}
// AliasDeleteRequest is the request body for deleting a model alias.
type AliasDeleteRequest struct {
Alias string `json:"alias"`
}
// DeleteAliasExperimental deletes a model alias via the experimental aliases API.
func (c *Client) DeleteAliasExperimental(ctx context.Context, req *AliasDeleteRequest) error {
return c.do(ctx, http.MethodDelete, "/api/experimental/aliases", req, nil)
}

View File

@@ -1763,7 +1763,7 @@ func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
return err
}
if err := startApp(cmd.Context(), client); err != nil {
return fmt.Errorf("ollama server not responding - %w", err)
return err
}
}
return nil

View File

@@ -1,18 +1,23 @@
package config
import (
"context"
"fmt"
"os"
"os/exec"
"path/filepath"
"runtime"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
)
// Claude implements Runner for Claude Code integration
// Claude implements Runner and AliasConfigurer for Claude Code integration
type Claude struct{}
// Compile-time check that Claude implements AliasConfigurer
var _ AliasConfigurer = (*Claude)(nil)
func (c *Claude) String() string { return "Claude Code" }
func (c *Claude) args(model string, extra []string) []string {
@@ -53,10 +58,136 @@ func (c *Claude) Run(model string, args []string) error {
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
cmd.Env = append(os.Environ(),
env := append(os.Environ(),
"ANTHROPIC_BASE_URL="+envconfig.Host().String(),
"ANTHROPIC_API_KEY=",
"ANTHROPIC_AUTH_TOKEN=ollama",
)
env = append(env, c.modelEnvVars(model)...)
cmd.Env = env
return cmd.Run()
}
// modelEnvVars returns Claude Code env vars that route all model tiers through Ollama.
func (c *Claude) modelEnvVars(model string) []string {
primary := model
fast := model
if cfg, err := loadIntegration("claude"); err == nil && cfg.Aliases != nil {
if p := cfg.Aliases["primary"]; p != "" {
primary = p
}
if f := cfg.Aliases["fast"]; f != "" {
fast = f
}
}
return []string{
"ANTHROPIC_DEFAULT_OPUS_MODEL=" + primary,
"ANTHROPIC_DEFAULT_SONNET_MODEL=" + primary,
"ANTHROPIC_DEFAULT_HAIKU_MODEL=" + fast,
"CLAUDE_CODE_SUBAGENT_MODEL=" + primary,
}
}
// ConfigureAliases sets up model aliases for Claude Code.
// model: the model to use (if empty, user will be prompted to select)
// aliases: existing alias configuration to preserve/update
// Cloud-only: subagent routing (fast model) is gated to cloud models only until
// there is a better strategy for prompt caching on local models.
func (c *Claude) ConfigureAliases(ctx context.Context, model string, existingAliases map[string]string, force bool) (map[string]string, bool, error) {
aliases := make(map[string]string)
for k, v := range existingAliases {
aliases[k] = v
}
if model != "" {
aliases["primary"] = model
}
if !force && aliases["primary"] != "" {
client, _ := api.ClientFromEnvironment()
if isCloudModel(ctx, client, aliases["primary"]) {
if isCloudModel(ctx, client, aliases["fast"]) {
return aliases, false, nil
}
} else {
delete(aliases, "fast")
return aliases, false, nil
}
}
items, existingModels, cloudModels, client, err := listModels(ctx)
if err != nil {
return nil, false, err
}
fmt.Fprintf(os.Stderr, "\n%sModel Configuration%s\n\n", ansiBold, ansiReset)
if aliases["primary"] == "" || force {
primary, err := selectPrompt("Select model:", items)
fmt.Fprintf(os.Stderr, "\033[3A\033[J")
if err != nil {
return nil, false, err
}
if err := pullIfNeeded(ctx, client, existingModels, primary); err != nil {
return nil, false, err
}
if err := ensureAuth(ctx, client, cloudModels, []string{primary}); err != nil {
return nil, false, err
}
aliases["primary"] = primary
}
if isCloudModel(ctx, client, aliases["primary"]) {
if aliases["fast"] == "" || !isCloudModel(ctx, client, aliases["fast"]) {
aliases["fast"] = aliases["primary"]
}
} else {
delete(aliases, "fast")
}
return aliases, true, nil
}
// SetAliases syncs the configured aliases to the Ollama server using prefix matching.
// Cloud-only: for local models (fast is empty), we delete any existing aliases to
// prevent stale routing to a previous cloud model.
func (c *Claude) SetAliases(ctx context.Context, aliases map[string]string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
prefixes := []string{"claude-sonnet-", "claude-haiku-"}
if aliases["fast"] == "" {
for _, prefix := range prefixes {
_ = client.DeleteAliasExperimental(ctx, &api.AliasDeleteRequest{Alias: prefix})
}
return nil
}
prefixAliases := map[string]string{
"claude-sonnet-": aliases["primary"],
"claude-haiku-": aliases["fast"],
}
var errs []string
for prefix, target := range prefixAliases {
req := &api.AliasRequest{
Alias: prefix,
Target: target,
PrefixMatching: true,
}
if err := client.SetAliasExperimental(ctx, req); err != nil {
errs = append(errs, prefix)
}
}
if len(errs) > 0 {
return fmt.Errorf("failed to set aliases: %v", errs)
}
return nil
}

View File

@@ -5,6 +5,7 @@ import (
"path/filepath"
"runtime"
"slices"
"strings"
"testing"
)
@@ -103,3 +104,95 @@ func TestClaudeArgs(t *testing.T) {
})
}
}
func TestClaudeModelEnvVars(t *testing.T) {
c := &Claude{}
envMap := func(envs []string) map[string]string {
m := make(map[string]string)
for _, e := range envs {
k, v, _ := strings.Cut(e, "=")
m[k] = v
}
return m
}
t.Run("falls back to model param when no aliases saved", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
got := envMap(c.modelEnvVars("llama3.2"))
if got["ANTHROPIC_DEFAULT_OPUS_MODEL"] != "llama3.2" {
t.Errorf("OPUS = %q, want llama3.2", got["ANTHROPIC_DEFAULT_OPUS_MODEL"])
}
if got["ANTHROPIC_DEFAULT_SONNET_MODEL"] != "llama3.2" {
t.Errorf("SONNET = %q, want llama3.2", got["ANTHROPIC_DEFAULT_SONNET_MODEL"])
}
if got["ANTHROPIC_DEFAULT_HAIKU_MODEL"] != "llama3.2" {
t.Errorf("HAIKU = %q, want llama3.2", got["ANTHROPIC_DEFAULT_HAIKU_MODEL"])
}
if got["CLAUDE_CODE_SUBAGENT_MODEL"] != "llama3.2" {
t.Errorf("SUBAGENT = %q, want llama3.2", got["CLAUDE_CODE_SUBAGENT_MODEL"])
}
})
t.Run("uses primary alias for opus sonnet and subagent", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
saveIntegration("claude", []string{"qwen3:8b"})
saveAliases("claude", map[string]string{"primary": "qwen3:8b"})
got := envMap(c.modelEnvVars("qwen3:8b"))
if got["ANTHROPIC_DEFAULT_OPUS_MODEL"] != "qwen3:8b" {
t.Errorf("OPUS = %q, want qwen3:8b", got["ANTHROPIC_DEFAULT_OPUS_MODEL"])
}
if got["ANTHROPIC_DEFAULT_SONNET_MODEL"] != "qwen3:8b" {
t.Errorf("SONNET = %q, want qwen3:8b", got["ANTHROPIC_DEFAULT_SONNET_MODEL"])
}
if got["ANTHROPIC_DEFAULT_HAIKU_MODEL"] != "qwen3:8b" {
t.Errorf("HAIKU = %q, want qwen3:8b (no fast alias)", got["ANTHROPIC_DEFAULT_HAIKU_MODEL"])
}
if got["CLAUDE_CODE_SUBAGENT_MODEL"] != "qwen3:8b" {
t.Errorf("SUBAGENT = %q, want qwen3:8b", got["CLAUDE_CODE_SUBAGENT_MODEL"])
}
})
t.Run("uses fast alias for haiku", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
saveIntegration("claude", []string{"llama3.2:70b"})
saveAliases("claude", map[string]string{
"primary": "llama3.2:70b",
"fast": "llama3.2:8b",
})
got := envMap(c.modelEnvVars("llama3.2:70b"))
if got["ANTHROPIC_DEFAULT_OPUS_MODEL"] != "llama3.2:70b" {
t.Errorf("OPUS = %q, want llama3.2:70b", got["ANTHROPIC_DEFAULT_OPUS_MODEL"])
}
if got["ANTHROPIC_DEFAULT_SONNET_MODEL"] != "llama3.2:70b" {
t.Errorf("SONNET = %q, want llama3.2:70b", got["ANTHROPIC_DEFAULT_SONNET_MODEL"])
}
if got["ANTHROPIC_DEFAULT_HAIKU_MODEL"] != "llama3.2:8b" {
t.Errorf("HAIKU = %q, want llama3.2:8b", got["ANTHROPIC_DEFAULT_HAIKU_MODEL"])
}
if got["CLAUDE_CODE_SUBAGENT_MODEL"] != "llama3.2:70b" {
t.Errorf("SUBAGENT = %q, want llama3.2:70b", got["CLAUDE_CODE_SUBAGENT_MODEL"])
}
})
t.Run("alias primary overrides model param", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
saveIntegration("claude", []string{"saved-model"})
saveAliases("claude", map[string]string{"primary": "saved-model"})
got := envMap(c.modelEnvVars("different-model"))
if got["ANTHROPIC_DEFAULT_OPUS_MODEL"] != "saved-model" {
t.Errorf("OPUS = %q, want saved-model", got["ANTHROPIC_DEFAULT_OPUS_MODEL"])
}
})
}

View File

@@ -6,6 +6,7 @@ import (
"os/exec"
"strings"
"github.com/ollama/ollama/envconfig"
"golang.org/x/mod/semver"
)
@@ -32,6 +33,10 @@ func (c *Codex) Run(model string, args []string) error {
cmd.Stdin = os.Stdin
cmd.Stdout = os.Stdout
cmd.Stderr = os.Stderr
cmd.Env = append(os.Environ(),
"OPENAI_BASE_URL="+envconfig.Host().String()+"/v1/",
"OPENAI_API_KEY=ollama",
)
return cmd.Run()
}

View File

@@ -6,14 +6,14 @@ import (
"encoding/json"
"errors"
"fmt"
"log/slog"
"os"
"path/filepath"
"strings"
)
type integration struct {
Models []string `json:"models"`
Models []string `json:"models"`
Aliases map[string]string `json:"aliases,omitempty"`
}
type config struct {
@@ -53,7 +53,6 @@ func migrateConfig() (bool, error) {
var js json.RawMessage
if err := json.Unmarshal(oldData, &js); err != nil {
slog.Warn("legacy config has invalid JSON, skipping migration", "path", oldPath, "error", err)
return false, nil
}
@@ -72,7 +71,6 @@ func migrateConfig() (bool, error) {
_ = os.Remove(oldPath)
_ = os.Remove(filepath.Dir(oldPath)) // clean up empty directory
slog.Info("migrated config", "from", oldPath, "to", newPath)
return true, nil
}
@@ -133,8 +131,16 @@ func saveIntegration(appName string, models []string) error {
return err
}
cfg.Integrations[strings.ToLower(appName)] = &integration{
Models: models,
key := strings.ToLower(appName)
existing := cfg.Integrations[key]
var aliases map[string]string
if existing != nil && existing.Aliases != nil {
aliases = existing.Aliases
}
cfg.Integrations[key] = &integration{
Models: models,
Aliases: aliases,
}
return save(cfg)
@@ -154,6 +160,29 @@ func loadIntegration(appName string) (*integration, error) {
return ic, nil
}
func saveAliases(appName string, aliases map[string]string) error {
if appName == "" {
return errors.New("app name cannot be empty")
}
cfg, err := load()
if err != nil {
return err
}
key := strings.ToLower(appName)
existing := cfg.Integrations[key]
if existing == nil {
existing = &integration{}
}
// Replace aliases entirely (not merge) so deletions are persisted
existing.Aliases = aliases
cfg.Integrations[key] = existing
return save(cfg)
}
func listIntegrations() ([]integration, error) {
cfg, err := load()
if err != nil {

View File

@@ -0,0 +1,677 @@
package config
import (
"context"
"errors"
"os"
"path/filepath"
"testing"
)
func TestSetAliases_CloudModel(t *testing.T) {
// Test the SetAliases logic by checking the alias map behavior
aliases := map[string]string{
"primary": "kimi-k2.5:cloud",
"fast": "kimi-k2.5:cloud",
}
// Verify fast is set (cloud model behavior)
if aliases["fast"] == "" {
t.Error("cloud model should have fast alias set")
}
if aliases["fast"] != aliases["primary"] {
t.Errorf("fast should equal primary for auto-set, got fast=%q primary=%q", aliases["fast"], aliases["primary"])
}
}
func TestSetAliases_LocalModel(t *testing.T) {
aliases := map[string]string{
"primary": "llama3.2:latest",
}
// Simulate local model behavior: fast should be empty
delete(aliases, "fast")
if aliases["fast"] != "" {
t.Error("local model should have empty fast alias")
}
}
func TestSaveAliases_ReplacesNotMerges(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// First save with both primary and fast
initial := map[string]string{
"primary": "cloud-model",
"fast": "cloud-model",
}
if err := saveAliases("claude", initial); err != nil {
t.Fatalf("failed to save initial aliases: %v", err)
}
// Verify both are saved
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if loaded.Aliases["fast"] != "cloud-model" {
t.Errorf("expected fast=cloud-model, got %q", loaded.Aliases["fast"])
}
// Now save without fast (simulating switch to local model)
updated := map[string]string{
"primary": "local-model",
// fast intentionally missing
}
if err := saveAliases("claude", updated); err != nil {
t.Fatalf("failed to save updated aliases: %v", err)
}
// Verify fast is GONE (not merged/preserved)
loaded, err = loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load after update: %v", err)
}
if loaded.Aliases["fast"] != "" {
t.Errorf("fast should be removed after saving without it, got %q", loaded.Aliases["fast"])
}
if loaded.Aliases["primary"] != "local-model" {
t.Errorf("primary should be updated to local-model, got %q", loaded.Aliases["primary"])
}
}
func TestSaveAliases_PreservesModels(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// First save integration with models
if err := saveIntegration("claude", []string{"model1", "model2"}); err != nil {
t.Fatalf("failed to save integration: %v", err)
}
// Then update aliases
aliases := map[string]string{"primary": "new-model"}
if err := saveAliases("claude", aliases); err != nil {
t.Fatalf("failed to save aliases: %v", err)
}
// Verify models are preserved
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if len(loaded.Models) != 2 || loaded.Models[0] != "model1" {
t.Errorf("models should be preserved, got %v", loaded.Models)
}
}
// TestSaveAliases_EmptyMap clears all aliases
func TestSaveAliases_EmptyMap(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Save with aliases
if err := saveAliases("claude", map[string]string{"primary": "model", "fast": "model"}); err != nil {
t.Fatalf("failed to save: %v", err)
}
// Save empty map
if err := saveAliases("claude", map[string]string{}); err != nil {
t.Fatalf("failed to save empty: %v", err)
}
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if len(loaded.Aliases) != 0 {
t.Errorf("aliases should be empty, got %v", loaded.Aliases)
}
}
// TestSaveAliases_NilMap handles nil gracefully
func TestSaveAliases_NilMap(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Save with aliases first
if err := saveAliases("claude", map[string]string{"primary": "model"}); err != nil {
t.Fatalf("failed to save: %v", err)
}
// Save nil map - should clear aliases
if err := saveAliases("claude", nil); err != nil {
t.Fatalf("failed to save nil: %v", err)
}
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if len(loaded.Aliases) > 0 {
t.Errorf("aliases should be nil or empty, got %v", loaded.Aliases)
}
}
// TestSaveAliases_EmptyAppName returns error
func TestSaveAliases_EmptyAppName(t *testing.T) {
err := saveAliases("", map[string]string{"primary": "model"})
if err == nil {
t.Error("expected error for empty app name")
}
}
func TestSaveAliases_CaseInsensitive(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
if err := saveAliases("Claude", map[string]string{"primary": "model1"}); err != nil {
t.Fatalf("failed to save: %v", err)
}
// Load with different case
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if loaded.Aliases["primary"] != "model1" {
t.Errorf("expected primary=model1, got %q", loaded.Aliases["primary"])
}
// Update with different case
if err := saveAliases("CLAUDE", map[string]string{"primary": "model2"}); err != nil {
t.Fatalf("failed to update: %v", err)
}
loaded, err = loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load after update: %v", err)
}
if loaded.Aliases["primary"] != "model2" {
t.Errorf("expected primary=model2, got %q", loaded.Aliases["primary"])
}
}
// TestSaveAliases_CreatesIntegration creates integration if it doesn't exist
func TestSaveAliases_CreatesIntegration(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Save aliases for non-existent integration
if err := saveAliases("newintegration", map[string]string{"primary": "model"}); err != nil {
t.Fatalf("failed to save: %v", err)
}
loaded, err := loadIntegration("newintegration")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if loaded.Aliases["primary"] != "model" {
t.Errorf("expected primary=model, got %q", loaded.Aliases["primary"])
}
}
func TestConfigureAliases_AliasMap(t *testing.T) {
t.Run("cloud model auto-sets fast to primary", func(t *testing.T) {
aliases := make(map[string]string)
aliases["primary"] = "cloud-model"
// Simulate cloud model behavior
isCloud := true
if isCloud {
if aliases["fast"] == "" {
aliases["fast"] = aliases["primary"]
}
}
if aliases["fast"] != "cloud-model" {
t.Errorf("expected fast=cloud-model, got %q", aliases["fast"])
}
})
t.Run("cloud model preserves custom fast", func(t *testing.T) {
aliases := map[string]string{
"primary": "cloud-model",
"fast": "custom-fast-model",
}
// Simulate cloud model behavior - should preserve existing fast
isCloud := true
if isCloud {
if aliases["fast"] == "" {
aliases["fast"] = aliases["primary"]
}
}
if aliases["fast"] != "custom-fast-model" {
t.Errorf("expected fast=custom-fast-model (preserved), got %q", aliases["fast"])
}
})
t.Run("local model clears fast", func(t *testing.T) {
aliases := map[string]string{
"primary": "local-model",
"fast": "should-be-cleared",
}
// Simulate local model behavior
isCloud := false
if !isCloud {
delete(aliases, "fast")
}
if aliases["fast"] != "" {
t.Errorf("expected fast to be cleared, got %q", aliases["fast"])
}
})
t.Run("switching cloud to local clears fast", func(t *testing.T) {
// Start with cloud config
aliases := map[string]string{
"primary": "cloud-model",
"fast": "cloud-model",
}
// Switch to local
aliases["primary"] = "local-model"
isCloud := false
if !isCloud {
delete(aliases, "fast")
}
if aliases["fast"] != "" {
t.Errorf("fast should be cleared when switching to local, got %q", aliases["fast"])
}
if aliases["primary"] != "local-model" {
t.Errorf("primary should be updated, got %q", aliases["primary"])
}
})
t.Run("switching local to cloud sets fast", func(t *testing.T) {
// Start with local config (no fast)
aliases := map[string]string{
"primary": "local-model",
}
// Switch to cloud
aliases["primary"] = "cloud-model"
isCloud := true
if isCloud {
if aliases["fast"] == "" {
aliases["fast"] = aliases["primary"]
}
}
if aliases["fast"] != "cloud-model" {
t.Errorf("fast should be set when switching to cloud, got %q", aliases["fast"])
}
})
}
func TestSetAliases_PrefixMapping(t *testing.T) {
// This tests the expected mapping without needing a real client
aliases := map[string]string{
"primary": "my-cloud-model",
"fast": "my-fast-model",
}
expectedMappings := map[string]string{
"claude-sonnet-": aliases["primary"],
"claude-haiku-": aliases["fast"],
}
if expectedMappings["claude-sonnet-"] != "my-cloud-model" {
t.Errorf("claude-sonnet- should map to primary")
}
if expectedMappings["claude-haiku-"] != "my-fast-model" {
t.Errorf("claude-haiku- should map to fast")
}
}
func TestSetAliases_LocalDeletesPrefixes(t *testing.T) {
aliases := map[string]string{
"primary": "local-model",
// fast is empty/missing - indicates local model
}
prefixesToDelete := []string{"claude-sonnet-", "claude-haiku-"}
// Verify the logic: when fast is empty, we should delete
if aliases["fast"] != "" {
t.Error("fast should be empty for local model")
}
// Verify we have the right prefixes to delete
if len(prefixesToDelete) != 2 {
t.Errorf("expected 2 prefixes to delete, got %d", len(prefixesToDelete))
}
}
// TestAtomicUpdate_ServerFailsConfigNotSaved simulates atomic update behavior
func TestAtomicUpdate_ServerFailsConfigNotSaved(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Simulate: server fails, config should NOT be saved
serverErr := errors.New("server unavailable")
if serverErr == nil {
t.Error("config should NOT be saved when server fails")
}
}
// TestAtomicUpdate_ServerSucceedsConfigSaved simulates successful atomic update
func TestAtomicUpdate_ServerSucceedsConfigSaved(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Simulate: server succeeds, config should be saved
var serverErr error
if serverErr != nil {
t.Fatal("server should succeed")
}
if err := saveAliases("claude", map[string]string{"primary": "model"}); err != nil {
t.Fatalf("saveAliases failed: %v", err)
}
// Verify it was actually saved
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if loaded.Aliases["primary"] != "model" {
t.Errorf("expected primary=model, got %q", loaded.Aliases["primary"])
}
}
func TestConfigFile_PreservesUnknownFields(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Write config with extra fields
configPath := filepath.Join(tmpDir, ".ollama", "config.json")
os.MkdirAll(filepath.Dir(configPath), 0o755)
// Note: Our config struct only has Integrations, so top-level unknown fields
// won't be preserved by our current implementation. This test documents that.
initialConfig := `{
"integrations": {
"claude": {
"models": ["model1"],
"aliases": {"primary": "model1"},
"unknownField": "should be lost"
}
},
"topLevelUnknown": "will be lost"
}`
os.WriteFile(configPath, []byte(initialConfig), 0o644)
// Update aliases
if err := saveAliases("claude", map[string]string{"primary": "model2"}); err != nil {
t.Fatalf("failed to save: %v", err)
}
// Read raw file to check
data, _ := os.ReadFile(configPath)
content := string(data)
// models should be preserved
if !contains(content, "model1") {
t.Error("models should be preserved")
}
// primary should be updated
if !contains(content, "model2") {
t.Error("primary should be updated to model2")
}
}
func contains(s, substr string) bool {
return len(s) >= len(substr) && (s == substr || len(s) > 0 && containsHelper(s, substr))
}
func containsHelper(s, substr string) bool {
for i := 0; i <= len(s)-len(substr); i++ {
if s[i:i+len(substr)] == substr {
return true
}
}
return false
}
func TestClaudeImplementsAliasConfigurer(t *testing.T) {
c := &Claude{}
var _ AliasConfigurer = c // Compile-time check
}
func TestModelNameEdgeCases(t *testing.T) {
testCases := []struct {
name string
model string
}{
{"simple", "llama3.2"},
{"with tag", "llama3.2:latest"},
{"with cloud tag", "kimi-k2.5:cloud"},
{"with namespace", "library/llama3.2"},
{"with dots", "glm-4.7-flash"},
{"with numbers", "qwen3:8b"},
}
for _, tc := range testCases {
t.Run(tc.name, func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
aliases := map[string]string{"primary": tc.model}
if err := saveAliases("claude", aliases); err != nil {
t.Fatalf("failed to save model %q: %v", tc.model, err)
}
loaded, err := loadIntegration("claude")
if err != nil {
t.Fatalf("failed to load: %v", err)
}
if loaded.Aliases["primary"] != tc.model {
t.Errorf("expected primary=%q, got %q", tc.model, loaded.Aliases["primary"])
}
})
}
}
func TestSwitchingScenarios(t *testing.T) {
t.Run("cloud to local removes fast", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Initial cloud config
if err := saveAliases("claude", map[string]string{
"primary": "cloud-model",
"fast": "cloud-model",
}); err != nil {
t.Fatal(err)
}
// Switch to local (no fast)
if err := saveAliases("claude", map[string]string{
"primary": "local-model",
}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
if loaded.Aliases["fast"] != "" {
t.Errorf("fast should be removed, got %q", loaded.Aliases["fast"])
}
if loaded.Aliases["primary"] != "local-model" {
t.Errorf("primary should be local-model, got %q", loaded.Aliases["primary"])
}
})
t.Run("local to cloud adds fast", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Initial local config
if err := saveAliases("claude", map[string]string{
"primary": "local-model",
}); err != nil {
t.Fatal(err)
}
// Switch to cloud (with fast)
if err := saveAliases("claude", map[string]string{
"primary": "cloud-model",
"fast": "cloud-model",
}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
if loaded.Aliases["fast"] != "cloud-model" {
t.Errorf("fast should be cloud-model, got %q", loaded.Aliases["fast"])
}
})
t.Run("cloud to different cloud updates both", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Initial cloud config
if err := saveAliases("claude", map[string]string{
"primary": "cloud-model-1",
"fast": "cloud-model-1",
}); err != nil {
t.Fatal(err)
}
// Switch to different cloud
if err := saveAliases("claude", map[string]string{
"primary": "cloud-model-2",
"fast": "cloud-model-2",
}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
if loaded.Aliases["primary"] != "cloud-model-2" {
t.Errorf("primary should be cloud-model-2, got %q", loaded.Aliases["primary"])
}
if loaded.Aliases["fast"] != "cloud-model-2" {
t.Errorf("fast should be cloud-model-2, got %q", loaded.Aliases["fast"])
}
})
}
func TestToolCapabilityFiltering(t *testing.T) {
t.Run("all models checked for tool capability", func(t *testing.T) {
// Both cloud and local models are checked for tool capability via Show API
// Only models with "tools" in capabilities are included
m := modelInfo{Name: "tool-model", Remote: false, ToolCapable: true}
if !m.ToolCapable {
t.Error("tool capable model should be marked as such")
}
})
t.Run("modelInfo includes ToolCapable field", func(t *testing.T) {
m := modelInfo{Name: "test", Remote: true, ToolCapable: true}
if !m.ToolCapable {
t.Error("ToolCapable field should be accessible")
}
})
}
func TestIsCloudModel_RequiresClient(t *testing.T) {
t.Run("nil client always returns false", func(t *testing.T) {
// isCloudModel now only uses Show API, no suffix detection
if isCloudModel(context.Background(), nil, "model:cloud") {
t.Error("nil client should return false regardless of suffix")
}
if isCloudModel(context.Background(), nil, "local-model") {
t.Error("nil client should return false")
}
})
}
func TestModelsAndAliasesMustStayInSync(t *testing.T) {
t.Run("saveAliases followed by saveIntegration keeps them in sync", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Save aliases with one model
if err := saveAliases("claude", map[string]string{"primary": "model-a"}); err != nil {
t.Fatal(err)
}
// Save integration with same model (this is the pattern we use)
if err := saveIntegration("claude", []string{"model-a"}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
if loaded.Aliases["primary"] != loaded.Models[0] {
t.Errorf("aliases.primary (%q) != models[0] (%q)", loaded.Aliases["primary"], loaded.Models[0])
}
})
t.Run("out of sync config is detectable", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Simulate out-of-sync state (like manual edit or bug)
if err := saveIntegration("claude", []string{"old-model"}); err != nil {
t.Fatal(err)
}
if err := saveAliases("claude", map[string]string{"primary": "new-model"}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
// They should be different (this is the bug state)
if loaded.Models[0] == loaded.Aliases["primary"] {
t.Error("expected out-of-sync state for this test")
}
// The fix: when updating aliases, also update models
if err := saveIntegration("claude", []string{loaded.Aliases["primary"]}); err != nil {
t.Fatal(err)
}
loaded, _ = loadIntegration("claude")
if loaded.Models[0] != loaded.Aliases["primary"] {
t.Errorf("after fix: models[0] (%q) should equal aliases.primary (%q)",
loaded.Models[0], loaded.Aliases["primary"])
}
})
t.Run("updating primary alias updates models too", func(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Initial state
if err := saveIntegration("claude", []string{"initial-model"}); err != nil {
t.Fatal(err)
}
if err := saveAliases("claude", map[string]string{"primary": "initial-model"}); err != nil {
t.Fatal(err)
}
// Update aliases AND models together
newAliases := map[string]string{"primary": "updated-model"}
if err := saveAliases("claude", newAliases); err != nil {
t.Fatal(err)
}
if err := saveIntegration("claude", []string{newAliases["primary"]}); err != nil {
t.Fatal(err)
}
loaded, _ := loadIntegration("claude")
if loaded.Models[0] != "updated-model" {
t.Errorf("models[0] should be updated-model, got %q", loaded.Models[0])
}
if loaded.Aliases["primary"] != "updated-model" {
t.Errorf("aliases.primary should be updated-model, got %q", loaded.Aliases["primary"])
}
})
}

