Add Nomic Embed model for atlas with localdocs.

This commit is contained in:
Adam Treat 2024-01-22 12:36:01 -05:00
parent eadc3b8d80
commit d14b95f4bd
15 changed files with 506 additions and 78 deletions

View File

@ -156,7 +156,7 @@ bool ChatLLM::loadModel(const ModelInfo &modelInfo)
if (isModelLoaded() && this->modelInfo() == modelInfo)
return true;
bool isChatGPT = modelInfo.isChatGPT;
bool isChatGPT = modelInfo.isOnline; // right now only chatgpt is offered for online chat models...
QString filePath = modelInfo.dirpath + modelInfo.filename();
QFileInfo fileInfo(filePath);

View File

@ -558,7 +558,6 @@ void Database::scheduleNext(int folder_id, size_t countForFolder)
if (!countForFolder) {
emit updateIndexing(folder_id, false);
emit updateInstalled(folder_id, true);
m_embeddings->save();
}
if (!m_docsToScan.isEmpty())
QTimer::singleShot(0, this, &Database::scanQueue);
@ -570,7 +569,7 @@ void Database::handleDocumentError(const QString &errorMessage,
qWarning() << errorMessage << document_id << document_path << error.text();
}
size_t Database::chunkStream(QTextStream &stream, int document_id, const QString &file,
size_t Database::chunkStream(QTextStream &stream, int folder_id, int document_id, const QString &file,
const QString &title, const QString &author, const QString &subject, const QString &keywords, int page,
int maxChunks)
{
@ -580,6 +579,8 @@ size_t Database::chunkStream(QTextStream &stream, int document_id, const QString
QList<QString> words;
int chunks = 0;
QVector<EmbeddingChunk> chunkList;
while (!stream.atEnd()) {
QString word;
stream >> word;
@ -605,9 +606,22 @@ size_t Database::chunkStream(QTextStream &stream, int document_id, const QString
qWarning() << "ERROR: Could not insert chunk into db" << q.lastError();
}
#if 1
EmbeddingChunk toEmbed;
toEmbed.folder_id = folder_id;
toEmbed.chunk_id = chunk_id;
toEmbed.chunk = chunk;
chunkList << toEmbed;
if (chunkList.count() == 100) {
m_embLLM->generateAsyncEmbeddings(chunkList);
emit updateTotalEmbeddingsToIndex(folder_id, 100);
chunkList.clear();
}
#else
const std::vector<float> result = m_embLLM->generateEmbeddings(chunk);
if (!m_embeddings->add(result, chunk_id))
qWarning() << "ERROR: Cannot add point to embeddings index";
#endif
++chunks;
@ -615,12 +629,39 @@ size_t Database::chunkStream(QTextStream &stream, int document_id, const QString
charCount = 0;
if (maxChunks > 0 && chunks == maxChunks)
return stream.pos();
break;
}
}
if (!chunkList.isEmpty()) {
m_embLLM->generateAsyncEmbeddings(chunkList);
emit updateTotalEmbeddingsToIndex(folder_id, chunkList.count());
chunkList.clear();
}
return stream.pos();
}
void Database::handleEmbeddingsGenerated(const QVector<EmbeddingResult> &embeddings)
{
if (embeddings.isEmpty())
return;
int folder_id = 0;
for (auto e : embeddings) {
folder_id = e.folder_id;
if (!m_embeddings->add(e.embedding, e.chunk_id))
qWarning() << "ERROR: Cannot add point to embeddings index";
}
emit updateCurrentEmbeddingsToIndex(folder_id, embeddings.count());
m_embeddings->save();
}
void Database::handleErrorGenerated(int folder_id, const QString &error)
{
emit updateError(folder_id, error);
}
void Database::removeEmbeddingsByDocumentId(int document_id)
{
QSqlQuery q;
@ -792,14 +833,13 @@ void Database::scanQueue()
const QPdfSelection selection = doc.getAllText(pageIndex);
QString text = selection.text();
QTextStream stream(&text);
chunkStream(stream, document_id, info.doc.fileName(),
chunkStream(stream, info.folder, document_id, info.doc.fileName(),
doc.metaData(QPdfDocument::MetaDataField::Title).toString(),
doc.metaData(QPdfDocument::MetaDataField::Author).toString(),
doc.metaData(QPdfDocument::MetaDataField::Subject).toString(),
doc.metaData(QPdfDocument::MetaDataField::Keywords).toString(),
pageIndex + 1
);
m_embeddings->save();
emit subtractCurrentBytesToIndex(info.folder, bytesPerPage);
if (info.currentPage < doc.pageCount()) {
info.currentPage += 1;
@ -828,9 +868,8 @@ void Database::scanQueue()
#if defined(DEBUG)
qDebug() << "scanning byteIndex" << byteIndex << "of" << bytes << document_path;
#endif
int pos = chunkStream(stream, document_id, info.doc.fileName(), QString() /*title*/, QString() /*author*/,
QString() /*subject*/, QString() /*keywords*/, -1 /*page*/, 5 /*maxChunks*/);
m_embeddings->save();
int pos = chunkStream(stream, info.folder, document_id, info.doc.fileName(), QString() /*title*/, QString() /*author*/,
QString() /*subject*/, QString() /*keywords*/, -1 /*page*/, 100 /*maxChunks*/);
file.close();
const size_t bytesChunked = pos - byteIndex;
emit subtractCurrentBytesToIndex(info.folder, bytesChunked);
@ -892,6 +931,8 @@ void Database::scanDocuments(int folder_id, const QString &folder_path)
void Database::start()
{
connect(m_watcher, &QFileSystemWatcher::directoryChanged, this, &Database::directoryChanged);
connect(m_embLLM, &EmbeddingLLM::embeddingsGenerated, this, &Database::handleEmbeddingsGenerated);
connect(m_embLLM, &EmbeddingLLM::errorGenerated, this, &Database::handleErrorGenerated);
connect(this, &Database::docsToScanChanged, this, &Database::scanQueue);
if (!QSqlDatabase::drivers().contains("QSQLITE")) {
qWarning() << "ERROR: missing sqllite driver";
@ -1081,6 +1122,10 @@ void Database::retrieveFromDB(const QList<QString> &collections, const QString &
QSqlQuery q;
if (m_embeddings->isLoaded()) {
std::vector<float> result = m_embLLM->generateEmbeddings(text);
if (result.empty()) {
qDebug() << "ERROR: generating embeddings returned a null result";
return;
}
std::vector<qint64> embeddings = m_embeddings->search(result, retrievalSize);
if (!selectChunk(q, collections, embeddings, retrievalSize)) {
qDebug() << "ERROR: selecting chunks:" << q.lastError().text();

