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-rw-r--r--examples/server/server.cpp218
1 files changed, 169 insertions, 49 deletions
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 81149591..d970202d 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -47,6 +47,7 @@ struct server_params
};
bool server_verbose = false;
+bool server_log_json = true;
static size_t common_part(const std::vector<llama_token> &a, const std::vector<llama_token> &b)
{
@@ -302,12 +303,43 @@ struct llama_client_slot
}
void print_timings() const {
- LOG_TEE("\n");
- LOG_TEE("%s: prompt eval time = %10.2f ms / %5d tokens (%8.2f ms per token, %8.2f tokens per second)\n",
- __func__, t_prompt_processing, num_prompt_tokens_processed, t_prompt_processing / num_prompt_tokens_processed, 1e3 / t_prompt_processing * num_prompt_tokens_processed);
- LOG_TEE("%s: eval time = %10.2f ms / %5d runs (%8.2f ms per token, %8.2f tokens per second)\n",
- __func__, t_token_generation, n_decoded,t_token_generation / n_decoded, 1e3 / t_token_generation * n_decoded);
- LOG_TEE("%s: total time = %10.2f ms\n", __func__, t_prompt_processing + t_token_generation);
+ char buffer[512];
+ double t_token = t_prompt_processing / num_prompt_tokens_processed;
+ double n_tokens_second = 1e3 / t_prompt_processing * num_prompt_tokens_processed;
+ sprintf(buffer, "prompt eval time = %10.2f ms / %5d tokens (%8.2f ms per token, %8.2f tokens per second)",
+ t_prompt_processing, num_prompt_tokens_processed,
+ t_token, n_tokens_second);
+ LOG_INFO(buffer, {
+ {"slot_id", id},
+ {"task_id", task_id},
+ {"t_prompt_processing", t_prompt_processing},
+ {"num_prompt_tokens_processed", num_prompt_tokens_processed},
+ {"t_token", t_token},
+ {"n_tokens_second", n_tokens_second},
+ });
+
+ t_token = t_token_generation / n_decoded;
+ n_tokens_second = 1e3 / t_token_generation * n_decoded;
+ sprintf(buffer, "generation eval time = %10.2f ms / %5d runs (%8.2f ms per token, %8.2f tokens per second)",
+ t_token_generation, n_decoded,
+ t_token, n_tokens_second);
+ LOG_INFO(buffer, {
+ {"slot_id", id},
+ {"task_id", task_id},
+ {"t_token_generation", t_token_generation},
+ {"n_decoded", n_decoded},
+ {"t_token", t_token},
+ {"n_tokens_second", n_tokens_second},
+ });
+
+ sprintf(buffer, " total time = %10.2f ms", t_prompt_processing + t_token_generation);
+ LOG_INFO(buffer, {
+ {"slot_id", id},
+ {"task_id", task_id},
+ {"t_prompt_processing", t_prompt_processing},
+ {"t_token_generation", t_token_generation},
+ {"t_total", t_prompt_processing + t_token_generation},
+ });
}
};
@@ -399,7 +431,7 @@ struct llama_server_context
params = params_;
if (!params.mmproj.empty()) {
multimodal = true;
- LOG_TEE("Multi Modal Mode Enabled");
+ LOG_INFO("Multi Modal Mode Enabled", {});
clp_ctx = clip_model_load(params.mmproj.c_str(), /*verbosity=*/ 1);
if(clp_ctx == nullptr) {
LOG_ERROR("unable to load clip model", {{"model", params.mmproj}});
