mirror of
https://github.com/ParisNeo/lollms-webui.git
synced 2024-12-19 12:27:52 +00:00
126 lines
4.3 KiB
Python
126 lines
4.3 KiB
Python
######
|
|
# 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 marella's binding
|
|
# Follow him on his github project : https://github.com/marella/ctransformers
|
|
|
|
######
|
|
from pathlib import Path
|
|
from typing import Callable
|
|
from api.binding import LLMBinding
|
|
from api.config import load_config
|
|
import yaml
|
|
import re
|
|
|
|
__author__ = "parisneo"
|
|
__github__ = "https://github.com/nomic-ai/gpt4all-ui"
|
|
__copyright__ = "Copyright 2023, "
|
|
__license__ = "Apache 2.0"
|
|
|
|
binding_name = "CustomBinding"
|
|
|
|
class CustomBinding(LLMBinding):
|
|
# Define what is the extension of the model files supported by your binding
|
|
# Only applicable for local models for remote models like gpt4 and others, you can keep it empty
|
|
# and reimplement your own list_models method
|
|
file_extension='*.bin'
|
|
def __init__(self, config:dict) -> None:
|
|
"""Builds a LLAMACPP binding
|
|
|
|
Args:
|
|
config (dict): The configuration file
|
|
"""
|
|
super().__init__(config, False)
|
|
|
|
# The local config can be used to store personal information that shouldn't be shared like chatgpt Key
|
|
# or other personal information
|
|
# This file is never commited to the repository as it is ignored by .gitignore
|
|
self._local_config_file_path = Path(__file__).parent/"config_local.yaml"
|
|
self.config = load_config(self._local_config_file_path)
|
|
|
|
# Do your initialization stuff
|
|
|
|
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 self.model.tokenize(prompt.encode())
|
|
|
|
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 self.model.detokenize(tokens_list)
|
|
|
|
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:
|
|
output = ""
|
|
self.model.reset()
|
|
tokens = self.model.tokenize(prompt)
|
|
count = 0
|
|
generated_text = """
|
|
This is an empty binding that shows how you can build your own binding.
|
|
Find it in bindings
|
|
"""
|
|
for tok in re.split(r' |\n', generated_text):
|
|
if count >= n_predict or self.model.is_eos_token(tok):
|
|
break
|
|
word = self.model.detokenize(tok)
|
|
if new_text_callback is not None:
|
|
if not new_text_callback(word):
|
|
break
|
|
output += word
|
|
count += 1
|
|
except Exception as ex:
|
|
print(ex)
|
|
return output
|
|
|
|
|
|
@staticmethod
|
|
def list_models(config:dict):
|
|
"""Lists the models for this binding
|
|
"""
|
|
return ["ChatGpt by Open AI"]
|
|
|
|
@staticmethod
|
|
def get_available_models():
|
|
# Create the file path relative to the child class's directory
|
|
binding_path = Path(__file__).parent
|
|
file_path = binding_path/"models.yaml"
|
|
|
|
with open(file_path, 'r') as file:
|
|
yaml_data = yaml.safe_load(file)
|
|
|
|
return yaml_data |