View File

@ -8,8 +8,9 @@
#include <QThread>
#include <QFileSystemWatcher>
#include "embllm.h"
class Embeddings;
class EmbeddingLLM;
struct DocumentInfo
{
int folder;
@ -39,10 +40,13 @@ struct CollectionItem {
int folder_id = -1;
bool installed = false;
bool indexing = false;
QString error;
int currentDocsToIndex = 0;
int totalDocsToIndex = 0;
size_t currentBytesToIndex = 0;
size_t totalBytesToIndex = 0;
size_t currentEmbeddingsToIndex = 0;
size_t totalEmbeddingsToIndex = 0;
};
Q_DECLARE_METATYPE(CollectionItem)
@ -66,11 +70,14 @@ Q_SIGNALS:
void docsToScanChanged();
void updateInstalled(int folder_id, bool b);
void updateIndexing(int folder_id, bool b);
void updateError(int folder_id, const QString &error);
void updateCurrentDocsToIndex(int folder_id, size_t currentDocsToIndex);
void updateTotalDocsToIndex(int folder_id, size_t totalDocsToIndex);
void subtractCurrentBytesToIndex(int folder_id, size_t subtractedBytes);
void updateCurrentBytesToIndex(int folder_id, size_t currentBytesToIndex);
void updateTotalBytesToIndex(int folder_id, size_t totalBytesToIndex);
void updateCurrentEmbeddingsToIndex(int folder_id, size_t currentBytesToIndex);
void updateTotalEmbeddingsToIndex(int folder_id, size_t totalBytesToIndex);
void addCollectionItem(const CollectionItem &item);
void removeFolderById(int folder_id);
void removeCollectionItem(const QString &collectionName);
@ -82,10 +89,12 @@ private Q_SLOTS:
bool addFolderToWatch(const QString &path);
bool removeFolderFromWatch(const QString &path);
void addCurrentFolders();
void handleEmbeddingsGenerated(const QVector<EmbeddingResult> &embeddings);
void handleErrorGenerated(int folder_id, const QString &error);
private:
void removeFolderInternal(const QString &collection, int folder_id, const QString &path);
size_t chunkStream(QTextStream &stream, int document_id, const QString &file,
size_t chunkStream(QTextStream &stream, int folder_id, int document_id, const QString &file,
const QString &title, const QString &author, const QString &subject, const QString &keywords, int page,
int maxChunks = -1);
void removeEmbeddingsByDocumentId(int document_id);

View File

@ -129,6 +129,9 @@ bool Embeddings::add(const std::vector<float> &embedding, qint64 label)
}
}
if (embedding.empty())
return false;
try {
m_hnsw->addPoint(embedding.data(), label, false);
} catch (const std::exception &e) {

