mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-18 03:25:46 +00:00
673 lines
21 KiB
C++
673 lines
21 KiB
C++
#include "chatllm.h"
|
|
#include "chat.h"
|
|
#include "download.h"
|
|
#include "network.h"
|
|
#include "../gpt4all-backend/llmodel.h"
|
|
#include "chatgpt.h"
|
|
|
|
#include <QCoreApplication>
|
|
#include <QDir>
|
|
#include <QFile>
|
|
#include <QProcess>
|
|
#include <QResource>
|
|
#include <QSettings>
|
|
#include <fstream>
|
|
|
|
//#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<LLModelInfo> 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<QString> 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<ChatGPT*>(m_modelInfo.model);
|
|
chatGPT->setContext(QList<QString>());
|
|
}
|
|
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<QString> 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<const char*>(m_ctx.logits.data()), m_ctx.logits.size() * sizeof(float));
|
|
stream << quint64(m_ctx.tokens.size());
|
|
stream.writeRawData(reinterpret_cast<const char*>(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<char*>(m_ctx.logits.data()), logitsSize * sizeof(float));
|
|
quint64 tokensSize;
|
|
stream >> tokensSize;
|
|
m_ctx.tokens.resize(tokensSize);
|
|
stream.readRawData(reinterpret_cast<char*>(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<ChatGPT*>(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<uint8_t*>(reinterpret_cast<void*>(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<ChatGPT*>(m_modelInfo.model);
|
|
QList<QString> 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<const uint8_t*>(reinterpret_cast<void*>(m_state.data())));
|
|
m_state.clear();
|
|
m_state.resize(0);
|
|
}
|