ollama/cmd/cmd.go

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package cmd
import (
"bufio"
"context"
"crypto/ed25519"
"crypto/rand"
"encoding/json"
"encoding/pem"
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"errors"
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"fmt"
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"io"
"log"
"math"
"net"
"net/http"
"os"
"os/signal"
"path/filepath"
"runtime"
"slices"
"sort"
"strconv"
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"strings"
"sync/atomic"
"syscall"
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"time"
"github.com/containerd/console"
"github.com/mattn/go-runewidth"
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"github.com/olekukonko/tablewriter"
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"github.com/spf13/cobra"
"golang.org/x/crypto/ssh"
"golang.org/x/sync/errgroup"
"golang.org/x/term"
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"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/progress"
"github.com/ollama/ollama/readline"
"github.com/ollama/ollama/runner"
"github.com/ollama/ollama/server"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/types/syncmap"
"github.com/ollama/ollama/version"
)
const ConnectInstructions = "To sign in, navigate to:\n %s\n\n"
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// ensureThinkingSupport emits a warning if the model does not advertise thinking support
func ensureThinkingSupport(ctx context.Context, client *api.Client, name string) {
if name == "" {
return
}
resp, err := client.Show(ctx, &api.ShowRequest{Model: name})
if err != nil {
return
}
if slices.Contains(resp.Capabilities, model.CapabilityThinking) {
return
}
fmt.Fprintf(os.Stderr, "warning: model %q does not support thinking output\n", name)
}
var errModelfileNotFound = errors.New("specified Modelfile wasn't found")
func getModelfileName(cmd *cobra.Command) (string, error) {
filename, _ := cmd.Flags().GetString("file")
if filename == "" {
filename = "Modelfile"
}
absName, err := filepath.Abs(filename)
if err != nil {
return "", err
}
_, err = os.Stat(absName)
if err != nil {
return "", err
}
return absName, nil
}
func CreateHandler(cmd *cobra.Command, args []string) error {
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p := progress.NewProgress(os.Stderr)
defer p.Stop()
var reader io.Reader
filename, err := getModelfileName(cmd)
if os.IsNotExist(err) {
if filename == "" {
reader = strings.NewReader("FROM .\n")
} else {
return errModelfileNotFound
}
} else if err != nil {
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return err
} else {
f, err := os.Open(filename)
if err != nil {
return err
}
reader = f
defer f.Close()
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}
modelfile, err := parser.ParseFile(reader)
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if err != nil {
return err
}
status := "gathering model components"
spinner := progress.NewSpinner(status)
p.Add(status, spinner)
req, err := modelfile.CreateRequest(filepath.Dir(filename))
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if err != nil {
return err
}
spinner.Stop()
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req.Model = args[0]
quantize, _ := cmd.Flags().GetString("quantize")
if quantize != "" {
req.Quantize = quantize
}
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
var g errgroup.Group
g.SetLimit(max(runtime.GOMAXPROCS(0)-1, 1))
files := syncmap.NewSyncMap[string, string]()
for f, digest := range req.Files {
g.Go(func() error {
if _, err := createBlob(cmd, client, f, digest, p); err != nil {
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return err
}
// TODO: this is incorrect since the file might be in a subdirectory
// instead this should take the path relative to the model directory
// but the current implementation does not allow this
files.Store(filepath.Base(f), digest)
return nil
})
}
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adapters := syncmap.NewSyncMap[string, string]()
for f, digest := range req.Adapters {
g.Go(func() error {
if _, err := createBlob(cmd, client, f, digest, p); err != nil {
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return err
}
// TODO: same here
adapters.Store(filepath.Base(f), digest)
return nil
})
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}
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if err := g.Wait(); err != nil {
return err
}
req.Files = files.Items()
req.Adapters = adapters.Items()
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bars := make(map[string]*progress.Bar)
fn := func(resp api.ProgressResponse) error {
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if resp.Digest != "" {
bar, ok := bars[resp.Digest]
if !ok {
msg := resp.Status
if msg == "" {
msg = fmt.Sprintf("pulling %s...", resp.Digest[7:19])
}
bar = progress.NewBar(msg, resp.Total, resp.Completed)
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bars[resp.Digest] = bar
p.Add(resp.Digest, bar)
}
bar.Set(resp.Completed)
} else if status != resp.Status {
spinner.Stop()
status = resp.Status
spinner = progress.NewSpinner(status)
p.Add(status, spinner)
}
return nil
}
if err := client.Create(cmd.Context(), req, fn); err != nil {
if strings.Contains(err.Error(), "path or Modelfile are required") {
return fmt.Errorf("the ollama server must be updated to use `ollama create` with this client")
}
return err
}
return nil
}
func createBlob(cmd *cobra.Command, client *api.Client, path string, digest string, p *progress.Progress) (string, error) {
realPath, err := filepath.EvalSymlinks(path)
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if err != nil {
return "", err
}
bin, err := os.Open(realPath)
if err != nil {
return "", err
}
defer bin.Close()
// Get file info to retrieve the size
fileInfo, err := bin.Stat()
if err != nil {
return "", err
}
fileSize := fileInfo.Size()
var pw progressWriter
status := fmt.Sprintf("copying file %s 0%%", digest)
spinner := progress.NewSpinner(status)
p.Add(status, spinner)
defer spinner.Stop()
done := make(chan struct{})
defer close(done)
go func() {
ticker := time.NewTicker(60 * time.Millisecond)
defer ticker.Stop()
for {
select {
case <-ticker.C:
spinner.SetMessage(fmt.Sprintf("copying file %s %d%%", digest, int(100*pw.n.Load()/fileSize)))
case <-done:
spinner.SetMessage(fmt.Sprintf("copying file %s 100%%", digest))
return
}
}
}()
if err := client.CreateBlob(cmd.Context(), digest, io.TeeReader(bin, &pw)); err != nil {
return "", err
}
return digest, nil
}
type progressWriter struct {
n atomic.Int64
}
func (w *progressWriter) Write(p []byte) (n int, err error) {
w.n.Add(int64(len(p)))
return len(p), nil
}
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func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
req := &api.GenerateRequest{
Model: opts.Model,
KeepAlive: opts.KeepAlive,
// pass Think here so we fail before getting to the chat prompt if the model doesn't support it
Think: opts.Think,
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}
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return client.Generate(cmd.Context(), req, func(r api.GenerateResponse) error {
if r.RemoteModel != "" && opts.ShowConnect {
p.StopAndClear()
if strings.HasPrefix(r.RemoteHost, "https://ollama.com") {
fmt.Fprintf(os.Stderr, "Connecting to '%s' on 'ollama.com' ⚡\n", r.RemoteModel)
} else {
fmt.Fprintf(os.Stderr, "Connecting to '%s' on '%s'\n", r.RemoteModel, r.RemoteHost)
}
}
return nil
})
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}
func StopHandler(cmd *cobra.Command, args []string) error {
opts := &runOptions{
Model: args[0],
KeepAlive: &api.Duration{Duration: 0},
}
if err := loadOrUnloadModel(cmd, opts); err != nil {
if strings.Contains(err.Error(), "not found") {
return fmt.Errorf("couldn't find model \"%s\" to stop", args[0])
}
return err
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}
return nil
}
func RunHandler(cmd *cobra.Command, args []string) error {
interactive := true
opts := runOptions{
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Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]any{},
ShowConnect: true,
}
format, err := cmd.Flags().GetString("format")
if err != nil {
return err
}
opts.Format = format
thinkFlag := cmd.Flags().Lookup("think")
if thinkFlag.Changed {
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
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thinkStr, err := cmd.Flags().GetString("think")
if err != nil {
return err
}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
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// Handle different values for --think
switch thinkStr {
case "", "true":
// --think or --think=true
opts.Think = &api.ThinkValue{Value: true}
case "false":
opts.Think = &api.ThinkValue{Value: false}
case "high", "medium", "low":
opts.Think = &api.ThinkValue{Value: thinkStr}
default:
return fmt.Errorf("invalid value for --think: %q (must be true, false, high, medium, or low)", thinkStr)
}
} else {
opts.Think = nil
}
hidethinking, err := cmd.Flags().GetBool("hidethinking")
if err != nil {
return err
}
opts.HideThinking = hidethinking
keepAlive, err := cmd.Flags().GetString("keepalive")
if err != nil {
return err
}
if keepAlive != "" {
d, err := time.ParseDuration(keepAlive)
if err != nil {
return err
}
opts.KeepAlive = &api.Duration{Duration: d}
}
prompts := args[1:]
// prepend stdin to the prompt if provided
if !term.IsTerminal(int(os.Stdin.Fd())) {
in, err := io.ReadAll(os.Stdin)
if err != nil {
return err
}
prompts = append([]string{string(in)}, prompts...)
