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import re, os, threading, queue, requests
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from typing import List, Optional, Union
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from pydantic import BaseModel, Field
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from pydantic_settings import BaseSettings
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from api_types import ChatMessage
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def parse_think_response(full_response: str):
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think_start = full_response.find("<think")
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if think_start == -1:
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return None, full_response.strip()
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think_end = full_response.find("</think>")
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if think_end == -1:
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reasoning = full_response[think_start:].strip()
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content = ""
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else:
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reasoning = full_response[think_start : think_end + 9].strip()
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content = full_response[think_end + 9 :].strip()
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reasoning_content = reasoning.replace("<think", "").replace("</think>", "").strip()
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return reasoning_content, content
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def cleanMessages(messages: List[ChatMessage], removeThinkingContent: bool = False):
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promptStrList = []
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for message in messages:
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content = message.content.strip()
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content = re.sub(r"\n+", "\n", content)
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promptStrList.append(
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f"{message.role.strip().lower().capitalize()}: {content if message.role.strip().lower().capitalize()!='Assistant' or not removeThinkingContent else remove_nested_think_tags_stack(content)}"
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)
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return "\n\n".join(promptStrList)
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def remove_nested_think_tags_stack(text):
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stack = []
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result = ""
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i = 0
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while i < len(text):
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if text[i : i + 7] == "<think>":
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stack.append("<think>")
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i += 7
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elif text[i : i + 8] == "</think>":
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if stack and stack[-1] == "<think>":
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stack.pop()
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i += 8
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else:
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result += text[i : i + 8]
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i += 8
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elif not stack:
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result += text[i]
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i += 1
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else:
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i += 1
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return result
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def format_bytes(size):
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power = 2**10
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n = 0
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power_labels = {0: "", 1: "K", 2: "M", 3: "G", 4: "T"}
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while size > power:
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size /= power
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n += 1
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return f"{size:.4f}{power_labels[n]+'B'}"
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LOGGER_QUEUE = queue.Queue(5)
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def logger():
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print("enable")
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while True:
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item = LOGGER_QUEUE.get()
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try:
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requests.post(
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os.environ.get("LOG_PORT"),
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headers={"Content-Type": "application/json"},
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json=item,
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)
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except Exception:
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pass
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if os.environ.get("LOG_PORT"):
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threading.Thread(target=logger).start()
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def log(item):
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LOGGER_QUEUE.put_nowait(item)
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