View File

@ -1,19 +1,31 @@
#include "embllm.h"
#include "modellist.h"
EmbeddingLLM::EmbeddingLLM()
: QObject{nullptr}
, m_model{nullptr}
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();
}
EmbeddingLLM::~EmbeddingLLM()
EmbeddingLLMWorker::~EmbeddingLLMWorker()
{
delete m_model;
m_model = nullptr;
if (m_model) {
delete m_model;
m_model = nullptr;
}
}
bool EmbeddingLLM::loadModel()
void EmbeddingLLMWorker::wait()
{
m_workerThread.wait();
}
bool EmbeddingLLMWorker::loadModel()
{
const EmbeddingModels *embeddingModels = ModelList::globalInstance()->embeddingModels();
if (!embeddingModels->count())
@ -29,6 +41,16 @@ bool EmbeddingLLM::loadModel()
return false;
}
bool isNomic = fileInfo.fileName().startsWith("nomic");
if (isNomic) {
QFile file(filePath);
file.open(QIODeviceBase::ReadOnly | QIODeviceBase::Text);
QTextStream stream(&file);
m_nomicAPIKey = stream.readAll();
file.close();
return true;
}
m_model = LLModel::Implementation::construct(filePath.toStdString());
bool success = m_model->loadModel(filePath.toStdString(), 2048, 0);
if (!success) {
@ -47,18 +69,236 @@ bool EmbeddingLLM::loadModel()
return true;
}
bool EmbeddingLLM::hasModel() const
bool EmbeddingLLMWorker::hasModel() const
{
return m_model;
return m_model || !m_nomicAPIKey.isEmpty();
}
bool EmbeddingLLMWorker::isNomic() const
{
return !m_nomicAPIKey.isEmpty();
}
std::vector<float> EmbeddingLLMWorker::generateSyncEmbedding(const QString &text)
{
if (!hasModel() && !loadModel()) {
qWarning() << "WARNING: Could not load model for embeddings";
return std::vector<float>();
}
if (isNomic()) {
qWarning() << "WARNING: Request to generate sync embeddings for non-local model invalid";
return std::vector<float>();
}
return m_model->embedding(text.toStdString());
}
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());
QJsonObject root;
root.insert("model", "nomic-embed-text-v1");
QJsonArray texts;
texts.append(text);
root.insert("texts", texts);
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());
QNetworkReply *reply = m_networkManager->post(request, doc.toJson(QJsonDocument::Compact));
connect(qApp, &QCoreApplication::aboutToQuit, reply, &QNetworkReply::abort);
connect(reply, &QNetworkReply::finished, this, &EmbeddingLLMWorker::handleFinished);
}
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;
result.embedding = m_model->embedding(c.chunk.toStdString());
results << result;
}
emit embeddingsGenerated(results);
return;
};
QJsonObject root;
root.insert("model", "nomic-embed-text-v1");
QJsonArray texts;
for (auto c : chunks)
texts.append(c.chunk);
root.insert("texts", texts);
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, QVariant::fromValue(chunks));
QNetworkReply *reply = m_networkManager->post(request, doc.toJson(QJsonDocument::Compact));
connect(qApp, &QCoreApplication::aboutToQuit, reply, &QNetworkReply::abort);
connect(reply, &QNetworkReply::finished, this, &EmbeddingLLMWorker::handleFinished);
}
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 (!hasModel() && !loadModel()) {
qWarning() << "WARNING: Could not load sbert model for embeddings";
return std::vector<float>();
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();
}
Q_ASSERT(hasModel());
return m_model->embedding(text.toStdString());
}
void EmbeddingLLM::generateAsyncEmbeddings(const QVector<EmbeddingChunk> &chunks)
{
emit requestAsyncEmbedding(chunks);
}

