lollms-webui/backends/gpt_j_m/__init__.py
2023-05-17 17:38:40 +02:00

84 lines
3.2 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 marella's backend
# Follow him on his github project : https://github.com/marella/gpt4all-j
######
from pathlib import Path
from typing import Callable
from gpt4allj import Model
from gpt4all_api.backend import GPTBackend
import yaml
__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=f"./models/llama_cpp/{self.config['model']}", avx2 = self.config["use_avx2"]
)
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()
for tok in self.model.generate(
prompt,
seed=self.config['seed'],
n_threads=self.config['n_threads'],
n_predict=n_predict,
top_k=self.config['top_k'],
top_p=self.config['top_p'],
temp=self.config['temperature'],
repeat_penalty=self.config['repeat_penalty'],
repeat_last_n=self.config['repeat_last_n'],
n_batch=8,
reset=True,
):
if not new_text_callback(tok):
return
except Exception as ex:
print(ex)
@staticmethod
def get_available_models():
# Create the file path relative to the child class's directory
backend_path = Path(__file__).parent
file_path = backend_path/"models.yaml"
with open(file_path, 'r') as file:
yaml_data = yaml.safe_load(file)
return yaml_data