Merge branch 'ollama:main' into main

This commit is contained in:
likelovewant
2025-09-21 10:33:39 +08:00
committed by GitHub
74 changed files with 4221 additions and 525 deletions

View File

@@ -1,6 +1,7 @@
# vim: filetype=dockerfile # vim: filetype=dockerfile
ARG FLAVOR=${TARGETARCH} ARG FLAVOR=${TARGETARCH}
ARG PARALLEL=8
ARG ROCMVERSION=6.3.3 ARG ROCMVERSION=6.3.3
ARG JETPACK5VERSION=r35.4.1 ARG JETPACK5VERSION=r35.4.1
@@ -34,46 +35,51 @@ ENV LDFLAGS=-s
FROM base AS cpu FROM base AS cpu
RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++ RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++
ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CPU' \ cmake --preset 'CPU' \
&& cmake --build --parallel --preset 'CPU' \ && cmake --build --parallel ${PARALLEL} --preset 'CPU' \
&& cmake --install build --component CPU --strip --parallel 8 && cmake --install build --component CPU --strip --parallel ${PARALLEL}
FROM base AS cuda-11 FROM base AS cuda-11
ARG CUDA11VERSION=11.8 ARG CUDA11VERSION=11.8
RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-} RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-}
ENV PATH=/usr/local/cuda-11/bin:$PATH ENV PATH=/usr/local/cuda-11/bin:$PATH
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 11' -DOLLAMA_RUNNER_DIR="cuda_v11" \ cmake --preset 'CUDA 11' -DOLLAMA_RUNNER_DIR="cuda_v11" \
&& cmake --build --parallel --preset 'CUDA 11' \ && cmake --build --parallel ${PARALLEL} --preset 'CUDA 11' \
&& cmake --install build --component CUDA --strip --parallel 8 && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS cuda-12 FROM base AS cuda-12
ARG CUDA12VERSION=12.8 ARG CUDA12VERSION=12.8
RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-} RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-}
ENV PATH=/usr/local/cuda-12/bin:$PATH ENV PATH=/usr/local/cuda-12/bin:$PATH
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 12' -DOLLAMA_RUNNER_DIR="cuda_v12"\ cmake --preset 'CUDA 12' -DOLLAMA_RUNNER_DIR="cuda_v12"\
&& cmake --build --parallel --preset 'CUDA 12' \ && cmake --build --parallel ${PARALLEL} --preset 'CUDA 12' \
&& cmake --install build --component CUDA --strip --parallel 8 && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS cuda-13 FROM base AS cuda-13
ARG CUDA13VERSION=13.0 ARG CUDA13VERSION=13.0
RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-} RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-}
ENV PATH=/usr/local/cuda-13/bin:$PATH ENV PATH=/usr/local/cuda-13/bin:$PATH
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'CUDA 13' -DOLLAMA_RUNNER_DIR="cuda_v13" \ cmake --preset 'CUDA 13' -DOLLAMA_RUNNER_DIR="cuda_v13" \
&& cmake --build --parallel --preset 'CUDA 13' \ && cmake --build --parallel ${PARALLEL} --preset 'CUDA 13' \
&& cmake --install build --component CUDA --strip --parallel 8 && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS rocm-6 FROM base AS rocm-6
ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'ROCm 6' \ cmake --preset 'ROCm 6' \
&& cmake --build --parallel --preset 'ROCm 6' \ && cmake --build --parallel ${PARALLEL} --preset 'ROCm 6' \
&& cmake --install build --component HIP --strip --parallel 8 && cmake --install build --component HIP --strip --parallel ${PARALLEL}
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
ARG CMAKEVERSION ARG CMAKEVERSION
@@ -81,10 +87,11 @@ RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1 && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json . COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 5' \ cmake --preset 'JetPack 5' \
&& cmake --build --parallel --preset 'JetPack 5' \ && cmake --build --parallel ${PARALLEL} --preset 'JetPack 5' \
&& cmake --install build --component CUDA --strip --parallel 8 && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6 FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
ARG CMAKEVERSION ARG CMAKEVERSION
@@ -92,10 +99,11 @@ RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1 && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json . COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
ARG PARALLEL
RUN --mount=type=cache,target=/root/.ccache \ RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 6' \ cmake --preset 'JetPack 6' \
&& cmake --build --parallel --preset 'JetPack 6' \ && cmake --build --parallel ${PARALLEL} --preset 'JetPack 6' \
&& cmake --install build --component CUDA --strip --parallel 8 && cmake --install build --component CUDA --strip --parallel ${PARALLEL}
FROM base AS build FROM base AS build
WORKDIR /go/src/github.com/ollama/ollama WORKDIR /go/src/github.com/ollama/ollama

View File

@@ -222,7 +222,17 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
return fmt.Errorf("unmarshal: %w", err) return fmt.Errorf("unmarshal: %w", err)
} }
if response.StatusCode >= http.StatusBadRequest { if response.StatusCode == http.StatusUnauthorized {
pubKey, pkErr := auth.GetPublicKey()
if pkErr != nil {
return pkErr
}
return AuthorizationError{
StatusCode: response.StatusCode,
Status: response.Status,
PublicKey: pubKey,
}
} else if response.StatusCode >= http.StatusBadRequest {
return StatusError{ return StatusError{
StatusCode: response.StatusCode, StatusCode: response.StatusCode,
Status: response.Status, Status: response.Status,
@@ -428,3 +438,16 @@ func (c *Client) Version(ctx context.Context) (string, error) {
return version.Version, nil return version.Version, nil
} }
// Signout will disconnect an ollama instance from ollama.com
func (c *Client) Signout(ctx context.Context, encodedKey string) error {
return c.do(ctx, http.MethodDelete, fmt.Sprintf("/api/user/keys/%s", encodedKey), nil, nil)
}
func (c *Client) Whoami(ctx context.Context) (*UserResponse, error) {
var resp UserResponse
if err := c.do(ctx, http.MethodPost, "/api/me", nil, &resp); err != nil {
return nil, err
}
return &resp, nil
}

View File

@@ -11,6 +11,8 @@ import (
"strings" "strings"
"time" "time"
"github.com/google/uuid"
"github.com/ollama/ollama/envconfig" "github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/types/model" "github.com/ollama/ollama/types/model"
) )
@@ -36,6 +38,19 @@ func (e StatusError) Error() string {
} }
} }
type AuthorizationError struct {
StatusCode int
Status string
PublicKey string `json:"public_key"`
}
func (e AuthorizationError) Error() string {
if e.Status != "" {
return e.Status
}
return "something went wrong, please see the ollama server logs for details"
}
// ImageData represents the raw binary data of an image file. // ImageData represents the raw binary data of an image file.
type ImageData []byte type ImageData []byte
@@ -313,12 +328,28 @@ func (t *ToolFunction) String() string {
// ChatResponse is the response returned by [Client.Chat]. Its fields are // ChatResponse is the response returned by [Client.Chat]. Its fields are
// similar to [GenerateResponse]. // similar to [GenerateResponse].
type ChatResponse struct { type ChatResponse struct {
// Model is the model name that generated the response.
Model string `json:"model"` Model string `json:"model"`
// RemoteModel is the name of the upstream model that generated the response.
RemoteModel string `json:"remote_model,omitempty"`
// RemoteHost is the URL of the upstream Ollama host that generated the response.
RemoteHost string `json:"remote_host,omitempty"`
// CreatedAt is the timestamp of the response.
CreatedAt time.Time `json:"created_at"` CreatedAt time.Time `json:"created_at"`
// Message contains the message or part of a message from the model.
Message Message `json:"message"` Message Message `json:"message"`
// Done specifies if the response is complete.
Done bool `json:"done"`
// DoneReason is the reason the model stopped generating text.
DoneReason string `json:"done_reason,omitempty"` DoneReason string `json:"done_reason,omitempty"`
Done bool `json:"done"` DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
Metrics Metrics
} }
@@ -329,13 +360,6 @@ type DebugInfo struct {
ImageCount int `json:"image_count,omitempty"` ImageCount int `json:"image_count,omitempty"`
} }
// DebugTemplateResponse is returned when _debug_render_only is set to true
type DebugTemplateResponse struct {
Model string `json:"model"`
CreatedAt time.Time `json:"created_at"`
DebugInfo DebugInfo `json:"_debug_info"`
}
type Metrics struct { type Metrics struct {
TotalDuration time.Duration `json:"total_duration,omitempty"` TotalDuration time.Duration `json:"total_duration,omitempty"`
LoadDuration time.Duration `json:"load_duration,omitempty"` LoadDuration time.Duration `json:"load_duration,omitempty"`
@@ -431,19 +455,48 @@ type EmbeddingResponse struct {
// CreateRequest is the request passed to [Client.Create]. // CreateRequest is the request passed to [Client.Create].
type CreateRequest struct { type CreateRequest struct {
// Model is the model name to create.
Model string `json:"model"` Model string `json:"model"`
// Stream specifies whether the response is streaming; it is true by default.
Stream *bool `json:"stream,omitempty"` Stream *bool `json:"stream,omitempty"`
// Quantize is the quantization format for the model; leave blank to not change the quantization level.
Quantize string `json:"quantize,omitempty"` Quantize string `json:"quantize,omitempty"`
// From is the name of the model or file to use as the source.
From string `json:"from,omitempty"` From string `json:"from,omitempty"`
// RemoteHost is the URL of the upstream ollama API for the model (if any).
RemoteHost string `json:"remote_host,omitempty"`
// Files is a map of files include when creating the model.
Files map[string]string `json:"files,omitempty"` Files map[string]string `json:"files,omitempty"`
// Adapters is a map of LoRA adapters to include when creating the model.
Adapters map[string]string `json:"adapters,omitempty"` Adapters map[string]string `json:"adapters,omitempty"`
// Template is the template used when constructing a request to the model.
Template string `json:"template,omitempty"` Template string `json:"template,omitempty"`
// License is a string or list of strings for licenses.
License any `json:"license,omitempty"` License any `json:"license,omitempty"`
// System is the system prompt for the model.
System string `json:"system,omitempty"` System string `json:"system,omitempty"`
// Parameters is a map of hyper-parameters which are applied to the model.
Parameters map[string]any `json:"parameters,omitempty"` Parameters map[string]any `json:"parameters,omitempty"`
// Messages is a list of messages added to the model before chat and generation requests.
Messages []Message `json:"messages,omitempty"` Messages []Message `json:"messages,omitempty"`
Renderer string `json:"renderer,omitempty"`
Parser string `json:"parser,omitempty"`
// Info is a map of additional information for the model
Info map[string]any `json:"info,omitempty"`
// Deprecated: set the model name with Model instead // Deprecated: set the model name with Model instead
Name string `json:"name"` Name string `json:"name"`
// Deprecated: use Quantize instead // Deprecated: use Quantize instead
@@ -480,8 +533,12 @@ type ShowResponse struct {
Parameters string `json:"parameters,omitempty"` Parameters string `json:"parameters,omitempty"`
Template string `json:"template,omitempty"` Template string `json:"template,omitempty"`
System string `json:"system,omitempty"` System string `json:"system,omitempty"`
Renderer string `json:"renderer,omitempty"`
Parser string `json:"parser,omitempty"`
Details ModelDetails `json:"details,omitempty"` Details ModelDetails `json:"details,omitempty"`
Messages []Message `json:"messages,omitempty"` Messages []Message `json:"messages,omitempty"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModelInfo map[string]any `json:"model_info,omitempty"` ModelInfo map[string]any `json:"model_info,omitempty"`
ProjectorInfo map[string]any `json:"projector_info,omitempty"` ProjectorInfo map[string]any `json:"projector_info,omitempty"`
Tensors []Tensor `json:"tensors,omitempty"` Tensors []Tensor `json:"tensors,omitempty"`
@@ -542,6 +599,8 @@ type ProcessResponse struct {
type ListModelResponse struct { type ListModelResponse struct {
Name string `json:"name"` Name string `json:"name"`
Model string `json:"model"` Model string `json:"model"`
RemoteModel string `json:"remote_model,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
ModifiedAt time.Time `json:"modified_at"` ModifiedAt time.Time `json:"modified_at"`
Size int64 `json:"size"` Size int64 `json:"size"`
Digest string `json:"digest"` Digest string `json:"digest"`
@@ -569,6 +628,12 @@ type GenerateResponse struct {
// Model is the model name that generated the response. // Model is the model name that generated the response.
Model string `json:"model"` Model string `json:"model"`
// RemoteModel is the name of the upstream model that generated the response.
RemoteModel string `json:"remote_model,omitempty"`
// RemoteHost is the URL of the upstream Ollama host that generated the response.
RemoteHost string `json:"remote_host,omitempty"`
// CreatedAt is the timestamp of the response. // CreatedAt is the timestamp of the response.
CreatedAt time.Time `json:"created_at"` CreatedAt time.Time `json:"created_at"`
@@ -592,6 +657,8 @@ type GenerateResponse struct {
Metrics Metrics
ToolCalls []ToolCall `json:"tool_calls,omitempty"` ToolCalls []ToolCall `json:"tool_calls,omitempty"`
DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
} }
// ModelDetails provides details about a model. // ModelDetails provides details about a model.
@@ -604,6 +671,18 @@ type ModelDetails struct {
QuantizationLevel string `json:"quantization_level"` QuantizationLevel string `json:"quantization_level"`
} }
// UserResponse provides information about a user.
type UserResponse struct {
ID uuid.UUID `json:"id"`
Email string `json:"email"`
Name string `json:"name"`
Bio string `json:"bio,omitempty"`
AvatarURL string `json:"avatarurl,omitempty"`
FirstName string `json:"firstname,omitempty"`
LastName string `json:"lastname,omitempty"`
Plan string `json:"plan,omitempty"`
}
// Tensor describes the metadata for a given tensor. // Tensor describes the metadata for a given tensor.
type Tensor struct { type Tensor struct {
Name string `json:"name"` Name string `json:"name"`

View File

@@ -19,6 +19,31 @@ import (
const defaultPrivateKey = "id_ed25519" const defaultPrivateKey = "id_ed25519"
func keyPath() (string, error) { func keyPath() (string, error) {
fileIsReadable := func(fp string) bool {
info, err := os.Stat(fp)
if err != nil {
return false
}
// Check that it's a regular file, not a directory or other file type
if !info.Mode().IsRegular() {
return false
}
// Try to open it to check readability
file, err := os.Open(fp)
if err != nil {
return false
}
file.Close()
return true
}
systemPath := filepath.Join("/usr/share/ollama/.ollama", defaultPrivateKey)
if fileIsReadable(systemPath) {
return systemPath, nil
}
home, err := os.UserHomeDir() home, err := os.UserHomeDir()
if err != nil { if err != nil {
return "", err return "", err

View File

@@ -5,6 +5,7 @@ import (
"context" "context"
"crypto/ed25519" "crypto/ed25519"
"crypto/rand" "crypto/rand"
"encoding/base64"
"encoding/json" "encoding/json"
"encoding/pem" "encoding/pem"
"errors" "errors"
@@ -14,6 +15,7 @@ import (
"math" "math"
"net" "net"
"net/http" "net/http"
"net/url"
"os" "os"
"os/signal" "os/signal"
"path/filepath" "path/filepath"
@@ -35,6 +37,7 @@ import (
"golang.org/x/term" "golang.org/x/term"
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
"github.com/ollama/ollama/auth"
"github.com/ollama/ollama/envconfig" "github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format" "github.com/ollama/ollama/format"
"github.com/ollama/ollama/parser" "github.com/ollama/ollama/parser"
@@ -47,6 +50,8 @@ import (
"github.com/ollama/ollama/version" "github.com/ollama/ollama/version"
) )
const ConnectInstructions = "To sign in, navigate to:\n https://ollama.com/connect?name=%s&key=%s\n\n"
// ensureThinkingSupport emits a warning if the model does not advertise thinking support // ensureThinkingSupport emits a warning if the model does not advertise thinking support
func ensureThinkingSupport(ctx context.Context, client *api.Client, name string) { func ensureThinkingSupport(ctx context.Context, client *api.Client, name string) {
if name == "" { if name == "" {
@@ -286,7 +291,17 @@ func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
Think: opts.Think, Think: opts.Think,
} }
return client.Generate(cmd.Context(), req, func(api.GenerateResponse) error { return nil }) 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
})
} }
func StopHandler(cmd *cobra.Command, args []string) error { func StopHandler(cmd *cobra.Command, args []string) error {
@@ -310,6 +325,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
Model: args[0], Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color", WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]any{}, Options: map[string]any{},
ShowConnect: true,
} }
format, err := cmd.Flags().GetString("format") format, err := cmd.Flags().GetString("format")
@@ -367,6 +383,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
} }
prompts = append([]string{string(in)}, prompts...) prompts = append([]string{string(in)}, prompts...)
opts.ShowConnect = false
opts.WordWrap = false opts.WordWrap = false
interactive = false interactive = false
} }
@@ -433,6 +450,21 @@ func RunHandler(cmd *cobra.Command, args []string) error {
if interactive { if interactive {
if err := loadOrUnloadModel(cmd, &opts); err != nil { if err := loadOrUnloadModel(cmd, &opts); err != nil {
var sErr api.AuthorizationError
if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
pubKey, pkErr := auth.GetPublicKey()
if pkErr != nil {
return pkErr
}
// the server and the client both have the same public key
if pubKey == sErr.PublicKey {
h, _ := os.Hostname()
encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
fmt.Printf("You need to be signed in to Ollama to run Cloud models.\n\n")
fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
}
return nil
}
return err return err
} }
@@ -453,6 +485,56 @@ func RunHandler(cmd *cobra.Command, args []string) error {
return generate(cmd, opts) return generate(cmd, opts)
} }
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 {
return err
}
if user != nil && user.Name != "" {
fmt.Printf("You are already signed in as user '%s'\n", user.Name)
fmt.Println()
return nil
}
pubKey, pkErr := auth.GetPublicKey()
if pkErr != nil {
return pkErr
}
encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
h, _ := os.Hostname()
fmt.Printf(ConnectInstructions, url.PathEscape(h), encKey)
return nil
}
func SignoutHandler(cmd *cobra.Command, args []string) error {
pubKey, pkErr := auth.GetPublicKey()
if pkErr != nil {
return pkErr
}
encKey := base64.RawURLEncoding.EncodeToString([]byte(pubKey))
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
err = client.Signout(cmd.Context(), encKey)
if err != nil {
return err
}
fmt.Println("You have signed out of ollama.com")
fmt.Println()
return nil
}
func PushHandler(cmd *cobra.Command, args []string) error { func PushHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment() client, err := api.ClientFromEnvironment()
if err != nil { if err != nil {
@@ -505,7 +587,8 @@ func PushHandler(cmd *cobra.Command, args []string) error {
if spinner != nil { if spinner != nil {
spinner.Stop() spinner.Stop()
} }
if strings.Contains(err.Error(), "access denied") { 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") return errors.New("you are not authorized to push to this namespace, create the model under a namespace you own")
} }
return err return err
@@ -539,7 +622,14 @@ func ListHandler(cmd *cobra.Command, args []string) error {
for _, m := range models.Models { for _, m := range models.Models {
if len(args) == 0 || strings.HasPrefix(strings.ToLower(m.Name), strings.ToLower(args[0])) { if len(args) == 0 || strings.HasPrefix(strings.ToLower(m.Name), strings.ToLower(args[0])) {
data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), format.HumanTime(m.ModifiedAt, "Never")}) 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")})
} }
} }
@@ -624,8 +714,8 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
KeepAlive: &api.Duration{Duration: 0}, KeepAlive: &api.Duration{Duration: 0},
} }
if err := loadOrUnloadModel(cmd, opts); err != nil { if err := loadOrUnloadModel(cmd, opts); err != nil {
if !strings.Contains(err.Error(), "not found") { if !strings.Contains(strings.ToLower(err.Error()), "not found") {
return fmt.Errorf("unable to stop existing running model \"%s\": %s", args[0], err) fmt.Fprintf(os.Stderr, "Warning: unable to stop model '%s'\n", args[0])
} }
} }
@@ -736,12 +826,36 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
} }
tableRender("Model", func() (rows [][]string) { tableRender("Model", func() (rows [][]string) {
if resp.RemoteHost != "" {
rows = append(rows, []string{"", "Remote model", resp.RemoteModel})
rows = append(rows, []string{"", "Remote URL", resp.RemoteHost})
}
if resp.ModelInfo != nil { if resp.ModelInfo != nil {
arch := resp.ModelInfo["general.architecture"].(string) arch := resp.ModelInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch}) rows = append(rows, []string{"", "architecture", arch})
rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ModelInfo["general.parameter_count"].(float64)))})
rows = append(rows, []string{"", "context length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64), 'f', -1, 64)}) var paramStr string
rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64), 'f', -1, 64)}) 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 { } else {
rows = append(rows, []string{"", "architecture", resp.Details.Family}) rows = append(rows, []string{"", "architecture", resp.Details.Family})
rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize}) rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
@@ -989,6 +1103,7 @@ type runOptions struct {
KeepAlive *api.Duration KeepAlive *api.Duration
Think *api.ThinkValue Think *api.ThinkValue
HideThinking bool HideThinking bool
ShowConnect bool
} }
type displayResponseState struct { type displayResponseState struct {
@@ -1544,6 +1659,22 @@ func NewCLI() *cobra.Command {
pushCmd.Flags().Bool("insecure", false, "Use an insecure registry") pushCmd.Flags().Bool("insecure", false, "Use an insecure registry")
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,
}
listCmd := &cobra.Command{ listCmd := &cobra.Command{
Use: "list", Use: "list",
Aliases: []string{"ls"}, Aliases: []string{"ls"},
@@ -1638,6 +1769,8 @@ func NewCLI() *cobra.Command {
stopCmd, stopCmd,
pullCmd, pullCmd,
pushCmd, pushCmd,
signinCmd,
signoutCmd,
listCmd, listCmd,
psCmd, psCmd,
copyCmd, copyCmd,

View File

@@ -3,6 +3,7 @@ package cmd
import ( import (
"bytes" "bytes"
"encoding/json" "encoding/json"
"fmt"
"io" "io"
"net/http" "net/http"
"net/http/httptest" "net/http/httptest"
@@ -304,6 +305,8 @@ func TestDeleteHandler(t *testing.T) {
w.WriteHeader(http.StatusOK) w.WriteHeader(http.StatusOK)
} else { } else {
w.WriteHeader(http.StatusNotFound) w.WriteHeader(http.StatusNotFound)
errPayload := `{"error":"model '%s' not found"}`
w.Write([]byte(fmt.Sprintf(errPayload, req.Name)))
} }
return return
} }
@@ -346,7 +349,7 @@ func TestDeleteHandler(t *testing.T) {
} }
err := DeleteHandler(cmd, []string{"test-model-not-found"}) err := DeleteHandler(cmd, []string{"test-model-not-found"})
if err == nil || !strings.Contains(err.Error(), "unable to stop existing running model \"test-model-not-found\"") { if err == nil || !strings.Contains(err.Error(), "model 'test-model-not-found' not found") {
t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err) t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err)
} }
} }
@@ -499,7 +502,7 @@ func TestPushHandler(t *testing.T) {
w.Header().Set("Content-Type", "application/json") w.Header().Set("Content-Type", "application/json")
w.WriteHeader(http.StatusUnauthorized) w.WriteHeader(http.StatusUnauthorized)
err := json.NewEncoder(w).Encode(map[string]string{ err := json.NewEncoder(w).Encode(map[string]string{
"error": "access denied", "error": "403: {\"errors\":[{\"code\":\"ACCESS DENIED\", \"message\":\"access denied\"}]}",
}) })
if err != nil { if err != nil {
t.Fatal(err) t.Fatal(err)
@@ -522,6 +525,7 @@ func TestPushHandler(t *testing.T) {
defer mockServer.Close() defer mockServer.Close()
t.Setenv("OLLAMA_HOST", mockServer.URL) t.Setenv("OLLAMA_HOST", mockServer.URL)
initializeKeypair()
cmd := &cobra.Command{} cmd := &cobra.Command{}
cmd.Flags().Bool("insecure", false, "") cmd.Flags().Bool("insecure", false, "")

View File

@@ -28,6 +28,7 @@ type bertModel struct {
LayerNormEPS float32 `json:"layer_norm_eps"` LayerNormEPS float32 `json:"layer_norm_eps"`
LayerNormEpsilon float32 `json:"layer_norm_epsilon"` LayerNormEpsilon float32 `json:"layer_norm_epsilon"`
NormEpsilon float32 `json:"norm_epsilon"` NormEpsilon float32 `json:"norm_epsilon"`
normalizeEmbeddings bool
PoolingType uint32 PoolingType uint32
} }
@@ -54,9 +55,11 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
var pooling string var pooling string
for _, m := range modules { for _, m := range modules {
if m.Type == "sentence_transformers.models.Pooling" { switch m.Type {
case "sentence_transformers.models.Pooling":
pooling = m.Path pooling = m.Path
break case "sentence_transformers.models.Normalize":
p.normalizeEmbeddings = true
} }
} }
@@ -90,6 +93,7 @@ func (p *bertModel) KV(t *Tokenizer) ggml.KV {
kv["general.architecture"] = "bert" kv["general.architecture"] = "bert"
kv["bert.attention.causal"] = false kv["bert.attention.causal"] = false
kv["bert.pooling_type"] = p.PoolingType kv["bert.pooling_type"] = p.PoolingType
kv["bert.normalize_embeddings"] = p.normalizeEmbeddings
kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer) kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)

