mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-02 09:40:42 +00:00
450 lines
13 KiB
C++
450 lines
13 KiB
C++
#include "chatllm.h"
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#include "chat.h"
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#include "download.h"
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#include "network.h"
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#include "llmodel/gptj.h"
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#include "llmodel/llamamodel.h"
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#include <QCoreApplication>
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#include <QDir>
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#include <QFile>
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#include <QProcess>
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#include <QResource>
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#include <QSettings>
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#include <fstream>
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//#define DEBUG
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static QString modelFilePath(const QString &modelName)
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{
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QString appPath = QCoreApplication::applicationDirPath()
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+ "/ggml-" + modelName + ".bin";
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QFileInfo infoAppPath(appPath);
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if (infoAppPath.exists())
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return appPath;
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QString downloadPath = Download::globalInstance()->downloadLocalModelsPath()
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+ "/ggml-" + modelName + ".bin";
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QFileInfo infoLocalPath(downloadPath);
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if (infoLocalPath.exists())
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return downloadPath;
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return QString();
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}
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ChatLLM::ChatLLM(Chat *parent)
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: QObject{nullptr}
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, m_llmodel(nullptr)
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, m_promptResponseTokens(0)
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, m_responseLogits(0)
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, m_isRecalc(false)
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, m_chat(parent)
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{
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moveToThread(&m_llmThread);
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connect(this, &ChatLLM::sendStartup, Network::globalInstance(), &Network::sendStartup);
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connect(this, &ChatLLM::sendModelLoaded, Network::globalInstance(), &Network::sendModelLoaded);
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connect(m_chat, &Chat::idChanged, this, &ChatLLM::handleChatIdChanged);
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m_llmThread.setObjectName(m_chat->id());
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m_llmThread.start();
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}
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bool ChatLLM::loadDefaultModel()
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{
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const QList<QString> models = m_chat->modelList();
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if (models.isEmpty()) {
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// try again when we get a list of models
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connect(Download::globalInstance(), &Download::modelListChanged, this,
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&ChatLLM::loadDefaultModel, Qt::SingleShotConnection);
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return false;
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}
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QSettings settings;
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settings.sync();
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QString defaultModel = settings.value("defaultModel", "gpt4all-j-v1.3-groovy").toString();
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if (defaultModel.isEmpty() || !models.contains(defaultModel))
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defaultModel = models.first();
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return loadModel(defaultModel);
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}
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bool ChatLLM::loadModel(const QString &modelName)
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{
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if (isModelLoaded() && m_modelName == modelName)
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return true;
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bool isFirstLoad = false;
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if (isModelLoaded()) {
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resetContextPrivate();
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delete m_llmodel;
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m_llmodel = nullptr;
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emit isModelLoadedChanged();
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} else {
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isFirstLoad = true;
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}
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bool isGPTJ = false;
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QString filePath = modelFilePath(modelName);
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QFileInfo info(filePath);
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if (info.exists()) {
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auto fin = std::ifstream(filePath.toStdString(), std::ios::binary);
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uint32_t magic;
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fin.read((char *) &magic, sizeof(magic));
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fin.seekg(0);
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fin.close();
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isGPTJ = magic == 0x67676d6c;
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if (isGPTJ) {
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m_llmodel = new GPTJ;
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m_llmodel->loadModel(filePath.toStdString());
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} else {
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m_llmodel = new LLamaModel;
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m_llmodel->loadModel(filePath.toStdString());
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}
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restoreState();
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#if defined(DEBUG)
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qDebug() << "chatllm modelLoadedChanged" << m_chat->id();
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fflush(stdout);
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#endif
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emit isModelLoadedChanged();
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if (isFirstLoad)
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emit sendStartup();
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else
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emit sendModelLoaded();
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} else {
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qWarning() << "ERROR: Could not find model at" << filePath;
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}
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if (m_llmodel)
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setModelName(info.completeBaseName().remove(0, 5)); // remove the ggml- prefix
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return m_llmodel;
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}
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bool ChatLLM::isModelLoaded() const
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{
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return m_llmodel && m_llmodel->isModelLoaded();
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}
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void ChatLLM::regenerateResponse()
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{
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m_ctx.n_past -= m_promptResponseTokens;
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m_ctx.n_past = std::max(0, m_ctx.n_past);
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// FIXME: This does not seem to be needed in my testing and llama models don't to it. Remove?
