#include "chatllm.h" #include "chat.h" #include "download.h" #include "network.h" #include "../gpt4all-backend/llmodel.h" #include "chatgpt.h" #include #include #include #include #include #include #include //#define DEBUG //#define DEBUG_MODEL_LOADING #define MPT_INTERNAL_STATE_VERSION 0 #define GPTJ_INTERNAL_STATE_VERSION 0 #define LLAMA_INTERNAL_STATE_VERSION 0 static QString modelFilePath(const QString &modelName, bool isChatGPT) { QString modelFilename = isChatGPT ? modelName + ".txt" : "/ggml-" + modelName + ".bin"; QString appPath = QCoreApplication::applicationDirPath() + modelFilename; QFileInfo infoAppPath(appPath); if (infoAppPath.exists()) return appPath; QString downloadPath = Download::globalInstance()->downloadLocalModelsPath() + modelFilename; QFileInfo infoLocalPath(downloadPath); if (infoLocalPath.exists()) return downloadPath; return QString(); } 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_responseLogits(0) , m_isRecalc(false) , m_chat(parent) , m_isServer(isServer) , m_isChatGPT(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(m_chat, &Chat::idChanged, this, &ChatLLM::handleChatIdChanged); connect(&m_llmThread, &QThread::started, this, &ChatLLM::threadStarted); // 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(m_chat->id()); m_llmThread.start(); } ChatLLM::~ChatLLM() { 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_modelInfo.model; m_modelInfo.model = nullptr; } } bool ChatLLM::loadDefaultModel() { const QList models = m_chat->modelList(); if (models.isEmpty()) { // try again when we get a list of models connect(Download::globalInstance(), &Download::modelListChanged, this, &ChatLLM::loadDefaultModel, Qt::SingleShotConnection); return false; } return loadModel(models.first()); } bool ChatLLM::loadModel(const QString &modelName) { // 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() && m_modelName == modelName) return true; m_isChatGPT = modelName.startsWith("chatgpt-"); QString filePath = modelFilePath(modelName, m_isChatGPT); 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_chat->id() << m_modelInfo.model; #endif delete m_modelInfo.model; m_modelInfo.model = nullptr; emit isModelLoadedChanged(); } 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_modelInfo = LLModelStore::globalInstance()->acquireModel(); #if defined(DEBUG_MODEL_LOADING) qDebug() << "acquired model from store" << m_chat->id() << m_modelInfo.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_chat->id() << m_modelInfo.model; #endif LLModelStore::globalInstance()->releaseModel(m_modelInfo); m_modelInfo = LLModelInfo(); emit isModelLoadedChanged(); return false; } // Check if the store just gave us exactly the model we were looking for if (m_modelInfo.model && m_modelInfo.fileInfo == fileInfo) { #if defined(DEBUG_MODEL_LOADING) qDebug() << "store had our model" << m_chat->id() << m_modelInfo.model; #endif restoreState(); emit isModelLoadedChanged(); return true; } else { // Release the memory since we have to switch to a different model. #if defined(DEBUG_MODEL_LOADING) qDebug() << "deleting model" << m_chat->id() << m_modelInfo.model; #endif delete m_modelInfo.model; m_modelInfo.model = nullptr; } } // Guarantee we've released the previous models memory Q_ASSERT(!m_modelInfo.model); // Store the file info in the modelInfo in case we have an error loading m_modelInfo.fileInfo = fileInfo; if (fileInfo.exists()) { if (m_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_modelType = LLModelType::CHATGPT_; ChatGPT *model = new ChatGPT(); model->setModelName(chatGPTModel); model->setAPIKey(apiKey); m_modelInfo.model = model; } else { m_modelInfo.model = LLModel::construct(filePath.toStdString()); if (m_modelInfo.model) { m_modelInfo.model->loadModel(filePath.toStdString()); switch (m_modelInfo.model->implementation().modelType[0]) { case 'L': m_modelType = LLModelType::LLAMA_; break; case 