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opts.ShowConnect = false
opts.WordWrap = false
interactive = false
}
opts.Prompt = strings.Join(prompts, " ")
if len(prompts) > 0 {
interactive = false
}
// Be quiet if we're redirecting to a pipe or file
if !term.IsTerminal(int(os.Stdout.Fd())) {
interactive = false
}
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
opts.WordWrap = !nowrap
cmd: defer stating model info until necessary (#5248) This commit changes the 'ollama run' command to defer fetching model information until it really needs it. That is, when in interactive mode. It also removes one such case where the model information is fetch in duplicate, just before calling generateInteractive and then again, first thing, in generateInteractive. This positively impacts the performance of the command: ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.168 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.220 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.217 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 4% cpu 0.652 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 5% cpu 0.498 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 3% cpu 0.479 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total
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// Fill out the rest of the options based on information about the
// model.
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
name := args[0]
info, err := func() (*api.ShowResponse, error) {
showReq := &api.ShowRequest{Name: name}
info, err := client.Show(cmd.Context(), showReq)
var se api.StatusError
if errors.As(err, &se) && se.StatusCode == http.StatusNotFound {
if err := PullHandler(cmd, []string{name}); err != nil {
return nil, err
}
return client.Show(cmd.Context(), &api.ShowRequest{Name: name})
}
return info, err
}()
if err != nil {
return err
}
opts.Think, err = inferThinkingOption(&info.Capabilities, &opts, thinkFlag.Changed)
if err != nil {
return err
}
opts.MultiModal = slices.Contains(info.Capabilities, model.CapabilityVision)
// TODO: remove the projector info and vision info checks below,
// these are left in for backwards compatibility with older servers
// that don't have the capabilities field in the model info
if len(info.ProjectorInfo) != 0 {
opts.MultiModal = true
}
for k := range info.ModelInfo {
if strings.Contains(k, ".vision.") {
opts.MultiModal = true
break
}
}
cmd: defer stating model info until necessary (#5248) This commit changes the 'ollama run' command to defer fetching model information until it really needs it. That is, when in interactive mode. It also removes one such case where the model information is fetch in duplicate, just before calling generateInteractive and then again, first thing, in generateInteractive. This positively impacts the performance of the command: ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.168 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.220 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.217 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 4% cpu 0.652 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 5% cpu 0.498 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 3% cpu 0.479 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total
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opts.ParentModel = info.Details.ParentModel
if interactive {
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if err := loadOrUnloadModel(cmd, &opts); err != nil {
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var sErr api.AuthorizationError
if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
fmt.Printf("You need to be signed in to Ollama to run Cloud models.\n\n")
if sErr.SigninURL != "" {
fmt.Printf(ConnectInstructions, sErr.SigninURL)
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}
return nil
}
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return err
}
for _, msg := range info.Messages {
switch msg.Role {
case "user":
fmt.Printf(">>> %s\n", msg.Content)
case "assistant":
state := &displayResponseState{}
displayResponse(msg.Content, opts.WordWrap, state)
fmt.Println()
fmt.Println()
}
}
cmd: defer stating model info until necessary (#5248) This commit changes the 'ollama run' command to defer fetching model information until it really needs it. That is, when in interactive mode. It also removes one such case where the model information is fetch in duplicate, just before calling generateInteractive and then again, first thing, in generateInteractive. This positively impacts the performance of the command: ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.168 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.220 total ; time ./before run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./before run llama3 'hi' 0.02s user 0.01s system 2% cpu 1.217 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 4% cpu 0.652 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 5% cpu 0.498 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with or would you like to chat? ./after run llama3 'hi' 0.01s user 0.01s system 3% cpu 0.479 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total ; time ./after run llama3 'hi' Hi! It's nice to meet you. Is there something I can help you with, or would you like to chat? ./after run llama3 'hi' 0.02s user 0.01s system 5% cpu 0.507 total
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return generateInteractive(cmd, opts)
}
return generate(cmd, opts)
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}
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func SigninHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
user, err := client.Whoami(cmd.Context())
if err != nil {
var aErr api.AuthorizationError
if errors.As(err, &aErr) && aErr.StatusCode == http.StatusUnauthorized {
fmt.Println("You need to be signed in to Ollama to run Cloud models.")
fmt.Println()
if aErr.SigninURL != "" {
fmt.Printf(ConnectInstructions, aErr.SigninURL)
}
return nil
}
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return err
}
if user != nil && user.Name != "" {
fmt.Printf("You are already signed in as user '%s'\n", user.Name)
fmt.Println()
return nil
}
return nil
}
func SignoutHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
err = client.Signout(cmd.Context())
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if err != nil {
var aErr api.AuthorizationError
if errors.As(err, &aErr) && aErr.StatusCode == http.StatusUnauthorized {
fmt.Println("You are not signed in to ollama.com")
fmt.Println()
return nil
} else {
return err
}
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}
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fmt.Println("You have signed out of ollama.com")
fmt.Println()
return nil
}
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func PushHandler(cmd *cobra.Command, args []string) error {
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
insecure, err := cmd.Flags().GetBool("insecure")
if err != nil {
return err
}
n := model.ParseName(args[0])
if strings.HasSuffix(n.Host, ".ollama.ai") || strings.HasSuffix(n.Host, ".ollama.com") {
_, err := client.Whoami(cmd.Context())
if err != nil {
var aErr api.AuthorizationError
if errors.As(err, &aErr) && aErr.StatusCode == http.StatusUnauthorized {
fmt.Println("You need to be signed in to push models to ollama.com.")
