Spaces:
Sleeping
Sleeping
File size: 2,151 Bytes
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import re
from typing import List, Optional, Union
from pydantic import BaseModel, Field
from pydantic_settings import BaseSettings
from api_types import ChatMessage
def parse_think_response(full_response: str):
think_start = full_response.find("<think")
if think_start == -1:
return None, full_response.strip()
think_end = full_response.find("</think>")
if think_end == -1: # 未闭合的情况
reasoning = full_response[think_start:].strip()
content = ""
else:
reasoning = full_response[think_start : think_end + 9].strip() # +9包含完整标签
content = full_response[think_end + 9 :].strip()
# 清理标签保留内容
reasoning_content = reasoning.replace("<think", "").replace("</think>", "").strip()
return reasoning_content, content
def cleanMessages(messages: List[ChatMessage], removeThinkingContent: bool = False):
promptStrList = []
for message in messages:
content = message.content.strip()
content = re.sub(r"\n+", "\n", content)
promptStrList.append(
f"{message.role.strip().lower().capitalize()}: {content if message.role!='Assistant' or not removeThinkingContent else remove_nested_think_tags_stack(content)}"
)
return "\n\n".join(promptStrList)
def remove_nested_think_tags_stack(text):
stack = []
result = ""
i = 0
while i < len(text):
if text[i : i + 7] == "<think>":
stack.append("<think>")
i += 7
elif text[i : i + 8] == "</think>":
if stack and stack[-1] == "<think>":
stack.pop()
i += 8
else:
result += text[i : i + 8]
i += 8
elif not stack:
result += text[i]
i += 1
else:
i += 1
return result
def format_bytes(size):
power = 2**10
n = 0
power_labels = {0: "", 1: "K", 2: "M", 3: "G", 4: "T"}
while size > power:
size /= power
n += 1
return f"{size:.4f}{power_labels[n]+'B'}"
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