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import os
import gradio as gr
import copy
import llama_cpp
from llama_cpp import Llama
import random
from huggingface_hub import hf_hub_download
import time
from modules.load_presets import load_presets_value
from modules.load_model import *
def generate_text(message, history, system_prompt, preset, temperature, max_tokens, top_p, top_k, repeat_penalty, model, n_ctx, n_gpu_layers, n_threads, verbose, f16_kv, logits_all, vocab_only, use_mmap, use_mlock, n_batch, last_n_tokens_size, low_vram, rope_freq_base, rope_freq_scale):
dir = os.getcwd()
global llm
llm = Llama(
model_path=f"{dir}\models\{model}",
n_ctx=n_ctx,
n_gpu_layers=n_gpu_layers,
n_threads=n_threads,
verbose=verbose,
f16_kv=f16_kv,
logits_all=logits_all,
vocab_only=vocab_only,
use_mmap=use_mmap,
use_mlock=use_mlock,
n_batch=n_batch,
last_n_tokens_size=last_n_tokens_size,
low_vram=low_vram,
rope_freq_base=rope_freq_base,
rope_freq_scale=rope_freq_scale,
)
global_sys_prompt = load_presets_value(preset) + " " + system_prompt
temp = ""
input_prompt = f"[INST] <<SYS>>\n{global_sys_prompt}.\n<</SYS>>\n\n "
for interaction in history:
input_prompt = input_prompt + str(interaction[0]) + " [/INST] " + str(interaction[1]) + " </s><s> [INST] "
input_prompt = input_prompt + str(message) + " [/INST] "
output = llm(
input_prompt,
temperature=temperature,
top_p=top_p,
top_k=top_k,
repeat_penalty=repeat_penalty,
max_tokens=max_tokens,
stop=[
"<|prompter|>",
"<|endoftext|>",
"<|endoftext|> \n",
"ASSISTANT:",
"USER:",
"SYSTEM:",
],
stream=True,
)
for out in output:
stream = copy.deepcopy(out)
temp += stream["choices"][0]["text"]
yield temp
history = ["init", input_prompt]
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