fmt.Println()
if aErr.SigninURL != "" {
fmt.Printf(ConnectInstructions, aErr.SigninURL)
}
return nil
}
return err
}
}
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p := progress.NewProgress(os.Stderr)
defer p.Stop()
bars := make(map[string]*progress.Bar)
var status string
var spinner *progress.Spinner
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fn := func(resp api.ProgressResponse) error {
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if resp.Digest != "" {
if spinner != nil {
spinner.Stop()
}
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bar, ok := bars[resp.Digest]
if !ok {
bar = progress.NewBar(fmt.Sprintf("pushing %s...", resp.Digest[7:19]), resp.Total, resp.Completed)
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bars[resp.Digest] = bar
p.Add(resp.Digest, bar)
}
bar.Set(resp.Completed)
} else if status != resp.Status {
if spinner != nil {
spinner.Stop()
}
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status = resp.Status
spinner = progress.NewSpinner(status)
p.Add(status, spinner)
}
return nil
}
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request := api.PushRequest{Name: args[0], Insecure: insecure}
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if err := client.Push(cmd.Context(), &request, fn); err != nil {
if spinner != nil {
spinner.Stop()
}
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errStr := strings.ToLower(err.Error())
if strings.Contains(errStr, "access denied") || strings.Contains(errStr, "unauthorized") {
return errors.New("you are not authorized to push to this namespace, create the model under a namespace you own")
}
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return err
}
p.Stop()
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spinner.Stop()
destination := n.String()
if strings.HasSuffix(n.Host, ".ollama.ai") || strings.HasSuffix(n.Host, ".ollama.com") {
destination = "https://ollama.com/" + strings.TrimSuffix(n.DisplayShortest(), ":latest")
}
fmt.Printf("\nYou can find your model at:\n\n")
fmt.Printf("\t%s\n", destination)
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return nil
}
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func ListHandler(cmd *cobra.Command, args []string) error {
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
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models, err := client.List(cmd.Context())
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if err != nil {
return err
}
var data [][]string
for _, m := range models.Models {
if len(args) == 0 || strings.HasPrefix(strings.ToLower(m.Name), strings.ToLower(args[0])) {
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var size string
if m.RemoteModel != "" {
size = "-"
} else {
size = format.HumanBytes(m.Size)
}
data = append(data, []string{m.Name, m.Digest[:12], size, format.HumanTime(m.ModifiedAt, "Never")})
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}
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}
table := tablewriter.NewWriter(os.Stdout)
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table.SetHeader([]string{"NAME", "ID", "SIZE", "MODIFIED"})
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table.SetHeaderAlignment(tablewriter.ALIGN_LEFT)
table.SetAlignment(tablewriter.ALIGN_LEFT)
table.SetHeaderLine(false)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
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table.AppendBulk(data)
table.Render()
return nil
}
func ListRunningHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
models, err := client.ListRunning(cmd.Context())
if err != nil {
return err
}
var data [][]string
for _, m := range models.Models {
if len(args) == 0 || strings.HasPrefix(m.Name, args[0]) {
var procStr string
switch {
case m.SizeVRAM == 0:
procStr = "100% CPU"
case m.SizeVRAM == m.Size:
procStr = "100% GPU"
case m.SizeVRAM > m.Size || m.Size == 0:
procStr = "Unknown"
default:
sizeCPU := m.Size - m.SizeVRAM
cpuPercent := math.Round(float64(sizeCPU) / float64(m.Size) * 100)
procStr = fmt.Sprintf("%d%%/%d%% CPU/GPU", int(cpuPercent), int(100-cpuPercent))
}
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var until string
delta := time.Since(m.ExpiresAt)
if delta > 0 {
until = "Stopping..."
} else {
until = format.HumanTime(m.ExpiresAt, "Never")
}
ctxStr := strconv.Itoa(m.ContextLength)
data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), procStr, ctxStr, until})
}
}
table := tablewriter.NewWriter(os.Stdout)
table.SetHeader([]string{"NAME", "ID", "SIZE", "PROCESSOR", "CONTEXT", "UNTIL"})
table.SetHeaderAlignment(tablewriter.ALIGN_LEFT)
table.SetAlignment(tablewriter.ALIGN_LEFT)
table.SetHeaderLine(false)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
table.AppendBulk(data)
table.Render()
return nil
}
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func DeleteHandler(cmd *cobra.Command, args []string) error {
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
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// Unload the model if it's running before deletion
opts := &runOptions{
Model: args[0],
KeepAlive: &api.Duration{Duration: 0},
}
if err := loadOrUnloadModel(cmd, opts); err != nil {
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if !strings.Contains(strings.ToLower(err.Error()), "not found") {
fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
}
}
for _, name := range args {
req := api.DeleteRequest{Name: name}
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if err := client.Delete(cmd.Context(), &req); err != nil {
return err
}
fmt.Printf("deleted '%s'\n", name)
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}
return nil
}
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func ShowHandler(cmd *cobra.Command, args []string) error {
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client, err := api.ClientFromEnvironment()
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if err != nil {
return err
}
license, errLicense := cmd.Flags().GetBool("license")
modelfile, errModelfile := cmd.Flags().GetBool("modelfile")
parameters, errParams := cmd.Flags().GetBool("parameters")
system, errSystem := cmd.Flags().GetBool("system")
template, errTemplate := cmd.Flags().GetBool("template")
verbose, errVerbose := cmd.Flags().GetBool("verbose")
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for _, boolErr := range []error{errLicense, errModelfile, errParams, errSystem, errTemplate, errVerbose} {
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if boolErr != nil {
return errors.New("error retrieving flags")
}
}
flagsSet := 0
showType := ""
if license {
flagsSet++
showType = "license"
}
if modelfile {
flagsSet++
showType = "modelfile"
}
if parameters {
flagsSet++
showType = "parameters"