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@ -3,8 +3,61 @@
#include <QObject>
#include <QThread>
#include <QNetworkReply>
#include <QNetworkAccessManager>
#include "../gpt4all-backend/llmodel.h"
struct EmbeddingChunk {
int folder_id;
int chunk_id;
QString chunk;
};
Q_DECLARE_METATYPE(EmbeddingChunk)
struct EmbeddingResult {
int folder_id;
int chunk_id;
std::vector<float> embedding;
};
class EmbeddingLLMWorker : public QObject {
Q_OBJECT
public:
EmbeddingLLMWorker();
virtual ~EmbeddingLLMWorker();
void wait();
std::vector<float> lastResponse() const { return m_lastResponse; }
bool loadModel();
bool hasModel() const;
bool isNomic() const;
std::vector<float> generateSyncEmbedding(const QString &text);
public Q_SLOTS:
void requestSyncEmbedding(const QString &text);
void requestAsyncEmbedding(const QVector<EmbeddingChunk> &chunks);
Q_SIGNALS:
void embeddingsGenerated(const QVector<EmbeddingResult> &embeddings);
void errorGenerated(int folder_id, const QString &error);
void finished();
private Q_SLOTS:
void handleFinished();
private:
QString m_nomicAPIKey;
QNetworkAccessManager *m_networkManager;
std::vector<float> m_lastResponse;
LLModel *m_model = nullptr;
QThread m_workerThread;
};
class EmbeddingLLM : public QObject
{
Q_OBJECT
@ -12,16 +65,21 @@ public:
EmbeddingLLM();
virtual ~EmbeddingLLM();
bool loadModel();
bool hasModel() const;
public Q_SLOTS:
std::vector<float> generateEmbeddings(const QString &text);
std::vector<float> generateEmbeddings(const QString &text); // synchronous
void generateAsyncEmbeddings(const QVector<EmbeddingChunk> &chunks);
Q_SIGNALS:
void requestSyncEmbedding(const QString &text);
void requestAsyncEmbedding(const QVector<EmbeddingChunk> &chunks);
void embeddingsGenerated(const QVector<EmbeddingResult> &embeddings);
void errorGenerated(int folder_id, const QString &error);
private:
bool loadModel();
private:
LLModel *m_model = nullptr;
EmbeddingLLMWorker *m_embeddingWorker;
};
#endif // EMBLLM_H

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@ -30,6 +30,8 @@ LocalDocs::LocalDocs()
m_localDocsModel, &LocalDocsModel::updateInstalled, Qt::QueuedConnection);
connect(m_database, &Database::updateIndexing,
m_localDocsModel, &LocalDocsModel::updateIndexing, Qt::QueuedConnection);
connect(m_database, &Database::updateError,
m_localDocsModel, &LocalDocsModel::updateError, Qt::QueuedConnection);
connect(m_database, &Database::updateCurrentDocsToIndex,
m_localDocsModel, &LocalDocsModel::updateCurrentDocsToIndex, Qt::QueuedConnection);
connect(m_database, &Database::updateTotalDocsToIndex,
@ -40,6 +42,10 @@ LocalDocs::LocalDocs()
m_localDocsModel, &LocalDocsModel::updateCurrentBytesToIndex, Qt::QueuedConnection);
connect(m_database, &Database::updateTotalBytesToIndex,
m_localDocsModel, &LocalDocsModel::updateTotalBytesToIndex, Qt::QueuedConnection);
connect(m_database, &Database::updateCurrentEmbeddingsToIndex,
m_localDocsModel, &LocalDocsModel::updateCurrentEmbeddingsToIndex, Qt::QueuedConnection);
connect(m_database, &Database::updateTotalEmbeddingsToIndex,
m_localDocsModel, &LocalDocsModel::updateTotalEmbeddingsToIndex, Qt::QueuedConnection);
connect(m_database, &Database::addCollectionItem,
m_localDocsModel, &LocalDocsModel::addCollectionItem, Qt::QueuedConnection);
connect(m_database, &Database::removeFolderById,

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@ -48,6 +48,8 @@ QVariant LocalDocsModel::data(const QModelIndex &index, int role) const
return item.installed;
case IndexingRole:
return item.indexing;
case ErrorRole:
return item.error;
case CurrentDocsToIndexRole:
return item.currentDocsToIndex;
case TotalDocsToIndexRole:
@ -56,6 +58,10 @@ QVariant LocalDocsModel::data(const QModelIndex &index, int role) const
return quint64(item.currentBytesToIndex);
case TotalBytesToIndexRole:
return quint64(item.totalBytesToIndex);
case CurrentEmbeddingsToIndexRole:
return quint64(item.currentEmbeddingsToIndex);
case TotalEmbeddingsToIndexRole:
return quint64(item.totalEmbeddingsToIndex);
}
return QVariant();
@ -68,10 +74,13 @@ QHash<int, QByteArray> LocalDocsModel::roleNames() const
roles[FolderPathRole] = "folder_path";
roles[InstalledRole] = "installed";
roles[IndexingRole] = "indexing";
roles[ErrorRole] = "error";
roles[CurrentDocsToIndexRole] = "currentDocsToIndex";
roles[TotalDocsToIndexRole] = "totalDocsToIndex";
roles[CurrentBytesToIndexRole] = "currentBytesToIndex";
roles[TotalBytesToIndexRole] = "totalBytesToIndex";
roles[CurrentEmbeddingsToIndexRole] = "currentEmbeddingsToIndex";
roles[TotalEmbeddingsToIndexRole] = "totalEmbeddingsToIndex";
return roles;
}
@ -101,6 +110,12 @@ void LocalDocsModel::updateIndexing(int folder_id, bool b)
[](CollectionItem& item, bool val) { item.indexing = val; }, {IndexingRole});
}
void LocalDocsModel::updateError(int folder_id, const QString &error)
{
updateField<QString>(folder_id, error,
[](CollectionItem& item, QString val) { item.error = val; }, {ErrorRole});
}
void LocalDocsModel::updateCurrentDocsToIndex(int folder_id, size_t currentDocsToIndex)
{
updateField<size_t>(folder_id, currentDocsToIndex,
@ -131,6 +146,18 @@ void LocalDocsModel::updateTotalBytesToIndex(int folder_id, size_t totalBytesToI
[](CollectionItem& item, size_t val) { item.totalBytesToIndex = val; }, {TotalBytesToIndexRole});
}
void LocalDocsModel::updateCurrentEmbeddingsToIndex(int folder_id, size_t currentEmbeddingsToIndex)
{
updateField<size_t>(folder_id, currentEmbeddingsToIndex,
[](CollectionItem& item, size_t val) { item.currentEmbeddingsToIndex += val; }, {CurrentEmbeddingsToIndexRole});
}
void LocalDocsModel::updateTotalEmbeddingsToIndex(int folder_id, size_t totalEmbeddingsToIndex)
{
updateField<size_t>(folder_id, totalEmbeddingsToIndex,
[](CollectionItem& item, size_t val) { item.totalEmbeddingsToIndex += val; }, {TotalEmbeddingsToIndexRole});
}
void LocalDocsModel::addCollectionItem(const CollectionItem &item)
{
beginInsertRows(QModelIndex(), m_collectionList.size(), m_collectionList.size());

