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server : include usage statistics only when user request them (#16052)

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* server : include usage statistics only when user request them

When serving the OpenAI compatible API, we should check if
{"stream_options": {"include_usage": true} is set in the request when
deciding whether we should send usage statistics

closes: #16048

* add unit test
This commit is contained in:
Radoslav Gerganov
2025-09-18 13:36:57 +03:00
committed by GitHub
parent e58174cecb
commit 2b6b55a59f
2 changed files with 37 additions and 26 deletions
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59
tools/server/server.cpp
View File

@@ -111,6 +111,7 @@ static bool server_task_type_need_logits(server_task_type task_type) {
struct slot_params { struct slot_params {
bool stream = true; bool stream = true;
bool include_usage = false;
bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt
bool return_tokens = false; bool return_tokens = false;
bool return_progress = false; bool return_progress = false;
@@ -310,17 +311,19 @@ struct server_task {
params.verbose = params_base.verbosity > 9; params.verbose = params_base.verbosity > 9;
params.timings_per_token = json_value(data, "timings_per_token", false); params.timings_per_token = json_value(data, "timings_per_token", false);
params.stream = json_value(data, "stream", false); params.stream = json_value(data, "stream", false);
params.cache_prompt = json_value(data, "cache_prompt", true); auto stream_opt = json_value(data, "stream_options", json::object());
params.return_tokens = json_value(data, "return_tokens", false); params.include_usage = json_value(stream_opt, "include_usage", false);
params.return_progress = json_value(data, "return_progress", false); params.cache_prompt = json_value(data, "cache_prompt", true);
params.n_predict = json_value(data, "n_predict", json_value(data, "max_tokens", defaults.n_predict)); params.return_tokens = json_value(data, "return_tokens", false);
params.n_indent = json_value(data, "n_indent", defaults.n_indent); params.return_progress = json_value(data, "return_progress", false);
params.n_keep = json_value(data, "n_keep", defaults.n_keep); params.n_predict = json_value(data, "n_predict", json_value(data, "max_tokens", defaults.n_predict));
params.n_discard = json_value(data, "n_discard", defaults.n_discard); params.n_indent = json_value(data, "n_indent", defaults.n_indent);
//params.t_max_prompt_ms = json_value(data, "t_max_prompt_ms", defaults.t_max_prompt_ms); // TODO: implement params.n_keep = json_value(data, "n_keep", defaults.n_keep);
params.t_max_predict_ms = json_value(data, "t_max_predict_ms", defaults.t_max_predict_ms); params.n_discard = json_value(data, "n_discard", defaults.n_discard);
params.response_fields = json_value(data, "response_fields", std::vector<std::string>()); //params.t_max_prompt_ms = json_value(data, "t_max_prompt_ms", defaults.t_max_prompt_ms); // TODO: implement
params.t_max_predict_ms = json_value(data, "t_max_predict_ms", defaults.t_max_predict_ms);
params.response_fields = json_value(data, "response_fields", std::vector<std::string>());
params.sampling.top_k = json_value(data, "top_k", defaults.sampling.top_k); params.sampling.top_k = json_value(data, "top_k", defaults.sampling.top_k);
params.sampling.top_p = json_value(data, "top_p", defaults.sampling.top_p); params.sampling.top_p = json_value(data, "top_p", defaults.sampling.top_p);
@@ -775,6 +778,7 @@ struct server_task_result_cmpl_final : server_task_result {
llama_tokens tokens; llama_tokens tokens;
bool stream; bool stream;
bool include_usage;
result_timings timings; result_timings timings;
std::string prompt; std::string prompt;
@@ -982,21 +986,23 @@ struct server_task_result_cmpl_final : server_task_result {
{"object", "chat.completion.chunk"}, {"object", "chat.completion.chunk"},
}); });
// OpenAI API spec for chat.completion.chunks specifies an empty `choices` array for the last chunk when including usage if (include_usage) {
// https://platform.openai.com/docs/api-reference/chat_streaming/streaming#chat_streaming/streaming-choices // OpenAI API spec for chat.completion.chunks specifies an empty `choices` array for the last chunk when including usage
deltas.push_back({ // https://platform.openai.com/docs/api-reference/chat_streaming/streaming#chat_streaming/streaming-choices
{"choices", json::array()}, deltas.push_back({
{"created", t}, {"choices", json::array()},
{"id", oaicompat_cmpl_id}, {"created", t},
{"model", oaicompat_model}, {"id", oaicompat_cmpl_id},
{"system_fingerprint", build_info}, {"model", oaicompat_model},
{"object", "chat.completion.chunk"}, {"system_fingerprint", build_info},
{"usage", json { {"object", "chat.completion.chunk"},
{"completion_tokens", n_decoded}, {"usage", json {
{"prompt_tokens", n_prompt_tokens}, {"completion_tokens", n_decoded},
{"total_tokens", n_decoded + n_prompt_tokens}, {"prompt_tokens", n_prompt_tokens},
}}, {"total_tokens", n_decoded + n_prompt_tokens},
}); }},
});
}
if (timings.prompt_n >= 0) { if (timings.prompt_n >= 0) {
deltas.back().push_back({"timings", timings.to_json()}); deltas.back().push_back({"timings", timings.to_json()});
@@ -2815,6 +2821,7 @@ struct server_context {
res->verbose = slot.params.verbose; res->verbose = slot.params.verbose;
res->stream = slot.params.stream; res->stream = slot.params.stream;
res->include_usage = slot.params.include_usage;
res->oaicompat = slot.params.oaicompat; res->oaicompat = slot.params.oaicompat;
res->oaicompat_model = slot.params.oaicompat_model; res->oaicompat_model = slot.params.oaicompat_model;
res->oaicompat_cmpl_id = slot.params.oaicompat_cmpl_id; res->oaicompat_cmpl_id = slot.params.oaicompat_cmpl_id;

4
tools/server/tests/unit/test_chat_completion.py
View File

@@ -271,8 +271,10 @@ def test_chat_completion_with_timings_per_token():
"max_tokens": 10, "max_tokens": 10,
"messages": [{"role": "user", "content": "test"}], "messages": [{"role": "user", "content": "test"}],
"stream": True, "stream": True,
"stream_options": {"include_usage": True},
"timings_per_token": True, "timings_per_token": True,
}) })
stats_received = False
for i, data in enumerate(res): for i, data in enumerate(res):
if i == 0: if i == 0:
# Check first role message for stream=True # Check first role message for stream=True
@@ -288,6 +290,8 @@ def test_chat_completion_with_timings_per_token():
assert "predicted_per_second" in data["timings"] assert "predicted_per_second" in data["timings"]
assert "predicted_n" in data["timings"] assert "predicted_n" in data["timings"]
assert data["timings"]["predicted_n"] <= 10 assert data["timings"]["predicted_n"] <= 10
stats_received = True
assert stats_received
def test_logprobs(): def test_logprobs():