#include "chatllm.h" #include "chat.h" #include "chatgpt.h" #include "modellist.h" #include "network.h" #include "mysettings.h" #include "../gpt4all-backend/llmodel.h" //#define DEBUG //#define DEBUG_MODEL_LOADING #define MPT_INTERNAL_STATE_VERSION 0 #define GPTJ_INTERNAL_STATE_VERSION 0 #define REPLIT_INTERNAL_STATE_VERSION 0 #define LLAMA_INTERNAL_STATE_VERSION 0 #define FALCON_INTERNAL_STATE_VERSION 0 #define BERT_INTERNAL_STATE_VERSION 0 #define STARCODER_INTERNAL_STATE_VERSION 0 class LLModelStore { public: static LLModelStore *globalInstance(); LLModelInfo acquireModel(); // will block until llmodel is ready void releaseModel(const LLModelInfo &info); // must be called when you are done private: LLModelStore() { // seed with empty model m_availableModels.append(LLModelInfo()); } ~LLModelStore() {} QVector m_availableModels; QMutex m_mutex; QWaitCondition m_condition; friend class MyLLModelStore; }; class MyLLModelStore : public LLModelStore { }; Q_GLOBAL_STATIC(MyLLModelStore, storeInstance) LLModelStore *LLModelStore::globalInstance() { return storeInstance(); } LLModelInfo LLModelStore::acquireModel() { QMutexLocker locker(&m_mutex); while (m_availableModels.isEmpty()) m_condition.wait(locker.mutex()); return m_availableModels.takeFirst(); } void LLModelStore::releaseModel(const LLModelInfo &info) { QMutexLocker locker(&m_mutex); m_availableModels.append(info); Q_ASSERT(m_availableModels.count() < 2); m_condition.wakeAll(); } ChatLLM::ChatLLM(Chat *parent, bool isServer) : QObject{nullptr} , m_promptResponseTokens(0) , m_promptTokens(0) , m_isRecalc(false) , m_shouldBeLoaded(true) , m_stopGenerating(false) , m_timer(nullptr) , m_isServer(isServer) , m_forceMetal(MySettings::globalInstance()->forceMetal()) , m_reloadingToChangeVariant(false) , m_processedSystemPrompt(false) { moveToThread(&m_llmThread); connect(this, &ChatLLM::sendStartup, Network::globalInstance(), &Network::sendStartup); connect(this, &ChatLLM::sendModelLoaded, Network::globalInstance(), &Network::sendModelLoaded); connect(this, &ChatLLM::shouldBeLoadedChanged, this, &ChatLLM::handleShouldBeLoadedChanged, Qt::QueuedConnection); // explicitly queued connect(parent, &Chat::idChanged, this, &ChatLLM::handleChatIdChanged); connect(&m_llmThread, &QThread::started, this, &ChatLLM::handleThreadStarted); connect(MySettings::globalInstance(), &MySettings::forceMetalChanged, this, &ChatLLM::handleForceMetalChanged); connect(MySettings::globalInstance(), &MySettings::deviceChanged, this, &ChatLLM::handleDeviceChanged); // The following are blocking operations and will block the llm thread connect(this, &ChatLLM::requestRetrieveFromDB, LocalDocs::globalInstance()->database(), &Database::retrieveFromDB, Qt::BlockingQueuedConnection); m_llmThread.setObjectName(parent->id()); m_llmThread.start(); } ChatLLM::~ChatLLM() { m_stopGenerating = true; m_llmThread.quit(); m_llmThread.wait(); // The only time we should have a model loaded here is on shutdown // as we explicitly unload the model in all other circumstances if (isModelLoaded()) { delete m_llModelInfo.model; m_llModelInfo.model = nullptr; } } void ChatLLM::handleThreadStarted() { m_timer = new TokenTimer(this); connect(m_timer, &TokenTimer::report, this, &ChatLLM::reportSpeed); emit threadStarted(); } void ChatLLM::handleForceMetalChanged(bool forceMetal) { #if defined(Q_OS_MAC) && defined(__arm__) m_forceMetal = forceMetal; if (isModelLoaded() && m_shouldBeLoaded) { m_reloadingToChangeVariant = true; unloadModel(); reloadModel(); m_reloadingToChangeVariant = false; } #endif } void ChatLLM::handleDeviceChanged() { if (isModelLoaded() && m_shouldBeLoaded) { m_reloadingToChangeVariant = true; unloadModel(); reloadModel(); m_reloadingToChangeVariant = false; } } bool ChatLLM::loadDefaultModel() { ModelInfo defaultModel = ModelList::globalInstance()->defaultModelInfo(); if (defaultModel.filename().isEmpty()) { emit