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@ -30,11 +30,13 @@ public:
FolderPathRole,
InstalledRole,
IndexingRole,
EmbeddingRole,
ErrorRole,
CurrentDocsToIndexRole,
TotalDocsToIndexRole,
CurrentBytesToIndexRole,
TotalBytesToIndexRole
TotalBytesToIndexRole,
CurrentEmbeddingsToIndexRole,
TotalEmbeddingsToIndexRole
};
explicit LocalDocsModel(QObject *parent = nullptr);
@ -45,11 +47,14 @@ public:
public Q_SLOTS:
void updateInstalled(int folder_id, bool b);
void updateIndexing(int folder_id, bool b);
void updateError(int folder_id, const QString &error);
void updateCurrentDocsToIndex(int folder_id, size_t currentDocsToIndex);
void updateTotalDocsToIndex(int folder_id, size_t totalDocsToIndex);
void subtractCurrentBytesToIndex(int folder_id, size_t subtractedBytes);
void updateCurrentBytesToIndex(int folder_id, size_t currentBytesToIndex);
void updateTotalBytesToIndex(int folder_id, size_t totalBytesToIndex);
void updateCurrentEmbeddingsToIndex(int folder_id, size_t currentBytesToIndex);
void updateTotalEmbeddingsToIndex(int folder_id, size_t totalBytesToIndex);
void addCollectionItem(const CollectionItem &item);
void removeFolderById(int folder_id);
void removeCollectionPath(const QString &name, const QString &path);

View File

@ -1129,7 +1129,7 @@ Window {
}
Image {
visible: currentChat.isServer || currentChat.modelInfo.isChatGPT
visible: currentChat.isServer || currentChat.modelInfo.isOnline
anchors.fill: parent
sourceSize.width: 1024
sourceSize.height: 1024

View File

@ -218,7 +218,7 @@
"quant": "f16",
"type": "Bert",
"systemPrompt": " ",
"description": "<strong>LocalDocs text embeddings model</strong><br><ul><li>Necessary for LocalDocs feature<li>Used for retrieval augmented generation (RAG)",
"description": "<strong>LocalDocs text embeddings model</strong><br><ul><li>For use with LocalDocs feature<li>Used for retrieval augmented generation (RAG)",
"url": "https://gpt4all.io/models/gguf/all-MiniLM-L6-v2-f16.gguf"
},
{