View File

@@ -96,7 +96,7 @@ type safetensor struct {
func (st safetensor) Kind() uint32 { func (st safetensor) Kind() uint32 {
kind := st.tensorBase.Kind() kind := st.tensorBase.Kind()
if st.dtype == "BF16" && kind != tensorKindFP32 { if !strings.HasPrefix(st.name, "v.") && st.dtype == "BF16" && kind != tensorKindFP32 {
kind = tensorKindBF16 kind = tensorKindBF16
} }

View File

@@ -230,3 +230,65 @@ func TestSafetensors(t *testing.T) {
}) })
} }
} }
func TestSafetensorKind(t *testing.T) {
tests := []struct {
name string
st safetensor
expected uint32
}{
{
name: "BF16 dtype with non-v. prefix and non-FP32 base kind should return BF16",
st: safetensor{
tensorBase: &tensorBase{
name: "weight.matrix",
shape: []uint64{10, 10}, // will default to FP16
},
dtype: "BF16",
},
expected: tensorKindBF16,
},
{
name: "BF16 dtype with v. prefix should return base kind",
st: safetensor{
tensorBase: &tensorBase{
name: "v.weight.matrix",
shape: []uint64{10, 10}, // will default to FP16
},
dtype: "BF16",
},
expected: tensorKindFP16,
},
{
name: "BF16 dtype with FP32 base kind should return FP32",
st: safetensor{
tensorBase: &tensorBase{
name: "weight.matrix",
shape: []uint64{10}, // will default to FP32
},
dtype: "BF16",
},
expected: tensorKindFP32,
},
{
name: "Non-BF16 dtype should return base kind",
st: safetensor{
tensorBase: &tensorBase{
name: "weight.matrix",
shape: []uint64{10, 10}, // will default to FP16
},
dtype: "FP16",
},
expected: tensorKindFP16,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := tt.st.Kind()
if result != tt.expected {
t.Errorf("Kind() = %d, expected %d", result, tt.expected)
}
})
}
}

View File

@@ -16,7 +16,7 @@ import (
// Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices. // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
var CudaTegra string = os.Getenv("JETSON_JETPACK") var CudaTegra string = os.Getenv("JETSON_JETPACK")
func cudaVariant(gpuInfo CudaGPUInfo) string { func cudaVariant(gpuInfos []CudaGPUInfo) string {
if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" { if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" {
if CudaTegra != "" { if CudaTegra != "" {
ver := strings.Split(CudaTegra, ".") ver := strings.Split(CudaTegra, ".")
@@ -45,12 +45,19 @@ func cudaVariant(gpuInfo CudaGPUInfo) string {
} }
} }
if gpuInfo.DriverMajor < 13 { // Check GPU compute capability FIRST, lowest common denominator if multi-gpu
for _, gpuInfo := range gpuInfos {
if gpuInfo.computeMajor < 7 || (gpuInfo.computeMajor == 7 && gpuInfo.computeMinor < 5) {
// GPU is Pascal or older (CC <= 7.4) - use CUDA v12 (supports CC 6.1)
return "v12"
}
}
// GPU is Turing or newer (CC >= 7.5) - can use newer CUDA
if len(gpuInfos) > 0 && gpuInfos[0].DriverMajor < 13 {
// The detected driver is older than 580 (Aug 2025) // The detected driver is older than 580 (Aug 2025)
// Warn if their CC is compatible with v13 and they should upgrade their driver to get better performance // Warn if their CC is compatible with v13 and they should upgrade their driver to get better performance
if gpuInfo.computeMajor > 7 || (gpuInfo.computeMajor == 7 && gpuInfo.computeMinor >= 5) { slog.Warn("old CUDA driver detected - please upgrade to a newer driver for best performance", "version", fmt.Sprintf("%d.%d", gpuInfos[0].DriverMajor, gpuInfos[0].DriverMinor))
slog.Warn("old CUDA driver detected - please upgrade to a newer driver for best performance", "version", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor))
}
return "v12" return "v12"
} }
return "v13" return "v13"

View File

@@ -284,18 +284,8 @@ func GetGPUInfo() GpuInfoList {
gpuInfo.MinimumMemory = cudaMinimumMemory gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DriverMajor = driverMajor gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor gpuInfo.DriverMinor = driverMinor
variant := cudaVariant(gpuInfo)
// Start with our bundled libraries
if variant != "" {
variantPath := filepath.Join(LibOllamaPath, "cuda_"+variant)
if _, err := os.Stat(variantPath); err == nil {
// Put the variant directory first in the search path to avoid runtime linking to the wrong library
gpuInfo.DependencyPath = append([]string{variantPath}, gpuInfo.DependencyPath...)
}
}
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0]) gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.Variant = variant
if int(memInfo.major) < cudaComputeMajorMin || (int(memInfo.major) == cudaComputeMajorMin && int(memInfo.minor) < cudaComputeMinorMin) { if int(memInfo.major) < cudaComputeMajorMin || (int(memInfo.major) == cudaComputeMajorMin && int(memInfo.minor) < cudaComputeMinorMin) {
unsupportedGPUs = append(unsupportedGPUs, unsupportedGPUs = append(unsupportedGPUs,
@@ -333,6 +323,24 @@ func GetGPUInfo() GpuInfoList {
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does... // TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
cudaGPUs = append(cudaGPUs, gpuInfo) cudaGPUs = append(cudaGPUs, gpuInfo)
} }
// Second pass on NVIDIA GPUs to set lowest common denominator variant and DependencyPaths
variant := cudaVariant(cudaGPUs)
var variantPath string
// Start with our bundled libraries
if variant != "" {
variantPath = filepath.Join(LibOllamaPath, "cuda_"+variant)
if _, err := os.Stat(variantPath); err != nil {
variantPath = ""
}
}
for i := range cudaGPUs {
cudaGPUs[i].Variant = variant
if variantPath != "" {
// Put the variant directory first in the search path to avoid runtime linking to the wrong library
cudaGPUs[i].DependencyPath = append([]string{variantPath}, cudaGPUs[i].DependencyPath...)
}
}
} }
// Intel // Intel

