mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-10-30 14:40:16 +01:00
9731134296
* server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test
634 lines
20 KiB
C++
634 lines
20 KiB
C++
#pragma once
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#include <string>
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#include <vector>
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#include <set>
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#include <mutex>
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#include <condition_variable>
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#include <unordered_map>
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#include "json.hpp"
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#include "../llava/clip.h"
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using json = nlohmann::json;
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extern bool server_verbose;
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extern bool server_log_json;
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#ifndef SERVER_VERBOSE
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#define SERVER_VERBOSE 1
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#endif
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#if SERVER_VERBOSE != 1
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#define LOG_VERBOSE(MSG, ...)
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#else
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#define LOG_VERBOSE(MSG, ...) \
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do \
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{ \
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if (server_verbose) \
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{ \
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server_log("VERB", __func__, __LINE__, MSG, __VA_ARGS__); \
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} \
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} while (0)
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#endif
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#define LOG_ERROR( MSG, ...) server_log("ERR", __func__, __LINE__, MSG, __VA_ARGS__)
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#define LOG_WARNING(MSG, ...) server_log("WARN", __func__, __LINE__, MSG, __VA_ARGS__)
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#define LOG_INFO( MSG, ...) server_log("INFO", __func__, __LINE__, MSG, __VA_ARGS__)
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enum server_state {
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SERVER_STATE_LOADING_MODEL, // Server is starting up, model not fully loaded yet
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SERVER_STATE_READY, // Server is ready and model is loaded
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SERVER_STATE_ERROR // An error occurred, load_model failed
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};
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enum task_type {
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TASK_TYPE_COMPLETION,
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TASK_TYPE_CANCEL,
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TASK_TYPE_NEXT_RESPONSE,
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TASK_TYPE_METRICS
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};
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struct task_server {
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int id = -1; // to be filled by llama_server_queue
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int target_id;
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task_type type;
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json data;
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bool infill_mode = false;
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bool embedding_mode = false;
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int multitask_id = -1;
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};
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struct task_result {
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int id;
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int multitask_id = -1;
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bool stop;
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bool error;
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json result_json;
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};
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struct task_multi {
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int id;
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std::set<int> subtasks_remaining{};
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std::vector<task_result> results{};
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};
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// completion token output with probabilities
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struct completion_token_output {
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struct token_prob
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{
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llama_token tok;
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float prob;
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};
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std::vector<token_prob> probs;
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llama_token tok;
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std::string text_to_send;
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};
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struct token_translator {
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llama_context * ctx;
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std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
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std::string operator()(const completion_token_output &cto) const { return (*this)(cto.tok); }
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};
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static inline void server_log(const char *level, const char *function, int line, const char *message, const nlohmann::ordered_json &extra) {
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std::stringstream ss_tid;
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ss_tid << std::this_thread::get_id();
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json log = nlohmann::ordered_json{
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{"tid", ss_tid.str()},
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{"timestamp", time(nullptr)},
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};
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if (server_log_json) {
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log.merge_patch(
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{
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{"level", level},
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{"function", function},
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{"line", line},
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{"msg", message},
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});
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if (!extra.empty()) {
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log.merge_patch(extra);
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}
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std::cout << log.dump(-1, ' ', false, json::error_handler_t::replace) << "\n" << std::flush;
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} else {
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char buf[1024];
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snprintf(buf, 1024, "%4s [%24s] %s", level, function, message);
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if (!extra.empty()) {
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log.merge_patch(extra);
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}
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std::stringstream ss;
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ss << buf << " |";
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for (const auto& el : log.items())
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{
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const std::string value = el.value().dump(-1, ' ', false, json::error_handler_t::replace);
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ss << " " << el.key() << "=" << value;
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}
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const std::string str = ss.str();
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printf("%.*s\n", (int)str.size(), str.data());
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fflush(stdout);
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}
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}
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//
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// server utils
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//
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template <typename T>
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static T json_value(const json &body, const std::string &key, const T &default_value) {
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// Fallback null to default value
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return body.contains(key) && !body.at(key).is_null()
