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https://github.com/ggerganov/llama.cpp.git
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multimodal support enabled by default
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@ -3,12 +3,8 @@
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#include "build-info.h"
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#include "grammar-parser.h"
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//#define SERVER_MULTIMODAL_SUPPORT
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#ifdef SERVER_MULTIMODAL_SUPPORT
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#include "../llava/clip.h"
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#include "stb_image.h"
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#endif
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#ifndef NDEBUG
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// crash the server in debug mode, otherwise send an http 500 error
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@ -63,7 +59,6 @@ static bool server_verbose = false;
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#define LOG_WARNING(MSG, ...) server_log("WARNING", __func__, __LINE__, MSG, __VA_ARGS__)
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#define LOG_INFO(MSG, ...) server_log("INFO", __func__, __LINE__, MSG, __VA_ARGS__)
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#ifdef SERVER_MULTIMODAL_SUPPORT
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static const std::string base64_chars =
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"ABCDEFGHIJKLMNOPQRSTUVWXYZ"
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"abcdefghijklmnopqrstuvwxyz"
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@ -112,7 +107,6 @@ std::vector<uint8_t> base64_decode(std::string const& encoded_string) {
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return ret;
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}
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#endif
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// parallel
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enum slot_state
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@ -267,7 +261,6 @@ static json probs_vector_to_json(const llama_context *ctx, const std::vector<com
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return out;
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}
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#ifdef SERVER_MULTIMODAL_SUPPORT
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struct slot_image {
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clip_image_u8 img_data;
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bool request_encode_image = false;
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@ -276,7 +269,6 @@ struct slot_image {
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int id;
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std::string prefix_prompt = ""; // before of this image
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};
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#endif
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struct llama_client_slot
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{
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@ -322,9 +314,8 @@ struct llama_client_slot
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grammar_parser::parse_state parsed_grammar;
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llama_grammar *grammar = nullptr;
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#ifdef SERVER_MULTIMODAL_SUPPORT
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// multimodal
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std::vector<slot_image> images;
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#endif
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void reset() {
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num_prompt_tokens = 0;
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@ -347,15 +338,12 @@ struct llama_client_slot
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ctx_sampling.grammar = NULL;
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}
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#ifdef SERVER_MULTIMODAL_SUPPORT
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for(slot_image img : images) {
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free(img.image_embedding);
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delete[] img.img_data.data;
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img.prefix_prompt = "";
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}
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images.clear();
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#endif
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// llama_set_rng_seed(ctx, params.seed); in batched the seed matter???????
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}
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@ -452,11 +440,9 @@ struct llama_server_context
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std::string user_name = ""; // this should be the anti prompt
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std::string assistant_name = ""; // this is for generate the prompt
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#ifdef SERVER_MULTIMODAL_SUPPORT
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bool multimodal = false;
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clip_ctx *clp_ctx = nullptr;
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int n_embd;
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#endif
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llama_model *model = nullptr;
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llama_context *ctx = nullptr;
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@ -490,7 +476,6 @@ struct llama_server_context
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bool loadModel(const gpt_params ¶ms_)
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{
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params = params_;
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#ifdef SERVER_MULTIMODAL_SUPPORT
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if(!params.mmproj.empty()) {
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multimodal = true;
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LOG_TEE("Multi Modal Mode Enabled");
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@ -504,7 +489,6 @@ struct llama_server_context
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params.n_ctx = 2048;
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}
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}
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#endif
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std::tie(model, ctx) = llama_init_from_gpt_params(params);
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if (model == nullptr)
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{
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@ -512,7 +496,6 @@ struct llama_server_context
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return false;
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}
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#ifdef SERVER_MULTIMODAL_SUPPORT
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if(multimodal) {
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int n_img_embd = clip_n_mmproj_embd(clp_ctx);
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n_embd = llama_n_embd(model);
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@ -523,7 +506,6 @@ struct llama_server_context
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return false;
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}
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}
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#endif
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n_ctx = llama_n_ctx(ctx);
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n_vocab = llama_n_vocab(model);
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candidates.reserve(n_vocab);
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@ -829,7 +811,6 @@ struct llama_server_context
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return slot.has_next_token; // continue
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}
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#ifdef SERVER_MULTIMODAL_SUPPORT
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bool processImages(llama_client_slot &slot) {
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for(slot_image &img : slot.images) {
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if(!img.request_encode_image) {
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@ -914,7 +895,6 @@ struct llama_server_context
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}
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return true;
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}
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#endif
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bool updateSlots() {
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// update the system prompt wait until all slots are idle state
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@ -1088,7 +1068,6 @@ struct llama_server_context
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{"to_eval", tokens_to_str(ctx, slot.cache_tokens.cbegin() + slot.n_past, slot.cache_tokens.cend())},
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});
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#ifdef SERVER_MULTIMODAL_SUPPORT
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bool ingest_images = processImages(slot); // has images?
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// process the prefix of first image
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@ -1105,15 +1084,7 @@ struct llama_server_context
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LOG_TEE("failed processing images\n");
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return false;
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}
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#else
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for (; slot.n_past < prompt_tokens.size(); ++slot.n_past) {
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batch.token [batch.n_tokens] = prompt_tokens[slot.n_past];
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batch.pos [batch.n_tokens] = slot.n_past + num_tokens_system;
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batch.seq_id[batch.n_tokens] = slot.id;
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batch.logits[batch.n_tokens] = false;
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batch.n_tokens += 1;
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}
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#endif
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// extract the logits only for the last token
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if (batch.n_tokens > 0) {
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batch.logits[batch.n_tokens - 1] = true;
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@ -1277,9 +1248,7 @@ static void server_print_usage(const char *argv0, const gpt_params ¶ms,
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printf(" -cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: disabled)\n");
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printf(" -spf FNAME, --system-prompt-file FNAME\n");
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printf(" Set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications.\n");
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#ifdef SERVER_MULTIMODAL_SUPPORT
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printf(" --mmproj MMPROJ_FILE path to a multimodal projector file for LLaVA.\n");
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#endif
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printf("\n");
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}
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@ -1570,7 +1539,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
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);
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llama.processSystemPromptData(json::parse(systm_content));
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}
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#ifdef SERVER_MULTIMODAL_SUPPORT
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else if(arg == "--mmproj") {
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if (++i >= argc)
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{
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@ -1579,7 +1547,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
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}
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params.mmproj = argv[i];
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}
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#endif
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else
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{
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fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
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@ -1697,11 +1664,7 @@ static json format_partial_response(
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{"content", content },
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{"stop", false},
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{ "slot_id", slot->id },
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#ifdef SERVER_MULTIMODAL_SUPPORT
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{"multimodal", llama.multimodal }
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#else
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{"multimodal", false }
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#endif
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};
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if (slot->sparams.n_probs > 0)
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@ -1810,8 +1773,8 @@ static void parse_options_completion(const json &body, llama_client_slot* slot,
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}
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}
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}
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LOG_VERBOSE("completion parameters parsed", format_generation_settings(llama, slot));
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#ifdef SERVER_MULTIMODAL_SUPPORT
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if(!llama.multimodal) {
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return;
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}
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@ -1882,7 +1845,6 @@ static void parse_options_completion(const json &body, llama_client_slot* slot,
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slot->params.cache_prompt = false; // multimodal doesn't support cache prompt
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}
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}
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#endif
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}
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static void parse_options_infill(const json &body, llama_server_context &llama, llama_client_slot *slot)
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