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https://github.com/ggerganov/llama.cpp.git
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server : add single-client multi-prompt support (#4232)
* * add multiprompt support * * cleanup * * more cleanup * * remove atomicity of id_gen, and change lock_guard to unique_lock on completion requests * * remove all references to mutex_multitasks * Update examples/server/server.cpp Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Update examples/server/server.cpp Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Update examples/server/server.cpp Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Update examples/server/server.cpp Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * * change to set --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
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@ -155,15 +155,23 @@ struct task_server {
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json data;
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json data;
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bool infill_mode = false;
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bool infill_mode = false;
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bool embedding_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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};
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struct task_result {
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struct task_result {
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int id;
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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 stop;
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bool error;
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bool error;
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json result_json;
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json result_json;
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};
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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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// TODO: can become bool if we can't find use of more states
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// TODO: can become bool if we can't find use of more states
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enum slot_state
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enum slot_state
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{
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{
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@ -406,6 +414,9 @@ struct llama_client_slot
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double t_prompt_processing; // ms
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double t_prompt_processing; // ms
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double t_token_generation; // ms
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double t_token_generation; // ms
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// multitasks
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int multitask_id = -1;
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void reset() {
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void reset() {
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num_prompt_tokens = 0;
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num_prompt_tokens = 0;
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generated_text = "";
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generated_text = "";
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@ -529,7 +540,8 @@ struct llama_server_context
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std::vector<task_server> queue_tasks;
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std::vector<task_server> queue_tasks;
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std::vector<task_result> queue_results;
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std::vector<task_result> queue_results;
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std::mutex mutex_tasks;
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std::vector<task_multi> queue_multitasks;
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std::mutex mutex_tasks; // also guards id_gen, and queue_multitasks
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std::mutex mutex_results;
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std::mutex mutex_results;
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~llama_server_context()
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~llama_server_context()
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@ -1112,17 +1124,40 @@ struct llama_server_context
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return slot.images.size() > 0;
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return slot.images.size() > 0;
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}
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}
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void send_error(int id, std::string error)
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void send_error(task_server& task, std::string error)
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{
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{
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std::lock_guard<std::mutex> lock(mutex_results);
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std::lock_guard<std::mutex> lock(mutex_results);
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task_result res;
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task_result res;
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res.id = id;
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res.id = task.id;
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res.multitask_id = task.multitask_id;
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res.stop = false;
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res.stop = false;
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res.error = true;
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res.error = true;
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res.result_json = { { "content", error } };
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res.result_json = { { "content", error } };
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queue_results.push_back(res);
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queue_results.push_back(res);
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}
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}
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void add_multi_task(int 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 = 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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void update_multi_task(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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json get_model_props()
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json get_model_props()
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{
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{
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return get_formated_generation(slots[0]);
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return get_formated_generation(slots[0]);
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@ -1167,6 +1202,7 @@ struct llama_server_context
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std::lock_guard<std::mutex> lock(mutex_results);
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std::lock_guard<std::mutex> lock(mutex_results);
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task_result res;
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task_result res;
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res.id = slot.task_id;
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res.id = slot.task_id;
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res.multitask_id = slot.multitask_id;
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res.error = false;
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res.error = false;
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res.stop = false;
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res.stop = false;
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@ -1206,6 +1242,7 @@ struct llama_server_context
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std::lock_guard<std::mutex> lock(mutex_results);
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std::lock_guard<std::mutex> lock(mutex_results);
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task_result res;