}
if system {
flagsSet++
showType = "system"
}
if template {
flagsSet++
showType = "template"
}
if flagsSet > 1 {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
}
req := api.ShowRequest{Name: args[0], Verbose: verbose}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
}
if flagsSet == 1 {
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Print(resp.System)
case "template":
fmt.Print(resp.Template)
}
return nil
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}
return showInfo(resp, verbose, os.Stdout)
}
func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
tableRender := func(header string, rows func() [][]string) {
fmt.Fprintln(w, " ", header)
table := tablewriter.NewWriter(w)
table.SetAlignment(tablewriter.ALIGN_LEFT)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
switch header {
case "Template", "System", "License":
table.SetColWidth(100)
}
table.AppendBulk(rows())
table.Render()
fmt.Fprintln(w)
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}
tableRender("Model", func() (rows [][]string) {
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if resp.RemoteHost != "" {
rows = append(rows, []string{"", "Remote model", resp.RemoteModel})
rows = append(rows, []string{"", "Remote URL", resp.RemoteHost})
}
if resp.ModelInfo != nil {
arch := resp.ModelInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch})
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var paramStr string
if resp.Details.ParameterSize != "" {
paramStr = resp.Details.ParameterSize
} else if v, ok := resp.ModelInfo["general.parameter_count"]; ok {
if f, ok := v.(float64); ok {
paramStr = format.HumanNumber(uint64(f))
}
}
rows = append(rows, []string{"", "parameters", paramStr})
if v, ok := resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)]; ok {
if f, ok := v.(float64); ok {
rows = append(rows, []string{"", "context length", strconv.FormatFloat(f, 'f', -1, 64)})
}
}
if v, ok := resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)]; ok {
if f, ok := v.(float64); ok {
rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(f, 'f', -1, 64)})
}
}
} else {
rows = append(rows, []string{"", "architecture", resp.Details.Family})
rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
}
rows = append(rows, []string{"", "quantization", resp.Details.QuantizationLevel})
return
})
if len(resp.Capabilities) > 0 {
tableRender("Capabilities", func() (rows [][]string) {
for _, capability := range resp.Capabilities {
rows = append(rows, []string{"", capability.String()})
}
return
})
}
if resp.ProjectorInfo != nil {
tableRender("Projector", func() (rows [][]string) {
arch := resp.ProjectorInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch})
rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))})
rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ProjectorInfo[fmt.Sprintf("%s.vision.embedding_length", arch)].(float64), 'f', -1, 64)})
rows = append(rows, []string{"", "dimensions", strconv.FormatFloat(resp.ProjectorInfo[fmt.Sprintf("%s.vision.projection_dim", arch)].(float64), 'f', -1, 64)})
return
})
}
if resp.Parameters != "" {
tableRender("Parameters", func() (rows [][]string) {
scanner := bufio.NewScanner(strings.NewReader(resp.Parameters))
for scanner.Scan() {
if text := scanner.Text(); text != "" {
rows = append(rows, append([]string{""}, strings.Fields(text)...))
}
}
return
})
}
if resp.ModelInfo != nil && verbose {
tableRender("Metadata", func() (rows [][]string) {
keys := make([]string, 0, len(resp.ModelInfo))
for k := range resp.ModelInfo {
keys = append(keys, k)
}
sort.Strings(keys)
for _, k := range keys {
var v string
switch vData := resp.ModelInfo[k].(type) {
case bool:
v = fmt.Sprintf("%t", vData)
case string:
v = vData
case float64:
v = fmt.Sprintf("%g", vData)
case []any:
targetWidth := 10 // Small width where we are displaying the data in a column
var itemsToShow int
totalWidth := 1 // Start with 1 for opening bracket
// Find how many we can fit
for i := range vData {
itemStr := fmt.Sprintf("%v", vData[i])
width := runewidth.StringWidth(itemStr)
// Add separator width (", ") for all items except the first
if i > 0 {
width += 2
}
// Check if adding this item would exceed our width limit
if totalWidth+width > targetWidth && i > 0 {
break
}
totalWidth += width
itemsToShow++
}
// Format the output
if itemsToShow < len(vData) {
v = fmt.Sprintf("%v", vData[:itemsToShow])
v = strings.TrimSuffix(v, "]")
v += fmt.Sprintf(" ...+%d more]", len(vData)-itemsToShow)
} else {
v = fmt.Sprintf("%v", vData)
}
default:
v = fmt.Sprintf("%T", vData)
}
rows = append(rows, []string{"", k, v})
}
return
})
}
if len(resp.Tensors) > 0 && verbose {
tableRender("Tensors", func() (rows [][]string) {
for _, t := range resp.Tensors {
rows = append(rows, []string{"", t.Name, t.Type, fmt.Sprint(t.Shape)})
}
return
})
}
head := func(s string, n int) (rows [][]string) {
scanner := bufio.NewScanner(strings.NewReader(s))
count := 0
for scanner.Scan() {
text := strings.TrimSpace(scanner.Text())
if text == "" {
continue
}
count++
if n < 0 || count <= n {
rows = append(rows, []string{"", text})
}
}
if n >= 0 && count > n {
rows = append(rows, []string{"", "..."})
}
return
}
if resp.System != "" {
tableRender("System", func() [][]string {
return head(resp.System, 2)
})
}
if resp.License != "" {
tableRender("License", func() [][]string {
return head(resp.License, 2)
})
}
return nil
}
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func CopyHandler(cmd *cobra.Command, args []string) error {
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
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req := api.CopyRequest{Source: args[0], Destination: args[1]}
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if err := client.Copy(cmd.Context(), &req); err != nil {
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return err
}
fmt.Printf("copied '%s' to '%s'\n", args[0], args[1])
return nil
}
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func PullHandler(cmd *cobra.Command, args []string) error {
insecure, err := cmd.Flags().GetBool("insecure")
if err != nil {
return err
}
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
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p := progress.NewProgress(os.Stderr)
defer p.Stop()
bars := make(map[string]*progress.Bar)
var status string
var spinner *progress.Spinner
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fn := func(resp api.ProgressResponse) error {
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if resp.Digest != "" {
if resp.Completed == 0 {
// This is the initial status update for the
// layer, which the server sends before
// beginning the download, for clients to
// compute total size and prepare for
// downloads, if needed.