View File

@@ -11,6 +11,10 @@ Then build and run Ollama from the root directory of the repository:
go run . serve go run . serve
``` ```
> [!NOTE]
> Ollama includes native code compiled with CGO. From time to time these data structures can change and CGO can get out of sync resulting in unexpected crashes. You can force a full build of the native code by running `go clean -cache` first.
## macOS (Apple Silicon) ## macOS (Apple Silicon)
macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required. macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required.

View File

@@ -134,6 +134,17 @@ func LoadTimeout() (loadTimeout time.Duration) {
return loadTimeout return loadTimeout
} }
func Remotes() []string {
var r []string
raw := strings.TrimSpace(Var("OLLAMA_REMOTES"))
if raw == "" {
r = []string{"ollama.com"}
} else {
r = strings.Split(raw, ",")
}
return r
}
func Bool(k string) func() bool { func Bool(k string) func() bool {
return func() bool { return func() bool {
if s := Var(k); s != "" { if s := Var(k); s != "" {
@@ -270,6 +281,7 @@ func AsMap() map[string]EnvVar {
"OLLAMA_MULTIUSER_CACHE": {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"}, "OLLAMA_MULTIUSER_CACHE": {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
"OLLAMA_CONTEXT_LENGTH": {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4096)"}, "OLLAMA_CONTEXT_LENGTH": {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4096)"},
"OLLAMA_NEW_ENGINE": {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"}, "OLLAMA_NEW_ENGINE": {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
"OLLAMA_REMOTES": {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
// Informational // Informational
"HTTP_PROXY": {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"}, "HTTP_PROXY": {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

View File

@@ -243,6 +243,7 @@ func (kv KV) OllamaEngineRequired() bool {
"gemma3", "gemma3",
"gemma3n", "gemma3n",
"mistral3", "mistral3",
"qwen3",
"llama4", "llama4",
"mllama", "mllama",
"qwen25vl", "qwen25vl",

View File

@@ -8,6 +8,7 @@ import (
"testing" "testing"
"time" "time"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
) )
@@ -44,9 +45,8 @@ func TestAllMiniLMEmbeddings(t *testing.T) {
} }
res, err := embeddingTestHelper(ctx, client, t, req) res, err := embeddingTestHelper(ctx, client, t, req)
if err != nil { if err != nil {
t.Fatalf("error: %v", err) t.Fatal(err)
} }
if len(res.Embedding) != 384 { if len(res.Embedding) != 384 {
@@ -74,9 +74,8 @@ func TestAllMiniLMEmbed(t *testing.T) {
} }
res, err := embedTestHelper(ctx, client, t, req) res, err := embedTestHelper(ctx, client, t, req)
if err != nil { if err != nil {
t.Fatalf("error: %v", err) t.Fatal(err)
} }
if len(res.Embeddings) != 1 { if len(res.Embeddings) != 1 {
@@ -112,9 +111,8 @@ func TestAllMiniLMBatchEmbed(t *testing.T) {
} }
res, err := embedTestHelper(ctx, client, t, req) res, err := embedTestHelper(ctx, client, t, req)
if err != nil { if err != nil {
t.Fatalf("error: %v", err) t.Fatal(err)
} }
if len(res.Embeddings) != 2 { if len(res.Embeddings) != 2 {
@@ -156,93 +154,135 @@ func TestAllMiniLMEmbedTruncate(t *testing.T) {
truncTrue, truncFalse := true, false truncTrue, truncFalse := true, false
type testReq struct { want, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
Name string Model: "all-minilm",
Request api.EmbedRequest Input: "why",
})
if err != nil {
t.Fatal(err)
} }
reqs := []testReq{ cases := []struct {
name string
request api.EmbedRequest
check func(*api.EmbedResponse, error)
}{
{ {
Name: "Target Truncation", name: "target truncation",
Request: api.EmbedRequest{ request: api.EmbedRequest{
Model: "all-minilm", Model: "all-minilm",
Input: "why", Input: "why",
}, },
check: func(got *api.EmbedResponse, err error) {
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
t.Errorf("embedding mismatch (-want +got):\n%s", diff)
}
},
}, },
{ {
Name: "Default Truncate", name: "default truncate",
Request: api.EmbedRequest{ request: api.EmbedRequest{
Model: "all-minilm", Model: "all-minilm",
Input: "why is the sky blue?", Input: "why is the sky blue?",
Options: map[string]any{"num_ctx": 1}, Options: map[string]any{"num_ctx": 3},
},
check: func(got *api.EmbedResponse, err error) {
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
t.Errorf("embedding mismatch (-want +got):\n%s", diff)
}
}, },
}, },
{ {
Name: "Explicit Truncate", name: "explicit truncate",
Request: api.EmbedRequest{ request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncTrue,
Options: map[string]any{"num_ctx": 3},
},
check: func(got *api.EmbedResponse, err error) {
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(want.Embeddings[0], got.Embeddings[0]); diff != "" {
t.Errorf("embedding mismatch (-want +got):\n%s", diff)
}
},
},
{
name: "truncate error",
request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncFalse,
Options: map[string]any{"num_ctx": 3},
},
check: func(res *api.EmbedResponse, err error) {
if err.Error() != "input exceeds maximum context length" {
t.Fatalf("expected truncation error, got: %v", err)
}
},
},
{
name: "input after truncate error",
request: api.EmbedRequest{
Model: "all-minilm", Model: "all-minilm",
Input: "why is the sky blue?", Input: "why is the sky blue?",
Truncate: &truncTrue, Truncate: &truncTrue,
Options: map[string]any{"num_ctx": 1}, Options: map[string]any{"num_ctx": 1},
}, },
check: func(res *api.EmbedResponse, err error) {
if err.Error() != "input after truncation exceeds maximum context length" {
t.Fatalf("expected truncation error, got: %v", err)
}
},
},
{
name: "input after truncate error",
request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncTrue,
Options: map[string]any{"num_ctx": 0},
},
check: func(res *api.EmbedResponse, err error) {
if err.Error() != "input after truncation exceeds maximum context length" {
t.Fatalf("expected truncation error, got: %v", err)
}
},
}, },
} }
res := make(map[string]*api.EmbedResponse) for _, req := range cases {
t.Run(req.name, func(t *testing.T) {
for _, req := range reqs { req.check(embedTestHelper(ctx, client, t, req.request))
response, err := embedTestHelper(ctx, client, t, req.Request)
if err != nil {
t.Fatalf("error: %v", err)
}
res[req.Name] = response
}
if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
t.Fatal("expected default request to truncate correctly")
}
if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
t.Fatal("expected default request and truncate true request to be the same")
}
// check that truncate set to false returns an error if context length is exceeded
_, err := embedTestHelper(ctx, client, t, api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncFalse,
Options: map[string]any{"num_ctx": 1},
}) })
if err == nil {
t.Fatal("expected error, got nil")
} }
} }
func embeddingTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbeddingRequest) (*api.EmbeddingResponse, error) { func embeddingTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbeddingRequest) (*api.EmbeddingResponse, error) {
t.Helper()
if err := PullIfMissing(ctx, client, req.Model); err != nil { if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("failed to pull model %s: %v", req.Model, err) t.Fatal(err)
} }
response, err := client.Embeddings(ctx, &req) return client.Embeddings(ctx, &req)
if err != nil {
return nil, err
}
return response, nil
} }
func embedTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) { func embedTestHelper(ctx context.Context, client *api.Client, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
t.Helper()
if err := PullIfMissing(ctx, client, req.Model); err != nil { if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("failed to pull model %s: %v", req.Model, err) t.Fatal(err)
} }
response, err := client.Embed(ctx, &req) return client.Embed(ctx, &req)
if err != nil {
return nil, err
}
return response, nil
} }

View File

@@ -5,6 +5,8 @@ import (
"io" "io"
"log/slog" "log/slog"
"path/filepath" "path/filepath"
"runtime"
"time"
) )
const LevelTrace slog.Level = -8 const LevelTrace slog.Level = -8
@@ -29,10 +31,18 @@ func NewLogger(w io.Writer, level slog.Level) *slog.Logger {
})) }))
} }
type key string
func Trace(msg string, args ...any) { func Trace(msg string, args ...any) {
slog.Log(context.TODO(), LevelTrace, msg, args...) TraceContext(context.WithValue(context.TODO(), key("skip"), 1), msg, args...)
} }
func TraceContext(ctx context.Context, msg string, args ...any) { func TraceContext(ctx context.Context, msg string, args ...any) {
slog.Log(ctx, LevelTrace, msg, args...) if logger := slog.Default(); logger.Enabled(ctx, LevelTrace) {
skip, _ := ctx.Value(key("skip")).(int)
pc, _, _, _ := runtime.Caller(1 + skip)
record := slog.NewRecord(time.Now(), LevelTrace, msg, pc)
record.Add(args...)
logger.Handler().Handle(ctx, record)
}
} }

View File

@@ -416,6 +416,7 @@ type Tensor interface {
AddID(ctx Context, t2, ids Tensor) Tensor AddID(ctx Context, t2, ids Tensor) Tensor
Softmax(ctx Context) Tensor Softmax(ctx Context) Tensor
L2Norm(ctx Context, eps float32) Tensor
LayerNorm(ctx Context, weight, bias Tensor, eps float32) Tensor LayerNorm(ctx Context, weight, bias Tensor, eps float32) Tensor
RMSNorm(ctx Context, weight Tensor, eps float32) Tensor RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
Scale(ctx Context, s float64) Tensor Scale(ctx Context, s float64) Tensor
@@ -429,12 +430,13 @@ type Tensor interface {
Sin(ctx Context) Tensor Sin(ctx Context) Tensor
Cos(ctx Context) Tensor Cos(ctx Context) Tensor
Tanh(ctx Context) Tensor Tanh(ctx Context) Tensor
GELU(ctx Context) Tensor GELU(ctx Context, up ...Tensor) Tensor
QuickGELU(ctx Context) Tensor SILU(ctx Context, up ...Tensor) Tensor
SILU(ctx Context) Tensor RELU(ctx Context, up ...Tensor) Tensor
RELU(ctx Context) Tensor
Sigmoid(ctx Context) Tensor Sigmoid(ctx Context) Tensor
SwiGLU(ctx Context, up Tensor, alpha, limit float32) Tensor
// AlphaLimitSILU is a variant of SILU that clamps the input to the range [-limit, limit]
SILUAlphaLimit(ctx Context, up Tensor, alpha, limit float32) Tensor
Reshape(ctx Context, shape ...int) Tensor Reshape(ctx Context, shape ...int) Tensor
View(ctx Context, offset int, shape ...int) Tensor View(ctx Context, offset int, shape ...int) Tensor

View File

@@ -1205,6 +1205,13 @@ func (t *Tensor) AddID(ctx ml.Context, t2, ids ml.Tensor) ml.Tensor {
} }
} }
func (t *Tensor) L2Norm(ctx ml.Context, eps float32) ml.Tensor {
return &Tensor{
b: t.b,
t: C.ggml_l2_norm(ctx.(*Context).ctx, t.t, C.float(eps)),
}
}
func (t *Tensor) LayerNorm(ctx ml.Context, w, b ml.Tensor, eps float32) ml.Tensor { func (t *Tensor) LayerNorm(ctx ml.Context, w, b ml.Tensor, eps float32) ml.Tensor {
tt := C.ggml_norm(ctx.(*Context).ctx, t.t, C.float(eps)) tt := C.ggml_norm(ctx.(*Context).ctx, t.t, C.float(eps))
if w != nil { if w != nil {
@@ -1424,35 +1431,46 @@ func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
} }
} }
func (t *Tensor) GELU(ctx ml.Context) ml.Tensor { func (t *Tensor) GELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
if len(t2) > 0 {
return &Tensor{
b: t.b,
t: C.ggml_geglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
}
}
return &Tensor{ return &Tensor{
b: t.b, b: t.b,
t: C.ggml_gelu_inplace(ctx.(*Context).ctx, t.t), t: C.ggml_gelu_inplace(ctx.(*Context).ctx, t.t),
} }
} }
func (t *Tensor) QuickGELU(ctx ml.Context) ml.Tensor { func (t *Tensor) SILU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
if len(t2) > 0 {
return &Tensor{ return &Tensor{
b: t.b, b: t.b,
t: C.ggml_gelu_quick_inplace(ctx.(*Context).ctx, t.t), t: C.ggml_swiglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
} }
} }
func (t *Tensor) SILU(ctx ml.Context) ml.Tensor {
return &Tensor{ return &Tensor{
b: t.b, b: t.b,
t: C.ggml_silu_inplace(ctx.(*Context).ctx, t.t), t: C.ggml_silu_inplace(ctx.(*Context).ctx, t.t),
} }
} }
func (t *Tensor) RELU(ctx ml.Context) ml.Tensor { func (t *Tensor) RELU(ctx ml.Context, t2 ...ml.Tensor) ml.Tensor {
if len(t2) > 0 {
return &Tensor{
b: t.b,
t: C.ggml_reglu_split(ctx.(*Context).ctx, t.t, t2[0].(*Tensor).t),
}
}
return &Tensor{ return &Tensor{
b: t.b, b: t.b,
t: C.ggml_relu_inplace(ctx.(*Context).ctx, t.t), t: C.ggml_relu_inplace(ctx.(*Context).ctx, t.t),
} }
} }
func (t *Tensor) SwiGLU(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor { func (t *Tensor) SILUAlphaLimit(ctx ml.Context, up ml.Tensor, alpha, limit float32) ml.Tensor {
return &Tensor{ return &Tensor{
b: t.b, b: t.b,
t: C.ggml_swiglu_oai(ctx.(*Context).ctx, t.t, up.(*Tensor).t, C.float(alpha), C.float(limit)), t: C.ggml_swiglu_oai(ctx.(*Context).ctx, t.t, up.(*Tensor).t, C.float(alpha), C.float(limit)),

View File

@@ -26,6 +26,7 @@ func Attention(ctx ml.Context, query, key, value ml.Tensor, scale float64, cache
} }
func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scale float64, cache kvcache.Cache) ml.Tensor { func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scale float64, cache kvcache.Cache) ml.Tensor {
ctx.Forward(query)
if key != nil && value != nil { if key != nil && value != nil {
if query.Dim(0) != key.Dim(0) { if query.Dim(0) != key.Dim(0) {
panic(fmt.Errorf("d_k in attention operation does not match between query(%v) and key(%v)", query.Dim(0), key.Dim(0))) panic(fmt.Errorf("d_k in attention operation does not match between query(%v) and key(%v)", query.Dim(0), key.Dim(0)))
@@ -39,6 +40,7 @@ func AttentionWithSinks(ctx ml.Context, query, key, value, sinks ml.Tensor, scal
panic(fmt.Errorf("seq_len_k in attention operation does not match between key(%v) and value(%v)", key.Dim(2), value.Dim(2))) panic(fmt.Errorf("seq_len_k in attention operation does not match between key(%v) and value(%v)", key.Dim(2), value.Dim(2)))
} }
ctx.Forward(key, value)
if cache != nil { if cache != nil {
cache.Put(ctx, key, value) cache.Put(ctx, key, value)
} }

42
ml/nn/pooling/pooling.go Normal file
View File

@@ -0,0 +1,42 @@
package pooling
import (
"github.com/ollama/ollama/ml"
)
type Type uint32
const (
TypeNone Type = iota
TypeMean
TypeCLS
TypeLast
)
func (t Type) String() string {
switch t {
case TypeMean:
return "Mean"
case TypeCLS:
return "CLS"
case TypeLast:
return "Last"
default:
return "Unknown"
}
}
func (t Type) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
switch t {
case TypeMean:
hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
return hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
case TypeCLS:
return hiddenStates.View(ctx, 0, hiddenStates.Dim(0))
case TypeLast:
hiddenStates = hiddenStates.View(ctx, (hiddenStates.Dim(1)-1)*hiddenStates.Stride(1), hiddenStates.Dim(0))
return hiddenStates
default:
panic("unknown pooling type")
}
}

View File

@@ -0,0 +1,79 @@
package pooling_test
import (
"bytes"
"os"
"slices"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/discover"
fsggml "github.com/ollama/ollama/fs/ggml"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/backend/ggml"
"github.com/ollama/ollama/ml/nn/pooling"
)
func setup(tb testing.TB, n int) ml.Backend {
tb.Helper()
f, err := os.CreateTemp(tb.TempDir(), "*.bin")
if err != nil {
tb.Fatal(err)
}
defer f.Close()
if err := fsggml.WriteGGUF(f, fsggml.KV{
"general.architecture": "test",
"test.block_count": uint32(1),
}, []*fsggml.Tensor{
{Name: "blk.0.weight", Shape: []uint64{1}, WriterTo: bytes.NewBuffer(make([]byte, 4))},
}); err != nil {
tb.Fatal(err)
}
var gpuLayers ml.GPULayersList
if gpus := discover.GetGPUInfo(); len(gpus) > 0 {
gpuLayers = append(gpuLayers, ml.GPULayers{
ID: gpus[0].ID,
Layers: slices.Collect(func(yield func(int) bool) {
for i := range n {
if !yield(i) {
return
}
}
}),
})
}
b, err := ggml.New(f.Name(), ml.BackendParams{AllocMemory: true, GPULayers: gpuLayers})
if err != nil {
tb.Fatal(err)
}
return b
}
func TestForward(t *testing.T) {
cases := map[pooling.Type][]float32{
pooling.TypeMean: {4, 5, 6, 7, 8, 9, 10, 11},
pooling.TypeCLS: {0, 1, 2, 3, 4, 5, 6, 7},
pooling.TypeLast: {8, 9, 10, 11, 12, 13, 14, 15},
}
for typ, want := range cases {
t.Run(typ.String(), func(t *testing.T) {
b := setup(t, 99)
defer b.Close()
ctx := b.NewContext()
defer ctx.Close()
tt := ctx.Input().Arange(0, 16, 1, ml.DTypeF32).Reshape(ctx, 8, 2)
tt = typ.Forward(ctx, tt)
ctx.Forward(tt).Compute(tt)
if diff := cmp.Diff(want, tt.Floats()); diff != "" {
t.Error(diff)
}
})
}
}

View File

@@ -54,10 +54,9 @@ type Batch struct {
// Inputs is the input tokens, including placeholders for multimodal inputs. // Inputs is the input tokens, including placeholders for multimodal inputs.
Inputs ml.Tensor Inputs ml.Tensor
// Multimodal is a set of multimodal embeddings previously created by // Outputs are the set of indicies into Inputs for which output data should
// EncodeMultimodal, along with an index into Inputs. Unused for text-only // be returned.
// models or for batches without multimodal elements. Outputs ml.Tensor
Multimodal []MultimodalIndex
// Positions is the position for each Input, relative to its sequence. Equal // Positions is the position for each Input, relative to its sequence. Equal
// in length to Inputs. // in length to Inputs.
@@ -66,7 +65,8 @@ type Batch struct {
// Sequences is the sequence for each Input. Equal in length to Inputs. // Sequences is the sequence for each Input. Equal in length to Inputs.
Sequences []int Sequences []int
// Outputs are the set of indicies into Inputs for which output data should // Multimodal is a set of multimodal embeddings previously created by
// be returned. // EncodeMultimodal, along with an index into Inputs. Unused for text-only
Outputs []int32 // models or for batches without multimodal elements.
Multimodal []MultimodalIndex
} }

View File

@@ -5,7 +5,6 @@ import (
"fmt" "fmt"
_ "image/jpeg" _ "image/jpeg"
_ "image/png" _ "image/png"
"math"
"os" "os"
"reflect" "reflect"
"strconv" "strconv"
@@ -21,10 +20,15 @@ import (
"github.com/ollama/ollama/logutil" "github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
_ "github.com/ollama/ollama/ml/backend" _ "github.com/ollama/ollama/ml/backend"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model/input" "github.com/ollama/ollama/model/input"
) )
var ErrNoVisionModel = errors.New("this model is missing data required for image input") var (
ErrNoVisionModel = errors.New("this model is missing data required for image input")
ErrUnsupportedModel = errors.New("model not supported")
ErrUnsupportedTokenizer = errors.New("tokenizer not supported")
)
// Model implements a specific model architecture, defining the forward pass and any model-specific configuration // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
type Model interface { type Model interface {
@@ -103,23 +107,12 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
return nil, err return nil, err
} }
arch := b.Config().Architecture() m, err := modelForArch(b.Config())
if b.Config().Uint("pooling_type", math.MaxUint32) != math.MaxUint32 {
arch = arch + "_embed"
}
f, ok := models[arch]
if !ok {
return nil, fmt.Errorf("unsupported model architecture %q", arch)
}
m, err := f(b.Config())
if err != nil { if err != nil {
return nil, err return nil, err
} }
base := Base{b: b, config: m.Config()} base := Base{b: b, config: m.Config()}
v := reflect.ValueOf(m) v := reflect.ValueOf(m)
v.Elem().Set(populateFields(base, v.Elem())) v.Elem().Set(populateFields(base, v.Elem()))
return m, nil return m, nil
@@ -131,30 +124,38 @@ func NewTextProcessor(s string) (TextProcessor, error) {
return nil, err return nil, err
} }
defer r.Close() defer r.Close()
meta, err := fsggml.Decode(r, -1) meta, err := fsggml.Decode(r, -1)
if err != nil { if err != nil {
return nil, err return nil, err
} }
return getTextProcessor(meta.KV())
}
func getTextProcessor(kv fsggml.KV) (TextProcessor, error) { m, err := modelForArch(meta.KV())
arch := kv.Architecture()
f, ok := models[arch]
if !ok {
return nil, fmt.Errorf("unsupported model architecture %q", arch)
}
m, err := f(kv)
if err != nil { if err != nil {
return nil, err return nil, err
} }
tp, ok := m.(TextProcessor) tp, ok := m.(TextProcessor)
if !ok { if !ok {
return nil, fmt.Errorf("%v is not a TextProcessor", m) return nil, ErrUnsupportedTokenizer
} }
return tp, nil return tp, nil
} }
func modelForArch(c fs.Config) (Model, error) {
arch := c.Architecture()
if pooling.Type(c.Uint("pooling_type")) != pooling.TypeNone {
arch = arch + "_embed"
}
f, ok := models[arch]
if !ok {
return nil, ErrUnsupportedModel
}
return f(c)
}
func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value { func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value {
t := v.Type() t := v.Type()
@@ -242,7 +243,7 @@ func setPointer(base Base, v reflect.Value, tags []Tag) {
vv = vv.Elem() vv = vv.Elem()
} }
vv = vv.Elem() vv = reflect.Indirect(vv)
if v.IsNil() { if v.IsNil() {
vv = reflect.New(v.Type().Elem()).Elem() vv = reflect.New(v.Type().Elem()).Elem()
} }

View File

@@ -1,9 +1,9 @@
package model package model
import ( import (
"errors"
"reflect" "reflect"
"slices" "slices"
"strings"
"testing" "testing"
"github.com/google/go-cmp/cmp" "github.com/google/go-cmp/cmp"
@@ -12,7 +12,6 @@ import (
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/backend/ggml" "github.com/ollama/ollama/ml/backend/ggml"
"github.com/ollama/ollama/ml/nn" "github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/model/input"
) )
func TestParseTags(t *testing.T) { func TestParseTags(t *testing.T) {
@@ -148,39 +147,58 @@ func TestPopulateFieldsAlternateName(t *testing.T) {
} }
} }
func TestGetTextProcessor(t *testing.T) { func TestModelForArch(t *testing.T) {
tp, err := getTextProcessor(fsggml.KV{}) type fakeModel struct {
if err == nil { Model
t.Error("expected error")
} else if !strings.Contains(err.Error(), "unsupported model architecture") {
t.Errorf("unexpected error: %v", err)
} else if tp != nil {
t.Error("expected nil tp")
} }
models["dummy"] = func(fs.Config) (Model, error) { type fakeEmbeddingModel struct {
return notTextProcessorModel{}, nil Model
}
tp, err = getTextProcessor(fsggml.KV{"general.architecture": "dummy"})
if err == nil {
t.Error("expected error")
} else if !strings.Contains(err.Error(), "not a TextProcessor") {
t.Errorf("unexpected error: %v", err)
} else if tp != nil {
t.Error("expected nil tp")
}
} }
type notTextProcessorModel struct{} models["model"] = func(c fs.Config) (Model, error) { return fakeModel{}, nil }
models["model_embed"] = func(c fs.Config) (Model, error) { return fakeEmbeddingModel{}, nil }
func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) { cases := []struct {
panic("unimplemented") name string
config fs.Config
want any
err error
}{
{
name: "model",
config: fsggml.KV{
"general.architecture": "model",
},
want: fakeModel{},
},
{
name: "embedding",
config: fsggml.KV{
"general.architecture": "model",
"model.pooling_type": uint32(1),
},
want: fakeEmbeddingModel{},
},
{
name: "unsupported",
config: fsggml.KV{
"general.architecture": "unsupported",
},
err: ErrUnsupportedModel,
},
} }
func (notTextProcessorModel) Backend() ml.Backend { for _, tt := range cases {
panic("unimplemented") t.Run(tt.name, func(t *testing.T) {
got, err := modelForArch(tt.config)
if !errors.Is(err, tt.err) {
t.Fatal(err)
} }
func (notTextProcessorModel) Config() config { if diff := cmp.Diff(tt.want, got); diff != "" {
panic("unimplemented") t.Errorf("modelForArch() returned unexpected values (-want +got):\n%s", diff)
}
})
}
} }

181
model/models/bert/embed.go Normal file
View File

@@ -0,0 +1,181 @@
package bert
import (
"cmp"
"math"
"github.com/ollama/ollama/fs"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
)
type Model struct {
model.Base
model.TextProcessor
TokenEmbedding *nn.Embedding `gguf:"token_embd"`
TypeEmbedding *nn.Embedding `gguf:"token_types"`
PositionEmbedding *nn.Embedding `gguf:"position_embd"`
TokenEmbeddingNorm *nn.LayerNorm `gguf:"token_embd_norm"`
Layers []EncoderLayer `gguf:"blk"`
Options
}
// Forward implements model.Model.
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
hiddenStates = hiddenStates.Add(ctx, m.TypeEmbedding.Weight.View(ctx, 0, m.hiddenSize))
hiddenStates = hiddenStates.Add(ctx, m.PositionEmbedding.Forward(ctx, ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))))
hiddenStates = m.TokenEmbeddingNorm.Forward(ctx, hiddenStates, m.eps)
for _, layer := range m.Layers {
hiddenStates = layer.Forward(ctx, hiddenStates, &m.Options)
}
hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
if m.normalize {
hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
}
return hiddenStates, nil
}
type EncoderLayer struct {
*Attention
AttentionNorm *nn.LayerNorm `gguf:"attn_output_norm"`
*MLP
MLPNorm *nn.LayerNorm `gguf:"layer_output_norm"`
}
func (e *EncoderLayer) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
// Attention
residual := hiddenStates
hiddenStates = e.Attention.Forward(ctx, hiddenStates, opts)
hiddenStates = hiddenStates.Add(ctx, residual)
hiddenStates = e.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
// MLP
residual = hiddenStates
hiddenStates = e.MLP.Forward(ctx, hiddenStates, opts)
hiddenStates = hiddenStates.Add(ctx, residual)
hiddenStates = e.MLPNorm.Forward(ctx, hiddenStates, opts.eps)
return hiddenStates
}
type Attention struct {
Query *nn.Linear `gguf:"attn_q"`
QueryNorm *nn.LayerNorm `gguf:"attn_q_norm"`
Key *nn.Linear `gguf:"attn_k"`
KeyNorm *nn.LayerNorm `gguf:"attn_k_norm"`
Value *nn.Linear `gguf:"attn_v"`
Output *nn.Linear `gguf:"attn_output"`
}
func (a *Attention) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
batchSize := hiddenStates.Dim(1)
query := a.Query.Forward(ctx, hiddenStates)
if a.QueryNorm != nil {
query = a.QueryNorm.Forward(ctx, query, opts.eps)
}
query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
key := a.Key.Forward(ctx, hiddenStates)
if a.KeyNorm != nil {
key = a.KeyNorm.Forward(ctx, key, opts.eps)
}
key = key.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
value := a.Value.Forward(ctx, hiddenStates)
value = value.Reshape(ctx, opts.headDim(), cmp.Or(opts.numKVHeads, opts.numHeads), batchSize)
attention := nn.Attention(ctx, query, key, value, 1/math.Sqrt(float64(opts.headDim())), nil)
attention = attention.Reshape(ctx, opts.hiddenSize, batchSize)
return a.Output.Forward(ctx, attention)
}
type MLP struct {
Up *nn.Linear `gguf:"ffn_up"`
Down *nn.Linear `gguf:"ffn_down"`
}
func (m *MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
return m.Down.Forward(ctx, m.Up.Forward(ctx, hiddenStates).GELU(ctx))
}
type Options struct {
hiddenSize,
numHeads,
numKVHeads,
keyLength,
valueLength int
poolingType pooling.Type
eps float32
normalize bool
}
func (o Options) headDim() int {
return cmp.Or(o.keyLength, o.valueLength, o.hiddenSize/o.numHeads)
}
func New(c fs.Config) (model.Model, error) {
var processor model.TextProcessor
switch c.String("tokenizer.ggml.model", "bert") {
case "bert":
processor = model.NewWordPiece(
&model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.cls_token_id"),
c.Uint("tokenizer.ggml.bos_token_id"),
)),
},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", true),
EOS: []int32{
int32(cmp.Or(
c.Uint("tokenizer.ggml.separator_token_id"),
//nolint:misspell
// NOTE: "seperator_token_id" is a typo in model metadata but we need to
// support it for compatibility.
c.Uint("tokenizer.ggml.seperator_token_id"),
c.Uint("tokenizer.ggml.eos_token_id"),
)),
},
},
)
default:
return nil, model.ErrUnsupportedTokenizer
}
return &Model{
TextProcessor: processor,
Layers: make([]EncoderLayer, c.Uint("block_count")),
Options: Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")),
eps: c.Float("attention.layer_norm_epsilon"),
poolingType: pooling.Type(c.Uint("pooling_type")),
normalize: c.Bool("normalize_embeddings", true),
},
}, nil
}
func init() {
model.Register("bert", New)
model.Register("bert_embed", New)
}

View File

@@ -24,7 +24,7 @@ type Options struct {
type Model struct { type Model struct {
model.Base model.Base
model.SentencePieceModel model.SentencePiece
TokenEmbedding *nn.Embedding `gguf:"token_embd"` TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"` Layers []Layer `gguf:"blk"`
@@ -40,7 +40,7 @@ const (
func New(c fs.Config) (model.Model, error) { func New(c fs.Config) (model.Model, error) {
m := Model{ m := Model{
SentencePieceModel: model.NewSentencePieceModel( SentencePiece: model.NewSentencePiece(
&model.Vocabulary{ &model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"), Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"), Scores: c.Floats("tokenizer.ggml.scores"),
