Merge pull request #4380 from ollama/mxyng/tokenize
use tokenize/detokenize
This commit is contained in:
commit
32cb1960c1
3 changed files with 66 additions and 242 deletions
148
llm/ext_server/server.cpp
vendored
148
llm/ext_server/server.cpp
vendored
|
@ -140,7 +140,6 @@ struct server_slot {
|
|||
std::vector<llama_token> cache_tokens;
|
||||
std::vector<completion_token_output> generated_token_probs;
|
||||
|
||||
bool infill = false;
|
||||
bool embedding = false;
|
||||
bool has_next_token = true;
|
||||
bool truncated = false;
|
||||
|
@ -187,7 +186,6 @@ struct server_slot {
|
|||
n_past = 0;
|
||||
n_sent_text = 0;
|
||||
n_sent_token_probs = 0;
|
||||
infill = false;
|
||||
ga_i = 0;
|
||||
n_past_se = 0;
|
||||
|
||||
|
@ -600,16 +598,6 @@ struct llama_server_context
|
|||
slot->params.n_predict = slot->n_predict;
|
||||
}
|
||||
|
||||
// infill
|
||||
if (data.count("input_prefix") != 0)
|
||||
{
|
||||
slot->params.input_prefix = data["input_prefix"];
|
||||
}
|
||||
else
|
||||
{
|
||||
slot->params.input_prefix = "";
|
||||
}
|
||||
|
||||
if (data.count("input_suffix") != 0)
|
||||
{
|
||||
slot->params.input_suffix = data["input_suffix"];
|
||||
|
@ -897,15 +885,6 @@ struct llama_server_context
|
|||
system_need_update = true;
|
||||
}
|
||||
|
||||
void system_prompt_process(const json &sys_props) {
|
||||
system_prompt = sys_props.value("prompt", "");
|
||||
name_user = sys_props.value("anti_prompt", "");
|
||||
name_assistant = sys_props.value("assistant_name", "");
|
||||
|
||||
|
||||
system_prompt_notify();
|
||||
}
|
||||
|
||||
static size_t find_stopping_strings(const std::string &text, const size_t last_token_size,
|
||||
const stop_type type, server_slot &slot)
|
||||
{
|
||||
|
@ -1263,13 +1242,12 @@ struct llama_server_context
|
|||
queue_results.send(res);
|
||||
}
|
||||
|
||||
void request_completion(int task_id, json data, bool infill, bool embedding, int multitask_id)
|
||||
void request_completion(int task_id, json data, bool embedding, int multitask_id)
|
||||
{
|
||||
task_server task;
|
||||
task.id = task_id;
|
||||
task.target_id = 0;
|
||||
task.data = std::move(data);
|
||||
task.infill_mode = infill;
|
||||
task.embedding_mode = embedding;
|
||||
task.type = TASK_TYPE_COMPLETION;
|
||||
task.multitask_id = multitask_id;
|
||||
|
@ -1415,8 +1393,8 @@ struct llama_server_context
|
|||
json subtask_data = multiprompt_task.data;
|
||||
subtask_data["prompt"] = subtask_data["prompt"][i];
|
||||
|
||||
// subtasks inherit everything else (infill mode, embedding mode, etc.)
|
||||
request_completion(subtask_ids[i], subtask_data, multiprompt_task.infill_mode, multiprompt_task.embedding_mode, multitask_id);
|
||||
// subtasks inherit everything else (embedding mode, etc.)