@@ -452,7 +484,7 @@ struct llama_server_context
const int32_t n_ctx_slot = n_ctx / params.n_parallel;
- LOG_TEE("Available slots:\n");
+ LOG_INFO("initializing slots", {{"n_slots", params.n_parallel}});
for (int i = 0; i < params.n_parallel; i++)
{
llama_client_slot slot;
@@ -461,7 +493,10 @@ struct llama_server_context
slot.n_ctx = n_ctx_slot;
slot.n_predict = params.n_predict;
- LOG_TEE(" -> Slot %i - max context: %i\n", slot.id, n_ctx_slot);
+ LOG_INFO("new slot", {
+ {"slot_id", slot.id},
+ {"n_ctx_slot", slot.n_ctx}
+ });
const int ga_n = params.grp_attn_n;
const int ga_w = params.grp_attn_w;
@@ -471,7 +506,12 @@ struct llama_server_context
GGML_ASSERT(ga_w % ga_n == 0 && "ga_w must be a multiple of ga_n"); // NOLINT
//GGML_ASSERT(n_ctx_train % ga_w == 0 && "n_ctx_train must be a multiple of ga_w"); // NOLINT
//GGML_ASSERT(n_ctx >= n_ctx_train * ga_n && "n_ctx must be at least n_ctx_train * ga_n"); // NOLINT
- LOG_TEE(" -> Slot %i - self-extend: ga_n = %d, ga_w = %d\n", slot.id, ga_n, ga_w);
+
+ LOG_INFO("slot self-extend", {
+ {"slot_id", slot.id},
+ {"ga_n", ga_n},
+ {"ga_w", ga_w}
+ });
}
slot.ga_i = 0;
@@ -765,10 +805,16 @@ struct llama_server_context
img_sl.img_data = clip_image_u8_init();
if (!clip_image_load_from_bytes(image_buffer.data(), image_buffer.size(), img_sl.img_data))
{
- LOG_TEE("slot %i - failed to load image [id: %i]\n", slot->id, img_sl.id);
+ LOG_ERROR("failed to load image", {
+ {"slot_id", slot->id},
+ {"img_sl_id", img_sl.id}
+ });
return false;
}
- LOG_TEE("slot %i - loaded image\n", slot->id);
+ LOG_VERBOSE("image loaded", {
+ {"slot_id", slot->id},
+ {"img_sl_id", img_sl.id}
+ });
img_sl.request_encode_image = true;
slot->images.push_back(img_sl);
}
@@ -828,7 +874,10 @@ struct llama_server_context
all_slots_are_idle = false;
- LOG_TEE("slot %i is processing [task id: %i]\n", slot->id, slot->task_id);
+ LOG_INFO("slot is processing task", {
+ {"slot_id", slot->id},
+ {"task_id", slot->task_id},
+ });
return true;
}
@@ -1391,7 +1440,7 @@ struct llama_server_context
if (slot == nullptr)
{
// if no slot is available, we defer this task for processing later
- LOG_VERBOSE("no slot is available", {});
+ LOG_VERBOSE("no slot is available", {{"task_id", task.id}});
queue_tasks.defer(task);
break;
}
@@ -1467,7 +1516,17 @@ struct llama_server_context
}
slots_data.push_back(slot_data);
}
- LOG_TEE("task %i - slots data: idle=%i processing=%i\n", task.id, n_idle_slots, n_processing_slots);
+ LOG_INFO("slot data", {
+ {"task_id", task.id},
+ {"n_idle_slots", n_idle_slots},
+ {"n_processing_slots", n_processing_slots}
+ });
+ LOG_VERBOSE("slot data", {
+ {"task_id", task.id},
+ {"n_idle_slots", n_idle_slots},
+ {"n_processing_slots", n_processing_slots},
+ {"slots", slots_data}
+ });
task_result res;
res.id = task.id;
res.multitask_id = task.multitask_id;
@@ -1519,7 +1578,7 @@ struct llama_server_context
bool update_slots() {