@@ -63,7 +63,7 @@ func New(c fs.Config) (model.Model, error) {
attnValLen: int(c.Uint("attention.value_length")), attnValLen: int(c.Uint("attention.value_length")),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base", 10000.0), ropeBase: c.Float("rope.freq_base", 10000.0),
ropeScale: c.Float("rope.freq_scale", 1.0), ropeScale: c.Float("rope.scaling.factor", 1.0),
attnLogitSoftcap: c.Float("attn_logit_softcapping"), attnLogitSoftcap: c.Float("attn_logit_softcapping"),
finalLogitSoftcap: c.Float("final_logit_softcapping"), finalLogitSoftcap: c.Float("final_logit_softcapping"),
}, },
@@ -88,7 +88,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
q := sa.Query.Forward(ctx, hiddenState) q := sa.Query.Forward(ctx, hiddenState)
q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize) q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
if opts.largeModelScaling { if opts.largeModelScaling {
q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads))) q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -98,7 +98,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
k := sa.Key.Forward(ctx, hiddenState) k := sa.Key.Forward(ctx, hiddenState)
k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize) k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
v := sa.Value.Forward(ctx, hiddenState) v := sa.Value.Forward(ctx, hiddenState)
v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize) v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -128,7 +128,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
} }
func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, m.Options.ropeScale, rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, m.Options.attnKeyLen, m.Options.ropeBase, 1/m.Options.ropeScale, rope.WithTypeNeoX()), nil
} }
type MLP struct { type MLP struct {
@@ -138,7 +138,7 @@ type MLP struct {
} }
func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor { func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }
@@ -176,7 +176,6 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs) hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize))) hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
@@ -193,7 +192,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
var lastLayerOutputs ml.Tensor var lastLayerOutputs ml.Tensor
if i == len(m.Layers)-1 { if i == len(m.Layers)-1 {
lastLayerOutputs = outputs lastLayerOutputs = batch.Outputs
} }
hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, m.Cache, m.Options) hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, m.Cache, m.Options)

View File

@@ -1,49 +1,38 @@
package gemma3 package gemma3
import ( import (
"errors"
"github.com/ollama/ollama/fs" "github.com/ollama/ollama/fs"
"github.com/ollama/ollama/kvcache" "github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn" "github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model" "github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input" "github.com/ollama/ollama/model/input"
) )
type embedModel struct { type embedModel struct {
model.Base model.Base
model.SentencePieceModel model.SentencePiece
*TextModel *TextModel
PoolingType uint32 poolingType pooling.Type
Dense [2]*nn.Linear `gguf:"dense"` Dense [2]*nn.Linear `gguf:"dense"`
} }
func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
batch.Outputs = batch.Positions // return all positions
hiddenStates := m.TextModel.Forward(ctx, batch, m.Cache) hiddenStates := m.TextModel.Forward(ctx, batch, m.Cache)
hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
switch m.PoolingType {
case 0: // None
case 1: // Mean
hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
default:
return nil, errors.New("unsupported pooling type")
}
for _, dense := range m.Dense { for _, dense := range m.Dense {
hiddenStates = dense.Forward(ctx, hiddenStates) hiddenStates = dense.Forward(ctx, hiddenStates)
} }
hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
return hiddenStates, nil return hiddenStates, nil
} }
func newEmbedModel(c fs.Config) (model.Model, error) { func newEmbedModel(c fs.Config) (model.Model, error) {
m := &embedModel{ m := &embedModel{
SentencePieceModel: model.NewSentencePieceModel( SentencePiece: model.NewSentencePiece(
&model.Vocabulary{ &model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"), Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"), Scores: c.Floats("tokenizer.ggml.scores"),
@@ -61,7 +50,7 @@ func newEmbedModel(c fs.Config) (model.Model, error) {
}, },
), ),
TextModel: newTextModel(c), TextModel: newTextModel(c),
PoolingType: c.Uint("pooling_type", 0), poolingType: pooling.Type(c.Uint("pooling_type", 0)),
} }
m.Cache = kvcache.NewWrapperCache( m.Cache = kvcache.NewWrapperCache(

View File

@@ -16,7 +16,7 @@ import (
type Model struct { type Model struct {
model.Base model.Base
model.SentencePieceModel model.SentencePiece
*VisionModel `gguf:"v"` *VisionModel `gguf:"v"`
*TextModel *TextModel
@@ -55,7 +55,7 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
func New(c fs.Config) (model.Model, error) { func New(c fs.Config) (model.Model, error) {
m := Model{ m := Model{
SentencePieceModel: model.NewSentencePieceModel( SentencePiece: model.NewSentencePiece(
&model.Vocabulary{ &model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"), Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"), Scores: c.Floats("tokenizer.ggml.scores"),

View File

@@ -53,7 +53,10 @@ func newTextModel(c fs.Config) *TextModel {
eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06), eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06),
ropeLocalBase: c.Float("rope.local.freq_base", 10000.0), ropeLocalBase: c.Float("rope.local.freq_base", 10000.0),
ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0), ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
ropeScale: c.Float("rope.freq_scale", 1.0), ropeScale: 1,
// NOTE: the rope.scaling.factor is set incorrectly in the official QAT weights
// (8 instead of 1)
// ropeScale: c.Float("rope.scaling.factor", 1.0),
}, },
} }
@@ -84,7 +87,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
q := sa.Query.Forward(ctx, hiddenState) q := sa.Query.Forward(ctx, hiddenState)
q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize) q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
q = sa.QueryNorm.Forward(ctx, q, opts.eps) q = sa.QueryNorm.Forward(ctx, q, opts.eps)
q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX()) q = fast.RoPE(ctx, q, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
if opts.largeModelScaling { if opts.largeModelScaling {
q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads))) q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
@@ -95,7 +98,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
k := sa.Key.Forward(ctx, hiddenState) k := sa.Key.Forward(ctx, hiddenState)
k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize) k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
k = sa.KeyNorm.Forward(ctx, k, opts.eps) k = sa.KeyNorm.Forward(ctx, k, opts.eps)
k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, opts.ropeScale, rope.WithTypeNeoX()) k = fast.RoPE(ctx, k, positionIDs, opts.attnKeyLen, ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
v := sa.Value.Forward(ctx, hiddenState) v := sa.Value.Forward(ctx, hiddenState)
v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize) v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
@@ -113,7 +116,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
ropeBase = m.TextConfig.ropeGlobalBase ropeBase = m.TextConfig.ropeGlobalBase
} }
return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, m.TextConfig.attnKeyLen, ropeBase, 1/m.TextConfig.ropeScale, rope.WithTypeNeoX()), nil
} }
type TextMLP struct { type TextMLP struct {
@@ -123,7 +126,7 @@ type TextMLP struct {
} }
func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextConfig) ml.Tensor { func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextConfig) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }
@@ -161,7 +164,6 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cache) ml.Tensor { func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cache) ml.Tensor {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs) hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextConfig.hiddenSize))) hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextConfig.hiddenSize)))
@@ -194,7 +196,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
var lastLayerOutputs ml.Tensor var lastLayerOutputs ml.Tensor
if i == len(m.Layers)-1 { if i == len(m.Layers)-1 {
lastLayerOutputs = outputs lastLayerOutputs = batch.Outputs
} }
hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextConfig) hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextConfig)

View File

@@ -10,7 +10,7 @@ import (
type Model struct { type Model struct {
model.Base model.Base
model.SentencePieceModel model.SentencePiece
*TextModel *TextModel
} }
@@ -23,7 +23,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
func New(c fs.Config) (model.Model, error) { func New(c fs.Config) (model.Model, error) {
m := Model{ m := Model{
TextModel: newTextModel(c), TextModel: newTextModel(c),
SentencePieceModel: model.NewSentencePieceModel( SentencePiece: model.NewSentencePiece(
&model.Vocabulary{ &model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"), Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"), Scores: c.Floats("tokenizer.ggml.scores"),

View File

@@ -83,7 +83,7 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
hiddenStates = hiddenStates.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx).Mean(ctx) hiddenStates = hiddenStates.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx).Mean(ctx)
hiddenStates = hiddenStates.Permute(ctx, 2, 0, 1, 3).Contiguous(ctx) hiddenStates = hiddenStates.Permute(ctx, 2, 0, 1, 3).Contiguous(ctx)
hiddenStates = hiddenStates.Rows(ctx, ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))) hiddenStates = hiddenStates.Rows(ctx, batch.Outputs)
hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps) hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps)
return m.Output.Forward(ctx, hiddenStates), nil return m.Output.Forward(ctx, hiddenStates), nil
@@ -95,7 +95,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
ropeBase = m.ropeBaseLocal ropeBase = m.ropeBaseLocal
} }
return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
} }
type TextScaledWordEmbedding struct { type TextScaledWordEmbedding struct {
@@ -170,8 +170,7 @@ func (d TextLayer) Forward(ctx ml.Context, hiddenStates, perLayerInput, position
} }
active = d.PerLayerInputGate.Forward(ctx, active) active = d.PerLayerInputGate.Forward(ctx, active)
active = active.GELU(ctx) active = active.GELU(ctx, perLayerInput)
active = active.Mul(ctx, perLayerInput)
active = d.PerLayerProjection.Forward(ctx, active) active = d.PerLayerProjection.Forward(ctx, active)
active = d.PostPerLayerNorm.Forward(ctx, active, opts.eps) active = d.PostPerLayerNorm.Forward(ctx, active, opts.eps)
@@ -257,14 +256,14 @@ func (attn TextAttention) Forward(ctx ml.Context, hiddenStates, positions ml.Ten
query := attn.Query.Forward(ctx, hiddenStates) query := attn.Query.Forward(ctx, hiddenStates)
query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize) query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
query = attn.QueryNorm.Forward(ctx, query, opts.eps) query = attn.QueryNorm.Forward(ctx, query, opts.eps)
query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX()) query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
var key, value ml.Tensor var key, value ml.Tensor
if !sharedKV { if !sharedKV {
key = attn.Key.Forward(ctx, hiddenStates) key = attn.Key.Forward(ctx, hiddenStates)
key = key.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize) key = key.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
key = attn.KeyNorm.Forward(ctx, key, opts.eps) key = attn.KeyNorm.Forward(ctx, key, opts.eps)
key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, opts.ropeScale, rope.WithTypeNeoX()) key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
value = attn.Value.Forward(ctx, hiddenStates) value = attn.Value.Forward(ctx, hiddenStates)
value = value.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize) value = value.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
@@ -292,7 +291,7 @@ func (mlp TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, activationSpa
hiddenStates = hiddenStates.Sub(ctx, cutoff).RELU(ctx) hiddenStates = hiddenStates.Sub(ctx, cutoff).RELU(ctx)
} }
hiddenStates = hiddenStates.GELU(ctx).Mul(ctx, upStates) hiddenStates = hiddenStates.GELU(ctx, upStates)
hiddenStates = mlp.Down.Forward(ctx, hiddenStates) hiddenStates = mlp.Down.Forward(ctx, hiddenStates)
return hiddenStates return hiddenStates
} }
@@ -350,7 +349,7 @@ func newTextModel(c fs.Config) *TextModel {
eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06), eps: c.Float("attention.layer_norm_rms_epsilon", 1e-06),
ropeBase: c.Float("rope.freq_base", 1_000_000), ropeBase: c.Float("rope.freq_base", 1_000_000),
ropeBaseLocal: c.Float("rope.freq_base_local", 10_000), ropeBaseLocal: c.Float("rope.freq_base_local", 10_000),
ropeScale: c.Float("rope.freq_scale", 1.0), ropeScale: c.Float("rope.scaling.factor", 1.0),
slidingWindowPattern: c.Bools("attention.sliding_window_pattern"), slidingWindowPattern: c.Bools("attention.sliding_window_pattern"),
activationSparsityScale: c.Floats("activation_sparsity_scale"), activationSparsityScale: c.Floats("activation_sparsity_scale"),

View File

@@ -41,8 +41,8 @@ func (m *Transformer) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, err
} }
var outputs ml.Tensor var outputs ml.Tensor
if len(batch.Outputs) > 0 && i == len(m.TransformerBlocks)-1 { if i == len(m.TransformerBlocks)-1 {
outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)) outputs = batch.Outputs
} }
hiddenStates = block.Forward(ctx, hiddenStates, positions, outputs, one, m.Cache, &m.Options) hiddenStates = block.Forward(ctx, hiddenStates, positions, outputs, one, m.Cache, &m.Options)
@@ -210,7 +210,7 @@ func (mlp *MLPBlock) Forward(ctx ml.Context, hiddenStates, one ml.Tensor, opts *
up = mlp.Up.Forward(ctx, hiddenStates, selectedExperts) up = mlp.Up.Forward(ctx, hiddenStates, selectedExperts)
} }
hiddenStates = gate.SwiGLU(ctx, up, 1.702, 7) hiddenStates = gate.SILUAlphaLimit(ctx, up, 1.702, 7)
experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts) experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
experts = experts.Mul(ctx, routingWeights) experts = experts.Mul(ctx, routingWeights)

View File

@@ -2,7 +2,6 @@ package llama
import ( import (
"cmp" "cmp"
"fmt"
"math" "math"
"github.com/ollama/ollama/fs" "github.com/ollama/ollama/fs"
@@ -23,30 +22,26 @@ type Options struct {
type Model struct { type Model struct {
model.Base model.Base
model.BytePairEncoding model.TextProcessor
TokenEmbedding *nn.Embedding `gguf:"token_embd"` TokenEmbedding *nn.Embedding `gguf:"token_embd"`
Layers []Layer `gguf:"blk"` Layers []Layer `gguf:"blk"`
OutputNorm *nn.RMSNorm `gguf:"output_norm"` OutputNorm *nn.RMSNorm `gguf:"output_norm"`
Output *nn.Linear `gguf:"output,alt:token_embd"` Output *nn.Linear `gguf:"output,alt:token_embd"`
*Options Options
} }
func New(c fs.Config) (model.Model, error) { func New(c fs.Config) (model.Model, error) {
// This model currently only supports the gpt2 tokenizer if c.Uint("expert_count") > 0 {
if c.String("tokenizer.ggml.model") == "llama" { // TODO: support mixtures of experts
return nil, fmt.Errorf("unsupported tokenizer: llama") return nil, model.ErrUnsupportedModel
} }
// Best effort detection of library/deepseek-coder model(s) which are incompatible
if c.String("general.name") == "deepseek-ai" { var processor model.TextProcessor
return nil, fmt.Errorf("unsupported model: %s", c.String("general.name")) vocabulary := model.Vocabulary{
}
m := Model{
BytePairEncoding: model.NewBytePairEncoding(
c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
&model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"), Values: c.Strings("tokenizer.ggml.tokens"),
Scores: c.Floats("tokenizer.ggml.scores"),
Types: c.Ints("tokenizer.ggml.token_type"), Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"), Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true), AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
@@ -56,18 +51,31 @@ func New(c fs.Config) (model.Model, error) {
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))}, []int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")..., c.Ints("tokenizer.ggml.eos_token_ids")...,
), ),
}, }
), switch c.String("tokenizer.ggml.model") {
case "gpt2":
processor = model.NewBytePairEncoding(
`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
&vocabulary,
)
case "llama":
processor = model.NewSentencePiece(&vocabulary)
default:
return nil, model.ErrUnsupportedTokenizer
}
m := Model{
TextProcessor: processor,
Layers: make([]Layer, c.Uint("block_count")), Layers: make([]Layer, c.Uint("block_count")),
Options: &Options{ Options: Options{
hiddenSize: int(c.Uint("embedding_length")), hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")), numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")), numKVHeads: int(c.Uint("attention.head_count_kv")),
headDim: int(c.Uint("attention.key_length")), headDim: int(c.Uint("attention.key_length")),
ropeDim: int(c.Uint("rope.dimension_count")), ropeDim: int(c.Uint("rope.dimension_count")),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base", 1e5),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
}, },
} }
@@ -98,8 +106,8 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
value := sa.Value.Forward(ctx, hiddenState) value := sa.Value.Forward(ctx, hiddenState)
value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize) value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache) attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize) attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -108,7 +116,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.Tenso
func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads) ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].SelfAttention.RopeFactors)), nil
} }
type MLP struct { type MLP struct {
@@ -118,7 +126,7 @@ type MLP struct {
} }
func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor { func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }
@@ -160,10 +168,10 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
var outputs ml.Tensor var outputs ml.Tensor
if i == len(m.Layers)-1 { if i == len(m.Layers)-1 {
outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)) outputs = batch.Outputs
} }
hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, m.Options) hiddenState = layer.Forward(ctx, hiddenState, positions, outputs, m.Cache, &m.Options)
} }
hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps) hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)

View File

@@ -176,9 +176,7 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)) return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
} }
func init() { func init() {

View File

@@ -33,8 +33,8 @@ func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, positions, attent
value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize) value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
if useRope { if useRope {
query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
} }
if opts.useQKNorm { if opts.useQKNorm {
@@ -58,14 +58,14 @@ type TextMLP struct {
} }
func (mlp *TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor { func (mlp *TextMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates)) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }
type TextExperts struct { type TextExperts struct {
Gate *nn.Linear `gguf:"ffn_gate_exps"` Gate *nn.LinearBatch `gguf:"ffn_gate_exps"`
Up *nn.Linear `gguf:"ffn_up_exps"` Up *nn.LinearBatch `gguf:"ffn_up_exps"`
Down *nn.Linear `gguf:"ffn_down_exps"` Down *nn.LinearBatch `gguf:"ffn_down_exps"`
} }
func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tensor, opts *TextOptions) ml.Tensor { func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tensor, opts *TextOptions) ml.Tensor {
@@ -76,9 +76,9 @@ func (e *TextExperts) Forward(ctx ml.Context, hiddenStates, routerLogits ml.Tens
hiddenStates = hiddenStates.Repeat(ctx, 1, opts.numExpertsUsed) hiddenStates = hiddenStates.Repeat(ctx, 1, opts.numExpertsUsed)
hiddenStates = hiddenStates.Mul(ctx, scores) hiddenStates = hiddenStates.Mul(ctx, scores)
upStates := e.Up.Weight.MulmatID(ctx, hiddenStates, experts) upStates := e.Up.Forward(ctx, hiddenStates, experts)
gateStates := e.Gate.Weight.MulmatID(ctx, hiddenStates, experts) gateStates := e.Gate.Forward(ctx, hiddenStates, experts)
downStates := e.Down.Weight.MulmatID(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts) downStates := e.Down.Forward(ctx, upStates.Mul(ctx, gateStates.SILU(ctx)), experts)
nextStates := downStates.View(ctx, 0, hiddenStates.Dim(0), downStates.Stride(2), hiddenStates.Dim(2)) nextStates := downStates.View(ctx, 0, hiddenStates.Dim(0), downStates.Stride(2), hiddenStates.Dim(2))
for i := 1; i < opts.numExpertsUsed; i++ { for i := 1; i < opts.numExpertsUsed; i++ {
@@ -96,7 +96,7 @@ type TextSharedExpert struct {
} }
func (mlp *TextSharedExpert) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor { func (mlp *TextSharedExpert) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *TextOptions) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates)) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }
@@ -196,7 +196,7 @@ func newTextModel(c fs.Config) *TextModel {
numExpertsUsed: int(c.Uint("expert_used_count")), numExpertsUsed: int(c.Uint("expert_used_count")),
ropeDim: int(c.Uint("rope.dimension_count")), ropeDim: int(c.Uint("rope.dimension_count")),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
interleaveLayerStep: int(c.Uint("interleave_moe_layer_step", 1)), interleaveLayerStep: int(c.Uint("interleave_moe_layer_step", 1)),
noRopeInterval: int(c.Uint("no_rope_interval", 4)), noRopeInterval: int(c.Uint("no_rope_interval", 4)),
@@ -248,5 +248,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
} }
func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(m.Layers[layer].Attention.RopeFactors)), nil
} }

View File

@@ -159,9 +159,8 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache), nil
} }
func init() { func init() {

View File

@@ -40,11 +40,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
q := sa.Query.Forward(ctx, hiddenState) q := sa.Query.Forward(ctx, hiddenState)
q = q.Reshape(ctx, headDim, opts.numHeads, batchSize) q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale) q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
k := sa.Key.Forward(ctx, hiddenState) k := sa.Key.Forward(ctx, hiddenState)
k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize) k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale) k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale)
v := sa.Value.Forward(ctx, hiddenState) v := sa.Value.Forward(ctx, hiddenState)
v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize) v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -55,7 +55,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
} }
func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale), nil return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale), nil
} }
type MLP struct { type MLP struct {
@@ -65,7 +65,7 @@ type MLP struct {
} }
func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor { func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }
@@ -132,7 +132,7 @@ func newTextModel(c fs.Config) *TextModel {
ropeDim: int(c.Uint("rope.dimension_count")), ropeDim: int(c.Uint("rope.dimension_count")),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
}, },
} }
} }

View File

@@ -51,7 +51,7 @@ type VisionMLP struct {
} }
func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor { func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates)) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }

View File

@@ -107,10 +107,9 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
} }
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
// TODO: attention mask, cross attention mask // TODO: attention mask, cross attention mask
return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
} }
func init() { func init() {

View File

@@ -26,11 +26,11 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
query := sa.Query.Forward(ctx, hiddenState) query := sa.Query.Forward(ctx, hiddenState)
query = query.Reshape(ctx, headDim, opts.numHeads, batchSize) query = query.Reshape(ctx, headDim, opts.numHeads, batchSize)
query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) query = fast.RoPE(ctx, query, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
key := sa.Key.Forward(ctx, hiddenState) key := sa.Key.Forward(ctx, hiddenState)
key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize) key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithFactors(sa.RopeFactors)) key = fast.RoPE(ctx, key, positions, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithFactors(sa.RopeFactors))
value := sa.Value.Forward(ctx, hiddenState) value := sa.Value.Forward(ctx, hiddenState)
value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize) value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -45,7 +45,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions ml.T
func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
// This will only get called for layers in the cache, which are just the self attention layers // This will only get called for layers in the cache, which are just the self attention layers
if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok { if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok {
return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithFactors(sa.SelfAttention.RopeFactors)), nil
} }
return key, nil return key, nil
@@ -58,7 +58,7 @@ type TextMLP struct {
} }
func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextModelOptions) ml.Tensor { func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextModelOptions) ml.Tensor {
hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }
@@ -244,7 +244,7 @@ func newTextModel(c fs.Config) *TextModel {
ropeDim: int(c.Uint("rope.dimension_count")), ropeDim: int(c.Uint("rope.dimension_count")),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
crossAttentionLayers: c.Ints("attention.cross_attention_layers"), crossAttentionLayers: c.Ints("attention.cross_attention_layers"),
}, },
} }

View File

@@ -1,6 +1,7 @@
package models package models
import ( import (
_ "github.com/ollama/ollama/model/models/bert"
_ "github.com/ollama/ollama/model/models/gemma2" _ "github.com/ollama/ollama/model/models/gemma2"
_ "github.com/ollama/ollama/model/models/gemma3" _ "github.com/ollama/ollama/model/models/gemma3"
_ "github.com/ollama/ollama/model/models/gemma3n" _ "github.com/ollama/ollama/model/models/gemma3n"

View File

@@ -43,8 +43,8 @@ func (attn Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
value := attn.Value.Forward(ctx, hiddenStates) value := attn.Value.Forward(ctx, hiddenStates)
value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize) value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) query = fast.RoPE(ctx, query, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) key = fast.RoPE(ctx, key, positions, ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache) attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), cache)
attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize) attention = attention.Reshape(ctx, headDim*opts.numHeads, batchSize)
@@ -59,7 +59,7 @@ type MLP struct {
} }
func (mlp MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor { func (mlp MLP) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates)) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }
@@ -111,7 +111,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
var outputs ml.Tensor var outputs ml.Tensor
if i == len(m.Layers)-1 { if i == len(m.Layers)-1 {
outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)) outputs = batch.Outputs
} }
hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, &m.Options) hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, &m.Options)
