lollms-webui/backends/gpt_j_a/__init__.py
2023-05-19 03:32:38 +02:00

96 lines
3.5 KiB
Python

######
# Project : GPT4ALL-UI
# File : backend.py
# Author : ParisNeo with the help of the community
# Underlying backend : Abdeladim's pygptj backend
# Supported by Nomic-AI
# Licence : Apache 2.0
# Description :
# This is an interface class for GPT4All-ui backends.
# This backend is a wrapper to abdeladim's backend
# 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 gpt4all_api.backend import GPTBackend
__author__ = "parisneo"
__github__ = "https://github.com/nomic-ai/gpt4all-ui"
__copyright__ = "Copyright 2023, "
__license__ = "Apache 2.0"
backend_name = "GptJ"
class GptJ(GPTBackend):
file_extension='*.bin'
def __init__(self, config:dict) -> None:
"""Builds a LLAMACPP backend
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=self.config['temperature'],
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'],
):
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