import argparse import time from PIL import Image import torch from transformers import AutoTokenizer, AutoModelForCausalLM, LlamaTokenizer from transformers import StoppingCriteria, StoppingCriteriaList import dataclasses from enum import auto, Enum from typing import List, Tuple, Any from minigpt4.common.registry import registry class SeparatorStyle(Enum): """Different separator style.""" SINGLE = auto() TWO = auto() @dataclasses.dataclass class Conversation: """A class that keeps all conversation history.""" system: str roles: List[str] messages: List[List[str]] offset: int # system_img: List[Image.Image] = [] sep_style: SeparatorStyle = SeparatorStyle.SINGLE sep: str = "###" sep2: str = None skip_next: bool = False conv_id: Any = None def get_prompt(self): if self.sep_style == SeparatorStyle.SINGLE: ret = self.system + self.sep for role, message in self.messages: if message: ret += role + ": " + message + self.sep else: ret += role + ":" return ret elif self.sep_style == SeparatorStyle.TWO: seps = [self.sep, self.sep2] ret = self.system + seps[0] for i, (role, message) in enumerate(self.messages): if message: ret += role + ": " + message + seps[i % 2] else: ret += role + ":" return ret else: raise ValueError(f"Invalid style: {self.sep_style}") def append_message(self, role, message): self.messages.append([role, message]) def to_gradio_chatbot(self): ret = [] for i, (role, msg) in enumerate(self.messages[self.offset:]): if i % 2 == 0: ret.append([msg, None]) else: ret[-1][-1] = msg return ret def copy(self): return Conversation( system=self.system, # system_img=self.system_img, roles=self.roles, messages=[[x, y] for x, y in self.messages], offset=self.offset, sep_style=self.sep_style, sep=self.sep, sep2=self.sep2, conv_id=self.conv_id) def dict(self): return { "system": self.system, # "system_img": self.system_img, "roles": self.roles, "messages": self.messages, "offset": self.offset