#include "chatllm.h" #include "chat.h" #include "chatapi.h" #include "localdocs.h" #include "modellist.h" #include "network.h" #include "mysettings.h" #include "../gpt4all-backend/llmodel.h" //#define DEBUG //#define DEBUG_MODEL_LOADING #define GPTJ_INTERNAL_STATE_VERSION 0 #define LLAMA_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(false) , m_forceUnloadModel(false) , m_markedForDeletion(false) , m_shouldTrySwitchContext(false) , m_stopGenerating(false) , m_timer(nullptr) , m_isServer(isServer) , m_forceMetal(MySettings::globalInstance()->forceMetal()) , m_reloadingToChangeVariant(false) , m_processedSystemPrompt(false) , m_restoreStateFromText(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(this, &ChatLLM::shouldTrySwitchContextChanged, this, &ChatLLM::handleShouldTrySwitchContextChanged, 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() { destroy(); } void ChatLLM::destroy() { 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::trySwitchContextOfLoadedModel(const ModelInfo &modelInfo) { // We're trying to see if the store already has the model fully loaded that we wish to use // and if so we just acquire it from the store and switch the context and return true. If the // store doesn't have it or we're already loaded or in any other case just return false. // If we're already loaded or a server or we're reloading to change the variant/device or the // modelInfo is empty, then this should fail if (isModelLoaded() || m_isServer || m_reloadingToChangeVariant || modelInfo.name().isEmpty()) { m_shouldTrySwitchContext = false; emit trySwitchContextOfLoadedModelCompleted(false); return false; } QString filePath = modelInfo.dirpath + modelInfo.filename(); QFileInfo fileInfo(filePath); m_llModelInfo = LLModelStore::globalInstance()->acquireModel(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "acquired model from store" << m_llmThread.objectName() << m_llModelInfo.model; #endif // The store gave us no already loaded model, the wrong type of model, then give it back to the // store and fail if (!m_llModelInfo.model || m_llModelInfo.fileInfo != fileInfo) { LLModelStore::globalInstance()->releaseModel(m_llModelInfo); m_llModelInfo = LLModelInfo(); m_shouldTrySwitchContext = false; emit trySwitchContextOfLoadedModelCompleted(false); return false; } #if defined(DEBUG_MODEL_LOADING) qDebug() << "store had our model" << m_llmThread.objectName() << m_llModelInfo.model; #endif // We should be loaded and now we are m_shouldBeLoaded = true; m_shouldTrySwitchContext = false; // Restore, signal and process restoreState(); emit modelLoadingPercentageChanged(1.0f); emit trySwitchContextOfLoadedModelCompleted(true); processSystemPrompt(); return true; } 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; 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 modelLoadingPercentageChanged(std::numeric_limits::min()); // small non-zero positive value } 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 modelLoadingPercentageChanged(0.0f); 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 modelLoadingPercentageChanged(1.0f); 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; if (fileInfo.exists()) { if (modelInfo.isOnline) { QString apiKey; QString modelName; { QFile file(filePath); bool success = file.open(QIODeviceBase::ReadOnly); (void)success; Q_ASSERT(success); QJsonDocument doc = QJsonDocument::fromJson(file.readAll()); QJsonObject obj = doc.object(); apiKey = obj["apiKey"].toString(); modelName = obj["modelName"].toString(); } m_llModelType = LLModelType::API_; ChatAPI *model = new ChatAPI(); model->setModelName(modelName); model->setRequestURL(modelInfo.url()); model->setAPIKey(apiKey); m_llModelInfo.model = model; } else { auto n_ctx = MySettings::globalInstance()->modelContextLength(modelInfo); m_ctx.n_ctx = n_ctx; auto ngl = MySettings::globalInstance()->modelGpuLayers(modelInfo); std::string buildVariant = "auto"; #if defined(Q_OS_MAC) && defined(__arm__) if (m_forceMetal) buildVariant = "metal"; #endif m_llModelInfo.model = LLModel::Implementation::construct(filePath.toStdString(), buildVariant, n_ctx); if (m_llModelInfo.model) { if (m_llModelInfo.model->isModelBlacklisted(filePath.toStdString())) { static QSet warned; auto fname = modelInfo.filename(); if (!warned.contains(fname)) { emit