ollama/server/prompt.go
Jesse Gross ed443a0393 Runner for Ollama engine
This provides integration with the new Ollama engine
(5824541 next ollama runner (#7913)) and the rest of the Ollama
infrastructure such as the runner and Ollama server.

In addition, it also builds out the KV cache infrastructure to
support requirements of how Ollama runs models such as:
 - Parallel processing
 - Memory management for defragmentation and shifting
 - Multi-modal modals

Both old and new engines continue to be supported. By default, only
the old engine is used. To enable the new engine:

Start the server with the OLLAMA_NEW_ENGINE environment variable set:
OLLAMA_NEW_ENGINE=1 ./ollama serve

Start a model that is supported by the Ollama engine. This one is Llama 3.1 8b Q4_K_M:
./ollama run jessegross/llama3.1
2025-02-13 17:09:26 -08:00

161 lines
3.9 KiB
Go

package server
import (
"bytes"
"context"
"encoding/binary"
"errors"
"fmt"
"log/slog"
"strings"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/model/models/mllama"
"github.com/ollama/ollama/template"
)
type tokenizeFunc func(context.Context, string) ([]int, error)
var errTooManyImages = errors.New("vision model only supports a single image per message")
// chatPrompt accepts a list of messages and returns the prompt and images that should be used for the next chat turn.
// chatPrompt truncates any messages that exceed the context window of the model, making sure to always include 1) the
// latest message and 2) system messages
func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.Options, msgs []api.Message, tools []api.Tool) (prompt string, images []llm.ImageData, _ error) {
var system []api.Message
isMllama := checkMllamaModelFamily(m)
var imageNumTokens int
// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
if isMllama {
// Our mllama implementation packs all of the embeddings into a single token
imageNumTokens = 1
} else {
// Clip images are represented as 768 tokens, each an embedding
imageNumTokens = 768
}
n := len(msgs) - 1
// in reverse, find all messages that fit into context window
for i := n; i >= 0; i-- {
if isMllama && len(msgs[i].Images) > 1 {
return "", nil, errTooManyImages
}
// always include the last message
if i == n {
continue
}
system = make([]api.Message, 0)
for j := range i {
if msgs[j].Role == "system" {
system = append(system, msgs[j])
}
}
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools}); err != nil {
return "", nil, err
}
s, err := tokenize(ctx, b.String())
if err != nil {
return "", nil, err
}
ctxLen := len(s)
if m.ProjectorPaths != nil {
for _, m := range msgs[i:] {
ctxLen += imageNumTokens * len(m.Images)
}
}
if ctxLen > opts.NumCtx {
slog.Debug("truncating input messages which exceed context length", "truncated", len(msgs[i:]))
break
} else {
n = i
}
}
currMsgIdx := n
for cnt, msg := range msgs[currMsgIdx:] {
prefix := ""
imgPrompt := ""
prompt := msg.Content
for _, i := range msg.Images {
var imgData llm.ImageData
if isMllama {
if envconfig.NewEngine() {
imgData = llm.ImageData{
ID: len(images),
Data: i,
}
} else {
data, opts, err := mllama.Preprocess(bytes.NewReader(i))
if err != nil {
return "", nil, err
}
buf := new(bytes.Buffer)
err = binary.Write(buf, binary.LittleEndian, data)
if err != nil {
return "", nil, err
}
ar, ok := opts["aspectRatioIndex"].(int)
if !ok {
return "", nil, fmt.Errorf("missing aspect ratio for image")
}
imgData = llm.ImageData{
ID: len(images),
Data: buf.Bytes(),
AspectRatioID: ar,
}
}
imgPrompt = "<|image|>"
} else {
imgData = llm.ImageData{
ID: len(images),
Data: i,
}
}
imgTag := fmt.Sprintf("[img-%d]", imgData.ID)
if !strings.Contains(prompt, "[img]") {
prefix += imgTag
} else {
prompt = strings.Replace(prompt, "[img]", imgTag, 1)
}
images = append(images, imgData)
}
msgs[currMsgIdx+cnt].Content = prefix + imgPrompt + prompt
}
// truncate any messages that do not fit into the context window
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[currMsgIdx:]...), Tools: tools}); err != nil {
return "", nil, err
}
return b.String(), images, nil
}
func checkMllamaModelFamily(m *Model) bool {
for _, arch := range m.Config.ModelFamilies {
if arch == "mllama" {
return true
}
}
return false
}