// 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 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); }