Add Nomic Embed model for atlas with localdocs.

gpt4all-chat/chatllm.cpp

@@ -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);
 

gpt4all-chat/database.cpp

@@ -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();

gpt4all-chat/database.h

@@ -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);

gpt4all-chat/embeddings.cpp

@@ -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) {

gpt4all-chat/embllm.cpp

@@ -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()
 {
+    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);
 }

gpt4all-chat/embllm.h

@@ -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

gpt4all-chat/localdocs.cpp

@@ -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,

gpt4all-chat/localdocsmodel.cpp

@@ -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());

gpt4all-chat/localdocsmodel.h

@@ -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);

gpt4all-chat/main.qml

@@ -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

gpt4all-chat/metadata/models2.json

@@ -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"
   },
   {

gpt4all-chat/modellist.cpp

@@ -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()

gpt4all-chat/modellist.h

@@ -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);

gpt4all-chat/qml/CollectionsDialog.qml

@@ -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
                 }

gpt4all-chat/qml/ModelDownloaderDialog.qml

@@ -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
                                     }
                                 }
                             }