mirror of
https://github.com/ollama/ollama.git
synced 2025-03-25 09:11:46 +01:00
89 lines
2.8 KiB
C++
Vendored
89 lines
2.8 KiB
C++
Vendored
// TODO: this is a temporary wrapper to allow calling C++ code from CGo
|
|
#include "sampling.h"
|
|
#include "sampling_ext.h"
|
|
#include "json-schema-to-grammar.h"
|
|
#include "llama.h"
|
|
#include "llama-model.h"
|
|
#include "llama-model-loader.h"
|
|
|
|
struct common_sampler *common_sampler_cinit(const struct llama_model *model, struct common_sampler_cparams *params) {
|
|
try {
|
|
common_params_sampling sparams;
|
|
sparams.top_k = params->top_k;
|
|
sparams.top_p = params->top_p;
|
|
sparams.min_p = params->min_p;
|
|
sparams.typ_p = params->typical_p;
|
|
sparams.temp = params->temp;
|
|
sparams.penalty_last_n = params->penalty_last_n;
|
|
sparams.penalty_repeat = params->penalty_repeat;
|
|
sparams.penalty_freq = params->penalty_freq;
|
|
sparams.penalty_present = params->penalty_present;
|
|
sparams.mirostat = params->mirostat;
|
|
sparams.mirostat_tau = params->mirostat_tau;
|
|
sparams.mirostat_eta = params->mirostat_eta;
|
|
sparams.seed = params->seed;
|
|
sparams.grammar = params->grammar;
|
|
sparams.xtc_probability = 0.0;
|
|
sparams.xtc_threshold = 0.5;
|
|
return common_sampler_init(model, sparams);
|
|
} catch (const std::exception &err) {
|
|
return nullptr;
|
|
}
|
|
}
|
|
|
|
void common_sampler_cfree(struct common_sampler *sampler) {
|
|
common_sampler_free(sampler);
|
|
}
|
|
|
|
void common_sampler_creset(struct common_sampler *sampler) {
|
|
common_sampler_reset(sampler);
|
|
}
|
|
|
|
void common_sampler_caccept(struct common_sampler *sampler, llama_token id, bool apply_grammar) {
|
|
common_sampler_accept(sampler, id, apply_grammar);
|
|
}
|
|
|
|
llama_token common_sampler_csample(struct common_sampler *sampler, struct llama_context *ctx, int idx) {
|
|
return common_sampler_sample(sampler, ctx, idx);
|
|
}
|
|
|
|
int schema_to_grammar(const char *json_schema, char *grammar, size_t max_len)
|
|
{
|
|
try
|
|
{
|
|
nlohmann::ordered_json schema = nlohmann::ordered_json::parse(json_schema);
|
|
std::string grammar_str = json_schema_to_grammar(schema);
|
|
size_t len = grammar_str.length();
|
|
if (len >= max_len)
|
|
{
|
|
len = max_len - 1;
|
|
}
|
|
strncpy(grammar, grammar_str.c_str(), len);
|
|
return len;
|
|
}
|
|
catch (const std::exception &e)
|
|
{
|
|
strncpy(grammar, "", max_len - 1);
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
struct llama_vocab * llama_load_vocab_from_file(const char * fname) {
|
|
llama_vocab * vocab = new llama_vocab();
|
|
try {
|
|
const auto kv = LLM_KV(LLM_ARCH_UNKNOWN);
|
|
std::vector<std::string> splits = {};
|
|
llama_model_loader ml(std::string(fname), splits, false, false, nullptr);
|
|
vocab->load(ml, kv);
|
|
} catch (const std::exception & err) {
|
|
LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
|
|
return nullptr;
|
|
}
|
|
|
|
return vocab;
|
|
}
|
|
|
|
void llama_free_vocab(struct llama_vocab * vocab) {
|
|
delete vocab;
|
|
}
|