//
// Skipping this here to avoid showing a 0%
// progress bar, which *should* clue the user
// into the fact that many things are being
// downloaded and that the current active
// download is not that last. However, in rare
// cases it seems to be triggering to some, and
// it isn't worth explaining, so just ignore
// and regress to the old UI that keeps giving
// you the "But wait, there is more!" after
// each "100% done" bar, which is "better."
return nil
}
if spinner != nil {
spinner.Stop()
}
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bar, ok := bars[resp.Digest]
if !ok {
name, isDigest := strings.CutPrefix(resp.Digest, "sha256:")
name = strings.TrimSpace(name)
if isDigest {
name = name[:min(12, len(name))]
}
bar = progress.NewBar(fmt.Sprintf("pulling %s:", name), resp.Total, resp.Completed)
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bars[resp.Digest] = bar
p.Add(resp.Digest, bar)
}
bar.Set(resp.Completed)
} else if status != resp.Status {
if spinner != nil {
spinner.Stop()
}
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status = resp.Status
spinner = progress.NewSpinner(status)
p.Add(status, spinner)
}
return nil
}
2023-07-07 22:22:37 +08:00
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request := api.PullRequest{Name: args[0], Insecure: insecure}
return client.Pull(cmd.Context(), &request, fn)
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}
type generateContextKey string
type runOptions struct {
Model string
ParentModel string
Prompt string
Messages []api.Message
WordWrap bool
Format string
System string
Images []api.ImageData
Options map[string]any
MultiModal bool
KeepAlive *api.Duration
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
Think *api.ThinkValue
HideThinking bool
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ShowConnect bool
}
func (r runOptions) Copy() runOptions {
var messages []api.Message
if r.Messages != nil {
messages = make([]api.Message, len(r.Messages))
copy(messages, r.Messages)
}
var images []api.ImageData
if r.Images != nil {
images = make([]api.ImageData, len(r.Images))
copy(images, r.Images)
}
var opts map[string]any
if r.Options != nil {
opts = make(map[string]any, len(r.Options))
for k, v := range r.Options {
opts[k] = v
}
}
var think *api.ThinkValue
if r.Think != nil {
cThink := *r.Think
think = &cThink
}
return runOptions{
Model: r.Model,
ParentModel: r.ParentModel,
Prompt: r.Prompt,
Messages: messages,
WordWrap: r.WordWrap,
Format: r.Format,
System: r.System,
Images: images,
Options: opts,
MultiModal: r.MultiModal,
KeepAlive: r.KeepAlive,
Think: think,
HideThinking: r.HideThinking,
ShowConnect: r.ShowConnect,
}
}
type displayResponseState struct {
lineLength int
wordBuffer string
}
func displayResponse(content string, wordWrap bool, state *displayResponseState) {
termWidth, _, _ := term.GetSize(int(os.Stdout.Fd()))
if wordWrap && termWidth >= 10 {
for _, ch := range content {
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if state.lineLength+1 > termWidth-5 {
if runewidth.StringWidth(state.wordBuffer) > termWidth-10 {
fmt.Printf("%s%c", state.wordBuffer, ch)
state.wordBuffer = ""
state.lineLength = 0
continue
}
// backtrack the length of the last word and clear to the end of the line
a := runewidth.StringWidth(state.wordBuffer)
if a > 0 {
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fmt.Printf("\x1b[%dD", a)
}
fmt.Printf("\x1b[K\n")
fmt.Printf("%s%c", state.wordBuffer, ch)
chWidth := runewidth.RuneWidth(ch)
state.lineLength = runewidth.StringWidth(state.wordBuffer) + chWidth
} else {
fmt.Print(string(ch))
state.lineLength += runewidth.RuneWidth(ch)
if runewidth.RuneWidth(ch) >= 2 {
state.wordBuffer = ""
continue
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}
switch ch {
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
case ' ', '\t':
state.wordBuffer = ""
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
case '\n', '\r':
state.lineLength = 0
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
state.wordBuffer = ""
default:
state.wordBuffer += string(ch)
}
}
}
} else {
fmt.Printf("%s%s", state.wordBuffer, content)
if len(state.wordBuffer) > 0 {
state.wordBuffer = ""
}
}
}
func thinkingOutputOpeningText(plainText bool) string {
text := "Thinking...\n"
if plainText {
return text
}
return readline.ColorGrey + readline.ColorBold + text + readline.ColorDefault + readline.ColorGrey
}
func thinkingOutputClosingText(plainText bool) string {
text := "...done thinking.\n\n"
if plainText {
return text
}
return readline.ColorGrey + readline.ColorBold + text + readline.ColorDefault
}
func chat(cmd *cobra.Command, opts runOptions) (*api.Message, error) {
client, err := api.ClientFromEnvironment()
if err != nil {
return nil, err
}
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
cancelCtx, cancel := context.WithCancel(cmd.Context())
defer cancel()
sigChan := make(chan os.Signal, 1)
signal.Notify(sigChan, syscall.SIGINT)
go func() {
<-sigChan
cancel()
}()
var state *displayResponseState = &displayResponseState{}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
var thinkingContent strings.Builder
var latest api.ChatResponse
var fullResponse strings.Builder
var thinkTagOpened bool = false
var thinkTagClosed bool = false
role := "assistant"
fn := func(response api.ChatResponse) error {
if response.Message.Content != "" || !opts.HideThinking {
p.StopAndClear()
}
latest = response
role = response.Message.Role
if response.Message.Thinking != "" && !opts.HideThinking {
if !thinkTagOpened {
fmt.Print(thinkingOutputOpeningText(false))
thinkTagOpened = true
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkTagClosed = false
}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkingContent.WriteString(response.Message.Thinking)
displayResponse(response.Message.Thinking, opts.WordWrap, state)
}
content := response.Message.Content
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
if thinkTagOpened && !thinkTagClosed && (content != "" || len(response.Message.ToolCalls) > 0) {
if !strings.HasSuffix(thinkingContent.String(), "\n") {
fmt.Println()
}
fmt.Print(thinkingOutputClosingText(false))
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkTagOpened = false
thinkTagClosed = true
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
state = &displayResponseState{}
}
// purposefully not putting thinking blocks in the response, which would
// only be needed if we later added tool calling to the cli (they get
// filtered out anyway since current models don't expect them unless you're
// about to finish some tool calls)
fullResponse.WriteString(content)
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
if response.Message.ToolCalls != nil {
toolCalls := response.Message.ToolCalls
if len(toolCalls) > 0 {
fmt.Print(renderToolCalls(toolCalls, false))
}
}
displayResponse(content, opts.WordWrap, state)
return nil
}
2024-12-07 06:13:15 +08:00
if opts.Format == "json" {
opts.Format = `"` + opts.Format + `"`
}
req := &api.ChatRequest{
Model: opts.Model,
Messages: opts.Messages,
Format: json.RawMessage(opts.Format),
Options: opts.Options,
Think: opts.Think,
}
if opts.KeepAlive != nil {
req.KeepAlive = opts.KeepAlive
}
if err := client.Chat(cancelCtx, req, fn); err != nil {
if errors.Is(err, context.Canceled) {
return nil, nil
}
// this error should ideally be wrapped properly by the client
if strings.Contains(err.Error(), "upstream error") {
p.StopAndClear()
fmt.Println("An error occurred while processing your message. Please try again.")