modelLoadingWarning(QString( "%1 is known to be broken. Please get a replacement via the download dialog." ).arg(fname)); warned.insert(fname); // don't warn again until restart } } m_llModelInfo.model->setProgressCallback([this](float progress) -> bool { emit modelLoadingPercentageChanged(progress); return m_shouldBeLoaded; }); // Pick the best match for the device QString actualDevice = m_llModelInfo.model->implementation().buildVariant() == "metal" ? "Metal" : "CPU"; const QString requestedDevice = MySettings::globalInstance()->device(); if (requestedDevice == "CPU") { emit reportFallbackReason(""); // fallback not applicable } else { const size_t requiredMemory = m_llModelInfo.model->requiredMem(filePath.toStdString(), n_ctx, ngl); std::vector availableDevices = m_llModelInfo.model->availableGPUDevices(requiredMemory); LLModel::GPUDevice *device = nullptr; if (!availableDevices.empty() && requestedDevice == "Auto" && availableDevices.front().type == 2 /*a discrete gpu*/) { device = &availableDevices.front(); } else { for (LLModel::GPUDevice &d : availableDevices) { if (QString::fromStdString(d.name) == requestedDevice) { device = &d; break; } } } emit reportFallbackReason(""); // no fallback yet std::string unavail_reason; if (!device) { // GPU not available } else if (!m_llModelInfo.model->initializeGPUDevice(device->index, &unavail_reason)) { emit reportFallbackReason(QString::fromStdString("
" + unavail_reason)); } else { actualDevice = QString::fromStdString(device->name); } } // Report which device we're actually using emit reportDevice(actualDevice); bool success = m_llModelInfo.model->loadModel(filePath.toStdString(), n_ctx, ngl); if (actualDevice == "CPU") { // we asked llama.cpp to use the CPU } else if (!success) { // llama_init_from_file returned nullptr emit reportDevice("CPU"); emit reportFallbackReason("
GPU loading failed (out of VRAM?)"); success = m_llModelInfo.model->loadModel(filePath.toStdString(), n_ctx, 0); } else if (!m_llModelInfo.model->usingGPUDevice()) { // ggml_vk_init was not called in llama.cpp // We might have had to fallback to CPU after load if the model is not possible to accelerate // for instance if the quantization method is not supported on Vulkan yet emit reportDevice("CPU"); emit reportFallbackReason("
model or quant has no GPU support"); } if (!success) { delete m_llModelInfo.model; 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; default: { delete m_llModelInfo.model; 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 modelLoadingPercentageChanged(isModelLoaded() ? 1.0f : 0.0f); 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(); } 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); }); if (first_non_whitespace == input.end()) return std::string(); 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); }); if (first_non_whitespace == input.end()) return std::string(); 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); } 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::API_) 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() { resetResponse(); m_processedSystemPrompt = false; m_ctx = LLModel::PromptContext(); } 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) { m_shouldBeLoaded = true; 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(remove_leading_whitespace(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(remove_leading_whitespace(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_restoreStateFromText) { Q_ASSERT(m_state.isEmpty()); processRestoreStateFromText(); } 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 min_p = MySettings::globalInstance()->modelMinP(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, min_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 min_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(); if (!collectionList.isEmpty()) { emit requestRetrieveFromDB(collectionList, prompt, retrievalSize, &databaseResults); // blocks emit databaseResultsChanged(databaseResults); } // Augment the prompt template with the results if any QList docsContext; if (!databaseResults.isEmpty()) docsContext.append("### Context:"); for (const ResultInfo &info : databaseResults) docsContext.append(info.text); 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(); m_ctx.n_predict = n_predict; m_ctx.top_k = top_k; m_ctx.top_p = top_p; m_ctx.min_p = min_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(prompt)); fflush(stdout); #endif m_timer->start(); if (!docsContext.isEmpty()) { auto old_n_predict = std::exchange(m_ctx.n_predict, 0); // decode localdocs context without a response m_llModelInfo.model->prompt(docsContext.join("\n").toStdString(), "%1", promptFunc, responseFunc, recalcFunc, m_ctx); m_ctx.n_predict = old_n_predict; // now we are ready for a response } m_llModelInfo.model->prompt(prompt.toStdString(), promptTemplate.