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m_ctx.logits.erase(m_ctx.logits.end() -= m_responseLogits, m_ctx.logits.end());
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m_ctx.tokens.erase(m_ctx.tokens.end() -= m_promptResponseTokens, m_ctx.tokens.end());
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m_promptResponseTokens = 0;
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m_responseLogits = 0;
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m_response = std::string();
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emit responseChanged();
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}
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void ChatLLM::resetResponse()
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{
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m_promptResponseTokens = 0;
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m_responseLogits = 0;
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m_response = std::string();
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emit responseChanged();
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}
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void ChatLLM::resetContext()
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{
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resetContextPrivate();
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emit sendResetContext();
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}
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void ChatLLM::resetContextPrivate()
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{
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regenerateResponse();
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m_ctx = LLModel::PromptContext();
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}
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std::string remove_leading_whitespace(const std::string& input) {
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auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) {
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return !std::isspace(c);
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});
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return std::string(first_non_whitespace, input.end());
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}
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std::string trim_whitespace(const std::string& input) {
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auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) {
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return !std::isspace(c);
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});
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auto last_non_whitespace = std::find_if(input.rbegin(), input.rend(), [](unsigned char c) {
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return !std::isspace(c);
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}).base();
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return std::string(first_non_whitespace, last_non_whitespace);
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}
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QString ChatLLM::response() const
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{
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return QString::fromStdString(remove_leading_whitespace(m_response));
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}
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QString ChatLLM::modelName() const
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{
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return m_modelName;
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}
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void ChatLLM::setModelName(const QString &modelName)
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{
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m_modelName = modelName;
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emit modelNameChanged();
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}
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void ChatLLM::modelNameChangeRequested(const QString &modelName)
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{
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if (!loadModel(modelName))
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qWarning() << "ERROR: Could not load model" << modelName;
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}
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bool ChatLLM::handlePrompt(int32_t token)
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{
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// m_promptResponseTokens and m_responseLogits are related to last prompt/response not
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// the entire context window which we can reset on regenerate prompt
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#if defined(DEBUG)
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qDebug() << "chatllm prompt process" << m_chat->id() << token;
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#endif
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++m_promptResponseTokens;
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return !m_stopGenerating;
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}
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bool ChatLLM::handleResponse(int32_t token, const std::string &response)
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{
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#if defined(DEBUG)
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printf("%s", response.c_str());
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fflush(stdout);
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#endif
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// check for error
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if (token < 0) {
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m_response.append(response);
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emit responseChanged();
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return false;
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}
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// m_promptResponseTokens and m_responseLogits are related to last prompt/response not
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// the entire context window which we can reset on regenerate prompt
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++m_promptResponseTokens;
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Q_ASSERT(!response.empty());
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m_response.append(response);
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emit responseChanged();
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return !m_stopGenerating;
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}
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bool ChatLLM::handleRecalculate(bool isRecalc)
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{
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if (m_isRecalc != isRecalc) {
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m_isRecalc = isRecalc;
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emit recalcChanged();
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}
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return !m_stopGenerating;
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}
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bool ChatLLM::prompt(const QString &prompt, const QString &prompt_template, int32_t n_predict, int32_t top_k,
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float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens, int n_threads)
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{
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if (!isModelLoaded())
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return false;
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QString instructPrompt = prompt_template.arg(prompt);
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m_stopGenerating = false;
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auto promptFunc = std::bind(&ChatLLM::handlePrompt, this, std::placeholders::_1);
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auto responseFunc = std::bind(&ChatLLM::handleResponse, this, std::placeholders::_1,
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std::placeholders::_2);
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auto recalcFunc = std::bind(&ChatLLM::handleRecalculate, this, std::placeholders::_1);
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emit responseStarted();
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qint32 logitsBefore = m_ctx.logits.size();
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m_ctx.n_predict = n_predict;
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m_ctx.top_k = top_k;
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m_ctx.top_p = top_p;
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m_ctx.temp = temp;
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m_ctx.n_batch = n_batch;
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m_ctx.repeat_penalty = repeat_penalty;
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m_ctx.repeat_last_n = repeat_penalty_tokens;
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m_llmodel->setThreadCount(n_threads);
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#if defined(DEBUG)
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printf("%s", qPrintable(instructPrompt));
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fflush(stdout);
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#endif
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m_llmodel->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, m_ctx);
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#if defined(DEBUG)
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printf("\n");
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fflush(stdout);
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#endif
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m_responseLogits += m_ctx.logits.size() - logitsBefore;
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std::string trimmed = trim_whitespace(m_response);
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if (trimmed != m_response) {
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m_response = trimmed;
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emit responseChanged();
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}
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emit responseStopped();
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return true;
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}
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void ChatLLM::unloadModel()
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{
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#if defined(DEBUG)
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qDebug() << "chatllm unloadModel" << m_chat->id();
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#endif
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saveState();
