gpt4all/gpt4all-chat/chatllm.cpp

669 lines
21 KiB
C++

#include "chatllm.h"
#include "chat.h"
#include "download.h"
#include "network.h"
#include "../gpt4all-backend/gptj.h"
#include "../gpt4all-backend/llamamodel.h"
#include "../gpt4all-backend/mpt.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);
connect(m_chat, &Chat::idChanged, this, &ChatLLM::handleChatIdChanged);
connect(&m_llmThread, &QThread::started, this, &ChatLLM::threadStarted);
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) {
resetContextProtected();
#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 {
auto fin = std::ifstream(filePath.toStdString(), std::ios::binary);
uint32_t magic;
fin.read((char *) &magic, sizeof(magic));
fin.seekg(0);
fin.close();
const bool isGPTJ = magic == 0x67676d6c;
const bool isMPT = magic == 0x67676d6d;
if (isGPTJ) {
m_modelType = LLModelType::GPTJ_;
m_modelInfo.model = new GPTJ;
m_modelInfo.model->loadModel(filePath.toStdString());
} else if (isMPT) {
m_modelType = LLModelType::MPT_;
m_modelInfo.model = new MPT;
m_modelInfo.model->loadModel(filePath.toStdString());
} else {
m_modelType = LLModelType::LLAMA_;
m_modelInfo.model = new LLamaModel;
m_modelInfo.model->loadModel(filePath.toStdString());
}
}
#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()
{
resetContextProtected();
emit sendResetContext();
}
void ChatLLM::resetContextProtected()
{
regenerateResponse();
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;
QString instructPrompt = prompt_template.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 responseStarted();
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);
}