ollama/llama/sampling_ext.cpp
2025-05-08 08:31:08 -07:00

132 lines
4.2 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"
#include "llama-grammar.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.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, 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;
}
struct llama_grammar *grammar_init(char* grammar, uint32_t* tokens, size_t n_tokens, const char** pieces, uint32_t* eog_tokens, size_t n_eog_tokens) {
try {
if (grammar == nullptr) {
LLAMA_LOG_ERROR("%s: null grammar input\n", __func__);
return nullptr;
}
ollama_vocab *vocab = new ollama_vocab();
vocab->set_eog_tokens(eog_tokens, n_eog_tokens);
vocab->add_token_pieces(tokens, n_tokens, pieces);
struct llama_grammar *g = llama_grammar_init_impl(nullptr, vocab, grammar, "root", false, nullptr, 0, nullptr, 0);
if (g == nullptr) {
LLAMA_LOG_ERROR("%s: failed to initialize grammar\n", __func__);
delete vocab;
return nullptr;
}
return g;
} catch (const std::exception& e) {
LLAMA_LOG_ERROR("%s: exception during initialization: %s\n", __func__, e.what());
return nullptr;
}
}
void grammar_free(struct llama_grammar *g) {
if (g != nullptr) {
if (g->vocab != nullptr) {
delete g->vocab;
}
llama_grammar_free_impl(g);
}
}
void grammar_apply(struct llama_grammar *g, struct llama_token_data_array *tokens) {
if (g == nullptr || tokens == nullptr) {
LLAMA_LOG_ERROR("%s: null grammar or tokens input\n", __func__);
return;
}
llama_grammar_apply_impl(*g, tokens);
}
void grammar_accept(struct llama_grammar *g, llama_token id) {
llama_grammar_accept_impl(*g, id);
}