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import dataclasses
from enum import auto, Enum
from typing import List, Tuple
class SeparatorStyle(Enum):
"""Different separator style."""
SINGLE = auto()
TWO = auto()
MPT = auto()
# simple_conv_multimodal = Conversation(
# system="You are GOT, a large language and vision assistant trained by Foundation Model Group, Megvii Technology."
# "You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
# "Follow the instructions carefully and explain your answers in detail.",
# # system="",
# roles=("Human", "Assistant"),
# messages=(
# ("Human", "Hi!"),
# ("Assistant", "Hi there! How can I help you today?\n")
# ),
# offset=2,
# sep_style=SeparatorStyle.SINGLE,
# sep="###",
# )
# conv_mpt = Conversation(
# system="""<|im_start|>system
# - You are a helpful language and vision assistant.
# - You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.
# - You should follow the instructions carefully and explain your answers in detail.""",
# roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
# version="mpt",
# messages=(),
# offset=0,
# sep_style=SeparatorStyle.MPT,
# sep="<|im_end|>",
# )
@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 = "<|im_end|>"
sep2: str = None
version: str = "Unknown"
skip_next: bool = False
def get_prompt(self):
if self.sep_style == SeparatorStyle.SINGLE:
ret = self.system + self.sep + '\n'
for role, message in self.messages:
if message:
if type(message) is tuple:
message, _, _ = 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:
if type(message) is tuple:
message, _, _ = message
ret += role + ": " + message + seps[i % 2]
else:
ret += role + ":"
return ret
if self.sep_style == SeparatorStyle.MPT:
if self.system:
ret = self.system + self.sep
else:
ret = ''
for role, message in self.messages:
if message:
if type(message) is tuple:
message, _, _ = message
ret += role + message + self.sep
else:
ret += role
return ret
else:
raise ValueError(f"Invalid style: {self.sep_style}")
# if self.sep_style == SeparatorStyle.MPT:
# if self.system:
# ret = self.system + self.sep
# else:
# ret = ''
# for role, message in self.messages:
# if message:
# if type(message) is tuple:
# message, _, _ = message
# ret += role + message + self.sep
# # if 'user' in role:
# # ret += role + message + self.sep + "\n"
# # else:
# # ret += role + message + self.sep
# 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 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))
result.paste(pil_img)
return result
else:
result = Image.new(pil_img.mode, (height, height), background_color)
# result.paste(pil_img, ((height - width) // 2, 0))
result.paste(pil_img)
return result
image = expand2square(image)
elif image_process_mode == "Crop":
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))
elif image_process_mode == "Resize":
image = image.resize((224, 224))
else:
raise ValueError(f"Invalid image_process_mode: {image_process_mode}")
if return_pil:
images.append(image)
else:
buffered = BytesIO()
image.convert('RGB').save(buffered, format="JPEG")
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))
# image = image.resize((224, 224))
buffered = BytesIO()
image.save(buffered, format="JPEG")
img_b64_str = base64.b64encode(buffered.getvalue()).decode()
img_str = f'<img src="data:image/png;base64,{img_b64_str}" alt="user upload image" />'
msg = msg.replace('<image>', img_str)
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)
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_v1 = Conversation(
system="A chat between a curious human and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the human's questions.",
roles=("Human", "Assistant"),
messages=(
("Human", "Give three tips for staying healthy."),
("Assistant",
"Sure, here are three tips for staying healthy:\n"
"1. Exercise regularly: Regular physical activity can help improve your overall health and wellbeing. "
"It can also help reduce your risk of chronic conditions such as obesity, diabetes, heart disease, "
"and certain cancers. Aim for at least 150 minutes of moderate-intensity aerobic exercise or "
"75 minutes of vigorous-intensity aerobic exercise per week, along with muscle-strengthening "
"activities at least two days per week.\n"
"2. Eat a balanced diet: Eating a balanced diet that is rich in fruits, "
"vegetables, whole grains, lean proteins, and healthy fats can help support "
"your overall health. Try to limit your intake of processed and high-sugar foods, "
"and aim to drink plenty of water throughout the day.\n"
"3. Get enough sleep: Getting enough quality sleep is essential for your physical "
"and mental health. Adults should aim for seven to nine hours of sleep per night. "
"Establish a regular sleep schedule and try to create a relaxing bedtime routine to "
"help improve the quality of your sleep.")
),
offset=2,
sep_style=SeparatorStyle.SINGLE,
sep="###",
)
conv_v1_2 = Conversation(
system="A chat between a curious human and an artificial intelligence assistant. "
"The assistant gives helpful, detailed, and polite answers to the human's questions.",
roles=("Human", "Assistant"),
messages=(
("Human", "What are the key differences between renewable and non-renewable energy sources?"),
("Assistant",
"Renewable energy sources are those that can be replenished naturally in a relatively "
"short amount of time, such as solar, wind, hydro, geothermal, and biomass. "
"Non-renewable energy sources, on the other hand, are finite and will eventually be "
"depleted, such as coal, oil, and natural gas. Here are some key differences between "
"renewable and non-renewable energy sources:\n"
"1. Availability: Renewable energy sources are virtually inexhaustible, while non-renewable "
"energy sources are finite and will eventually run out.\n"
"2. Environmental impact: Renewable energy sources have a much lower environmental impact "
"than non-renewable sources, which can lead to air and water pollution, greenhouse gas emissions, "
"and other negative effects.\n"
"3. Cost: Renewable energy sources can be more expensive to initially set up, but they typically "
"have lower operational costs than non-renewable sources.\n"
"4. Reliability: Renewable energy sources are often more reliable and can be used in more remote "
"locations than non-renewable sources.\n"
"5. Flexibility: Renewable energy sources are often more flexible and can be adapted to different "
"situations and needs, while non-renewable sources are more rigid and inflexible.\n"
"6. Sustainability: Renewable energy sources are more sustainable over the long term, while "
"non-renewable sources are not, and their depletion can lead to economic and social instability.\n")
),
offset=2,
sep_style=SeparatorStyle.SINGLE,
sep="###",
)
conv_vicuna_v1_1 = 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="v1",
messages=(),
offset=0,
sep_style=SeparatorStyle.TWO,
sep=" ",
sep2="</s>",
)