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::setShouldTrySwitchContext(bool b) { m_shouldTrySwitchContext = b; // atomic emit shouldTrySwitchContextChanged(); } void ChatLLM::handleShouldBeLoadedChanged() { if (m_shouldBeLoaded) reloadModel(); else unloadModel(); } void ChatLLM::handleShouldTrySwitchContextChanged() { if (m_shouldTrySwitchContext) trySwitchContextOfLoadedModel(modelInfo()); } void ChatLLM::unloadModel() { if (!isModelLoaded() || m_isServer) return; if (!m_forceUnloadModel || !m_shouldBeLoaded) emit modelLoadingPercentageChanged(0.0f); else emit modelLoadingPercentageChanged(std::numeric_limits::min()); // small non-zero positive value if (!m_markedForDeletion) saveState(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "unloadModel" << m_llmThread.objectName() << m_llModelInfo.model; #endif if (m_forceUnloadModel) { delete m_llModelInfo.model; m_llModelInfo.model = nullptr; m_forceUnloadModel = false; } LLModelStore::globalInstance()->releaseModel(m_llModelInfo); m_llModelInfo = LLModelInfo(); } void ChatLLM::reloadModel() { if (isModelLoaded() && m_forceUnloadModel) unloadModel(); // we unload first if we are forcing an unload 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; std::string instructPrompt("### Instruction:\n%1\n### Response:\n"); // standard Alpaca 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; m_llModelInfo.model->prompt("Describe response above in three words.", instructPrompt, promptFunc, responseFunc, recalcFunc, ctx); 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::handleSystemRecalculate(bool isRecalc) { #if defined(DEBUG) qDebug() << "system recalc" << m_llmThread.objectName() << isRecalc; #endif Q_UNUSED(isRecalc); return false; } bool ChatLLM::handleRestoreStateFromTextPrompt(int32_t token) { #if defined(DEBUG) qDebug() << "restore state from text prompt" << m_llmThread.objectName() << token << m_stopGenerating; #endif Q_UNUSED(token); return !m_stopGenerating; } bool ChatLLM::handleRestoreStateFromTextRecalculate(bool isRecalc) { #if defined(DEBUG) qDebug() << "restore state from text recalc" << m_llmThread.objectName() << isRecalc; #endif Q_UNUSED(isRecalc); return false; } // this function serialized the cached model state to disk. // we want to also serialize n_ctx, and read it at load time. bool ChatLLM::serialize(QDataStream &stream, int version, bool serializeKV) { if (version > 1) { stream << m_llModelType; switch (m_llModelType) { case GPTJ_: stream << GPTJ_INTERNAL_STATE_VERSION; break; case LLAMA_: stream << LLAMA_INTERNAL_STATE_VERSION; break; default: Q_UNREACHABLE(); } } stream << response(); stream << generatedName(); stream << m_promptResponseTokens; if (!serializeKV) { #if defined(DEBUG) qDebug() << "serialize" << m_llmThread.objectName() << m_state.size(); #endif return stream.status() == QDataStream::Ok; } if (version <= 3) { int responseLogits = 0; stream << responseLogits; } stream << m_ctx.n_past; if (version >= 7) { stream << m_ctx.n_ctx; } 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, bool deserializeKV, bool discardKV) { 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 we do not deserialize the KV or it is discarded, then we need to restore the state from the // text only. This will be a costly operation, but the chat has to be restored from the text archive // alone. m_restoreStateFromText = !deserializeKV || discardKV; if (!deserializeKV) { #if defined(DEBUG) qDebug() << "deserialize" << m_llmThread.objectName(); #endif return stream.status() == QDataStream::Ok; } if (version <= 3) { int responseLogits; stream >> responseLogits; } int32_t n_past; stream >> n_past; if (!discardKV) m_ctx.n_past = n_past; if (version >= 7) { uint32_t