@@ -124,7 +124,7 @@ func (m Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
func (m Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads) ropeDim := cmp.Or(m.ropeDim, m.hiddenSize/m.numHeads)
return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
} }
func New(c fs.Config) (model.Model, error) { func New(c fs.Config) (model.Model, error) {
@@ -160,7 +160,7 @@ func New(c fs.Config) (model.Model, error) {
headDim: int(c.Uint("attention.key_length")), headDim: int(c.Uint("attention.key_length")),
ropeDim: int(c.Uint("rope.dimension_count")), ropeDim: int(c.Uint("rope.dimension_count")),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
}, },
} }

View File

@@ -140,9 +140,8 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
outputs := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache) return m.TextModel.Forward(ctx, batch.Inputs, positions, batch.Outputs, batch, m.Cache)
} }
func init() { func init() {

View File

@@ -38,7 +38,7 @@ func NewTextModel(c fs.Config) *TextModel {
originalContextLength: int(c.Uint("context_length", 128000)), originalContextLength: int(c.Uint("context_length", 128000)),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
}, },
} }
@@ -60,11 +60,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
q := sa.Query.Forward(ctx, hiddenState) q := sa.Query.Forward(ctx, hiddenState)
q = q.Reshape(ctx, headDim, opts.numHeads, batchSize) q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX()) q = fast.RoPE(ctx, q, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
k := sa.Key.Forward(ctx, hiddenState) k := sa.Key.Forward(ctx, hiddenState)
k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize) k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX()) k = fast.RoPE(ctx, k, positionIDs, opts.ropeDim, opts.ropeBase, 1./opts.ropeScale, rope.WithOriginalContextLength(opts.originalContextLength), rope.WithTypeNeoX())
v := sa.Value.Forward(ctx, hiddenState) v := sa.Value.Forward(ctx, hiddenState)
v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize) v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -78,7 +78,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
// Shift applies rotary position embeddings to the key tensor for causal attention caching // Shift applies rotary position embeddings to the key tensor for causal attention caching
func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, m.ropeDim, m.ropeBase, 1./m.ropeScale, rope.WithOriginalContextLength(m.originalContextLength), rope.WithTypeNeoX()), nil
} }
// MLP implements the feed-forward network component with SwiGLU activation // MLP implements the feed-forward network component with SwiGLU activation
@@ -90,7 +90,7 @@ type MLP struct {
func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor { func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
// Apply SwiGLU activation gating // Apply SwiGLU activation gating
hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState)) hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx, mlp.Up.Forward(ctx, hiddenState))
// Project back to hidden dimension // Project back to hidden dimension
return mlp.Down.Forward(ctx, hiddenState) return mlp.Down.Forward(ctx, hiddenState)
} }

View File

@@ -100,8 +100,7 @@ type VisionMLP struct {
func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor { func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
// Using activation as specified in config (likely GELU or SiLU/Swish) // Using activation as specified in config (likely GELU or SiLU/Swish)
gateOutput := mlp.Gate.Forward(ctx, hiddenStates) gateOutput := mlp.Gate.Forward(ctx, hiddenStates)
upOutput := mlp.Up.Forward(ctx, hiddenStates) hiddenStates = gateOutput.SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
hiddenStates = gateOutput.SILU(ctx).Mul(ctx, upOutput)
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }

View File

@@ -0,0 +1,73 @@
package qwen3
import (
"github.com/ollama/ollama/fs"
"github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input"
)
type embedModel struct {
model.Base
model.BytePairEncoding
*Model
poolingType pooling.Type
}
func (m *embedModel) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
hiddenStates, err := m.forward(ctx, batch)
if err != nil {
return nil, err
}
hiddenStates = m.poolingType.Forward(ctx, hiddenStates)
hiddenStates = hiddenStates.L2Norm(ctx, 1e-12)
return hiddenStates, nil
}
func newEmbed(c fs.Config) (model.Model, error) {
layers := make([]Layer, c.Uint("block_count"))
for i := range layers {
layers[i].MLP = &dense{}
}
m := embedModel{
BytePairEncoding: model.NewBytePairEncoding(
`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
&model.Vocabulary{
Values: c.Strings("tokenizer.ggml.tokens"),
Types: c.Ints("tokenizer.ggml.token_type"),
Merges: c.Strings("tokenizer.ggml.merges"),
AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
BOS: []int32{int32(c.Uint("tokenizer.ggml.bos_token_id"))},
AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
EOS: append(
[]int32{int32(c.Uint("tokenizer.ggml.eos_token_id"))},
c.Ints("tokenizer.ggml.eos_token_ids")...,
),
},
),
Model: &Model{
Layers: layers,
Options: &Options{
hiddenSize: int(c.Uint("embedding_length")),
numHeads: int(c.Uint("attention.head_count")),
numKVHeads: int(c.Uint("attention.head_count_kv")),
keyLength: int(c.Uint("attention.key_length")),
valueLength: int(c.Uint("attention.value_length")),
eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1),
numExperts: int(c.Uint("expert_count")),
numExpertsUsed: int(c.Uint("expert_used_count")),
normTopKProb: c.Bool("norm_top_k_prob", true),
},
},
poolingType: pooling.Type(c.Uint("pooling_type")),
}
m.Cache = kvcache.NewCausalCache(m.Shift)
return &m, nil
}

View File

@@ -30,10 +30,10 @@ func (o Options) headDim() int {
} }
type Attention struct { type Attention struct {
QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
Query *nn.Linear `gguf:"attn_q"` Query *nn.Linear `gguf:"attn_q"`
KeyNorm *nn.RMSNorm `gguf:"attn_k_norm"` QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
Key *nn.Linear `gguf:"attn_k"` Key *nn.Linear `gguf:"attn_k"`
KeyNorm *nn.RMSNorm `gguf:"attn_k_norm"`
Value *nn.Linear `gguf:"attn_v"` Value *nn.Linear `gguf:"attn_v"`
Output *nn.Linear `gguf:"attn_output"` Output *nn.Linear `gguf:"attn_output"`
} }
@@ -52,8 +52,8 @@ func (sa *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor,
query = sa.QueryNorm.Forward(ctx, query, opts.eps) query = sa.QueryNorm.Forward(ctx, query, opts.eps)
key = sa.KeyNorm.Forward(ctx, key, opts.eps) key = sa.KeyNorm.Forward(ctx, key, opts.eps)
query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) query = fast.RoPE(ctx, query, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, opts.ropeScale, rope.WithTypeNeoX()) key = fast.RoPE(ctx, key, positions, opts.headDim(), opts.ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache) attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache)
attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize) attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize)
@@ -66,9 +66,9 @@ type MLP interface {
type sparse struct { type sparse struct {
Router *nn.Linear `gguf:"ffn_gate_inp"` Router *nn.Linear `gguf:"ffn_gate_inp"`
Gate *nn.Linear `gguf:"ffn_gate_exps"` Gate *nn.LinearBatch `gguf:"ffn_gate_exps"`
Up *nn.Linear `gguf:"ffn_up_exps"` Up *nn.LinearBatch `gguf:"ffn_up_exps"`
Down *nn.Linear `gguf:"ffn_down_exps"` Down *nn.LinearBatch `gguf:"ffn_down_exps"`
} }
func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor { func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options) ml.Tensor {
@@ -87,13 +87,9 @@ func (mlp *sparse) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Options
hiddenStates = hiddenStates.Reshape(ctx, hiddenStates.Dim(0), 1, hiddenStates.Dim(1)) hiddenStates = hiddenStates.Reshape(ctx, hiddenStates.Dim(0), 1, hiddenStates.Dim(1))
upStates := mlp.Up.Weight.MulmatID(ctx, hiddenStates, selectedExperts) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates, selectedExperts).SILU(ctx, mlp.Up.Forward(ctx, hiddenStates, selectedExperts))
hiddenStates = mlp.Gate.Weight.MulmatID(ctx, hiddenStates, selectedExperts) experts := mlp.Down.Forward(ctx, hiddenStates, selectedExperts)
hiddenStates = hiddenStates.SILU(ctx)
hiddenStates = hiddenStates.Mul(ctx, upStates)
experts := mlp.Down.Weight.MulmatID(ctx, hiddenStates, selectedExperts)
experts = experts.Mul(ctx, routingWeights) experts = experts.Mul(ctx, routingWeights)
nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2)) nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2))
@@ -111,7 +107,8 @@ type dense struct {
} }
func (mlp *dense) Forward(ctx ml.Context, hiddenStates ml.Tensor, _ *Options) ml.Tensor { func (mlp *dense) Forward(ctx ml.Context, hiddenStates ml.Tensor, _ *Options) ml.Tensor {
hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates)) hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).
SILU(ctx, mlp.Up.Forward(ctx, hiddenStates))
return mlp.Down.Forward(ctx, hiddenStates) return mlp.Down.Forward(ctx, hiddenStates)
} }
@@ -154,29 +151,39 @@ type Model struct {
*Options *Options
} }
// Forward implements model.Model.
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
hiddenStates, err := m.forward(ctx, batch)
if err != nil {
return nil, err
}
return m.Output.Forward(ctx, hiddenStates), nil
}
// Forward implements model.Model.
func (m *Model) forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions)) positions := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs) hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
for i, layer := range m.Layers { for i, layer := range m.Layers {
if m.Cache != nil {
m.Cache.SetLayer(i) m.Cache.SetLayer(i)
}
var outputs ml.Tensor var outputs ml.Tensor
if i == len(m.Layers)-1 { if i == len(m.Layers)-1 {
outputs = ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs)) outputs = batch.Outputs
} }
hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options) hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options)
} }
hiddenStates = m.OutputNorm.Forward(ctx, hiddenStates, m.eps) return m.OutputNorm.Forward(ctx, hiddenStates, m.eps), nil
return m.Output.Forward(ctx, hiddenStates), nil
} }
func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, m.ropeScale, rope.WithTypeNeoX()), nil return fast.RoPE(ctx, key, shift, m.headDim(), m.ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
} }
var _ model.Model = (*Model)(nil) var _ model.Model = (*Model)(nil)
@@ -216,7 +223,7 @@ func New(c fs.Config) (model.Model, error) {
valueLength: int(c.Uint("attention.value_length")), valueLength: int(c.Uint("attention.value_length")),
eps: c.Float("attention.layer_norm_rms_epsilon"), eps: c.Float("attention.layer_norm_rms_epsilon"),
ropeBase: c.Float("rope.freq_base"), ropeBase: c.Float("rope.freq_base"),
ropeScale: c.Float("rope.freq_scale", 1), ropeScale: c.Float("rope.scaling.factor", 1),
numExperts: int(c.Uint("expert_count")), numExperts: int(c.Uint("expert_count")),
numExpertsUsed: int(c.Uint("expert_used_count")), numExpertsUsed: int(c.Uint("expert_used_count")),
normTopKProb: c.Bool("norm_top_k_prob", true), normTopKProb: c.Bool("norm_top_k_prob", true),
@@ -230,4 +237,5 @@ func New(c fs.Config) (model.Model, error) {
func init() { func init() {
model.Register("qwen3", New) model.Register("qwen3", New)
model.Register("qwen3moe", New) model.Register("qwen3moe", New)
model.Register("qwen3_embed", newEmbed)
} }

37
model/parsers/parsers.go Normal file
View File

@@ -0,0 +1,37 @@
package parsers
import (
"github.com/ollama/ollama/api"
)
type Parser interface {
Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error)
HasToolSupport() bool
HasThinkingSupport() bool
}
func ParserForName(name string) Parser {
switch name {
case "qwen3-coder":
parser := &Qwen3CoderParser{}
return parser
case "passthrough":
return &PassthroughParser{}
default:
return nil
}
}
type PassthroughParser struct{}
func (p *PassthroughParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
return s, "", nil, nil
}
func (p *PassthroughParser) HasToolSupport() bool {
return false
}
func (p *PassthroughParser) HasThinkingSupport() bool {
return false
}

447
model/parsers/qwen3coder.go Normal file
View File

@@ -0,0 +1,447 @@
package parsers
import (
"context"
"encoding/json"
"encoding/xml"
"fmt"
"log/slog"
"math"
"regexp"
"strconv"
"strings"
"unicode"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/logutil"
)
type qwenParserState int
const (
toolOpenTag = "<tool_call>"
toolCloseTag = "</tool_call>"
)
const (
qwenParserState_LookingForToolStart qwenParserState = iota
qwenParserState_CollectingToolContent
)
type Qwen3CoderParser struct {
state qwenParserState
acc strings.Builder
}
func (p *Qwen3CoderParser) HasToolSupport() bool {
return true
}
func (p *Qwen3CoderParser) HasThinkingSupport() bool {
return false
}
func (p *Qwen3CoderParser) Add(s string, tools []api.Tool) (content string, thinking string, calls []api.ToolCall, err error) {
p.acc.WriteString(s)
events := p.parseEvents()
var toolCalls []api.ToolCall
var sb strings.Builder
for _, event := range events {
switch event := event.(type) {
case qwenEventRawToolCall:
toolCall, err := parseToolCall(event, tools)
if err != nil {
slog.Warn("qwen tool call parsing failed", "error", err)
return "", "", nil, err
}
toolCalls = append(toolCalls, toolCall)
case qwenEventContent:
// TODO(drifkin): if the same turn contains multiple interleaved content
// events, we naively append them together here. See the note below about
// `qwenEvent`s for more details
sb.WriteString(event.content)
}
}
return sb.String(), "", toolCalls, nil
}
func (p *Qwen3CoderParser) parseEvents() []qwenEvent {
var all []qwenEvent
keepLooping := true
for keepLooping {
var events []qwenEvent
events, keepLooping = eat(p)
if len(events) > 0 {
all = append(all, events...)
}
}
if len(all) > 0 {
slog.Log(context.TODO(), logutil.LevelTrace, "qwen events parsed", "events", all, "state", p.state, "acc", p.acc.String())
}
return all
}
// we use some internal event types in order to communicate between `Add` and
// `eat`. We do this to support interleaving content and parallel tool calls in
// the parser, even though qwen3-coder isn't supposed to do this. Our API
// doesn't currently support models outputting multiple messages in a turn, so
// we wouldn't be able to represent it yet, but there's no reason to prevent the
// parser from supporting it, especially for future models if they end up using
// a similar format.
type qwenEvent interface {
isQwenEvent()
}
type qwenEventRawToolCall struct {
raw string
}
type qwenEventContent struct {
content string
}
func (qwenEventContent) isQwenEvent() {}
func (qwenEventRawToolCall) isQwenEvent() {}
// eat consumes the parser's buffer, and returns a list of any unambiguous
// events from the current parser state. If the parser transitions to another
// state, it may have additional events to emit on the next call, which is what
// the second return value indicates
func eat(p *Qwen3CoderParser) ([]qwenEvent, bool) {
var events []qwenEvent
switch p.state {
case qwenParserState_LookingForToolStart:
if strings.Contains(p.acc.String(), toolOpenTag) {
// we found a full tool open tag, so we can emit the content before the
// tag, being sure to trim any trailing whitespace
split := strings.SplitN(p.acc.String(), toolOpenTag, 2)
before := split[0]
before = strings.TrimRightFunc(before, unicode.IsSpace)
if len(before) > 0 {
events = append(events, qwenEventContent{content: before})
}
after := split[1]
p.acc.Reset()
p.acc.WriteString(after)
p.state = qwenParserState_CollectingToolContent
return events, true
} else if overlap := overlap(p.acc.String(), toolOpenTag); overlap > 0 {
// we found a partial tool open tag, so we can emit the unambiguous part,
// which is the (trailing-whitespace trimmed) content before the partial
// tool open tag
beforePartialTag := p.acc.String()[:len(p.acc.String())-overlap]
trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
unambiguous := p.acc.String()[:ambiguousStart]
ambiguous := p.acc.String()[ambiguousStart:]
p.acc.Reset()
p.acc.WriteString(ambiguous)
events = append(events, qwenEventContent{content: unambiguous})
return events, false
} else {
// we found content that is entirely not a tool call. We should withhold
// any trailing whitespace in case this is the end of the content
whitespaceLen := trailingWhitespaceLen(p.acc.String())
ambiguousStart := len(p.acc.String()) - whitespaceLen
unambiguous := p.acc.String()[:ambiguousStart]
ambiguous := p.acc.String()[ambiguousStart:]
p.acc.Reset()
p.acc.WriteString(ambiguous)
if len(unambiguous) > 0 {
events = append(events, qwenEventContent{content: unambiguous})
}
return events, false
}
case qwenParserState_CollectingToolContent:
if strings.Contains(p.acc.String(), toolCloseTag) {
split := strings.SplitN(p.acc.String(), toolCloseTag, 2)
before := split[0]
if len(before) == 0 {
slog.Warn("qwen tool call closing tag found but no content before it")
}
// remove any whitespace between the tool call and any content after it
after := strings.TrimLeftFunc(split[1], unicode.IsSpace)
p.acc.Reset()
p.acc.WriteString(after)
events = append(events, qwenEventRawToolCall{raw: before})
p.state = qwenParserState_LookingForToolStart
return events, true
} else {
// note that we don't need to check the overlap here because we only plan
// on parsing the tool call once we see the full closing tag. We don't
// stream back the unparsed tool content, so there's no need to be eager
// here
return events, false
}
default:
panic("unreachable")
}
}
// TODO(drifkin): move this to a shared location
// longest overlap between suffix of s and prefix of delim
func overlap(s, delim string) int {
max := min(len(delim), len(s))
for i := max; i > 0; i-- {
if strings.HasSuffix(s, delim[:i]) {
return i
}
}
return 0
}
func trailingWhitespaceLen(s string) int {
for i := len(s) - 1; i >= 0; i-- {
if !unicode.IsSpace(rune(s[i])) {
return len(s) - i - 1
}
}
return len(s)
}
type XMLFunctionCall struct {
XMLName xml.Name `xml:"function"`
Name string `xml:"name,attr"`
Parameters []XMLParameter `xml:"parameter"`
}
type XMLParameter struct {
Name string `xml:"name,attr"`
Value string `xml:",chardata"`
}
// parseToolCall parses a raw tool call string into an api.ToolCall.
// The raw string follows an xml-like format, here's an example:
//
// <function=get_current_temperature>
// <parameter=location>
// San Francisco
// </parameter>
// <parameter=unit>
// celsius
// </parameter>
// </function>
func parseToolCall(raw qwenEventRawToolCall, tools []api.Tool) (api.ToolCall, error) {
toolCall := api.ToolCall{}
xmlString := transformToXML(raw.raw)
var functionCall XMLFunctionCall
err := xml.Unmarshal([]byte(xmlString), &functionCall)
if err != nil {
return api.ToolCall{}, err
}
toolCall.Function = api.ToolCallFunction{
Name: functionCall.Name,
}
// Find the matching tool to get parameter types
var matchedTool *api.Tool
for i := range tools {
if tools[i].Function.Name == functionCall.Name {
matchedTool = &tools[i]
break
}
}
toolCall.Function.Arguments = make(api.ToolCallFunctionArguments)
for _, parameter := range functionCall.Parameters {
// Look up the parameter type if we found the tool
var paramType api.PropertyType
if matchedTool != nil && matchedTool.Function.Parameters.Properties != nil {
if prop, ok := matchedTool.Function.Parameters.Properties[parameter.Name]; ok {
paramType = prop.Type
}
}
toolCall.Function.Arguments[parameter.Name] = parseValue(parameter.Value, paramType)
}
return toolCall, nil
}
// parseValue converts a raw string value to the appropriate type based on the parameter type specification.
//
// For union types (multiple types in PropertyType, which we support but doesn't
// seem as though the reference parser does type coercion with those types in
// mind) we use a type precedence approach:
// 1. null - checked first regardless of declared types (matches reference implementation)
// 2. boolean - only "true"/"false" are valid booleans
// 3. integer - must parse as a whole number
// 4. number - must parse as numeric (returns int if no decimal part)
// 5. array - must parse as valid JSON array
// 6. object - must parse as valid JSON object
// 7. string - always succeeds (least specific type)
//
// This precedence ensures we return the most specific type that successfully parses,
// following the principle of least surprise. For example, with PropertyType{"string", "number"},
// "123" becomes 123 (number), while "hello" becomes "hello" (string).
func parseValue(raw string, paramType api.PropertyType) any {
// first remove a single leading newlines, and a single trailing newline (if
// they exist). This follows the reference implementation
raw = strings.TrimPrefix(raw, "\n")
raw = strings.TrimSuffix(raw, "\n")
// Check for null first (case-insensitive) - this takes precedence over any type
if strings.ToLower(raw) == "null" {
return nil
}
// If no type is specified, default to string
if len(paramType) == 0 {
return raw
}
// Check if any of the specified types match, using type precedence
// Order: boolean -> integer -> number -> array -> object -> string
typeSet := make(map[string]bool)
for _, t := range paramType {
typeSet[t] = true
}
// Try boolean first (most restrictive)
if typeSet["boolean"] {
lower := strings.ToLower(raw)
switch lower {
case "true":
return true
case "false":
return false
}
// If not a valid boolean but boolean is the only type, return false (matching reference)
if len(paramType) == 1 {
return false
}
// Otherwise try other types
}
// Try integer
if typeSet["integer"] {
if i, err := strconv.ParseInt(raw, 10, 64); err == nil {
// Return as int if it fits in int32, otherwise int64
if i >= math.MinInt32 && i <= math.MaxInt32 {
return int(i)
}
return i
}
// If integer is the only type and parsing failed, fall back to string
if len(paramType) == 1 {
return raw
}
}
// Try number (float)
if typeSet["number"] {
if f, err := strconv.ParseFloat(raw, 64); err == nil {
// If the number has no decimal part, return as int (matching reference)
if f == math.Trunc(f) {
i := int64(f)
if i >= math.MinInt32 && i <= math.MaxInt32 {
return int(i)
}
return i
}
return f
}
// If number is the only type and parsing failed, fall back to string
if len(paramType) == 1 {
return raw
}
}
// Try array
if typeSet["array"] {
var arr []interface{}
if err := json.Unmarshal([]byte(raw), &arr); err == nil {
return arr
}
// If array is the only type and parsing failed, fall back to string
if len(paramType) == 1 {
return raw
}
}
// Try object
if typeSet["object"] {
var obj map[string]interface{}
if err := json.Unmarshal([]byte(raw), &obj); err == nil {
return obj
}
// If object is the only type and parsing failed, fall back to string
if len(paramType) == 1 {
return raw
}
}
// String always succeeds (or if "string" is in the type set)
if typeSet["string"] {
return raw
}
// If we get here, none of the types matched and string wasn't an option
// We return string as a fallback. The reference implementation will attempt
// to parse the value as a python literal, but we purposefully don't support
// that
return raw
}
var (
qwenTagRegex = regexp.MustCompile(`<(\w+)=([^>]+)>`)
qwenXMLTagRegex = regexp.MustCompile(`</?(?:function|parameter)(?:\s+name="[^"]*")?>`)
)
// transformToXML transforms a raw qwen tool call with xml-like tags into valid
// xml so that it can be parsed by any xml parser
func transformToXML(raw string) string {
// take the form `<tag=abc>` and transform it to `<tag name="abc">`, taking
// care to properly escape the string that becomes the attribute value
transformed := qwenTagRegex.ReplaceAllStringFunc(raw, func(match string) string {
groups := qwenTagRegex.FindStringSubmatch(match)
tag := groups[1]
var escapedValue strings.Builder
xml.EscapeText(&escapedValue, []byte(groups[2]))
return fmt.Sprintf(`<%s name="%s">`, tag, escapedValue.String())
})
// Walk the resulting string, escaping any character data that sits between the
// xml tags we just emitted
var out strings.Builder
lastIdx := 0
for _, loc := range qwenXMLTagRegex.FindAllStringIndex(transformed, -1) {
if loc[0] > lastIdx {
escapeTextNode(&out, transformed[lastIdx:loc[0]])
}
out.WriteString(transformed[loc[0]:loc[1]])
lastIdx = loc[1]
}
if lastIdx < len(transformed) {
escapeTextNode(&out, transformed[lastIdx:])
}
return out.String()
}
// escapeTextNode escapes XML character data without altering other characters
// like newlines or tabs (which is why we don't use xml.EscapeText for this)
func escapeTextNode(sb *strings.Builder, s string) {
for _, r := range s {
switch r {
case '&':
sb.WriteString("&amp;")
case '<':
sb.WriteString("&lt;")
case '>':
sb.WriteString("&gt;")
default:
sb.WriteRune(r)
}
}
}

View File

@@ -0,0 +1,878 @@
package parsers
import (
"reflect"
"testing"
"github.com/ollama/ollama/api"
)
// tool creates a test tool with the given name and properties
func tool(name string, props map[string]api.ToolProperty) api.Tool {
t := api.Tool{Type: "function", Function: api.ToolFunction{Name: name}}
t.Function.Parameters.Type = "object"
t.Function.Parameters.Properties = props
return t
}
func TestQwenParserStreaming(t *testing.T) {
type step struct {
input string
wantEvents []qwenEvent
}
cases := []struct {
desc string
steps []step
only bool
}{
{
desc: "simple message streamed word by word",
steps: []step{
{
input: "hi",
wantEvents: []qwenEvent{qwenEventContent{content: "hi"}},
},
{
input: " there",
wantEvents: []qwenEvent{qwenEventContent{content: " there"}},
},
},
},
{
desc: "content before tool call",
steps: []step{
{
input: "hi there<tool_call>",
wantEvents: []qwenEvent{qwenEventContent{content: "hi there"}},
},
},
},
{
desc: "multiple tool calls in one message",
steps: []step{
{
input: "before1<tool_call>in tool call</tool_call>after1<tool_call>in tool call 2</tool_call>after2",
wantEvents: []qwenEvent{
qwenEventContent{content: "before1"},
qwenEventRawToolCall{raw: "in tool call"},
qwenEventContent{content: "after1"},
qwenEventRawToolCall{raw: "in tool call 2"},
qwenEventContent{content: "after2"},
},
},
},
},
{
desc: "tool calls with split tags",
steps: []step{
{
input: "before<tool",
wantEvents: []qwenEvent{
qwenEventContent{content: "before"},
},
},
{
input: "_call>in tool call</tool",
wantEvents: []qwenEvent{},
},
{
input: "_call>af",
wantEvents: []qwenEvent{
qwenEventRawToolCall{raw: "in tool call"},
qwenEventContent{content: "af"},
},
},
{
input: "ter",
wantEvents: []qwenEvent{
qwenEventContent{content: "ter"},
},
},
},
},
{
desc: "trailing whitespace between content and tool call",
steps: []step{
{
input: "abc\n<tool_call>def</tool_call>",
wantEvents: []qwenEvent{
qwenEventContent{content: "abc"},
qwenEventRawToolCall{raw: "def"},
},
},
},
},
{
desc: "trailing whitespace between tool call and content",
steps: []step{
{
input: "<tool_call>abc</tool_call>\ndef",
wantEvents: []qwenEvent{
qwenEventRawToolCall{raw: "abc"},
qwenEventContent{content: "def"},
},
},
},
},
{
desc: "empty content before tool call",
steps: []step{
{
input: "\n<tool_call>abc</tool_call>",
wantEvents: []qwenEvent{
qwenEventRawToolCall{raw: "abc"},
},
},
},
},
{
desc: "partial tool open tag fakeout",
steps: []step{
{
input: "abc\n<tool_call",
wantEvents: []qwenEvent{
// \n should not be emitted yet because `<tool_call` might be a tool
// open tag, in which case the whitespace should be trimmed
qwenEventContent{content: "abc"},
},
},
{
input: " fakeout",
wantEvents: []qwenEvent{
qwenEventContent{content: "\n<tool_call fakeout"},
},
},
},
},
{
desc: "token-by-token whitespace handling",
steps: []step{
{
input: "a",
wantEvents: []qwenEvent{
qwenEventContent{content: "a"},
},
},
{
input: "\n",
wantEvents: []qwenEvent{},
},
{
input: "b",
wantEvents: []qwenEvent{
qwenEventContent{content: "\nb"},
},
},
},
},
}
anyOnlies := false
for _, tc := range cases {
if tc.only {
anyOnlies = true
}
}
for _, tc := range cases {
if anyOnlies && !tc.only {
continue
}
t.Run(tc.desc, func(t *testing.T) {
parser := Qwen3CoderParser{}
for i, step := range tc.steps {
parser.acc.WriteString(step.input)
gotEvents := parser.parseEvents()
if len(gotEvents) == 0 && len(step.wantEvents) == 0 {
// avoid deep equal on empty vs. nil slices
continue
}
if !reflect.DeepEqual(gotEvents, step.wantEvents) {
t.Errorf("step %d: input %q: got events %#v, want %#v", i, step.input, gotEvents, step.wantEvents)
}
}
})
}
}
func TestQwenToolParser(t *testing.T) {