if (system_need_update)
{
- LOG_TEE("updating system prompt\n");
+ LOG_INFO("updating system prompt", {});
update_system_prompt();
}
@@ -1529,12 +1588,13 @@ struct llama_server_context
{
if (system_prompt.empty() && clean_kv_cache)
{
- LOG_TEE("all slots are idle and system prompt is empty, clear the KV cache\n");
+ LOG_INFO("all slots are idle and system prompt is empty, clear the KV cache", {});
kv_cache_clear();
}
return true;
}
+ LOG_VERBOSE("posting NEXT_RESPONSE", {});
task_server task;
task.type = TASK_TYPE_NEXT_RESPONSE;
task.target_id = -1;
@@ -1548,10 +1608,20 @@ struct llama_server_context
{
// Shift context
const int n_keep = slot.params.n_keep + add_bos_token;
- const int n_left = system_tokens.size() + slot.n_past - n_keep;
+ const int n_left = (int) system_tokens.size() + slot.n_past - n_keep;
const int n_discard = n_left / 2;
- LOG_TEE("slot %d: context shift - n_keep = %d, n_left = %d, n_discard = %d\n", slot.id, n_keep, n_left, n_discard);
+ LOG_INFO("slot context shift", {
+ {"slot_id", slot.id},
+ {"task_id", slot.task_id},
+ {"n_keep", n_keep},
+ {"n_left", n_left},
+ {"n_discard", n_discard},
+ {"n_ctx", n_ctx},
+ {"n_past", slot.n_past},
+ {"n_system_tokens", system_tokens.size()},
+ {"n_cache_tokens", slot.cache_tokens.size()}
+ });
llama_kv_cache_seq_rm (ctx, slot.id, n_keep , n_keep + n_discard);
llama_kv_cache_seq_shift(ctx, slot.id, n_keep + n_discard, system_tokens.size() + slot.n_past, -n_discard);
@@ -1565,17 +1635,12 @@ struct llama_server_context
slot.n_past -= n_discard;
slot.truncated = true;
-
- LOG_VERBOSE("context shift", {
- { "n_ctx", n_ctx },
- { "n_keep", n_keep },
- { "n_left", n_left },
- });
}
}
}
// decode any currently ongoing sequences
+ LOG_VERBOSE("decoding ongoing sequences", {});
for (auto & slot : slots)
{
// release the slot
@@ -1585,7 +1650,15 @@ struct llama_server_context
slot.command = NONE;
slot.t_last_used = ggml_time_us();
- LOG_TEE("slot %d released (%d tokens in cache)\n", slot.id, (int) slot.cache_tokens.size());
+ LOG_INFO("slot released", {
+ {"slot_id", slot.id},
+ {"task_id", slot.task_id},
+ {"n_ctx", n_ctx},
+ {"n_past", slot.n_past},
+ {"n_system_tokens", system_tokens.size()},
+ {"n_cache_tokens", slot.cache_tokens.size()},
+ {"truncated", slot.truncated}
+ });
queue_tasks.notify_slot_changed();
continue;
@@ -1733,7 +1806,12 @@ struct llama_server_context
slot.ga_i = ga_i;
}
- LOG_TEE("slot %d : in cache: %i tokens | to process: %i tokens\n", slot.id, slot.n_past, slot.num_prompt_tokens_processed);
+ LOG_INFO("slot progression", {
+ { "slot_id", slot.id },
+ { "task_id", slot.task_id },
+ { "n_past", slot.n_past },
+ { "num_prompt_tokens_processed", slot.num_prompt_tokens_processed }
+ });
}
slot.cache_tokens = prompt_tokens;
@@ -1741,7 +1819,10 @@ struct llama_server_context
if (slot.n_past == slot.num_prompt_tokens && slot.n_past > 0)
{
// we have to evaluate at least 1 token to generate logits.
