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https://github.com/ikawrakow/ik_llama.cpp.git
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* server: stop processing the prompt when client disconnects implement generator-based API for task results Update httplib.h to 0.27.0 Fix embedding error Stop prompt processing when disconnected * Port upstream https://github.com/ggml-org/llama.cpp/pull/18551 * add back anthropic * Fix merge issue caused by github webui --------- Co-authored-by: firecoperana <firecoperana>
376 lines
9.3 KiB
C++
376 lines
9.3 KiB
C++
#pragma once
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#include "common.h"
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#include "llama.h"
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#include <string>
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#include <unordered_set>
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#include <list>
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// TODO: prevent including the whole server-common.h as we only use server_tokens
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#include "server-common.h"
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using json = nlohmann::ordered_json;
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enum stop_type {
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STOP_TYPE_NONE,
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STOP_TYPE_EOS,
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STOP_TYPE_WORD,
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STOP_TYPE_LIMIT,
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};
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enum server_task_type {
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SERVER_TASK_TYPE_COMPLETION,
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SERVER_TASK_TYPE_EMBEDDING,
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SERVER_TASK_TYPE_RERANK,
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SERVER_TASK_TYPE_INFILL,
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SERVER_TASK_TYPE_CANCEL,
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SERVER_TASK_TYPE_NEXT_RESPONSE,
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SERVER_TASK_TYPE_METRICS,
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SERVER_TASK_TYPE_SLOT_SAVE,
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SERVER_TASK_TYPE_SLOT_RESTORE,
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SERVER_TASK_TYPE_SLOT_ERASE,
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SERVER_TASK_TYPE_SET_LORA,
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};
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enum oaicompat_type {
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OAICOMPAT_TYPE_NONE,
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OAICOMPAT_TYPE_CHAT,
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OAICOMPAT_TYPE_COMPLETION,
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OAICOMPAT_TYPE_EMBEDDING,
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OAICOMPAT_TYPE_ANTHROPIC,
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};
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struct slot_params {
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bool stream = true;
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bool include_usage = false;
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bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_discard = 0; // number of tokens after n_keep that may be discarded when shifting context, 0 defaults to half
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int32_t n_predict = -1; // new tokens to predict
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thinking_tokens think_tokens;
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std::vector<std::string> antiprompt;
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bool timings_per_token = false;
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bool post_sampling_probs = false;
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json input_prefix;
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json input_suffix;
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// speculative decoding parameters
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struct {
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int n_max = 16; // max drafted tokens
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int n_min = 0; // min drafted tokens to accept
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float p_min = 0.75f; // min probability required to accept a token in the draft
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} speculative;
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// OAI-compat fields
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oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
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std::string oaicompat_model;
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std::string oaicompat_cmpl_id;
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common_chat_syntax oaicompat_chat_syntax;
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// Embeddings
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int32_t embd_normalize = 2; // (-1=none, 0=max absolute int16, 1=taxicab, 2=Euclidean/L2, >2=p-norm)
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};
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struct server_task {
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int id = -1; // to be filled by server_queue
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int id_multi = -1;
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int index = -1; // used when there are multiple prompts (batch request)
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// used by SERVER_TASK_TYPE_CANCEL
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int id_target = -1;
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int id_slot = -1;
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// used by SERVER_TASK_TYPE_INFERENCE
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struct slot_params params;
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server_tokens tokens;
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server_task_type type;
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json data;
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bool infill = false;
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bool embedding = false;
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server_task() = default;
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server_task(server_task_type type) : type(type) {}
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int32_t n_tokens() const {
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return tokens.size();
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}
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// utility function
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static std::unordered_set<int> get_list_id(const std::vector<server_task>& tasks) {
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std::unordered_set<int> ids(tasks.size());
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for (size_t i = 0; i < tasks.size(); i++) {
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ids.insert(tasks[i].id);
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}
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return ids;
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}
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};
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struct result_timings {
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int32_t prompt_n = -1;
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double prompt_ms;
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double prompt_per_token_ms;
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double prompt_per_second;
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int32_t predicted_n = -1;
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double predicted_ms;
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double predicted_per_token_ms;
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double predicted_per_second;
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int32_t n_ctx = 0;
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int32_t n_past = 0;
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// Optional speculative metrics - only included when > 0
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int32_t draft_n = 0;
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int32_t draft_n_accepted = 0;
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json to_json() const;
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};
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struct server_task_result {
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int id = -1;
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int id_multi = -1;
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json data;
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bool stop;
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bool error;
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bool final_result = false;
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result_timings timings;
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// OAI-compat fields
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//bool verbose = false;
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oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
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std::string oaicompat_model;
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std::string oaicompat_cmpl_id;
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common_chat_format oaicompat_chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
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common_chat_msg oaicompat_msg;
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std::vector<common_chat_msg_diff> oaicompat_msg_diffs;
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int index = 0;
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std::string content;
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std::vector<llama_token> tokens;
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bool stream;
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bool include_usage;
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std::string prompt;
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//slot_params generation_params;
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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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int32_t n_tokens_cached;
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bool has_new_line;
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std::string stopping_word;
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bool post_sampling_probs = false;
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std::vector<completion_token_output> probs_output;
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std::vector<std::string> response_fields;
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//slot_params generation_params;