type step struct {
name string
rawToolCall string
tools []api.Tool
wantToolCall api.ToolCall
}
steps := []step{
{
name: "simple tool call",
tools: []api.Tool{},
rawToolCall: `<function=get_current_temperature>
<parameter=location>
San Francisco
</parameter>
<parameter=unit>
celsius
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "get_current_temperature",
Arguments: map[string]any{
"location": "San Francisco",
"unit": "celsius",
},
},
},
},
{
name: "names with spaces",
tools: []api.Tool{},
rawToolCall: `<function=get current temperature>
<parameter=location with spaces>
San Francisco
</parameter>
<parameter=unit with spaces>
celsius
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "get current temperature",
Arguments: map[string]any{
"location with spaces": "San Francisco",
"unit with spaces": "celsius",
},
},
},
},
// this mirrors the reference implementation's behavior, but unclear if it
// ever happens. If so, then we should probably remove them instead, this
// test is to just document the current behavior and test that we don't get
// xml errors
{
name: "names with quotes",
tools: []api.Tool{},
rawToolCall: `<function="get current temperature">
<parameter="location with spaces">
San Francisco
</parameter>
<parameter="unit with spaces">
"celsius"
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "\"get current temperature\"",
Arguments: map[string]any{
"\"location with spaces\"": "San Francisco",
"\"unit with spaces\"": "\"celsius\"",
},
},
},
},
{
name: "tool call with typed parameters",
tools: []api.Tool{
tool("calculate", map[string]api.ToolProperty{
"x": {Type: api.PropertyType{"number"}},
"y": {Type: api.PropertyType{"integer"}},
"enabled": {Type: api.PropertyType{"boolean"}},
"items": {Type: api.PropertyType{"array"}},
}),
},
rawToolCall: `<function=calculate>
<parameter=x>
3.14
</parameter>
<parameter=y>
42
</parameter>
<parameter=enabled>
true
</parameter>
<parameter=items>
["a", "b", "c"]
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "calculate",
Arguments: map[string]any{
"x": 3.14,
"y": 42,
"enabled": true,
"items": []any{"a", "b", "c"},
},
},
},
},
// regression test for <https://github.com/ollama/ollama/issues/12357>
{
name: "ampersands in parameter values",
tools: []api.Tool{},
rawToolCall: `<function=exec>
<parameter=command>
ls && echo "done"
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "exec",
Arguments: map[string]any{
"command": "ls && echo \"done\"",
},
},
},
},
{
name: "angle brackets in parameter values",
tools: []api.Tool{},
rawToolCall: `<function=exec>
<parameter=command>
ls && echo "a > b and a < b"
</parameter>
</function>`,
wantToolCall: api.ToolCall{
Function: api.ToolCallFunction{
Name: "exec",
Arguments: map[string]any{
"command": "ls && echo \"a > b and a < b\"",
},
},
},
},
}
for i, step := range steps {
gotToolCall, err := parseToolCall(qwenEventRawToolCall{raw: step.rawToolCall}, step.tools)
if err != nil {
t.Errorf("step %d (%s): %v", i, step.name, err)
}
if !reflect.DeepEqual(gotToolCall, step.wantToolCall) {
t.Errorf("step %d (%s): got tool call %#v, want %#v", i, step.name, gotToolCall, step.wantToolCall)
}
}
}
func TestQwenToolCallValueParsing(t *testing.T) {
cases := []struct {
desc string
raw string
paramType api.PropertyType
want any
}{
{
desc: "default string value (no type specified)",
paramType: api.PropertyType{},
raw: "some-string",
want: "some-string",
},
{
desc: "trim a single leading and trailing newline",
paramType: api.PropertyType{},
raw: "\nsome-string\n",
want: "some-string",
},
{
desc: "trim at most one leading and trailing newline",
paramType: api.PropertyType{},
raw: "\n\nsome-string\n\n",
want: "\nsome-string\n",
},
{
desc: "newline really has to be the first character to be trimmed",
paramType: api.PropertyType{},
raw: " \nsome-string\n ",
want: " \nsome-string\n ",
},
{
desc: "numeric type",
paramType: api.PropertyType{"number"},
raw: "123",
want: 123,
},
// Integer parsing tests
{
desc: "integer type",
paramType: api.PropertyType{"integer"},
raw: "42",
want: 42,
},
{
desc: "negative integer",
paramType: api.PropertyType{"integer"},
raw: "-100",
want: -100,
},
{
desc: "zero integer",
paramType: api.PropertyType{"integer"},
raw: "0",
want: 0,
},
{
desc: "integer with leading zeros",
paramType: api.PropertyType{"integer"},
raw: "007",
want: 7,
},
{
desc: "large integer",
paramType: api.PropertyType{"integer"},
raw: "2147483648", // Just beyond int32 max
want: int64(2147483648),
},
// Float/number parsing tests
{
desc: "float type",
paramType: api.PropertyType{"number"},
raw: "3.14",
want: 3.14,
},
{
desc: "negative float",
paramType: api.PropertyType{"number"},
raw: "-273.15",
want: -273.15,
},
{
desc: "float without decimal part",
paramType: api.PropertyType{"number"},
raw: "100.0",
want: 100,
},
{
desc: "scientific notation positive",
paramType: api.PropertyType{"number"},
raw: "1.23e5",
want: 123000, // Will be int since it has no decimal part
},
{
desc: "scientific notation negative",
paramType: api.PropertyType{"number"},
raw: "1.5e-3",
want: 0.0015,
},
{
desc: "very small float",
paramType: api.PropertyType{"number"},
raw: "0.00000001",
want: 0.00000001,
},
// String parsing tests
{
desc: "explicit string type",
paramType: api.PropertyType{"string"},
raw: "hello world",
want: "hello world",
},
{
desc: "string with special characters",
paramType: api.PropertyType{"string"},
raw: "/usr/local/bin/test-file_v2.0.sh",
want: "/usr/local/bin/test-file_v2.0.sh",
},
{
desc: "string with quotes",
paramType: api.PropertyType{"string"},
raw: `He said "hello" to me`,
want: `He said "hello" to me`,
},
{
desc: "multiline string",
paramType: api.PropertyType{"string"},
raw: "line one\nline two\nline three",
want: "line one\nline two\nline three",
},
{
desc: "empty string",
paramType: api.PropertyType{"string"},
raw: "",
want: "",
},
{
desc: "string that looks like a number",
paramType: api.PropertyType{"string"},
raw: "12345",
want: "12345",
},
// Boolean parsing tests
{
desc: "boolean true",
paramType: api.PropertyType{"boolean"},
raw: "true",
want: true,
},
{
desc: "boolean false",
paramType: api.PropertyType{"boolean"},
raw: "false",
want: false,
},
{
desc: "boolean case insensitive true",
paramType: api.PropertyType{"boolean"},
raw: "True",
want: true,
},
{
desc: "boolean case insensitive false",
paramType: api.PropertyType{"boolean"},
raw: "FALSE",
want: false,
},
// Null parsing tests
{
desc: "null value lowercase",
paramType: api.PropertyType{"string"},
raw: "null",
want: nil,
},
{
desc: "null value case insensitive",
paramType: api.PropertyType{"integer"},
raw: "NULL",
want: nil,
},
// Array parsing tests
{
desc: "array of strings",
paramType: api.PropertyType{"array"},
raw: `["foo", "bar", "baz"]`,
want: []any{"foo", "bar", "baz"},
},
{
desc: "array of numbers",
paramType: api.PropertyType{"array"},
raw: `[1, 2.5, 3]`,
want: []any{float64(1), 2.5, float64(3)},
},
{
desc: "array of mixed types",
paramType: api.PropertyType{"array"},
raw: `["string", 123, true, null]`,
want: []any{"string", float64(123), true, nil},
},
{
desc: "empty array",
paramType: api.PropertyType{"array"},
raw: `[]`,
want: []any{},
},
// Object parsing tests
{
desc: "simple object",
paramType: api.PropertyType{"object"},
raw: `{"key": "value", "number": 42}`,
want: map[string]any{"key": "value", "number": float64(42)},
},
{
desc: "nested object",
paramType: api.PropertyType{"object"},
raw: `{"outer": {"inner": "value"}}`,
want: map[string]any{"outer": map[string]any{"inner": "value"}},
},
{
desc: "empty object",
paramType: api.PropertyType{"object"},
raw: `{}`,
want: map[string]any{},
},
// Error cases and fallback behavior
{
desc: "invalid integer falls back to string",
paramType: api.PropertyType{"integer"},
raw: "not-a-number",
want: "not-a-number",
},
{
desc: "invalid float falls back to string",
paramType: api.PropertyType{"number"},
raw: "3.14.159",
want: "3.14.159",
},
{
desc: "invalid boolean falls back to false",
paramType: api.PropertyType{"boolean"},
raw: "yes",
want: false,
},
{
desc: "invalid JSON array falls back to string",
paramType: api.PropertyType{"array"},
raw: "[1, 2, unclosed",
want: "[1, 2, unclosed",
},
{
desc: "invalid JSON object falls back to string",
paramType: api.PropertyType{"object"},
raw: `{"key": unclosed`,
want: `{"key": unclosed`,
},
// Edge cases
{
desc: "integer overflow should use int64",
paramType: api.PropertyType{"integer"},
raw: "2147483648", // Beyond int32 max
want: int64(2147483648),
},
{
desc: "float with many decimal places",
paramType: api.PropertyType{"number"},
raw: "3.141592653589793",
want: 3.141592653589793,
},
{
desc: "string with JSON-like content",
paramType: api.PropertyType{"string"},
raw: `{"this": "is", "just": "a string"}`,
want: `{"this": "is", "just": "a string"}`,
},
{
desc: "whitespace-only string",
paramType: api.PropertyType{"string"},
raw: " ",
want: " ",
},
// Unknown parameter (no type specified in tools)
{
desc: "parameter not in tool definition defaults to string",
paramType: api.PropertyType{},
raw: "some value",
want: "some value",
},
// Union type tests
{
desc: "string or number union - valid number",
paramType: api.PropertyType{"string", "number"},
raw: "42.5",
want: 42.5,
},
{
desc: "string or number union - non-numeric string",
paramType: api.PropertyType{"string", "number"},
raw: "hello",
want: "hello",
},
{
desc: "number or string union - valid number (order shouldn't matter)",
paramType: api.PropertyType{"number", "string"},
raw: "42.5",
want: 42.5,
},
{
desc: "integer or null union - valid integer",
paramType: api.PropertyType{"integer", "null"},
raw: "123",
want: 123,
},
{
desc: "integer or null union - null value",
paramType: api.PropertyType{"integer", "null"},
raw: "null",
want: nil,
},
{
desc: "null or integer union - null value (order shouldn't matter)",
paramType: api.PropertyType{"null", "integer"},
raw: "null",
want: nil,
},
{
desc: "boolean or string union - valid boolean",
paramType: api.PropertyType{"boolean", "string"},
raw: "true",
want: true,
},
{
desc: "boolean or string union - non-boolean becomes string",
paramType: api.PropertyType{"boolean", "string"},
raw: "yes",
want: "yes",
},
{
desc: "string or boolean union - valid boolean (precedence test)",
paramType: api.PropertyType{"string", "boolean"},
raw: "false",
want: false, // Should be boolean, not string "false"
},
{
desc: "integer or number union - integer value",
paramType: api.PropertyType{"integer", "number"},
raw: "42",
want: 42,
},
{
desc: "integer or number union - float value",
paramType: api.PropertyType{"integer", "number"},
raw: "42.5",
want: 42.5,
},
{
desc: "number or integer union - integer value (precedence test)",
paramType: api.PropertyType{"number", "integer"},
raw: "42",
want: 42, // Should try integer first due to precedence
},
{
desc: "array or object union - valid array",
paramType: api.PropertyType{"array", "object"},
raw: `[1, 2, 3]`,
want: []any{float64(1), float64(2), float64(3)},
},
{
desc: "array or object union - valid object",
paramType: api.PropertyType{"array", "object"},
raw: `{"key": "value"}`,
want: map[string]any{"key": "value"},
},
{
desc: "object or array union - valid array (precedence test)",
paramType: api.PropertyType{"object", "array"},
raw: `[1, 2, 3]`,
want: []any{float64(1), float64(2), float64(3)},
},
{
desc: "complex multi-type union - null",
paramType: api.PropertyType{"string", "number", "boolean", "null"},
raw: "null",
want: nil,
},
{
desc: "complex multi-type union - boolean",
paramType: api.PropertyType{"string", "number", "boolean", "null"},
raw: "true",
want: true,
},
{
desc: "complex multi-type union - number",
paramType: api.PropertyType{"string", "number", "boolean", "null"},
raw: "3.14",
want: 3.14,
},
{
desc: "complex multi-type union - string",
paramType: api.PropertyType{"string", "number", "boolean", "null"},
raw: "hello",
want: "hello",
},
{
desc: "integer string union - integer string becomes integer",
paramType: api.PropertyType{"integer", "string"},
raw: "123",
want: 123,
},
{
desc: "string integer union - integer string becomes integer (precedence)",
paramType: api.PropertyType{"string", "integer"},
raw: "123",
want: 123, // Integer has higher precedence than string
},
}
for _, tc := range cases {
t.Run(tc.desc, func(t *testing.T) {
got := parseValue(tc.raw, tc.paramType)
if !reflect.DeepEqual(got, tc.want) {
t.Errorf("got %v (type %T), want %v (type %T)", got, got, tc.want, tc.want)
}
})
}
}
func TestQwenXMLTransform(t *testing.T) {
cases := []struct {
desc string
raw string
want string
}{
{
desc: "simple example",
raw: `<function=get_current_temperature>
<parameter=location>
San Francisco
</parameter>
<parameter=unit>
celsius
</parameter>
</function>`,
want: `<function name="get_current_temperature">
<parameter name="location">
San Francisco
</parameter>
<parameter name="unit">
celsius
</parameter>
</function>`,
},
// even though quotes aren't expected in these tags, we have these tests to
// make sure they're escaped so they don't blow up the xml parser in case
// they happen
{
desc: "names with quotes",
raw: `<function="get current temperature">
<parameter="location with spaces">
San Francisco
</parameter>
<parameter="unit with spaces">
celsius
</parameter>
</function>`,
want: `<function name="&#34;get current temperature&#34;">
<parameter name="&#34;location with spaces&#34;">
San Francisco
</parameter>
<parameter name="&#34;unit with spaces&#34;">
celsius
</parameter>
</function>`,
},
{
desc: "ampersands in parameter values",
raw: `<function=get_current_temperature>
<parameter=location>
San Francisco & San Jose
</parameter>
</function>`,
want: `<function name="get_current_temperature">
<parameter name="location">
San Francisco &amp; San Jose
</parameter>
</function>`,
},
}
for _, tc := range cases {
got := transformToXML(tc.raw)
if got != tc.want {
t.Errorf("got %q, want %q", got, tc.want)
}
}
}
func TestTrailingWhitespaceLen(t *testing.T) {
cases := []struct {
desc string
s string
want int
}{
{desc: "no whitespace", s: "abc", want: 0},
{desc: "trailing whitespace", s: "abc ", want: 1},
{desc: "trailing whitespace with newlines", s: "abc \n", want: 2},
{desc: "only whitespace", s: " \n ", want: 4},
{desc: "leading whitespace doesn't count", s: " \n abc", want: 0},
}
for _, tc := range cases {
got := trailingWhitespaceLen(tc.s)
if got != tc.want {
t.Errorf("got %d, want %d", got, tc.want)
}
}
}

View File

@@ -0,0 +1,217 @@
package renderers
import (
"encoding/json"
"fmt"
"reflect"
"strings"
"github.com/ollama/ollama/api"
)
var (
imStartTag = "<|im_start|>"
imEndTag = "<|im_end|>"
)
// renderAdditionalKeys renders all JSON fields except the ones in handledKeys
// This follows the same approach from the reference implementation, which gives
// a particular key ordering
func renderAdditionalKeys(obj any, handledKeys map[string]bool) string {
data, err := json.Marshal(obj)
if err != nil {
return ""
}
var m map[string]any
if err := json.Unmarshal(data, &m); err != nil {
return ""
}
var sb strings.Builder
for key, value := range m {
if handledKeys[key] {
continue
}
// Check if value is a map or array (needs JSON serialization)
switch v := value.(type) {
case map[string]any, []any:
jsonBytes, _ := json.Marshal(v)
// TODO(drifkin): it would be nice to format the JSON here similarly to
// python's default json.dumps behavior (spaces after commas and colons).
// This would let us be byte-for-byte compatible with the reference
// implementation for most common inputs
jsonStr := string(jsonBytes)
sb.WriteString("\n<" + key + ">" + jsonStr + "</" + key + ">")
case nil:
continue
default:
// Simple types, convert to string
sb.WriteString("\n<" + key + ">" + fmt.Sprintf("%v", value) + "</" + key + ">")
}
}
return sb.String()
}
func Qwen3CoderRenderer(messages []api.Message, tools []api.Tool, _ *api.ThinkValue) (string, error) {
var sb strings.Builder
// filter out system messages and choose the first (if any) to win
var systemMessage string
var filteredMessages []api.Message
for _, message := range messages {
if message.Role != "system" {
filteredMessages = append(filteredMessages, message)
continue
}
if systemMessage == "" {
systemMessage = message.Content
}
}
if systemMessage != "" || len(tools) > 0 {
sb.WriteString(imStartTag + "system\n")
// if we have tools but no system message, match the reference implementation by providing a default system message
if systemMessage == "" {
systemMessage = "You are Qwen, a helpful AI assistant that can interact with a computer to solve tasks."
}
sb.WriteString(systemMessage)
if len(tools) > 0 {
sb.WriteString("\n\n# Tools\n\nYou have access to the following functions:\n\n")
sb.WriteString("<tools>")
for _, tool := range tools {
sb.WriteString("\n")
sb.WriteString("<function>\n")
sb.WriteString("<name>" + tool.Function.Name + "</name>")
if tool.Function.Description != "" {
sb.WriteString("\n<description>" + tool.Function.Description + "</description>")
}
sb.WriteString("\n<parameters>")
for name, prop := range tool.Function.Parameters.Properties {
sb.WriteString("\n<parameter>")
sb.WriteString("\n<name>" + name + "</name>")
if len(prop.Type) > 0 {
// TODO(!!!)(drifkin): we should match the reference implementation for
// more complex types here instead of using this format
sb.WriteString("\n<type>" + prop.ToTypeScriptType() + "</type>")
}
if prop.Description != "" {
sb.WriteString("\n<description>" + prop.Description + "</description>")
}
// Render any additional keys not already handled
handledKeys := map[string]bool{
"type": true,
"description": true,
}
sb.WriteString(renderAdditionalKeys(prop, handledKeys))
sb.WriteString("\n</parameter>")
}
// Render extra keys for parameters (everything except 'type' and 'properties')
paramHandledKeys := map[string]bool{
"type": true,
"properties": true,
}
sb.WriteString(renderAdditionalKeys(tool.Function.Parameters, paramHandledKeys))
sb.WriteString("\n</parameters>")
sb.WriteString("\n</function>")
}
sb.WriteString("\n</tools>")
sb.WriteString("\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>")
}
sb.WriteString(imEndTag + "\n")
}
for i, message := range filteredMessages {
lastMessage := i == len(filteredMessages)-1
prefill := lastMessage && message.Role == "assistant"
switch message.Role {
case "assistant":
if len(message.ToolCalls) > 0 {
sb.WriteString(imStartTag + "assistant\n")
if message.Content != "" {
sb.WriteString(message.Content + "\n")
}
for _, toolCall := range message.ToolCalls {
sb.WriteString("\n<tool_call>\n<function=" + toolCall.Function.Name + ">")
for name, value := range toolCall.Function.Arguments {
valueStr := formatToolCallArgument(value)
sb.WriteString("\n<parameter=" + name + ">\n" + valueStr + "\n</parameter>")
}
sb.WriteString("\n</function>\n</tool_call>")
}
sb.WriteString("<|im_end|>\n")
} else {
sb.WriteString(imStartTag + "assistant\n")
sb.WriteString(message.Content)
if !prefill {
sb.WriteString(imEndTag + "\n")
}
}
case "tool":
// consecutive tool responses should share a single `<im_start>user`, but
// have their own <tool_response> tags
// only start a new user block if this is the first tool response
if i == 0 || filteredMessages[i-1].Role != "tool" {
sb.WriteString(imStartTag + "user\n")
}
sb.WriteString("<tool_response>\n")
sb.WriteString(message.Content)
sb.WriteString("\n</tool_response>\n")
// close the user block only if this is the last tool response
if i == len(filteredMessages)-1 || filteredMessages[i+1].Role != "tool" {
sb.WriteString(imEndTag + "\n")
}
default:
sb.WriteString(imStartTag + message.Role + "\n")
sb.WriteString(message.Content)
sb.WriteString(imEndTag + "\n")
}
if lastMessage && !prefill {
sb.WriteString(imStartTag + "assistant\n")
}
}
return sb.String(), nil
}
func formatToolCallArgument(value any) string {
if value == nil {
return "null"
}
switch v := value.(type) {
case string:
return v
case []byte:
return string(v)
}
if reflect.TypeOf(value) != nil {
kind := reflect.TypeOf(value).Kind()
if kind == reflect.Map || kind == reflect.Slice || kind == reflect.Array {
if marshalled, err := json.Marshal(value); err == nil {
return string(marshalled)
}
}
}
return fmt.Sprintf("%v", value)
}

View File

@@ -0,0 +1,338 @@
package renderers
import (
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
)
func TestQwen3CoderRenderer(t *testing.T) {
tests := []struct {
name string
msgs []api.Message
tools []api.Tool
expected string
}{
{
name: "basic",
msgs: []api.Message{
{Role: "system", Content: "You are a helpful assistant."},
{Role: "user", Content: "Hello, how are you?"},
},
expected: `<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
Hello, how are you?<|im_end|>
<|im_start|>assistant
`,
},
{
name: "with tools and response",
msgs: []api.Message{
{Role: "system", Content: "You are a helpful assistant with access to tools."},
{Role: "user", Content: "What is the weather like in San Francisco?"},
{
Role: "assistant",
Content: "I'll check the weather in San Francisco for you.",
ToolCalls: []api.ToolCall{
{
Function: api.ToolCallFunction{
Name: "get_weather",
Arguments: map[string]any{
"unit": "fahrenheit",
},
},
},
},
},
{Role: "tool", Content: "{\"location\": \"San Francisco, CA\", \"temperature\": 68, \"condition\": \"partly cloudy\", \"humidity\": 65, \"wind_speed\": 12}", ToolName: "get_weather"},
{Role: "user", Content: "That sounds nice! What about New York?"},
},
tools: []api.Tool{
{Function: api.ToolFunction{
Name: "get_weather",
Description: "Get the current weather in a given location",
Parameters: api.ToolFunctionParameters{
Required: []string{"unit"},
Properties: map[string]api.ToolProperty{
"unit": {Type: api.PropertyType{"string"}, Enum: []any{"celsius", "fahrenheit"}, Description: "The unit of temperature"},
// TODO(drifkin): add multiple params back once we have predictable
// order via some sort of ordered map type (see
// <https://github.com/ollama/ollama/issues/12244>)
/*
"location": {Type: api.PropertyType{"string"}, Description: "The city and state, e.g. San Francisco, CA"},
*/
},
},
}},
},
expected: `<|im_start|>system
You are a helpful assistant with access to tools.
# Tools
You have access to the following functions:
<tools>
<function>
<name>get_weather</name>
<description>Get the current weather in a given location</description>
<parameters>
<parameter>
<name>unit</name>
<type>string</type>
<description>The unit of temperature</description>
<enum>["celsius","fahrenheit"]</enum>
</parameter>
<required>["unit"]</required>
</parameters>
</function>
</tools>
If you choose to call a function ONLY reply in the following format with NO suffix:
<tool_call>
<function=example_function_name>
<parameter=example_parameter_1>
value_1
</parameter>
<parameter=example_parameter_2>
This is the value for the second parameter
that can span
multiple lines
</parameter>
</function>
</tool_call>
<IMPORTANT>
Reminder:
- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
- Required parameters MUST be specified
- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
</IMPORTANT><|im_end|>
<|im_start|>user
What is the weather like in San Francisco?<|im_end|>
<|im_start|>assistant
I'll check the weather in San Francisco for you.
<tool_call>
<function=get_weather>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call><|im_end|>
<|im_start|>user
<tool_response>
{"location": "San Francisco, CA", "temperature": 68, "condition": "partly cloudy", "humidity": 65, "wind_speed": 12}
</tool_response>
<|im_end|>
<|im_start|>user
That sounds nice! What about New York?<|im_end|>
<|im_start|>assistant
`,
},
{
name: "parallel tool calls",
msgs: []api.Message{
{Role: "system", Content: "You are a helpful assistant with access to tools."},
{Role: "user", Content: "call double(1) and triple(2)"},
{Role: "assistant", Content: "I'll call double(1) and triple(2) for you.", ToolCalls: []api.ToolCall{
{Function: api.ToolCallFunction{Name: "double", Arguments: map[string]any{"number": "1"}}},
{Function: api.ToolCallFunction{Name: "triple", Arguments: map[string]any{"number": "2"}}},
}},
{Role: "tool", Content: "{\"number\": 2}", ToolName: "double"},
{Role: "tool", Content: "{\"number\": 6}", ToolName: "triple"},
},
tools: []api.Tool{
{Function: api.ToolFunction{Name: "double", Description: "Double a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
"number": {Type: api.PropertyType{"string"}, Description: "The number to double"},
}}}},
{Function: api.ToolFunction{Name: "triple", Description: "Triple a number", Parameters: api.ToolFunctionParameters{Properties: map[string]api.ToolProperty{
"number": {Type: api.PropertyType{"string"}, Description: "The number to triple"},
}}}},
},
expected: `<|im_start|>system
You are a helpful assistant with access to tools.
# Tools
You have access to the following functions:
<tools>
<function>
<name>double</name>
<description>Double a number</description>
<parameters>
<parameter>
<name>number</name>
<type>string</type>
<description>The number to double</description>
</parameter>
</parameters>
</function>
<function>
<name>triple</name>
<description>Triple a number</description>
<parameters>
<parameter>
<name>number</name>
<type>string</type>
<description>The number to triple</description>
</parameter>
</parameters>
</function>
</tools>
If you choose to call a function ONLY reply in the following format with NO suffix:
<tool_call>
<function=example_function_name>
<parameter=example_parameter_1>
value_1
</parameter>
<parameter=example_parameter_2>
This is the value for the second parameter
that can span
multiple lines
</parameter>
</function>
</tool_call>
<IMPORTANT>
Reminder:
- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags
- Required parameters MUST be specified
- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after
- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
</IMPORTANT><|im_end|>
<|im_start|>user
call double(1) and triple(2)<|im_end|>
<|im_start|>assistant
I'll call double(1) and triple(2) for you.
<tool_call>
<function=double>
<parameter=number>
1
</parameter>
</function>
</tool_call>
<tool_call>
<function=triple>
<parameter=number>
2
</parameter>
</function>
</tool_call><|im_end|>
<|im_start|>user
<tool_response>
{"number": 2}
</tool_response>
<tool_response>
{"number": 6}
</tool_response>
<|im_end|>
<|im_start|>assistant
`,
},
{
name: "prefill",
msgs: []api.Message{
{Role: "system", Content: "You are a helpful assistant."},
{Role: "user", Content: "Tell me something interesting."},
{Role: "assistant", Content: "I'll tell you something interesting about cats"},
},
expected: `<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
Tell me something interesting.<|im_end|>
<|im_start|>assistant
I'll tell you something interesting about cats`,
},
{
name: "complex tool call arguments should remain json encoded",
msgs: []api.Message{
{Role: "user", Content: "call tool"},
{Role: "assistant", ToolCalls: []api.ToolCall{
{Function: api.ToolCallFunction{
Name: "echo",
Arguments: map[string]any{
"payload": map[string]any{"foo": "bar"},
},
}},
}},
{Role: "tool", Content: "{\"payload\": {\"foo\": \"bar\"}}", ToolName: "echo"},
},
expected: `<|im_start|>user
call tool<|im_end|>
<|im_start|>assistant
<tool_call>
<function=echo>
<parameter=payload>
{"foo":"bar"}
</parameter>
</function>
</tool_call><|im_end|>
<|im_start|>user
<tool_response>
{"payload": {"foo": "bar"}}
</tool_response>
<|im_end|>
<|im_start|>assistant
`,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
rendered, err := Qwen3CoderRenderer(tt.msgs, tt.tools, nil)
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(rendered, tt.expected); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
}
}
func TestFormatToolCallArgument(t *testing.T) {
tests := []struct {
name string
arg any
expected string
}{
{
name: "string",
arg: "foo",
// notice no quotes around the string
expected: "foo",
},
{
name: "map",
arg: map[string]any{"foo": "bar"},
expected: "{\"foo\":\"bar\"}",
},
{
name: "number",
arg: 1,
expected: "1",
},
{
name: "boolean",
arg: true,
expected: "true",
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := formatToolCallArgument(tt.arg)
if got != tt.expected {
t.Errorf("formatToolCallArgument(%v) = %v, want %v", tt.arg, got, tt.expected)
}
})
}
}

View File

@@ -0,0 +1,26 @@
package renderers
import (
"fmt"
"github.com/ollama/ollama/api"
)
type rendererFunc func([]api.Message, []api.Tool, *api.ThinkValue) (string, error)
func RenderWithRenderer(name string, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
