mirror of
https://github.com/ParisNeo/lollms-webui.git
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92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
######
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# Project : GPT4ALL-UI
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# File : backend.py
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# Author : ParisNeo with the help of the community
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# Underlying backend : Abdeladim's pygptj backend
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# Supported by Nomic-AI
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# Licence : Apache 2.0
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# Description :
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# This is an interface class for GPT4All-ui backends.
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# This backend is a wrapper to abdeladim's backend
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# Follow him on his github project : https://github.com/abdeladim-s/pygptj
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######
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from pathlib import Path
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from typing import Callable
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from pygptj.model import Model
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from gpt4all_api.backend import GPTBackend
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__author__ = "parisneo"
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__github__ = "https://github.com/nomic-ai/gpt4all-ui"
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__copyright__ = "Copyright 2023, "
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__license__ = "Apache 2.0"
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backend_name = "GptJ"
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class GptJ(GPTBackend):
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file_extension='*.bin'
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def __init__(self, config:dict) -> None:
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"""Builds a LLAMACPP backend
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Args:
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config (dict): The configuration file
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"""
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super().__init__(config, False)
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self.model = Model(
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model_path=f"./models/gpt_j/{self.config['model']}",
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prompt_context="", prompt_prefix="", prompt_suffix=""
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)
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def tokenize(self, prompt):
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"""
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Tokenizes the given prompt using the model's tokenizer.
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Args:
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prompt (str): The input prompt to be tokenized.
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Returns:
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list: A list of tokens representing the tokenized prompt.
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"""
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return None
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def detokenize(self, tokens_list):
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"""
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Detokenizes the given list of tokens using the model's tokenizer.
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Args:
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tokens_list (list): A list of tokens to be detokenized.
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Returns:
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str: The detokenized text as a string.
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"""
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return None
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def generate(self,
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prompt:str,
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n_predict: int = 128,
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new_text_callback: Callable[[str], None] = bool,
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verbose: bool = False,
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**gpt_params ):
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"""Generates text out of a prompt
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Args:
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prompt (str): The prompt to use for generation
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n_predict (int, optional): Number of tokens to prodict. Defaults to 128.
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new_text_callback (Callable[[str], None], optional): A callback function that is called everytime a new text element is generated. Defaults to None.
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verbose (bool, optional): If true, the code will spit many informations about the generation process. Defaults to False.
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"""
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try:
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self.model.reset()
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for tok in self.model.generate(prompt,
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n_predict=n_predict,
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temp=self.config['temperature'],
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top_k=self.config['top_k'],
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top_p=self.config['top_p'],
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#repeat_penalty=self.config['repeat_penalty'],
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#repeat_last_n = self.config['repeat_last_n'],
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n_threads=self.config['n_threads'],
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):
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if not new_text_callback(tok):
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return
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except Exception as ex:
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print(ex) |