|
||||
request_completion(subtask_ids[i], subtask_data, multiprompt_task.embedding_mode, multitask_id);
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -1434,26 +1412,8 @@ struct llama_server_context
|
|||
break;
|
||||
}
|
||||
|
||||
if (task.data.contains("system_prompt"))
|
||||
{
|
||||
if (!all_slots_are_idle) {
|
||||
send_error(task, "system prompt can only be updated when all slots are idle");
|
||||
break;
|
||||
}
|
||||
system_prompt_process(task.data["system_prompt"]);
|
||||
|
||||
// reset cache_tokens for all slots
|
||||
for (server_slot &slot : slots)
|
||||
{
|
||||
slot.cache_tokens.clear();
|
||||
slot.n_past = 0;
|
||||
slot.n_past_se = 0;
|
||||
}
|
||||
}
|
||||
|
||||
slot->reset();
|
||||
|
||||
slot->infill = task.infill_mode;
|
||||
slot->embedding = task.embedding_mode;
|
||||
slot->task_id = task.id;
|
||||
slot->multitask_id = task.multitask_id;
|
||||
|
@ -1679,8 +1639,7 @@ struct llama_server_context
|
|||
const bool has_prompt = slot.prompt.is_array() || (slot.prompt.is_string() && !slot.prompt.get<std::string>().empty()) || !slot.images.empty();
|
||||
|
||||
// empty prompt passed -> release the slot and send empty response
|
||||
// note: infill mode allows empty prompt
|
||||
if (slot.state == IDLE && slot.command == LOAD_PROMPT && !has_prompt && !slot.infill)
|
||||
if (slot.state == IDLE && slot.command == LOAD_PROMPT && !has_prompt)
|
||||
{
|
||||
slot.release();
|
||||
slot.print_timings();
|
||||
|
@ -1697,33 +1656,7 @@ struct llama_server_context
|
|||
slot.t_start_process_prompt = ggml_time_us();
|
||||
slot.t_start_genereration = 0;
|
||||
|
||||
if (slot.infill)
|
||||
{
|
||||
bool suff_rm_leading_spc = true;
|
||||
if (params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1)
|
||||
{
|
||||
params.input_suffix.erase(0, 1);
|
||||
suff_rm_leading_spc = false;
|
||||
}
|
||||
auto prefix_tokens = tokenize(slot.params.input_prefix, false);
|
||||
auto suffix_tokens = tokenize(slot.params.input_suffix, false);
|
||||
|
||||
const int space_token = 29871; // TODO: this should not be hardcoded
|
||||
if (suff_rm_leading_spc && !suffix_tokens.empty() && suffix_tokens[0] == space_token) {
|
||||
suffix_tokens.erase(suffix_tokens.begin());
|
||||
}
|
||||
|
||||
prefix_tokens.insert(prefix_tokens.begin(), llama_token_prefix(model));
|
||||
prefix_tokens.insert(prefix_tokens.begin(), llama_token_bos(model)); // always add BOS
|
||||
prefix_tokens.insert(prefix_tokens.end(), llama_token_suffix(model));
|
||||
prefix_tokens.insert(prefix_tokens.end(), suffix_tokens.begin(), suffix_tokens.end());
|
||||
prefix_tokens.push_back(llama_token_middle(model));
|
||||
prompt_tokens = prefix_tokens;
|
||||
}
|
||||
else
|
||||
{
|
||||
prompt_tokens = tokenize(slot.prompt, system_prompt.empty() && add_bos_token); // add BOS if there isn't system prompt
|
||||
}
|
||||
|
||||
slot.n_prompt_tokens = prompt_tokens.size();
|
||||
|
||||
|
@ -2130,8 +2063,7 @@ static void server_print_usage(const char *argv0, const gpt_params ¶ms,
|
|||
printf("\n");
|
||||
}
|
||||
|
||||
static void server_params_parse(int argc, char **argv, server_params &sparams,
|
||||
gpt_params ¶ms, llama_server_context& llama)
|
||||
static void server_params_parse(int argc, char **argv, server_params &sparams, gpt_params ¶ms)
|
||||
{
|
||||
gpt_params default_params;
|
||||
server_params default_sparams;
|
||||
|
@ -2546,27 +2478,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
|
|||
}
|
||||
params.n_predict = std::stoi(argv[i]);
|
||||
}
|
||||
else if (arg == "-spf" || arg == "--system-prompt-file")
