import dataclasses from enum import auto, Enum from typing import List, Tuple class SeparatorStyle(Enum): """Different separator style.""" SINGLE = auto() TWO = auto() MPT = auto() PLAIN = auto() LLAMA_2 = auto() @dataclasses.dataclass class Conversation: """A class that keeps all conversation history.""" system: str roles: List[str] messages: List[List[str]] offset: int sep_style: SeparatorStyle = SeparatorStyle.SINGLE sep: str = "###" sep2: str = None version: str = "Unknown" skip_next: bool = False def get_prompt(self): messages = self.messages if len(messages) > 0 and type(messages[0][1]) is tuple: messages = self.messages.copy() init_role, init_msg = messages[0].copy() init_msg = init_msg[0].replace("", "").strip() if 'mmtag' in self.version: messages[0] = (init_role, init_msg) messages.insert(0, (self.roles[0], "")) messages.insert(1, (self.roles[1], "Received.")) else: messages[0] = (init_role, "\n" + init_msg) if self.sep_style == SeparatorStyle.SINGLE: ret = self.system + self.sep for role, message in messages: if message: if type(message) is tuple: message, _, _ = message ret += role + ": " + message + self.sep else: ret += role + ":" elif self.sep_style == SeparatorStyle.TWO: seps = [self.sep, self.sep2] ret = self.system + seps[0] for i, (role, message) in enumerate(messages): if message: if type(message) is tuple: message, _, _ = message ret += role + ": " + message + seps[i % 2] else: ret += role + ":" elif self.sep_style == SeparatorStyle.PLAIN: seps = [self.sep, self.sep2] ret = self.system for i, (role, message) in enumerate(messages): if message: if type(message) is tuple: message, _, _ = message ret += message + seps[i % 2] else: ret += "" else: raise ValueError(f"Invalid style: {self.sep_style}") return ret def append_message(self, role, message): self.messages.append([role, message]) def get_images(self, return_pil=False): images = [] for i, (role, msg) in enumerate(self.messages[self.offset:]): if i % 2 == 0: if type(msg) is tuple: import base64 from io import BytesIO from PIL import Image msg, image, image_process_mode = msg if image_process_mode == "Pad": def expand2square(pil_img, background_color=(122, 116, 104)): width, height = pil_img.size if width == height: return pil_img elif width > height: result = Image.new(pil_img.mode, (width, width), background_color) result.paste(pil_img, (0, (width - height) // 2)) return result else: result = Image.new(pil_img.mode, (height, height), background_color) result.paste(pil_img, ((height - width) // 2, 0)) return result image = expand2square(image) elif image_process_mode in ["Default", "Crop"]: pass elif image_process_mode == "Resize": image = image.resize((336, 336)) else: raise ValueError(f"Invalid image_process_mode: {image_process_mode}") max_hw, min_hw = max(image.size), min(image.size) aspect_ratio = max_hw / min_hw max_len, min_len = 800, 400 shortest_edge = int(min(max_len / aspect_ratio, min_len, min_hw)) longest_edge = int(shortest_edge * aspect_ratio) W, H = image.size if longest_edge != max(image.size): if H > W: H, W = longest_edge, shortest_edge else: H, W = shortest_edge, longest_edge image = image.resize((W, H)) if return_pil: images.append(image) else: buffered = BytesIO() image.save(buffered, format="PNG") img_b64_str = base64.b64encode(buffered.getvalue()).decode() images.append(img_b64_str) return images def to_gradio_chatbot(self): ret = [] for i, (role, msg) in enumerate(self.messages[self.offset:]): if i % 2 == 0: if type(msg) is tuple: import base64 from io import BytesIO msg, image, image_process_mode = msg max_hw, min_hw = max(image.size), min(image.size) aspect_ratio = max_hw / min_hw max_len, min_len = 800, 400 shortest_edge = int(min(max_len / aspect_ratio, min_len, min_hw)) longest_edge = int(shortest_edge * aspect_ratio) W, H = image.size if H > W: H, W = longest_edge, shortest_edge else: H, W = shortest_edge, longest_edge image = image.resize((W, H)) buffered = BytesIO() image.save(buffered, format="JPEG") img_b64_str = base64.b64encode(buffered.getvalue()).decode() img_str = f'user upload image' msg = img_str + msg.replace('', '').strip() ret.append([msg, None]) else: ret.append([msg, None]) else: ret[-1][-1] = msg return ret def copy(self): return Conversation( system=self.system, 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, version=self.version) def dict(self): if len(self.get_images()) > 0: return { "system": self.system, "roles": self.roles, "messages": [[x, y[0] if type(y) is tuple else y] for x, y in self.messages], "offset": self.offset, "sep": self.sep, "sep2": self.sep2, } return { "system": self.system, "roles": self.roles, "messages": self.messages, "offset": self.offset, "sep": self.sep, "sep2": self.sep2, } conv_phi_v0 = Conversation( system="A chat between a curious user and an artificial intelligence assistant. " "The assistant gives helpful, detailed, and polite answers to the user's questions.", roles=("USER", "ASSISTANT"), version="v0", messages=(), offset=0, sep_style=SeparatorStyle.TWO, sep=" ", sep2="<|endoftext|>", ) conv_llava_plain = Conversation( system="", roles=("", ""), messages=( ), offset=0, sep_style=SeparatorStyle.PLAIN, sep="\n", ) default_conversation = conv_phi_v0 conv_templates = { "default": conv_phi_v0, "v0": conv_phi_v0, "phi-2_v0": conv_phi_v0, "plain": conv_llava_plain, } if __name__ == "__main__": print(default_conversation.get_prompt())