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? body.value(key, default_value)
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: default_value;
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}
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// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
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inline bool verify_custom_template(const std::string & tmpl) {
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llama_chat_message chat[] = {{"user", "test"}};
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std::vector<char> buf(1);
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int res = llama_chat_apply_template(nullptr, tmpl.c_str(), chat, 1, true, buf.data(), buf.size());
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return res >= 0;
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}
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// Format given chat. If tmpl is empty, we take the template from model metadata
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inline std::string format_chat(const struct llama_model * model, const std::string & tmpl, const std::vector<json> & messages) {
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size_t alloc_size = 0;
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// vector holding all allocated string to be passed to llama_chat_apply_template
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std::vector<std::string> str(messages.size() * 2);
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std::vector<llama_chat_message> chat(messages.size());
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for (size_t i = 0; i < messages.size(); ++i) {
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auto &curr_msg = messages[i];
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str[i*2 + 0] = json_value(curr_msg, "role", std::string(""));
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str[i*2 + 1] = json_value(curr_msg, "content", std::string(""));
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alloc_size += str[i*2 + 1].length();
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chat[i].role = str[i*2 + 0].c_str();
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chat[i].content = str[i*2 + 1].c_str();
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}
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const char * ptr_tmpl = tmpl.empty() ? nullptr : tmpl.c_str();
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std::vector<char> buf(alloc_size * 2);
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// run the first time to get the total output length
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int32_t res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
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// if it turns out that our buffer is too small, we resize it
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if ((size_t) res > buf.size()) {
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buf.resize(res);
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res = llama_chat_apply_template(model, ptr_tmpl, chat.data(), chat.size(), true, buf.data(), buf.size());
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}
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std::string formatted_chat(buf.data(), res);
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LOG_VERBOSE("formatted_chat", {{"text", formatted_chat.c_str()}});
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return formatted_chat;
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}
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//
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// work queue utils
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//
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struct llama_server_queue {
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int id = 0;
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std::mutex mutex_tasks;
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bool running;
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// queues
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std::vector<task_server> queue_tasks;
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std::vector<task_server> queue_tasks_deferred;
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std::vector<task_multi> queue_multitasks;
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std::condition_variable condition_tasks;
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// callback functions
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std::function<void(task_server&)> callback_new_task;
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std::function<void(task_multi&)> callback_finish_multitask;
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std::function<void(void)> callback_run_slots;
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// Add a new task to the end of the queue
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int post(task_server task) {
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std::unique_lock<std::mutex> lock(mutex_tasks);
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if (task.id == -1) {
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task.id = id++;
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LOG_VERBOSE("new task id", {{"new_id", task.id}});
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}
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queue_tasks.push_back(std::move(task));
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condition_tasks.notify_one();
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return task.id;
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}
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// Add a new task, but defer until one slot is available
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void defer(task_server task) {
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std::unique_lock<std::mutex> lock(mutex_tasks);
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queue_tasks_deferred.push_back(std::move(task));
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}
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// Get the next id for creating anew task
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int get_new_id() {
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std::unique_lock<std::mutex> lock(mutex_tasks);
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int new_id = id++;
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LOG_VERBOSE("new task id", {{"new_id", new_id}});
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return new_id;
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}
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// Register function to process a new task
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void on_new_task(std::function<void(task_server&)> callback) {
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callback_new_task = callback;
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}
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// Register function to process a multitask when it is finished
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void on_finish_multitask(std::function<void(task_multi&)> callback) {
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callback_finish_multitask = callback;
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}
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// Register the function to be called when all slots data is ready to be processed
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void on_run_slots(std::function<void(void)> callback) {
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callback_run_slots = callback;
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}
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// Call when the state of one slot is changed
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void notify_slot_changed() {
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// move deferred tasks back to main loop
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std::unique_lock<std::mutex> lock(mutex_tasks);
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for (auto & task : queue_tasks_deferred) {
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queue_tasks.push_back(std::move(task));
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}
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queue_tasks_deferred.clear();
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}
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// end the start_loop routine
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void terminate() {
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{
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std::unique_lock<std::mutex> lock(mutex_tasks);
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running = false;
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}
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condition_tasks.notify_all();
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}
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/**
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* Main loop consists of these steps:
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* - Wait until a new task arrives
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* - Process the task (i.e. maybe copy data into slot)