renderer := rendererForName(name)
if renderer == nil {
return "", fmt.Errorf("unknown renderer %q", name)
}
return renderer(msgs, tools, think)
}
func rendererForName(name string) rendererFunc {
switch name {
case "qwen3-coder":
return Qwen3CoderRenderer
default:
return nil
}
}

View File

@@ -12,18 +12,18 @@ import (
const spmWhitespaceSep = "▁" const spmWhitespaceSep = "▁"
type SentencePieceModel struct { type SentencePiece struct {
maxTokenLen int maxTokenLen int
vocab *Vocabulary vocab *Vocabulary
} }
var _ TextProcessor = (*SentencePieceModel)(nil) var _ TextProcessor = (*SentencePiece)(nil)
func (spm SentencePieceModel) Vocabulary() *Vocabulary { func (spm SentencePiece) Vocabulary() *Vocabulary {
return spm.vocab return spm.vocab
} }
func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel { func NewSentencePiece(vocab *Vocabulary) SentencePiece {
logutil.Trace("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5]) logutil.Trace("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
counter := map[int]int{} counter := map[int]int{}
@@ -42,17 +42,17 @@ func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
"user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE], "user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE],
"max token len", maxTokenLen) "max token len", maxTokenLen)
return SentencePieceModel{ return SentencePiece{
maxTokenLen: maxTokenLen, maxTokenLen: maxTokenLen,
vocab: vocab, vocab: vocab,
} }
} }
func (spm SentencePieceModel) Is(id int32, special Special) bool { func (spm SentencePiece) Is(id int32, special Special) bool {
return spm.vocab.Is(id, special) return spm.vocab.Is(id, special)
} }
func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) { func (spm SentencePiece) Encode(s string, addSpecial bool) ([]int32, error) {
fragments := []fragment{{value: s}} fragments := []fragment{{value: s}}
for _, special := range spm.vocab.SpecialVocabulary() { for _, special := range spm.vocab.SpecialVocabulary() {
id := spm.vocab.Encode(special) id := spm.vocab.Encode(special)
@@ -218,7 +218,7 @@ func (q *queue) Pop() interface{} {
return item return item
} }
func (spm SentencePieceModel) Decode(ids []int32) (string, error) { func (spm SentencePiece) Decode(ids []int32) (string, error) {
var sb strings.Builder var sb strings.Builder
for _, id := range ids { for _, id := range ids {
data := spm.vocab.Decode(id) data := spm.vocab.Decode(id)

View File

@@ -12,7 +12,7 @@ import (
"github.com/ollama/ollama/convert/sentencepiece" "github.com/ollama/ollama/convert/sentencepiece"
) )
func loadSentencePieceVocab(t *testing.T) SentencePieceModel { func loadSentencePieceVocab(t *testing.T) SentencePiece {
t.Helper() t.Helper()
bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model")) bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model"))
@@ -45,7 +45,7 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
} }
} }
return NewSentencePieceModel(&v) return NewSentencePiece(&v)
} }
func TestSentencePieceEncode(t *testing.T) { func TestSentencePieceEncode(t *testing.T) {
@@ -115,7 +115,7 @@ func TestSentencePieceEncode(t *testing.T) {
}) })
} }
func TestSentencePieceModelDecodeByteTokens(t *testing.T) { func TestSentencePieceDecodeByteTokens(t *testing.T) {
vocab := &Vocabulary{ vocab := &Vocabulary{
Values: []string{ Values: []string{
"normal", "normal",
@@ -134,7 +134,7 @@ func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
Scores: []float32{0, 0, 0, 0, 0}, Scores: []float32{0, 0, 0, 0, 0},
} }
spm := NewSentencePieceModel(vocab) spm := NewSentencePiece(vocab)
tests := []struct { tests := []struct {
name string name string

167
model/wordpiece.go Normal file
View File

@@ -0,0 +1,167 @@
package model
import (
"fmt"
"iter"
"strings"
"unicode"
"github.com/ollama/ollama/logutil"
)
type WordPiece struct {
vocab *Vocabulary
}
// ggmlPrefix is the prefix used by GGML vocabularies to indicate word boundaries.
// this differs from original word piece which uses "##" to indicate subwords.
const ggmlPrefix = "▁"
var wordPieceReplacer = strings.NewReplacer(
" .", ".",
" ?", "?",
" !", "!",
" ,", ",",
" ' ", "'",
" n't", "n't",
" 'm", "'m",
" do not", " don't",
" 's", "'s",
" 've", "'ve",
" 're", "'re",
)
// Decode implements TextProcessor.
func (wpm WordPiece) Decode(ids []int32) (string, error) {
var sb strings.Builder
for i, id := range ids {
if id < 0 || int(id) >= len(wpm.vocab.Values) {
return "", fmt.Errorf("invalid token id: %d", id)
}
var separator string
piece := wpm.vocab.Values[id]
if i > 0 &&
(strings.HasPrefix(piece, ggmlPrefix) ||
(strings.HasPrefix(piece, "[") && strings.HasSuffix(piece, "]"))) {
separator = " "
}
sb.WriteString(wordPieceReplacer.Replace(separator + strings.TrimPrefix(piece, ggmlPrefix)))
}
return sb.String(), nil
}
// words splits a string into words, treating CJK characters as separate words.
// TODO: this is specifically for BERT and may need to be adjusted or refactored for other models.
func (wpm WordPiece) words(s string) iter.Seq[string] {
return func(yield func(string) bool) {
runes := make([]rune, 0, len(s)*3)
for _, r := range s {
switch {
case r >= 0x4E00 && r <= 0x9FFF,
r >= 0x3400 && r <= 0x4DBF,
r >= 0x20000 && r <= 0x2A6DF,
r >= 0x2A700 && r <= 0x2B73F,
r >= 0x2B740 && r <= 0x2B81F,
r >= 0x2B820 && r <= 0x2CEAF,
r >= 0xF900 && r <= 0xFAFF,
r >= 0x2F800 && r <= 0x2FA1F:
runes = append(runes, ' ', r, ' ')
default:
runes = append(runes, r)
}
}
for w := range strings.FieldsFuncSeq(string(runes), unicode.IsSpace) {
// split on but keep punctuation
var start int
for start < len(w) {
end := strings.IndexFunc(w[start:], unicode.IsPunct)
if end < 0 {
end = len(w) - start
} else if end == 0 {
end = 1
}
if !yield(w[start : start+end]) {
return
}
start += end
}
}
}
}
// Encode implements TextProcessor.
func (wpm WordPiece) Encode(s string, addSpecial bool) ([]int32, error) {
var ids []int32
// TODO: use [UNK] from config
unk := wpm.vocab.Encode("[UNK]")
for word := range wpm.words(s) {
var start int
var pieces []int32
for start < len(word) {
end := len(word)
var piece int32
for start < end {
subword := word[start:end]
if start == 0 {
subword = ggmlPrefix + subword
}
// TODO: some models might not want [ToLower]
piece = wpm.vocab.Encode(strings.ToLower(subword))
if piece >= 0 {
break
}
end--
}
if piece < 0 {
// Unknown token
pieces = pieces[:0]
break
}
pieces = append(pieces, piece)
start = end
}
if len(pieces) > 0 {
ids = append(ids, pieces...)
} else {
ids = append(ids, unk)
}
}
if addSpecial && len(ids) > 0 {
ids = wpm.vocab.addSpecials(ids)
}
logutil.Trace("encoded", "string", s, "ids", ids)
return ids, nil
}
// Is implements TextProcessor.
func (wpm WordPiece) Is(id int32, special Special) bool {
return wpm.vocab.Is(id, special)
}
// Vocabulary implements TextProcessor.
func (wpm WordPiece) Vocabulary() *Vocabulary {
return wpm.vocab
}
var _ TextProcessor = (*WordPiece)(nil)
func NewWordPiece(vocab *Vocabulary) WordPiece {
return WordPiece{
vocab: vocab,
}
}

51
model/wordpiece_test.go Normal file
View File

@@ -0,0 +1,51 @@
package model
import (
"slices"
"testing"
"github.com/google/go-cmp/cmp"
)
func TestWordPiece(t *testing.T) {
wpm := NewWordPiece(
&Vocabulary{
Values: []string{"[UNK]", "[CLS]", "[SEP]", "▁hello", "▁world", "s", "▁!", "▁@", "▁#"},
AddBOS: true,
AddEOS: true,
BOS: []int32{1},
EOS: []int32{2},
})
ids, err := wpm.Encode("Hello world!", true)
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff([]int32{1, 3, 4, 6, 2}, ids); diff != "" {
t.Errorf("unexpected ids (-want +got):\n%s", diff)
}
words, err := wpm.Decode(ids)
if err != nil {
t.Fatal(err)
}
if diff := cmp.Diff("[CLS] hello world! [SEP]", words); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
}
func TestWordPieceWords(t *testing.T) {
var wpm WordPiece
basic := slices.Collect(wpm.words("Hey friend! How are you?!?"))
if diff := cmp.Diff([]string{"Hey", "friend", "!", "How", "are", "you", "?", "!", "?"}, basic); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
chinese := slices.Collect(wpm.words("野口里佳 Noguchi Rika"))
if diff := cmp.Diff([]string{"野", "口", "里", "佳", "Noguchi", "Rika"}, chinese); diff != "" {
t.Errorf("unexpected words (-want +got):\n%s", diff)
}
}

View File

@@ -105,6 +105,7 @@ type ChatCompletionRequest struct {
Tools []api.Tool `json:"tools"` Tools []api.Tool `json:"tools"`
Reasoning *Reasoning `json:"reasoning,omitempty"` Reasoning *Reasoning `json:"reasoning,omitempty"`
ReasoningEffort *string `json:"reasoning_effort,omitempty"` ReasoningEffort *string `json:"reasoning_effort,omitempty"`
DebugRenderOnly bool `json:"_debug_render_only"`
} }
type ChatCompletion struct { type ChatCompletion struct {
@@ -115,6 +116,7 @@ type ChatCompletion struct {
SystemFingerprint string `json:"system_fingerprint"` SystemFingerprint string `json:"system_fingerprint"`
Choices []Choice `json:"choices"` Choices []Choice `json:"choices"`
Usage Usage `json:"usage,omitempty"` Usage Usage `json:"usage,omitempty"`
DebugInfo *api.DebugInfo `json:"_debug_info,omitempty"`
} }
type ChatCompletionChunk struct { type ChatCompletionChunk struct {
@@ -141,6 +143,7 @@ type CompletionRequest struct {
Temperature *float32 `json:"temperature"` Temperature *float32 `json:"temperature"`
TopP float32 `json:"top_p"` TopP float32 `json:"top_p"`
Suffix string `json:"suffix"` Suffix string `json:"suffix"`
DebugRenderOnly bool `json:"_debug_render_only"`
} }
type Completion struct { type Completion struct {
@@ -273,8 +276,8 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
} }
return nil return nil
}(r.DoneReason), }(r.DoneReason),
}}, }}, Usage: toUsage(r),
Usage: toUsage(r), DebugInfo: r.DebugInfo,
} }
} }
@@ -575,6 +578,7 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
Stream: &r.Stream, Stream: &r.Stream,
Tools: r.Tools, Tools: r.Tools,
Think: think, Think: think,
DebugRenderOnly: r.DebugRenderOnly,
}, nil }, nil
} }
@@ -653,6 +657,7 @@ func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
Options: options, Options: options,
Stream: &r.Stream, Stream: &r.Stream,
Suffix: r.Suffix, Suffix: r.Suffix,
DebugRenderOnly: r.DebugRenderOnly,
}, nil }, nil
} }

View File

@@ -100,6 +100,10 @@ func (f Modelfile) CreateRequest(relativeDir string) (*api.CreateRequest, error)
req.System = c.Args req.System = c.Args
case "license": case "license":
licenses = append(licenses, c.Args) licenses = append(licenses, c.Args)
case "renderer":
req.Renderer = c.Args
case "parser":
req.Parser = c.Args
case "message": case "message":
role, msg, _ := strings.Cut(c.Args, ": ") role, msg, _ := strings.Cut(c.Args, ": ")
messages = append(messages, api.Message{Role: role, Content: msg}) messages = append(messages, api.Message{Role: role, Content: msg})
@@ -320,7 +324,7 @@ func (c Command) String() string {
switch c.Name { switch c.Name {
case "model": case "model":
fmt.Fprintf(&sb, "FROM %s", c.Args) fmt.Fprintf(&sb, "FROM %s", c.Args)
case "license", "template", "system", "adapter": case "license", "template", "system", "adapter", "renderer", "parser":
fmt.Fprintf(&sb, "%s %s", strings.ToUpper(c.Name), quote(c.Args)) fmt.Fprintf(&sb, "%s %s", strings.ToUpper(c.Name), quote(c.Args))
case "message": case "message":
role, message, _ := strings.Cut(c.Args, ": ") role, message, _ := strings.Cut(c.Args, ": ")
@@ -346,7 +350,7 @@ const (
var ( var (
errMissingFrom = errors.New("no FROM line") errMissingFrom = errors.New("no FROM line")
errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"") errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"")
errInvalidCommand = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"") errInvalidCommand = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"renderer\", \"parser\", \"parameter\", or \"message\"")
) )
type ParserError struct { type ParserError struct {
@@ -606,7 +610,7 @@ func isValidMessageRole(role string) bool {
func isValidCommand(cmd string) bool { func isValidCommand(cmd string) bool {
switch strings.ToLower(cmd) { switch strings.ToLower(cmd) {
case "from", "license", "template", "system", "adapter", "parameter", "message": case "from", "license", "template", "system", "adapter", "renderer", "parser", "parameter", "message":
return true return true
default: default:
return false return false

View File

@@ -198,6 +198,34 @@ BADCOMMAND param1 value1
} }
} }
func TestParseFileRenderer(t *testing.T) {
input := `
FROM foo
RENDERER renderer1
`
reader := strings.NewReader(input)
modelfile, err := ParseFile(reader)
require.NoError(t, err)
assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "renderer", Args: "renderer1"}}, modelfile.Commands)
}
func TestParseFileParser(t *testing.T) {
input := `
FROM foo
PARSER parser1
`
reader := strings.NewReader(input)
modelfile, err := ParseFile(reader)
require.NoError(t, err)
assert.Equal(t, []Command{{Name: "model", Args: "foo"}, {Name: "parser", Args: "parser1"}}, modelfile.Commands)
}
func TestParseFileMessages(t *testing.T) { func TestParseFileMessages(t *testing.T) {
cases := []struct { cases := []struct {
input string input string

View File

@@ -204,13 +204,8 @@ func (c *InputCache) ShiftDiscard(inputLen int, numKeep int) int {
targetFree = max(targetFree, 1) targetFree = max(targetFree, 1)
currentFree := c.numCtx - inputLen currentFree := c.numCtx - inputLen
discard := targetFree - currentFree
if discard < 0 { return max(targetFree-currentFree, 0)
discard = 0
}
return discard
} }
type ErrReprocessInputs struct { type ErrReprocessInputs struct {

View File

@@ -242,13 +242,8 @@ func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
targetFree = max(targetFree, 1) targetFree = max(targetFree, 1)
currentFree := c.numCtx - inputLen currentFree := c.numCtx - inputLen
discard := targetFree - currentFree
if discard < 0 { return max(targetFree-currentFree, 0)
discard = 0
}
return discard
} }
type ErrReprocessInputs struct { type ErrReprocessInputs struct {

View File

@@ -11,7 +11,6 @@ import (
"image" "image"
"log" "log"
"log/slog" "log/slog"
"math"
"net" "net"
"net/http" "net/http"
"os" "os"
@@ -32,6 +31,7 @@ import (
"github.com/ollama/ollama/llm" "github.com/ollama/ollama/llm"
"github.com/ollama/ollama/logutil" "github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn/pooling"
"github.com/ollama/ollama/model" "github.com/ollama/ollama/model"
"github.com/ollama/ollama/model/input" "github.com/ollama/ollama/model/input"
"github.com/ollama/ollama/runner/common" "github.com/ollama/ollama/runner/common"
@@ -405,7 +405,7 @@ func (s *Server) removeSequence(seqIndex int, reason llm.DoneReason) {
func (s *Server) run(ctx context.Context) { func (s *Server) run(ctx context.Context) {
s.ready.Wait() s.ready.Wait()
supportsAsync := s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32 supportsAsync := pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone
var activeBatch batchState var activeBatch batchState
for { for {
@@ -467,6 +467,7 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
// Prepare the seqs and batch, but defer the input token values as we may not be ready yet // Prepare the seqs and batch, but defer the input token values as we may not be ready yet
var batchInputs []*input.Input var batchInputs []*input.Input
var batchOutputs []int32
var batch input.Batch var batch input.Batch
resumeSeq := -1 resumeSeq := -1
@@ -549,9 +550,9 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs))) batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
batch.Sequences = append(batch.Sequences, seq.cache.Id) batch.Sequences = append(batch.Sequences, seq.cache.Id)
seq.iBatch = len(batch.Outputs) seq.iBatch = len(batchOutputs)
if i+1 == len(seq.inputs) { if i+1 == len(seq.inputs) || seq.embeddingOnly {
batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1)) batchOutputs = append(batchOutputs, int32(len(batchInputs)-1))
} }
logutil.Trace("forwardBatch iBatch", "batchID", s.batchID, "seqIdx", seqIdx, "seq.iBatch", seq.iBatch, "i+1", i+1, "len(seq.inputs)", len(seq.inputs)) logutil.Trace("forwardBatch iBatch", "batchID", s.batchID, "seqIdx", seqIdx, "seq.iBatch", seq.iBatch, "i+1", i+1, "len(seq.inputs)", len(seq.inputs))
seq.pendingInputs = append(seq.pendingInputs, inp) seq.pendingInputs = append(seq.pendingInputs, inp)
@@ -576,6 +577,7 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
// Actual batchInputs values will be injected into the batch.Inputs tensor before calling Compute // Actual batchInputs values will be injected into the batch.Inputs tensor before calling Compute
batch.Inputs = nextBatch.ctx.Input().Empty(ml.DTypeI32, len(batchInputs)) batch.Inputs = nextBatch.ctx.Input().Empty(ml.DTypeI32, len(batchInputs))
batch.Outputs = nextBatch.ctx.Input().FromIntSlice(batchOutputs, len(batchOutputs))
nextBatch.modelOutput, err = model.Forward(nextBatch.ctx, s.model, batch) nextBatch.modelOutput, err = model.Forward(nextBatch.ctx, s.model, batch)
if err != nil { if err != nil {
err = fmt.Errorf("failed to build graph: %w", err) err = fmt.Errorf("failed to build graph: %w", err)
@@ -703,8 +705,8 @@ func (s *Server) computeBatch(activeBatch batchState) {
} }
// sample a token // sample a token
vocabSize := len(outputs) / len(activeBatch.batch.Outputs) vocabSize := len(outputs) / activeBatch.batch.Outputs.Dim(0)
logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", len(activeBatch.batch.Outputs), "vocabSize", vocabSize, "iBatches", iBatches) logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", activeBatch.batch.Outputs.Dim(0), "vocabSize", vocabSize, "iBatches", iBatches)
token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize]) token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize])
if err != nil { if err != nil {
s.hardErrCh <- fmt.Errorf("failed to sample token: %w", err) s.hardErrCh <- fmt.Errorf("failed to sample token: %w", err)
@@ -898,7 +900,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
} }
func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) { func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
if s.model.Backend().Config().Uint("pooling_type", math.MaxUint32) == math.MaxUint32 { if pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone {
http.Error(w, "this model does not support embeddings", http.StatusNotImplemented) http.Error(w, "this model does not support embeddings", http.StatusNotImplemented)
return return
} }
@@ -1046,12 +1048,8 @@ func (s *Server) reserveWorstCaseGraph() error {
batch.Positions[i] = int32(i) batch.Positions[i] = int32(i)
} }
batch.Outputs = make([]int32, s.parallel)
for i := range batch.Outputs {
batch.Outputs[i] = int32(i)
}
batch.Inputs = ctx.Input().FromIntSlice(batchInputs, len(batchInputs)) batch.Inputs = ctx.Input().FromIntSlice(batchInputs, len(batchInputs))
batch.Outputs = ctx.Input().Empty(ml.DTypeI32, s.parallel)
cache := s.model.Config().Cache cache := s.model.Config().Cache
if cache != nil { if cache != nil {

View File

@@ -16,6 +16,7 @@ OLLAMA_COMMON_BUILD_ARGS="--build-arg=VERSION \
--build-arg=OLLAMA_FAST_BUILD \ --build-arg=OLLAMA_FAST_BUILD \
--build-arg=CUSTOM_CPU_FLAGS \ --build-arg=CUSTOM_CPU_FLAGS \
--build-arg=GPU_RUNNER_CPU_FLAGS \ --build-arg=GPU_RUNNER_CPU_FLAGS \
--build-arg=PARALLEL \
--build-arg=AMDGPU_TARGETS" --build-arg=AMDGPU_TARGETS"
echo "Building Ollama" echo "Building Ollama"

View File

@@ -10,8 +10,11 @@ import (
"io" "io"
"io/fs" "io/fs"
"log/slog" "log/slog"
"net"
"net/http" "net/http"
"net/url"
"os" "os"
"path"
"path/filepath" "path/filepath"
"slices" "slices"
"strings" "strings"
@@ -39,6 +42,14 @@ var (
) )
func (s *Server) CreateHandler(c *gin.Context) { func (s *Server) CreateHandler(c *gin.Context) {
config := &ConfigV2{
OS: "linux",
Architecture: "amd64",
RootFS: RootFS{
Type: "layers",
},
}
var r api.CreateRequest var r api.CreateRequest
if err := c.ShouldBindJSON(&r); errors.Is(err, io.EOF) { if err := c.ShouldBindJSON(&r); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"}) c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
@@ -48,6 +59,9 @@ func (s *Server) CreateHandler(c *gin.Context) {
return return
} }
config.Renderer = r.Renderer
config.Parser = r.Parser
for v := range r.Files { for v := range r.Files {
if !fs.ValidPath(v) { if !fs.ValidPath(v) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": errFilePath.Error()}) c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": errFilePath.Error()})
@@ -77,14 +91,27 @@ func (s *Server) CreateHandler(c *gin.Context) {
oldManifest, _ := ParseNamedManifest(name) oldManifest, _ := ParseNamedManifest(name)
var baseLayers []*layerGGML var baseLayers []*layerGGML
var err error
var remote bool
if r.From != "" { if r.From != "" {
slog.Debug("create model from model name") slog.Debug("create model from model name", "from", r.From)
fromName := model.ParseName(r.From) fromName := model.ParseName(r.From)
if !fromName.IsValid() { if !fromName.IsValid() {
ch <- gin.H{"error": errtypes.InvalidModelNameErrMsg, "status": http.StatusBadRequest} ch <- gin.H{"error": errtypes.InvalidModelNameErrMsg, "status": http.StatusBadRequest}
return return
} }
if r.RemoteHost != "" {
ru, err := remoteURL(r.RemoteHost)
if err != nil {
ch <- gin.H{"error": "bad remote", "status": http.StatusBadRequest}
return
}
config.RemoteModel = r.From
config.RemoteHost = ru
remote = true
} else {
ctx, cancel := context.WithCancel(c.Request.Context()) ctx, cancel := context.WithCancel(c.Request.Context())
defer cancel() defer cancel()
@@ -92,6 +119,7 @@ func (s *Server) CreateHandler(c *gin.Context) {
if err != nil { if err != nil {
ch <- gin.H{"error": err.Error()} ch <- gin.H{"error": err.Error()}
} }
}
} else if r.Files != nil { } else if r.Files != nil {
baseLayers, err = convertModelFromFiles(r.Files, baseLayers, false, fn) baseLayers, err = convertModelFromFiles(r.Files, baseLayers, false, fn)
if err != nil { if err != nil {
@@ -110,7 +138,7 @@ func (s *Server) CreateHandler(c *gin.Context) {
} }
var adapterLayers []*layerGGML var adapterLayers []*layerGGML
if r.Adapters != nil { if !remote && r.Adapters != nil {
adapterLayers, err = convertModelFromFiles(r.Adapters, baseLayers, true, fn) adapterLayers, err = convertModelFromFiles(r.Adapters, baseLayers, true, fn)
if err != nil { if err != nil {
for _, badReq := range []error{errNoFilesProvided, errOnlyOneAdapterSupported, errOnlyGGUFSupported, errUnknownType, errFilePath} { for _, badReq := range []error{errNoFilesProvided, errOnlyOneAdapterSupported, errOnlyGGUFSupported, errUnknownType, errFilePath} {
@@ -128,7 +156,56 @@ func (s *Server) CreateHandler(c *gin.Context) {
baseLayers = append(baseLayers, adapterLayers...) baseLayers = append(baseLayers, adapterLayers...)
} }
if err := createModel(r, name, baseLayers, fn); err != nil { // Info is not currently exposed by Modelfiles, but allows overriding various
// config values
if r.Info != nil {
caps, ok := r.Info["capabilities"]
if ok {
switch tcaps := caps.(type) {
case []any:
caps := make([]string, len(tcaps))
for i, c := range tcaps {
str, ok := c.(string)
if !ok {
continue
}
caps[i] = str
}
config.Capabilities = append(config.Capabilities, caps...)
}
}
strFromInfo := func(k string) string {
v, ok := r.Info[k]
if ok {
val := v.(string)
return val
}
return ""
}
vFromInfo := func(k string) float64 {
v, ok := r.Info[k]
if ok {
val := v.(float64)
return val
}
return 0
}
config.ModelFamily = strFromInfo("model_family")
if config.ModelFamily != "" {
config.ModelFamilies = []string{config.ModelFamily}
}
config.BaseName = strFromInfo("base_name")
config.FileType = strFromInfo("quantization_level")
config.ModelType = strFromInfo("parameter_size")
config.ContextLen = int(vFromInfo("context_length"))
config.EmbedLen = int(vFromInfo("embedding_length"))
}
if err := createModel(r, name, baseLayers, config, fn); err != nil {
if errors.Is(err, errBadTemplate) { if errors.Is(err, errBadTemplate) {
ch <- gin.H{"error": err.Error(), "status": http.StatusBadRequest} ch <- gin.H{"error": err.Error(), "status": http.StatusBadRequest}
return return
@@ -154,6 +231,51 @@ func (s *Server) CreateHandler(c *gin.Context) {
streamResponse(c, ch) streamResponse(c, ch)
} }
func remoteURL(raw string) (string, error) {
// Specialcase: user supplied only a path ("/foo/bar").
if strings.HasPrefix(raw, "/") {
return (&url.URL{
Scheme: "http",
Host: net.JoinHostPort("localhost", "11434"),
Path: path.Clean(raw),
}).String(), nil
}
if !strings.Contains(raw, "://") {
raw = "http://" + raw
}
if raw == "ollama.com" || raw == "http://ollama.com" {
raw = "https://ollama.com:443"
}
u, err := url.Parse(raw)
if err != nil {
return "", fmt.Errorf("parse error: %w", err)
}
if u.Host == "" {
u.Host = "localhost"
}
hostPart, portPart, err := net.SplitHostPort(u.Host)
if err == nil {
u.Host = net.JoinHostPort(hostPart, portPart)
} else {
u.Host = net.JoinHostPort(u.Host, "11434")
}
if u.Path != "" {
u.Path = path.Clean(u.Path)
}
if u.Path == "/" {
u.Path = ""
}
return u.String(), nil
}
func convertModelFromFiles(files map[string]string, baseLayers []*layerGGML, isAdapter bool, fn func(resp api.ProgressResponse)) ([]*layerGGML, error) { func convertModelFromFiles(files map[string]string, baseLayers []*layerGGML, isAdapter bool, fn func(resp api.ProgressResponse)) ([]*layerGGML, error) {
switch detectModelTypeFromFiles(files) { switch detectModelTypeFromFiles(files) {
case "safetensors": case "safetensors":
@@ -316,15 +438,7 @@ func kvFromLayers(baseLayers []*layerGGML) (ggml.KV, error) {
return ggml.KV{}, fmt.Errorf("no base model was found") return ggml.KV{}, fmt.Errorf("no base model was found")
} }
func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, fn func(resp api.ProgressResponse)) (err error) { func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML, config *ConfigV2, fn func(resp api.ProgressResponse)) (err error) {
config := ConfigV2{
OS: "linux",
Architecture: "amd64",
RootFS: RootFS{
Type: "layers",
},
}
var layers []Layer var layers []Layer
for _, layer := range baseLayers { for _, layer := range baseLayers {
if layer.GGML != nil { if layer.GGML != nil {
@@ -404,7 +518,7 @@ func createModel(r api.CreateRequest, name model.Name, baseLayers []*layerGGML,
return err return err
} }
configLayer, err := createConfigLayer(layers, config) configLayer, err := createConfigLayer(layers, *config)
if err != nil { if err != nil {
return err return err
} }

View File

@@ -104,3 +104,154 @@ func TestConvertFromSafetensors(t *testing.T) {
}) })
} }
} }
func TestRemoteURL(t *testing.T) {
tests := []struct {
name string
input string
expected string
hasError bool
}{
{
name: "absolute path",
input: "/foo/bar",
expected: "http://localhost:11434/foo/bar",
hasError: false,
},
{
name: "absolute path with cleanup",
input: "/foo/../bar",
expected: "http://localhost:11434/bar",
hasError: false,
},
{
name: "root path",
input: "/",
expected: "http://localhost:11434/",
hasError: false,
},
{
name: "host without scheme",
input: "example.com",
expected: "http://example.com:11434",
hasError: false,
},
{
name: "host with port",
input: "example.com:8080",
expected: "http://example.com:8080",
hasError: false,
},
{
name: "full URL",
input: "https://example.com:8080/path",
expected: "https://example.com:8080/path",
hasError: false,
},
{
name: "full URL with path cleanup",
input: "https://example.com:8080/path/../other",
expected: "https://example.com:8080/other",
hasError: false,
},
{
name: "ollama.com special case",
input: "ollama.com",
expected: "https://ollama.com:443",
hasError: false,
},
{
name: "http ollama.com special case",
input: "http://ollama.com",
expected: "https://ollama.com:443",
hasError: false,
},
{
name: "URL with only host",
input: "http://example.com",
expected: "http://example.com:11434",
hasError: false,
},
{
name: "URL with root path cleaned",
input: "http://example.com/",
expected: "http://example.com:11434",
hasError: false,
},
{
name: "invalid URL",
input: "http://[::1]:namedport", // invalid port
expected: "",
hasError: true,
},
{
name: "empty string",
input: "",
expected: "http://localhost:11434",
hasError: false,
},
{
name: "host with scheme but no port",
input: "http://localhost",
expected: "http://localhost:11434",
hasError: false,
},
{
name: "complex path cleanup",
input: "/a/b/../../c/./d",
expected: "http://localhost:11434/c/d",
hasError: false,
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result, err := remoteURL(tt.input)
if tt.hasError {
if err == nil {
t.Errorf("expected error but got none")
}
return
}
if err != nil {