View File

@@ -46,6 +46,53 @@ func TestIntegrationConfig(t *testing.T) {
}
})
t.Run("save and load aliases", func(t *testing.T) {
models := []string{"llama3.2"}
if err := saveIntegration("claude", models); err != nil {
t.Fatal(err)
}
aliases := map[string]string{
"primary": "llama3.2:70b",
"fast": "llama3.2:8b",
}
if err := saveAliases("claude", aliases); err != nil {
t.Fatal(err)
}
config, err := loadIntegration("claude")
if err != nil {
t.Fatal(err)
}
if config.Aliases == nil {
t.Fatal("expected aliases to be saved")
}
for k, v := range aliases {
if config.Aliases[k] != v {
t.Errorf("alias %s: expected %s, got %s", k, v, config.Aliases[k])
}
}
})
t.Run("saveIntegration preserves aliases", func(t *testing.T) {
if err := saveIntegration("claude", []string{"model-a"}); err != nil {
t.Fatal(err)
}
if err := saveAliases("claude", map[string]string{"primary": "model-a", "fast": "model-small"}); err != nil {
t.Fatal(err)
}
if err := saveIntegration("claude", []string{"model-b"}); err != nil {
t.Fatal(err)
}
config, err := loadIntegration("claude")
if err != nil {
t.Fatal(err)
}
if config.Aliases["primary"] != "model-a" {
t.Errorf("expected aliases to be preserved, got %v", config.Aliases)
}
})
t.Run("defaultModel returns first model", func(t *testing.T) {
saveIntegration("codex", []string{"model-a", "model-b"})

View File

@@ -1,6 +1,7 @@
package config
import (
"context"
"encoding/json"
"fmt"
"os"
@@ -8,6 +9,7 @@ import (
"path/filepath"
"slices"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
)
@@ -112,9 +114,17 @@ func (d *Droid) Edit(models []string) error {
}
// Build new Ollama model entries with sequential indices (0, 1, 2, ...)
client, _ := api.ClientFromEnvironment()
var newModels []any
var defaultModelID string
for i, model := range models {
maxOutput := 64000
if isCloudModel(context.Background(), client, model) {
if l, ok := lookupCloudModelLimit(model); ok {
maxOutput = l.Output
}
}
modelID := fmt.Sprintf("custom:%s-%d", model, i)
newModels = append(newModels, modelEntry{
Model: model,
@@ -122,7 +132,7 @@ func (d *Droid) Edit(models []string) error {
BaseURL: envconfig.Host().String() + "/v1",
APIKey: "ollama",
Provider: "generic-chat-completion-api",
MaxOutputTokens: 64000,
MaxOutputTokens: maxOutput,
SupportsImages: false,
ID: modelID,
Index: i,

View File

@@ -1251,6 +1251,55 @@ func TestDroidEdit_LargeNumberOfModels(t *testing.T) {
}
}
func TestDroidEdit_LocalModelDefaultMaxOutput(t *testing.T) {
d := &Droid{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
settingsDir := filepath.Join(tmpDir, ".factory")
settingsPath := filepath.Join(settingsDir, "settings.json")
if err := d.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
data, _ := os.ReadFile(settingsPath)
var settings map[string]any
json.Unmarshal(data, &settings)
models := settings["customModels"].([]any)
entry := models[0].(map[string]any)
if entry["maxOutputTokens"] != float64(64000) {
t.Errorf("local model maxOutputTokens = %v, want 64000", entry["maxOutputTokens"])
}
}
func TestDroidEdit_CloudModelLimitsUsed(t *testing.T) {
// Verify that every cloud model in cloudModelLimits has a valid output
// value that would be used for maxOutputTokens when isCloudModel returns true.
// :cloud suffix stripping must also work since that's how users specify them.
for name, expected := range cloudModelLimits {
t.Run(name, func(t *testing.T) {
l, ok := lookupCloudModelLimit(name)
if !ok {
t.Fatalf("lookupCloudModelLimit(%q) returned false", name)
}
if l.Output != expected.Output {
t.Errorf("output = %d, want %d", l.Output, expected.Output)
}
// Also verify :cloud suffix lookup
cloudName := name + ":cloud"
l2, ok := lookupCloudModelLimit(cloudName)
if !ok {
t.Fatalf("lookupCloudModelLimit(%q) returned false", cloudName)
}
if l2.Output != expected.Output {
t.Errorf(":cloud output = %d, want %d", l2.Output, expected.Output)
}
})
}
}
func TestDroidEdit_ArraysWithMixedTypes(t *testing.T) {
d := &Droid{}
tmpDir := t.TempDir()

View File

@@ -39,6 +39,15 @@ type Editor interface {
Models() []string
}
// AliasConfigurer can configure model aliases (e.g., for subagent routing).
// Integrations like Claude and Codex use this to route model requests to local models.
type AliasConfigurer interface {
// ConfigureAliases prompts the user to configure aliases and returns the updated map.
ConfigureAliases(ctx context.Context, primaryModel string, existing map[string]string, force bool) (map[string]string, bool, error)
// SetAliases syncs the configured aliases to the server
SetAliases(ctx context.Context, aliases map[string]string) error
}
// integrations is the registry of available integrations.
var integrations = map[string]Runner{
"claude": &Claude{},
@@ -129,7 +138,11 @@ func selectModels(ctx context.Context, name, current string) ([]string, error) {
return nil, err
}
} else {
model, err := selectPrompt(fmt.Sprintf("Select model for %s:", r), items)
prompt := fmt.Sprintf("Select model for %s:", r)
if _, ok := r.(AliasConfigurer); ok {
prompt = fmt.Sprintf("Select Primary model for %s:", r)
}
model, err := selectPrompt(prompt, items)
if err != nil {
return nil, err
}
@@ -157,73 +170,123 @@ func selectModels(ctx context.Context, name, current string) ([]string, error) {
}
}
if err := ensureAuth(ctx, client, cloudModels, selected); err != nil {
return nil, err
}
return selected, nil
}
func pullIfNeeded(ctx context.Context, client *api.Client, existingModels map[string]bool, model string) error {
if existingModels[model] {
return nil
}
msg := fmt.Sprintf("Download %s?", model)
if ok, err := confirmPrompt(msg); err != nil {
return err
} else if !ok {
return errCancelled
}
fmt.Fprintf(os.Stderr, "\n")
if err := pullModel(ctx, client, model); err != nil {
return fmt.Errorf("failed to pull %s: %w", model, err)
}
return nil
}
func listModels(ctx context.Context) ([]selectItem, map[string]bool, map[string]bool, *api.Client, error) {
client, err := api.ClientFromEnvironment()
if err != nil {
return nil, nil, nil, nil, err
}
models, err := client.List(ctx)
if err != nil {
return nil, nil, nil, nil, err
}
var existing []modelInfo
for _, m := range models.Models {
existing = append(existing, modelInfo{
Name: m.Name,
Remote: m.RemoteModel != "",
})
}
items, _, existingModels, cloudModels := buildModelList(existing, nil, "")
if len(items) == 0 {
return nil, nil, nil, nil, fmt.Errorf("no models available, run 'ollama pull <model>' first")
}
return items, existingModels, cloudModels, client, nil
}
func ensureAuth(ctx context.Context, client *api.Client, cloudModels map[string]bool, selected []string) error {
var selectedCloudModels []string
for _, m := range selected {
if cloudModels[m] {
selectedCloudModels = append(selectedCloudModels, m)
}
}
if len(selectedCloudModels) > 0 {
// ensure user is signed in
user, err := client.Whoami(ctx)
if err == nil && user != nil && user.Name != "" {
return selected, nil
}
if len(selectedCloudModels) == 0 {
return nil
}
var aErr api.AuthorizationError
if !errors.As(err, &aErr) || aErr.SigninURL == "" {
return nil, err
}
user, err := client.Whoami(ctx)
if err == nil && user != nil && user.Name != "" {
return nil
}
modelList := strings.Join(selectedCloudModels, ", ")
yes, err := confirmPrompt(fmt.Sprintf("sign in to use %s?", modelList))
if err != nil || !yes {
return nil, fmt.Errorf("%s requires sign in", modelList)
}
var aErr api.AuthorizationError
if !errors.As(err, &aErr) || aErr.SigninURL == "" {
return err
}
fmt.Fprintf(os.Stderr, "\nTo sign in, navigate to:\n %s\n\n", aErr.SigninURL)
modelList := strings.Join(selectedCloudModels, ", ")
yes, err := confirmPrompt(fmt.Sprintf("sign in to use %s?", modelList))
if err != nil || !yes {
return fmt.Errorf("%s requires sign in", modelList)
}
// TODO(parthsareen): extract into auth package for cmd
// Auto-open browser (best effort, fail silently)
switch runtime.GOOS {
case "darwin":
_ = exec.Command("open", aErr.SigninURL).Start()
case "linux":
_ = exec.Command("xdg-open", aErr.SigninURL).Start()
case "windows":
_ = exec.Command("rundll32", "url.dll,FileProtocolHandler", aErr.SigninURL).Start()
}
fmt.Fprintf(os.Stderr, "\nTo sign in, navigate to:\n %s\n\n", aErr.SigninURL)
spinnerFrames := []string{"|", "/", "-", "\\"}
frame := 0
switch runtime.GOOS {
case "darwin":
_ = exec.Command("open", aErr.SigninURL).Start()
case "linux":
_ = exec.Command("xdg-open", aErr.SigninURL).Start()
case "windows":
_ = exec.Command("rundll32", "url.dll,FileProtocolHandler", aErr.SigninURL).Start()
}
fmt.Fprintf(os.Stderr, "\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[0])
spinnerFrames := []string{"|", "/", "-", "\\"}
frame := 0
ticker := time.NewTicker(200 * time.Millisecond)
defer ticker.Stop()
fmt.Fprintf(os.Stderr, "\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[0])
for {
select {
case <-ctx.Done():
fmt.Fprintf(os.Stderr, "\r\033[K")
return nil, ctx.Err()
case <-ticker.C:
frame++
fmt.Fprintf(os.Stderr, "\r\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[frame%len(spinnerFrames)])
ticker := time.NewTicker(200 * time.Millisecond)
defer ticker.Stop()
// poll every 10th frame (~2 seconds)
if frame%10 == 0 {
u, err := client.Whoami(ctx)
if err == nil && u != nil && u.Name != "" {
fmt.Fprintf(os.Stderr, "\r\033[K\033[A\r\033[K\033[1msigned in:\033[0m %s\n", u.Name)
return selected, nil
}
for {
select {
case <-ctx.Done():
fmt.Fprintf(os.Stderr, "\r\033[K")
return ctx.Err()
case <-ticker.C:
frame++
fmt.Fprintf(os.Stderr, "\r\033[90mwaiting for sign in to complete... %s\033[0m", spinnerFrames[frame%len(spinnerFrames)])
// poll every 10th frame (~2 seconds)
if frame%10 == 0 {
u, err := client.Whoami(ctx)
if err == nil && u != nil && u.Name != "" {
fmt.Fprintf(os.Stderr, "\r\033[K\033[A\r\033[K\033[1msigned in:\033[0m %s\n", u.Name)
return nil
}
}
}
}
return selected, nil
}
func runIntegration(name, modelName string, args []string) error {
@@ -231,10 +294,33 @@ func runIntegration(name, modelName string, args []string) error {
if !ok {
return fmt.Errorf("unknown integration: %s", name)
}
fmt.Fprintf(os.Stderr, "\nLaunching %s with %s...\n", r, modelName)
return r.Run(modelName, args)
}
// syncAliases syncs aliases to server and saves locally for an AliasConfigurer.
func syncAliases(ctx context.Context, client *api.Client, ac AliasConfigurer, name, model string, existing map[string]string) error {
aliases := make(map[string]string)
for k, v := range existing {
aliases[k] = v
}
aliases["primary"] = model
if isCloudModel(ctx, client, model) {
if aliases["fast"] == "" || !isCloudModel(ctx, client, aliases["fast"]) {
aliases["fast"] = model
}
} else {
delete(aliases, "fast")
}
if err := ac.SetAliases(ctx, aliases); err != nil {
return err
}
return saveAliases(name, aliases)
}
// LaunchCmd returns the cobra command for launching integrations.
func LaunchCmd(checkServerHeartbeat func(cmd *cobra.Command, args []string) error) *cobra.Command {
var modelFlag string
@@ -302,9 +388,87 @@ Examples:
return fmt.Errorf("unknown integration: %s", name)
}
if !configFlag && modelFlag == "" {
if config, err := loadIntegration(name); err == nil && len(config.Models) > 0 {
return runIntegration(name, config.Models[0], passArgs)
// Handle AliasConfigurer integrations (claude, codex)
if ac, ok := r.(AliasConfigurer); ok {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
// Validate --model flag if provided
if modelFlag != "" {
if _, err := client.Show(cmd.Context(), &api.ShowRequest{Name: modelFlag}); err != nil {
return fmt.Errorf("model %q not found", modelFlag)
}
}
var model string
var existingAliases map[string]string
// Load saved config
if cfg, err := loadIntegration(name); err == nil {
existingAliases = cfg.Aliases
if len(cfg.Models) > 0 {
model = cfg.Models[0]
// AliasConfigurer integrations use single model; sanitize if multiple
if len(cfg.Models) > 1 {
_ = saveIntegration(name, []string{model})
}
}
}
// --model flag overrides saved model
if modelFlag != "" {
model = modelFlag
}
// Validate saved model still exists
if model != "" && modelFlag == "" {
if _, err := client.Show(cmd.Context(), &api.ShowRequest{Name: model}); err != nil {
fmt.Fprintf(os.Stderr, "%sConfigured model %q not found%s\n\n", ansiGray, model, ansiReset)
model = ""
}
}
// If no valid model or --config flag, show picker
if model == "" || configFlag {
aliases, _, err := ac.ConfigureAliases(cmd.Context(), model, existingAliases, configFlag)
if errors.Is(err, errCancelled) {
return nil
}
if err != nil {
return err
}
model = aliases["primary"]
existingAliases = aliases
}
// Sync aliases and save
if err := syncAliases(cmd.Context(), client, ac, name, model, existingAliases); err != nil {
fmt.Fprintf(os.Stderr, "%sWarning: Could not sync aliases: %v%s\n", ansiGray, err, ansiReset)
}
if err := saveIntegration(name, []string{model}); err != nil {
return fmt.Errorf("failed to save: %w", err)
}
// Launch (unless --config without confirmation)
if configFlag {
if launch, _ := confirmPrompt(fmt.Sprintf("Launch %s now?", r)); launch {
return runIntegration(name, model, passArgs)
}
return nil
}
return runIntegration(name, model, passArgs)
}
// Validate --model flag for non-AliasConfigurer integrations
if modelFlag != "" {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
if _, err := client.Show(cmd.Context(), &api.ShowRequest{Name: modelFlag}); err != nil {
return fmt.Errorf("model %q not found", modelFlag)
}
}
@@ -318,6 +482,8 @@ Examples:
}
}
}
} else if saved, err := loadIntegration(name); err == nil && len(saved.Models) > 0 && !configFlag {
return runIntegration(name, saved.Models[0], passArgs)
} else {
var err error
models, err = selectModels(cmd.Context(), name, "")
@@ -380,8 +546,9 @@ Examples:
}
type modelInfo struct {
Name string
Remote bool
Name string
Remote bool
ToolCapable bool
}
// buildModelList merges existing models with recommendations, sorts them, and returns
@@ -418,7 +585,7 @@ func buildModelList(existing []modelInfo, preChecked []string, current string) (
continue
}
items = append(items, rec)
if isCloudModel(rec.Name) {
if strings.HasSuffix(rec.Name, ":cloud") {
cloudModels[rec.Name] = true
}
}
@@ -478,8 +645,16 @@ func buildModelList(existing []modelInfo, preChecked []string, current string) (
return items, preChecked, existingModels, cloudModels
}
func isCloudModel(name string) bool {
return strings.HasSuffix(name, ":cloud")
// isCloudModel checks if a model is a cloud model using the Show API.
func isCloudModel(ctx context.Context, client *api.Client, name string) bool {
if client == nil {
return false
}
resp, err := client.Show(ctx, &api.ShowRequest{Name: name})
if err != nil {
return false
}
return resp.RemoteModel != ""
}
func pullModel(ctx context.Context, client *api.Client, model string) error {

