mirror of
https://github.com/nomic-ai/gpt4all
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394d9b4076
* chore: boilerplate, refactor in future * chore: boilerplate * feat: can compile succesfully * document .gyp file * add src, test and fix gyp * progress on prompting and some helper methods * add destructor and basic prompting work, prepare download function * download function done * download function edits and adding documentation * fix bindings memory issue and add tests and specs * add more documentation and readme * add npmignore * Update README.md Signed-off-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com> * Update package.json - redundant scripts Signed-off-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com> --------- Signed-off-by: Jacob Nguyen <76754747+jacoobes@users.noreply.github.com>
228 lines
8.1 KiB
C++
228 lines
8.1 KiB
C++
#include <napi.h>
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#include <iostream>
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#include "llmodel_c.h"
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#include "llmodel.h"
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#include "gptj.h"
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#include "llamamodel.h"
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#include "mpt.h"
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#include "stdcapture.h"
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class NodeModelWrapper : public Napi::ObjectWrap<NodeModelWrapper> {
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public:
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static Napi::Object Init(Napi::Env env, Napi::Object exports) {
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Napi::Function func = DefineClass(env, "LLModel", {
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InstanceMethod("type", &NodeModelWrapper::getType),
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InstanceMethod("name", &NodeModelWrapper::getName),
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InstanceMethod("stateSize", &NodeModelWrapper::StateSize),
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InstanceMethod("raw_prompt", &NodeModelWrapper::Prompt),
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InstanceMethod("setThreadCount", &NodeModelWrapper::SetThreadCount),
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InstanceMethod("threadCount", &NodeModelWrapper::ThreadCount),
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});
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Napi::FunctionReference* constructor = new Napi::FunctionReference();
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*constructor = Napi::Persistent(func);
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env.SetInstanceData(constructor);
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exports.Set("LLModel", func);
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return exports;
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}
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Napi::Value getType(const Napi::CallbackInfo& info)
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{
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return Napi::String::New(info.Env(), type);
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}
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NodeModelWrapper(const Napi::CallbackInfo& info) : Napi::ObjectWrap<NodeModelWrapper>(info)
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{
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auto env = info.Env();
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std::string weights_path = info[0].As<Napi::String>().Utf8Value();
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const char *c_weights_path = weights_path.c_str();
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inference_ = create_model_set_type(c_weights_path);
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auto success = llmodel_loadModel(inference_, c_weights_path);
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if(!success) {
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Napi::Error::New(env, "Failed to load model at given path").ThrowAsJavaScriptException();
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return;
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}
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name = weights_path.substr(weights_path.find_last_of("/\\") + 1);
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};
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~NodeModelWrapper() {
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// destroying the model manually causes exit code 3221226505, why?
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// However, bindings seem to operate fine without destructing pointer
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//llmodel_model_destroy(inference_);
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}
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Napi::Value IsModelLoaded(const Napi::CallbackInfo& info) {
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return Napi::Boolean::New(info.Env(), llmodel_isModelLoaded(inference_));
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}
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Napi::Value StateSize(const Napi::CallbackInfo& info) {
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// Implement the binding for the stateSize method
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return Napi::Number::New(info.Env(), static_cast<int64_t>(llmodel_get_state_size(inference_)));
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}
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/**
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* Generate a response using the model.
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* @param model A pointer to the llmodel_model instance.
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* @param prompt A string representing the input prompt.
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* @param prompt_callback A callback function for handling the processing of prompt.
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* @param response_callback A callback function for handling the generated response.
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* @param recalculate_callback A callback function for handling recalculation requests.
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* @param ctx A pointer to the llmodel_prompt_context structure.
