import asyncio import os, tempfile import logging import json import requests from transformers import AutoTokenizer, AutoConfig from huggingface_hub import hf_hub_download import io import base64 from PIL import Image, PngImagePlugin logger = logging.getLogger(__name__) async def get_full_prompt(simple_prompt: str, bot, chat_history): # https://github.com/ggerganov/llama.cpp/tree/master/examples # prompt = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n" prompt = "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n" #"BEGINNING OF CONVERSATION:" prompt += "### Human: " + simple_prompt + "\n" prompt += "### Assistant:" prompt = f"This is a transcript of a 1000 page, never ending conversation between {bot.user_name} and the cute and helpful AI assistant {bot.name}. {bot.name} is a girl who is an AI running on the users computer.\n" prompt += f"{bot.name} can think for herself without the user seeing her thoughts by adding a /think prefix to her output. She uses this to reason about the world and to think about what she should say next.\n" prompt += f"{bot.name} is always coherent and makes sense, but if she isn't sure if what she is saying is correct she will ask the user for help.\n" prompt += f"{bot.name} is a very helpful AI and will help the user with anything they need, she is also very friendly and will try to make the user feel better if they are sad.\n" prompt += f"{bot.name} is also very curious and will ask the user a lot of questions about themselves and their life, she will also try to make the user like her.\n" prompt += f"\n" prompt += f"{bot.user_name}: " + simple_prompt + "\n" prompt += f"{bot.name}:" return prompt async def num_tokens(input_text: str): return estimate_num_tokens(input_text) async def estimate_num_tokens(input_text: str): return len(input_text)//4+1