- LOG_TEE("slot %d : we have to evaluate at least 1 token to generate logits\n", slot.id);
+ LOG_INFO("we have to evaluate at least 1 token to generate logits", {
+ { "slot_id", slot.id },
+ { "task_id", slot.task_id }
+ });
slot.n_past--;
if (slot.ga_i > 0)
{
@@ -1749,9 +1830,13 @@ struct llama_server_context
}
}
- LOG_TEE("slot %d : kv cache rm - [%d, end)\n", slot.id, (int) system_tokens.size() + slot.n_past);
-
- llama_kv_cache_seq_rm(ctx, slot.id, system_tokens.size() + slot.n_past, -1);
+ int p0 = (int) system_tokens.size() + slot.n_past;
+ LOG_INFO("kv cache rm [p0, end)", {
+ { "slot_id", slot.id },
+ { "task_id", slot.task_id },
+ { "p0", p0 }
+ });
+ llama_kv_cache_seq_rm(ctx, slot.id, p0, -1);
LOG_VERBOSE("prompt ingested", {
{"n_past", slot.n_past},
@@ -1786,7 +1871,13 @@ struct llama_server_context
if (has_images && !ingest_images(slot, n_batch))
{
- LOG_TEE("failed processing images\n");
+ LOG_ERROR("failed processing images", {
+ "slot_id", slot.id,
+ "task_id", slot.task_id,
+ });
+ // FIXME @phymbert: to be properly tested
+ // early returning without changing the slot state will block the slot for ever
+ // no one at the moment is checking the return value
return false;
}
@@ -1928,6 +2019,8 @@ struct llama_server_context
slot.i_batch = -1;
}
}
+
+ LOG_VERBOSE("slots updated", {});
return true;
}
@@ -2005,6 +2098,7 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
printf(" -ctv TYPE, --cache-type-v TYPE\n");
printf(" KV cache data type for V (default: f16)\n");
printf(" --mmproj MMPROJ_FILE path to a multimodal projector file for LLaVA.\n");
+ printf(" --log-format log output format: json or text (default: json)\n");
printf(" --log-disable disables logging to a file.\n");
printf(" --slots-endpoint-disable disables slots monitoring endpoint.\n");
printf(" --metrics enable prometheus compatible metrics endpoint (default: %s).\n", sparams.metrics_endpoint ? "enabled" : "disabled");
@@ -2458,6 +2552,27 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
}
params.mmproj = argv[i];
}
+ else if (arg == "--log-format")
+ {
+ if (++i >= argc)
+ {
+ invalid_param = true;
+ break;
+ }
+ if (std::strcmp(argv[i], "json") == 0)
+ {
+ server_log_json = true;
+ }
+ else if (std::strcmp(argv[i], "text") == 0)
+ {
+ server_log_json = false;
+ }
+ else
+ {
+ invalid_param = true;
+ break;
+ }
+ }
else if (arg == "--log-disable")
{
log_set_target(stdout);
@@ -2571,32 +2686,40 @@ static json format_partial_response(
static json format_tokenizer_response(const std::vector<llama_token> &tokens)
{
- return json{
- {"tokens", tokens}};
+ return json {
+ {"tokens", tokens}
+ };
}
static json format_detokenized_response(std::string content)
{
- return json{
- {"content", 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
+ if (req.path == "/v1/health" || req.path == "/v1/completions")
+ {
+ return;
+ }
+
LOG_INFO("request", {
- {"remote_addr", req.remote_addr},
- {"remote_port", req.remote_port},
- {"status", res.status},
- {"method", req.method},
- {"path", req.path},
- {"params", req.params},
- });
+ {"remote_addr", req.remote_addr},
+ {"remote_port", req.remote_port},
+ {"status", res.status},
+ {"method", req.method},
+ {"path", req.path},
+ {"params", req.params},
+ });
LOG_VERBOSE("request", {
- {"request", req.body},
- {"response", res.body},
- });
+ {"request", req.body},
+ {"response", res.body},
+ });
}
struct token_translator
@@ -2873,9 +2996,6 @@ int main(int argc, char **argv)
// Set the base directory for serving static files
svr.set_base_dir(sparams.public_path);
- // to make it ctrl+clickable:
- LOG_TEE("\nllama server listening at http://%s:%d\n\n", sparams.hostname.c_str(), sparams.port);
-
std::unordered_map<std::string, std::string> log_data;
log_data["hostname"] = sparams.hostname;
log_data["port"] = std::to_string(sparams.port);
generated by cgit v1.2.3 (git 2.25.1) at 2025-08-16 10:20:07 +0000