gpt4all/gpt4all-backend/llamamodel_impl.h
Jared Van Bortel 406e88b59a
implement local Nomic Embed via llama.cpp (#2086)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
2024-03-13 18:09:24 -04:00

68 lines
3.0 KiB
C++

#ifndef LLAMAMODEL_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
#error This file is NOT meant to be included outside of llamamodel.cpp. Doing so is DANGEROUS. Be sure to know what you are doing before proceeding to #define LLAMAMODEL_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
#endif
#ifndef LLAMAMODEL_H
#define LLAMAMODEL_H
#include <functional>
#include <memory>
#include <string>
#include <vector>
#include "llmodel.h"
struct LLamaPrivate;
struct EmbModelSpec;
class LLamaModel : public LLModel {
public:
LLamaModel();
~LLamaModel();
bool supportsEmbedding() const override { return m_supportsEmbedding; }
bool supportsCompletion() const override { return m_supportsCompletion; }
bool loadModel(const std::string &modelPath, int n_ctx, int ngl) override;
bool isModelBlacklisted(const std::string &modelPath) const override;
bool isEmbeddingModel(const std::string &modelPath) const override;
bool isModelLoaded() const override;
size_t requiredMem(const std::string &modelPath, int n_ctx, int ngl) override;
size_t stateSize() const override;
size_t saveState(uint8_t *dest) const override;
size_t restoreState(const uint8_t *src) override;
void setThreadCount(int32_t n_threads) override;
int32_t threadCount() const override;
std::vector<GPUDevice> availableGPUDevices(size_t memoryRequired) const override;
bool initializeGPUDevice(size_t memoryRequired, const std::string &name) const override;
bool initializeGPUDevice(int device, std::string *unavail_reason = nullptr) const override;
bool hasGPUDevice() override;
bool usingGPUDevice() override;
size_t embeddingSize() const override;
// user-specified prefix
void embed(const std::vector<std::string> &texts, float *embeddings, std::optional<std::string> prefix,
int dimensionality = -1, bool doMean = true, bool atlas = false) override;
// automatic prefix
void embed(const std::vector<std::string> &texts, float *embeddings, bool isRetrieval, int dimensionality = -1,
bool doMean = true, bool atlas = false) override;
private:
std::unique_ptr<LLamaPrivate> d_ptr;
bool m_supportsEmbedding = false;
bool m_supportsCompletion = false;
protected:
std::vector<Token> tokenize(PromptContext &ctx, const std::string &str, bool special) const override;
std::string tokenToString(Token id) const override;
Token sampleToken(PromptContext &ctx) const override;
bool evalTokens(PromptContext &ctx, const std::vector<int32_t> &tokens) const override;
int32_t contextLength() const override;
const std::vector<Token> &endTokens() const override;
bool shouldAddBOS() const override;
int32_t maxContextLength(std::string const &modelPath) const override;
int32_t layerCount(std::string const &modelPath) const override;
void embedInternal(const std::vector<std::string> &texts, float *embeddings, std::string prefix, int dimensionality,
bool doMean, bool atlas, const EmbModelSpec *spec);
};
#endif // LLAMAMODEL_H