View File

@@ -1,6 +1,7 @@
package config
import (
"context"
"fmt"
"slices"
"strings"
@@ -297,24 +298,15 @@ func TestParseArgs(t *testing.T) {
}
func TestIsCloudModel(t *testing.T) {
tests := []struct {
name string
want bool
}{
{"glm-4.7:cloud", true},
{"kimi-k2.5:cloud", true},
{"glm-4.7-flash", false},
{"glm-4.7-flash:latest", false},
{"cloud-model", false},
{"model:cloudish", false},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
if got := isCloudModel(tt.name); got != tt.want {
t.Errorf("isCloudModel(%q) = %v, want %v", tt.name, got, tt.want)
// isCloudModel now only uses Show API, so nil client always returns false
t.Run("nil client returns false", func(t *testing.T) {
models := []string{"glm-4.7:cloud", "kimi-k2.5:cloud", "local-model"}
for _, model := range models {
if isCloudModel(context.Background(), nil, model) {
t.Errorf("isCloudModel(%q) with nil client should return false", model)
}
})
}
}
})
}
func names(items []selectItem) []string {
@@ -509,3 +501,41 @@ func TestBuildModelList_ReturnsExistingAndCloudMaps(t *testing.T) {
t.Error("llama3.2 should not be in cloudModels")
}
}
func TestEditorIntegration_SavedConfigSkipsSelection(t *testing.T) {
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
// Save a config for opencode so it looks like a previous launch
if err := saveIntegration("opencode", []string{"llama3.2"}); err != nil {
t.Fatal(err)
}
// Verify loadIntegration returns the saved models
saved, err := loadIntegration("opencode")
if err != nil {
t.Fatal(err)
}
if len(saved.Models) == 0 {
t.Fatal("expected saved models")
}
if saved.Models[0] != "llama3.2" {
t.Errorf("expected llama3.2, got %s", saved.Models[0])
}
}
func TestAliasConfigurerInterface(t *testing.T) {
t.Run("claude implements AliasConfigurer", func(t *testing.T) {
claude := &Claude{}
if _, ok := interface{}(claude).(AliasConfigurer); !ok {
t.Error("Claude should implement AliasConfigurer")
}
})
t.Run("codex does not implement AliasConfigurer", func(t *testing.T) {
codex := &Codex{}
if _, ok := interface{}(codex).(AliasConfigurer); ok {
t.Error("Codex should not implement AliasConfigurer")
}
})
}

View File

@@ -17,8 +17,6 @@ type Openclaw struct{}
func (c *Openclaw) String() string { return "OpenClaw" }
const ansiGreen = "\033[32m"
func (c *Openclaw) Run(model string, args []string) error {
bin := "openclaw"
if _, err := exec.LookPath(bin); err != nil {

View File

@@ -1,6 +1,7 @@
package config
import (
"context"
"encoding/json"
"fmt"
"maps"
@@ -10,12 +11,53 @@ import (
"slices"
"strings"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
)
// OpenCode implements Runner and Editor for OpenCode integration
type OpenCode struct{}
// cloudModelLimit holds context and output token limits for a cloud model.
type cloudModelLimit struct {
Context int
Output int
}
// cloudModelLimits maps cloud model base names to their token limits.
// TODO(parthsareen): grab context/output limits from model info instead of hardcoding
var cloudModelLimits = map[string]cloudModelLimit{
"cogito-2.1:671b": {Context: 163_840, Output: 65_536},
"deepseek-v3.1:671b": {Context: 163_840, Output: 163_840},
"deepseek-v3.2": {Context: 163_840, Output: 65_536},
"glm-4.6": {Context: 202_752, Output: 131_072},
"glm-4.7": {Context: 202_752, Output: 131_072},
"gpt-oss:120b": {Context: 131_072, Output: 131_072},
"gpt-oss:20b": {Context: 131_072, Output: 131_072},
"kimi-k2:1t": {Context: 262_144, Output: 262_144},
"kimi-k2.5": {Context: 262_144, Output: 262_144},
"kimi-k2-thinking": {Context: 262_144, Output: 262_144},
"nemotron-3-nano:30b": {Context: 1_048_576, Output: 131_072},
"qwen3-coder:480b": {Context: 262_144, Output: 65_536},
"qwen3-coder-next": {Context: 262_144, Output: 32_768},
"qwen3-next:80b": {Context: 262_144, Output: 32_768},
}
// lookupCloudModelLimit returns the token limits for a cloud model.
// It tries the exact name first, then strips the ":cloud" suffix.
func lookupCloudModelLimit(name string) (cloudModelLimit, bool) {
if l, ok := cloudModelLimits[name]; ok {
return l, true
}
base := strings.TrimSuffix(name, ":cloud")
if base != name {
if l, ok := cloudModelLimits[base]; ok {
return l, true
}
}
return cloudModelLimit{}, false
}
func (o *OpenCode) String() string { return "OpenCode" }
func (o *OpenCode) Run(model string, args []string) error {
@@ -113,6 +155,8 @@ func (o *OpenCode) Edit(modelList []string) error {
}
}
client, _ := api.ClientFromEnvironment()
for _, model := range modelList {
if existing, ok := models[model].(map[string]any); ok {
// migrate existing models without _launch marker
@@ -122,12 +166,29 @@ func (o *OpenCode) Edit(modelList []string) error {
existing["name"] = strings.TrimSuffix(name, " [Ollama]")
}
}
if isCloudModel(context.Background(), client, model) {
if l, ok := lookupCloudModelLimit(model); ok {
existing["limit"] = map[string]any{
"context": l.Context,
"output": l.Output,
}
}
}
continue
}
models[model] = map[string]any{
entry := map[string]any{
"name": model,
"_launch": true,
}
if isCloudModel(context.Background(), client, model) {
if l, ok := lookupCloudModelLimit(model); ok {
entry["limit"] = map[string]any{
"context": l.Context,
"output": l.Output,
}
}
}
models[model] = entry
}
ollama["models"] = models

View File

@@ -2,6 +2,7 @@ package config
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
"testing"
@@ -495,6 +496,166 @@ func TestOpenCodeEdit_SpecialCharsInModelName(t *testing.T) {
}
}
func readOpenCodeModel(t *testing.T, configPath, model string) map[string]any {
t.Helper()
data, err := os.ReadFile(configPath)
if err != nil {
t.Fatal(err)
}
var cfg map[string]any
json.Unmarshal(data, &cfg)
provider := cfg["provider"].(map[string]any)
ollama := provider["ollama"].(map[string]any)
models := ollama["models"].(map[string]any)
entry, ok := models[model].(map[string]any)
if !ok {
t.Fatalf("model %s not found in config", model)
}
return entry
}
func TestOpenCodeEdit_LocalModelNoLimit(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configPath := filepath.Join(tmpDir, ".config", "opencode", "opencode.json")
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
entry := readOpenCodeModel(t, configPath, "llama3.2")
if entry["limit"] != nil {
t.Errorf("local model should not have limit set, got %v", entry["limit"])
}
}
func TestOpenCodeEdit_PreservesUserLimit(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
// Set up a model with a user-configured limit
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(`{
"provider": {
"ollama": {
"models": {
"llama3.2": {
"name": "llama3.2",
"_launch": true,
"limit": {"context": 8192, "output": 4096}
}
}
}
}
}`), 0o644)
// Re-edit should preserve the user's limit (not delete it)
if err := o.Edit([]string{"llama3.2"}); err != nil {
t.Fatal(err)
}
entry := readOpenCodeModel(t, configPath, "llama3.2")
limit, ok := entry["limit"].(map[string]any)
if !ok {
t.Fatal("user-configured limit was removed")
}
if limit["context"] != float64(8192) {
t.Errorf("context limit changed: got %v, want 8192", limit["context"])
}
if limit["output"] != float64(4096) {
t.Errorf("output limit changed: got %v, want 4096", limit["output"])
}
}
func TestOpenCodeEdit_CloudModelLimitStructure(t *testing.T) {
// Verify that when a cloud model entry has limits set (as Edit would do),
// the structure matches what opencode expects and re-edit preserves them.
o := &OpenCode{}
tmpDir := t.TempDir()
setTestHome(t, tmpDir)
configDir := filepath.Join(tmpDir, ".config", "opencode")
configPath := filepath.Join(configDir, "opencode.json")
expected := cloudModelLimits["glm-4.7"]
// Simulate a cloud model that already has the limit set by a previous Edit
os.MkdirAll(configDir, 0o755)
os.WriteFile(configPath, []byte(fmt.Sprintf(`{
"provider": {
"ollama": {
"models": {
"glm-4.7:cloud": {
"name": "glm-4.7:cloud",
"_launch": true,
"limit": {"context": %d, "output": %d}
}
}
}
}
}`, expected.Context, expected.Output)), 0o644)
// Re-edit should preserve the cloud model limit
if err := o.Edit([]string{"glm-4.7:cloud"}); err != nil {
t.Fatal(err)
}
entry := readOpenCodeModel(t, configPath, "glm-4.7:cloud")
limit, ok := entry["limit"].(map[string]any)
if !ok {
t.Fatal("cloud model limit was removed on re-edit")
}
if limit["context"] != float64(expected.Context) {
t.Errorf("context = %v, want %d", limit["context"], expected.Context)
}
if limit["output"] != float64(expected.Output) {
t.Errorf("output = %v, want %d", limit["output"], expected.Output)
}
}
func TestLookupCloudModelLimit(t *testing.T) {
tests := []struct {
name string
wantOK bool
wantContext int
wantOutput int
}{
{"glm-4.7", true, 202_752, 131_072},
{"glm-4.7:cloud", true, 202_752, 131_072},
{"kimi-k2.5", true, 262_144, 262_144},
{"kimi-k2.5:cloud", true, 262_144, 262_144},
{"deepseek-v3.2", true, 163_840, 65_536},
{"deepseek-v3.2:cloud", true, 163_840, 65_536},
{"qwen3-coder:480b", true, 262_144, 65_536},
{"qwen3-coder-next:cloud", true, 262_144, 32_768},
{"llama3.2", false, 0, 0},
{"unknown-model:cloud", false, 0, 0},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
l, ok := lookupCloudModelLimit(tt.name)
if ok != tt.wantOK {
t.Errorf("lookupCloudModelLimit(%q) ok = %v, want %v", tt.name, ok, tt.wantOK)
}
if ok {
if l.Context != tt.wantContext {
t.Errorf("context = %d, want %d", l.Context, tt.wantContext)
}
if l.Output != tt.wantOutput {
t.Errorf("output = %d, want %d", l.Output, tt.wantOutput)
}
}
})
}
}
func TestOpenCodeModels_NoConfig(t *testing.T) {
o := &OpenCode{}
tmpDir := t.TempDir()

View File

@@ -17,6 +17,7 @@ const (
ansiBold = "\033[1m"
ansiReset = "\033[0m"
ansiGray = "\033[37m"
ansiGreen = "\033[32m"
ansiClearDown = "\033[J"
)

View File

@@ -96,6 +96,14 @@ func TestSelectState(t *testing.T) {
}
})
t.Run("Enter_EmptyFilteredList_EmptyFilter_DoesNothing", func(t *testing.T) {
s := newSelectState([]selectItem{})
done, result, err := s.handleInput(eventEnter, 0)
if done || result != "" || err != nil {
t.Errorf("expected (false, '', nil), got (%v, %v, %v)", done, result, err)
}
})
t.Run("Escape_ReturnsCancelledError", func(t *testing.T) {
s := newSelectState(items)
done, result, err := s.handleInput(eventEscape, 0)
@@ -574,8 +582,19 @@ func TestRenderSelect(t *testing.T) {
var buf bytes.Buffer
renderSelect(&buf, "Select:", s)
output := buf.String()
if !strings.Contains(output, "no matches") {
t.Errorf("expected 'no matches' message, got: %s", output)
}
})
t.Run("EmptyFilteredList_EmptyFilter_ShowsNoMatches", func(t *testing.T) {
s := newSelectState([]selectItem{})
var buf bytes.Buffer
renderSelect(&buf, "Select:", s)
if !strings.Contains(buf.String(), "no matches") {
t.Error("expected 'no matches' message")
t.Error("expected 'no matches' message for empty list with no filter")
}
})

View File

@@ -10,19 +10,21 @@ import (
"github.com/ollama/ollama/api"
)
var errNotRunning = errors.New("could not connect to ollama server, run 'ollama serve' to start it")
func startApp(ctx context.Context, client *api.Client) error {
exe, err := os.Executable()
if err != nil {
return err
return errNotRunning
}
link, err := os.Readlink(exe)
if err != nil {
return err
return errNotRunning
}
r := regexp.MustCompile(`^.*/Ollama\s?\d*.app`)
m := r.FindStringSubmatch(link)
if len(m) != 1 {
return errors.New("could not find ollama app")
return errNotRunning
}
if err := exec.Command("/usr/bin/open", "-j", "-a", m[0], "--args", "--fast-startup").Run(); err != nil {
return err

View File

@@ -188,8 +188,6 @@ func LogLevel() slog.Level {
var (
// FlashAttention enables the experimental flash attention feature.
FlashAttention = BoolWithDefault("OLLAMA_FLASH_ATTENTION")
// DebugLogRequests logs inference requests to disk for replay/debugging.
DebugLogRequests = Bool("OLLAMA_DEBUG_LOG_REQUESTS")
// KvCacheType is the quantization type for the K/V cache.
KvCacheType = String("OLLAMA_KV_CACHE_TYPE")
// NoHistory disables readline history.
@@ -275,27 +273,26 @@ type EnvVar struct {
func AsMap() map[string]EnvVar {
ret := map[string]EnvVar{
"OLLAMA_DEBUG": {"OLLAMA_DEBUG", LogLevel(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
"OLLAMA_DEBUG_LOG_REQUESTS": {"OLLAMA_DEBUG_LOG_REQUESTS", DebugLogRequests(), "Log inference request bodies and replay curl commands to a temp directory"},
"OLLAMA_FLASH_ATTENTION": {"OLLAMA_FLASH_ATTENTION", FlashAttention(false), "Enabled flash attention"},
"OLLAMA_KV_CACHE_TYPE": {"OLLAMA_KV_CACHE_TYPE", KvCacheType(), "Quantization type for the K/V cache (default: f16)"},
"OLLAMA_GPU_OVERHEAD": {"OLLAMA_GPU_OVERHEAD", GpuOverhead(), "Reserve a portion of VRAM per GPU (bytes)"},
"OLLAMA_HOST": {"OLLAMA_HOST", Host(), "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_KEEP_ALIVE": {"OLLAMA_KEEP_ALIVE", KeepAlive(), "The duration that models stay loaded in memory (default \"5m\")"},
"OLLAMA_LLM_LIBRARY": {"OLLAMA_LLM_LIBRARY", LLMLibrary(), "Set LLM library to bypass autodetection"},
"OLLAMA_LOAD_TIMEOUT": {"OLLAMA_LOAD_TIMEOUT", LoadTimeout(), "How long to allow model loads to stall before giving up (default \"5m\")"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners(), "Maximum number of loaded models per GPU"},
"OLLAMA_MAX_QUEUE": {"OLLAMA_MAX_QUEUE", MaxQueue(), "Maximum number of queued requests"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", Models(), "The path to the models directory"},
"OLLAMA_NOHISTORY": {"OLLAMA_NOHISTORY", NoHistory(), "Do not preserve readline history"},
"OLLAMA_NOPRUNE": {"OLLAMA_NOPRUNE", NoPrune(), "Do not prune model blobs on startup"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel(), "Maximum number of parallel requests"},
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", AllowedOrigins(), "A comma separated list of allowed origins"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
"OLLAMA_MULTIUSER_CACHE": {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
"OLLAMA_CONTEXT_LENGTH": {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4k/32k/256k based on VRAM)"},
"OLLAMA_NEW_ENGINE": {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
"OLLAMA_REMOTES": {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
"OLLAMA_DEBUG": {"OLLAMA_DEBUG", LogLevel(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
"OLLAMA_FLASH_ATTENTION": {"OLLAMA_FLASH_ATTENTION", FlashAttention(false), "Enabled flash attention"},
"OLLAMA_KV_CACHE_TYPE": {"OLLAMA_KV_CACHE_TYPE", KvCacheType(), "Quantization type for the K/V cache (default: f16)"},
"OLLAMA_GPU_OVERHEAD": {"OLLAMA_GPU_OVERHEAD", GpuOverhead(), "Reserve a portion of VRAM per GPU (bytes)"},
"OLLAMA_HOST": {"OLLAMA_HOST", Host(), "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_KEEP_ALIVE": {"OLLAMA_KEEP_ALIVE", KeepAlive(), "The duration that models stay loaded in memory (default \"5m\")"},
"OLLAMA_LLM_LIBRARY": {"OLLAMA_LLM_LIBRARY", LLMLibrary(), "Set LLM library to bypass autodetection"},
"OLLAMA_LOAD_TIMEOUT": {"OLLAMA_LOAD_TIMEOUT", LoadTimeout(), "How long to allow model loads to stall before giving up (default \"5m\")"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners(), "Maximum number of loaded models per GPU"},
"OLLAMA_MAX_QUEUE": {"OLLAMA_MAX_QUEUE", MaxQueue(), "Maximum number of queued requests"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", Models(), "The path to the models directory"},
"OLLAMA_NOHISTORY": {"OLLAMA_NOHISTORY", NoHistory(), "Do not preserve readline history"},
"OLLAMA_NOPRUNE": {"OLLAMA_NOPRUNE", NoPrune(), "Do not prune model blobs on startup"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel(), "Maximum number of parallel requests"},
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", AllowedOrigins(), "A comma separated list of allowed origins"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
"OLLAMA_MULTIUSER_CACHE": {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
"OLLAMA_CONTEXT_LENGTH": {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4k/32k/256k based on VRAM)"},
"OLLAMA_NEW_ENGINE": {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
"OLLAMA_REMOTES": {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
// Informational
"HTTP_PROXY": {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

1
go.mod
View File

@@ -24,6 +24,7 @@ require (
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/dlclark/regexp2 v1.11.4
github.com/emirpasic/gods/v2 v2.0.0-alpha
github.com/klauspost/compress v1.18.3
github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c

4
go.sum
View File

@@ -106,7 +106,6 @@ github.com/golang/protobuf v1.5.0/go.mod h1:FsONVRAS9T7sI+LIUmWTfcYkHO4aIWwzhcaS
github.com/golang/protobuf v1.5.2/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiuN0vRsmY=
github.com/golang/protobuf v1.5.4 h1:i7eJL8qZTpSEXOPTxNKhASYpMn+8e5Q6AdndVa1dWek=
github.com/golang/protobuf v1.5.4/go.mod h1:lnTiLA8Wa4RWRcIUkrtSVa5nRhsEGBg48fD6rSs7xps=
github.com/golang/snappy v0.0.3 h1:fHPg5GQYlCeLIPB9BZqMVR5nR9A+IM5zcgeTdjMYmLA=
github.com/golang/snappy v0.0.3/go.mod h1:/XxbfmMg8lxefKM7IXC3fBNl/7bRcc72aCRzEWrmP2Q=
github.com/google/flatbuffers v2.0.0+incompatible/go.mod h1:1AeVuKshWv4vARoZatz6mlQ0JxURH0Kv5+zNeJKJCa8=
github.com/google/flatbuffers v24.3.25+incompatible h1:CX395cjN9Kke9mmalRoL3d81AtFUxJM+yDthflgJGkI=
@@ -134,8 +133,9 @@ github.com/jung-kurt/gofpdf v1.0.0/go.mod h1:7Id9E/uU8ce6rXgefFLlgrJj/GYY22cpxn+
github.com/jung-kurt/gofpdf v1.0.3-0.20190309125859-24315acbbda5/go.mod h1:7Id9E/uU8ce6rXgefFLlgrJj/GYY22cpxn+r32jIOes=
github.com/kisielk/errcheck v1.5.0/go.mod h1:pFxgyoBC7bSaBwPgfKdkLd5X25qrDl4LWUI2bnpBCr8=
github.com/kisielk/gotool v1.0.0/go.mod h1:XhKaO+MFFWcvkIS/tQcRk01m1F5IRFswLeQ+oQHNcck=
github.com/klauspost/compress v1.13.1 h1:wXr2uRxZTJXHLly6qhJabee5JqIhTRoLBhDOA74hDEQ=
github.com/klauspost/compress v1.13.1/go.mod h1:8dP1Hq4DHOhN9w426knH3Rhby4rFm6D8eO+e+Dq5Gzg=
github.com/klauspost/compress v1.18.3 h1:9PJRvfbmTabkOX8moIpXPbMMbYN60bWImDDU7L+/6zw=
github.com/klauspost/compress v1.18.3/go.mod h1:R0h/fSBs8DE4ENlcrlib3PsXS61voFxhIs2DeRhCvJ4=
github.com/klauspost/cpuid/v2 v2.0.9/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
github.com/klauspost/cpuid/v2 v2.2.7 h1:ZWSB3igEs+d0qvnxR/ZBzXVmxkgt8DdzP6m9pfuVLDM=
github.com/klauspost/cpuid/v2 v2.2.7/go.mod h1:Lcz8mBdAVJIBVzewtcLocK12l3Y+JytZYpaMropDUws=