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* - Check if multitask is finished
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* - Run all slots
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*/
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void start_loop() {
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running = true;
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while (true) {
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LOG_VERBOSE("new task may arrive", {});
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{
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while (true)
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{
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std::unique_lock<std::mutex> lock(mutex_tasks);
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if (queue_tasks.empty()) {
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lock.unlock();
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break;
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}
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task_server task = queue_tasks.front();
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queue_tasks.erase(queue_tasks.begin());
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lock.unlock();
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LOG_VERBOSE("callback_new_task", {{"task_id", task.id}});
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callback_new_task(task);
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}
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LOG_VERBOSE("update_multitasks", {});
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// check if we have any finished multitasks
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auto queue_iterator = queue_multitasks.begin();
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while (queue_iterator != queue_multitasks.end())
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{
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if (queue_iterator->subtasks_remaining.empty())
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{
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// all subtasks done == multitask is done
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task_multi current_multitask = *queue_iterator;
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callback_finish_multitask(current_multitask);
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// remove this multitask
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queue_iterator = queue_multitasks.erase(queue_iterator);
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}
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else
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{
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++queue_iterator;
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}
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}
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// all tasks in the current loop is processed, slots data is now ready
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LOG_VERBOSE("callback_run_slots", {});
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callback_run_slots();
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}
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LOG_VERBOSE("wait for new task", {});
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// wait for new task
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{
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std::unique_lock<std::mutex> lock(mutex_tasks);
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if (queue_tasks.empty()) {
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if (!running) {
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LOG_VERBOSE("ending start_loop", {});
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return;
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}
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condition_tasks.wait(lock, [&]{
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return (!queue_tasks.empty() || !running);
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});
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}
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}
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}
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}
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//
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// functions to manage multitasks
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//
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// add a multitask by specifying the id of all subtask (subtask is a task_server)
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void add_multitask(int multitask_id, std::vector<int>& sub_ids)
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{
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std::lock_guard<std::mutex> lock(mutex_tasks);
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task_multi multi;
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multi.id = multitask_id;
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std::copy(sub_ids.begin(), sub_ids.end(), std::inserter(multi.subtasks_remaining, multi.subtasks_remaining.end()));
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queue_multitasks.push_back(multi);
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}
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// updatethe remaining subtasks, while appending results to multitask
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void update_multitask(int multitask_id, int subtask_id, task_result& result)
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{
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std::lock_guard<std::mutex> lock(mutex_tasks);
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for (auto& multitask : queue_multitasks)
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{
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if (multitask.id == multitask_id)
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{
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multitask.subtasks_remaining.erase(subtask_id);
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multitask.results.push_back(result);
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}
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}
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}
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};
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struct llama_server_response {
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typedef std::function<void(int, int, task_result&)> callback_multitask_t;
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callback_multitask_t callback_update_multitask;
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// for keeping track of all tasks waiting for the result
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std::set<int> waiting_task_ids;
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// the main result queue
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std::vector<task_result> queue_results;
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std::mutex mutex_results;
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std::condition_variable condition_results;
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// add the task_id to the list of tasks waiting for response
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void add_waiting_task_id(int task_id) {
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LOG_VERBOSE("waiting for task id", {{"task_id", task_id}});
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std::unique_lock<std::mutex> lock(mutex_results);
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waiting_task_ids.insert(task_id);
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}
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// when the request is finished, we can remove task associated with it
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void remove_waiting_task_id(int task_id) {
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LOG_VERBOSE("remove waiting for task id", {{"task_id", task_id}});
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std::unique_lock<std::mutex> lock(mutex_results);
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waiting_task_ids.erase(task_id);
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}
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// This function blocks the thread until there is a response for this task_id
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task_result recv(int task_id) {
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while (true)
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{
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std::unique_lock<std::mutex> lock(mutex_results);
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condition_results.wait(lock, [&]{
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return !queue_results.empty();
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});
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for (int i = 0; i < (int) queue_results.size(); i++)
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{
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if (queue_results[i].id == task_id)
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{
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assert(queue_results[i].multitask_id == -1);
