You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
gpt4all/gpt4all-backend/llmodel_c.cpp

266 lines
9.5 KiB
C++

#include "llmodel_c.h"
#include "llmodel.h"
#include <cstring>
#include <cerrno>
#include <utility>
struct LLModelWrapper {
LLModel *llModel = nullptr;
LLModel::PromptContext promptContext;
~LLModelWrapper() { delete llModel; }
};
thread_local static std::string last_error_message;
llmodel_model llmodel_model_create(const char *model_path) {
auto fres = llmodel_model_create2(model_path, "auto", nullptr);
if (!fres) {
fprintf(stderr, "Invalid model file\n");
}
return fres;
}
llmodel_model llmodel_model_create2(const char *model_path, const char *build_variant, llmodel_error *error) {
auto wrapper = new LLModelWrapper;
int error_code = 0;
try {
wrapper->llModel = LLModel::Implementation::construct(model_path, build_variant);
} catch (const std::exception& e) {
error_code = EINVAL;
last_error_message = e.what();
}
if (!wrapper->llModel) {
delete std::exchange(wrapper, nullptr);
// Get errno and error message if none
if (error_code == 0) {
if (errno != 0) {
error_code = errno;
last_error_message = std::strerror(error_code);
} else {
error_code = ENOTSUP;
last_error_message = "Model format not supported (no matching implementation found)";
}
}
// Set error argument
if (error) {
error->message = last_error_message.c_str();
error->code = error_code;
}
}
return reinterpret_cast<llmodel_model*>(wrapper);
}
void llmodel_model_destroy(llmodel_model model) {
delete reinterpret_cast<LLModelWrapper*>(model);
}
size_t llmodel_required_mem(llmodel_model model, const char *model_path)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->requiredMem(model_path);
}
bool llmodel_loadModel(llmodel_model model, const char *model_path)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->loadModel(model_path);
}
bool llmodel_isModelLoaded(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->isModelLoaded();
}
uint64_t llmodel_get_state_size(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->stateSize();
}
uint64_t llmodel_save_state_data(llmodel_model model, uint8_t *dest)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->saveState(dest);
}
uint64_t llmodel_restore_state_data(llmodel_model model, const uint8_t *src)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->restoreState(src);
}
// Wrapper functions for the C callbacks
bool prompt_wrapper(int32_t token_id, void *user_data) {
llmodel_prompt_callback callback = reinterpret_cast<llmodel_prompt_callback>(user_data);
return callback(token_id);
}
bool response_wrapper(int32_t token_id, const std::string &response, void *user_data) {
llmodel_response_callback callback = reinterpret_cast<llmodel_response_callback>(user_data);
return callback(token_id, response.c_str());
}
bool recalculate_wrapper(bool is_recalculating, void *user_data) {
llmodel_recalculate_callback callback = reinterpret_cast<llmodel_recalculate_callback>(user_data);
return callback(is_recalculating);
}
void llmodel_prompt(llmodel_model model, const char *prompt,
llmodel_prompt_callback prompt_callback,
llmodel_response_callback response_callback,
llmodel_recalculate_callback recalculate_callback,
llmodel_prompt_context *ctx)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
// Create std::function wrappers that call the C function pointers
std::function<bool(int32_t)> prompt_func =
std::bind(&prompt_wrapper, std::placeholders::_1, reinterpret_cast<void*>(prompt_callback));
std::function<bool(int32_t, const std::string&)> response_func =
std::bind(&response_wrapper, std::placeholders::_1, std::placeholders::_2, reinterpret_cast<void*>(response_callback));
std::function<bool(bool)> recalc_func =
std::bind(&recalculate_wrapper, std::placeholders::_1, reinterpret_cast<void*>(recalculate_callback));
if (size_t(ctx->n_past) < wrapper->promptContext.tokens.size())
wrapper->promptContext.tokens.resize(ctx->n_past);
// Copy the C prompt context
wrapper->promptContext.n_past = ctx->n_past;
wrapper->promptContext.n_ctx = ctx->n_ctx;
wrapper->promptContext.n_predict = ctx->n_predict;
wrapper->promptContext.top_k = ctx->top_k;
wrapper->promptContext.top_p = ctx->top_p;
wrapper->promptContext.temp = ctx->temp;
