mirror of
https://github.com/nomic-ai/gpt4all
synced 2024-11-06 09:20:33 +00:00
128 lines
3.2 KiB
C++
128 lines
3.2 KiB
C++
#include "../../gpt4all-backend/llmodel_c.h"
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#include "../../gpt4all-backend/llmodel.h"
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#include "../../gpt4all-backend/llama.cpp/llama.h"
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#include "../../gpt4all-backend/llmodel_c.cpp"
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#include "../../gpt4all-backend/mpt.h"
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#include "../../gpt4all-backend/mpt.cpp"
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#include "../../gpt4all-backend/llamamodel.h"
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#include "../../gpt4all-backend/gptj.h"
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#include "binding.h"
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#include <cassert>
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#include <cmath>
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#include <cstdio>
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#include <cstring>
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#include <fstream>
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#include <map>
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#include <string>
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#include <vector>
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#include <iostream>
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#include <unistd.h>
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void* load_mpt_model(const char *fname, int n_threads) {
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// load the model
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auto gptj = llmodel_mpt_create();
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llmodel_setThreadCount(gptj, n_threads);
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if (!llmodel_loadModel(gptj, fname)) {
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return nullptr;
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}
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return gptj;
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}
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void* load_llama_model(const char *fname, int n_threads) {
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// load the model
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auto gptj = llmodel_llama_create();
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llmodel_setThreadCount(gptj, n_threads);
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if (!llmodel_loadModel(gptj, fname)) {
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return nullptr;
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}
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return gptj;
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}
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void* load_gptj_model(const char *fname, int n_threads) {
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// load the model
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auto gptj = llmodel_gptj_create();
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llmodel_setThreadCount(gptj, n_threads);
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if (!llmodel_loadModel(gptj, fname)) {
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return nullptr;
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}
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return gptj;
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}
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std::string res = "";
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void * mm;
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void gptj_model_prompt( const char *prompt, void *m, char* result, int repeat_last_n, float repeat_penalty, int n_ctx, int tokens, int top_k,
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float top_p, float temp, int n_batch,float ctx_erase)
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{
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llmodel_model* model = (llmodel_model*) m;
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// std::string res = "";
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auto lambda_prompt = [](int token_id) {
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return true;
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};
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mm=model;
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res="";
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auto lambda_response = [](int token_id, const char *responsechars) {
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res.append((char*)responsechars);
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return !!getTokenCallback(mm, (char*)responsechars);
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};
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auto lambda_recalculate = [](bool is_recalculating) {
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// You can handle recalculation requests here if needed
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return is_recalculating;
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};
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llmodel_prompt_context* prompt_context = new llmodel_prompt_context{
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.logits = NULL,
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.logits_size = 0,
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.tokens = NULL,
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.tokens_size = 0,
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.n_past = 0,
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.n_ctx = 1024,
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.n_predict = 50,
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.top_k = 10,
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.top_p = 0.9,
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.temp = 1.0,
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.n_batch = 1,
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.repeat_penalty = 1.2,
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.repeat_last_n = 10,
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.context_erase = 0.5
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};
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prompt_context->n_predict = tokens;
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prompt_context->repeat_last_n = repeat_last_n;
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prompt_context->repeat_penalty = repeat_penalty;
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prompt_context->n_ctx = n_ctx;
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prompt_context->top_k = top_k;
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prompt_context->context_erase = ctx_erase;
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prompt_context->top_p = top_p;
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prompt_context->temp = temp;
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prompt_context->n_batch = n_batch;
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llmodel_prompt(model, prompt,
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lambda_prompt,
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lambda_response,
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lambda_recalculate,
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prompt_context );
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strcpy(result, res.c_str());
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free(prompt_context);
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}
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void gptj_free_model(void *state_ptr) {
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llmodel_model* ctx = (llmodel_model*) state_ptr;
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llmodel_llama_destroy(ctx);
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}
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