mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 02:44:36 +00:00
server : bring back info of final chunk in stream mode (#10722)
* server : bring back into to final chunk in stream mode * clarify a bit * traling space
This commit is contained in:
Xuan Son Nguyen
GitHub
parent
06d70147e6
commit
e52522b869
@ -392,7 +392,7 @@ struct server_task_result {
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return false;
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}
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virtual bool is_stop() {
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// only used by server_task_result_cmpl_partial
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// only used by server_task_result_cmpl_*
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return false;
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}
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virtual int get_index() {
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@ -478,14 +478,20 @@ struct server_task_result_cmpl_final : server_task_result {
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return index;
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}
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virtual bool is_stop() override {
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return true; // in stream mode, final responses are considered stop
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}
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virtual json to_json() override {
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return oaicompat ? to_json_oaicompat_chat() : to_json_non_oaicompat();
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return oaicompat
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? (stream ? to_json_oaicompat_chat_stream() : to_json_oaicompat_chat())
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: to_json_non_oaicompat();
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}
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json to_json_non_oaicompat() {
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json res = json {
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{"index", index},
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{"content", content},
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{"content", stream ? "" : content}, // in stream mode, content is already in last partial chunk
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{"id_slot", id_slot},
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{"stop", true},
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{"model", oaicompat_model},
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@ -546,18 +552,46 @@ struct server_task_result_cmpl_final : server_task_result {
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return res;
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}
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json to_json_oaicompat_chat_stream() {
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std::time_t t = std::time(0);
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std::string finish_reason = "length";
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if (stop == STOP_TYPE_WORD || stop == STOP_TYPE_EOS) {
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finish_reason = "stop";
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}
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json choices = json::array({json{{"finish_reason", finish_reason},
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{"index", 0},
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{"delta", json::object()}}});
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json ret = json {
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{"choices", choices},
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{"created", t},
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{"id", oaicompat_cmpl_id},
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{"model", oaicompat_model},
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{"object", "chat.completion.chunk"},
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{"usage", json {
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{"completion_tokens", n_decoded},
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{"prompt_tokens", n_prompt_tokens},
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{"total_tokens", n_decoded + n_prompt_tokens},
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}},
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};
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if (timings.prompt_n >= 0) {
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ret.push_back({"timings", timings.to_json()});
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}
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return ret;
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}
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};
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struct server_task_result_cmpl_partial : server_task_result {
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int index = 0;
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std::string content;
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bool truncated;
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int32_t n_decoded;
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int32_t n_prompt_tokens;
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stop_type stop = STOP_TYPE_NONE;
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std::vector<completion_token_output> probs_output;
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result_timings timings;
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@ -573,20 +607,19 @@ struct server_task_result_cmpl_partial : server_task_result {
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}
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virtual bool is_stop() override {
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return stop != STOP_TYPE_NONE;
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return false; // in stream mode, partial responses are not considered stop
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}
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virtual json to_json() override {
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if (oaicompat) {
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return to_json_oaicompat();
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}
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bool is_stop = stop != STOP_TYPE_NONE;
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return oaicompat ? to_json_oaicompat() : to_json_non_oaicompat();
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}
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json to_json_non_oaicompat() {
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// non-OAI-compat JSON
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json res = json {
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{"index", index},
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{"content", content},
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{"stop_type", stop_type_to_str(stop)},
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{"stop", is_stop},
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{"stop", false},
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{"id_slot", id_slot},
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{"tokens_predicted", n_decoded},
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{"tokens_evaluated", n_prompt_tokens},
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@ -598,72 +631,54 @@ struct server_task_result_cmpl_partial : server_task_result {
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if (!probs_output.empty()) {
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res["completion_probabilities"] = completion_token_output::probs_vector_to_json(probs_output);
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}
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if (is_stop) {
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res.push_back({"truncated", truncated});
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}
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return res;
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}
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json to_json_oaicompat() {
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bool first = n_decoded == 0;
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std::string finish_reason;
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if (stop == STOP_TYPE_WORD || stop == STOP_TYPE_EOS) {
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finish_reason = "stop";
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} else if (stop == STOP_TYPE_LIMIT) {
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finish_reason = "length";
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}
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std::time_t t = std::time(0);
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json choices;
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if (!finish_reason.empty()) {
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choices = json::array({json{{"finish_reason", finish_reason},
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{"index", 0},
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{"delta", json::object()}}});
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} else {
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if (first) {
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if (content.empty()) {
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choices = json::array({json{{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{{"role", "assistant"}}}}});
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} else {
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// We have to send this as two updates to conform to openai behavior