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task_result res;
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res.id = slot.task_id;
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res.id = slot.task_id;
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res.multitask_id = slot.multitask_id;
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res.error = false;
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res.error = false;
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res.stop = true;
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res.stop = true;
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@ -1251,6 +1288,12 @@ struct llama_server_context
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res.result_json["model"] = slot.oaicompat_model;
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res.result_json["model"] = slot.oaicompat_model;
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}
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}
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// parent multitask, if any, needs to be updated
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if (slot.multitask_id != -1)
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{
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update_multi_task(slot.multitask_id, slot.task_id, res);
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}
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queue_results.push_back(res);
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queue_results.push_back(res);
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}
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}
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@ -1259,6 +1302,7 @@ struct llama_server_context
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std::lock_guard<std::mutex> lock(mutex_results);
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std::lock_guard<std::mutex> lock(mutex_results);
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task_result res;
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task_result res;
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res.id = slot.task_id;
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res.id = slot.task_id;
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res.multitask_id = slot.multitask_id;
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res.error = false;
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res.error = false;
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res.stop = true;
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res.stop = true;
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@ -1285,9 +1329,9 @@ struct llama_server_context
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queue_results.push_back(res);
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queue_results.push_back(res);
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}
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}
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int request_completion(json data, bool infill, bool embedding)
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int request_completion(json data, bool infill, bool embedding, int multitask_id)
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{
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{
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std::lock_guard<std::mutex> lock(mutex_tasks);
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std::unique_lock<std::mutex> lock(mutex_tasks);
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task_server task;
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task_server task;
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task.id = id_gen++;
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task.id = id_gen++;
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task.target_id = 0;
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task.target_id = 0;
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@ -1295,6 +1339,16 @@ struct llama_server_context
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task.infill_mode = infill;
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task.infill_mode = infill;
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task.embedding_mode = embedding;
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task.embedding_mode = embedding;
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task.type = COMPLETION_TASK;
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task.type = COMPLETION_TASK;
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task.multitask_id = multitask_id;
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// when a completion task's prompt array is not a singleton, we split it into multiple requests
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if (task.data.at("prompt").size() > 1)
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{
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lock.unlock(); // entering new func scope
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return split_multiprompt_task(task);
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}
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// otherwise, it's a single-prompt task, we actually queue it
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queue_tasks.push_back(task);
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queue_tasks.push_back(task);
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return task.id;
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return task.id;
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}
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}
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@ -1313,8 +1367,17 @@ struct llama_server_context
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for (int i = 0; i < (int) queue_results.size(); i++)
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for (int i = 0; i < (int) queue_results.size(); i++)
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{
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{
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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 (queue_results[i].multitask_id == task_id)
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{
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update_multi_task(task_id, queue_results[i].id, queue_results[i]);
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queue_results.erase(queue_results.begin() + i);
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continue;
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}
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if (queue_results[i].id == task_id)
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if (queue_results[i].id == task_id)
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{
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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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task_result res = queue_results[i];
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queue_results.erase(queue_results.begin() + i);
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queue_results.erase(queue_results.begin() + i);
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return res;
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return res;
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@ -1404,6 +1467,27 @@ struct llama_server_context
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queue_tasks.push_back(task);
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queue_tasks.push_back(task);
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}
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}
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int split_multiprompt_task(task_server& multiprompt_task)
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{
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auto prompt_count = multiprompt_task.data.at("prompt").size();
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assert(prompt_count > 1);
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int multitask_id = id_gen++;
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std::vector<int> subtask_ids(prompt_count);
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for (int i = 0; i < prompt_count; i++)
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{
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json subtask_data = multiprompt_task.data;
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subtask_data["prompt"] = subtask_data["prompt"][i];
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// subtasks inherit everything else (infill mode, embedding mode, etc.)