|
||||
{
|
||||
if (++i >= argc)
|
||||
{
|
||||
invalid_param = true;
|
||||
break;
|
||||
}
|
||||
std::ifstream file(argv[i]);
|
||||
if (!file) {
|
||||
fprintf(stderr, "error: failed to open file '%s'\n", argv[i]);
|
||||
invalid_param = true;
|
||||
break;
|
||||
}
|
||||
std::string systm_content;
|
||||
std::copy(
|
||||
std::istreambuf_iterator<char>(file),
|
||||
std::istreambuf_iterator<char>(),
|
||||
std::back_inserter(systm_content)
|
||||
);
|
||||
llama.system_prompt_process(json::parse(systm_content));
|
||||
}
|
||||
else if (arg == "-ctk" || arg == "--cache-type-k") {
|
||||
params.cache_type_k = argv[++i];
|
||||
}
|
||||
|
@ -2714,21 +2625,6 @@ static json format_partial_response(
|
|||
return res;
|
||||
}
|
||||
|
||||
static json format_tokenizer_response(const std::vector<llama_token> &tokens)
|
||||
{
|
||||
return json {
|
||||
{"tokens", tokens}
|
||||
};
|
||||
}
|
||||
|
||||
static json format_detokenized_response(std::string content)
|
||||
{
|
||||
return json {
|
||||
{"content", content}
|
||||
};
|
||||
}
|
||||
|
||||
|
||||
static void log_server_request(const httplib::Request &req, const httplib::Response &res)
|
||||
{
|
||||
// skip GH copilot requests when using default port
|
||||
|
@ -2818,7 +2714,7 @@ int main(int argc, char **argv) {
|
|||
// struct that contains llama context and inference
|
||||
llama_server_context llama;
|
||||
|
||||
server_params_parse(argc, argv, sparams, params, llama);
|
||||
server_params_parse(argc, argv, sparams, params);
|
||||
|
||||
if (params.model_alias == "unknown")
|
||||
{
|
||||
|
@ -3150,7 +3046,7 @@ int main(int argc, char **argv) {
|
|||
json data = json::parse(req.body);
|
||||
const int task_id = llama.queue_tasks.get_new_id();
|
||||
llama.queue_results.add_waiting_task_id(task_id);
|
||||
llama.request_completion(task_id, data, false, false, -1);
|
||||
llama.request_completion(task_id, data, false, -1);
|
||||
if (!json_value(data, "stream", false)) {
|
||||
std::string completion_text;
|
||||
task_result result = llama.queue_results.recv(task_id);
|
||||
|
@ -3218,34 +3114,6 @@ int main(int argc, char **argv) {
|
|||
}
|
||||
});
|
||||
|
||||
svr.Post("/tokenize", [&llama](const httplib::Request &req, httplib::Response &res)
|
||||
{
|
||||
res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
|
||||
const json body = json::parse(req.body);
|
||||
std::vector<llama_token> tokens;
|
||||
if (body.count("content") != 0)
|
||||
{
|
||||
tokens = llama.tokenize(body["content"], false);
|
||||
}
|
||||
const json data = format_tokenizer_response(tokens);
|
||||
return res.set_content(data.dump(), "application/json; charset=utf-8");
|
||||
});
|
||||
|
||||
svr.Post("/detokenize", [&llama](const httplib::Request &req, httplib::Response &res)
|
||||
{
|
||||
res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
|
||||
const json body = json::parse(req.body);
|
||||
std::string content;
|
||||
if (body.count("tokens") != 0)
|
||||
{
|
||||
const std::vector<llama_token> tokens = body["tokens"];
|
||||
content = tokens_to_str(llama.ctx, tokens.cbegin(), tokens.cend());
|
||||
}
|
||||
|
||||
const json data = format_detokenized_response(content);
|
||||
return res.set_content(data.dump(), "application/json; charset=utf-8");
|
||||
});
|
||||
|
||||
svr.Post("/embedding", [&llama](const httplib::Request &req, httplib::Response &res)
|
||||
{
|
||||
res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
|
||||
|
@ -3272,7 +3140,7 @@ int main(int argc, char **argv) {
|
|||
