gpt4all/gpt4all-chat/embllm.cpp

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#include "embllm.h"
#include "modellist.h"
EmbeddingLLMWorker::EmbeddingLLMWorker()
: QObject(nullptr)
, m_networkManager(new QNetworkAccessManager(this))
, m_model(nullptr)
{
moveToThread(&m_workerThread);
connect(this, &EmbeddingLLMWorker::finished, &m_workerThread, &QThread::quit, Qt::DirectConnection);
m_workerThread.setObjectName("embedding");
m_workerThread.start();
}
EmbeddingLLMWorker::~EmbeddingLLMWorker()
{
if (m_model) {
delete m_model;
m_model = nullptr;
}
}
void EmbeddingLLMWorker::wait()
{
m_workerThread.wait();
}
bool EmbeddingLLMWorker::loadModel()
{
const EmbeddingModels *embeddingModels = ModelList::globalInstance()->installedEmbeddingModels();
if (!embeddingModels->count())
return false;
const ModelInfo defaultModel = embeddingModels->defaultModelInfo();
QString filePath = defaultModel.dirpath + defaultModel.filename();
QFileInfo fileInfo(filePath);
if (!fileInfo.exists()) {
qWarning() << "WARNING: Could not load sbert because file does not exist";
m_model = nullptr;
return false;
}
auto filename = fileInfo.fileName();
bool isNomic = filename.startsWith("gpt4all-nomic-") && filename.endsWith(".rmodel");
if (isNomic) {
QFile file(filePath);
if (!file.open(QIODeviceBase::ReadOnly)) {
qWarning() << "failed to open" << filePath << ":" << file.errorString();
m_model = nullptr;
return false;
}
QJsonDocument doc = QJsonDocument::fromJson(file.readAll());
QJsonObject obj = doc.object();
m_nomicAPIKey = obj["apiKey"].toString();
file.close();
return true;
}
try {
m_model = LLModel::Implementation::construct(filePath.toStdString());
} catch (const std::exception &e) {
qWarning() << "WARNING: Could not load embedding model:" << e.what();
m_model = nullptr;
return false;
}
// NOTE: explicitly loads model on CPU to avoid GPU OOM
// TODO(cebtenzzre): support GPU-accelerated embeddings
bool success = m_model->loadModel(filePath.toStdString(), 2048, 0);
if (!success) {
qWarning() << "WARNING: Could not load embedding model";
delete m_model;
m_model = nullptr;
return false;
}
if (!m_model->supportsEmbedding()) {
qWarning() << "WARNING: Model type does not support embeddings";
delete m_model;
m_model = nullptr;
return false;
}
return true;
}
bool EmbeddingLLMWorker::hasModel() const
{
return m_model || !m_nomicAPIKey.isEmpty();
}
bool EmbeddingLLMWorker::isNomic() const
{
return !m_nomicAPIKey.isEmpty();
}
// this function is always called for retrieval tasks
std::vector<float> EmbeddingLLMWorker::generateSyncEmbedding(const QString &text)
{
if (!hasModel() && !loadModel()) {
qWarning() << "WARNING: Could not load model for embeddings";
return {};
}
if (isNomic()) {
qWarning() << "WARNING: Request to generate sync embeddings for non-local model invalid";
return {};
}
std::vector<float> embedding(m_model->embeddingSize());
try {
m_model->embed({text.toStdString()}, embedding.data(), true);
} catch (const std::exception &e) {
qWarning() << "WARNING: LLModel::embed failed: " << e.what();
return {};
}
return embedding;
}
void EmbeddingLLMWorker::sendAtlasRequest(const QStringList &texts, const QString &taskType, QVariant userData) {
QJsonObject root;
root.insert("model", "nomic-embed-text-v1");
root.insert("texts", QJsonArray::fromStringList(texts));
root.insert("task_type", taskType);
QJsonDocument doc(root);
QUrl nomicUrl("https://api-atlas.nomic.ai/v1/embedding/text");
const QString authorization = QString("Bearer %1").arg(m_nomicAPIKey).trimmed();
QNetworkRequest request(nomicUrl);
request.setHeader(QNetworkRequest::ContentTypeHeader, "application/json");
request.setRawHeader("Authorization", authorization.toUtf8());
request.setAttribute(QNetworkRequest::User, userData);
QNetworkReply *reply = m_networkManager->post(request, doc.toJson(QJsonDocument::Compact));
connect(qApp, &QCoreApplication::aboutToQuit, reply, &QNetworkReply::abort);
connect(reply, &QNetworkReply::finished, this, &EmbeddingLLMWorker::handleFinished);
}
// this function is always called for retrieval tasks
void EmbeddingLLMWorker::requestSyncEmbedding(const QString &text)
{
if (!hasModel() && !loadModel()) {
qWarning() << "WARNING: Could not load model for embeddings";
return;
}
if (!isNomic()) {
qWarning() << "WARNING: Request to generate sync embeddings for local model invalid";
return;
}
Q_ASSERT(hasModel());
sendAtlasRequest({text}, "search_query");
}
// this function is always called for storage into the database
void EmbeddingLLMWorker::requestAsyncEmbedding(const QVector<EmbeddingChunk> &chunks)
{
if (!hasModel() && !loadModel()) {
qWarning() << "WARNING: Could not load model for embeddings";
return;
}
if (m_nomicAPIKey.isEmpty()) {
QVector<EmbeddingResult> results;