n_ctx; stream >> n_ctx; if (!discardKV) m_ctx.n_ctx = n_ctx; } quint64 logitsSize; stream >> logitsSize; if (!discardKV) { m_ctx.logits.resize(logitsSize); stream.readRawData(reinterpret_cast(m_ctx.logits.data()), logitsSize * sizeof(float)); } else { stream.skipRawData(logitsSize * sizeof(float)); } quint64 tokensSize; stream >> tokensSize; if (!discardKV) { m_ctx.tokens.resize(tokensSize); stream.readRawData(reinterpret_cast(m_ctx.tokens.data()), tokensSize * sizeof(int)); } else { stream.skipRawData(tokensSize * sizeof(int)); } if (version > 0) { QByteArray compressed; stream >> compressed; if (!discardKV) m_state = qUncompress(compressed); } else { if (!discardKV) { stream >> m_state; } else { QByteArray state; stream >> 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::API_) { m_state.clear(); QDataStream stream(&m_state, QIODeviceBase::WriteOnly); stream.setVersion(QDataStream::Qt_6_4); ChatAPI *chatAPI = static_cast(m_llModelInfo.model); stream << chatAPI->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()) return; if (m_llModelType == LLModelType::API_) { QDataStream stream(&m_state, QIODeviceBase::ReadOnly); stream.setVersion(QDataStream::Qt_6_4); ChatAPI *chatAPI = static_cast(m_llModelInfo.model); QList context; stream >> context; chatAPI->setContext(context); m_state.clear(); m_state.squeeze(); return; } #if defined(DEBUG) qDebug() << "restoreState" << m_llmThread.objectName() << "size:" << m_state.size(); #endif if (m_state.isEmpty()) return; if (m_llModelInfo.model->stateSize() == m_state.size()) { m_llModelInfo.model->restoreState(static_cast(reinterpret_cast(m_state.data()))); m_processedSystemPrompt = true; } else { qWarning() << "restoring state from text because" << m_llModelInfo.model->stateSize() << "!=" << m_state.size(); m_restoreStateFromText = true; } m_state.clear(); m_state.squeeze(); } void ChatLLM::processSystemPrompt() { Q_ASSERT(isModelLoaded()); if (!isModelLoaded() || m_processedSystemPrompt || m_restoreStateFromText || m_isServer) return; const std::string systemPrompt = MySettings::globalInstance()->modelSystemPrompt(m_modelInfo).toStdString(); if (QString::fromStdString(systemPrompt).trimmed().isEmpty()) { m_processedSystemPrompt = true; return; } // Start with a whole new context m_stopGenerating = false; m_ctx = LLModel::PromptContext(); auto promptFunc = std::bind(&ChatLLM::handleSystemPrompt, this, std::placeholders::_1); 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 min_p = MySettings::globalInstance()->modelMinP(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.min_p = min_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 auto old_n_predict = std::exchange(m_ctx.n_predict, 0); // decode system prompt without a response // use "%1%2" and not "%1" to avoid implicit whitespace m_llModelInfo.model->prompt(systemPrompt, "%1%2", promptFunc, nullptr, recalcFunc, m_ctx, true); m_ctx.n_predict = old_n_predict; #if defined(DEBUG) printf("\n"); fflush(stdout); #endif m_processedSystemPrompt = m_stopGenerating == false; } void ChatLLM::processRestoreStateFromText() { Q_ASSERT(isModelLoaded()); if (!isModelLoaded() || !m_restoreStateFromText || m_isServer) return; m_isRecalc = true; emit recalcChanged(); m_stopGenerating = false; m_ctx = LLModel::PromptContext(); auto promptFunc = std::bind(&ChatLLM::handleRestoreStateFromTextPrompt, this, std::placeholders::_1); auto recalcFunc = std::bind(&ChatLLM::handleRestoreStateFromTextRecalculate, this, std::placeholders::_1); 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 min_p = MySettings::globalInstance()->modelMinP(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.min_p = min_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); auto it = m_stateFromText.begin(); while (it < m_stateFromText.end()) { auto &prompt = *it++; Q_ASSERT(prompt.first == "Prompt: "); Q_ASSERT(it < m_stateFromText.end()); auto &response = *it++; Q_ASSERT(response.first != "Prompt: "); auto responseText = response.second.toStdString(); m_llModelInfo.model->prompt(prompt.second.toStdString(), promptTemplate.toStdString(), promptFunc, nullptr, recalcFunc, m_ctx, false, &responseText); } if (!m_stopGenerating) { m_restoreStateFromText = false; m_stateFromText.clear(); } m_isRecalc = false; emit recalcChanged(); }