View File

@@ -34,6 +34,7 @@ import (
"github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/tokenizer"
)
type filteredEnv []string
@@ -116,7 +117,7 @@ type llamaServer struct {
type ollamaServer struct {
llmServer
textProcessor model.TextProcessor // textProcessor handles text encoding/decoding
tokenizer tokenizer.Tokenizer // tokenizer handles text encoding/decoding
}
// LoadModel will load a model from disk. The model must be in the GGML format.
@@ -142,11 +143,11 @@ func LoadModel(model string, maxArraySize int) (*ggml.GGML, error) {
// NewLlamaServer will run a server for the given GPUs
func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath string, f *ggml.GGML, adapters, projectors []string, opts api.Options, numParallel int) (LlamaServer, error) {
var llamaModel *llama.Model
var textProcessor model.TextProcessor
var tok tokenizer.Tokenizer
var err error
if envconfig.NewEngine() || f.KV().OllamaEngineRequired() {
if len(projectors) == 0 {
textProcessor, err = model.NewTextProcessor(modelPath)
tok, err = model.NewTextProcessor(modelPath)
} else {
err = errors.New("split vision models aren't supported")
}
@@ -155,7 +156,7 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
slog.Debug("model not yet supported by Ollama engine, switching to compatibility mode", "model", modelPath, "error", err)
}
}
if textProcessor == nil {
if tok == nil {
llamaModel, err = llama.LoadModelFromFile(modelPath, llama.ModelParams{VocabOnly: true})
if err != nil {
return nil, err
@@ -211,7 +212,7 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
kvct := strings.ToLower(envconfig.KvCacheType())
if textProcessor == nil {
if tok == nil {
flashAttention := ml.FlashAttentionAuto
if faUserSet {
if fa {
@@ -261,7 +262,7 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
gpuLibs := ml.LibraryPaths(gpus)
status := NewStatusWriter(os.Stderr)
cmd, port, err := StartRunner(
textProcessor != nil,
tok != nil,
modelPath,
gpuLibs,
status,
@@ -310,8 +311,8 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
}
}()
if textProcessor != nil {
return &ollamaServer{llmServer: s, textProcessor: textProcessor}, nil
if tok != nil {
return &ollamaServer{llmServer: s, tokenizer: tok}, nil
} else {
return &llamaServer{llmServer: s, ggml: f}, nil
}
@@ -1774,7 +1775,7 @@ func (s *llamaServer) Tokenize(ctx context.Context, content string) ([]int, erro
}
func (s *ollamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
tokens, err := s.textProcessor.Encode(content, false)
tokens, err := s.tokenizer.Encode(content, false)
if err != nil {
return nil, err
}
@@ -1809,7 +1810,7 @@ func (s *ollamaServer) Detokenize(ctx context.Context, tokens []int) (string, er
toks[i] = int32(t)
}
content, err := s.textProcessor.Decode(toks)
content, err := s.tokenizer.Decode(toks)
if err != nil {
return "", err
}

View File

@@ -131,12 +131,15 @@ func AnthropicMessagesMiddleware() gin.HandlerFunc {
messageID := anthropic.GenerateMessageID()
// Estimate input tokens for streaming (actual count not available until generation completes)
estimatedTokens := anthropic.EstimateInputTokens(req)
w := &AnthropicWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: messageID,
model: req.Model,
converter: anthropic.NewStreamConverter(messageID, req.Model),
converter: anthropic.NewStreamConverter(messageID, req.Model, estimatedTokens),
}
if req.Stream {

View File

@@ -11,6 +11,7 @@ import (
"time"
"github.com/gin-gonic/gin"
"github.com/klauspost/compress/zstd"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/openai"
@@ -496,6 +497,17 @@ func (w *ResponsesWriter) Write(data []byte) (int, error) {
func ResponsesMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
if c.GetHeader("Content-Encoding") == "zstd" {
reader, err := zstd.NewReader(c.Request.Body, zstd.WithDecoderMaxMemory(8<<20))
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, "failed to decompress zstd body"))
return
}
defer reader.Close()
c.Request.Body = io.NopCloser(reader)
c.Request.Header.Del("Content-Encoding")
}
var req openai.ResponsesRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, openai.NewError(http.StatusBadRequest, err.Error()))

View File

@@ -14,6 +14,7 @@ import (
"github.com/gin-gonic/gin"
"github.com/google/go-cmp/cmp"
"github.com/klauspost/compress/zstd"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/openai"
@@ -1238,3 +1239,102 @@ func TestImageEditsMiddleware(t *testing.T) {
})
}
}
func zstdCompress(t *testing.T, data []byte) []byte {
t.Helper()
var buf bytes.Buffer
w, err := zstd.NewWriter(&buf)
if err != nil {
t.Fatal(err)
}
if _, err := w.Write(data); err != nil {
t.Fatal(err)
}
if err := w.Close(); err != nil {
t.Fatal(err)
}
return buf.Bytes()
}
func TestResponsesMiddlewareZstd(t *testing.T) {
tests := []struct {
name string
body string
useZstd bool
oversized bool
wantCode int
wantModel string
wantMessage string
}{
{
name: "plain JSON",
body: `{"model": "test-model", "input": "Hello"}`,
wantCode: http.StatusOK,
wantModel: "test-model",
wantMessage: "Hello",
},
{
name: "zstd compressed",
body: `{"model": "test-model", "input": "Hello"}`,
useZstd: true,
wantCode: http.StatusOK,
wantModel: "test-model",
wantMessage: "Hello",
},
{
name: "zstd over max decompressed size",
oversized: true,
useZstd: true,
wantCode: http.StatusBadRequest,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
var capturedRequest *api.ChatRequest
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(ResponsesMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/v1/responses", func(c *gin.Context) {
c.Status(http.StatusOK)
})
var bodyReader io.Reader
if tt.oversized {
bodyReader = bytes.NewReader(zstdCompress(t, bytes.Repeat([]byte("A"), 9<<20)))
} else if tt.useZstd {
bodyReader = bytes.NewReader(zstdCompress(t, []byte(tt.body)))
} else {
bodyReader = strings.NewReader(tt.body)
}
req, _ := http.NewRequest(http.MethodPost, "/v1/responses", bodyReader)
req.Header.Set("Content-Type", "application/json")
if tt.useZstd || tt.oversized {
req.Header.Set("Content-Encoding", "zstd")
}
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
if resp.Code != tt.wantCode {
t.Fatalf("expected status %d, got %d: %s", tt.wantCode, resp.Code, resp.Body.String())
}
if tt.wantCode != http.StatusOK {
return
}
if capturedRequest == nil {
t.Fatal("expected captured request, got nil")
}
if capturedRequest.Model != tt.wantModel {
t.Fatalf("expected model %q, got %q", tt.wantModel, capturedRequest.Model)
}
if len(capturedRequest.Messages) != 1 || capturedRequest.Messages[0].Content != tt.wantMessage {
t.Fatalf("expected single user message %q, got %+v", tt.wantMessage, capturedRequest.Messages)
}
})
}
}

View File

@@ -1,272 +0,0 @@
package model
import (
"cmp"
"iter"
"slices"
"strings"
"github.com/dlclark/regexp2"
heap "github.com/emirpasic/gods/v2/trees/binaryheap"
"github.com/ollama/ollama/logutil"
)
type BytePairEncoding struct {
vocab *Vocabulary
regexps []*regexp2.Regexp
}
var _ TextProcessor = (*BytePairEncoding)(nil)
func NewBytePairEncoding(vocab *Vocabulary, pretokenizers ...string) BytePairEncoding {
if len(pretokenizers) == 0 {
// set default byte-level pretokenizer if none provided, e.g.
// https://github.com/huggingface/tokenizers/blob/main/tokenizers/src/pre_tokenizers/byte_level.rs#L44
pretokenizers = []string{`'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`}
}
return BytePairEncoding{
vocab: vocab,
regexps: slices.Collect(func(yield func(*regexp2.Regexp) bool) {
for _, p := range pretokenizers {
if !yield(regexp2.MustCompile(p, regexp2.RE2)) {
return
}
}
}),
}
}
func (bpe BytePairEncoding) Vocabulary() *Vocabulary {
return bpe.vocab
}
func (bpe BytePairEncoding) Is(id int32, special Special) bool {
return bpe.vocab.Is(id, special)
}
func (bpe *BytePairEncoding) split(s string) iter.Seq[string] {
parts := []string{s}
for _, re := range bpe.regexps {
parts = slices.Collect(func(yield func(string) bool) {
for _, part := range parts {
r := []rune(part)
var offset int
for m, _ := re.FindRunesMatch(r); m != nil; m, _ = re.FindNextMatch(m) {
if offset-m.Index != 0 {
if !yield(string(r[:m.Index])) {
return
}
}
if !yield(m.String()) {
return
}
offset = m.Index + m.Length
}
if offset < len(r) {
if !yield(string(r[offset:])) {
return
}
}
}
})
}
return slices.Values(parts)
}
// fragment is a string fragment and their corresponding token IDs
type fragment struct {
value string
ids []int32
}
// pair is a pair of runes and its rank
type pair struct {
a, b int
rank int
value string
}
type merge struct {
p, n int
runes []rune
}
func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
fragments := []fragment{{value: s}}
for _, special := range bpe.vocab.SpecialVocabulary() {
// TODO: process special tokens concurrently
id := bpe.vocab.Encode(special)
for i := 0; i < len(fragments); i++ {
frag := fragments[i]
if len(frag.ids) > 0 {
continue
}
var middle []fragment
switch i := strings.Index(frag.value, special); {
case i < 0:
middle = append(middle, frag)
case i > 0:
middle = append(middle, fragment{value: frag.value[:i]})
fallthrough
default:
middle = append(middle, fragment{value: special, ids: []int32{id}})
if rest := frag.value[i+len(special):]; rest != "" {
middle = append(middle, fragment{value: rest})
}
}
fragments = append(fragments[:i], append(middle, fragments[i+1:]...)...)
}
}
var ids []int32
for _, frag := range fragments {
if len(frag.ids) > 0 {
ids = append(ids, frag.ids...)
continue
}
for split := range bpe.split(frag.value) {
// TODO: process splits concurrently
var sb strings.Builder
for _, b := range []byte(split) {
r := rune(b)
switch {
case r == 0x00ad:
r = 0x0143
case r <= 0x0020:
r = r + 0x0100
case r >= 0x007f && r <= 0x00a0:
r = r + 0x00a2
}
sb.WriteRune(r)
}
// short circuit if the fragment is in the vocabulary
if id := bpe.vocab.Encode(sb.String()); id >= 0 {
ids = append(ids, id)
continue
}
runes := []rune(sb.String())
merges := make([]merge, len(runes))
for r := range runes {
merges[r] = merge{
p: r - 1,
n: r + 1,
runes: []rune{runes[r]},
}
}
pairwise := func(a, b int) *pair {
if a < 0 || b >= len(runes) {
return nil
}
left, right := string(merges[a].runes), string(merges[b].runes)
rank := bpe.vocab.Merge(left, right)
if rank < 0 {
return nil
}
return &pair{
a: a,
b: b,
rank: rank,
value: left + right,
}
}
pairs := heap.NewWith(func(i, j *pair) int {
return cmp.Compare(i.rank, j.rank)
})
for i := range len(runes) - 1 {
if pair := pairwise(i, i+1); pair != nil {
pairs.Push(pair)
}
}
for !pairs.Empty() {
pair, _ := pairs.Pop()
left, right := merges[pair.a], merges[pair.b]
if len(left.runes) == 0 || len(right.runes) == 0 ||
string(left.runes)+string(right.runes) != pair.value {
continue
}
if id := bpe.vocab.Encode(pair.value); id < 0 {
continue
}
merges[pair.a].runes = append(left.runes, right.runes...)
merges[pair.b].runes = nil
merges[pair.a].n = right.n
if right.n < len(merges) {
merges[right.n].p = pair.a
}
if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
pairs.Push(pair)
}
if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
pairs.Push(pair)
}
}
for _, merge := range merges {
if len(merge.runes) > 0 {
// TODO: handle the edge case where the rune isn't in the vocabulary
if id := bpe.vocab.Encode(string(merge.runes)); id >= 0 {
ids = append(ids, id)
}
}
}
}
}
if addSpecial {
ids = bpe.vocab.addSpecials(ids)
}
logutil.Trace("encoded", "string", s, "ids", ids)
return ids, nil
}
func (bpe BytePairEncoding) Decode(ids []int32) (string, error) {
var sb strings.Builder
for _, id := range ids {
for _, r := range bpe.vocab.Decode(id) {
switch {
case r == 0x0100:
// this produces 0x00 aka NULL
continue
case r == 0x0143:
r = 0x00ad
case r > 0x0100 && r <= 0x0120:
r = r - 0x0100
case r > 0x0120 && r <= 0x0142:
r = r - 0x00a2
}
// NOTE: not using WriteRune here because it writes the UTF-8
// encoding of the rune which is _not_ what we want
if err := sb.WriteByte(byte(r)); err != nil {
return "", err
}
}
}
logutil.Trace("decoded", "string", sb.String(), "from", ids)
return sb.String(), nil
}

View File

@@ -23,6 +23,7 @@ import (
_ "github.com/ollama/ollama/ml/backend"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
var (
@@ -133,7 +134,7 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
return m, nil
}
func NewTextProcessor(s string) (TextProcessor, error) {
func NewTextProcessor(s string) (tokenizer.Tokenizer, error) {
r, err := os.Open(s)
if err != nil {
return nil, err
@@ -150,7 +151,7 @@ func NewTextProcessor(s string) (TextProcessor, error) {
return nil, err
}
tp, ok := m.(TextProcessor)
tp, ok := m.(tokenizer.Tokenizer)
if !ok {
return nil, ErrUnsupportedTokenizer
}

View File

@@ -10,11 +10,12 @@ import (
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
TypeEmbedding *nn.Embedding `gguf:"token_types"`
@@ -129,7 +130,7 @@ func (o Options) headDim() int {
}
func New(c fs.Config) (model.Model, error) {
vocab := &model.Vocabulary{
vocab := &tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
@@ -153,17 +154,17 @@ func New(c fs.Config) (model.Model, error) {
},
}
var processor model.TextProcessor
var t tokenizer.Tokenizer
switch c.String("tokenizer.ggml.model", "bert") {
case "bert":
processor = model.NewWordPiece(vocab, true)
t = tokenizer.NewWordPiece(vocab, true)
default:
return nil, model.ErrUnsupportedTokenizer
}
return &Model{
TextProcessor: processor,
Layers: make([]EncoderLayer, c.Uint("block_count")),
Tokenizer: t,
Layers: make([]EncoderLayer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),

View File

@@ -13,6 +13,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -222,7 +223,7 @@ func (t *Layer) Forward(ctx ml.Context, hiddenStates, positions, outputs ml.Tens
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -277,8 +278,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -10,11 +10,12 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
Sam *samModel `gguf:"s"`
Vision *visionModel `gguf:"v"`
@@ -134,8 +135,8 @@ func init() {
}
m := Model{
TextProcessor: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -10,6 +10,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -27,7 +28,7 @@ func (o Options) applyRotaryPositionEmbeddings(ctx ml.Context, states, positions
type Model struct {
model.Base
model.SentencePiece
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -43,8 +44,8 @@ const (
func New(c fs.Config) (model.Model, error) {
m := Model{
SentencePiece: model.NewSentencePiece(
&model.Vocabulary{
Tokenizer: tokenizer.NewSentencePiece(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),

View File

@@ -7,11 +7,12 @@ import (
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type embedModel struct {
model.Base
model.SentencePiece
tokenizer.Tokenizer
*TextModel
poolingType pooling.Type
@@ -31,8 +32,8 @@ func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, erro
func newEmbedModel(c fs.Config) (model.Model, error) {
m := &embedModel{
SentencePiece: model.NewSentencePiece(
&model.Vocabulary{
Tokenizer: tokenizer.NewSentencePiece(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),

View File

@@ -12,11 +12,12 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
*VisionModel `gguf:"v"`
*TextModel
@@ -54,7 +55,7 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
}
func New(c fs.Config) (model.Model, error) {
vocabulary := model.Vocabulary{
vocabulary := tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
@@ -70,19 +71,19 @@ func New(c fs.Config) (model.Model, error) {
),
}
var processor model.TextProcessor
var t tokenizer.Tokenizer
switch c.String("tokenizer.ggml.model") {
case "gpt2":
processor = model.NewBytePairEncoding(&vocabulary)
t = tokenizer.NewBytePairEncoding(&vocabulary)
default:
// Previous uploads of Gemma 3 on Ollama did not have token 106
// (i.e. "<end_of_turn>") so we need to add in case it's not already present
vocabulary.EOS = append(vocabulary.EOS, int32(c.Uint("tokenizer.ggml.eot_token_id", 106)))
processor = model.NewSentencePiece(&vocabulary)
t = tokenizer.NewSentencePiece(&vocabulary)
}
m := Model{
TextProcessor: processor,
Tokenizer: t,
ImageProcessor: newImageProcessor(c),
VisionModel: newVisionModel(c),
TextModel: newTextModel(c),

View File

@@ -6,11 +6,12 @@ import (
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.SentencePiece
tokenizer.Tokenizer
*TextModel
}
@@ -23,8 +24,8 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
func New(c fs.Config) (model.Model, error) {
m := Model{
TextModel: newTextModel(c),
SentencePiece: model.NewSentencePiece(
&model.Vocabulary{
Tokenizer: tokenizer.NewSentencePiece(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),

View File

@@ -10,6 +10,7 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
var ErrOldModelFormat = errors.New("this model uses a weight format that is no longer supported; please re-download it")
@@ -198,7 +199,7 @@ func (t *Layer) Forward(ctx ml.Context, hiddenStates, positions, outputs ml.Tens
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -236,8 +237,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -11,11 +11,12 @@ import (
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
*TextModel
*VisionModel `gguf:"v"`
@@ -37,8 +38,8 @@ func New(c fs.Config) (model.Model, error) {
allEOS := append([]int32{eosTokenID}, eosTokenIDs...)
m := &Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -12,11 +12,12 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Transformer struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
TransformerBlocks []TransformerBlock `gguf:"blk"`
@@ -196,8 +197,8 @@ func (mlp *MLPBlock) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Optio
func New(c fs.Config) (model.Model, error) {
m := Transformer{
TransformerBlocks: make([]TransformerBlock, c.Uint("block_count")),
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -10,6 +10,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -59,7 +60,7 @@ func (o Options) applyRotaryPositionEmbeddings(ctx ml.Context, states, positions
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -78,7 +79,7 @@ func New(c fs.Config) (model.Model, error) {
return nil, model.ErrUnsupportedTokenizer
}
vocabulary := model.Vocabulary{
vocabulary := tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
@@ -104,8 +105,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
TextProcessor: model.NewBytePairEncoding(&vocabulary, pretokenizers...),
Layers: make([]Layer, c.Uint("block_count")),
Tokenizer: tokenizer.NewBytePairEncoding(&vocabulary, pretokenizers...),
Layers: make([]Layer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
headDim: int(c.Uint("attention.key_length")),

View File

@@ -11,6 +11,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -25,7 +26,7 @@ func (o Options) applyRotaryPositionEmbeddings(ctx ml.Context, states, positions
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -41,8 +42,8 @@ func New(c fs.Config) (model.Model, error) {
return nil, model.ErrUnsupportedModel
}
var processor model.TextProcessor
vocabulary := model.Vocabulary{
var processor tokenizer.Tokenizer
vocabulary := tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
@@ -80,16 +81,16 @@ func New(c fs.Config) (model.Model, error) {
"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
}
}
processor = model.NewBytePairEncoding(&vocabulary, pretokenizers...)
processor = tokenizer.NewBytePairEncoding(&vocabulary, pretokenizers...)
case "llama":
processor = model.NewSentencePiece(&vocabulary)
processor = tokenizer.NewSentencePiece(&vocabulary)
default:
return nil, model.ErrUnsupportedTokenizer
}
m := Model{
TextProcessor: processor,
Layers: make([]Layer, c.Uint("block_count")),
Tokenizer: processor,
Layers: make([]Layer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),

View File

@@ -11,11 +11,12 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
ImageProcessor
*VisionModel `gguf:"v"`
@@ -33,8 +34,8 @@ func (p *Projector) Forward(ctx ml.Context, visionOutputs ml.Tensor) ml.Tensor {
func New(c fs.Config) (model.Model, error) {
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -11,11 +11,12 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
*TextModel
*VisionModel `gguf:"v"`
@@ -28,12 +29,12 @@ type Model struct {
var _ model.MultimodalProcessor = (*Model)(nil)
// Implement TextProcessor interface
var _ model.TextProcessor = (*Model)(nil)
var _ tokenizer.Tokenizer = (*Model)(nil)
func New(c fs.Config) (model.Model, error) {
m := &Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -11,11 +11,12 @@ import (
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
*VisionModel `gguf:"v"`
*TextModel
@@ -32,8 +33,8 @@ const (
func New(c fs.Config) (model.Model, error) {
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -11,11 +11,12 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
TypeEmbedding *nn.Embedding `gguf:"token_types"`
@@ -178,29 +179,6 @@ func New(c fs.Config) (model.Model, error) {
numHeads := int(c.Uint("attention.head_count"))
headDim := hiddenSize / numHeads
processor := model.NewWordPiece(
&model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.cls_token_id"),
c.Uint("tokenizer.ggml.bos_token_id"),
)),
},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", true),
EOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.separator_token_id"),
c.Uint("tokenizer.ggml.eos_token_id"),
)),
},
},
false,
)
blockCount := int(c.Uint("block_count"))
moeEveryNLayers := int(c.Uint("moe_every_n_layers", 0))
layers := make([]EncoderLayer, blockCount)
@@ -219,8 +197,29 @@ func New(c fs.Config) (model.Model, error) {
}
return &Model{
TextProcessor: processor,
Layers: layers,
Tokenizer: tokenizer.NewWordPiece(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.cls_token_id"),
c.Uint("tokenizer.ggml.bos_token_id"),
)),
},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", true),
EOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.separator_token_id"),
c.Uint("tokenizer.ggml.eos_token_id"),
)),
},
},
false,
),
Layers: layers,
Options: Options{
hiddenSize: hiddenSize,
numHeads: numHeads,

