lollms-webui/api/backend.py
2023-05-25 12:51:31 +02:00

88 lines
2.7 KiB
Python

######
# Project : GPT4ALL-UI
# File : backend.py
# Author : ParisNeo with the help of the community
# Supported by Nomic-AI
# license : Apache 2.0
# Description :
# This is an interface class for GPT4All-ui backends.
######
from pathlib import Path
from typing import Callable
import inspect
import yaml
import sys
__author__ = "parisneo"
__github__ = "https://github.com/nomic-ai/gpt4all-ui"
__copyright__ = "Copyright 2023, "
__license__ = "Apache 2.0"
class LLMBackend:
file_extension='*.bin'
backend_path = Path(__file__).parent
def __init__(self, config:dict, inline:bool) -> None:
self.config = config
self.inline = inline
def generate(self,
prompt:str,
n_predict: int = 128,
new_text_callback: Callable[[str], None] = None,
verbose: bool = False,
**gpt_params ):
"""Generates text out of a prompt
This should ber implemented by child class
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.
"""
pass
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.
"""
pass
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.
"""
pass
@staticmethod
def list_models(config:dict):
"""Lists the models for this backend
"""
models_dir = Path('./models')/config["backend"] # replace with the actual path to the models folder
return [f.name for f in models_dir.glob(LLMBackend.file_extension)]
@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