'G': m_modelType = LLModelType::GPTJ_; break; case 'M': m_modelType = LLModelType::MPT_; break; default: delete std::exchange(m_modelInfo.model, nullptr); } } } #if defined(DEBUG_MODEL_LOADING) qDebug() << "new model" << m_chat->id() << m_modelInfo.model; #endif restoreState(); #if defined(DEBUG) qDebug() << "modelLoadedChanged" << m_chat->id(); fflush(stdout); #endif emit isModelLoadedChanged(); static bool isFirstLoad = true; if (isFirstLoad) { emit sendStartup(); isFirstLoad = false; } else emit sendModelLoaded(); } else { if (!m_isServer) LLModelStore::globalInstance()->releaseModel(m_modelInfo); // release back into the store const QString error = QString("Could not find model %1").arg(modelName); emit modelLoadingError(error); } if (m_modelInfo.model) { QString basename = fileInfo.completeBaseName(); setModelName(m_isChatGPT ? basename : basename.remove(0, 5)); // remove the ggml- prefix } return m_modelInfo.model; } bool ChatLLM::isModelLoaded() const { return m_modelInfo.model && m_modelInfo.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_isChatGPT) m_ctx.n_past -= 1; else m_ctx.n_past -= m_promptResponseTokens; m_ctx.n_past = std::max(0, m_ctx.n_past); // FIXME: This does not seem to be needed in my testing and llama models don't to it. Remove? m_ctx.logits.erase(m_ctx.logits.end() -= m_responseLogits, m_ctx.logits.end()); m_ctx.tokens.erase(m_ctx.tokens.end() -= m_promptResponseTokens, m_ctx.tokens.end()); m_promptResponseTokens = 0; m_promptTokens = 0; m_responseLogits = 0; m_response = std::string(); emit responseChanged(); } void ChatLLM::resetResponse() { m_promptTokens = 0; m_promptResponseTokens = 0; m_responseLogits = 0; m_response = std::string(); emit responseChanged(); } void ChatLLM::resetContext() { regenerateResponse(); if (m_isChatGPT && isModelLoaded()) { ChatGPT *chatGPT = static_cast(m_modelInfo.model); chatGPT->setContext(QList()); } 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)); } QString ChatLLM::modelName() const { return m_modelName; } void ChatLLM::setModelName(const QString &modelName) { m_modelName = modelName; emit modelNameChanged(); } void ChatLLM::modelNameChangeRequested(const QString &modelName) { if (!loadModel(modelName)) qWarning() << "ERROR: Could not load model" << modelName; } bool ChatLLM::handlePrompt(int32_t token) { // m_promptResponseTokens and m_responseLogits are related to last prompt/response not // the entire context window which we can reset on regenerate prompt #if defined(DEBUG) qDebug() << "prompt process" << m_chat->id() << token; #endif ++m_promptTokens; ++m_promptResponseTokens; 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(); return false; } // m_promptResponseTokens and m_responseLogits are related to last prompt/response not // the entire context window which we can reset on regenerate prompt ++m_promptResponseTokens; Q_ASSERT(!response.empty()); m_response.append(response); emit responseChanged(); return !m_stopGenerating; } bool ChatLLM::handleRecalculate(bool isRecalc) { if (m_isRecalc != isRecalc) { m_isRecalc = isRecalc; emit recalcChanged(); } return !m_stopGenerating; } bool ChatLLM::prompt(const QString &prompt, const QString &prompt_template, 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, int n_threads) { if (!isModelLoaded()) return false; m_databaseResults.clear(); const int retrievalSize = LocalDocs::globalInstance()->retrievalSize(); emit requestRetrieveFromDB(m_chat->collectionList(), prompt, retrievalSize, &m_databaseResults); // blocks // Augment the prompt template with the results if any QList augmentedTemplate; if (!m_databaseResults.isEmpty()) augmentedTemplate.append("### Context:"); for (const ResultInfo &info : m_databaseResults) augmentedTemplate.append(info.text); augmentedTemplate.append(prompt_template); QString instructPrompt = augmentedTemplate.join("\n").arg(prompt); 