View File

@ -10,6 +10,7 @@
//#define USE_LOCAL_MODELSJSON
#define DEFAULT_EMBEDDING_MODEL "all-MiniLM-L6-v2-f16.gguf"
#define NOMIC_EMBEDDING_MODEL "nomic-embed-text-v1.txt"
QString ModelInfo::id() const
{
@ -202,7 +203,8 @@ bool EmbeddingModels::filterAcceptsRow(int sourceRow,
{
QModelIndex index = sourceModel()->index(sourceRow, 0, sourceParent);
bool isInstalled = sourceModel()->data(index, ModelList::InstalledRole).toBool();
bool isEmbedding = sourceModel()->data(index, ModelList::FilenameRole).toString() == DEFAULT_EMBEDDING_MODEL;
bool isEmbedding = sourceModel()->data(index, ModelList::FilenameRole).toString() == DEFAULT_EMBEDDING_MODEL ||
sourceModel()->data(index, ModelList::FilenameRole).toString() == NOMIC_EMBEDDING_MODEL;
return isInstalled && isEmbedding;
}
@ -405,7 +407,7 @@ ModelInfo ModelList::defaultModelInfo() const
const size_t ramrequired = defaultModel->ramrequired;
// If we don't have either setting, then just use the first model that requires less than 16GB that is installed
if (!hasUserDefaultName && !info->isChatGPT && ramrequired > 0 && ramrequired < 16)
if (!hasUserDefaultName && !info->isOnline && ramrequired > 0 && ramrequired < 16)
break;
// If we have a user specified default and match, then use it
@ -526,8 +528,8 @@ QVariant ModelList::dataInternal(const ModelInfo *info, int role) const
return info->installed;
case DefaultRole:
return info->isDefault;
case ChatGPTRole:
return info->isChatGPT;
case OnlineRole:
return info->isOnline;
case DisableGUIRole:
return info->disableGUI;
case DescriptionRole:
@ -655,8 +657,8 @@ void ModelList::updateData(const QString &id, int role, const QVariant &value)
info->installed = value.toBool(); break;
case DefaultRole:
info->isDefault = value.toBool(); break;
case ChatGPTRole:
info->isChatGPT = value.toBool(); break;
case OnlineRole:
info->isOnline = value.toBool(); break;
case DisableGUIRole:
info->disableGUI = value.toBool(); break;
case DescriptionRole:
@ -791,7 +793,7 @@ QString ModelList::clone(const ModelInfo &model)
updateData(id, ModelList::FilenameRole, model.filename());
updateData(id, ModelList::DirpathRole, model.dirpath);
updateData(id, ModelList::InstalledRole, model.installed);
updateData(id, ModelList::ChatGPTRole, model.isChatGPT);
updateData(id, ModelList::OnlineRole, model.isOnline);
updateData(id, ModelList::TemperatureRole, model.temperature());
updateData(id, ModelList::TopPRole, model.topP());
updateData(id, ModelList::TopKRole, model.topK());
@ -873,10 +875,10 @@ QString ModelList::uniqueModelName(const ModelInfo &model) const
return baseName;
}
QString ModelList::modelDirPath(const QString &modelName, bool isChatGPT)
QString ModelList::modelDirPath(const QString &modelName, bool isOnline)
{
QVector<QString> possibleFilePaths;
if (isChatGPT)
if (isOnline)
possibleFilePaths << "/" + modelName + ".txt";
else {
possibleFilePaths << "/ggml-" + modelName + ".bin";
@ -911,7 +913,7 @@ void ModelList::updateModelsFromDirectory()
// All files that end with .bin and have 'ggml' somewhere in the name
if (((filename.endsWith(".bin") || filename.endsWith(".gguf")) && (/*filename.contains("ggml") ||*/ filename.contains("gguf")) && !filename.startsWith("incomplete"))
|| (filename.endsWith(".txt") && filename.startsWith("chatgpt-"))) {
|| (filename.endsWith(".txt") && (filename.startsWith("chatgpt-") || filename.startsWith("nomic-")))) {
QString filePath = it.filePath();
QFileInfo info(filePath);
@ -934,7 +936,8 @@ void ModelList::updateModelsFromDirectory()
for (const QString &id : modelsById) {
updateData(id, FilenameRole, filename);
updateData(id, ChatGPTRole, filename.startsWith("chatgpt-"));
// FIXME: WE should change this to use a consistent filename for online models
updateData(id, OnlineRole, filename.startsWith("chatgpt-") || filename.startsWith("nomic-"));
updateData(id, DirpathRole, info.dir().absolutePath() + "/");
updateData(id, FilesizeRole, toFileSize(info.size()));
}
@ -1195,7 +1198,7 @@ void ModelList::parseModelsJsonFile(const QByteArray &jsonData, bool save)
updateData(id, ModelList::NameRole, modelName);
updateData(id, ModelList::FilenameRole, modelFilename);
updateData(id, ModelList::FilesizeRole, "minimal");
updateData(id, ModelList::ChatGPTRole, true);
updateData(id, ModelList::OnlineRole, true);
updateData(id, ModelList::DescriptionRole,
tr("<strong>OpenAI's ChatGPT model GPT-3.5 Turbo</strong><br>") + chatGPTDesc);
updateData(id, ModelList::RequiresVersionRole, "2.4.2");
@ -1219,7 +1222,7 @@ void ModelList::parseModelsJsonFile(const QByteArray &jsonData, bool save)
updateData(id, ModelList::NameRole, modelName);
updateData(id, ModelList::FilenameRole, modelFilename);
updateData(id, ModelList::FilesizeRole, "minimal");
updateData(id, ModelList::ChatGPTRole, true);
updateData(id, ModelList::OnlineRole, true);
updateData(id, ModelList::DescriptionRole,
tr("<strong>OpenAI's ChatGPT model GPT-4</strong><br>") + chatGPTDesc + chatGPT4Warn);
updateData(id, ModelList::RequiresVersionRole, "2.4.2");
@ -1229,6 +1232,34 @@ void ModelList::parseModelsJsonFile(const QByteArray &jsonData, bool save)
updateData(id, ModelList::QuantRole, "NA");
updateData(id, ModelList::TypeRole, "GPT");
}
{
const QString nomicEmbedDesc = tr("<ul><li>For use with LocalDocs feature</li>"
"<li>Used for retrieval augmented generation (RAG)</li>"
"<li>Requires personal Nomic API key.</li>"
"<li>WARNING: Will send your localdocs to Nomic Atlas!</li>"
"<li>You can apply for an API key <a href=\"https://atlas.nomic.ai/\">with Nomic Atlas.</a></li>");
const QString modelName = "Nomic Embed";
const QString id = modelName;
const QString modelFilename = "nomic-embed-text-v1.txt";
if (contains(modelFilename))
changeId(modelFilename, id);
if (!contains(id))
addModel(id);
updateData(id, ModelList::NameRole, modelName);
updateData(id, ModelList::FilenameRole, modelFilename);
updateData(id, ModelList::FilesizeRole, "minimal");
updateData(id, ModelList::OnlineRole, true);
updateData(id, ModelList::DisableGUIRole, true);
updateData(id, ModelList::DescriptionRole,
tr("<strong>LocalDocs Nomic Atlas Embed</strong><br>") + nomicEmbedDesc);
updateData(id, ModelList::RequiresVersionRole, "2.6.3");
updateData(id, ModelList::OrderRole, "na");
updateData(id, ModelList::RamrequiredRole, 0);
updateData(id, ModelList::ParametersRole, "?");
updateData(id, ModelList::QuantRole, "NA");
updateData(id, ModelList::TypeRole, "Bert");
}
}
void ModelList::updateModelsFromSettings()