// create and queue the task
|
||||
const int task_id = llama.queue_tasks.get_new_id();
|
||||
llama.queue_results.add_waiting_task_id(task_id);
|
||||
llama.request_completion(task_id, { {"prompt", prompt}, { "n_predict", 0}, {"image_data", image_data} }, false, true, -1);
|
||||
llama.request_completion(task_id, { {"prompt", prompt}, { "n_predict", 0}, {"image_data", image_data} }, true, -1);
|
||||
|
||||
// get the result
|
||||
task_result result = llama.queue_results.recv(task_id);
|
||||
|
|
45
llm/llm.go
45
llm/llm.go
|
@ -12,6 +12,7 @@ package llm
|
|||
import "C"
|
||||
import (
|
||||
"fmt"
|
||||
"strings"
|
||||
"unsafe"
|
||||
)
|
||||
|
||||
|
@ -37,3 +38,47 @@ func Quantize(infile, outfile string, ftype fileType) error {
|
|||
|
||||
return nil
|
||||
}
|
||||
|
||||
type llamaModel struct {
|
||||
m *C.struct_llama_model
|
||||
}
|
||||
|
||||
func newLlamaModel(p string) *llamaModel {
|
||||
cs := C.CString(p)
|
||||
defer C.free(unsafe.Pointer(cs))
|
||||
|
||||
return &llamaModel{
|
||||
C.llama_load_model_from_file(
|
||||
cs,
|
||||
C.llama_model_default_params(),
|
||||
),
|
||||
}
|
||||
}
|
||||
|
||||
func (llm *llamaModel) Close() {
|
||||
C.llama_free_model(llm.m)
|
||||
}
|
||||
|
||||
func (llm *llamaModel) Tokenize(s string) []int {
|
||||
cs := C.CString(s)
|
||||
defer C.free(unsafe.Pointer(cs))
|
||||
|
||||
tokens := make([]int, len(s)+2)
|
||||
if n := C.llama_tokenize(llm.m, cs, C.int(len(s)), (*C.llama_token)(unsafe.Pointer(&tokens[0])), C.int(len(s)+2), false, true); n > 0 {
|
||||
return tokens[:n]
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *llamaModel) Detokenize(i32s []int) string {
|
||||
var sb strings.Builder
|
||||
for _, i32 := range i32s {
|
||||
c := make([]byte, 512)
|
||||
if n := C.llama_token_to_piece(llm.m, C.llama_token(i32), (*C.char)(unsafe.Pointer(&c[0])), C.int(len(c)), false); n > 0 {
|
||||
sb.WriteString(unsafe.String(&c[0], n))
|
||||
}
|
||||
}
|
||||
|
||||
return sb.String()
|
||||
}
|
||||
|
|
113
llm/server.go
113
llm/server.go
|
@ -57,6 +57,8 @@ type llmServer struct {
|
|||
loadDuration time.Duration // Record how long it took the model to load
|
||||
loadProgress float32
|
||||
|
||||
*llamaModel
|
||||
|
||||
sem *semaphore.Weighted
|
||||
}
|
||||
|
||||
|
@ -306,6 +308,7 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
|
|||
totalLayers: ggml.KV().BlockCount() + 1,
|
||||
gpuCount: gpuCount,
|
||||
done: make(chan error, 1),
|
||||
llamaModel: newLlamaModel(model),
|
||||
}
|
||||
|
||||
s.cmd.Env = os.Environ()
|
||||
|
@ -843,12 +846,12 @@ func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, er
|
|||
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
|
||||
}
|
||||
|
||||
data, err := json.Marshal(TokenizeRequest{Content: prompt})
|
||||
if err != nil {
|
||||
var b bytes.Buffer
|
||||
if err := json.NewEncoder(&b).Encode(EmbeddingRequest{Content: prompt}); err != nil {
|
||||
return nil, fmt.Errorf("error marshaling embed data: %w", err)
|
||||
}
|
||||
|
||||
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/embedding", s.port), bytes.NewBuffer(data))
|
||||
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/embedding", s.port), &b)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("error creating embed request: %w", err)
|
||||
}
|
||||
|
@ -878,108 +881,12 @@ func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, er
|
|||
return embedding.Embedding, nil
|
||||
}
|
||||
|
||||
type TokenizeRequest struct {
|
||||
Content string `json:"content"`
|
||||
}
|
||||
|
||||
type TokenizeResponse struct {