modelLoadingError(QString("Could not find any model to load")); return false; } return loadModel(defaultModel); } bool ChatLLM::loadModel(const ModelInfo &modelInfo) { // This is a complicated method because N different possible threads are interested in the outcome // of this method. Why? Because we have a main/gui thread trying to monitor the state of N different // possible chat threads all vying for a single resource - the currently loaded model - as the user // switches back and forth between chats. It is important for our main/gui thread to never block // but simultaneously always have up2date information with regards to which chat has the model loaded // and what the type and name of that model is. I've tried to comment extensively in this method // to provide an overview of what we're doing here. // We're already loaded with this model if (isModelLoaded() && this->modelInfo() == modelInfo) return true; bool isChatGPT = modelInfo.isChatGPT; QString filePath = modelInfo.dirpath + modelInfo.filename(); QFileInfo fileInfo(filePath); // We have a live model, but it isn't the one we want bool alreadyAcquired = isModelLoaded(); if (alreadyAcquired) { resetContext(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "already acquired model deleted" << m_llmThread.objectName() << m_llModelInfo.model; #endif delete m_llModelInfo.model; m_llModelInfo.model = nullptr; emit isModelLoadedChanged(false); } else if (!m_isServer) { // This is a blocking call that tries to retrieve the model we need from the model store. // If it succeeds, then we just have to restore state. If the store has never had a model // returned to it, then the modelInfo.model pointer should be null which will happen on startup m_llModelInfo = LLModelStore::globalInstance()->acquireModel(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "acquired model from store" << m_llmThread.objectName() << m_llModelInfo.model; #endif // At this point it is possible that while we were blocked waiting to acquire the model from the // store, that our state was changed to not be loaded. If this is the case, release the model // back into the store and quit loading if (!m_shouldBeLoaded) { #if defined(DEBUG_MODEL_LOADING) qDebug() << "no longer need model" << m_llmThread.objectName() << m_llModelInfo.model; #endif LLModelStore::globalInstance()->releaseModel(m_llModelInfo); m_llModelInfo = LLModelInfo(); emit isModelLoadedChanged(false); return false; } // Check if the store just gave us exactly the model we were looking for if (m_llModelInfo.model && m_llModelInfo.fileInfo == fileInfo && !m_reloadingToChangeVariant) { #if defined(DEBUG_MODEL_LOADING) qDebug() << "store had our model" << m_llmThread.objectName() << m_llModelInfo.model; #endif restoreState(); emit isModelLoadedChanged(true); setModelInfo(modelInfo); Q_ASSERT(!m_modelInfo.filename().isEmpty()); if (m_modelInfo.filename().isEmpty()) emit modelLoadingError(QString("Modelinfo is left null for %1").arg(modelInfo.filename())); else processSystemPrompt(); return true; } else { // Release the memory since we have to switch to a different model. #if defined(DEBUG_MODEL_LOADING) qDebug() << "deleting model" << m_llmThread.objectName() << m_llModelInfo.model; #endif delete m_llModelInfo.model; m_llModelInfo.model = nullptr; } } // Guarantee we've released the previous models memory Q_ASSERT(!m_llModelInfo.model); // Store the file info in the modelInfo in case we have an error loading m_llModelInfo.fileInfo = fileInfo; // Check if we've previously tried to load this file and failed/crashed if (MySettings::globalInstance()->attemptModelLoad() == filePath) { MySettings::globalInstance()->setAttemptModelLoad(QString()); // clear the flag if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_llModelInfo); // release back into the store m_llModelInfo = LLModelInfo(); emit modelLoadingError(QString("Previous