t.Errorf("unexpected error: %v", err)
return
}
if result != tt.expected {
t.Errorf("expected %q, got %q", tt.expected, result)
}
})
}
}
func TestRemoteURL_Idempotent(t *testing.T) {
// Test that applying remoteURL twice gives the same result as applying it once
testInputs := []string{
"/foo/bar",
"example.com",
"https://example.com:8080/path",
"ollama.com",
"http://localhost:11434",
}
for _, input := range testInputs {
t.Run(input, func(t *testing.T) {
firstResult, err := remoteURL(input)
if err != nil {
t.Fatalf("first call failed: %v", err)
}
secondResult, err := remoteURL(firstResult)
if err != nil {
t.Fatalf("second call failed: %v", err)
}
if firstResult != secondResult {
t.Errorf("function is not idempotent: first=%q, second=%q", firstResult, secondResult)
}
})
}
}

View File

@@ -24,6 +24,7 @@ import (
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig" "github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/fs/gguf" "github.com/ollama/ollama/fs/gguf"
"github.com/ollama/ollama/model/parsers"
"github.com/ollama/ollama/parser" "github.com/ollama/ollama/parser"
"github.com/ollama/ollama/template" "github.com/ollama/ollama/template"
"github.com/ollama/ollama/thinking" "github.com/ollama/ollama/thinking"
@@ -73,6 +74,7 @@ func (m *Model) Capabilities() []model.Capability {
capabilities := []model.Capability{} capabilities := []model.Capability{}
// Check for completion capability // Check for completion capability
if m.ModelPath != "" {
f, err := gguf.Open(m.ModelPath) f, err := gguf.Open(m.ModelPath)
if err == nil { if err == nil {
defer f.Close() defer f.Close()
@@ -89,13 +91,21 @@ func (m *Model) Capabilities() []model.Capability {
} else { } else {
slog.Error("couldn't open model file", "error", err) slog.Error("couldn't open model file", "error", err)
} }
} else if len(m.Config.Capabilities) > 0 {
for _, c := range m.Config.Capabilities {
capabilities = append(capabilities, model.Capability(c))
}
} else {
slog.Warn("unknown capabilities for model", "model", m.Name)
}
if m.Template == nil { if m.Template == nil {
return capabilities return capabilities
} }
builtinParser := parsers.ParserForName(m.Config.Parser)
// Check for tools capability // Check for tools capability
if slices.Contains(m.Template.Vars(), "tools") { if slices.Contains(m.Template.Vars(), "tools") || (builtinParser != nil && builtinParser.HasToolSupport()) {
capabilities = append(capabilities, model.CapabilityTools) capabilities = append(capabilities, model.CapabilityTools)
} }
@@ -109,10 +119,16 @@ func (m *Model) Capabilities() []model.Capability {
capabilities = append(capabilities, model.CapabilityVision) capabilities = append(capabilities, model.CapabilityVision)
} }
// Skip the thinking check if it's already set
if slices.Contains(capabilities, "thinking") {
return capabilities
}
// Check for thinking capability // Check for thinking capability
openingTag, closingTag := thinking.InferTags(m.Template.Template) openingTag, closingTag := thinking.InferTags(m.Template.Template)
hasTags := openingTag != "" && closingTag != "" hasTags := openingTag != "" && closingTag != ""
if hasTags || slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily) { isGptoss := slices.Contains([]string{"gptoss", "gpt-oss"}, m.Config.ModelFamily)
if hasTags || isGptoss || (builtinParser != nil && builtinParser.HasThinkingSupport()) {
capabilities = append(capabilities, model.CapabilityThinking) capabilities = append(capabilities, model.CapabilityThinking)
} }
@@ -198,6 +214,20 @@ func (m *Model) String() string {
}) })
} }
if m.Config.Renderer != "" {
modelfile.Commands = append(modelfile.Commands, parser.Command{
Name: "renderer",
Args: m.Config.Renderer,
})
}
if m.Config.Parser != "" {
modelfile.Commands = append(modelfile.Commands, parser.Command{
Name: "parser",
Args: m.Config.Parser,
})
}
for k, v := range m.Options { for k, v := range m.Options {
switch v := v.(type) { switch v := v.(type) {
case []any: case []any:
@@ -236,8 +266,19 @@ type ConfigV2 struct {
ModelFormat string `json:"model_format"` ModelFormat string `json:"model_format"`
ModelFamily string `json:"model_family"` ModelFamily string `json:"model_family"`
ModelFamilies []string `json:"model_families"` ModelFamilies []string `json:"model_families"`
ModelType string `json:"model_type"` ModelType string `json:"model_type"` // shown as Parameter Size
FileType string `json:"file_type"` FileType string `json:"file_type"` // shown as Quantization Level
Renderer string `json:"renderer,omitempty"`
Parser string `json:"parser,omitempty"`
RemoteHost string `json:"remote_host,omitempty"`
RemoteModel string `json:"remote_model,omitempty"`
// used for remotes
Capabilities []string `json:"capabilities,omitempty"`
ContextLen int `json:"context_length,omitempty"`
EmbedLen int `json:"embedding_length,omitempty"`
BaseName string `json:"base_name,omitempty"`
// required by spec // required by spec
Architecture string `json:"architecture"` Architecture string `json:"architecture"`

View File

@@ -25,10 +25,7 @@ func Loop(ctx context.Context, maxBackoff time.Duration) iter.Seq2[int, error] {
// n^2 backoff timer is a little smoother than the // n^2 backoff timer is a little smoother than the
// common choice of 2^n. // common choice of 2^n.
d := time.Duration(n*n) * 10 * time.Millisecond d := min(time.Duration(n*n)*10*time.Millisecond, maxBackoff)
if d > maxBackoff {
d = maxBackoff
}
// Randomize the delay between 0.5-1.5 x msec, in order // Randomize the delay between 0.5-1.5 x msec, in order
// to prevent accidental "thundering herd" problems. // to prevent accidental "thundering herd" problems.
d = time.Duration(float64(d) * (rand.Float64() + 0.5)) d = time.Duration(float64(d) * (rand.Float64() + 0.5))

View File

@@ -11,6 +11,7 @@ import (
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
"github.com/ollama/ollama/llm" "github.com/ollama/ollama/llm"
"github.com/ollama/ollama/model/renderers"
"github.com/ollama/ollama/template" "github.com/ollama/ollama/template"
) )
@@ -41,18 +42,12 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
} }
} }
thinkVal := false p, err := renderPrompt(m, append(system, msgs[i:]...), tools, think)
thinkLevel := "" if err != nil {
if think != nil {
thinkVal = think.Bool()
thinkLevel = think.String()
}
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
return "", nil, err return "", nil, err
} }
s, err := tokenize(ctx, b.String()) s, err := tokenize(ctx, p)
if err != nil { if err != nil {
return "", nil, err return "", nil, err
} }
@@ -101,6 +96,23 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
} }
// truncate any messages that do not fit into the context window // truncate any messages that do not fit into the context window
p, err := renderPrompt(m, append(system, msgs[currMsgIdx:]...), tools, think)
if err != nil {
return "", nil, err
}
return p, images, nil
}
func renderPrompt(m *Model, msgs []api.Message, tools []api.Tool, think *api.ThinkValue) (string, error) {
if m.Config.Renderer != "" {
rendered, err := renderers.RenderWithRenderer(m.Config.Renderer, msgs, tools, think)
if err != nil {
return "", err
}
return rendered, nil
}
var b bytes.Buffer var b bytes.Buffer
thinkVal := false thinkVal := false
thinkLevel := "" thinkLevel := ""
@@ -108,9 +120,8 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
thinkVal = think.Bool() thinkVal = think.Bool()
thinkLevel = think.String() thinkLevel = think.String()
} }
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[currMsgIdx:]...), Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil { if err := m.Template.Execute(&b, template.Values{Messages: msgs, Tools: tools, Think: thinkVal, ThinkLevel: thinkLevel, IsThinkSet: think != nil}); err != nil {
return "", nil, err return "", err
} }
return b.String(), nil
return b.String(), images, nil
} }

View File

@@ -15,6 +15,7 @@ import (
"net" "net"
"net/http" "net/http"
"net/netip" "net/netip"
"net/url"
"os" "os"
"os/signal" "os/signal"
"slices" "slices"
@@ -28,6 +29,7 @@ import (
"golang.org/x/sync/errgroup" "golang.org/x/sync/errgroup"
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
"github.com/ollama/ollama/auth"
"github.com/ollama/ollama/discover" "github.com/ollama/ollama/discover"
"github.com/ollama/ollama/envconfig" "github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format" "github.com/ollama/ollama/format"
@@ -35,6 +37,7 @@ import (
"github.com/ollama/ollama/harmony" "github.com/ollama/ollama/harmony"
"github.com/ollama/ollama/llm" "github.com/ollama/ollama/llm"
"github.com/ollama/ollama/logutil" "github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/model/parsers"
"github.com/ollama/ollama/openai" "github.com/ollama/ollama/openai"
"github.com/ollama/ollama/server/internal/client/ollama" "github.com/ollama/ollama/server/internal/client/ollama"
"github.com/ollama/ollama/server/internal/registry" "github.com/ollama/ollama/server/internal/registry"
@@ -188,6 +191,87 @@ func (s *Server) GenerateHandler(c *gin.Context) {
return return
} }
if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
origModel := req.Model
remoteURL, err := url.Parse(m.Config.RemoteHost)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
return
}
req.Model = m.Config.RemoteModel
if req.Template == "" && m.Template.String() != "" {
req.Template = m.Template.String()
}
if req.Options == nil {
req.Options = map[string]any{}
}
for k, v := range m.Options {
if _, ok := req.Options[k]; !ok {
req.Options[k] = v
}
}
// update the system prompt from the model if one isn't already specified
if req.System == "" && m.System != "" {
req.System = m.System
}
if len(m.Messages) > 0 {
slog.Warn("embedded messages in the model not supported with '/api/generate'; try '/api/chat' instead")
}
fn := func(resp api.GenerateResponse) error {
resp.Model = origModel
resp.RemoteModel = m.Config.RemoteModel
resp.RemoteHost = m.Config.RemoteHost
data, err := json.Marshal(resp)
if err != nil {
return err
}
if _, err = c.Writer.Write(append(data, '\n')); err != nil {
return err
}
c.Writer.Flush()
return nil
}
client := api.NewClient(remoteURL, http.DefaultClient)
err = client.Generate(c, &req, fn)
if err != nil {
var sErr api.AuthorizationError
if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
pk, pkErr := auth.GetPublicKey()
if pkErr != nil {
slog.Error("couldn't get public key", "error", pkErr)
c.JSON(http.StatusUnauthorized, gin.H{"error": "error getting public key"})
return
}
c.JSON(http.StatusUnauthorized, gin.H{
"error": "unauthorized",
"public_key": pk,
})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
return
}
// expire the runner // expire the runner
if req.Prompt == "" && req.KeepAlive != nil && req.KeepAlive.Duration == 0 { if req.Prompt == "" && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
s.sched.expireRunner(m) s.sched.expireRunner(m)
@@ -329,10 +413,10 @@ func (s *Server) GenerateHandler(c *gin.Context) {
// If debug mode is enabled, return the rendered template instead of calling the model // If debug mode is enabled, return the rendered template instead of calling the model
if req.DebugRenderOnly { if req.DebugRenderOnly {
c.JSON(http.StatusOK, api.DebugTemplateResponse{ c.JSON(http.StatusOK, api.GenerateResponse{
Model: req.Model, Model: req.Model,
CreatedAt: time.Now().UTC(), CreatedAt: time.Now().UTC(),
DebugInfo: api.DebugInfo{ DebugInfo: &api.DebugInfo{
RenderedTemplate: prompt, RenderedTemplate: prompt,
ImageCount: len(images), ImageCount: len(images),
}, },
@@ -348,6 +432,9 @@ func (s *Server) GenerateHandler(c *gin.Context) {
OpeningTag: openingTag, OpeningTag: openingTag,
ClosingTag: closingTag, ClosingTag: closingTag,
} }
if strings.HasSuffix(strings.TrimSpace(prompt), openingTag) {
thinkingState.AddContent(openingTag)
}
} }
} }
@@ -488,7 +575,6 @@ func (s *Server) EmbedHandler(c *gin.Context) {
} }
truncate := true truncate := true
if req.Truncate != nil && !*req.Truncate { if req.Truncate != nil && !*req.Truncate {
truncate = false truncate = false
} }
@@ -551,11 +637,27 @@ func (s *Server) EmbedHandler(c *gin.Context) {
ctxLen := min(opts.NumCtx, int(kvData.ContextLength())) ctxLen := min(opts.NumCtx, int(kvData.ContextLength()))
if len(tokens) > ctxLen { if len(tokens) > ctxLen {
if !truncate { if !truncate {
c.JSON(http.StatusBadRequest, gin.H{"error": "input length exceeds maximum context length"}) c.JSON(http.StatusBadRequest, gin.H{"error": "input exceeds maximum context length"})
return
}
if bos := kvData.Uint("tokenizer.ggml.bos_token_id"); tokens[0] != int(bos) && kvData.Bool("add_bos_token", true) {
ctxLen--
}
if eos := kvData.Uint("tokenizer.ggml.eos_token_id"); tokens[len(tokens)-1] != int(eos) && kvData.Bool("add_eos_token", true) {
ctxLen--
}
slog.Info("", "ctxLen", ctxLen, "tokenCount", len(tokens))
if ctxLen <= 0 {
// return error if the truncated input would be empty or just special tokens
c.JSON(http.StatusBadRequest, gin.H{"error": "input after truncation exceeds maximum context length"})
return return
} }
tokens = tokens[:ctxLen] tokens = tokens[:ctxLen]
s, err = r.Detokenize(c.Request.Context(), tokens) s, err = r.Detokenize(c.Request.Context(), tokens)
if err != nil { if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()}) c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
@@ -922,6 +1024,28 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
ModifiedAt: manifest.fi.ModTime(), ModifiedAt: manifest.fi.ModTime(),
} }
if m.Config.RemoteHost != "" {
resp.RemoteHost = m.Config.RemoteHost
resp.RemoteModel = m.Config.RemoteModel
if m.Config.ModelFamily != "" {
resp.ModelInfo = make(map[string]any)
resp.ModelInfo["general.architecture"] = m.Config.ModelFamily
if m.Config.BaseName != "" {
resp.ModelInfo["general.basename"] = m.Config.BaseName
}
if m.Config.ContextLen > 0 {
resp.ModelInfo[fmt.Sprintf("%s.context_length", m.Config.ModelFamily)] = m.Config.ContextLen
}
if m.Config.EmbedLen > 0 {
resp.ModelInfo[fmt.Sprintf("%s.embedding_length", m.Config.ModelFamily)] = m.Config.EmbedLen
}
}
}
var params []string var params []string
cs := 30 cs := 30
for k, v := range m.Options { for k, v := range m.Options {
@@ -952,6 +1076,11 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
fmt.Fprint(&sb, m.String()) fmt.Fprint(&sb, m.String())
resp.Modelfile = sb.String() resp.Modelfile = sb.String()
// skip loading tensor information if this is a remote model
if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
return resp, nil
}
kvData, tensors, err := getModelData(m.ModelPath, req.Verbose) kvData, tensors, err := getModelData(m.ModelPath, req.Verbose)
if err != nil { if err != nil {
return nil, err return nil, err
@@ -1030,6 +1159,8 @@ func (s *Server) ListHandler(c *gin.Context) {
models = append(models, api.ListModelResponse{ models = append(models, api.ListModelResponse{
Model: n.DisplayShortest(), Model: n.DisplayShortest(),
Name: n.DisplayShortest(), Name: n.DisplayShortest(),
RemoteModel: cf.RemoteModel,
RemoteHost: cf.RemoteHost,
Size: m.Size(), Size: m.Size(),
Digest: m.digest, Digest: m.digest,
ModifiedAt: m.fi.ModTime(), ModifiedAt: m.fi.ModTime(),
@@ -1292,6 +1423,9 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
r.POST("/api/show", s.ShowHandler) r.POST("/api/show", s.ShowHandler)
r.DELETE("/api/delete", s.DeleteHandler) r.DELETE("/api/delete", s.DeleteHandler)
r.DELETE("/api/user/keys/:encodedKey", s.SignoutHandler)
r.POST("/api/me", s.WhoamiHandler)
// Create // Create
r.POST("/api/create", s.CreateHandler) r.POST("/api/create", s.CreateHandler)
r.POST("/api/blobs/:digest", s.CreateBlobHandler) r.POST("/api/blobs/:digest", s.CreateBlobHandler)
@@ -1488,6 +1622,49 @@ func streamResponse(c *gin.Context, ch chan any) {
}) })
} }
func (s *Server) WhoamiHandler(c *gin.Context) {
// todo allow other hosts
u, err := url.Parse("https://ollama.com")
if err != nil {
slog.Error(err.Error())
c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
return
}
client := api.NewClient(u, http.DefaultClient)
user, err := client.Whoami(c)
if err != nil {
slog.Error(err.Error())
}
c.JSON(http.StatusOK, user)
}
func (s *Server) SignoutHandler(c *gin.Context) {
encodedKey := c.Param("encodedKey")
// todo allow other hosts
u, err := url.Parse("https://ollama.com")
if err != nil {
slog.Error(err.Error())
c.JSON(http.StatusInternalServerError, gin.H{"error": "URL parse error"})
return
}
client := api.NewClient(u, http.DefaultClient)
err = client.Signout(c, encodedKey)
if err != nil {
slog.Error(err.Error())
if strings.Contains(err.Error(), "page not found") || strings.Contains(err.Error(), "invalid credentials") {
c.JSON(http.StatusNotFound, gin.H{"error": "you are not currently signed in"})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": "there was an error signing out"})
return
}
c.JSON(http.StatusOK, nil)
}
func (s *Server) PsHandler(c *gin.Context) { func (s *Server) PsHandler(c *gin.Context) {
models := []api.ProcessModelResponse{} models := []api.ProcessModelResponse{}
@@ -1544,9 +1721,19 @@ func (s *Server) ChatHandler(c *gin.Context) {
return return
} }
// expire the runner name := model.ParseName(req.Model)
if len(req.Messages) == 0 && req.KeepAlive != nil && req.KeepAlive.Duration == 0 { if !name.IsValid() {
model, err := GetModel(req.Model) c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
}
name, err := getExistingName(name)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
}
m, err := GetModel(req.Model)
if err != nil { if err != nil {
switch { switch {
case os.IsNotExist(err): case os.IsNotExist(err):
@@ -1558,7 +1745,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
} }
return return
} }
s.sched.expireRunner(model)
// expire the runner
if len(req.Messages) == 0 && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
s.sched.expireRunner(m)
c.JSON(http.StatusOK, api.ChatResponse{ c.JSON(http.StatusOK, api.ChatResponse{
Model: req.Model, Model: req.Model,
@@ -1570,6 +1760,80 @@ func (s *Server) ChatHandler(c *gin.Context) {
return return
} }
if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
origModel := req.Model
remoteURL, err := url.Parse(m.Config.RemoteHost)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if !slices.Contains(envconfig.Remotes(), remoteURL.Hostname()) {
slog.Info("remote model", "remotes", envconfig.Remotes(), "remoteURL", m.Config.RemoteHost, "hostname", remoteURL.Hostname())
c.JSON(http.StatusBadRequest, gin.H{"error": "this server cannot run this remote model"})
return
}
req.Model = m.Config.RemoteModel
if req.Options == nil {
req.Options = map[string]any{}
}
msgs := append(m.Messages, req.Messages...)
if req.Messages[0].Role != "system" && m.System != "" {
msgs = append([]api.Message{{Role: "system", Content: m.System}}, msgs...)
}
msgs = filterThinkTags(msgs, m)
req.Messages = msgs
for k, v := range m.Options {
if _, ok := req.Options[k]; !ok {
req.Options[k] = v
}
}
fn := func(resp api.ChatResponse) error {
resp.Model = origModel
resp.RemoteModel = m.Config.RemoteModel
resp.RemoteHost = m.Config.RemoteHost
data, err := json.Marshal(resp)
if err != nil {
return err
}
if _, err = c.Writer.Write(append(data, '\n')); err != nil {
return err
}
c.Writer.Flush()
return nil
}
client := api.NewClient(remoteURL, http.DefaultClient)
err = client.Chat(c, &req, fn)
if err != nil {
var sErr api.AuthorizationError
if errors.As(err, &sErr) && sErr.StatusCode == http.StatusUnauthorized {
pk, pkErr := auth.GetPublicKey()
if pkErr != nil {
slog.Error("couldn't get public key", "error", pkErr)
c.JSON(http.StatusUnauthorized, gin.H{"error": "error getting public key"})
return
}
c.JSON(http.StatusUnauthorized, gin.H{
"error": "unauthorized",
"public_key": pk,
})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
return
}
caps := []model.Capability{model.CapabilityCompletion} caps := []model.Capability{model.CapabilityCompletion}
if len(req.Tools) > 0 { if len(req.Tools) > 0 {
caps = append(caps, model.CapabilityTools) caps = append(caps, model.CapabilityTools)
@@ -1578,17 +1842,6 @@ func (s *Server) ChatHandler(c *gin.Context) {
caps = append(caps, model.CapabilityThinking) caps = append(caps, model.CapabilityThinking)
} }
name := model.ParseName(req.Model)
if !name.IsValid() {
c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
}
name, err := getExistingName(name)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
}
r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive) r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
if errors.Is(err, errCapabilityCompletion) { if errors.Is(err, errCapabilityCompletion) {
c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support chat", req.Model)}) c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support chat", req.Model)})
@@ -1617,10 +1870,15 @@ func (s *Server) ChatHandler(c *gin.Context) {
} }
msgs = filterThinkTags(msgs, m) msgs = filterThinkTags(msgs, m)
var builtinParser parsers.Parser
if m.Config.Parser != "" {
builtinParser = parsers.ParserForName(m.Config.Parser)
}
var harmonyMessageHandler *harmony.HarmonyMessageHandler var harmonyMessageHandler *harmony.HarmonyMessageHandler
var harmonyToolParser *harmony.HarmonyToolCallAccumulator var harmonyToolParser *harmony.HarmonyToolCallAccumulator
useHarmony := shouldUseHarmony(m) useHarmony := shouldUseHarmony(m) || m.Config.Parser == "harmony"
processedTools := req.Tools processedTools := req.Tools
if useHarmony { if useHarmony {
@@ -1650,10 +1908,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
// If debug mode is enabled, return the rendered template instead of calling the model // If debug mode is enabled, return the rendered template instead of calling the model
if req.DebugRenderOnly { if req.DebugRenderOnly {
c.JSON(http.StatusOK, api.DebugTemplateResponse{ c.JSON(http.StatusOK, api.ChatResponse{
Model: req.Model, Model: req.Model,
CreatedAt: time.Now().UTC(), CreatedAt: time.Now().UTC(),
DebugInfo: api.DebugInfo{ DebugInfo: &api.DebugInfo{
RenderedTemplate: prompt, RenderedTemplate: prompt,
ImageCount: len(images), ImageCount: len(images),
}, },
@@ -1713,6 +1971,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
res.LoadDuration = checkpointLoaded.Sub(checkpointStart) res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
} }
// TODO(drifkin): fold this as much as possibleinto the generic m.Config.Parser logic
if useHarmony { if useHarmony {
content, thinking, toolContent := harmonyMessageHandler.AddContent(r.Content, harmonyToolParser) content, thinking, toolContent := harmonyMessageHandler.AddContent(r.Content, harmonyToolParser)
res.Message.Content = content res.Message.Content = content
@@ -1739,6 +1998,27 @@ func (s *Server) ChatHandler(c *gin.Context) {
ch <- res ch <- res
} }
return
} else if builtinParser != nil {
slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser input", "parser", m.Config.Parser, "content", r.Content)
content, thinking, toolCalls, err := builtinParser.Add(r.Content, req.Tools)
if err != nil {
ch <- gin.H{"error": err.Error()}
return
}
res.Message.Content = content
res.Message.Thinking = thinking
res.Message.ToolCalls = toolCalls
if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || r.Done {
slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser output", "parser", m.Config.Parser, "content", content, "thinking", thinking, "toolCalls", toolCalls, "done", r.Done)
ch <- res
} else {
slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser empty output", "parser", m.Config.Parser)
}
return return
} }

View File

@@ -11,6 +11,7 @@ import (
"net/http/httptest" "net/http/httptest"
"os" "os"
"path/filepath" "path/filepath"
"reflect"
"slices" "slices"
"strings" "strings"
"testing" "testing"
@@ -20,6 +21,7 @@ import (
"github.com/ollama/ollama/api" "github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig" "github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/fs/ggml" "github.com/ollama/ollama/fs/ggml"
"github.com/ollama/ollama/types/model"
) )
var stream bool = false var stream bool = false
@@ -615,6 +617,78 @@ func TestCreateTemplateSystem(t *testing.T) {
}) })
} }
func TestCreateAndShowRemoteModel(t *testing.T) {
gin.SetMode(gin.TestMode)
var s Server
w := createRequest(t, s.CreateHandler, api.CreateRequest{
Model: "test",
From: "bob",
RemoteHost: "https://ollama.com",
Info: map[string]any{
"capabilities": []string{"completion", "tools", "thinking"},
"model_family": "gptoss",
"context_length": 131072,
"embedding_length": 2880,
"quantization_level": "MXFP4",
"parameter_size": "20.9B",
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("exected status code 200, actual %d", w.Code)
}
w = createRequest(t, s.ShowHandler, api.ShowRequest{Model: "test"})
if w.Code != http.StatusOK {
t.Fatalf("exected status code 200, actual %d", w.Code)
}
var resp api.ShowResponse
if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
t.Fatal(err)
}
expectedDetails := api.ModelDetails{
ParentModel: "",
Format: "",
Family: "gptoss",
Families: []string{"gptoss"},
ParameterSize: "20.9B",
QuantizationLevel: "MXFP4",
}
if !reflect.DeepEqual(resp.Details, expectedDetails) {
t.Errorf("model details: expected %#v, actual %#v", expectedDetails, resp.Details)
}
expectedCaps := []model.Capability{
model.Capability("completion"),
model.Capability("tools"),
model.Capability("thinking"),
}
if !slices.Equal(resp.Capabilities, expectedCaps) {
t.Errorf("capabilities: expected %#v, actual %#v", expectedCaps, resp.Capabilities)
}
v, ok := resp.ModelInfo["gptoss.context_length"]
ctxlen := v.(float64)
if !ok || int(ctxlen) != 131072 {
t.Errorf("context len: expected %d, actual %d", 131072, int(ctxlen))
}
v, ok = resp.ModelInfo["gptoss.embedding_length"]
embedlen := v.(float64)
if !ok || int(embedlen) != 2880 {
t.Errorf("embed len: expected %d, actual %d", 2880, int(embedlen))
}
fmt.Printf("resp = %#v\n", resp)
}
func TestCreateLicenses(t *testing.T) { func TestCreateLicenses(t *testing.T) {
gin.SetMode(gin.TestMode) gin.SetMode(gin.TestMode)

View File

@@ -180,7 +180,7 @@ func TestGenerateDebugRenderOnly(t *testing.T) {
t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String()) t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
} }
var response api.DebugTemplateResponse var response api.GenerateResponse
if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil { if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
t.Fatalf("failed to unmarshal response: %v", err) t.Fatalf("failed to unmarshal response: %v", err)
} }
@@ -385,7 +385,7 @@ func TestChatDebugRenderOnly(t *testing.T) {
t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String()) t.Errorf("expected status %d, got %d, body: %s", http.StatusOK, w.Code, w.Body.String())
} }
var response api.DebugTemplateResponse var response api.ChatResponse
if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil { if err := json.Unmarshal(w.Body.Bytes(), &response); err != nil {
t.Fatalf("failed to unmarshal response: %v", err) t.Fatalf("failed to unmarshal response: %v", err)
} }

View File

@@ -126,7 +126,15 @@ func TestRoutes(t *testing.T) {
t.Fatalf("failed to create model: %v", err) t.Fatalf("failed to create model: %v", err)
} }
if err := createModel(r, modelName, baseLayers, fn); err != nil { config := &ConfigV2{
OS: "linux",
Architecture: "amd64",
RootFS: RootFS{
Type: "layers",
},
}
if err := createModel(r, modelName, baseLayers, config, fn); err != nil {
t.Fatal(err) t.Fatal(err)
} }
} }

View File

@@ -382,10 +382,7 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
// load creates a new model based on req and loads it. If requireFull is true then the model must be loaded fully onto GPUs // load creates a new model based on req and loads it. If requireFull is true then the model must be loaded fully onto GPUs
// (if any). Returns whether the scheduler needs to evict a model to make this one fit. // (if any). Returns whether the scheduler needs to evict a model to make this one fit.
func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList, requireFull bool) bool { func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList, requireFull bool) bool {
numParallel := int(envconfig.NumParallel()) numParallel := max(int(envconfig.NumParallel()), 1)
if numParallel < 1 {
numParallel = 1
}
// Embedding models should always be loaded with parallel=1 // Embedding models should always be loaded with parallel=1
if req.model.CheckCapabilities(model.CapabilityCompletion) != nil { if req.model.CheckCapabilities(model.CapabilityCompletion) != nil {