gpt4all/gpt4all-bindings/typescript/index.cc
Jacob Nguyen 4462d2d755
nodejs bindings (#602)
* 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>
2023-05-22 12:55:22 -07:00

228 lines
8.1 KiB
C++

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