mirror of
https://github.com/ParisNeo/lollms-webui.git
synced 2025-01-27 22:59:41 +00:00
123 lines
4.3 KiB
Python
123 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 open ai's api
|
|
|
|
######
|
|
from pathlib import Path
|
|
from typing import Callable
|
|
from api.binding import LLMBinding
|
|
from api.config import load_config
|
|
import openai
|
|
import yaml
|
|
import re
|
|
|
|
__author__ = "parisneo"
|
|
__github__ = "https://github.com/ParisNeo/gpt4all-ui"
|
|
__copyright__ = "Copyright 2023, "
|
|
__license__ = "Apache 2.0"
|
|
|
|
binding_name = "OpenAIGPT"
|
|
|
|
class OpenAIGPT(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 OpenAIGPT 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.config = config
|
|
self._local_config_file_path = Path(__file__).parent/"config_local.yaml"
|
|
self.local_config = load_config(self._local_config_file_path)
|
|
openai.api_key = self.local_config["openai_key"]
|
|
|
|
# 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 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:
|
|
response = openai.Completion.create(
|
|
engine=self.config["model"], # Choose the engine according to your OpenAI plan
|
|
prompt=prompt,
|
|
max_tokens=n_predict, # Adjust the desired length of the generated response
|
|
n=1, # Specify the number of responses you want
|
|
stop=None, # Define a stop sequence if needed
|
|
temperature=gpt_params["temp"] # Adjust the temperature for more or less randomness in the output
|
|
)
|
|
|
|
# Extract the generated reply from the API response
|
|
reply = response.choices[0].text.strip()
|
|
return reply
|
|
except Exception as ex:
|
|
print(ex)
|
|
return ""
|
|
|
|
|
|
@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 |