View File

@@ -11,6 +11,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
const (
@@ -33,7 +34,7 @@ type Options struct {
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"`
@@ -44,28 +45,24 @@ type Model struct {
}
func New(c fs.Config) (model.Model, error) {
vocabulary := model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", false),
BOS: []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
EOS: append(
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")...,
),
}
processor := model.NewBytePairEncoding(
&vocabulary,
"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
)
m := Model{
TextProcessor: processor,
Layers: make([]Layer, c.Uint("block_count")),
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", false),
BOS: []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
EOS: append(
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")...,
),
},
"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
),
Layers: make([]Layer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),

View File

@@ -13,6 +13,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -92,7 +93,7 @@ func (d DecoderLayer) Forward(ctx ml.Context, hiddenStates, positions, outputs m
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []DecoderLayer `gguf:"blk"`
@@ -139,8 +140,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
Layers: make([]DecoderLayer, c.Uint("block_count")),
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -10,11 +10,12 @@ import (
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
*TextModel
*VisionModel `gguf:"v"`
@@ -27,8 +28,8 @@ var _ model.MultimodalProcessor = (*Model)(nil)
func New(c fs.Config) (model.Model, error) {
m := &Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -7,11 +7,12 @@ import (
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type embedModel struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
*Model
poolingType pooling.Type
@@ -34,8 +35,8 @@ func newEmbed(c fs.Config) (model.Model, error) {
layers[i].MLP = &dense{}
}
m := embedModel{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -12,6 +12,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Options struct {
@@ -159,7 +160,7 @@ func (d *Layer) Forward(ctx ml.Context, hiddenStates, positions, outputs ml.Tens
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
OutputNorm *nn.RMSNorm `gguf:"output_norm"`
@@ -218,8 +219,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -11,6 +11,7 @@ import (
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
// Options contains model configuration
@@ -207,7 +208,7 @@ func (l *Layer) Forward(ctx ml.Context, layer int, hiddenStates, positions, outp
// Model is the main Qwen3-Next model
type Model struct {
model.Base
model.BytePairEncoding
tokenizer.Tokenizer
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
OutputNorm *nn.RMSNorm `gguf:"output_norm"`
@@ -353,8 +354,8 @@ func New(c fs.Config) (model.Model, error) {
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -10,11 +10,12 @@ import (
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/tokenizer"
)
type Model struct {
model.Base
model.TextProcessor
tokenizer.Tokenizer
*TextModel
*VisionModel `gguf:"v"`
@@ -172,8 +173,8 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
func New(c fs.Config) (model.Model, error) {
m := Model{
TextProcessor: model.NewBytePairEncoding(
&model.Vocabulary{
Tokenizer: tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),

View File

@@ -1,53 +0,0 @@
package model
import (
"slices"
"testing"
"github.com/google/go-cmp/cmp"
)
func TestWordPiece(t *testing.T) {
wpm := NewWordPiece(
&Vocabulary{
Values: []string{"[UNK]", "[CLS]", "[SEP]", "▁hello", "▁world", "s", "▁!", "▁@", "▁#"},
AddBOS: true,
AddEOS: true,
BOS: []int32{1},
EOS: []int32{2},
},
true, // lowercase
)
ids, err := wpm.Encode("Hello world!", true)
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff([]int32{1, 3, 4, 6, 2}, ids); diff != "" {
t.Errorf("unexpected ids (-want +got):\n%s", diff)
}
words, err := wpm.Decode(ids)
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff("[CLS] hello world! [SEP]", words); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
}
func TestWordPieceWords(t *testing.T) {
var wpm WordPiece
basic := slices.Collect(wpm.words("Hey friend! How are you?!?"))
if diff := cmp.Diff([]string{"Hey", "friend", "!", "How", "are", "you", "?", "!", "?"}, basic); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
chinese := slices.Collect(wpm.words("野口里佳 Noguchi Rika"))
if diff := cmp.Diff([]string{"野", "口", "里", "佳", "Noguchi", "Rika"}, chinese); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
}

View File

@@ -37,6 +37,7 @@ import (
"github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/runner/common"
"github.com/ollama/ollama/sample"
"github.com/ollama/ollama/tokenizer"
_ "github.com/ollama/ollama/model/models"
)
@@ -210,9 +211,9 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
}
// calculateLogprobs converts raw logits to log probabilities and finds top K tokens
func calculateLogprobs(logits []float32, selectedToken int32, topK int, textProcessor model.TextProcessor) []llm.Logprob {
func calculateLogprobs(logits []float32, selectedToken int32, topK int, tok tokenizer.Tokenizer) []llm.Logprob {
decoder := func(tokenID int) string {
text, _ := textProcessor.Decode([]int32{int32(tokenID)})
text, _ := tok.Decode([]int32{int32(tokenID)})
return text
}
return common.CalculateLogprobs(logits, int(selectedToken), topK, decoder)
@@ -242,7 +243,7 @@ func (s *Server) inputs(prompt string, images []llm.ImageData) ([]*input.Input,
for i, part := range parts {
// text - tokenize
tokens, err := s.model.(model.TextProcessor).Encode(part, i == 0)
tokens, err := s.model.(tokenizer.Tokenizer).Encode(part, i == 0)
if err != nil {
return nil, nil, nil, err
}
@@ -764,7 +765,7 @@ func (s *Server) computeBatch(activeBatch batchState) {
nextBatchTokens[i].Token = token
// if it's an end of sequence token, break
if s.model.(model.TextProcessor).Is(token, model.SpecialEOS) {
if s.model.(tokenizer.Tokenizer).Is(token, tokenizer.SpecialEOS) {
// TODO (jmorganca): we should send this back
// as it's important for the /api/generate context
// seq.responses <- piece
@@ -773,14 +774,14 @@ func (s *Server) computeBatch(activeBatch batchState) {
continue
}
piece, err := s.model.(model.TextProcessor).Decode([]int32{token})
piece, err := s.model.(tokenizer.Tokenizer).Decode([]int32{token})
if err != nil {
panic("failed to decode token")
}
// Calculate logprobs if requested (after EOS check to avoid logprobs for EOS tokens)
if seq.logprobs {
logprobs := calculateLogprobs(logits, token, seq.topLogprobs, s.model.(model.TextProcessor))
logprobs := calculateLogprobs(logits, token, seq.topLogprobs, s.model.(tokenizer.Tokenizer))
seq.pendingLogprobs = append(seq.pendingLogprobs, logprobs...)
}
@@ -878,7 +879,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
var grammar *sample.GrammarSampler
var err error
if req.Grammar != "" {
grammar, err = sample.NewGrammarSampler(s.model.(model.TextProcessor), req.Grammar)
grammar, err = sample.NewGrammarSampler(s.model.(tokenizer.Tokenizer), req.Grammar)
if err != nil {
http.Error(w, "failed to load model vocabulary required for format", http.StatusInternalServerError)
return

View File

@@ -3,7 +3,7 @@ package runner
import (
"github.com/ollama/ollama/runner/llamarunner"
"github.com/ollama/ollama/runner/ollamarunner"
"github.com/ollama/ollama/x/mlxrunner"
"github.com/ollama/ollama/x/imagegen"
)
func Execute(args []string) error {
@@ -11,22 +11,13 @@ func Execute(args []string) error {
args = args[1:]
}
var newRunner bool
var mlxRunner bool
if len(args) > 0 && args[0] == "--ollama-engine" {
args = args[1:]
newRunner = true
}
if len(args) > 0 && args[0] == "--mlx-engine" {
args = args[1:]
mlxRunner = true
}
if mlxRunner {
return mlxrunner.Execute(args)
} else if newRunner {
return ollamarunner.Execute(args)
} else {
return llamarunner.Execute(args)
if len(args) > 0 {
switch args[0] {
case "--ollama-engine":
return ollamarunner.Execute(args[1:])
case "--imagegen-engine":
return imagegen.Execute(args[1:])
}
}
return llamarunner.Execute(args)
}

View File

@@ -7,7 +7,7 @@ import (
"slices"
"github.com/ollama/ollama/llama"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/tokenizer"
)
// token represents information about a single token during sampling
@@ -168,15 +168,15 @@ type GrammarSampler struct {
grammar *llama.Grammar
}
func NewGrammarSampler(model model.TextProcessor, grammarStr string) (*GrammarSampler, error) {
vocabIds := make([]uint32, len(model.Vocabulary().Values))
pieces := make([]string, len(model.Vocabulary().Values))
for i := range model.Vocabulary().Values {
pieces[i], _ = model.Decode([]int32{int32(i)})
func NewGrammarSampler(tok tokenizer.Tokenizer, grammarStr string) (*GrammarSampler, error) {
vocabIds := make([]uint32, len(tok.Vocabulary().Values))
pieces := make([]string, len(tok.Vocabulary().Values))
for i := range tok.Vocabulary().Values {
pieces[i], _ = tok.Decode([]int32{int32(i)})
vocabIds[i] = uint32(i)
}
grammar := llama.NewGrammar(grammarStr, vocabIds, pieces, model.Vocabulary().EOS)
grammar := llama.NewGrammar(grammarStr, vocabIds, pieces, tok.Vocabulary().EOS)
if grammar == nil {
return nil, errors.New("sample: failed to initialize grammar")
}

View File

@@ -8,7 +8,7 @@ import (
"path/filepath"
"testing"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/tokenizer"
)
func TestWeighted(t *testing.T) {
@@ -60,10 +60,10 @@ func TestWeighted(t *testing.T) {
}
}
func modelHelper(t testing.TB) model.BytePairEncoding {
func modelHelper(t testing.TB) tokenizer.Tokenizer {
t.Helper()
f, err := os.Open(filepath.Join("..", "model", "testdata", "llama3.2", "encoder.json"))
f, err := os.Open(filepath.FromSlash("../tokenizer/testdata/llama3.2/encoder.json"))
if err != nil {
t.Fatal(err)
}
@@ -81,8 +81,8 @@ func modelHelper(t testing.TB) model.BytePairEncoding {
merges := make([]string, 0, 1)
// Only need vocab for Grammar Test
return model.NewBytePairEncoding(
&model.Vocabulary{
return tokenizer.NewBytePairEncoding(
&tokenizer.Vocabulary{
Values: tokens,
Types: make([]int32, len(vocab)),
Merges: merges,

View File

@@ -1,5 +1,5 @@
#!/bin/sh
# This script installs Ollama on Linux.
# This script installs Ollama on Linux and macOS.
# It detects the current operating system architecture and installs the appropriate version of Ollama.
set -eu
@@ -27,8 +27,7 @@ require() {
echo $MISSING
}
[ "$(uname -s)" = "Linux" ] || error 'This script is intended to run on Linux only.'
OS="$(uname -s)"
ARCH=$(uname -m)
case "$ARCH" in
x86_64) ARCH="amd64" ;;
@@ -36,6 +35,65 @@ case "$ARCH" in
*) error "Unsupported architecture: $ARCH" ;;
esac
###########################################
# macOS
###########################################
if [ "$OS" = "Darwin" ]; then
NEEDS=$(require curl unzip)
if [ -n "$NEEDS" ]; then
status "ERROR: The following tools are required but missing:"
for NEED in $NEEDS; do
echo " - $NEED"
done
exit 1
fi
if [ -n "${OLLAMA_VERSION:-}" ]; then
DOWNLOAD_URL="https://github.com/ollama/ollama/releases/download/${OLLAMA_VERSION}/Ollama-darwin.zip"
else
DOWNLOAD_URL="https://github.com/ollama/ollama/releases/latest/download/Ollama-darwin.zip"
fi
if pgrep -x Ollama >/dev/null 2>&1; then
status "Stopping running Ollama instance..."
pkill -x Ollama 2>/dev/null || true
sleep 2
fi
if [ -d "/Applications/Ollama.app" ]; then
status "Removing existing Ollama installation..."
rm -rf "/Applications/Ollama.app"
fi
status "Downloading Ollama for macOS..."
curl --fail --show-error --location --progress-bar \
-o "$TEMP_DIR/Ollama-darwin.zip" "$DOWNLOAD_URL"
status "Installing Ollama to /Applications..."
unzip -q "$TEMP_DIR/Ollama-darwin.zip" -d "$TEMP_DIR"
mv "$TEMP_DIR/Ollama.app" "/Applications/"
status "Adding 'ollama' command to PATH (may require password)..."
mkdir -p "/usr/local/bin" 2>/dev/null || sudo mkdir -p "/usr/local/bin"
ln -sf "/Applications/Ollama.app/Contents/Resources/ollama" "/usr/local/bin/ollama" 2>/dev/null || \
sudo ln -sf "/Applications/Ollama.app/Contents/Resources/ollama" "/usr/local/bin/ollama"
if [ -z "${OLLAMA_NO_START:-}" ]; then
status "Starting Ollama..."
open -a Ollama --args hidden
fi
status "Install complete. You can now run 'ollama'."
exit 0
fi
###########################################
# Linux
###########################################
[ "$OS" = "Linux" ] || error 'This script is intended to run on Linux and macOS only.'
IS_WSL2=false
KERN=$(uname -r)

422
server/aliases.go Normal file
View File

@@ -0,0 +1,422 @@
package server
import (
"encoding/json"
"errors"
"fmt"
"log/slog"
"os"
"path/filepath"
"sort"
"strings"
"sync"
"github.com/ollama/ollama/manifest"
"github.com/ollama/ollama/types/model"
)
const (
serverConfigFilename = "server.json"
serverConfigVersion = 1
)
var errAliasCycle = errors.New("alias cycle detected")
type aliasEntry struct {
Alias string `json:"alias"`
Target string `json:"target"`
PrefixMatching bool `json:"prefix_matching,omitempty"`
}
type serverConfig struct {
Version int `json:"version"`
Aliases []aliasEntry `json:"aliases"`
}
type store struct {
mu sync.RWMutex
path string
entries map[string]aliasEntry // normalized alias -> entry (exact matches)
prefixEntries []aliasEntry // prefix matches, sorted longest-first
}
func createStore(path string) (*store, error) {
store := &store{
path: path,
entries: make(map[string]aliasEntry),
}
if err := store.load(); err != nil {
return nil, err
}
return store, nil
}
func (s *store) load() error {
data, err := os.ReadFile(s.path)
if err != nil {
if errors.Is(err, os.ErrNotExist) {
return nil
}
return err
}
var cfg serverConfig
if err := json.Unmarshal(data, &cfg); err != nil {
return err
}
if cfg.Version != 0 && cfg.Version != serverConfigVersion {
return fmt.Errorf("unsupported router config version %d", cfg.Version)
}
for _, entry := range cfg.Aliases {
targetName := model.ParseName(entry.Target)
if !targetName.IsValid() {
slog.Warn("invalid alias target in router config", "target", entry.Target)
continue
}
canonicalTarget := displayAliasName(targetName)
if entry.PrefixMatching {
// Prefix aliases don't need to be valid model names
alias := strings.TrimSpace(entry.Alias)
if alias == "" {
slog.Warn("empty prefix alias in router config")
continue
}
s.prefixEntries = append(s.prefixEntries, aliasEntry{
Alias: alias,
Target: canonicalTarget,
PrefixMatching: true,
})
} else {
aliasName := model.ParseName(entry.Alias)
if !aliasName.IsValid() {
slog.Warn("invalid alias name in router config", "alias", entry.Alias)
continue
}
canonicalAlias := displayAliasName(aliasName)
s.entries[normalizeAliasKey(aliasName)] = aliasEntry{
Alias: canonicalAlias,
Target: canonicalTarget,
}
}
}
// Sort prefix entries by alias length descending (longest prefix wins)
s.sortPrefixEntriesLocked()
return nil
}
func (s *store) saveLocked() error {
dir := filepath.Dir(s.path)
if err := os.MkdirAll(dir, 0o755); err != nil {
return err
}
// Combine exact and prefix entries
entries := make([]aliasEntry, 0, len(s.entries)+len(s.prefixEntries))
for _, entry := range s.entries {
entries = append(entries, entry)
}
entries = append(entries, s.prefixEntries...)
sort.Slice(entries, func(i, j int) bool {
return strings.Compare(entries[i].Alias, entries[j].Alias) < 0
})
cfg := serverConfig{
Version: serverConfigVersion,
Aliases: entries,
}
f, err := os.CreateTemp(dir, "router-*.json")
if err != nil {
return err
}
enc := json.NewEncoder(f)
enc.SetIndent("", " ")
if err := enc.Encode(cfg); err != nil {
_ = f.Close()
_ = os.Remove(f.Name())
return err
}
if err := f.Close(); err != nil {
_ = os.Remove(f.Name())
return err
}
if err := os.Chmod(f.Name(), 0o644); err != nil {
_ = os.Remove(f.Name())
return err
}
return os.Rename(f.Name(), s.path)
}
func (s *store) ResolveName(name model.Name) (model.Name, bool, error) {
// If a local model exists, do not allow alias shadowing (highest priority).
exists, err := localModelExists(name)
if err != nil {
return name, false, err
}
if exists {
return name, false, nil
}
key := normalizeAliasKey(name)
s.mu.RLock()
entry, exactMatch := s.entries[key]
var prefixMatch *aliasEntry
if !exactMatch {
// Try prefix matching - prefixEntries is sorted longest-first
nameStr := strings.ToLower(displayAliasName(name))
for i := range s.prefixEntries {
prefix := strings.ToLower(s.prefixEntries[i].Alias)
if strings.HasPrefix(nameStr, prefix) {
prefixMatch = &s.prefixEntries[i]
break // First match is longest due to sorting
}
}
}
s.mu.RUnlock()
if !exactMatch && prefixMatch == nil {
return name, false, nil
}
var current string
var visited map[string]struct{}
if exactMatch {
visited = map[string]struct{}{key: {}}
current = entry.Target
} else {
// For prefix match, use the target as-is
visited = map[string]struct{}{}
current = prefixMatch.Target
}
targetKey := normalizeAliasKeyString(current)
for {
targetName := model.ParseName(current)
if !targetName.IsValid() {
return name, false, fmt.Errorf("alias target %q is invalid", current)
}
if _, seen := visited[targetKey]; seen {
return name, false, errAliasCycle
}
visited[targetKey] = struct{}{}
s.mu.RLock()
next, ok := s.entries[targetKey]
s.mu.RUnlock()
if !ok {
return targetName, true, nil
}
current = next.Target
targetKey = normalizeAliasKeyString(current)
}
}
func (s *store) Set(alias, target model.Name, prefixMatching bool) error {
targetKey := normalizeAliasKey(target)
s.mu.Lock()
defer s.mu.Unlock()
if prefixMatching {
// For prefix aliases, we skip cycle detection since prefix matching
// works differently and the target is a specific model
aliasStr := displayAliasName(alias)
// Remove any existing prefix entry with the same alias
for i, e := range s.prefixEntries {
if strings.EqualFold(e.Alias, aliasStr) {
s.prefixEntries = append(s.prefixEntries[:i], s.prefixEntries[i+1:]...)
break
}
}
s.prefixEntries = append(s.prefixEntries, aliasEntry{
Alias: aliasStr,
Target: displayAliasName(target),
PrefixMatching: true,
})
s.sortPrefixEntriesLocked()
return s.saveLocked()
}
aliasKey := normalizeAliasKey(alias)
if aliasKey == targetKey {
return fmt.Errorf("alias cannot point to itself")
}
visited := map[string]struct{}{aliasKey: {}}
currentKey := targetKey
for {
if _, seen := visited[currentKey]; seen {
return errAliasCycle
}
visited[currentKey] = struct{}{}
next, ok := s.entries[currentKey]
if !ok {
break
}
currentKey = normalizeAliasKeyString(next.Target)
}
s.entries[aliasKey] = aliasEntry{
Alias: displayAliasName(alias),
Target: displayAliasName(target),
}
return s.saveLocked()
}
func (s *store) Delete(alias model.Name) (bool, error) {
aliasKey := normalizeAliasKey(alias)
s.mu.Lock()
defer s.mu.Unlock()
// Try exact match first
if _, ok := s.entries[aliasKey]; ok {
delete(s.entries, aliasKey)
return true, s.saveLocked()
}
// Try prefix entries
aliasStr := displayAliasName(alias)
for i, e := range s.prefixEntries {
if strings.EqualFold(e.Alias, aliasStr) {
s.prefixEntries = append(s.prefixEntries[:i], s.prefixEntries[i+1:]...)
return true, s.saveLocked()
}
}
return false, nil
}
// DeleteByString deletes an alias by its raw string value, useful for prefix
// aliases that may not be valid model names.
func (s *store) DeleteByString(alias string) (bool, error) {
alias = strings.TrimSpace(alias)
aliasLower := strings.ToLower(alias)
s.mu.Lock()
defer s.mu.Unlock()
// Try prefix entries first (since this is mainly for prefix aliases)
for i, e := range s.prefixEntries {
if strings.EqualFold(e.Alias, alias) {
s.prefixEntries = append(s.prefixEntries[:i], s.prefixEntries[i+1:]...)
return true, s.saveLocked()
}
}
// Also check exact entries by normalized key
if _, ok := s.entries[aliasLower]; ok {
delete(s.entries, aliasLower)
return true, s.saveLocked()
}
return false, nil
}
func (s *store) List() []aliasEntry {
s.mu.RLock()
defer s.mu.RUnlock()
entries := make([]aliasEntry, 0, len(s.entries)+len(s.prefixEntries))
for _, entry := range s.entries {
entries = append(entries, entry)
}
entries = append(entries, s.prefixEntries...)
sort.Slice(entries, func(i, j int) bool {
return strings.Compare(entries[i].Alias, entries[j].Alias) < 0
})
return entries
}
func normalizeAliasKey(name model.Name) string {
return strings.ToLower(displayAliasName(name))
}
func (s *store) sortPrefixEntriesLocked() {
sort.Slice(s.prefixEntries, func(i, j int) bool {
// Sort by length descending (longest prefix first)
return len(s.prefixEntries[i].Alias) > len(s.prefixEntries[j].Alias)
})
}
func normalizeAliasKeyString(value string) string {
n := model.ParseName(value)
if !n.IsValid() {
return strings.ToLower(strings.TrimSpace(value))
}
return normalizeAliasKey(n)
}
func displayAliasName(n model.Name) string {
display := n.DisplayShortest()
if strings.EqualFold(n.Tag, "latest") {
if idx := strings.LastIndex(display, ":"); idx != -1 {
return display[:idx]
}
}
return display
}
func localModelExists(name model.Name) (bool, error) {
manifests, err := manifest.Manifests(true)
if err != nil {
return false, err
}
needle := name.String()
for existing := range manifests {
if strings.EqualFold(existing.String(), needle) {
return true, nil
}
}
return false, nil
}
func serverConfigPath() string {
home, err := os.UserHomeDir()
if err != nil {
return filepath.Join(".ollama", serverConfigFilename)
}
return filepath.Join(home, ".ollama", serverConfigFilename)
}
func (s *Server) aliasStore() (*store, error) {
s.aliasesOnce.Do(func() {
s.aliases, s.aliasesErr = createStore(serverConfigPath())
})
return s.aliases, s.aliasesErr
}
func (s *Server) resolveAlias(name model.Name) (model.Name, bool, error) {
store, err := s.aliasStore()
if err != nil {
return name, false, err
}
if store == nil {
return name, false, nil
}
return store.ResolveName(name)
}

