mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-18 03:25:46 +00:00
c19b763e03
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
266 lines
9.9 KiB
C++
266 lines
9.9 KiB
C++
#include "llmodel_c.h"
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#include "llmodel.h"
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#include <cerrno>
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#include <cstring>
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#include <iostream>
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#include <utility>
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struct LLModelWrapper {
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LLModel *llModel = nullptr;
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LLModel::PromptContext promptContext;
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~LLModelWrapper() { delete llModel; }
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};
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thread_local static std::string last_error_message;
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llmodel_model llmodel_model_create(const char *model_path) {
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const char *error;
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auto fres = llmodel_model_create2(model_path, "auto", &error);
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if (!fres) {
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fprintf(stderr, "Unable to instantiate model: %s\n", error);
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}
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return fres;
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}
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llmodel_model llmodel_model_create2(const char *model_path, const char *build_variant, const char **error) {
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auto wrapper = new LLModelWrapper;
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try {
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wrapper->llModel = LLModel::Implementation::construct(model_path, build_variant);
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if (!wrapper->llModel) {
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last_error_message = "Model format not supported (no matching implementation found)";
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}
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} catch (const std::exception& e) {
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last_error_message = e.what();
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}
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if (!wrapper->llModel) {
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delete std::exchange(wrapper, nullptr);
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if (error) {
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*error = last_error_message.c_str();
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}
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}
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return reinterpret_cast<llmodel_model*>(wrapper);
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}
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void llmodel_model_destroy(llmodel_model model) {
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delete reinterpret_cast<LLModelWrapper*>(model);
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}
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size_t llmodel_required_mem(llmodel_model model, const char *model_path, int n_ctx, int ngl)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->requiredMem(model_path, n_ctx, ngl);
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}
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bool llmodel_loadModel(llmodel_model model, const char *model_path, int n_ctx, int ngl)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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std::string modelPath(model_path);
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if (wrapper->llModel->isModelBlacklisted(modelPath)) {
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size_t slash = modelPath.find_last_of("/\\");
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auto basename = slash == std::string::npos ? modelPath : modelPath.substr(slash + 1);
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std::cerr << "warning: model '" << basename << "' is out-of-date, please check for an updated version\n";
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}
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return wrapper->llModel->loadModel(modelPath, n_ctx, ngl);
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}
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bool llmodel_isModelLoaded(llmodel_model model)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->isModelLoaded();
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}
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uint64_t llmodel_get_state_size(llmodel_model model)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->stateSize();
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}
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uint64_t llmodel_save_state_data(llmodel_model model, uint8_t *dest)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->saveState(dest);
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}
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uint64_t llmodel_restore_state_data(llmodel_model model, const uint8_t *src)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->restoreState(src);
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}
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// Wrapper functions for the C callbacks
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bool prompt_wrapper(int32_t token_id, void *user_data) {
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llmodel_prompt_callback callback = reinterpret_cast<llmodel_prompt_callback>(user_data);
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return callback(token_id);
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}
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bool response_wrapper(int32_t token_id, const std::string &response, void *user_data) {
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llmodel_response_callback callback = reinterpret_cast<llmodel_response_callback>(user_data);
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return callback(token_id, response.c_str());
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}
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bool recalculate_wrapper(bool is_recalculating, void *user_data) {
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llmodel_recalculate_callback callback = reinterpret_cast<llmodel_recalculate_callback>(user_data);
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return callback(is_recalculating);
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}
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void llmodel_prompt(llmodel_model model, const char *prompt,
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const char *prompt_template,
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llmodel_prompt_callback prompt_callback,
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llmodel_response_callback response_callback,
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llmodel_recalculate_callback recalculate_callback,
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llmodel_prompt_context *ctx,
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bool special,
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const char *fake_reply)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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// Create std::function wrappers that call the C function pointers
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std::function<bool(int32_t)> prompt_func =
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std::bind(&prompt_wrapper, std::placeholders::_1, reinterpret_cast<void*>(prompt_callback));
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std::function<bool(int32_t, const std::string&)> response_func =
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std::bind(&response_wrapper, std::placeholders::_1, std::placeholders::_2, reinterpret_cast<void*>(response_callback));
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std::function<bool(bool)> recalc_func =
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std::bind(&recalculate_wrapper, std::placeholders::_1, reinterpret_cast<void*>(recalculate_callback));
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if (size_t(ctx->n_past) < wrapper->promptContext.tokens.size())
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wrapper->promptContext.tokens.resize(ctx->n_past);
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// Copy the C prompt context
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wrapper->promptContext.n_past = ctx->n_past;
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wrapper->promptContext.n_ctx = ctx->n_ctx;
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wrapper->promptContext.n_predict = ctx->n_predict;
