###### # Project : GPT4ALL-UI # File : binding.py # Author : ParisNeo with the help of the community # Underlying binding : Abdeladim's pygptj binding # Supported by Nomic-AI # license : Apache 2.0 # Description : # This is an interface class for GPT4All-ui bindings. # This binding is a wrapper to abdeladim's binding # Follow him on his github project : https://github.com/abdeladim-s/pygptj ###### from pathlib import Path from typing import Callable from pygptj.model import Model from api.binding import LLMBinding __author__ = "parisneo" __github__ = "https://github.com/ParisNeo/gpt4all-ui" __copyright__ = "Copyright 2023, " __license__ = "Apache 2.0" binding_name = "GptJ" class GptJ(LLMBinding): file_extension='*.bin' def __init__(self, config:dict) -> None: """Builds a LLAMACPP binding Args: config (dict): The configuration file """ super().__init__(config, False) self.model = Model( model_path=f"./models/gpt_j/{self.config['model']}", prompt_context="", prompt_prefix="", prompt_suffix="" ) def tokenize(self, prompt): """ Tokenizes the given prompt using the model's tokenizer. Args: prompt (str): The input prompt to be tokenized. Returns: list: A list of tokens representing the tokenized prompt. """ return None def detokenize(self, tokens_list): """ Detokenizes the given list of tokens using the model's tokenizer. Args: tokens_list (list): A list of tokens to be detokenized. Returns: str: The detokenized text as a string. """ return None 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. """ try: self.model.reset() output = "" for tok in self.model.generate(prompt, n_predict=n_predict, temp=gpt_params["temperature"], top_k=gpt_params['top_k'], top_p=gpt_params['top_p'], #repeat_penalty=gpt_params['repeat_penalty'], #repeat_last_n = self.config['repeat_last_n'], n_threads=self.config['n_threads'], ): output += tok if new_text_callback is not None: if not new_text_callback(tok): return output except Exception as ex: print(ex) return output