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*/
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Napi::Value Prompt(const Napi::CallbackInfo& info) {
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auto env = info.Env();
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std::string question;
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if(info[0].IsString()) {
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question = info[0].As<Napi::String>().Utf8Value();
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} else {
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Napi::Error::New(env, "invalid string argument").ThrowAsJavaScriptException();
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return env.Undefined();
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}
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//defaults copied from python bindings
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llmodel_prompt_context promptContext = {
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.logits = nullptr,
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.tokens = nullptr,
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.n_past = 0,
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.n_ctx = 1024,
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.n_predict = 128,
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.top_k = 40,
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.top_p = 0.9f,
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.temp = 0.72f,
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.n_batch = 8,
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.repeat_penalty = 1.0f,
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.repeat_last_n = 10,
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.context_erase = 0.5
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};
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if(info[1].IsObject())
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{
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auto inputObject = info[1].As<Napi::Object>();
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// Extract and assign the properties
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if (inputObject.Has("logits") || inputObject.Has("tokens")) {
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Napi::Error::New(env, "Invalid input: 'logits' or 'tokens' properties are not allowed").ThrowAsJavaScriptException();
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return env.Undefined();
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}
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// Assign the remaining properties
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if(inputObject.Has("n_past")) {
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promptContext.n_past = inputObject.Get("n_past").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("n_ctx")) {
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promptContext.n_ctx = inputObject.Get("n_ctx").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("n_predict")) {
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promptContext.n_predict = inputObject.Get("n_predict").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("top_k")) {
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promptContext.top_k = inputObject.Get("top_k").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("top_p")) {
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promptContext.top_p = inputObject.Get("top_p").As<Napi::Number>().FloatValue();
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}
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if(inputObject.Has("temp")) {
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promptContext.temp = inputObject.Get("temp").As<Napi::Number>().FloatValue();
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}
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if(inputObject.Has("n_batch")) {
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promptContext.n_batch = inputObject.Get("n_batch").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("repeat_penalty")) {
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promptContext.repeat_penalty = inputObject.Get("repeat_penalty").As<Napi::Number>().FloatValue();
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}
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if(inputObject.Has("repeat_last_n")) {
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promptContext.repeat_last_n = inputObject.Get("repeat_last_n").As<Napi::Number>().Int32Value();
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}
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if(inputObject.Has("context_erase")) {
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promptContext.context_erase = inputObject.Get("context_erase").As<Napi::Number>().FloatValue();
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}
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}
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// custom callbacks are weird with the gpt4all c bindings: I need to turn Napi::Functions into raw c function pointers,
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// but it doesn't seem like its possible? (TODO, is it possible?)
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// if(info[1].IsFunction()) {
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// Napi::Callback cb = *info[1].As<Napi::Function>();
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// }
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// For now, simple capture of stdout
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// possible TODO: put this on a libuv async thread. (AsyncWorker)
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CoutRedirect cr;
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llmodel_prompt(inference_, question.c_str(), &prompt_callback, &response_callback, &recalculate_callback, &promptContext);
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return Napi::String::New(env, cr.getString());
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}
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void SetThreadCount(const Napi::CallbackInfo& info) {
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if(info[0].IsNumber()) {
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llmodel_setThreadCount(inference_, info[0].As<Napi::Number>().Int64Value());
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} else {
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Napi::Error::New(info.Env(), "Could not set thread count: argument 1 is NaN").ThrowAsJavaScriptException();
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return;
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}
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}
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Napi::Value getName(const Napi::CallbackInfo& info) {
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return Napi::String::New(info.Env(), name);
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}
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Napi::Value ThreadCount(const Napi::CallbackInfo& info) {
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return Napi::Number::New(info.Env(), llmodel_threadCount(inference_));
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}
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private:
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llmodel_model inference_;
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std::string type;
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std::string name;
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//wrapper cb to capture output into stdout.then, CoutRedirect captures this
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// and writes it to a file
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static bool response_callback(int32_t tid, const char* resp)
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{
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if(tid != -1) {
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std::cout<<std::string(resp);
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return true;
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}
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return false;
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}
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static bool prompt_callback(int32_t tid) { return true; }
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static bool recalculate_callback(bool isrecalculating) { return isrecalculating; }
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// Had to use this instead of the c library in order
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// set the type of the model loaded.
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// causes side effect: type is mutated;
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llmodel_model create_model_set_type(const char* c_weights_path)
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{
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uint32_t magic;
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llmodel_model model;
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FILE *f = fopen(c_weights_path, "rb");
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fread(&magic, sizeof(magic), 1, f);
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if (magic == 0x67676d6c) {
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model = llmodel_gptj_create();
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type = "gptj";
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}
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else if (magic == 0x67676a74) {
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model = llmodel_llama_create();
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type = "llama";
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}
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else if (magic == 0x67676d6d) {
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model = llmodel_mpt_create();
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type = "mpt";
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}
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else {fprintf(stderr, "Invalid model file\n");}
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fclose(f);
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return model;
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}
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};
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//Exports Bindings
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Napi::Object Init(Napi::Env env, Napi::Object exports) {
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return NodeModelWrapper::Init(env, exports);
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}
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NODE_API_MODULE(NODE_GYP_MODULE_NAME, Init)
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