View File

@ -16,7 +16,7 @@ struct ModelInfo {
Q_PROPERTY(bool installed MEMBER installed)
Q_PROPERTY(bool isDefault MEMBER isDefault)
Q_PROPERTY(bool disableGUI MEMBER disableGUI)
Q_PROPERTY(bool isChatGPT MEMBER isChatGPT)
Q_PROPERTY(bool isOnline MEMBER isOnline)
Q_PROPERTY(QString description MEMBER description)
Q_PROPERTY(QString requiresVersion MEMBER requiresVersion)
Q_PROPERTY(QString deprecatedVersion MEMBER deprecatedVersion)
@ -64,7 +64,7 @@ public:
bool calcHash = false;
bool installed = false;
bool isDefault = false;
bool isChatGPT = false;
bool isOnline = false;
bool disableGUI = false;
QString description;
QString requiresVersion;
@ -217,7 +217,7 @@ public:
CalcHashRole,
InstalledRole,
DefaultRole,
ChatGPTRole,
OnlineRole,
DisableGUIRole,
DescriptionRole,
RequiresVersionRole,
@ -261,7 +261,7 @@ public:
roles[CalcHashRole] = "calcHash";
roles[InstalledRole] = "installed";
roles[DefaultRole] = "isDefault";
roles[ChatGPTRole] = "isChatGPT";
roles[OnlineRole] = "isOnline";
roles[DisableGUIRole] = "disableGUI";
roles[DescriptionRole] = "description";
roles[RequiresVersionRole] = "requiresVersion";
@ -359,7 +359,7 @@ private Q_SLOTS:
void handleSslErrors(QNetworkReply *reply, const QList<QSslError> &errors);
private:
QString modelDirPath(const QString &modelName, bool isChatGPT);
QString modelDirPath(const QString &modelName, bool isOnline);
int indexForModel(ModelInfo *model);
QVariant dataInternal(const ModelInfo *info, int role) const;
static bool lessThan(const ModelInfo* a, const ModelInfo* b);