View File

@@ -1,144 +0,0 @@
package server
import (
"bytes"
"fmt"
"io"
"log/slog"
"os"
"path/filepath"
"strings"
"sync/atomic"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/envconfig"
)
type inferenceRequestLogger struct {
dir string
counter uint64
}
func newInferenceRequestLogger() (*inferenceRequestLogger, error) {
dir, err := os.MkdirTemp("", "ollama-request-logs-*")
if err != nil {
return nil, err
}
return &inferenceRequestLogger{dir: dir}, nil
}
func (s *Server) initRequestLogging() error {
if !envconfig.DebugLogRequests() {
return nil
}
requestLogger, err := newInferenceRequestLogger()
if err != nil {
return fmt.Errorf("enable OLLAMA_DEBUG_LOG_REQUESTS: %w", err)
}
s.requestLogger = requestLogger
slog.Info(fmt.Sprintf("request debug logging enabled; inference request logs will be stored in %s and include request bodies and replay curl commands", requestLogger.dir))
return nil
}
func (s *Server) withInferenceRequestLogging(route string, handlers ...gin.HandlerFunc) []gin.HandlerFunc {
if s.requestLogger == nil {
return handlers
}
return append([]gin.HandlerFunc{s.requestLogger.middleware(route)}, handlers...)
}
func (l *inferenceRequestLogger) middleware(route string) gin.HandlerFunc {
return func(c *gin.Context) {
if c.Request == nil {
c.Next()
return
}
method := c.Request.Method
host := c.Request.Host
scheme := "http"
if c.Request.TLS != nil {
scheme = "https"
}
contentType := c.GetHeader("Content-Type")
var body []byte
if c.Request.Body != nil {
var err error
body, err = io.ReadAll(c.Request.Body)
c.Request.Body = io.NopCloser(bytes.NewReader(body))
if err != nil {
slog.Warn("failed to read request body for debug logging", "route", route, "error", err)
}
}
c.Next()
l.log(route, method, scheme, host, contentType, body)
}
}
func (l *inferenceRequestLogger) log(route, method, scheme, host, contentType string, body []byte) {
if l == nil || l.dir == "" {
return
}
if contentType == "" {
contentType = "application/json"
}
if host == "" || scheme == "" {
base := envconfig.Host()
if host == "" {
host = base.Host
}
if scheme == "" {
scheme = base.Scheme
}
}
routeForFilename := sanitizeRouteForFilename(route)
timestamp := fmt.Sprintf("%s-%06d", time.Now().UTC().Format("20060102T150405.000000000Z"), atomic.AddUint64(&l.counter, 1))
bodyFilename := fmt.Sprintf("%s_%s_body.json", timestamp, routeForFilename)
curlFilename := fmt.Sprintf("%s_%s_request.sh", timestamp, routeForFilename)
bodyPath := filepath.Join(l.dir, bodyFilename)
curlPath := filepath.Join(l.dir, curlFilename)
if err := os.WriteFile(bodyPath, body, 0o600); err != nil {
slog.Warn("failed to write debug request body", "route", route, "error", err)
return
}
url := fmt.Sprintf("%s://%s%s", scheme, host, route)
curl := fmt.Sprintf("#!/bin/sh\nSCRIPT_DIR=\"$(CDPATH= cd -- \"$(dirname -- \"$0\")\" && pwd)\"\ncurl --request %s --url %q --header %q --data-binary @\"${SCRIPT_DIR}/%s\"\n", method, url, "Content-Type: "+contentType, bodyFilename)
if err := os.WriteFile(curlPath, []byte(curl), 0o600); err != nil {
slog.Warn("failed to write debug request replay command", "route", route, "error", err)
return
}
slog.Info(fmt.Sprintf("logged to %s, replay using curl with `sh %s`", bodyPath, curlPath))
}
func sanitizeRouteForFilename(route string) string {
route = strings.TrimPrefix(route, "/")
if route == "" {
return "root"
}
var b strings.Builder
b.Grow(len(route))
for _, r := range route {
if ('a' <= r && r <= 'z') || ('A' <= r && r <= 'Z') || ('0' <= r && r <= '9') {
b.WriteRune(r)
} else {
b.WriteByte('_')
}
}
return b.String()
}

View File

@@ -22,6 +22,7 @@ import (
"os/signal"
"slices"
"strings"
"sync"
"sync/atomic"
"syscall"
"time"
@@ -51,7 +52,7 @@ import (
"github.com/ollama/ollama/types/errtypes"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
"github.com/ollama/ollama/x/imagegen"
imagegenmanifest "github.com/ollama/ollama/x/imagegen/manifest"
xserver "github.com/ollama/ollama/x/server"
)
@@ -81,7 +82,9 @@ type Server struct {
addr net.Addr
sched *Scheduler
defaultNumCtx int
requestLogger *inferenceRequestLogger
aliasesOnce sync.Once
aliases *store
aliasesErr error
}
func init() {
@@ -192,9 +195,16 @@ func (s *Server) GenerateHandler(c *gin.Context) {
return
}
resolvedName, _, err := s.resolveAlias(name)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
name = resolvedName
// We cannot currently consolidate this into GetModel because all we'll
// induce infinite recursion given the current code structure.
name, err := getExistingName(name)
name, err = getExistingName(name)
if err != nil {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Model)})
return
@@ -1096,7 +1106,7 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
// For image generation models, populate details from imagegen package
if slices.Contains(m.Capabilities(), model.CapabilityImage) {
if info, err := imagegen.GetModelInfo(name.String()); err == nil {
if info, err := imagegenmanifest.GetModelInfo(name.String()); err == nil {
modelDetails.Family = info.Architecture
modelDetails.ParameterSize = format.HumanNumber(uint64(info.ParameterCount))
modelDetails.QuantizationLevel = info.Quantization
@@ -1581,27 +1591,30 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
r.POST("/api/blobs/:digest", s.CreateBlobHandler)
r.HEAD("/api/blobs/:digest", s.HeadBlobHandler)
r.POST("/api/copy", s.CopyHandler)
r.GET("/api/experimental/aliases", s.ListAliasesHandler)
r.POST("/api/experimental/aliases", s.CreateAliasHandler)
r.DELETE("/api/experimental/aliases", s.DeleteAliasHandler)
// Inference
r.GET("/api/ps", s.PsHandler)
r.POST("/api/generate", s.withInferenceRequestLogging("/api/generate", s.GenerateHandler)...)
r.POST("/api/chat", s.withInferenceRequestLogging("/api/chat", s.ChatHandler)...)
r.POST("/api/generate", s.GenerateHandler)
r.POST("/api/chat", s.ChatHandler)
r.POST("/api/embed", s.EmbedHandler)
r.POST("/api/embeddings", s.EmbeddingsHandler)
// Inference (OpenAI compatibility)
r.POST("/v1/chat/completions", s.withInferenceRequestLogging("/v1/chat/completions", middleware.ChatMiddleware(), s.ChatHandler)...)
r.POST("/v1/completions", s.withInferenceRequestLogging("/v1/completions", middleware.CompletionsMiddleware(), s.GenerateHandler)...)
r.POST("/v1/chat/completions", middleware.ChatMiddleware(), s.ChatHandler)
r.POST("/v1/completions", middleware.CompletionsMiddleware(), s.GenerateHandler)
r.POST("/v1/embeddings", middleware.EmbeddingsMiddleware(), s.EmbedHandler)
r.GET("/v1/models", middleware.ListMiddleware(), s.ListHandler)
r.GET("/v1/models/:model", middleware.RetrieveMiddleware(), s.ShowHandler)
r.POST("/v1/responses", s.withInferenceRequestLogging("/v1/responses", middleware.ResponsesMiddleware(), s.ChatHandler)...)
r.POST("/v1/responses", middleware.ResponsesMiddleware(), s.ChatHandler)
// OpenAI-compatible image generation endpoints
r.POST("/v1/images/generations", middleware.ImageGenerationsMiddleware(), s.GenerateHandler)
r.POST("/v1/images/edits", middleware.ImageEditsMiddleware(), s.GenerateHandler)
// Inference (Anthropic compatibility)
r.POST("/v1/messages", s.withInferenceRequestLogging("/v1/messages", middleware.AnthropicMessagesMiddleware(), s.ChatHandler)...)
r.POST("/v1/messages", middleware.AnthropicMessagesMiddleware(), s.ChatHandler)
if rc != nil {
// wrap old with new
@@ -1651,9 +1664,6 @@ func Serve(ln net.Listener) error {
}
s := &Server{addr: ln.Addr()}
if err := s.initRequestLogging(); err != nil {
return err
}
var rc *ollama.Registry
if useClient2 {
@@ -1954,13 +1964,20 @@ func (s *Server) ChatHandler(c *gin.Context) {
return
}
name, err := getExistingName(name)
resolvedName, _, err := s.resolveAlias(name)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
name = resolvedName
name, err = getExistingName(name)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
}
m, err := GetModel(req.Model)
m, err := GetModel(name.String())
if err != nil {
switch {
case os.IsNotExist(err):

159
server/routes_aliases.go Normal file
View File

@@ -0,0 +1,159 @@
package server
import (
"errors"
"fmt"
"io"
"net/http"
"strings"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/types/model"
)
type aliasListResponse struct {
Aliases []aliasEntry `json:"aliases"`
}
type aliasDeleteRequest struct {
Alias string `json:"alias"`
}
func (s *Server) ListAliasesHandler(c *gin.Context) {
store, err := s.aliasStore()
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var aliases []aliasEntry
if store != nil {
aliases = store.List()
}
c.JSON(http.StatusOK, aliasListResponse{Aliases: aliases})
}
func (s *Server) CreateAliasHandler(c *gin.Context) {
var req aliasEntry
if err := c.ShouldBindJSON(&req); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
return
} else if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
req.Alias = strings.TrimSpace(req.Alias)
req.Target = strings.TrimSpace(req.Target)
if req.Alias == "" || req.Target == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "alias and target are required"})
return
}
// Target must always be a valid model name
targetName := model.ParseName(req.Target)
if !targetName.IsValid() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("target %q is invalid", req.Target)})
return
}
var aliasName model.Name
if req.PrefixMatching {
// For prefix aliases, we still parse the alias to normalize it,
// but we allow any non-empty string since prefix patterns may not be valid model names
aliasName = model.ParseName(req.Alias)
// Even if not valid as a model name, we accept it for prefix matching
} else {
aliasName = model.ParseName(req.Alias)
if !aliasName.IsValid() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("alias %q is invalid", req.Alias)})
return
}
if normalizeAliasKey(aliasName) == normalizeAliasKey(targetName) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "alias cannot point to itself"})
return
}
exists, err := localModelExists(aliasName)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if exists {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("alias %q conflicts with existing model", req.Alias)})
return
}
}
store, err := s.aliasStore()
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if err := store.Set(aliasName, targetName, req.PrefixMatching); err != nil {
status := http.StatusInternalServerError
if errors.Is(err, errAliasCycle) {
status = http.StatusBadRequest
}
c.AbortWithStatusJSON(status, gin.H{"error": err.Error()})
return
}
resp := aliasEntry{
Alias: displayAliasName(aliasName),
Target: displayAliasName(targetName),
PrefixMatching: req.PrefixMatching,
}
if req.PrefixMatching && !aliasName.IsValid() {
// For prefix aliases that aren't valid model names, use the raw alias
resp.Alias = req.Alias
}
c.JSON(http.StatusOK, resp)
}
func (s *Server) DeleteAliasHandler(c *gin.Context) {
var req aliasDeleteRequest
if err := c.ShouldBindJSON(&req); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
return
} else if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
req.Alias = strings.TrimSpace(req.Alias)
if req.Alias == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "alias is required"})
return
}
store, err := s.aliasStore()
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
aliasName := model.ParseName(req.Alias)
var deleted bool
if aliasName.IsValid() {
deleted, err = store.Delete(aliasName)
} else {
// For invalid model names (like prefix aliases), try deleting by raw string
deleted, err = store.DeleteByString(req.Alias)
}
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if !deleted {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("alias %q not found", req.Alias)})
return
}
c.JSON(http.StatusOK, gin.H{"deleted": true})
}

View File

@@ -0,0 +1,426 @@
package server
import (
"encoding/json"
"net/http"
"net/http/httptest"
"net/url"
"path/filepath"
"testing"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/types/model"
)
func TestAliasShadowingRejected(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("HOME", t.TempDir())
s := Server{}
w := createRequest(t, s.CreateHandler, api.CreateRequest{
Model: "shadowed-model",
RemoteHost: "example.com",
From: "test",
Info: map[string]any{
"capabilities": []string{"completion"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.CreateAliasHandler, aliasEntry{Alias: "shadowed-model", Target: "other-model"})
if w.Code != http.StatusBadRequest {
t.Fatalf("expected status 400, got %d", w.Code)
}
}
func TestAliasResolvesForChatRemote(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("HOME", t.TempDir())
var remoteModel string
rs := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
var req api.ChatRequest
if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
t.Fatal(err)
}
remoteModel = req.Model
w.Header().Set("Content-Type", "application/json")
resp := api.ChatResponse{
Model: req.Model,
Done: true,
DoneReason: "load",
}
if err := json.NewEncoder(w).Encode(&resp); err != nil {
t.Fatal(err)
}
}))
defer rs.Close()
p, err := url.Parse(rs.URL)
if err != nil {
t.Fatal(err)
}
t.Setenv("OLLAMA_REMOTES", p.Hostname())
s := Server{}
w := createRequest(t, s.CreateHandler, api.CreateRequest{
Model: "target-model",
RemoteHost: rs.URL,
From: "test",
Info: map[string]any{
"capabilities": []string{"completion"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.CreateAliasHandler, aliasEntry{Alias: "alias-model", Target: "target-model"})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "alias-model",
Messages: []api.Message{{Role: "user", Content: "hi"}},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
var resp api.ChatResponse
if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
t.Fatal(err)
}
if resp.Model != "alias-model" {
t.Fatalf("expected response model to be alias-model, got %q", resp.Model)
}
if remoteModel != "test" {
t.Fatalf("expected remote model to be 'test', got %q", remoteModel)
}
}
func TestPrefixAliasBasicMatching(t *testing.T) {
tmpDir := t.TempDir()
store, err := createStore(filepath.Join(tmpDir, "server.json"))
if err != nil {
t.Fatal(err)
}
// Create a prefix alias: "myprefix-" -> "targetmodel"
targetName := model.ParseName("targetmodel")
// Set a prefix alias (using "myprefix-" as the pattern)
store.mu.Lock()
store.prefixEntries = append(store.prefixEntries, aliasEntry{
Alias: "myprefix-",
Target: "targetmodel",
PrefixMatching: true,
})
store.mu.Unlock()
// Test that "myprefix-foo" resolves to "targetmodel"
testName := model.ParseName("myprefix-foo")
resolved, wasResolved, err := store.ResolveName(testName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved")
}
if resolved.DisplayShortest() != targetName.DisplayShortest() {
t.Fatalf("expected resolved name to be %q, got %q", targetName.DisplayShortest(), resolved.DisplayShortest())
}
// Test that "otherprefix-foo" does not resolve
otherName := model.ParseName("otherprefix-foo")
_, wasResolved, err = store.ResolveName(otherName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if wasResolved {
t.Fatal("expected name not to be resolved")
}
// Test that exact alias takes precedence
exactAlias := model.ParseName("myprefix-exact")
exactTarget := model.ParseName("exacttarget")
if err := store.Set(exactAlias, exactTarget, false); err != nil {
t.Fatal(err)
}
resolved, wasResolved, err = store.ResolveName(exactAlias)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved")
}
if resolved.DisplayShortest() != exactTarget.DisplayShortest() {
t.Fatalf("expected resolved name to be %q (exact match), got %q", exactTarget.DisplayShortest(), resolved.DisplayShortest())
}
}
func TestPrefixAliasLongestMatchWins(t *testing.T) {
tmpDir := t.TempDir()
store, err := createStore(filepath.Join(tmpDir, "server.json"))
if err != nil {
t.Fatal(err)
}
// Add two prefix aliases with overlapping patterns
store.mu.Lock()
store.prefixEntries = []aliasEntry{
{Alias: "abc-", Target: "short-target", PrefixMatching: true},
{Alias: "abc-def-", Target: "long-target", PrefixMatching: true},
}
store.sortPrefixEntriesLocked()
store.mu.Unlock()
// "abc-def-ghi" should match the longer prefix "abc-def-"
testName := model.ParseName("abc-def-ghi")
resolved, wasResolved, err := store.ResolveName(testName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved")
}
expectedLongTarget := model.ParseName("long-target")
if resolved.DisplayShortest() != expectedLongTarget.DisplayShortest() {
t.Fatalf("expected resolved name to be %q (longest prefix match), got %q", expectedLongTarget.DisplayShortest(), resolved.DisplayShortest())
}
// "abc-xyz" should match the shorter prefix "abc-"
testName2 := model.ParseName("abc-xyz")
resolved, wasResolved, err = store.ResolveName(testName2)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved")
}
expectedShortTarget := model.ParseName("short-target")
if resolved.DisplayShortest() != expectedShortTarget.DisplayShortest() {
t.Fatalf("expected resolved name to be %q, got %q", expectedShortTarget.DisplayShortest(), resolved.DisplayShortest())
}
}
func TestPrefixAliasChain(t *testing.T) {
tmpDir := t.TempDir()
store, err := createStore(filepath.Join(tmpDir, "server.json"))
if err != nil {
t.Fatal(err)
}
// Create a chain: prefix "test-" -> "intermediate" -> "final"
intermediate := model.ParseName("intermediate")
final := model.ParseName("final")
// Add prefix alias
store.mu.Lock()
store.prefixEntries = []aliasEntry{
{Alias: "test-", Target: "intermediate", PrefixMatching: true},
}
store.mu.Unlock()
// Add exact alias for the intermediate step
if err := store.Set(intermediate, final, false); err != nil {
t.Fatal(err)
}
// "test-foo" should resolve through the chain to "final"
testName := model.ParseName("test-foo")
resolved, wasResolved, err := store.ResolveName(testName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved")
}
if resolved.DisplayShortest() != final.DisplayShortest() {
t.Fatalf("expected resolved name to be %q, got %q", final.DisplayShortest(), resolved.DisplayShortest())
}
}
func TestPrefixAliasCRUD(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("HOME", t.TempDir())
s := Server{}
// Create a prefix alias via API
w := createRequest(t, s.CreateAliasHandler, aliasEntry{
Alias: "myprefix-",
Target: "llama2",
PrefixMatching: true,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", w.Code, w.Body.String())
}
var createResp aliasEntry
if err := json.NewDecoder(w.Body).Decode(&createResp); err != nil {
t.Fatal(err)
}
if !createResp.PrefixMatching {
t.Fatal("expected prefix_matching to be true in response")
}
// List aliases and verify the prefix alias is included
w = createRequest(t, s.ListAliasesHandler, nil)
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
var listResp aliasListResponse
if err := json.NewDecoder(w.Body).Decode(&listResp); err != nil {
t.Fatal(err)
}
found := false
for _, a := range listResp.Aliases {
if a.PrefixMatching && a.Target == "llama2" {
found = true
break
}
}
if !found {
t.Fatal("expected to find prefix alias in list")
}
// Delete the prefix alias
w = createRequest(t, s.DeleteAliasHandler, aliasDeleteRequest{Alias: "myprefix-"})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", w.Code, w.Body.String())
}
// Verify it's deleted
w = createRequest(t, s.ListAliasesHandler, nil)
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
if err := json.NewDecoder(w.Body).Decode(&listResp); err != nil {
t.Fatal(err)
}
for _, a := range listResp.Aliases {
if a.PrefixMatching {
t.Fatal("expected prefix alias to be deleted")
}
}
}
func TestPrefixAliasCaseInsensitive(t *testing.T) {
tmpDir := t.TempDir()
store, err := createStore(filepath.Join(tmpDir, "server.json"))
if err != nil {
t.Fatal(err)
}
// Add a prefix alias with mixed case
store.mu.Lock()
store.prefixEntries = []aliasEntry{
{Alias: "MyPrefix-", Target: "targetmodel", PrefixMatching: true},
}
store.mu.Unlock()
// Test that matching is case-insensitive
testName := model.ParseName("myprefix-foo")
resolved, wasResolved, err := store.ResolveName(testName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved (case-insensitive)")
}
expectedTarget := model.ParseName("targetmodel")
if resolved.DisplayShortest() != expectedTarget.DisplayShortest() {
t.Fatalf("expected resolved name to be %q, got %q", expectedTarget.DisplayShortest(), resolved.DisplayShortest())
}
// Test uppercase request
testName2 := model.ParseName("MYPREFIX-BAR")
_, wasResolved, err = store.ResolveName(testName2)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected name to be resolved (uppercase)")
}
}
func TestPrefixAliasLocalModelPrecedence(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("HOME", t.TempDir())
s := Server{}
// Create a local model that would match a prefix alias
w := createRequest(t, s.CreateHandler, api.CreateRequest{
Model: "myprefix-localmodel",
RemoteHost: "example.com",
From: "test",
Info: map[string]any{
"capabilities": []string{"completion"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", w.Code, w.Body.String())
}
// Create a prefix alias that would match the local model name
w = createRequest(t, s.CreateAliasHandler, aliasEntry{
Alias: "myprefix-",
Target: "someothermodel",
PrefixMatching: true,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d: %s", w.Code, w.Body.String())
}
// Verify that resolving "myprefix-localmodel" returns the local model, not the alias target
store, err := s.aliasStore()
if err != nil {
t.Fatal(err)
}
localModelName := model.ParseName("myprefix-localmodel")
resolved, wasResolved, err := store.ResolveName(localModelName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if wasResolved {
t.Fatalf("expected local model to take precedence (wasResolved should be false), but got resolved to %q", resolved.DisplayShortest())
}
if resolved.DisplayShortest() != localModelName.DisplayShortest() {
t.Fatalf("expected resolved name to be local model %q, got %q", localModelName.DisplayShortest(), resolved.DisplayShortest())
}
// Also verify that a non-local model matching the prefix DOES resolve to the alias target
nonLocalName := model.ParseName("myprefix-nonexistent")
resolved, wasResolved, err = store.ResolveName(nonLocalName)
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if !wasResolved {
t.Fatal("expected non-local model to resolve via prefix alias")
}
expectedTarget := model.ParseName("someothermodel")
if resolved.DisplayShortest() != expectedTarget.DisplayShortest() {
t.Fatalf("expected resolved name to be %q, got %q", expectedTarget.DisplayShortest(), resolved.DisplayShortest())
}
}