wrapper->promptContext.n_batch = ctx->n_batch;
wrapper->promptContext.repeat_penalty = ctx->repeat_penalty;
wrapper->promptContext.repeat_last_n = ctx->repeat_last_n;
wrapper->promptContext.contextErase = ctx->context_erase;
// Call the C++ prompt method
wrapper->llModel->prompt(prompt, prompt_func, response_func, recalc_func, wrapper->promptContext);
// Update the C context by giving access to the wrappers raw pointers to std::vector data
// which involves no copies
ctx->logits = wrapper->promptContext.logits.data();
ctx->logits_size = wrapper->promptContext.logits.size();
ctx->tokens = wrapper->promptContext.tokens.data();
ctx->tokens_size = wrapper->promptContext.tokens.size();
// Update the rest of the C prompt context
ctx->n_past = wrapper->promptContext.n_past;
ctx->n_ctx = wrapper->promptContext.n_ctx;
ctx->n_predict = wrapper->promptContext.n_predict;
ctx->top_k = wrapper->promptContext.top_k;
ctx->top_p = wrapper->promptContext.top_p;
ctx->temp = wrapper->promptContext.temp;
ctx->n_batch = wrapper->promptContext.n_batch;
ctx->repeat_penalty = wrapper->promptContext.repeat_penalty;
ctx->repeat_last_n = wrapper->promptContext.repeat_last_n;
ctx->context_erase = wrapper->promptContext.contextErase;
}
float *llmodel_embedding(llmodel_model model, const char *text, size_t *embedding_size)
{
if (model == nullptr || text == nullptr || !strlen(text)) {
*embedding_size = 0;
return nullptr;
}
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
std::vector<float> embeddingVector = wrapper->llModel->embedding(text);
float *embedding = (float *)malloc(embeddingVector.size() * sizeof(float));
if (embedding == nullptr) {
*embedding_size = 0;
return nullptr;
}
std::copy(embeddingVector.begin(), embeddingVector.end(), embedding);
*embedding_size = embeddingVector.size();
return embedding;
}
void llmodel_free_embedding(float *ptr)
{
free(ptr);
}
void llmodel_setThreadCount(llmodel_model model, int32_t n_threads)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
wrapper->llModel->setThreadCount(n_threads);
}
int32_t llmodel_threadCount(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->threadCount();
}
void llmodel_set_implementation_search_path(const char *path)
{
LLModel::Implementation::setImplementationsSearchPath(path);
}
const char *llmodel_get_implementation_search_path()
{
return LLModel::Implementation::implementationsSearchPath().c_str();
}
struct llmodel_gpu_device* llmodel_available_gpu_devices(llmodel_model model, size_t memoryRequired, int* num_devices)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
std::vector<LLModel::GPUDevice> devices = wrapper->llModel->availableGPUDevices(memoryRequired);
// Set the num_devices
*num_devices = devices.size();
if (*num_devices == 0) return nullptr; // Return nullptr if no devices are found
// Allocate memory for the output array
struct llmodel_gpu_device* output = (struct llmodel_gpu_device*) malloc(*num_devices * sizeof(struct llmodel_gpu_device));
for (int i = 0; i < *num_devices; i++) {
output[i].index = devices[i].index;
output[i].type = devices[i].type;
output[i].heapSize = devices[i].heapSize;
output[i].name = strdup(devices[i].name.c_str()); // Convert std::string to char* and allocate memory
output[i].vendor = strdup(devices[i].vendor.c_str()); // Convert std::string to char* and allocate memory
}
return output;
}
bool llmodel_gpu_init_gpu_device_by_string(llmodel_model model, size_t memoryRequired, const char *device)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->initializeGPUDevice(memoryRequired, std::string(device));
}
bool llmodel_gpu_init_gpu_device_by_struct(llmodel_model model, const llmodel_gpu_device *device)
{
LLModel::GPUDevice d;
d.index = device->index;
d.type = device->type;
d.heapSize = device->heapSize;
d.name = device->name;
d.vendor = device->vendor;
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->initializeGPUDevice(d);
}
bool llmodel_gpu_init_gpu_device_by_int(llmodel_model model, int device)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->initializeGPUDevice(device);
}
bool llmodel_has_gpu_device(llmodel_model model)
{
LLModelWrapper *wrapper = reinterpret_cast<LLModelWrapper*>(model);
return wrapper->llModel->hasGPUDevice();
}