ollama/llm/llama.cpp/ext_server.h
Daniel Hiltgen 9a70aecccb Refactor how we augment llama.cpp
This changes the model for llama.cpp inclusion so we're not applying a patch,
but instead have the C++ code directly in the ollama tree, which should make it
easier to refine and update over time.
2024-01-02 15:35:55 -08:00

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3.5 KiB
C

#if defined(LLAMA_SERVER_LIBRARY)
#ifndef LLAMA_SERVER_H
#define LLAMA_SERVER_H
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#include <stdio.h>
int __main(int argc, char **argv);
// This exposes extern C entrypoints into the llama_server
// To enable the server compile with LLAMA_SERVER_LIBRARY
#ifdef __cplusplus
extern "C" {
#endif
typedef struct ext_server_resp {
int id; // < 0 on error
size_t msg_len; // caller must allocate msg and set msg_len
char *msg;
} ext_server_resp_t;
// Allocated and freed by caller
typedef struct ext_server_lora_adapter {
char *adapter;
float scale;
struct ext_server_lora_adapter *next;
} ext_server_lora_adapter_t;
// Allocated and freed by caller
typedef struct ext_server_params {
char *model;
uint32_t n_ctx; // token context window, 0 = from model
uint32_t n_batch; // prompt processing maximum batch size
uint32_t n_threads; // number of threads to use for generation
int32_t n_parallel; // number of parallel sequences to decodewra
float rope_freq_base; // RoPE base frequency, 0 = from model
float rope_freq_scale; // RoPE frequency scaling factor, 0 = from model
bool memory_f16; // use f16 instead of f32 for memory kv
int32_t n_gpu_layers; // number of layers to store in VRAM (-1 - use default)
int32_t main_gpu; // the GPU that is used for scratch and small tensors
bool use_mlock; // force system to keep model in RAM
bool use_mmap; // use mmap if possible
bool numa; // attempt optimizations that help on some NUMA systems
bool embedding; // get only sentence embedding
ext_server_lora_adapter_t *lora_adapters;
char *mmproj;
} ext_server_params_t;
typedef struct ext_server_task_result {
int id;
bool stop;
bool error;
char *json_resp; // null terminated, memory managed by ext_server
} ext_server_task_result_t;
// Initialize the server once per process
// err->id = 0 for success and err->msg[0] = NULL
// err->id != 0 for failure, and err->msg contains error message
void llama_server_init(ext_server_params_t *sparams, ext_server_resp_t *err);
// Run the main loop, called once per init
void llama_server_start();
// Stop the main loop and free up resources allocated in init and start. Init
// must be called again to reuse
void llama_server_stop();
// json_req null terminated string, memory managed by caller
// resp->id >= 0 on success (task ID)
// resp->id < 0 on error, and resp->msg contains error message
void llama_server_completion(const char *json_req, ext_server_resp_t *resp);
// Caller must call llama_server_release_task_result to free resp->json_resp
void llama_server_completion_next_result(const int task_id,
ext_server_task_result_t *result);
void llama_server_completion_cancel(const int task_id, ext_server_resp_t *err);
void llama_server_release_task_result(ext_server_task_result_t *result);
// Caller must call llama_server_releaes_json_resp to free json_resp if err.id <
// 0
void llama_server_tokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_detokenize(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_embedding(const char *json_req, char **json_resp,
ext_server_resp_t *err);
void llama_server_release_json_resp(char **json_resp);
#ifdef __cplusplus
}
#endif
#endif
#endif // LLAMA_SERVER_LIBRARY