View File

@ -94,11 +94,13 @@ MyDialog {
anchors.right: parent.right
anchors.margins: 20
anchors.leftMargin: 40
visible: model.indexing
value: (model.totalBytesToIndex - model.currentBytesToIndex) / model.totalBytesToIndex
visible: model.indexing || model.currentEmbeddingsToIndex !== model.totalEmbeddingsToIndex || model.error !== ""
value: model.error !== "" ? 0 : model.indexing ?
(model.totalBytesToIndex - model.currentBytesToIndex) / model.totalBytesToIndex :
(model.currentEmbeddingsToIndex / model.totalEmbeddingsToIndex)
background: Rectangle {
implicitHeight: 45
color: theme.progressBackground
color: model.error ? theme.textErrorColor : theme.progressBackground
radius: 3
}
contentItem: Item {
@ -114,16 +116,18 @@ MyDialog {
Accessible.role: Accessible.ProgressBar
Accessible.name: qsTr("Indexing progressBar")
Accessible.description: qsTr("Shows the progress made in the indexing")
ToolTip.text: model.error
ToolTip.visible: hovered && model.error !== ""
}
Label {
id: speedLabel
color: theme.textColor
visible: model.indexing
visible: model.indexing || model.currentEmbeddingsToIndex !== model.totalEmbeddingsToIndex
anchors.verticalCenter: itemProgressBar.verticalCenter
anchors.left: itemProgressBar.left
anchors.right: itemProgressBar.right
horizontalAlignment: Text.AlignHCenter
text: qsTr("indexing...")
text: model.error !== "" ? qsTr("error...") : (model.indexing ? qsTr("indexing...") : qsTr("embeddings..."))
elide: Text.ElideRight
font.pixelSize: theme.fontSizeLarge
}

View File

@ -135,10 +135,10 @@ MyDialog {
font.pixelSize: theme.fontSizeLarge
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: openaiKey.width
Layout.minimumWidth: apiKey.width
Layout.fillWidth: true
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
visible: !isChatGPT && !installed && !calcHash && downloadError === ""
visible: !isOnline && !installed && !calcHash && downloadError === ""
Accessible.description: qsTr("Stop/restart/start the download")
onClicked: {
if (!isDownloading) {
@ -154,7 +154,7 @@ MyDialog {
text: qsTr("Remove")
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: openaiKey.width
Layout.minimumWidth: apiKey.width
Layout.fillWidth: true
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
visible: installed || downloadError !== ""
@ -166,23 +166,23 @@ MyDialog {
MySettingsButton {
id: installButton
visible: !installed && isChatGPT
visible: !installed && isOnline
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: openaiKey.width
Layout.minimumWidth: apiKey.width
Layout.fillWidth: true
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
text: qsTr("Install")
font.pixelSize: theme.fontSizeLarge
onClicked: {
if (openaiKey.text === "")
openaiKey.showError();
if (apiKey.text === "")
apiKey.showError();
else
Download.installModel(filename, openaiKey.text);
Download.installModel(filename, apiKey.text);
}
Accessible.role: Accessible.Button
Accessible.name: qsTr("Install")
Accessible.description: qsTr("Install chatGPT model")
Accessible.description: qsTr("Install online model")
}
ColumnLayout {
@ -238,7 +238,7 @@ MyDialog {
visible: LLM.systemTotalRAMInGB() < ramrequired
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.maximumWidth: openaiKey.width
Layout.maximumWidth: apiKey.width
textFormat: Text.StyledText
text: qsTr("<strong><font size=\"2\">WARNING: Not recommended for your hardware.")
+ qsTr(" Model requires more memory (") + ramrequired
@ -261,7 +261,7 @@ MyDialog {
visible: isDownloading && !calcHash
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: openaiKey.width
Layout.minimumWidth: apiKey.width
Layout.fillWidth: true
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
spacing: 20
@ -269,7 +269,7 @@ MyDialog {
ProgressBar {
id: itemProgressBar
Layout.fillWidth: true
width: openaiKey.width
width: apiKey.width
value: bytesReceived / bytesTotal
background: Rectangle {
implicitHeight: 45
@ -307,7 +307,7 @@ MyDialog {
visible: calcHash
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: openaiKey.width
Layout.minimumWidth: apiKey.width
Layout.fillWidth: true
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
@ -331,8 +331,8 @@ MyDialog {
}
MyTextField {
id: openaiKey
visible: !installed && isChatGPT
id: apiKey
visible: !installed && isOnline
Layout.topMargin: 20
Layout.leftMargin: 20
Layout.minimumWidth: 150
@ -340,19 +340,19 @@ MyDialog {
Layout.alignment: Qt.AlignTop | Qt.AlignHCenter
wrapMode: Text.WrapAnywhere
function showError() {
openaiKey.placeholderTextColor = theme.textErrorColor
apiKey.placeholderTextColor = theme.textErrorColor
}
onTextChanged: {
openaiKey.placeholderTextColor = theme.mutedTextColor
apiKey.placeholderTextColor = theme.mutedTextColor
}
placeholderText: qsTr("enter $OPENAI_API_KEY")
placeholderText: qsTr("enter $API_KEY")
Accessible.role: Accessible.EditableText
Accessible.name: placeholderText
Accessible.description: qsTr("Whether the file hash is being calculated")
TextMetrics {
id: textMetrics
font: openaiKey.font
text: openaiKey.placeholderText
font: apiKey.font
text: apiKey.placeholderText
}
}
}