|
||||
Tokens []int `json:"tokens"`
|
||||
}
|
||||
|
||||
func (s *llmServer) Tokenize(ctx context.Context, content string) ([]int, error) {
|
||||
// Make sure the server is ready
|
||||
status, err := s.getServerStatus(ctx)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
} else if status != ServerStatusReady && status != ServerStatusNoSlotsAvailable {
|
||||
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
|
||||
}
|
||||
|
||||
data, err := json.Marshal(TokenizeRequest{Content: content})
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("marshaling encode data: %w", err)
|
||||
}
|
||||
|
||||
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/tokenize", s.port), bytes.NewBuffer(data))
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("encode request: %w", err)
|
||||
}
|
||||
req.Header.Set("Content-Type", "application/json")
|
||||
|
||||
resp, err := http.DefaultClient.Do(req)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("do encode request: %w", err)
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("read encode request: %w", err)
|
||||
}
|
||||
|
||||
if resp.StatusCode >= 400 {
|
||||
log.Printf("llm encode error: %s", body)
|
||||
return nil, fmt.Errorf("%s", body)
|
||||
}
|
||||
|
||||
var encoded TokenizeResponse
|
||||
if err := json.Unmarshal(body, &encoded); err != nil {
|
||||
return nil, fmt.Errorf("unmarshal encode response: %w", err)
|
||||
}
|
||||
|
||||
return encoded.Tokens, nil
|
||||
}
|
||||
|
||||
type DetokenizeRequest struct {
|
||||
Tokens []int `json:"tokens"`
|
||||
}
|
||||
|
||||
type DetokenizeResponse struct {
|
||||
Content string `json:"content"`
|
||||
return s.llamaModel.Tokenize(content), nil
|
||||
}
|
||||
|
||||
func (s *llmServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
|
||||
// Make sure the server is ready
|
||||
status, err := s.getServerStatus(ctx)
|
||||
if err != nil {
|
||||
return "", err
|
||||
} else if status != ServerStatusReady && status != ServerStatusNoSlotsAvailable {
|
||||
return "", fmt.Errorf("unexpected server status: %s", status.ToString())
|
||||
}
|
||||
|
||||
data, err := json.Marshal(DetokenizeRequest{Tokens: tokens})
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("marshaling decode data: %w", err)
|
||||
}
|
||||
|
||||
req, err := http.NewRequestWithContext(ctx, http.MethodPost, fmt.Sprintf("http://127.0.0.1:%d/detokenize", s.port), bytes.NewBuffer(data))
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("decode request: %w", err)
|
||||
}
|
||||
req.Header.Set("Content-Type", "application/json")
|
||||
|
||||
resp, err := http.DefaultClient.Do(req)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("do decode request: %w", err)
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("read decode request: %w", err)
|
||||
}
|
||||
|
||||
if resp.StatusCode >= 400 {
|
||||
log.Printf("llm decode error: %s", body)
|
||||
return "", fmt.Errorf("%s", body)
|
||||
}
|
||||
|
||||
var decoded DetokenizeResponse
|
||||
if err := json.Unmarshal(body, &decoded); err != nil {
|
||||
return "", fmt.Errorf("unmarshal encode response: %w", err)
|
||||
}
|
||||
|
||||
return decoded.Content, nil
|
||||
return s.llamaModel.Detokenize(tokens), nil
|
||||
}
|
||||
|
||||
func (s *llmServer) Close() error {
|
||||
|
@ -997,6 +904,10 @@ func (s *llmServer) Close() error {
|
|||
slog.Debug("llama server stopped")
|
||||
}
|
||||
|
||||
if s.llamaModel != nil {
|
||||
s.llamaModel.Close()
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
|
|
Loading…
Reference in a new issue