lollms-webui/pyGpt4All/backends/llama_cpp.py

######
# Project       : GPT4ALL-UI
# File          : backend.py
# Author        : ParisNeo with the help of the community
# Supported by Nomic-AI
# Licence       : Apache 2.0
# Description   : 
# This is an interface class for GPT4All-ui backends.
######
from pathlib import Path
from typing import Callable
from pyllamacpp.model import Model
from pyGpt4All.backends.backend import GPTBackend

__author__ = "parisneo"
__github__ = "https://github.com/nomic-ai/gpt4all-ui"
__copyright__ = "Copyright 2023, "
__license__ = "Apache 2.0"

backend_name = "LLAMACPP"

class LLAMACPP(GPTBackend):
    file_extension='*.bin'
    def __init__(self, config:dict) -> None:
        """Builds a LLAMACPP backend

        Args:
            config (dict): The configuration file
        """
        super().__init__(config)
        
        self.model = Model(
                ggml_model=f"./models/llama_cpp/{self.config['model']}", 
                n_ctx=self.config['ctx_size'], 
                seed=self.config['seed'],
                )


    def generate(self, 
                 prompt:str,                  
                 n_predict: int = 128,
                 new_text_callback: Callable[[str], None] = bool,
                 verbose: bool = False,
                 **gpt_params ):
        """Generates text out of a prompt

        Args:
            prompt (str): The prompt to use for generation
            n_predict (int, optional): Number of tokens to prodict. Defaults to 128.
            new_text_callback (Callable[[str], None], optional): A callback function that is called everytime a new text element is generated. Defaults to None.
            verbose (bool, optional): If true, the code will spit many informations about the generation process. Defaults to False.
        """
        self.model.generate(
            prompt,
            new_text_callback=new_text_callback,
            n_predict=n_predict,
            temp=self.config['temp'],
            top_k=self.config['top_k'],
            top_p=self.config['top_p'],
            repeat_penalty=self.config['repeat_penalty'],
            repeat_last_n = self.config['repeat_last_n'],
            n_threads=self.config['n_threads'],
            verbose=verbose
        )