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task_result res = queue_results[i];
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queue_results.erase(queue_results.begin() + i);
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return res;
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}
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}
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}
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// should never reach here
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}
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// Register the function to update multitask
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void on_multitask_update(callback_multitask_t callback) {
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callback_update_multitask = callback;
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}
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// Send a new result to a waiting task_id
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void send(task_result result) {
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std::unique_lock<std::mutex> lock(mutex_results);
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LOG_VERBOSE("send new result", {{"task_id", result.id}});
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for (auto& task_id : waiting_task_ids) {
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// LOG_TEE("waiting task id %i \n", task_id);
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// for now, tasks that have associated parent multitasks just get erased once multitask picks up the result
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if (result.multitask_id == task_id)
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{
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LOG_VERBOSE("callback_update_multitask", {{"task_id", task_id}});
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callback_update_multitask(task_id, result.id, result);
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continue;
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}
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if (result.id == task_id)
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{
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LOG_VERBOSE("queue_results.push_back", {{"task_id", task_id}});
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queue_results.push_back(result);
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condition_results.notify_all();
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return;
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}
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}
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}
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};
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//
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// base64 utils (TODO: move to common in the future)
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//
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static const std::string base64_chars =
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"ABCDEFGHIJKLMNOPQRSTUVWXYZ"
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"abcdefghijklmnopqrstuvwxyz"
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"0123456789+/";
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static inline bool is_base64(uint8_t c)
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{
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return (isalnum(c) || (c == '+') || (c == '/'));
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}
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static inline std::vector<uint8_t> base64_decode(const std::string & encoded_string)
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{
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int i = 0;
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int j = 0;
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int in_ = 0;
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int in_len = encoded_string.size();
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uint8_t char_array_4[4];
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uint8_t char_array_3[3];
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std::vector<uint8_t> ret;
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while (in_len-- && (encoded_string[in_] != '=') && is_base64(encoded_string[in_]))
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{
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char_array_4[i++] = encoded_string[in_]; in_++;
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if (i == 4)
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{
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for (i = 0; i <4; i++)
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{
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char_array_4[i] = base64_chars.find(char_array_4[i]);
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}
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char_array_3[0] = ((char_array_4[0] ) << 2) + ((char_array_4[1] & 0x30) >> 4);
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char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
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char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
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for (i = 0; (i < 3); i++)
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{
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ret.push_back(char_array_3[i]);
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}
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i = 0;
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}
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}
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if (i)
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{
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for (j = i; j <4; j++)
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{
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char_array_4[j] = 0;
|
|
}
|
|
|
|
for (j = 0; j <4; j++)
|
|
{
|
|
char_array_4[j] = base64_chars.find(char_array_4[j]);
|
|
}
|
|
|
|
char_array_3[0] = ((char_array_4[0] ) << 2) + ((char_array_4[1] & 0x30) >> 4);
|
|
char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
|
|
char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
|
|
|
|
for (j = 0; (j < i - 1); j++)
|
|
{
|
|
ret.push_back(char_array_3[j]);
|
|
}
|
|
}
|
|
|
|
return ret;
|
|
}
|
|
|
|
//
|
|
// random string / id
|
|
//
|
|
|
|
static std::string random_string()
|
|
{
|
|
static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz");
|
|
|
|
std::random_device rd;
|
|
std::mt19937 generator(rd());
|
|
|
|
std::string result(32, ' ');
|
|
|
|
for (int i = 0; i < 32; ++i) {
|
|
result[i] = str[generator() % str.size()];
|
|
}
|
|
|
|
return result;
|
|
}
|
|
|
|
static std::string gen_chatcmplid()
|
|
{
|
|
std::stringstream chatcmplid;
|
|
chatcmplid << "chatcmpl-" << random_string();
|
|
return chatcmplid.str();
|
|
}
|
|
|
|
//
|
|
// other common utils
|
|
//
|
|
|
|
static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
|
|
{
|
|
size_t i;
|
|
for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++)
|
|
{
|
|
}
|
|
return i;
|
|
}
|
|
|
|
static bool ends_with(const std::string &str, const std::string &suffix)
|
|
{
|
|
return str.size() >= suffix.size() &&
|
|
0 == str.compare(str.size() - suffix.size(), suffix.size(), suffix);
|
|
}
|
|
|
|
static size_t find_partial_stop_string(const std::string &stop,
|
|
const std::string &text)
|
|
{
|
|
if (!text.empty() && !stop.empty())
|
|
{
|
|
const char text_last_char = text.back();
|
|
for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--)
|
|
{
|
|
if (stop[char_index] == text_last_char)
|
|
{
|
|
const std::string current_partial = stop.substr(0, char_index + 1);
|
|
if (ends_with(text, current_partial))
|
|
{
|
|
return text.size() - char_index - 1;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return std::string::npos;
|
|
}
|
|
|
|
// TODO: reuse llama_detokenize
|
|
template <class Iter>
|
|
static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
|
|
{
|
|
std::string ret;
|
|
for (; begin != end; ++begin)
|
|
{
|
|
ret += llama_token_to_piece(ctx, *begin);
|
|
}
|
|
return ret;
|
|
}
|
|
|
|
// format incomplete utf-8 multibyte character for output
|
|
static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
|
|
{
|
|
std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
|
|
// if the size is 1 and first bit is 1, meaning it's a partial character
|
|
// (size > 1 meaning it's already a known token)
|
|
if (out.size() == 1 && (out[0] & 0x80) == 0x80)
|
|
{
|
|
std::stringstream ss;
|
|
ss << std::hex << (out[0] & 0xff);
|
|
std::string res(ss.str());
|
|
out = "byte: \\x" + res;
|
|
}
|
|
return out;
|
|
}
|
|
|
|
// convert a vector of completion_token_output to json
|
|
static json probs_vector_to_json(const llama_context *ctx, const std::vector<completion_token_output> &probs)
|
|
{
|
|
json out = json::array();
|
|
for (const auto &prob : probs)
|
|
{
|
|
json probs_for_token = json::array();
|
|
for (const auto &p : prob.probs)
|
|
{
|
|
std::string tok_str = tokens_to_output_formatted_string(ctx, p.tok);
|
|
probs_for_token.push_back(json
|
|
{
|
|
{"tok_str", tok_str},
|
|
{"prob", p.prob},
|
|
});
|
|
}
|
|
std::string tok_str = tokens_to_output_formatted_string(ctx, prob.tok);
|
|
out.push_back(json{
|
|
{"content", tok_str},
|
|
{"probs", probs_for_token},
|
|
});
|
|
}
|
|
return out;
|
|
}
|