fmt.Println()
return nil, nil
}
return nil, err
}
if len(opts.Messages) > 0 {
fmt.Println()
fmt.Println()
}
verbose, err := cmd.Flags().GetBool("verbose")
if err != nil {
return nil, err
}
if verbose {
latest.Summary()
}
return &api.Message{Role: role, Content: fullResponse.String()}, nil
}
func generate(cmd *cobra.Command, opts runOptions) error {
2023-10-10 03:18:26 +08:00
client, err := api.ClientFromEnvironment()
2023-09-19 03:26:56 +08:00
if err != nil {
return err
2023-09-19 03:26:56 +08:00
}
2023-07-08 01:12:58 +08:00
2023-11-15 08:58:51 +08:00
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
2023-11-15 08:58:51 +08:00
spinner := progress.NewSpinner("")
p.Add("", spinner)
var latest api.GenerateResponse
generateContext, ok := cmd.Context().Value(generateContextKey("context")).([]int)
if !ok {
generateContext = []int{}
}
2023-10-13 06:56:40 +08:00
ctx, cancel := context.WithCancel(cmd.Context())
defer cancel()
sigChan := make(chan os.Signal, 1)
signal.Notify(sigChan, syscall.SIGINT)
go func() {
<-sigChan
cancel()
}()
var state *displayResponseState = &displayResponseState{}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
var thinkingContent strings.Builder
var thinkTagOpened bool = false
var thinkTagClosed bool = false
plainText := !term.IsTerminal(int(os.Stdout.Fd()))
fn := func(response api.GenerateResponse) error {
2023-09-19 03:26:56 +08:00
latest = response
content := response.Response
2023-07-13 09:18:06 +08:00
if response.Response != "" || !opts.HideThinking {
p.StopAndClear()
}
if response.Thinking != "" && !opts.HideThinking {
if !thinkTagOpened {
fmt.Print(thinkingOutputOpeningText(plainText))
thinkTagOpened = true
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkTagClosed = false
}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkingContent.WriteString(response.Thinking)
displayResponse(response.Thinking, opts.WordWrap, state)
}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
if thinkTagOpened && !thinkTagClosed && (content != "" || len(response.ToolCalls) > 0) {
if !strings.HasSuffix(thinkingContent.String(), "\n") {
fmt.Println()
}
fmt.Print(thinkingOutputClosingText(plainText))
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
thinkTagOpened = false
thinkTagClosed = true
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
state = &displayResponseState{}
}
displayResponse(content, opts.WordWrap, state)
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
if response.ToolCalls != nil {
toolCalls := response.ToolCalls
if len(toolCalls) > 0 {
fmt.Print(renderToolCalls(toolCalls, plainText))
}
}
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return nil
}
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if opts.MultiModal {
opts.Prompt, opts.Images, err = extractFileData(opts.Prompt)
if err != nil {
return err
}
}
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if opts.Format == "json" {
opts.Format = `"` + opts.Format + `"`
}
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request := api.GenerateRequest{
Model: opts.Model,
Prompt: opts.Prompt,
Context: generateContext,
Images: opts.Images,
Format: json.RawMessage(opts.Format),
System: opts.System,
Options: opts.Options,
KeepAlive: opts.KeepAlive,
Think: opts.Think,
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}
if err := client.Generate(ctx, &request, fn); err != nil {
if errors.Is(err, context.Canceled) {
return nil
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}
return err
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}
if opts.Prompt != "" {
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fmt.Println()
fmt.Println()
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}
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if !latest.Done {
return nil
}
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verbose, err := cmd.Flags().GetBool("verbose")
if err != nil {
return err
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}
2023-07-19 02:59:42 +08:00
2023-09-19 03:26:56 +08:00
if verbose {
latest.Summary()
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}
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ctx = context.WithValue(cmd.Context(), generateContextKey("context"), latest.Context)
cmd.SetContext(ctx)
return nil
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}
func RunServer(_ *cobra.Command, _ []string) error {
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if err := initializeKeypair(); err != nil {
return err
}
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ln, err := net.Listen("tcp", envconfig.Host().Host)
if err != nil {
return err
}
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err = server.Serve(ln)
if errors.Is(err, http.ErrServerClosed) {
return nil
}
return err
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}
func initializeKeypair() error {
home, err := os.UserHomeDir()
if err != nil {
return err
}
privKeyPath := filepath.Join(home, ".ollama", "id_ed25519")
pubKeyPath := filepath.Join(home, ".ollama", "id_ed25519.pub")
_, err = os.Stat(privKeyPath)
if os.IsNotExist(err) {
fmt.Printf("Couldn't find '%s'. Generating new private key.\n", privKeyPath)
cryptoPublicKey, cryptoPrivateKey, err := ed25519.GenerateKey(rand.Reader)
if err != nil {
return err
}
privateKeyBytes, err := ssh.MarshalPrivateKey(cryptoPrivateKey, "")
if err != nil {
return err
}
if err := os.MkdirAll(filepath.Dir(privKeyPath), 0o755); err != nil {
return fmt.Errorf("could not create directory %w", err)
}
if err := os.WriteFile(privKeyPath, pem.EncodeToMemory(privateKeyBytes), 0o600); err != nil {
return err
}
sshPublicKey, err := ssh.NewPublicKey(cryptoPublicKey)
if err != nil {
return err
}
publicKeyBytes := ssh.MarshalAuthorizedKey(sshPublicKey)
if err := os.WriteFile(pubKeyPath, publicKeyBytes, 0o644); err != nil {
return err
}
fmt.Printf("Your new public key is: \n\n%s\n", publicKeyBytes)
}
return nil
}
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func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
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client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
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if err := client.Heartbeat(cmd.Context()); err != nil {
if !(strings.Contains(err.Error(), " refused") || strings.Contains(err.Error(), "could not connect")) {
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return err
}
if err := startApp(cmd.Context(), client); err != nil {
return fmt.Errorf("ollama server not responding - %w", err)
}
}
return nil
}
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func versionHandler(cmd *cobra.Command, _ []string) {
client, err := api.ClientFromEnvironment()
if err != nil {
return
}
serverVersion, err := client.Version(cmd.Context())
if err != nil {
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fmt.Println("Warning: could not connect to a running Ollama instance")
}
if serverVersion != "" {
fmt.Printf("ollama version is %s\n", serverVersion)
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}
if serverVersion != version.Version {
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fmt.Printf("Warning: client version is %s\n", version.Version)
}