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wrapper->promptContext.top_k = ctx->top_k;
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wrapper->promptContext.top_p = ctx->top_p;
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wrapper->promptContext.min_p = ctx->min_p;
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wrapper->promptContext.temp = ctx->temp;
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wrapper->promptContext.n_batch = ctx->n_batch;
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wrapper->promptContext.repeat_penalty = ctx->repeat_penalty;
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wrapper->promptContext.repeat_last_n = ctx->repeat_last_n;
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wrapper->promptContext.contextErase = ctx->context_erase;
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std::string fake_reply_str;
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if (fake_reply) { fake_reply_str = fake_reply; }
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auto *fake_reply_p = fake_reply ? &fake_reply_str : nullptr;
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// Call the C++ prompt method
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wrapper->llModel->prompt(prompt, prompt_template, prompt_func, response_func, recalc_func, wrapper->promptContext,
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special, fake_reply_p);
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// Update the C context by giving access to the wrappers raw pointers to std::vector data
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// which involves no copies
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ctx->logits = wrapper->promptContext.logits.data();
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ctx->logits_size = wrapper->promptContext.logits.size();
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ctx->tokens = wrapper->promptContext.tokens.data();
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ctx->tokens_size = wrapper->promptContext.tokens.size();
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// Update the rest of the C prompt context
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ctx->n_past = wrapper->promptContext.n_past;
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ctx->n_ctx = wrapper->promptContext.n_ctx;
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ctx->n_predict = wrapper->promptContext.n_predict;
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ctx->top_k = wrapper->promptContext.top_k;
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ctx->top_p = wrapper->promptContext.top_p;
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ctx->min_p = wrapper->promptContext.min_p;
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ctx->temp = wrapper->promptContext.temp;
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ctx->n_batch = wrapper->promptContext.n_batch;
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ctx->repeat_penalty = wrapper->promptContext.repeat_penalty;
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ctx->repeat_last_n = wrapper->promptContext.repeat_last_n;
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ctx->context_erase = wrapper->promptContext.contextErase;
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}
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float *llmodel_embedding(llmodel_model model, const char *text, size_t *embedding_size)
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{
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if (model == nullptr || text == nullptr || !strlen(text)) {
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*embedding_size = 0;
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return nullptr;
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}
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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std::vector<float> embeddingVector = wrapper->llModel->embedding(text);
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float *embedding = (float *)malloc(embeddingVector.size() * sizeof(float));
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if (embedding == nullptr) {
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*embedding_size = 0;
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return nullptr;
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}
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std::copy(embeddingVector.begin(), embeddingVector.end(), embedding);
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*embedding_size = embeddingVector.size();
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return embedding;
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}
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void llmodel_free_embedding(float *ptr)
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{
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free(ptr);
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}
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void llmodel_setThreadCount(llmodel_model model, int32_t n_threads)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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wrapper->llModel->setThreadCount(n_threads);
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}
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int32_t llmodel_threadCount(llmodel_model model)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->threadCount();
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}
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void llmodel_set_implementation_search_path(const char *path)
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{
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LLModel::Implementation::setImplementationsSearchPath(path);
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}
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const char *llmodel_get_implementation_search_path()
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{
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return LLModel::Implementation::implementationsSearchPath().c_str();
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}
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struct llmodel_gpu_device* llmodel_available_gpu_devices(llmodel_model model, size_t memoryRequired, int* num_devices)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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std::vector<LLModel::GPUDevice> devices = wrapper->llModel->availableGPUDevices(memoryRequired);
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// Set the num_devices
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*num_devices = devices.size();
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if (*num_devices == 0) return nullptr; // Return nullptr if no devices are found
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// Allocate memory for the output array
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struct llmodel_gpu_device* output = (struct llmodel_gpu_device*) malloc(*num_devices * sizeof(struct llmodel_gpu_device));
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for (int i = 0; i < *num_devices; i++) {
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output[i].index = devices[i].index;
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output[i].type = devices[i].type;
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output[i].heapSize = devices[i].heapSize;
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output[i].name = strdup(devices[i].name.c_str()); // Convert std::string to char* and allocate memory
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output[i].vendor = strdup(devices[i].vendor.c_str()); // Convert std::string to char* and allocate memory
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}
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return output;
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}
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bool llmodel_gpu_init_gpu_device_by_string(llmodel_model model, size_t memoryRequired, const char *device)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->initializeGPUDevice(memoryRequired, std::string(device));
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}
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bool llmodel_gpu_init_gpu_device_by_struct(llmodel_model model, const llmodel_gpu_device *device)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->initializeGPUDevice(device->index);
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}
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bool llmodel_gpu_init_gpu_device_by_int(llmodel_model model, int device)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->initializeGPUDevice(device);
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}
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bool llmodel_has_gpu_device(llmodel_model model)
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{
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LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
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return wrapper->llModel->hasGPUDevice();
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}
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