attempt to load model resulted in crash for `%1` most likely due to out of memory. You should either remove this model or decrease your system RAM by closing other applications.").arg(modelInfo.filename())); } if (fileInfo.exists()) { if (isChatGPT) { QString apiKey; QString chatGPTModel = fileInfo.completeBaseName().remove(0, 8); // remove the chatgpt- prefix { QFile file(filePath); file.open(QIODeviceBase::ReadOnly | QIODeviceBase::Text); QTextStream stream(&file); apiKey = stream.readAll(); file.close(); } m_llModelType = LLModelType::CHATGPT_; ChatGPT *model = new ChatGPT(); model->setModelName(chatGPTModel); model->setAPIKey(apiKey); m_llModelInfo.model = model; } else { #if defined(Q_OS_MAC) && defined(__arm__) if (m_forceMetal) m_llModelInfo.model = LLMImplementation::construct(filePath.toStdString(), "metal"); else m_llModelInfo.model = LLMImplementation::construct(filePath.toStdString(), "auto"); #else m_llModelInfo.model = LLModel::Implementation::construct(filePath.toStdString(), "auto"); #endif if (m_llModelInfo.model) { // Update the settings that a model is being loaded and update the device list MySettings::globalInstance()->setAttemptModelLoad(filePath); std::vector devices = m_llModelInfo.model->availableGPUDevices(0); QVector deviceList{ "Auto" }; for (LLModel::GPUDevice &d : devices) deviceList << QString::fromStdString(d.name); deviceList << "CPU"; MySettings::globalInstance()->setDeviceList(deviceList); // Pick the best match for the device const QString requestedDevice = MySettings::globalInstance()->device(); if (requestedDevice != "CPU") { const size_t requiredMemory = m_llModelInfo.model->requiredMem(filePath.toStdString()); std::vector availableDevices = m_llModelInfo.model->availableGPUDevices(requiredMemory); if (!availableDevices.empty() && requestedDevice == "Auto" && availableDevices.front().type == 2 /*a discrete gpu*/) { m_llModelInfo.model->initializeGPUDevice(availableDevices.front()); } else { for (LLModel::GPUDevice &d : availableDevices) { if (QString::fromStdString(d.name) == requestedDevice) { m_llModelInfo.model->initializeGPUDevice(d); break; } } } } bool success = m_llModelInfo.model->loadModel(filePath.toStdString()); MySettings::globalInstance()->setAttemptModelLoad(QString()); if (!success) { delete std::exchange(m_llModelInfo.model, nullptr); if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_llModelInfo); // release back into the store m_llModelInfo = LLModelInfo(); emit modelLoadingError(QString("Could not load model due to invalid model file for %1").arg(modelInfo.filename())); } else { switch (m_llModelInfo.model->implementation().modelType()[0]) { case 'L': m_llModelType = LLModelType::LLAMA_; break; case 'G': m_llModelType = LLModelType::GPTJ_; break; case 'M': m_llModelType = LLModelType::MPT_; break; case 'R': m_llModelType = LLModelType::REPLIT_; break; case 'F': m_llModelType = LLModelType::FALCON_; break; case 'B': m_llModelType = LLModelType::BERT_; break; case 'S': m_llModelType = LLModelType::STARCODER_; break; default: { delete std::exchange(m_llModelInfo.model, nullptr); if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_llModelInfo); // release back into the store m_llModelInfo = LLModelInfo(); emit modelLoadingError(QString("Could not determine model type for %1").arg(modelInfo.filename())); } } } } else { if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_llModelInfo); // release back into the store m_llModelInfo = LLModelInfo(); emit modelLoadingError(QString("Could not load model due to invalid format for %1").arg(modelInfo.filename())); } } #if defined(DEBUG_MODEL_LOADING) qDebug() << "new model" << m_llmThread.objectName() << m_llModelInfo.model; #endif restoreState(); #if defined(DEBUG) qDebug() << "modelLoadedChanged" << m_llmThread.objectName(); fflush(stdout); #endif emit isModelLoadedChanged(isModelLoaded()); static bool isFirstLoad = true; if (isFirstLoad) { emit sendStartup(); isFirstLoad = false; } else emit sendModelLoaded(); } else { if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_llModelInfo); // release back into the store m_llModelInfo = LLModelInfo(); emit modelLoadingError(QString("Could not find file for model %1").arg(modelInfo.filename())); } if (m_llModelInfo.model) setModelInfo(modelInfo); processSystemPrompt(); return m_llModelInfo.model; } bool ChatLLM::isModelLoaded() const { return m_llModelInfo.model && m_llModelInfo.model->isModelLoaded(); } void ChatLLM::regenerateResponse() { // ChatGPT uses a different semantic meaning for n_past than local models. For ChatGPT, the meaning // of n_past is of the number of prompt/response pairs, rather than for total tokens. if (m_llModelType == LLModelType::CHATGPT_) m_ctx.n_past -= 1; else m_ctx.n_past -= m_promptResponseTokens; m_ctx.n_past = std::max(0, m_ctx.n_past); m_ctx.tokens.erase(m_ctx.tokens.end() -= m_promptResponseTokens, m_ctx.tokens.end()); m_promptResponseTokens = 0; m_promptTokens = 0; m_response = std::string(); emit responseChanged(QString::fromStdString(m_response)); } void ChatLLM::resetResponse() { m_promptTokens = 0; m_promptResponseTokens = 0; m_response = std::string(); emit responseChanged(QString::fromStdString(m_response)); } void ChatLLM::resetContext() { regenerateResponse(); m_processedSystemPrompt = false; m_ctx = LLModel::PromptContext(); } std::string remove_leading_whitespace(const std::string& input) { auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) { return !std::isspace(c); }); return std::string(first_non_whitespace, input.end()); } std::string trim_whitespace(const std::string& input) { auto first_non_whitespace = std::find_if(input.begin(), input.end(), [](unsigned char c) { return !std::isspace(c); }); auto last_non_whitespace = std::find_if(input.rbegin(), input.rend(), [](unsigned char c) { return !std::isspace(c); }).base(); return std::string(first_non_whitespace, last_non_whitespace); } QString ChatLLM::response() const { return QString::fromStdString(remove_leading_whitespace(m_response)); } ModelInfo ChatLLM::modelInfo() const { return m_modelInfo; } void ChatLLM::setModelInfo(const ModelInfo &modelInfo) { m_modelInfo = modelInfo; emit modelInfoChanged(modelInfo); } void ChatLLM::modelChangeRequested(const ModelInfo &modelInfo) { loadModel(modelInfo); } bool ChatLLM::handlePrompt(int32_t token) { // m_promptResponseTokens is related to last prompt/response not // the entire context window which we can reset on regenerate prompt #if defined(DEBUG) qDebug() << "prompt process" << m_llmThread.objectName() << token; #endif ++m_promptTokens; ++m_promptResponseTokens; m_timer->start(); return !m_stopGenerating; } bool ChatLLM::handleResponse(int32_t token, const std::string &response) { #if defined(DEBUG) printf("%s", response.c_str()); fflush(stdout); #endif // check for error if (token < 0) { m_response.append(response); emit responseChanged(QString::fromStdString(m_response)); return false; } // m_promptResponseTokens is related to last prompt/response not // the entire context window which we can reset on regenerate prompt ++m_promptResponseTokens; m_timer->inc(); Q_ASSERT(!response.empty()); m_response.append(response); emit responseChanged(QString::fromStdString(m_response)); return !m_stopGenerating; } bool ChatLLM::handleRecalculate(bool isRecalc) { #if defined(DEBUG) qDebug() << "recalculate" << m_llmThread.objectName() << isRecalc; #endif if (m_isRecalc != isRecalc) { m_isRecalc = isRecalc; emit recalcChanged(); } return !m_stopGenerating; } bool ChatLLM::prompt(const QList &collectionList, const QString &prompt) { if (!m_processedSystemPrompt) processSystemPrompt(); const QString promptTemplate = MySettings::globalInstance()->modelPromptTemplate(m_modelInfo); const int32_t n_predict = MySettings::globalInstance()->modelMaxLength(m_modelInfo); const int32_t top_k = MySettings::globalInstance()->modelTopK(m_modelInfo); const float top_p = MySettings::globalInstance()->modelTopP(m_modelInfo); const float temp = MySettings::globalInstance()->modelTemperature(m_modelInfo); const int32_t n_batch = MySettings::globalInstance()->modelPromptBatchSize(m_modelInfo); const float repeat_penalty = MySettings::globalInstance()->modelRepeatPenalty(m_modelInfo); const int32_t repeat_penalty_tokens = MySettings::globalInstance()->modelRepeatPenaltyTokens(m_modelInfo); return promptInternal(collectionList, prompt, promptTemplate, n_predict, top_k, top_p, temp, n_batch, repeat_penalty, repeat_penalty_tokens); } bool ChatLLM::promptInternal(const QList &collectionList, const QString &prompt, const QString &promptTemplate, int32_t n_predict, int32_t top_k, float top_p, float temp, int32_t n_batch, float repeat_penalty, int32_t repeat_penalty_tokens) { if (!isModelLoaded()) return false; QList databaseResults; const int retrievalSize = MySettings::globalInstance()->localDocsRetrievalSize(); emit requestRetrieveFromDB(collectionList, prompt, retrievalSize, &databaseResults); // blocks emit databaseResultsChanged(databaseResults); // Augment the prompt template with the results if any QList augmentedTemplate; if (!databaseResults.isEmpty()) augmentedTemplate.append("### Context:"); for (const ResultInfo &info : databaseResults) augmentedTemplate.append(info.text); augmentedTemplate.append(promptTemplate); QString instructPrompt = augmentedTemplate.join("\n").arg(prompt); int n_threads = MySettings::globalInstance()->threadCount(); m_stopGenerating = false; auto promptFunc = std::bind(&ChatLLM::handlePrompt, this, std::placeholders::_1); auto responseFunc = std::bind(&ChatLLM::handleResponse, this, std::placeholders::_1, std::placeholders::_2); auto recalcFunc = std::bind(&ChatLLM::handleRecalculate, this, std::placeholders::_1); emit promptProcessing(); qint32 logitsBefore = m_ctx.logits.size(); m_ctx.n_predict = n_predict; m_ctx.top_k = top_k; m_ctx.top_p = top_p; m_ctx.temp = temp; m_ctx.n_batch = n_batch; m_ctx.repeat_penalty = repeat_penalty; m_ctx.repeat_last_n = repeat_penalty_tokens; m_llModelInfo.model->setThreadCount(n_threads); #if defined(DEBUG) printf("%s", qPrintable(instructPrompt)); fflush(stdout); #endif m_timer->start(); m_llModelInfo.model->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, m_ctx); #if defined(DEBUG) printf("\n"); fflush(stdout); #endif m_timer->stop(); std::string trimmed = trim_whitespace(m_response); if (trimmed != m_response) { m_response = trimmed; emit responseChanged(QString::fromStdString(m_response)); } emit responseStopped(); return true; } void ChatLLM::setShouldBeLoaded(bool b) { #if defined(DEBUG_MODEL_LOADING) qDebug() << "setShouldBeLoaded" << m_llmThread.objectName() << b << m_llModelInfo.model; #endif m_shouldBeLoaded = b; // atomic emit shouldBeLoadedChanged(); } void ChatLLM::handleShouldBeLoadedChanged() { if (m_shouldBeLoaded) reloadModel(); else unloadModel(); } void ChatLLM::forceUnloadModel() { m_shouldBeLoaded = false; // atomic unloadModel(); } void ChatLLM::unloadModel() { if (!isModelLoaded() || m_isServer) return; saveState(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "unloadModel" << m_llmThread.objectName() << m_llModelInfo.model; #endif LLModelStore::globalInstance()->releaseModel(m_llModelInfo); m_llModelInfo = LLModelInfo(); emit isModelLoadedChanged(false); } void ChatLLM::reloadModel() { if (isModelLoaded() || m_isServer) return; #if defined(DEBUG_MODEL_LOADING) qDebug() << "reloadModel" << m_llmThread.objectName() << m_llModelInfo.model; #endif const ModelInfo m = modelInfo(); if (m.name().isEmpty()) loadDefaultModel(); else loadModel(m); } void ChatLLM::generateName() { Q_ASSERT(isModelLoaded()); if (!isModelLoaded()) return; QString instructPrompt("### Instruction:\n" "Describe response above in three words.