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server : add "samplers" param to control the samplers order (#5494)
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@ -341,7 +341,7 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
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break;
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}
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const auto sampler_names = string_split(argv[i], ';');
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sparams.samplers_sequence = sampler_types_from_names(sampler_names);
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sparams.samplers_sequence = sampler_types_from_names(sampler_names, true);
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} else if (arg == "--sampling-seq") {
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if (++i >= argc) {
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invalid_param = true;
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@ -964,7 +964,8 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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printf(" -n N, --n-predict N number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)\n", params.n_predict);
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printf(" -c N, --ctx-size N size of the prompt context (default: %d, 0 = loaded from model)\n", params.n_ctx);
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printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
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printf(" --samplers samplers that will be used for generation in the order, separated by \';\' (default: %s)\n", sampler_type_names.c_str());
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printf(" --samplers samplers that will be used for generation in the order, separated by \';\'\n");
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printf(" (default: %s)\n", sampler_type_names.c_str());
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printf(" --sampling-seq simplified sequence for samplers that will be used (default: %s)\n", sampler_type_chars.c_str());
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printf(" --top-k N top-k sampling (default: %d, 0 = disabled)\n", sparams.top_k);
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printf(" --top-p N top-p sampling (default: %.1f, 1.0 = disabled)\n", (double)sparams.top_p);
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@ -1133,34 +1134,50 @@ std::vector<std::string> string_split(std::string input, char separator) {
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return parts;
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}
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std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names) {
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std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
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std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map {
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{"top_k", llama_sampler_type::TOP_K},
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{"top_p", llama_sampler_type::TOP_P},
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{"typical_p", llama_sampler_type::TYPICAL_P},
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{"min_p", llama_sampler_type::MIN_P},
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{"tfs_z", llama_sampler_type::TFS_Z},
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{"temperature", llama_sampler_type::TEMPERATURE}
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};
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// since samplers names are written multiple ways
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// make it ready for both system names and input names
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std::unordered_map<std::string, llama_sampler_type> sampler_name_map {
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{"top_k", llama_sampler_type::TOP_K},
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std::unordered_map<std::string, llama_sampler_type> sampler_alt_name_map {
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{"top-k", llama_sampler_type::TOP_K},
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{"top_p", llama_sampler_type::TOP_P},
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{"top-p", llama_sampler_type::TOP_P},
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{"nucleus", llama_sampler_type::TOP_P},
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{"typical_p", llama_sampler_type::TYPICAL_P},
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{"typical-p", llama_sampler_type::TYPICAL_P},
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{"typical", llama_sampler_type::TYPICAL_P},
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{"min_p", llama_sampler_type::MIN_P},
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{"min-p", llama_sampler_type::MIN_P},
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{"tfs_z", llama_sampler_type::TFS_Z},
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{"tfs-z", llama_sampler_type::TFS_Z},
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{"tfs", llama_sampler_type::TFS_Z},
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{"temp", llama_sampler_type::TEMP},
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{"temperature", llama_sampler_type::TEMP}
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{"temp", llama_sampler_type::TEMPERATURE}
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};
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std::vector<llama_sampler_type> sampler_types;
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sampler_types.reserve(names.size());
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for (const auto& name : names) {
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const auto sampler_item = sampler_name_map.find(name);
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if (sampler_item != sampler_name_map.end()) {
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for (const auto & name : names)
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{
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auto sampler_item = sampler_canonical_name_map.find(name);
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if (sampler_item != sampler_canonical_name_map.end())
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{
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sampler_types.push_back(sampler_item->second);
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}
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else
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{
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if (allow_alt_names)
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{
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sampler_item = sampler_alt_name_map.find(name);
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if (sampler_item != sampler_alt_name_map.end())
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{
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sampler_types.push_back(sampler_item->second);
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}
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}
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}
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}
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return sampler_types;
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}
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@ -1172,7 +1189,7 @@ std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & nam
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{'y', llama_sampler_type::TYPICAL_P},
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{'m', llama_sampler_type::MIN_P},
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{'f', llama_sampler_type::TFS_Z},
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{'t', llama_sampler_type::TEMP}
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{'t', llama_sampler_type::TEMPERATURE}
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};
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std::vector<llama_sampler_type> sampler_types;
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@ -1188,12 +1205,12 @@ std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & nam
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std::string sampler_type_to_name_string(llama_sampler_type sampler_type) {
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switch (sampler_type) {
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case llama_sampler_type::TOP_K: return "top_k";
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case llama_sampler_type::TFS_Z: return "tfs_z";
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case llama_sampler_type::TYPICAL_P: return "typical_p";
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case llama_sampler_type::TOP_P: return "top_p";