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subtask_ids[i] = request_completion(subtask_data, multiprompt_task.infill_mode, multiprompt_task.embedding_mode, multitask_id);
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}
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// queue up the multitask so we can track its subtask progression
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add_multi_task(multitask_id, subtask_ids);
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return multitask_id;
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}
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void process_tasks()
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void process_tasks()
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{
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{
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std::lock_guard<std::mutex> lock(mutex_tasks);
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std::lock_guard<std::mutex> lock(mutex_tasks);
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@ -1419,7 +1503,7 @@ struct llama_server_context
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{
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{
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LOG_TEE("slot unavailable\n");
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LOG_TEE("slot unavailable\n");
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// send error result
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// send error result
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send_error(task.id, "slot unavailable");
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send_error(task, "slot unavailable");
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return;
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return;
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}
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}
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@ -1433,11 +1517,12 @@ struct llama_server_context
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slot->infill = task.infill_mode;
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slot->infill = task.infill_mode;
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slot->embedding = task.embedding_mode;
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slot->embedding = task.embedding_mode;
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slot->task_id = task.id;
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slot->task_id = task.id;
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slot->multitask_id = task.multitask_id;
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if (!launch_slot_with_data(slot, task.data))
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if (!launch_slot_with_data(slot, task.data))
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{
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{
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// send error result
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// send error result
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send_error(task.id, "internal_error");
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send_error(task, "internal_error");
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break;
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break;
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}
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}
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} break;
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} break;
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@ -1453,6 +1538,38 @@ struct llama_server_context
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} break;
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} break;
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}
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}
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}
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}
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// remove finished multitasks from the queue of multitasks, and add the corresponding result to the result queue
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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_result aggregate_result;
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aggregate_result.id = queue_iterator->id;
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aggregate_result.stop = true;
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aggregate_result.error = false;
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// collect json results into one json result
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std::vector<json> result_jsons;
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for (auto& subres : queue_iterator->results)
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{
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result_jsons.push_back(subres.result_json);
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aggregate_result.error = aggregate_result.error && subres.error;
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}
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aggregate_result.result_json = json{ "results", result_jsons };
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std::lock_guard<std::mutex> lock(mutex_results);
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queue_results.push_back(aggregate_result);
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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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}
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}
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bool update_slots() {
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bool update_slots() {
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@ -2596,7 +2713,7 @@ int main(int argc, char **argv)
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svr.Post("/completion", [&llama](const httplib::Request &req, httplib::Response &res)
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svr.Post("/completion", [&llama](const httplib::Request &req, httplib::Response &res)
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{
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{
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json data = json::parse(req.body);
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json data = json::parse(req.body);
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const int task_id = llama.request_completion(data, false, false);
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const int task_id = llama.request_completion(data, false, false, -1);
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if (!json_value(data, "stream", false)) {
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if (!json_value(data, "stream", false)) {
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std::string completion_text;
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std::string completion_text;
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task_result result = llama.next_result(task_id);
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task_result result = llama.next_result(task_id);
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@ -2685,7 +2802,7 @@ int main(int argc, char **argv)
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{
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{
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json data = oaicompat_completion_params_parse(json::parse(req.body));
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json data = oaicompat_completion_params_parse(json::parse(req.body));
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const int task_id = llama.request_completion(data, false, false);
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const int task_id = llama.request_completion(data, false, false, -1);
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if (!json_value(data, "stream", false)) {
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if (!json_value(data, "stream", false)) {
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std::string completion_text;
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std::string completion_text;
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@ -2754,7 +2871,7 @@ int main(int argc, char **argv)
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svr.Post("/infill", [&llama](const httplib::Request &req, httplib::Response &res)
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svr.Post("/infill", [&llama](const httplib::Request &req, httplib::Response &res)
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{
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{
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json data = json::parse(req.body);
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json data = json::parse(req.body);
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const int task_id = llama.request_completion(data, true, false);
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const int task_id = llama.request_completion(data, true, false, -1);
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if (!json_value(data, "stream", false)) {
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if (!json_value(data, "stream", false)) {
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std::string completion_text;
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std::string completion_text;
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task_result result = llama.next_result(task_id);
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task_result result = llama.next_result(task_id);
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@ -2858,7 +2975,7 @@ int main(int argc, char **argv)
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{
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{
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prompt = "";
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prompt = "";
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}
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}
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const int task_id = llama.request_completion({ {"prompt", prompt}, { "n_predict", 0} }, false, true);
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const int task_id = llama.request_completion({ {"prompt", prompt}, { "n_predict", 0} }, false, true, -1);
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task_result result = llama.next_result(task_id);
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task_result result = llama.next_result(task_id);
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return res.set_content(result.result_json.dump(), "application/json");
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return res.set_content(result.result_json.dump(), "application/json");
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});
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});
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