LLM.h

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#pragma once
 
#include "defs.h"
#include "error_handling.h"
#include <sstream>
#if defined(__APPLE__)
#include <TargetConditionals.h>
#endif
 
 
struct LoraIdScale
{
    int id;      
    float scale; 
 
    bool operator==(const LoraIdScale &other) const
    {
        return id == other.id && scale == other.scale;
    }
};
 
struct LoraIdScalePath
{
    int id;           
    float scale;      
    std::string path; 
 
    bool operator==(const LoraIdScalePath &other) const
    {
        return id == other.id && scale == other.scale && path == other.path;
    }
};
 
void ensure_error_handlers_initialized();
 
class UNDREAMAI_API LLM
{
public:
    int32_t n_keep = 0;       
    std::string grammar = ""; 
    json completion_params;   
 
    virtual ~LLM() = default;
 
    virtual std::vector<int> tokenize(const std::string &query);
 
    virtual std::string tokenize_json(const json &data) = 0;
 
    virtual std::string detokenize(const std::vector<int32_t> &tokens);
 
    virtual std::string detokenize_json(const json &data) = 0;
 
    virtual std::vector<float> embeddings(const std::string &query);
 
    virtual std::string embeddings_json(const json &data) = 0;
 
    //  See https://github.com/ggml-org/llama.cpp/tree/master/tools/server#post-completion-given-a-prompt-it-returns-the-predicted-completion for the different parameters
    virtual void set_completion_params(json completion_params_) { completion_params = completion_params_; }
 
    virtual std::string get_completion_params() { return completion_params; }
 
    virtual std::string completion(const std::string &prompt, CharArrayFn callback = nullptr, int id_slot = -1, bool return_response_json = false);
 
    virtual std::string completion_json(const json &data, CharArrayFn callback, bool callbackWithJSON) = 0;
 
    virtual void set_grammar(std::string grammar_) { grammar = grammar_; }
 
    virtual std::string get_grammar() { return grammar; }
 
    virtual std::string apply_template(const json &messages);
 
    virtual std::string apply_template_json(const json &data) = 0;
 
    static bool has_gpu_layers(const std::string &command);
 
    static std::string LLM_args_to_command(const std::string &model_path, int num_slots = 1, int num_threads = -1, int num_GPU_layers = 0, bool flash_attention = false, int context_size = 4096, int batch_size = 2048, bool embedding_only = false, const std::vector<std::string> &lora_paths = {});
 
protected:
    virtual json build_apply_template_json(const json &messages);
 
    virtual std::string parse_apply_template_json(const json &result);
 
    virtual json build_tokenize_json(const std::string &query);
 
    virtual std::vector<int> parse_tokenize_json(const json &result);
 
    virtual json build_detokenize_json(const std::vector<int32_t> &tokens);
 
    virtual std::string parse_detokenize_json(const json &result);
 
    virtual json build_embeddings_json(const std::string &query);
 
    virtual std::vector<float> parse_embeddings_json(const json &result);
 
    virtual json build_completion_json(const std::string &prompt, int id_slot = -1);
 
    virtual std::string parse_completion_json(const json &result);
};
 
class UNDREAMAI_API LLMLocal : public LLM
{
public:
    virtual int get_next_available_slot() = 0;
 
    virtual std::string save_slot(int id_slot, const std::string &filepath) { return slot(id_slot, "save", filepath); }
 
    virtual std::string load_slot(int id_slot, const std::string &filepath) { return slot(id_slot, "restore", filepath); }
 
    virtual void cancel(int id_slot) = 0;
 
    virtual std::string slot_json(const json &data) = 0;
 
protected:
    virtual std::string slot(int id_slot, const std::string &action, const std::string &filepath);
 
    virtual json build_slot_json(int id_slot, const std::string &action, const std::string &filepath);
 
    virtual std::string parse_slot_json(const json &result);
};
 
class UNDREAMAI_API LLMProvider : public LLMLocal
{
public:
    virtual ~LLMProvider();
 
    virtual bool lora_weight(const std::vector<LoraIdScale> &loras);
 
    virtual std::string lora_weight_json(const json &data) = 0;
 
    virtual std::vector<LoraIdScalePath> lora_list();
 
    virtual std::string lora_list_json() = 0;
 
    virtual void enable_reasoning(bool reasoning) { reasoning_enabled = reasoning; }
 
    virtual void debug(int debug_level) = 0;
 
    virtual void logging_callback(CharArrayFn callback) = 0;
 
    virtual void logging_stop();
 
    virtual void start() = 0;
 
    virtual bool started() = 0;
 
    virtual void stop() = 0;
 
    virtual void start_server(const std::string &host = "0.0.0.0", int port = -1, const std::string &API_key = "") = 0;
 
    virtual void stop_server() = 0;
 
    virtual void join_service() = 0;
 
    virtual void join_server() = 0;
 
    virtual void set_SSL(const std::string &SSL_cert, const std::string &SSL_key) = 0;
 
    virtual int embedding_size() = 0;
 
    virtual std::string debug_implementation() = 0;
 
