server : various fixes
ggml-ci
This commit is contained in:
Georgi Gerganov
parent
86a1934978
commit
4e218c7255
2 changed files with 38 additions and 43 deletions
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@ -34,14 +34,6 @@ endforeach()
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add_executable(${TARGET} ${TARGET_SRCS})
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install(TARGETS ${TARGET} RUNTIME)
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# clean up generated files in pre-build step
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foreach(asset ${PUBLIC_ASSETS})
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set(output "${CMAKE_CURRENT_BINARY_DIR}/${asset}.hpp")
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add_custom_command(TARGET ${TARGET} PRE_BUILD
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COMMAND "${CMAKE_COMMAND}" -E remove -f "${output}"
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)
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endforeach()
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target_link_libraries(${TARGET} PRIVATE common ${CMAKE_THREAD_LIBS_INIT})
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if (LLAMA_SERVER_SSL)
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@ -122,11 +122,6 @@ struct slot_params {
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struct common_params_sampling sampling;
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struct common_params_speculative speculative;
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// params only used in to_json()
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int32_t n_ctx;
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uint32_t seed_cur;
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bool can_speculative;
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// OAI-compat fields
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bool verbose = false;
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bool oaicompat = false;
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@ -134,7 +129,7 @@ struct slot_params {
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std::string oaicompat_model;
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std::string oaicompat_cmpl_id;
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json to_json() {
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json to_json() const {
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std::vector<std::string> samplers;
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samplers.reserve(sampling.samplers.size());
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for (const auto & sampler : sampling.samplers) {
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@ -142,7 +137,6 @@ struct slot_params {
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}
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return json {
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{"n_ctx", n_ctx},
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{"n_predict", n_predict}, // Server configured n_predict
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{"temperature", sampling.temp},
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{"dynatemp_range", sampling.dynatemp_range},
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@ -177,7 +171,6 @@ struct slot_params {
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{"min_keep", sampling.min_keep},
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{"grammar", sampling.grammar},
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{"samplers", samplers},
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{"speculative", can_speculative},
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{"speculative.n_max", speculative.n_max},
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{"speculative.n_min", speculative.n_min},
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{"speculative.p_min", speculative.p_min},
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@ -483,12 +476,6 @@ struct server_task_result_cmpl_partial : server_task_result {
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return std::vector<json>({initial_ret, second_ret});
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}
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} else {
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// Some idiosyncrasy in task processing logic makes several trailing calls
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// with empty content, we ignore these at the calee site.
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if (content.empty()) {
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return std::vector<json>({json::object()});
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}
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choices = json::array({json{
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{"finish_reason", nullptr},
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{"index", 0},
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@ -722,6 +709,7 @@ struct server_slot {
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llama_batch batch_spec;
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llama_context * ctx = nullptr;
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llama_context * ctx_dft = nullptr;
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common_speculative * spec = nullptr;
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@ -906,6 +894,27 @@ struct server_slot {
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t_token_generation, n_decoded, t_gen, n_gen_second,
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t_prompt_processing + t_token_generation, n_prompt_tokens_processed + n_decoded);
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}
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json to_json() const {
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return json {
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{"id", id},
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{"id_task", id_task},
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{"n_ctx", n_ctx},
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{"speculative", can_speculate()},
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{"is_processing", is_processing()},
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{"params", params.to_json()},
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{"prompt", common_detokenize(ctx, prompt_tokens)},
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{"next_token",
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{
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{"has_next_token", has_next_token},
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{"has_new_line", has_new_line},
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{"n_remain", n_remaining},
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{"n_decoded", n_decoded},
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{"stopping_word", stopping_word},
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}
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},
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};
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}
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};
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struct server_metrics {
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@ -1338,6 +1347,7 @@ struct server_context {
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server_slot slot;
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slot.id = i;
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slot.ctx = ctx;
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slot.n_ctx = n_ctx_slot;
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slot.n_predict = params_base.n_predict;
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@ -1370,7 +1380,7 @@ struct server_context {
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slots.push_back(slot);
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}
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default_generation_settings_for_props = slots[0].params.to_json();
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default_generation_settings_for_props = slots[0].to_json();
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default_generation_settings_for_props["seed"] = -1;
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// the update_slots() logic will always submit a maximum of n_batch or n_parallel tokens
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@ -1848,8 +1858,9 @@ struct server_context {
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queue_results.send(std::move(res));
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}
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void send_partial_response(server_slot & slot, completion_token_output tkn) {
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void send_partial_response(server_slot & slot, const completion_token_output & tkn) {
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auto res = std::make_unique<server_task_result_cmpl_partial>();
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res->id = slot.id_task;
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res->index = slot.index;
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res->content = tkn.text_to_send;
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@ -1869,6 +1880,7 @@ struct server_context {
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// populate res.probs_output
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if (slot.params.sampling.n_probs > 0) {
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const llama_tokens to_send_toks = common_tokenize(ctx, tkn.text_to_send, false);
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const size_t probs_pos = std::min(slot.n_sent_token_probs, slot.generated_token_probs.size());
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const size_t probs_stop_pos = std::min(slot.n_sent_token_probs + to_send_toks.size(), slot.generated_token_probs.size());
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@ -1891,7 +1903,8 @@ struct server_context {
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void send_final_response(server_slot & slot) {
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if (slot.params.stream) {
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// if in stream mode, send the last partial response
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return send_partial_response(slot, {0, "", {}});
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send_partial_response(slot, {0, "", {}});
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return;
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}
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auto res = std::make_unique<server_task_result_cmpl_final>();
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@ -2012,6 +2025,7 @@ struct server_context {
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std::vector<server_task> tasks;
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auto create_task = [&](json & task_data, llama_tokens & prompt_tokens) {
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SRV_DBG("create task, n_tokens = %d\n", (int) prompt_tokens.size());
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server_task task;
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task.id = queue_tasks.get_new_id();
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task.inf_type = inf_type;
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@ -2205,18 +2219,7 @@ struct server_context {
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int n_processing_slots = 0;
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for (server_slot & slot : slots) {
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json slot_data = slot.params.to_json();
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slot_data["id"] = slot.id;
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slot_data["id_task"] = slot.id_task;
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slot_data["is_processing"] = slot.is_processing();
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slot_data["prompt"] = common_detokenize(ctx, slot.prompt_tokens);
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slot_data["next_token"] = {
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{"has_next_token", slot.has_next_token},
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{"has_new_line", slot.has_new_line},
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{"n_remain", slot.n_remaining},
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{"n_decoded", slot.n_decoded},
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{"stopping_word", slot.stopping_word},
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};
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json slot_data = slot.to_json();
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if (slot.is_processing()) {
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n_processing_slots++;
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@ -3003,11 +3006,11 @@ int main(int argc, char ** argv) {
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res.status = 200;
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};
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svr->set_exception_handler([&res_error](const httplib::Request &, httplib::Response & res, std::exception_ptr ep) {
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svr->set_exception_handler([&res_error](const httplib::Request &, httplib::Response & res, const std::exception_ptr & ep) {
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std::string message;
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try {
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std::rethrow_exception(ep);
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} catch (std::exception & e) {
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} catch (const std::exception & e) {
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message = e.what();
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} catch (...) {
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message = "Unknown Exception";
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