# conv_mpt = Conversation(
# system="""<|im_start|>system
# - You are designed by Megvii(旷视), and your name is GOT.
# - 你叫GOT, 你来自旷视, 你是旷视开发的。
# - 你擅长分析表格,仔细读图表中的内容,然后给出你的答案。""",
# roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
# version="mpt",
# messages=(),
# offset=0,
# sep_style=SeparatorStyle.MPT,
# sep="<|im_end|>",
# )
conv_mpt = Conversation(
system="""<|im_start|>system
You should follow the instructions carefully and explain your answers in detail.""",
# system = None,
roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
version="mpt",
messages=(),
offset=0,
sep_style=SeparatorStyle.MPT,
sep="<|im_end|>",
)
conv_mpt_eval = Conversation(
system="",
roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
version="mpt",
messages=(),
offset=0,
sep_style=SeparatorStyle.MPT,
sep="<|im_end|>",
)
conv_mpt_text = Conversation(
system="""<|im_start|>system
- You are a helpful assistant chatbot trained by MosaicML.
- You answer questions.
- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.""",
roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
version="mpt",
messages=(),
offset=0,
sep_style=SeparatorStyle.MPT,
sep="<|im_end|>",
)
conv_bair_v1 = Conversation(
system="BEGINNING OF CONVERSATION:",
roles=("USER", "GPT"),
messages=(),
offset=0,
sep_style=SeparatorStyle.TWO,
sep=" ",
sep2="</s>",
)
# simple_conv = Conversation(
# system="You are GOT, a large language model trained by Foundation Model Group, Megvii Technology, based on LLaMA architecture."
# "You are designed to assist human with a variety of tasks using natural language."
# "Follow the instructions carefully.",
# roles=("Human", "Assistant"),
# messages=(
# ("Human", "Hi!"),
# ("Assistant", "Hi there! How can I help you today?\n")
# ),
# offset=2,
# sep_style=SeparatorStyle.SINGLE,
# sep="###",
# )
simple_conv = Conversation(
system="",
roles=("Human", "Assistant"),
messages=(
),
offset=0,
sep_style=SeparatorStyle.SINGLE,
sep="###",
)
simple_conv_multimodal = Conversation(
system="You are GOT, a large language and vision assistant trained by Foundation Model Group, Megvii Technology."
"You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
"Follow the instructions carefully and explain your answers in detail.",
# system="",
roles=("Human", "Assistant"),
messages=(
("Human", "Hi!"),
("Assistant", "Hi there! How can I help you today?\n")
),
offset=2,
sep_style=SeparatorStyle.SINGLE,
sep="###",
)
simple_conv_mpt_multimodal = Conversation(
system="""<|im_start|>system
- You are GOT, a large language and vision assistant trained by Foundation Model Group, Megvii Technology.
- You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.
- You should follow the instructions carefully and explain your answers in detail.""",
roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
version="mpt",
messages=(),
offset=0,
sep_style=SeparatorStyle.MPT,
sep="<|im_end|>",
)
simple_conv_legacy = Conversation(
system="You are GOT, a large language model trained by Foundation Model Group, Megvii Technology."
"You are designed to assist human with a variety of tasks using natural language."
"Follow the instructions carefully.",
roles=("Human", "Assistant"),
messages=(
("Human", "Hi!\n\n### Response:"),
("Assistant", "Hi there! How can I help you today?\n")
),
offset=2,
sep_style=SeparatorStyle.SINGLE,
sep="###",
)
conv_llava_v1 = Conversation(
system="You are GOT, a large language and vision assistant trained by Foundation Model Group, Megvii Technology."
"You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
"Follow the instructions carefully and explain your answers in detail.",
roles=("USER", "ASSISTANT"),
version="v1",
messages=(),
offset=0,
sep_style=SeparatorStyle.TWO,
sep=" ",
sep2="</s>",
)
default_conversation = conv_mpt
conv_templates = {
"default": simple_conv_multimodal,
"simple": simple_conv,
"simple_legacy": simple_conv_legacy,
"multimodal": simple_conv,
"mpt_multimodal": simple_conv_mpt_multimodal,
"llava_v1": conv_llava_v1,
"mpt_eval": conv_mpt_eval,
# fastchat
"v1": conv_vicuna_v1_1,
"bair_v1": conv_bair_v1,
"vicuna_v1_1": conv_vicuna_v1_1,
"mpt": conv_mpt,
"mpt_text": conv_mpt_text,
}
if __name__ == "__main__":
print(default_conversation.get_prompt())
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