View File

@@ -1,128 +0,0 @@
package server
import (
"io"
"net/http"
"net/http/httptest"
"os"
"path/filepath"
"strings"
"testing"
"github.com/gin-gonic/gin"
)
func TestInferenceRequestLoggerMiddlewareWritesReplayArtifacts(t *testing.T) {
gin.SetMode(gin.TestMode)
logDir := t.TempDir()
requestLogger := &inferenceRequestLogger{dir: logDir}
const route = "/v1/chat/completions"
const requestBody = `{"model":"test-model","messages":[{"role":"user","content":"hello"}]}`
var bodySeenByHandler string
r := gin.New()
r.POST(route, requestLogger.middleware(route), func(c *gin.Context) {
body, err := io.ReadAll(c.Request.Body)
if err != nil {
t.Fatalf("failed to read body in handler: %v", err)
}
bodySeenByHandler = string(body)
c.Status(http.StatusOK)
})
req := httptest.NewRequest(http.MethodPost, route, strings.NewReader(requestBody))
req.Host = "127.0.0.1:11434"
req.Header.Set("Content-Type", "application/json")
w := httptest.NewRecorder()
r.ServeHTTP(w, req)
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
if bodySeenByHandler != requestBody {
t.Fatalf("handler body mismatch:\nexpected: %s\ngot: %s", requestBody, bodySeenByHandler)
}
bodyFiles, err := filepath.Glob(filepath.Join(logDir, "*_v1_chat_completions_body.json"))
if err != nil {
t.Fatalf("failed to glob body logs: %v", err)
}
if len(bodyFiles) != 1 {
t.Fatalf("expected 1 body log, got %d (%v)", len(bodyFiles), bodyFiles)
}
curlFiles, err := filepath.Glob(filepath.Join(logDir, "*_v1_chat_completions_request.sh"))
if err != nil {
t.Fatalf("failed to glob curl logs: %v", err)
}
if len(curlFiles) != 1 {
t.Fatalf("expected 1 curl log, got %d (%v)", len(curlFiles), curlFiles)
}
bodyData, err := os.ReadFile(bodyFiles[0])
if err != nil {
t.Fatalf("failed to read body log: %v", err)
}
if string(bodyData) != requestBody {
t.Fatalf("body log mismatch:\nexpected: %s\ngot: %s", requestBody, string(bodyData))
}
curlData, err := os.ReadFile(curlFiles[0])
if err != nil {
t.Fatalf("failed to read curl log: %v", err)
}
curlString := string(curlData)
if !strings.Contains(curlString, "http://127.0.0.1:11434"+route) {
t.Fatalf("curl log does not contain expected route URL: %s", curlString)
}
bodyFileName := filepath.Base(bodyFiles[0])
if !strings.Contains(curlString, "@\"${SCRIPT_DIR}/"+bodyFileName+"\"") {
t.Fatalf("curl log does not reference sibling body file: %s", curlString)
}
}
func TestNewInferenceRequestLoggerCreatesDirectory(t *testing.T) {
requestLogger, err := newInferenceRequestLogger()
if err != nil {
t.Fatalf("expected no error creating request logger: %v", err)
}
t.Cleanup(func() {
_ = os.RemoveAll(requestLogger.dir)
})
if requestLogger == nil || requestLogger.dir == "" {
t.Fatalf("expected request logger directory to be set")
}
info, err := os.Stat(requestLogger.dir)
if err != nil {
t.Fatalf("expected directory to exist: %v", err)
}
if !info.IsDir() {
t.Fatalf("expected %q to be a directory", requestLogger.dir)
}
}
func TestSanitizeRouteForFilename(t *testing.T) {
tests := []struct {
route string
want string
}{
{route: "/api/generate", want: "api_generate"},
{route: "/v1/chat/completions", want: "v1_chat_completions"},
{route: "/v1/messages", want: "v1_messages"},
}
for _, tt := range tests {
if got := sanitizeRouteForFilename(tt.route); got != tt.want {
t.Fatalf("sanitizeRouteForFilename(%q) = %q, want %q", tt.route, got, tt.want)
}
}
}

View File

@@ -21,7 +21,7 @@ import (
"github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/x/mlxrunner"
"github.com/ollama/ollama/x/imagegen"
)
type LlmRequest struct {
@@ -567,16 +567,16 @@ iGPUScan:
// This supports both LLM (completion) and image generation models.
func (s *Scheduler) loadMLX(req *LlmRequest) bool {
// Determine mode based on capabilities
var mode mlxrunner.ModelMode
var mode imagegen.ModelMode
if slices.Contains(req.model.Config.Capabilities, "image") {
mode = mlxrunner.ModeImageGen
mode = imagegen.ModeImageGen
} else {
mode = mlxrunner.ModeLLM
mode = imagegen.ModeLLM
}
// Use model name for MLX (it resolves manifests by name, not file path)
modelName := req.model.ShortName
server, err := mlxrunner.NewServer(modelName, mode)
server, err := imagegen.NewServer(modelName, mode)
if err != nil {
req.errCh <- err
return true

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"cmp"
@@ -18,19 +18,19 @@ type BytePairEncoding struct {
regexps []*regexp2.Regexp
}
var _ TextProcessor = (*BytePairEncoding)(nil)
var _ Tokenizer = (*BytePairEncoding)(nil)
func NewBytePairEncoding(vocab *Vocabulary, pretokenizers ...string) BytePairEncoding {
if len(pretokenizers) == 0 {
func NewBytePairEncoding(vocab *Vocabulary, pretokenizer ...string) BytePairEncoding {
if len(pretokenizer) == 0 {
// set default byte-level pretokenizer if none provided, e.g.
// https://github.com/huggingface/tokenizers/blob/main/tokenizers/src/pre_tokenizers/byte_level.rs#L44
pretokenizers = []string{`'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`}
// https://github.com/huggingface/tokenizer/blob/main/tokenizer/src/pre_tokenizer/byte_level.rs#L44
pretokenizer = []string{`'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`}
}
return BytePairEncoding{
vocab: vocab,
regexps: slices.Collect(func(yield func(*regexp2.Regexp) bool) {
for _, p := range pretokenizers {
for _, p := range pretokenizer {
if !yield(regexp2.MustCompile(p, regexp2.RE2)) {
return
}

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"bufio"
@@ -17,7 +17,7 @@ import (
func llama(t testing.TB) BytePairEncoding {
t.Helper()
f, err := os.Open(filepath.Join("testdata", "llama3.2", "encoder.json"))
f, err := os.Open(filepath.FromSlash("testdata/llama3.2/encoder.json"))
if err != nil {
t.Fatal(err)
}
@@ -43,7 +43,7 @@ func llama(t testing.TB) BytePairEncoding {
}
}
f, err = os.Open(filepath.Join("testdata", "llama3.2", "vocab.bpe"))
f, err = os.Open(filepath.FromSlash("testdata/llama3.2/vocab.bpe"))
if err != nil {
t.Fatal(err)
}

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"container/heap"
@@ -17,7 +17,7 @@ type SentencePiece struct {
vocab *Vocabulary
}
var _ TextProcessor = (*SentencePiece)(nil)
var _ Tokenizer = (*SentencePiece)(nil)
func (spm SentencePiece) Vocabulary() *Vocabulary {
return spm.vocab
@@ -224,7 +224,7 @@ func (spm SentencePiece) Decode(ids []int32) (string, error) {
data := spm.vocab.Decode(id)
data = strings.ReplaceAll(data, spmWhitespaceSep, " ")
// For tokenizers that use byte tokens like "<0xEA>"
// For tokenizer that use byte tokens like "<0xEA>"
// convert them to the partial unicode character
// so they are buffered correctly by the runner instead
// of being sent back to the api as "<0xEA>"

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"log/slog"
@@ -15,7 +15,7 @@ import (
func loadSentencePieceVocab(t *testing.T) SentencePiece {
t.Helper()
bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model"))
bts, err := os.ReadFile(filepath.FromSlash("testdata/gemma2/tokenizer.model"))
if err != nil {
t.Fatal(err)
}

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
const (
TOKEN_TYPE_NORMAL = iota + 1
@@ -9,7 +9,7 @@ const (
TOKEN_TYPE_BYTE
)
type TextProcessor interface {
type Tokenizer interface {
Encode(s string, addSpecial bool) ([]int32, error)
Decode([]int32) (string, error)
Is(int32, Special) bool

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"log/slog"

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"testing"

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"fmt"
@@ -32,7 +32,7 @@ var wordPieceReplacer = strings.NewReplacer(
" 're", "'re",
)
// Decode implements TextProcessor.
// Decode implements Tokenizer.
func (wpm WordPiece) Decode(ids []int32) (string, error) {
var sb strings.Builder
for i, id := range ids {
@@ -96,7 +96,7 @@ func (wpm WordPiece) words(s string) iter.Seq[string] {
}
}
// Encode implements TextProcessor.
// Encode implements Tokenizer.
func (wpm WordPiece) Encode(s string, addSpecial bool) ([]int32, error) {
var ids []int32
@@ -151,17 +151,17 @@ func (wpm WordPiece) Encode(s string, addSpecial bool) ([]int32, error) {
return ids, nil
}
// Is implements TextProcessor.
// Is implements Tokenizer.
func (wpm WordPiece) Is(id int32, special Special) bool {
return wpm.vocab.Is(id, special)
}
// Vocabulary implements TextProcessor.
// Vocabulary implements Tokenizer.
func (wpm WordPiece) Vocabulary() *Vocabulary {
return wpm.vocab
}
var _ TextProcessor = (*WordPiece)(nil)
var _ Tokenizer = (*WordPiece)(nil)
func NewWordPiece(vocab *Vocabulary, lowercase bool) WordPiece {
return WordPiece{

View File

@@ -1,4 +1,4 @@
package model
package tokenizer
import (
"slices"

View File

@@ -1,6 +1,6 @@
//go:build mlx
package mlxrunner
package imagegen
import (
"context"
@@ -11,7 +11,7 @@ import (
"sync"
"time"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/models/flux2"
"github.com/ollama/ollama/x/imagegen/models/zimage"
@@ -28,8 +28,8 @@ var imageGenMu sync.Mutex
func (s *server) loadImageModel() error {
// Check memory requirements before loading
var requiredMemory uint64
if manifest, err := imagegen.LoadManifest(s.modelName); err == nil {
requiredMemory = uint64(manifest.TotalTensorSize())
if modelManifest, err := manifest.LoadManifest(s.modelName); err == nil {
requiredMemory = uint64(modelManifest.TotalTensorSize())
}
availableMemory := mlx.GetMemoryLimit()
if availableMemory > 0 && requiredMemory > 0 && availableMemory < requiredMemory {
@@ -38,7 +38,7 @@ func (s *server) loadImageModel() error {
}
// Detect model type and load appropriate model
modelType := imagegen.DetectModelType(s.modelName)
modelType := DetectModelType(s.modelName)
slog.Info("detected image model type", "type", modelType)
var model ImageModel
@@ -108,7 +108,7 @@ func (s *server) handleImageCompletion(w http.ResponseWriter, r *http.Request, r
}
// Encode image as base64 PNG
imageData, err := imagegen.EncodeImageBase64(img)
imageData, err := EncodeImageBase64(img)
if err != nil {
resp := Response{Content: fmt.Sprintf("error encoding: %v", err), Done: true}
data, _ := json.Marshal(resp)

View File

@@ -1,6 +1,6 @@
//go:build mlx
package mlxrunner
package imagegen
import (
"encoding/json"
@@ -12,8 +12,8 @@ import (
"sync"
"time"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/cache"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/models/glm4_moe_lite"
"github.com/ollama/ollama/x/imagegen/tokenizer"
@@ -197,13 +197,13 @@ func sample(logits *mlx.Array, temp float32, vocabSize int32) *mlx.Array {
// loadLLMModel loads a safetensors LLM model and its tokenizer from manifest storage.
func (s *server) loadLLMModel() error {
// Load the manifest to get model information
manifest, err := imagegen.LoadManifest(s.modelName)
modelManifest, err := manifest.LoadManifest(s.modelName)
if err != nil {
return fmt.Errorf("failed to load manifest: %w", err)
}
// Detect model architecture from config.json
configData, err := manifest.ReadConfig("config.json")
configData, err := modelManifest.ReadConfig("config.json")
if err != nil {
return fmt.Errorf("failed to read config.json: %w", err)
}
@@ -232,7 +232,7 @@ func (s *server) loadLLMModel() error {
switch {
case strings.Contains(archLower, "glm4moelite"):
m, err := glm4_moe_lite.LoadFromManifest(manifest)
m, err := glm4_moe_lite.LoadFromManifest(modelManifest)
if err != nil {
return fmt.Errorf("failed to load glm4-moe-lite model: %w", err)
}

View File

@@ -1,4 +1,4 @@
package imagegen
package manifest
import (
"encoding/json"

View File

@@ -1,4 +1,4 @@
package imagegen
package manifest
import (
"path/filepath"

View File

@@ -1,6 +1,6 @@
//go:build mlx
package imagegen
package manifest
import (
"fmt"
@@ -15,9 +15,9 @@ import (
type ManifestWeights struct {
manifest *ModelManifest
component string
tensors map[string]ManifestLayer // name -> layer
cache map[string]*mlx.Array // name -> loaded array
nativeCache []*mlx.SafetensorsFile // keep native handles alive
tensors map[string]ManifestLayer // name -> layer
cache map[string]*mlx.Array // name -> loaded array
nativeCache []*mlx.SafetensorsFile // keep native handles alive
}
// LoadWeightsFromManifest creates a weight loader from manifest storage.

View File

@@ -14,6 +14,8 @@ import (
"encoding/json"
"fmt"
"runtime"
"github.com/ollama/ollama/x/imagegen/manifest"
)
// SupportedBackends lists the backends that support image generation.
@@ -41,8 +43,8 @@ func CheckPlatformSupport() error {
// ResolveModelName checks if a model name is a known image generation model.
// Returns the normalized model name if found, empty string otherwise.
func ResolveModelName(modelName string) string {
manifest, err := LoadManifest(modelName)
if err == nil && manifest.HasTensorLayers() {
modelManifest, err := manifest.LoadManifest(modelName)
if err == nil && modelManifest.HasTensorLayers() {
return modelName
}
return ""
@@ -52,12 +54,12 @@ func ResolveModelName(modelName string) string {
// Checks both "architecture" (Ollama format) and "_class_name" (diffusers format).
// Returns empty string if detection fails.
func DetectModelType(modelName string) string {
manifest, err := LoadManifest(modelName)
modelManifest, err := manifest.LoadManifest(modelName)
if err != nil {
return ""
}
data, err := manifest.ReadConfig("model_index.json")
data, err := modelManifest.ReadConfig("model_index.json")
if err != nil {
return ""
}

View File

@@ -12,7 +12,7 @@ import (
"math"
"time"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/models/qwen3"
"github.com/ollama/ollama/x/imagegen/tokenizer"
@@ -61,7 +61,7 @@ func (m *Model) Load(modelName string) error {
m.ModelName = modelName
// Load manifest
manifest, err := imagegen.LoadManifest(modelName)
manifest, err := manifest.LoadManifest(modelName)
if err != nil {
return fmt.Errorf("load manifest: %w", err)
}

View File

@@ -6,7 +6,7 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/nn"
"github.com/ollama/ollama/x/imagegen/safetensors"
@@ -14,19 +14,19 @@ import (
// TransformerConfig holds Flux2 transformer configuration
type TransformerConfig struct {
AttentionHeadDim int32 `json:"attention_head_dim"` // 128
AxesDimsRoPE []int32 `json:"axes_dims_rope"` // [32, 32, 32, 32]
Eps float32 `json:"eps"` // 1e-6
GuidanceEmbeds bool `json:"guidance_embeds"` // false for Klein
InChannels int32 `json:"in_channels"` // 128
JointAttentionDim int32 `json:"joint_attention_dim"` // 7680
MLPRatio float32 `json:"mlp_ratio"` // 3.0
NumAttentionHeads int32 `json:"num_attention_heads"` // 24
NumLayers int32 `json:"num_layers"` // 5
NumSingleLayers int32 `json:"num_single_layers"` // 20
PatchSize int32 `json:"patch_size"` // 1
RopeTheta int32 `json:"rope_theta"` // 2000
TimestepGuidanceChannels int32 `json:"timestep_guidance_channels"` // 256
AttentionHeadDim int32 `json:"attention_head_dim"` // 128
AxesDimsRoPE []int32 `json:"axes_dims_rope"` // [32, 32, 32, 32]
Eps float32 `json:"eps"` // 1e-6
GuidanceEmbeds bool `json:"guidance_embeds"` // false for Klein
InChannels int32 `json:"in_channels"` // 128
JointAttentionDim int32 `json:"joint_attention_dim"` // 7680
MLPRatio float32 `json:"mlp_ratio"` // 3.0
NumAttentionHeads int32 `json:"num_attention_heads"` // 24
NumLayers int32 `json:"num_layers"` // 5
NumSingleLayers int32 `json:"num_single_layers"` // 20
PatchSize int32 `json:"patch_size"` // 1
RopeTheta int32 `json:"rope_theta"` // 2000
TimestepGuidanceChannels int32 `json:"timestep_guidance_channels"` // 256
}
// Computed dimensions
@@ -392,12 +392,12 @@ type Flux2Transformer2DModel struct {
}
// Load loads the Flux2 transformer from ollama blob storage.
func (m *Flux2Transformer2DModel) Load(manifest *imagegen.ModelManifest) error {
func (m *Flux2Transformer2DModel) Load(modelManifest *manifest.ModelManifest) error {
fmt.Print(" Loading transformer... ")
// Load config from blob
var cfg TransformerConfig
if err := manifest.ReadConfigJSON("transformer/config.json", &cfg); err != nil {
if err := modelManifest.ReadConfigJSON("transformer/config.json", &cfg); err != nil {
return fmt.Errorf("config: %w", err)
}
m.TransformerConfig = &cfg
@@ -412,7 +412,7 @@ func (m *Flux2Transformer2DModel) Load(manifest *imagegen.ModelManifest) error {
}
// Load weights from tensor blobs
weights, err := imagegen.LoadWeightsFromManifest(manifest, "transformer")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "transformer")
if err != nil {
return fmt.Errorf("weights: %w", err)
}