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delete m_llmodel;
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m_llmodel = nullptr;
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emit isModelLoadedChanged();
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}
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void ChatLLM::reloadModel(const QString &modelName)
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{
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#if defined(DEBUG)
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qDebug() << "chatllm reloadModel" << m_chat->id();
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#endif
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if (modelName.isEmpty()) {
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loadDefaultModel();
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} else {
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loadModel(modelName);
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}
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}
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void ChatLLM::generateName()
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{
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Q_ASSERT(isModelLoaded());
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if (!isModelLoaded())
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return;
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QString instructPrompt("### Instruction:\n"
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"Describe response above in three words.\n"
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"### Response:\n");
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auto promptFunc = std::bind(&ChatLLM::handleNamePrompt, this, std::placeholders::_1);
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auto responseFunc = std::bind(&ChatLLM::handleNameResponse, this, std::placeholders::_1,
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std::placeholders::_2);
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auto recalcFunc = std::bind(&ChatLLM::handleNameRecalculate, this, std::placeholders::_1);
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LLModel::PromptContext ctx = m_ctx;
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#if defined(DEBUG)
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printf("%s", qPrintable(instructPrompt));
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fflush(stdout);
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#endif
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m_llmodel->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, ctx);
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#if defined(DEBUG)
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printf("\n");
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fflush(stdout);
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#endif
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std::string trimmed = trim_whitespace(m_nameResponse);
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if (trimmed != m_nameResponse) {
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m_nameResponse = trimmed;
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emit generatedNameChanged();
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}
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}
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void ChatLLM::handleChatIdChanged()
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{
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m_llmThread.setObjectName(m_chat->id());
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}
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bool ChatLLM::handleNamePrompt(int32_t token)
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{
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Q_UNUSED(token);
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qt_noop();
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return true;
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}
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bool ChatLLM::handleNameResponse(int32_t token, const std::string &response)
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{
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Q_UNUSED(token);
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m_nameResponse.append(response);
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emit generatedNameChanged();
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QString gen = QString::fromStdString(m_nameResponse).simplified();
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QStringList words = gen.split(' ', Qt::SkipEmptyParts);
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int wordCount = words.size();
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return words.size() <= 3;
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}
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bool ChatLLM::handleNameRecalculate(bool isRecalc)
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{
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Q_UNUSED(isRecalc);
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Q_UNREACHABLE();
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return true;
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}
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bool ChatLLM::serialize(QDataStream &stream, int version)
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{
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stream << response();
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stream << generatedName();
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stream << m_promptResponseTokens;
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stream << m_responseLogits;
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stream << m_ctx.n_past;
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stream << quint64(m_ctx.logits.size());
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stream.writeRawData(reinterpret_cast<const char*>(m_ctx.logits.data()), m_ctx.logits.size() * sizeof(float));
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stream << quint64(m_ctx.tokens.size());
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stream.writeRawData(reinterpret_cast<const char*>(m_ctx.tokens.data()), m_ctx.tokens.size() * sizeof(int));
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saveState();
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QByteArray compressed = qCompress(m_state);
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stream << compressed;
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#if defined(DEBUG)
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qDebug() << "chatllm serialize" << m_chat->id() << m_state.size();
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#endif
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return stream.status() == QDataStream::Ok;
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}
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bool ChatLLM::deserialize(QDataStream &stream, int version)
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{
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QString response;
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stream >> response;
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m_response = response.toStdString();
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QString nameResponse;
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stream >> nameResponse;
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m_nameResponse = nameResponse.toStdString();
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stream >> m_promptResponseTokens;
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stream >> m_responseLogits;
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stream >> m_ctx.n_past;
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quint64 logitsSize;
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stream >> logitsSize;
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m_ctx.logits.resize(logitsSize);
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stream.readRawData(reinterpret_cast<char*>(m_ctx.logits.data()), logitsSize * sizeof(float));
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quint64 tokensSize;
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stream >> tokensSize;
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m_ctx.tokens.resize(tokensSize);
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stream.readRawData(reinterpret_cast<char*>(m_ctx.tokens.data()), tokensSize * sizeof(int));
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if (version > 0) {
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QByteArray compressed;
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stream >> compressed;
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m_state = qUncompress(compressed);
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} else {
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stream >> m_state;
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}
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#if defined(DEBUG)
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qDebug() << "chatllm deserialize" << m_chat->id();
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#endif
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return stream.status() == QDataStream::Ok;
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}
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void ChatLLM::saveState()
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{
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if (!isModelLoaded())
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return;
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const size_t stateSize = m_llmodel->stateSize();
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m_state.resize(stateSize);
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#if defined(DEBUG)
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qDebug() << "chatllm saveState" << m_chat->id() << "size:" << m_state.size();
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#endif
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m_llmodel->saveState(static_cast<uint8_t*>(reinterpret_cast<void*>(m_state.data())));
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}
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void ChatLLM::restoreState()
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{
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if (!isModelLoaded() || m_state.isEmpty())
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return;
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#if defined(DEBUG)
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qDebug() << "chatllm restoreState" << m_chat->id() << "size:" << m_state.size();
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#endif
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m_llmodel->restoreState(static_cast<const uint8_t*>(reinterpret_cast<void*>(m_state.data())));
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}
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