gpt4all/gpt4all-chat/embllm.h

#ifndef EMBLLM_H
#define EMBLLM_H

#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
public:
    EmbeddingLLM();
    virtual ~EmbeddingLLM();

    bool loadModel();
    bool hasModel() const;

public Q_SLOTS:
    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:
    EmbeddingLLMWorker *m_embeddingWorker;
};

#endif // EMBLLM_H