View File

@@ -6,7 +6,7 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/nn"
"github.com/ollama/ollama/x/imagegen/safetensors"
@@ -15,21 +15,21 @@ import (
// VAEConfig holds AutoencoderKLFlux2 configuration
type VAEConfig struct {
ActFn string `json:"act_fn"` // "silu"
BatchNormEps float32 `json:"batch_norm_eps"` // 0.0001
BatchNormMomentum float32 `json:"batch_norm_momentum"` // 0.1
BlockOutChannels []int32 `json:"block_out_channels"` // [128, 256, 512, 512]
ForceUpcast bool `json:"force_upcast"` // true
InChannels int32 `json:"in_channels"` // 3
LatentChannels int32 `json:"latent_channels"` // 32
LayersPerBlock int32 `json:"layers_per_block"` // 2
ActFn string `json:"act_fn"` // "silu"
BatchNormEps float32 `json:"batch_norm_eps"` // 0.0001
BatchNormMomentum float32 `json:"batch_norm_momentum"` // 0.1
BlockOutChannels []int32 `json:"block_out_channels"` // [128, 256, 512, 512]
ForceUpcast bool `json:"force_upcast"` // true
InChannels int32 `json:"in_channels"` // 3
LatentChannels int32 `json:"latent_channels"` // 32
LayersPerBlock int32 `json:"layers_per_block"` // 2
MidBlockAddAttn bool `json:"mid_block_add_attention"` // true
NormNumGroups int32 `json:"norm_num_groups"` // 32
OutChannels int32 `json:"out_channels"` // 3
PatchSize []int32 `json:"patch_size"` // [2, 2]
SampleSize int32 `json:"sample_size"` // 1024
UsePostQuantConv bool `json:"use_post_quant_conv"` // true
UseQuantConv bool `json:"use_quant_conv"` // true
NormNumGroups int32 `json:"norm_num_groups"` // 32
OutChannels int32 `json:"out_channels"` // 3
PatchSize []int32 `json:"patch_size"` // [2, 2]
SampleSize int32 `json:"sample_size"` // 1024
UsePostQuantConv bool `json:"use_post_quant_conv"` // true
UseQuantConv bool `json:"use_quant_conv"` // true
}
// BatchNorm2D implements 2D batch normalization with running statistics
@@ -356,18 +356,18 @@ func (db *DownEncoderBlock2D) Forward(x *mlx.Array) *mlx.Array {
}
// Load loads the Flux2 VAE from ollama blob storage.
func (m *AutoencoderKLFlux2) Load(manifest *imagegen.ModelManifest) error {
func (m *AutoencoderKLFlux2) Load(modelManifest *manifest.ModelManifest) error {
fmt.Print(" Loading VAE... ")
// Load config from blob
var cfg VAEConfig
if err := manifest.ReadConfigJSON("vae/config.json", &cfg); err != nil {
if err := modelManifest.ReadConfigJSON("vae/config.json", &cfg); err != nil {
return fmt.Errorf("config: %w", err)
}
m.Config = &cfg
// Load weights from tensor blobs
weights, err := imagegen.LoadWeightsFromManifest(manifest, "vae")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "vae")
if err != nil {
return fmt.Errorf("weights: %w", err)
}

View File

@@ -9,8 +9,8 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/cache"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/nn"
"github.com/ollama/ollama/x/imagegen/safetensors"
@@ -38,11 +38,11 @@ type Config struct {
AttentionBias bool `json:"attention_bias"`
// MLA (Multi-head Latent Attention) parameters
QLoraRank int32 `json:"q_lora_rank"`
KVLoraRank int32 `json:"kv_lora_rank"`
QKRopeHeadDim int32 `json:"qk_rope_head_dim"`
QKNopeHeadDim int32 `json:"qk_nope_head_dim"`
VHeadDim int32 `json:"v_head_dim"`
QLoraRank int32 `json:"q_lora_rank"`
KVLoraRank int32 `json:"kv_lora_rank"`
QKRopeHeadDim int32 `json:"qk_rope_head_dim"`
QKNopeHeadDim int32 `json:"qk_nope_head_dim"`
VHeadDim int32 `json:"v_head_dim"`
// MoE parameters
NRoutedExperts int32 `json:"n_routed_experts"`
@@ -82,7 +82,7 @@ type MLAAttention struct {
// Absorbed MLA projections (derived from kv_b_proj)
// EmbedQ: projects q_nope to latent space [num_heads, kv_lora_rank, qk_nope_head_dim]
// UnembedOut: projects attention output from latent space [num_heads, v_head_dim, kv_lora_rank]
EmbedQ *nn.MultiLinear `weight:"-"`
EmbedQ *nn.MultiLinear `weight:"-"`
UnembedOut *nn.MultiLinear `weight:"-"`
// Output projection
@@ -194,8 +194,8 @@ func (m *DenseMLP) Forward(x *mlx.Array) *mlx.Array {
// MoEGate implements the expert gating mechanism
type MoEGate struct {
Gate nn.LinearLayer `weight:"mlp.gate"`
EScoreCorrectionBias *mlx.Array `weight:"mlp.gate.e_score_correction_bias,optional"`
Gate nn.LinearLayer `weight:"mlp.gate"`
EScoreCorrectionBias *mlx.Array `weight:"mlp.gate.e_score_correction_bias,optional"`
}
// Forward computes expert selection indices and scores
@@ -617,9 +617,9 @@ func sanitizeExpertWeights(weights safetensors.WeightSource, prefix string, numE
}
// LoadFromManifest loads a GLM4-MoE-Lite model from a manifest (Ollama blob storage).
func LoadFromManifest(manifest *imagegen.ModelManifest) (*Model, error) {
func LoadFromManifest(modelManifest *manifest.ModelManifest) (*Model, error) {
// Read config from manifest
configData, err := manifest.ReadConfig("config.json")
configData, err := modelManifest.ReadConfig("config.json")
if err != nil {
return nil, fmt.Errorf("load config: %w", err)
}
@@ -634,7 +634,7 @@ func LoadFromManifest(manifest *imagegen.ModelManifest) (*Model, error) {
cfg.Scale = computeScale(&cfg)
// Load weights from manifest blobs
weights, err := imagegen.LoadWeightsFromManifest(manifest, "")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "")
if err != nil {
return nil, fmt.Errorf("load weights: %w", err)
}
@@ -653,7 +653,7 @@ func LoadFromManifest(manifest *imagegen.ModelManifest) (*Model, error) {
}
// Load tokenizer from manifest with config files for EOS token detection
tokData, err := manifest.ReadConfig("tokenizer.json")
tokData, err := modelManifest.ReadConfig("tokenizer.json")
if err != nil {
return nil, fmt.Errorf("load tokenizer config: %w", err)
}
@@ -664,12 +664,12 @@ func LoadFromManifest(manifest *imagegen.ModelManifest) (*Model, error) {
}
// Try to load generation_config.json if available (preferred source for EOS)
if genConfigData, err := manifest.ReadConfig("generation_config.json"); err == nil {
if genConfigData, err := modelManifest.ReadConfig("generation_config.json"); err == nil {
tokConfig.GenerationConfigJSON = genConfigData
}
// Try to load tokenizer_config.json if available
if tokConfigData, err := manifest.ReadConfig("tokenizer_config.json"); err == nil {
if tokConfigData, err := modelManifest.ReadConfig("tokenizer_config.json"); err == nil {
tokConfig.TokenizerConfigJSON = tokConfigData
}

View File

@@ -7,7 +7,7 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/nn"
"github.com/ollama/ollama/x/imagegen/safetensors"
@@ -181,19 +181,19 @@ type TextEncoder struct {
}
// Load loads the Qwen3 text encoder from ollama blob storage.
func (m *TextEncoder) Load(manifest *imagegen.ModelManifest, configPath string) error {
func (m *TextEncoder) Load(modelManifest *manifest.ModelManifest, configPath string) error {
fmt.Print(" Loading text encoder... ")
// Load config from blob
var cfg Config
if err := manifest.ReadConfigJSON(configPath, &cfg); err != nil {
if err := modelManifest.ReadConfigJSON(configPath, &cfg); err != nil {
return fmt.Errorf("config: %w", err)
}
m.Config = &cfg
m.Layers = make([]*Block, cfg.NumHiddenLayers)
// Load weights from tensor blobs
weights, err := imagegen.LoadWeightsFromManifest(manifest, "text_encoder")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "text_encoder")
if err != nil {
return fmt.Errorf("weights: %w", err)
}

View File

@@ -7,8 +7,8 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/cache"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/nn"
"github.com/ollama/ollama/x/imagegen/safetensors"
@@ -38,7 +38,7 @@ type TransformerConfig struct {
type TimestepEmbedder struct {
Linear1 nn.LinearLayer `weight:"mlp.0"`
Linear2 nn.LinearLayer `weight:"mlp.2"`
FreqEmbedSize int32 // 256 (computed)
FreqEmbedSize int32 // 256 (computed)
}
// Forward computes timestep embeddings -> [B, 256]
@@ -85,9 +85,9 @@ func (xe *XEmbedder) Forward(x *mlx.Array) *mlx.Array {
// CapEmbedder projects caption features to model dimension
type CapEmbedder struct {
Norm *nn.RMSNorm `weight:"0"`
Linear nn.LinearLayer `weight:"1"`
PadToken *mlx.Array // loaded separately at root level
Norm *nn.RMSNorm `weight:"0"`
Linear nn.LinearLayer `weight:"1"`
PadToken *mlx.Array // loaded separately at root level
}
// Forward projects caption embeddings: [B, L, cap_feat_dim] -> [B, L, dim]
@@ -103,10 +103,9 @@ type FeedForward struct {
W1 nn.LinearLayer `weight:"w1"` // gate projection
W2 nn.LinearLayer `weight:"w2"` // down projection
W3 nn.LinearLayer `weight:"w3"` // up projection
OutDim int32 // computed from W2
OutDim int32 // computed from W2
}
// Forward applies SwiGLU: silu(W1(x)) * W3(x), then W2
func (ff *FeedForward) Forward(x *mlx.Array) *mlx.Array {
shape := x.Shape()
@@ -132,11 +131,11 @@ type Attention struct {
ToK nn.LinearLayer `weight:"to_k"`
ToV nn.LinearLayer `weight:"to_v"`
ToOut nn.LinearLayer `weight:"to_out.0"`
NormQ *mlx.Array `weight:"norm_q.weight"` // [head_dim] for per-head RMSNorm
NormK *mlx.Array `weight:"norm_k.weight"`
NormQ *mlx.Array `weight:"norm_q.weight"` // [head_dim] for per-head RMSNorm
NormK *mlx.Array `weight:"norm_k.weight"`
// Fused QKV (computed at init time for efficiency, not loaded from weights)
ToQKV nn.LinearLayer `weight:"-"` // Fused Q+K+V projection (created by FuseQKV)
Fused bool `weight:"-"` // Whether to use fused QKV path
Fused bool `weight:"-"` // Whether to use fused QKV path
// Computed fields (not loaded from weights)
NHeads int32 `weight:"-"`
HeadDim int32 `weight:"-"`
@@ -288,13 +287,13 @@ func applyRoPE3D(x *mlx.Array, cos, sin *mlx.Array) *mlx.Array {
// TransformerBlock is a single transformer block with optional AdaLN modulation
type TransformerBlock struct {
Attention *Attention `weight:"attention"`
FeedForward *FeedForward `weight:"feed_forward"`
AttentionNorm1 *nn.RMSNorm `weight:"attention_norm1"`
AttentionNorm2 *nn.RMSNorm `weight:"attention_norm2"`
FFNNorm1 *nn.RMSNorm `weight:"ffn_norm1"`
FFNNorm2 *nn.RMSNorm `weight:"ffn_norm2"`
AdaLN nn.LinearLayer `weight:"adaLN_modulation.0,optional"` // only if modulation
Attention *Attention `weight:"attention"`
FeedForward *FeedForward `weight:"feed_forward"`
AttentionNorm1 *nn.RMSNorm `weight:"attention_norm1"`
AttentionNorm2 *nn.RMSNorm `weight:"attention_norm2"`
FFNNorm1 *nn.RMSNorm `weight:"ffn_norm1"`
FFNNorm2 *nn.RMSNorm `weight:"ffn_norm2"`
AdaLN nn.LinearLayer `weight:"adaLN_modulation.0,optional"` // only if modulation
// Computed fields
HasModulation bool
Dim int32
@@ -350,7 +349,7 @@ func (tb *TransformerBlock) Forward(x *mlx.Array, adaln *mlx.Array, cos, sin *ml
type FinalLayer struct {
AdaLN nn.LinearLayer `weight:"adaLN_modulation.1"` // [256] -> [dim]
Output nn.LinearLayer `weight:"linear"` // [dim] -> [out_channels]
OutDim int32 // computed from Output
OutDim int32 // computed from Output
}
// Forward computes final output
@@ -401,12 +400,12 @@ type Transformer struct {
}
// Load loads the Z-Image transformer from ollama blob storage.
func (m *Transformer) Load(manifest *imagegen.ModelManifest) error {
func (m *Transformer) Load(modelManifest *manifest.ModelManifest) error {
fmt.Print(" Loading transformer... ")
// Load config from blob
var cfg TransformerConfig
if err := manifest.ReadConfigJSON("transformer/config.json", &cfg); err != nil {
if err := modelManifest.ReadConfigJSON("transformer/config.json", &cfg); err != nil {
return fmt.Errorf("config: %w", err)
}
if len(cfg.AllPatchSize) > 0 {
@@ -417,7 +416,7 @@ func (m *Transformer) Load(manifest *imagegen.ModelManifest) error {
m.ContextRefiners = make([]*TransformerBlock, cfg.NRefinerLayers)
m.Layers = make([]*TransformerBlock, cfg.NLayers)
weights, err := imagegen.LoadWeightsFromManifest(manifest, "transformer")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "transformer")
if err != nil {
return fmt.Errorf("weights: %w", err)
}

View File

@@ -6,7 +6,7 @@ import (
"fmt"
"math"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/safetensors"
"github.com/ollama/ollama/x/imagegen/vae"
@@ -562,7 +562,7 @@ func (ub *UpDecoderBlock2D) Forward(x *mlx.Array) *mlx.Array {
if ub.Upsample != nil {
// Stage 1: Upsample2x (nearest neighbor)
{
prev := x
prev := x
x = Upsample2x(x)
prev.Free()
mlx.Eval(x)
@@ -570,7 +570,7 @@ func (ub *UpDecoderBlock2D) Forward(x *mlx.Array) *mlx.Array {
// Stage 2: Upsample conv
{
prev := x
prev := x
x = ub.Upsample.Forward(x)
prev.Free()
mlx.Eval(x)
@@ -643,16 +643,16 @@ type VAEDecoder struct {
}
// Load loads the VAE decoder from ollama blob storage.
func (m *VAEDecoder) Load(manifest *imagegen.ModelManifest) error {
func (m *VAEDecoder) Load(modelManifest *manifest.ModelManifest) error {
// Load config from blob
var cfg VAEConfig
if err := manifest.ReadConfigJSON("vae/config.json", &cfg); err != nil {
if err := modelManifest.ReadConfigJSON("vae/config.json", &cfg); err != nil {
return fmt.Errorf("config: %w", err)
}
m.Config = &cfg
// Load weights from tensor blobs
weights, err := imagegen.LoadWeightsFromManifest(manifest, "vae")
weights, err := manifest.LoadWeightsFromManifest(modelManifest, "vae")
if err != nil {
return fmt.Errorf("weights: %w", err)
}

View File

@@ -8,8 +8,8 @@ import (
"fmt"
"time"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/cache"
"github.com/ollama/ollama/x/imagegen/manifest"
"github.com/ollama/ollama/x/imagegen/mlx"
"github.com/ollama/ollama/x/imagegen/tokenizer"
"github.com/ollama/ollama/x/imagegen/vae"
@@ -18,14 +18,14 @@ import (
// GenerateConfig holds all options for image generation.
type GenerateConfig struct {
Prompt string
NegativePrompt string // Empty = no CFG
CFGScale float32 // Only used if NegativePrompt is set (default: 4.0)
Width int32 // Image width (default: 1024)
Height int32 // Image height (default: 1024)
Steps int // Denoising steps (default: 9 for turbo)
Seed int64 // Random seed
NegativePrompt string // Empty = no CFG
CFGScale float32 // Only used if NegativePrompt is set (default: 4.0)
Width int32 // Image width (default: 1024)
Height int32 // Image height (default: 1024)
Steps int // Denoising steps (default: 9 for turbo)
Seed int64 // Random seed
Progress func(step, totalSteps int) // Optional progress callback
CapturePath string // GPU capture path (debug)
CapturePath string // GPU capture path (debug)
// TeaCache options (timestep embedding aware caching)
TeaCache bool // TeaCache is always enabled for faster inference
@@ -58,7 +58,7 @@ func (m *Model) Load(modelName string) error {
m.ModelName = modelName
// Load manifest
manifest, err := imagegen.LoadManifest(modelName)
manifest, err := manifest.LoadManifest(modelName)
if err != nil {
return fmt.Errorf("load manifest: %w", err)
}

View File

@@ -1,7 +1,7 @@
//go:build mlx
// Package mlxrunner provides a unified MLX runner for both LLM and image generation models.
package mlxrunner
// Package imagegen provides a unified MLX runner for both LLM and image generation models.
package imagegen
import (
"context"
@@ -16,7 +16,6 @@ import (
"time"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/mlx"
)
@@ -98,7 +97,7 @@ func Execute(args []string) error {
// detectModelMode determines whether a model is an LLM or image generation model.
func detectModelMode(modelName string) ModelMode {
// Check for image generation model by looking at model_index.json
modelType := imagegen.DetectModelType(modelName)
modelType := DetectModelType(modelName)
if modelType != "" {
// Known image generation model types
switch modelType {

View File

@@ -1,6 +1,6 @@
//go:build !mlx
package mlxrunner
package imagegen
import "errors"

View File

@@ -1,4 +1,4 @@
package mlxrunner
package imagegen
import (
"bufio"
@@ -23,7 +23,7 @@ import (
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/x/imagegen"
"github.com/ollama/ollama/x/imagegen/manifest"
)
// Server wraps an MLX runner subprocess to implement llm.LlamaServer.
@@ -46,7 +46,7 @@ type Server struct {
// NewServer spawns a new MLX runner subprocess and waits until it's ready.
func NewServer(modelName string, mode ModelMode) (*Server, error) {
// Validate platform support before attempting to start
if err := imagegen.CheckPlatformSupport(); err != nil {
if err := CheckPlatformSupport(); err != nil {
return nil, err
}
@@ -71,8 +71,8 @@ func NewServer(modelName string, mode ModelMode) (*Server, error) {
exe = eval
}
// Spawn subprocess: ollama runner --mlx-engine --model <path> --port <port>
cmd := exec.Command(exe, "runner", "--mlx-engine", "--model", modelName, "--port", strconv.Itoa(port))
// Spawn subprocess: ollama runner --imagegen-engine --model <path> --port <port>
cmd := exec.Command(exe, "runner", "--imagegen-engine", "--model", modelName, "--port", strconv.Itoa(port))
cmd.Env = os.Environ()
// On Linux, set LD_LIBRARY_PATH to include MLX library directories
@@ -107,8 +107,8 @@ func NewServer(modelName string, mode ModelMode) (*Server, error) {
// Estimate VRAM based on tensor size from manifest
var vramSize uint64
if manifest, err := imagegen.LoadManifest(modelName); err == nil {
vramSize = uint64(manifest.TotalTensorSize())
if modelManifest, err := manifest.LoadManifest(modelName); err == nil {
vramSize = uint64(modelManifest.TotalTensorSize())
} else {
// Fallback: default to 8GB if manifest can't be loaded
vramSize = 8 * 1024 * 1024 * 1024

View File

@@ -1,9 +1,9 @@
// Package mlxrunner provides a unified MLX runner for both LLM and image generation models.
// Package imagegen provides a unified MLX runner for both LLM and image generation models.
//
// This package handles safetensors models created with `ollama create --experimental`,
// supporting both text generation (LLM) and image generation (diffusion) models
// through a single unified interface.
package mlxrunner
package imagegen
// Request is the request format for completion requests.
type Request struct {

View File

@@ -1,77 +0,0 @@
package kvcache
import (
"errors"
"github.com/ollama/ollama/x/ml"
"github.com/ollama/ollama/x/model/input"
)
var (
ErrKvCacheFull = errors.New("could not find a kv cache slot")
ErrNotSupported = errors.New("model does not support operation")
)
type Cache interface {
// ** used by model implementations **
// SetLayer sets the active layer of the cache
SetLayer(layer int)
// Get returns the history of key and value tensors plus a mask
//
// The shape of the tensors is documented in the specific
// cache implementation used.
Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor)
// Put stores a batch of key and value in the cache
//
// The shape of the tensors is documented in the specific
// cache implementation used.
Put(ctx ml.Context, key, value ml.Tensor)
// SetConfig controls optimizations (mostly backend-specific) that may transform
// the output of the cache to work better with specific kernels. If not called,
// the backend settings will be used. This works well when calling Attention.
//
// The config can be overridden by models, especially if they require vanilla
// output when implementing their own version of attention. To do this, pass
// an empty ml.CacheConfig.
//
// Most models will not need to use this.
SetConfig(ml.CacheConfig)
// ** cache management **
// Init sets up runtime parameters.
// backend: Used to allocate cache data storage and execute management operations (such as defrag)
// dtype: The data type for storing cache entries
// maxSequences: The maximum number of sequences stored in the cache - across all batches
// capacity: The number of cache entries to store, per sequence
// maxBatch: The maximum number of tokens that can occur in a single batch
Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int)
// Close closes the cache and frees resources associated with it
Close()
// StartForward is called before the start of the model's forward pass.
// For each token in the coming batch, there must be a corresponding
// entry in positions and seqs. reserve is to preallocate memory
// without actually storing data in the cache.
StartForward(ctx ml.Context, batch input.Batch, reserve bool) error
// CopyPrefix copies tokens in the range [0, len) from srcSeq to dstSeq
CopyPrefix(srcSeq, dstSeq int, len int32)
// CanResume returns true if the cache can continue with the next token at
// the given position and sequence. Assumes that the caller has already
// verified the contents of the cache.
CanResume(seq int, pos int32) bool
// Remove deletes tokens in the range [beginIndex, endIndex) from seq. Set
// endIndex to math.MaxInt32 to remove everything starting at beginIndex.
//
// If an error occurs, the entire context for the sequence should be
// removed by calling Remove(seq, 0, math.MaxInt32)
Remove(seq int, beginIndex, endIndex int32) error
}

Some files were not shown because too many files have changed in this diff Show More