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bool verbose = false;
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virtual bool is_error() {
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// only used by server_task_result_error
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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_*
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// in stream mode, final responses are considered stop
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return true;
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}
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virtual json to_json() {
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return {};
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};
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int get_index() {
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return index;
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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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bool anthropic_has_reasoning = false;
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bool anthropic_thinking_block_started = false;
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bool anthropic_text_block_started = false;
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virtual bool is_stop() override {
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return false; // in stream mode, partial responses are not considered stop
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}
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json to_json_non_oaicompat_partial();
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json to_json_oaicompat_partial();
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json to_json_anthropic_partial();
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json to_json_oaicompat_chat_partial();
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virtual json to_json() override {
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switch (oaicompat) {
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case OAICOMPAT_TYPE_NONE:
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return to_json_non_oaicompat_partial();
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case OAICOMPAT_TYPE_COMPLETION:
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return to_json_oaicompat_partial();
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case OAICOMPAT_TYPE_CHAT:
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return to_json_oaicompat_chat_partial();
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case OAICOMPAT_TYPE_ANTHROPIC:
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return to_json_anthropic_partial();
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default:
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GGML_ASSERT(false && "Invalid oaicompat_type");
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};
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}
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};
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struct server_task_result_cmpl_final : server_task_result {
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virtual bool is_stop() override {
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return true;
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}
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json to_json_non_oaicompat_final();
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json to_json_oaicompat_final();
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json to_json_oaicompat_chat_final();
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json to_json_anthropic_final();
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json to_json_anthropic_stream();
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json to_json_oaicompat_chat_stream();
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virtual json to_json() override {
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switch (oaicompat) {
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case OAICOMPAT_TYPE_NONE:
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return to_json_non_oaicompat_final();
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case OAICOMPAT_TYPE_COMPLETION:
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return to_json_oaicompat_final();
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case OAICOMPAT_TYPE_CHAT:
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return stream ? to_json_oaicompat_chat_stream() : to_json_oaicompat_chat_final();
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case OAICOMPAT_TYPE_ANTHROPIC:
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return stream ? to_json_anthropic_stream() : to_json_anthropic_final();
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default:
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GGML_ASSERT(false && "Invalid oaicompat_type");
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}
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}
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};
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struct server_task_result_error : server_task_result {
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int index = 0;
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error_type err_type = ERROR_TYPE_SERVER;
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std::string err_msg;
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// for ERROR_TYPE_EXCEED_CONTEXT_SIZE
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int32_t n_prompt_tokens = 0;
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int32_t n_ctx = 0;
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virtual bool is_error() override {
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return true;
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}
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virtual json to_json() override {
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json res = format_error_response(err_msg, err_type);
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return res;
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}
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};
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struct server_task_result_embd : server_task_result {
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int index = 0;
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std::vector<std::vector<float>> embedding;
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int32_t n_tokens;
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// OAI-compat fields
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oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
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virtual json to_json() override {
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return oaicompat == OAICOMPAT_TYPE_EMBEDDING
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? to_json_oaicompat()
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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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return json{
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{"index", index},
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{"embedding", embedding},
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};
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}
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json to_json_oaicompat() {
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return json{
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{"index", index},
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{"embedding", embedding[0]},
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{"tokens_evaluated", n_tokens},
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};
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}
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};
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// using shared_ptr for polymorphism of server_task_result
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using server_task_result_ptr = std::unique_ptr<server_task_result>;
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struct server_prompt_checkpoint {
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llama_pos pos_min;
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llama_pos pos_max;
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std::vector<uint8_t> data;
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size_t size() const {
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return data.size();
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}
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};
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struct server_prompt {
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server_tokens tokens;
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int n_kept_prompt;
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int n_discarded_prompt;
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thinking_tokens think_tokens;
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std::vector<uint8_t> data;
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std::list<server_prompt_checkpoint> checkpoints;
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size_t size() const;
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int n_tokens() const {
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return tokens.size();
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}
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};
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struct server_prompt_cache {
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server_prompt_cache(llama_context* ctx, int32_t limit_size_mib, size_t limit_tokens) {
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this->ctx = ctx;
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this->limit_size = 1024ull * 1024ull * (limit_size_mib < 0 ? 0 : limit_size_mib);
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this->limit_tokens = limit_tokens;
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}
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std::list<server_prompt> states;
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// in bytes, 0 = no limit
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size_t limit_size = 0;
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// in tokens, 0 = no limit
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size_t limit_tokens = 0;
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llama_context* ctx;
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size_t size() const;
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size_t n_tokens() const;
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server_prompt* alloc(const server_prompt& prompt, size_t state_size);
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bool load(server_prompt& prompt, const server_tokens& tokens_new, llama_context* ctx, int32_t id_slot);
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void update();
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};
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