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_modelInfo.model->setThreadCount(n_threads); #if defined(DEBUG) printf("%s", qPrintable(instructPrompt)); fflush(stdout); #endif m_modelInfo.model->prompt(instructPrompt.toStdString(), promptFunc, responseFunc, recalcFunc, m_ctx); #if defined(DEBUG) printf("\n"); fflush(stdout); #endif m_responseLogits += m_ctx.logits.size() - logitsBefore; std::string trimmed = trim_whitespace(m_response); if (trimmed != m_response) { m_response = trimmed; emit responseChanged(); } emit responseStopped(); return true; } void ChatLLM::setShouldBeLoaded(bool b) { #if defined(DEBUG_MODEL_LOADING) qDebug() << "setShouldBeLoaded" << m_chat->id() << b << m_modelInfo.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_chat->id() << m_modelInfo.model; #endif LLModelStore::globalInstance()->releaseModel(m_modelInfo); m_modelInfo = LLModelInfo(); emit isModelLoadedChanged(); } void ChatLLM::reloadModel() { if (isModelLoaded() || m_isServer) return; #if defined(DEBUG_MODEL_LOADING) qDebug() << "reloadModel" << m_chat->id() << m_modelInfo.model; #endif if (m_modelName.isEmpty()) { loadDefaultModel(); } else { loadModel(m_modelName); } } 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_modelInfo.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(); } } void ChatLLM::handleChatIdChanged() { m_llmThread.setObjectName(m_chat->id()); } bool ChatLLM::handleNamePrompt(int32_t token) { Q_UNUSED(token); qt_noop(); return true; } bool ChatLLM::handleNameResponse(int32_t token, const std::string &response) { Q_UNUSED(token); m_nameResponse.append(response); emit generatedNameChanged(); QString gen = QString::fromStdString(m_nameResponse).simplified(); QStringList words = gen.split(' ', Qt::SkipEmptyParts); int wordCount = words.size(); return words.size() <= 3; } bool ChatLLM::handleNameRecalculate(bool isRecalc) { Q_UNUSED(isRecalc); Q_UNREACHABLE(); return true; } bool ChatLLM::serialize(QDataStream &stream, int version) { if (version > 1) { stream << m_modelType; switch (m_modelType) { case MPT_: stream << MPT_INTERNAL_STATE_VERSION; break; 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; stream << m_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_chat->id() << m_state.size(); #endif return stream.status() == QDataStream::Ok; } bool ChatLLM::deserialize(QDataStream &stream, int version) { if (version > 1) { int internalStateVersion; stream >> m_modelType; stream >> internalStateVersion; // for future use } QString response; stream >> response; m_response = response.toStdString(); QString nameResponse; stream >> nameResponse; m_nameResponse = nameResponse.toStdString(); stream >> m_promptResponseTokens; stream >> m_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_chat->id(); #endif return stream.status() == QDataStream::Ok; } void ChatLLM::saveState() { if (!isModelLoaded()) return; if (m_isChatGPT) { m_state.clear(); QDataStream stream(&m_state, QIODeviceBase::WriteOnly); stream.setVersion(QDataStream::Qt_6_5); ChatGPT *chatGPT = static_cast(m_modelInfo.model); stream << chatGPT->context(); return; } const size_t stateSize = m_modelInfo.model->stateSize(); m_state.resize(stateSize); #if defined(DEBUG) qDebug() << "saveState" << m_chat->id() << "size:" << m_state.size(); #endif m_modelInfo.model->saveState(static_cast(reinterpret_cast(m_state.data()))); } void ChatLLM::restoreState() { if (!isModelLoaded() || m_state.isEmpty()) return; if (m_isChatGPT) { QDataStream stream(&m_state, QIODeviceBase::ReadOnly); stream.setVersion(QDataStream::Qt_6_5); ChatGPT *chatGPT = static_cast(m_modelInfo.model); QList context; stream >> context; chatGPT->setContext(context); m_state.clear(); m_state.resize(0); return; } #if defined(DEBUG) qDebug() << "restoreState" << m_chat->id() << "size:" << m_state.size(); #endif m_modelInfo.model->restoreState(static_cast(reinterpret_cast(m_state.data()))); m_state.clear(); m_state.resize(0); }