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}
func appendEnvDocs(cmd *cobra.Command, envs []envconfig.EnvVar) {
if len(envs) == 0 {
return
}
envUsage := `
Environment Variables:
`
for _, e := range envs {
envUsage += fmt.Sprintf(" %-24s %s\n", e.Name, e.Description)
}
cmd.SetUsageTemplate(cmd.UsageTemplate() + envUsage)
}
func NewCLI() *cobra.Command {
log.SetFlags(log.LstdFlags | log.Lshortfile)
2023-11-23 01:41:02 +08:00
cobra.EnableCommandSorting = false
if runtime.GOOS == "windows" && term.IsTerminal(int(os.Stdout.Fd())) {
console.ConsoleFromFile(os.Stdin) //nolint:errcheck
}
rootCmd := &cobra.Command{
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Use: "ollama",
Short: "Large language model runner",
SilenceUsage: true,
SilenceErrors: true,
CompletionOptions: cobra.CompletionOptions{
DisableDefaultCmd: true,
},
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Run: func(cmd *cobra.Command, args []string) {
if version, _ := cmd.Flags().GetBool("version"); version {
versionHandler(cmd, args)
return
}
cmd.Print(cmd.UsageString())
},
}
2023-11-23 01:41:02 +08:00
rootCmd.Flags().BoolP("version", "v", false, "Show version information")
createCmd := &cobra.Command{
Use: "create MODEL",
Short: "Create a model",
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Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: CreateHandler,
}
createCmd.Flags().StringP("file", "f", "", "Name of the Modelfile (default \"Modelfile\")")
createCmd.Flags().StringP("quantize", "q", "", "Quantize model to this level (e.g. q4_K_M)")
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showCmd := &cobra.Command{
Use: "show MODEL",
Short: "Show information for a model",
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Args: cobra.ExactArgs(1),
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PreRunE: checkServerHeartbeat,
RunE: ShowHandler,
}
showCmd.Flags().Bool("license", false, "Show license of a model")
showCmd.Flags().Bool("modelfile", false, "Show Modelfile of a model")
showCmd.Flags().Bool("parameters", false, "Show parameters of a model")
showCmd.Flags().Bool("template", false, "Show template of a model")
showCmd.Flags().Bool("system", false, "Show system message of a model")
showCmd.Flags().BoolP("verbose", "v", false, "Show detailed model information")
2023-09-07 02:04:17 +08:00
runCmd := &cobra.Command{
Use: "run MODEL [PROMPT]",
Short: "Run a model",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: RunHandler,
}
runCmd.Flags().String("keepalive", "", "Duration to keep a model loaded (e.g. 5m)")
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runCmd.Flags().Bool("verbose", false, "Show timings for response")
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runCmd.Flags().Bool("insecure", false, "Use an insecure registry")
runCmd.Flags().Bool("nowordwrap", false, "Don't wrap words to the next line automatically")
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runCmd.Flags().String("format", "", "Response format (e.g. json)")
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
runCmd.Flags().String("think", "", "Enable thinking mode: true/false or high/medium/low for supported models")
runCmd.Flags().Lookup("think").NoOptDefVal = "true"
runCmd.Flags().Bool("hidethinking", false, "Hide thinking output (if provided)")
2024-09-12 07:36:21 +08:00
stopCmd := &cobra.Command{
Use: "stop MODEL",
Short: "Stop a running model",
Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: StopHandler,
}
serveCmd := &cobra.Command{
Use: "serve",
Aliases: []string{"start"},
Short: "Start ollama",
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Args: cobra.ExactArgs(0),
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RunE: RunServer,
}
pullCmd := &cobra.Command{
Use: "pull MODEL",
Short: "Pull a model from a registry",
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Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: PullHandler,
}
pullCmd.Flags().Bool("insecure", false, "Use an insecure registry")
pushCmd := &cobra.Command{
Use: "push MODEL",
Short: "Push a model to a registry",
2023-10-19 02:57:22 +08:00
Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: PushHandler,
}
pushCmd.Flags().Bool("insecure", false, "Use an insecure registry")
2025-09-18 05:40:53 +08:00
signinCmd := &cobra.Command{
Use: "signin",
Short: "Sign in to ollama.com",
Args: cobra.ExactArgs(0),
PreRunE: checkServerHeartbeat,
RunE: SigninHandler,
}
signoutCmd := &cobra.Command{
Use: "signout",
Short: "Sign out from ollama.com",
Args: cobra.ExactArgs(0),
PreRunE: checkServerHeartbeat,
RunE: SignoutHandler,
}
2023-07-19 00:09:45 +08:00
listCmd := &cobra.Command{
Use: "list",
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Aliases: []string{"ls"},
Short: "List models",
PreRunE: checkServerHeartbeat,
RunE: ListHandler,
2023-07-21 07:09:23 +08:00
}
psCmd := &cobra.Command{
Use: "ps",
Short: "List running models",
PreRunE: checkServerHeartbeat,
RunE: ListRunningHandler,
}
2023-07-24 23:27:28 +08:00
copyCmd := &cobra.Command{
2024-05-02 03:39:05 +08:00
Use: "cp SOURCE DESTINATION",
Short: "Copy a model",
2023-10-19 02:57:22 +08:00
Args: cobra.ExactArgs(2),
PreRunE: checkServerHeartbeat,
RunE: CopyHandler,
2023-07-24 23:27:28 +08:00
}
2023-07-21 07:09:23 +08:00
deleteCmd := &cobra.Command{
2023-10-19 02:57:22 +08:00
Use: "rm MODEL [MODEL...]",
Short: "Remove a model",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: DeleteHandler,
2023-07-19 00:09:45 +08:00
}
build: Make target improvements (#7499) * llama: wire up builtin runner This adds a new entrypoint into the ollama CLI to run the cgo built runner. On Mac arm64, this will have GPU support, but on all other platforms it will be the lowest common denominator CPU build. After we fully transition to the new Go runners more tech-debt can be removed and we can stop building the "default" runner via make and rely on the builtin always. * build: Make target improvements Add a few new targets and help for building locally. This also adjusts the runner lookup to favor local builds, then runners relative to the executable, and finally payloads. * Support customized CPU flags for runners This implements a simplified custom CPU flags pattern for the runners. When built without overrides, the runner name contains the vector flag we check for (AVX) to ensure we don't try to run on unsupported systems and crash. If the user builds a customized set, we omit the naming scheme and don't check for compatibility. This avoids checking requirements at runtime, so that logic has been removed as well. This can be used to build GPU runners with no vector flags, or CPU/GPU runners with additional flags (e.g. AVX512) enabled. * Use relative paths If the user checks out the repo in a path that contains spaces, make gets really confused so use relative paths for everything in-repo to avoid breakage. * Remove payloads from main binary * install: clean up prior libraries This removes support for v0.3.6 and older versions (before the tar bundle) and ensures we clean up prior libraries before extracting the bundle(s). Without this change, runners and dependent libraries could leak when we update and lead to subtle runtime errors.