\n" "### Response:\n"); auto promptFunc = std::bind(&ChatLLM::handleNamePrompt, this, std::placeholders::_1); auto responseFunc = std::bind(&ChatLLM::handleNameResponse, this, std::placeholders::_1, std::placeholders::_2); auto recalcFunc = std::bind(&ChatLLM::handleNameRecalculate, this, std::placeholders::_1); LLModel::PromptContext ctx = m_ctx; #if defined(DEBUG) printf("%s", qPrintable(instructPrompt)); fflush(stdout); #endif m_llModelInfo.model->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, ctx); #if defined(DEBUG) printf("\n"); fflush(stdout); #endif std::string trimmed = trim_whitespace(m_nameResponse); if (trimmed != m_nameResponse) { m_nameResponse = trimmed; emit generatedNameChanged(QString::fromStdString(m_nameResponse)); } } void ChatLLM::handleChatIdChanged(const QString &id) { m_llmThread.setObjectName(id); } bool ChatLLM::handleNamePrompt(int32_t token) { #if defined(DEBUG) qDebug() << "name prompt" << m_llmThread.objectName() << token; #endif Q_UNUSED(token); qt_noop(); return !m_stopGenerating; } bool ChatLLM::handleNameResponse(int32_t token, const std::string &response) { #if defined(DEBUG) qDebug() << "name response" << m_llmThread.objectName() << token << response; #endif Q_UNUSED(token); m_nameResponse.append(response); emit generatedNameChanged(QString::fromStdString(m_nameResponse)); QString gen = QString::fromStdString(m_nameResponse).simplified(); QStringList words = gen.split(' ', Qt::SkipEmptyParts); return words.size() <= 3; } bool ChatLLM::handleNameRecalculate(bool isRecalc) { #if defined(DEBUG) qDebug() << "name recalc" << m_llmThread.objectName() << isRecalc; #endif Q_UNUSED(isRecalc); qt_noop(); return true; } bool ChatLLM::handleSystemPrompt(int32_t token) { #if defined(DEBUG) qDebug() << "system prompt" << m_llmThread.objectName() << token << m_stopGenerating; #endif Q_UNUSED(token); return !m_stopGenerating; } bool ChatLLM::handleSystemResponse(int32_t token, const std::string &response) { #if defined(DEBUG) qDebug() << "system response" << m_llmThread.objectName() << token << response << m_stopGenerating; #endif Q_UNUSED(token); Q_UNUSED(response); return false; } bool ChatLLM::handleSystemRecalculate(bool isRecalc) { #if defined(DEBUG) qDebug() << "system recalc" << m_llmThread.objectName() << isRecalc; #endif Q_UNUSED(isRecalc); return false; } bool ChatLLM::serialize(QDataStream &stream, int version) { if (version > 1) { stream << m_llModelType; switch (m_llModelType) { case REPLIT_: stream << REPLIT_INTERNAL_STATE_VERSION; break; case MPT_: stream << MPT_INTERNAL_STATE_VERSION; break; case GPTJ_: stream << GPTJ_INTERNAL_STATE_VERSION; break; case LLAMA_: stream << LLAMA_INTERNAL_STATE_VERSION; break; case FALCON_: stream << FALCON_INTERNAL_STATE_VERSION; break; case BERT_: stream << BERT_INTERNAL_STATE_VERSION; break; case STARCODER_: stream << STARCODER_INTERNAL_STATE_VERSION; break; default: Q_UNREACHABLE(); } } stream << response(); stream << generatedName(); stream << m_promptResponseTokens; if (version <= 3) { int responseLogits; stream << responseLogits; } stream << m_ctx.n_past; stream << quint64(m_ctx.logits.size()); stream.writeRawData(reinterpret_cast(m_ctx.logits.data()), m_ctx.logits.size() * sizeof(float)); stream << quint64(m_ctx.tokens.size()); stream.writeRawData(reinterpret_cast(m_ctx.tokens.data()), m_ctx.tokens.size() * sizeof(int)); saveState(); QByteArray compressed = qCompress(m_state); stream << compressed; #if defined(DEBUG) qDebug() << "serialize" << m_llmThread.objectName() << m_state.size(); #endif return stream.status() == QDataStream::Ok; } bool ChatLLM::deserialize(QDataStream &stream, int version) { if (version > 1) { int internalStateVersion; stream >> m_llModelType; stream >> internalStateVersion; // for future use } QString response; stream >> response; m_response = response.toStdString(); QString