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json initial_ret = json{{"choices", json::array({json{
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{"finish_reason", nullptr},
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if (first) {
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if (content.empty()) {
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choices = json::array({json{{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{
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{"role", "assistant"}
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}}}})},
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{"created", t},
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{"id", oaicompat_cmpl_id},
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{"model", oaicompat_model},
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{"object", "chat.completion.chunk"}};
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json second_ret = json{
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{"choices", json::array({json{{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{
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{"content", content}}}
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}})},
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{"created", t},
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{"id", oaicompat_cmpl_id},
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{"model", oaicompat_model},
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{"object", "chat.completion.chunk"}};
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return std::vector<json>({initial_ret, second_ret});
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}
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{"delta", json{{"role", "assistant"}}}}});
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} else {
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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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{"delta",
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json{
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{"content", content},
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}},
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}});
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// We have to send this as two updates to conform to openai behavior
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json initial_ret = json{{"choices", json::array({json{
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{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{
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{"role", "assistant"}
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}}}})},
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{"created", t},
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{"id", oaicompat_cmpl_id},
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{"model", oaicompat_model},
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{"object", "chat.completion.chunk"}};
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json second_ret = json{
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{"choices", json::array({json{{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{
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{"content", content}}}
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}})},
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{"created", t},
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{"id", oaicompat_cmpl_id},
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{"model", oaicompat_model},
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{"object", "chat.completion.chunk"}};
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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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choices = json::array({json{
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{"finish_reason", nullptr},
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{"index", 0},
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{"delta",
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json{
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{"content", content},
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}},
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}});
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}
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json ret = json {
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@ -678,14 +693,6 @@ struct server_task_result_cmpl_partial : server_task_result {
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ret.push_back({"timings", timings.to_json()});
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}
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if (!finish_reason.empty()) {
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ret.push_back({"usage", json {
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{"completion_tokens", n_decoded},
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{"prompt_tokens", n_prompt_tokens},
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{"total_tokens", n_decoded + n_prompt_tokens},
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}});
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}
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return std::vector<json>({ret});
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}
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};
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@ -1888,12 +1895,9 @@ struct server_context {
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res->index = slot.index;
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res->content = tkn.text_to_send;
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res->truncated = slot.truncated;
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res->n_decoded = slot.n_decoded;
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res->n_prompt_tokens = slot.n_prompt_tokens;
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res->stop = slot.stop;
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res->verbose = slot.params.verbose;
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res->oaicompat = slot.params.oaicompat;
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res->oaicompat_chat = slot.params.oaicompat_chat;
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@ -1924,12 +1928,6 @@ struct server_context {
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}
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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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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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res->id = slot.id_task;
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res->id_slot = slot.id;
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@ -1948,6 +1946,7 @@ struct server_context {
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res->stop = slot.stop;
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res->verbose = slot.params.verbose;
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res->stream = slot.params.stream;
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res->oaicompat = slot.params.oaicompat;
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res->oaicompat_chat = slot.params.oaicompat_chat;
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res->oaicompat_model = slot.params.oaicompat_model;
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@ -2100,7 +2099,10 @@ struct server_context {
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return;
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}
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GGML_ASSERT(dynamic_cast<server_task_result_cmpl_partial*>(result.get()) != nullptr);
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GGML_ASSERT(
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dynamic_cast<server_task_result_cmpl_partial*>(result.get()) != nullptr
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|| dynamic_cast<server_task_result_cmpl_final*>(result.get()) != nullptr
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);
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if (!result_handler(result)) {
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cancel_tasks(id_tasks);
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break;
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@ -42,10 +42,16 @@ def test_completion_stream(prompt: str, n_predict: int, re_content: str, n_promp
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})
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content = ""
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for data in res:
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assert "stop" in data and type(data["stop"]) == bool
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if data["stop"]:
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assert data["timings"]["prompt_n"] == n_prompt
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assert data["timings"]["predicted_n"] == n_predicted
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assert data["truncated"] == truncated
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assert data["stop_type"] == "limit"
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assert "generation_settings" in data
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assert server.n_predict is not None
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assert data["generation_settings"]["n_predict"] == min(n_predict, server.n_predict)
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assert data["generation_settings"]["seed"] == server.seed
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assert match_regex(re_content, content)
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else:
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content += data["content"]
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