protected:
    bool reasoning_enabled = false; 
 
    virtual bool parse_lora_weight_json(const json &result);
 
    virtual json build_lora_weight_json(const std::vector<LoraIdScale> &loras);
 
    virtual std::vector<LoraIdScalePath> parse_lora_list_json(const json &result);
 
    virtual json build_lora_list_json(const std::vector<LoraIdScalePath> &loras);
};
 
class LLMProviderRegistry
{
public:
    static bool initialised; 
 
    static void inject_registry(LLMProviderRegistry *instance)
    {
        custom_instance_ = instance;
        initialised = true;
    }
 
    static LLMProviderRegistry &instance()
    {
        if (custom_instance_)
            return *custom_instance_;
 
        static LLMProviderRegistry registry;
        initialised = true;
        return registry;
    }
 
    void register_instance(LLMProvider *service)
    {
        std::lock_guard<std::mutex> lock(mutex_);
        instances_.push_back(service);
    }
 
    void unregister_instance(LLMProvider *service)
    {
        std::lock_guard<std::mutex> lock(mutex_);
        instances_.erase(std::remove(instances_.begin(), instances_.end(), service), instances_.end());
    }
 
    std::vector<LLMProvider *> get_instances()
    {
        std::lock_guard<std::mutex> lock(mutex_);
        return instances_;
    }
 
    void set_debug_level(int level)
    {
        debug_level_ = level;
    }
 
    const int get_debug_level()
    {
        return debug_level_;
    }
 
    void set_log_callback(CharArrayFn callback)
    {
        log_callback_ = callback;
    }
 
    const CharArrayFn get_log_callback()
    {
        return log_callback_;
    }
 
private:
    static LLMProviderRegistry *custom_instance_; 
 
    std::mutex mutex_;                     
    std::vector<LLMProvider *> instances_; 
    int debug_level_ = 0;                  
    CharArrayFn log_callback_ = nullptr;   
 
    LLMProviderRegistry() = default;
    ~LLMProviderRegistry() = default;
    LLMProviderRegistry(const LLMProviderRegistry &) = delete;
    LLMProviderRegistry &operator=(const LLMProviderRegistry &) = delete;
};
 
 
extern "C"
{
    UNDREAMAI_API bool Has_GPU_Layers(const char *command);
 
    UNDREAMAI_API void LLM_Debug(int debug_level);
 
    UNDREAMAI_API void LLM_Logging_Callback(CharArrayFn callback);
 
    UNDREAMAI_API void LLM_Logging_Stop();
 
#ifdef _DEBUG
    UNDREAMAI_API const bool IsDebuggerAttached(void);
#endif
 
    UNDREAMAI_API void LLM_Set_Completion_Parameters(LLM *llm, const char *params_json = "{}");
 
    UNDREAMAI_API const char *LLM_Get_Completion_Parameters(LLM *llm);
 
    UNDREAMAI_API void LLM_Set_Grammar(LLM *llm, const char *grammar = "");
 
    UNDREAMAI_API const char *LLM_Get_Grammar(LLM *llm);
 
    UNDREAMAI_API const char *LLM_Apply_Template(LLM *llm, const char *messages_as_json);
 
    UNDREAMAI_API const char *LLM_Tokenize(LLM *llm, const char *query);
 
    UNDREAMAI_API const char *LLM_Detokenize(LLM *llm, const char *tokens_as_json);
 
    UNDREAMAI_API const char *LLM_Embeddings(LLM *llm, const char *query);
 
    UNDREAMAI_API const char *LLM_Completion(LLM *llm, const char *prompt, CharArrayFn callback = nullptr, int id_slot = -1, bool return_response_json = false);
 
    UNDREAMAI_API const char *LLM_Save_Slot(LLMLocal *llm, int id_slot, const char *filepath);
 
    UNDREAMAI_API const char *LLM_Load_Slot(LLMLocal *llm, int id_slot, const char *filepath);
 
    UNDREAMAI_API void LLM_Cancel(LLMLocal *llm, int id_slot);
 
    UNDREAMAI_API bool LLM_Lora_Weight(LLMProvider *llm, const char *loras_as_json);
 
    UNDREAMAI_API void LLM_Enable_Reasoning(LLMProvider *llm, bool enable_reasoning);
 
    UNDREAMAI_API const char *LLM_Lora_List(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Delete(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Start(LLMProvider *llm);
 
    UNDREAMAI_API const bool LLM_Started(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Stop(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Start_Server(LLMProvider *llm, const char *host = "0.0.0.0", int port = -1, const char *API_key = "");
 
    UNDREAMAI_API void LLM_Stop_Server(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Join_Service(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Join_Server(LLMProvider *llm);
 
    UNDREAMAI_API void LLM_Set_SSL(LLMProvider *llm, const char *SSL_cert, const char *SSL_key);
 
    UNDREAMAI_API const int LLM_Status_Code();
 
    UNDREAMAI_API const char *LLM_Status_Message();
 
    UNDREAMAI_API const int LLM_Embedding_Size(LLMProvider *llm);
}