results.reserve(chunks.size());
for (auto c : chunks) {
EmbeddingResult result;
result.folder_id = c.folder_id;
result.chunk_id = c.chunk_id;
// TODO(cebtenzzre): take advantage of batched embeddings
result.embedding.resize(m_model->embeddingSize());
try {
m_model->embed({c.chunk.toStdString()}, result.embedding.data(), false);
} catch (const std::exception &e) {
qWarning() << "WARNING: LLModel::embed failed:" << e.what();
return;
}
results << result;
}
emit embeddingsGenerated(results);
return;
};
QStringList texts;
for (auto &c: chunks)
texts.append(c.chunk);
sendAtlasRequest(texts, "search_document", QVariant::fromValue(chunks));
}
std::vector<float> jsonArrayToVector(const QJsonArray &jsonArray) {
std::vector<float> result;
for (const QJsonValue &innerValue : jsonArray) {
if (innerValue.isArray()) {
QJsonArray innerArray = innerValue.toArray();
result.reserve(result.size() + innerArray.size());
for (const QJsonValue &value : innerArray) {
result.push_back(static_cast<float>(value.toDouble()));
}
}
}
return result;
}
QVector<EmbeddingResult> jsonArrayToEmbeddingResults(const QVector<EmbeddingChunk>& chunks, const QJsonArray& embeddings) {
QVector<EmbeddingResult> results;
if (chunks.size() != embeddings.size()) {
qWarning() << "WARNING: Size of json array result does not match input!";
return results;
}
for (int i = 0; i < chunks.size(); ++i) {
const EmbeddingChunk& chunk = chunks.at(i);
const QJsonArray embeddingArray = embeddings.at(i).toArray();
std::vector<float> embeddingVector;
for (const QJsonValue& value : embeddingArray)
embeddingVector.push_back(static_cast<float>(value.toDouble()));
EmbeddingResult result;
result.folder_id = chunk.folder_id;
result.chunk_id = chunk.chunk_id;
result.embedding = std::move(embeddingVector);
results.push_back(std::move(result));
}
return results;
}
void EmbeddingLLMWorker::handleFinished()
{
QNetworkReply *reply = qobject_cast<QNetworkReply *>(sender());
if (!reply)
return;
QVariant retrievedData = reply->request().attribute(QNetworkRequest::User);
QVector<EmbeddingChunk> chunks;
if (retrievedData.isValid() && retrievedData.canConvert<QVector<EmbeddingChunk>>())
chunks = retrievedData.value<QVector<EmbeddingChunk>>();
int folder_id = 0;
if (!chunks.isEmpty())
folder_id = chunks.first().folder_id;
QVariant response = reply->attribute(QNetworkRequest::HttpStatusCodeAttribute);
Q_ASSERT(response.isValid());
bool ok;
int code = response.toInt(&ok);
if (!ok || code != 200) {
QString errorDetails;
QString replyErrorString = reply->errorString().trimmed();
QByteArray replyContent = reply->readAll().trimmed();
errorDetails = QString("ERROR: Nomic Atlas responded with error code \"%1\"").arg(code);
if (!replyErrorString.isEmpty())
errorDetails += QString(". Error Details: \"%1\"").arg(replyErrorString);
if (!replyContent.isEmpty())
errorDetails += QString(". Response Content: \"%1\"").arg(QString::fromUtf8(replyContent));
qWarning() << errorDetails;
emit errorGenerated(folder_id, errorDetails);
return;
}
QByteArray jsonData = reply->readAll();
QJsonParseError err;
QJsonDocument document = QJsonDocument::fromJson(jsonData, &err);
if (err.error != QJsonParseError::NoError) {
qWarning() << "ERROR: Couldn't parse Nomic Atlas response: " << jsonData << err.errorString();
return;
}
const QJsonObject root = document.object();
const QJsonArray embeddings = root.value("embeddings").toArray();
if (!chunks.isEmpty()) {
emit embeddingsGenerated(jsonArrayToEmbeddingResults(chunks, embeddings));
} else {
m_lastResponse = jsonArrayToVector(embeddings);
emit finished();
}
reply->deleteLater();
}
EmbeddingLLM::EmbeddingLLM()
: QObject(nullptr)
, m_embeddingWorker(new EmbeddingLLMWorker)
{
connect(this, &EmbeddingLLM::requestAsyncEmbedding, m_embeddingWorker,
&EmbeddingLLMWorker::requestAsyncEmbedding, Qt::QueuedConnection);
connect(m_embeddingWorker, &EmbeddingLLMWorker::embeddingsGenerated, this,
&EmbeddingLLM::embeddingsGenerated, Qt::QueuedConnection);
connect(m_embeddingWorker, &EmbeddingLLMWorker::errorGenerated, this,
&EmbeddingLLM::errorGenerated, Qt::QueuedConnection);
}
EmbeddingLLM::~EmbeddingLLM()
{
delete m_embeddingWorker;
m_embeddingWorker = nullptr;
}
std::vector<float> EmbeddingLLM::generateEmbeddings(const QString &text)
{
if (!m_embeddingWorker->isNomic()) {
return m_embeddingWorker->generateSyncEmbedding(text);
} else {
EmbeddingLLMWorker worker;
connect(this, &EmbeddingLLM::requestSyncEmbedding, &worker,
&EmbeddingLLMWorker::requestSyncEmbedding, Qt::QueuedConnection);
emit requestSyncEmbedding(text);
worker.wait();
return worker.lastResponse();
}
}
void EmbeddingLLM::generateAsyncEmbeddings(const QVector<EmbeddingChunk> &chunks)
{
emit requestAsyncEmbedding(chunks);
}