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case llama_sampler_type::MIN_P: return "min_p";
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case llama_sampler_type::TEMP: return "temp";
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case llama_sampler_type::TOP_K: return "top_k";
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case llama_sampler_type::TFS_Z: return "tfs_z";
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case llama_sampler_type::TYPICAL_P: return "typical_p";
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case llama_sampler_type::TOP_P: return "top_p";
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case llama_sampler_type::MIN_P: return "min_p";
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case llama_sampler_type::TEMPERATURE: return "temperature";
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default : return "";
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}
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}
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@ -165,7 +165,7 @@ void process_escapes(std::string& input);
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// String utils
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//
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std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names);
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std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
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std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string);
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std::vector<std::string> string_split(std::string input, char separator);
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std::string sampler_type_to_name_string(llama_sampler_type sampler_type);
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@ -139,7 +139,7 @@ static void sampler_queue(
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case llama_sampler_type::TYPICAL_P: llama_sample_typical (ctx_main, &cur_p, typical_p, min_keep); break;
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case llama_sampler_type::TOP_P : llama_sample_top_p (ctx_main, &cur_p, top_p, min_keep); break;
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case llama_sampler_type::MIN_P : llama_sample_min_p (ctx_main, &cur_p, min_p, min_keep); break;
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case llama_sampler_type::TEMP:
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case llama_sampler_type::TEMPERATURE:
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if (dynatemp_range > 0) {
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float dynatemp_min = std::max(0.0f, temp - dynatemp_range);
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float dynatemp_max = std::max(0.0f, temp + dynatemp_range);
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@ -10,12 +10,12 @@
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// sampler types
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enum class llama_sampler_type : char {
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TOP_K = 'k',
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TOP_P = 'p',
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MIN_P = 'm',
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TFS_Z = 'f',
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TYPICAL_P = 'y',
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TEMP = 't'
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TOP_K = 'k',
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TOP_P = 'p',
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MIN_P = 'm',
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TFS_Z = 'f',
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TYPICAL_P = 'y',
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TEMPERATURE = 't'
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};
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// sampling parameters
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@ -45,7 +45,7 @@ typedef struct llama_sampling_params {
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llama_sampler_type::TYPICAL_P,
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llama_sampler_type::TOP_P,
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llama_sampler_type::MIN_P,
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llama_sampler_type::TEMP
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llama_sampler_type::TEMPERATURE
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};
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std::string grammar; // optional BNF-like grammar to constrain sampling
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@ -204,6 +204,8 @@ node index.js
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`system_prompt`: Change the system prompt (initial prompt of all slots), this is useful for chat applications. [See more](#change-system-prompt-on-runtime)
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`samplers`: The order the samplers should be applied in. An array of strings representing sampler type names. If a sampler is not set, it will not be used. If a sampler is specified more than once, it will be applied multiple times. (default: `["top_k", "tfs_z", "typical_p", "top_p", "min_p", "temperature"]` - these are all the available values)
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### Result JSON
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- Note: When using streaming mode (`stream`) only `content` and `stop` will be returned until end of completion.
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@ -672,6 +672,24 @@ struct llama_server_context
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}
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}
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const auto &samplers_sequence = data.find("samplers");
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if (samplers_sequence != data.end() && samplers_sequence->is_array())
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{
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std::vector<std::string> sampler_names;
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for (const auto &sampler_name : *samplers_sequence)
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{
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if (sampler_name.is_string())
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{
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sampler_names.emplace_back(sampler_name);
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}
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}
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slot->sparams.samplers_sequence = sampler_types_from_names(sampler_names, false);
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}
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else
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{
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slot->sparams.samplers_sequence = default_sparams.samplers_sequence;
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}
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if (multimodal)
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{
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const auto &images_data = data.find("image_data");
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@ -1026,6 +1044,12 @@ struct llama_server_context
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const auto eos_bias = slot.sparams.logit_bias.find(llama_token_eos(model));
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const bool ignore_eos = eos_bias != slot.sparams.logit_bias.end() &&
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eos_bias->second < 0.0f && std::isinf(eos_bias->second);
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std::vector<std::string> samplers_sequence;
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for (const auto &sampler_type : slot.sparams.samplers_sequence)
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{
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samplers_sequence.emplace_back(sampler_type_to_name_string(sampler_type));
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}
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return json {
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{"n_ctx", slot.n_ctx},
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{"model", params.model_alias},
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@ -1056,6 +1080,7 @@ struct llama_server_context
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{"logit_bias", slot.sparams.logit_bias},
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{"n_probs", slot.sparams.n_probs},
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{"grammar", slot.sparams.grammar},
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{"samplers", samplers_sequence}
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};
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}
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