gpt4all/gpt4all-chat/embllm.h

86 lines
1.9 KiB
C++

#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