nameResponse; stream >> nameResponse; m_nameResponse = nameResponse.toStdString(); stream >> m_promptResponseTokens; if (version <= 3) { int responseLogits; stream >> responseLogits; } stream >> m_ctx.n_past; quint64 logitsSize; stream >> logitsSize; m_ctx.logits.resize(logitsSize); stream.readRawData(reinterpret_cast(m_ctx.logits.data()), logitsSize * sizeof(float)); quint64 tokensSize; stream >> tokensSize; m_ctx.tokens.resize(tokensSize); stream.readRawData(reinterpret_cast(m_ctx.tokens.data()), tokensSize * sizeof(int)); if (version > 0) { QByteArray compressed; stream >> compressed; m_state = qUncompress(compressed); } else { stream >> m_state; } #if defined(DEBUG) qDebug() << "deserialize" << m_llmThread.objectName(); #endif return stream.status() == QDataStream::Ok; } void ChatLLM::saveState() { if (!isModelLoaded()) return; if (m_llModelType == LLModelType::CHATGPT_) { m_state.clear(); QDataStream stream(&m_state, QIODeviceBase::WriteOnly); stream.setVersion(QDataStream::Qt_6_5); ChatGPT *chatGPT = static_cast(m_llModelInfo.model); stream << chatGPT->context(); return; } const size_t stateSize = m_llModelInfo.model->stateSize(); m_state.resize(stateSize); #if defined(DEBUG) qDebug() << "saveState" << m_llmThread.objectName() << "size:" << m_state.size(); #endif m_llModelInfo.model->saveState(static_cast(reinterpret_cast(m_state.data()))); } void ChatLLM::restoreState() { if (!isModelLoaded() || m_state.isEmpty()) return; if (m_llModelType == LLModelType::CHATGPT_) { QDataStream stream(&m_state, QIODeviceBase::ReadOnly); stream.setVersion(QDataStream::Qt_6_5); ChatGPT *chatGPT = static_cast(m_llModelInfo.model); QList context; stream >> context; chatGPT->setContext(context); m_state.clear(); m_state.resize(0); return; } #if defined(DEBUG) qDebug() << "restoreState" << m_llmThread.objectName() << "size:" << m_state.size(); #endif m_processedSystemPrompt = true; m_llModelInfo.model->restoreState(static_cast(reinterpret_cast(m_state.data()))); m_state.clear(); m_state.resize(0); } void ChatLLM::processSystemPrompt() { Q_ASSERT(isModelLoaded()); if (!isModelLoaded() || m_processedSystemPrompt || m_isServer) return; const std::string systemPrompt = MySettings::globalInstance()->modelSystemPrompt(m_modelInfo).toStdString(); if (QString::fromStdString(systemPrompt).trimmed().isEmpty()) { m_processedSystemPrompt = true; return; } m_stopGenerating = false; auto promptFunc = std::bind(&ChatLLM::handleSystemPrompt, this, std::placeholders::_1); auto responseFunc = std::bind(&ChatLLM::handleSystemResponse, this, std::placeholders::_1, std::placeholders::_2); auto recalcFunc = std::bind(&ChatLLM::handleSystemRecalculate, this, std::placeholders::_1); const int32_t n_predict = MySettings::globalInstance()->modelMaxLength(m_modelInfo); const int32_t top_k = MySettings::globalInstance()->modelTopK(m_modelInfo); const float top_p = MySettings::globalInstance()->modelTopP(m_modelInfo); const float temp = MySettings::globalInstance()->modelTemperature(m_modelInfo); const int32_t n_batch = MySettings::globalInstance()->modelPromptBatchSize(m_modelInfo); const float repeat_penalty = MySettings::globalInstance()->modelRepeatPenalty(m_modelInfo); const int32_t repeat_penalty_tokens = MySettings::globalInstance()->modelRepeatPenaltyTokens(m_modelInfo); int n_threads = MySettings::globalInstance()->threadCount(); m_ctx.n_predict = n_predict; m_ctx.top_k = top_k; m_ctx.top_p = top_p; m_ctx.temp = temp; m_ctx.n_batch = n_batch; m_ctx.repeat_penalty = repeat_penalty; m_ctx.repeat_last_n = repeat_penalty_tokens; m_llModelInfo.model->setThreadCount(n_threads); #if defined(DEBUG) printf("%s", qPrintable(QString::fromStdString(systemPrompt))); fflush(stdout); #endif m_llModelInfo.model->prompt(systemPrompt, promptFunc, responseFunc, recalcFunc, m_ctx); #if defined(DEBUG) printf("\n"); fflush(stdout); #endif m_processedSystemPrompt = true; }