2024-12-11 01:47:19 +08:00
runnerCmd := &cobra.Command{
Use: "runner",
Hidden: true,
RunE: func(cmd *cobra.Command, args []string) error {
return runner.Execute(os.Args[1:])
},
FParseErrWhitelist: cobra.FParseErrWhitelist{UnknownFlags: true},
}
runnerCmd.SetHelpFunc(func(cmd *cobra.Command, args []string) {
_ = runner.Execute(args[1:])
})
envVars := envconfig.AsMap()
envs := []envconfig.EnvVar{envVars["OLLAMA_HOST"]}
for _, cmd := range []*cobra.Command{
createCmd,
showCmd,
runCmd,
2024-09-12 07:36:21 +08:00
stopCmd,
pullCmd,
pushCmd,
listCmd,
psCmd,
copyCmd,
deleteCmd,
serveCmd,
} {
switch cmd {
case runCmd:
appendEnvDocs(cmd, []envconfig.EnvVar{envVars["OLLAMA_HOST"], envVars["OLLAMA_NOHISTORY"]})
case serveCmd:
appendEnvDocs(cmd, []envconfig.EnvVar{
envVars["OLLAMA_DEBUG"],
envVars["OLLAMA_HOST"],
envVars["OLLAMA_CONTEXT_LENGTH"],
envVars["OLLAMA_KEEP_ALIVE"],
envVars["OLLAMA_MAX_LOADED_MODELS"],
envVars["OLLAMA_MAX_QUEUE"],
envVars["OLLAMA_MODELS"],
envVars["OLLAMA_NUM_PARALLEL"],
envVars["OLLAMA_NOPRUNE"],
envVars["OLLAMA_ORIGINS"],
2024-07-24 06:14:28 +08:00
envVars["OLLAMA_SCHED_SPREAD"],
envVars["OLLAMA_FLASH_ATTENTION"],
envVars["OLLAMA_KV_CACHE_TYPE"],
envVars["OLLAMA_LLM_LIBRARY"],
envVars["OLLAMA_GPU_OVERHEAD"],
envVars["OLLAMA_LOAD_TIMEOUT"],
})
default:
appendEnvDocs(cmd, envs)
}
}
rootCmd.AddCommand(
serveCmd,
createCmd,
2023-09-07 02:04:17 +08:00
showCmd,
runCmd,
2024-09-12 07:36:21 +08:00
stopCmd,
pullCmd,
pushCmd,
2025-09-18 05:40:53 +08:00
signinCmd,
signoutCmd,
2023-07-19 00:09:45 +08:00
listCmd,
psCmd,
2023-07-24 23:27:28 +08:00
copyCmd,
2023-07-21 07:09:23 +08:00
deleteCmd,
build: Make target improvements (#7499) * llama: wire up builtin runner This adds a new entrypoint into the ollama CLI to run the cgo built runner. On Mac arm64, this will have GPU support, but on all other platforms it will be the lowest common denominator CPU build. After we fully transition to the new Go runners more tech-debt can be removed and we can stop building the "default" runner via make and rely on the builtin always. * build: Make target improvements Add a few new targets and help for building locally. This also adjusts the runner lookup to favor local builds, then runners relative to the executable, and finally payloads. * Support customized CPU flags for runners This implements a simplified custom CPU flags pattern for the runners. When built without overrides, the runner name contains the vector flag we check for (AVX) to ensure we don't try to run on unsupported systems and crash. If the user builds a customized set, we omit the naming scheme and don't check for compatibility. This avoids checking requirements at runtime, so that logic has been removed as well. This can be used to build GPU runners with no vector flags, or CPU/GPU runners with additional flags (e.g. AVX512) enabled. * Use relative paths If the user checks out the repo in a path that contains spaces, make gets really confused so use relative paths for everything in-repo to avoid breakage. * Remove payloads from main binary * install: clean up prior libraries This removes support for v0.3.6 and older versions (before the tar bundle) and ensures we clean up prior libraries before extracting the bundle(s). Without this change, runners and dependent libraries could leak when we update and lead to subtle runtime errors.
2024-12-11 01:47:19 +08:00
runnerCmd,
)
return rootCmd
}
// If the user has explicitly set thinking options, either through the CLI or
// through the `/set think` or `set nothink` interactive options, then we
// respect them. Otherwise, we check model capabilities to see if the model
// supports thinking. If the model does support thinking, we enable it.
// Otherwise, we unset the thinking option (which is different than setting it
// to false).
//
// If capabilities are not provided, we fetch them from the server.
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
func inferThinkingOption(caps *[]model.Capability, runOpts *runOptions, explicitlySetByUser bool) (*api.ThinkValue, error) {
if explicitlySetByUser {
return runOpts.Think, nil
}
if caps == nil {
client, err := api.ClientFromEnvironment()
if err != nil {
return nil, err
}
ret, err := client.Show(context.Background(), &api.ShowRequest{
Model: runOpts.Model,
})
if err != nil {
return nil, err
}
caps = &ret.Capabilities
}
thinkingSupported := false
for _, cap := range *caps {
if cap == model.CapabilityThinking {
thinkingSupported = true
}
}
if thinkingSupported {
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
return &api.ThinkValue{Value: true}, nil
}
return nil, nil
}
gpt-oss (#11672) * bf16 * tests * gpt-oss * enable gptoss for engine * rough estimate * convert to mxfp4 * handle safetensors U8 * clamp glu/linear * update tokenizer * MXFP4 support This implements the Open Compute Microscaling (MX) FP4 format as a tensor type with backend implementations focusing on mulmat and mulmatid on CPU, CUDA, and Metal. * Unit tests for MXFP4 support This exercises various operations and shapes on both CPU and GPU (if detected on the system) * cuda graph * unit test adjustments * cuda: optimize memory access Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4 * mac: fix crash on old macos versions cblas_sgemm is only supported on v13.3 and up, however bf16 is only supported on v14+ so we were falling back to ggml-blas and crashing on bf16 tensors. Checking for the function being null seems to be the simplest way to condittionally avoid registering the backend. * server: Minimum context length for gptoss This model requires a minimum context length of 8192 to function effectively. Users can set higher values through all normal mechanisms but lower values will be silently reset. * ggml: Multiply by numParallel for gptoss sliding window When computing the graph size estimate, the context size is already multiplied by numParallel so estimates reflect that. However, since sliding window models use a smaller, fixed context size, they need to manually take numParallel into account. * gpt-oss integration includes harmony parser and thinking levels, etc. * fix sync * fix tests * fix lint --------- Co-authored-by: Daniel Hiltgen <daniel@ollama.com> Co-authored-by: Jesse Gross <jesse@ollama.com> Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-06 03:21:16 +08:00
func renderToolCalls(toolCalls []api.ToolCall, plainText bool) string {
out := ""
formatExplanation := ""
formatValues := ""
if !plainText {
formatExplanation = readline.ColorGrey + readline.ColorBold
formatValues = readline.ColorDefault
out += formatExplanation
}
for i, toolCall := range toolCalls {
argsAsJSON, err := json.Marshal(toolCall.Function.Arguments)
if err != nil {
return ""
}
if i > 0 {
out += "\n"
}
// all tool calls are unexpected since we don't currently support registering any in the CLI
out += fmt.Sprintf(" Model called a non-existent function '%s()' with arguments: %s", formatValues+toolCall.Function.Name+formatExplanation, formatValues+string(argsAsJSON)+formatExplanation)
}
if !plainText {
out += readline.ColorDefault
}
return out
}