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1d9c77522a
- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
275 lines
9.3 KiB
Python
275 lines
9.3 KiB
Python
"""
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Claude Token计数插件
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专门为Claude模型设计的Token计数器
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"""
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from __future__ import annotations
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import json
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import re
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from typing import Any
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from .base import TokenCounterPlugin
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_CJK_PATTERN = re.compile(r"[\u4e00-\u9fff\u3040-\u30ff\uac00-\ud7af]")
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class ClaudeTokenCounterPlugin(TokenCounterPlugin):
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"""
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Claude专用Token计数插件
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使用简化的估算方法
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"""
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# Claude模型信息
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CLAUDE_MODELS = {
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"claude-3-5-sonnet-20241022": {
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"max_tokens": 200000,
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"max_output": 8192,
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"chars_per_token": 3.5, # 平均字符/token比例
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},
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"claude-3-5-haiku-20241022": {
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"max_tokens": 200000,
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"max_output": 8192,
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"chars_per_token": 3.5,
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},
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"claude-3-opus-20240229": {
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"max_tokens": 200000,
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"max_output": 4096,
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"chars_per_token": 3.5,
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},
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"claude-3-sonnet-20240229": {
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"max_tokens": 200000,
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"max_output": 4096,
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"chars_per_token": 3.5,
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},
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"claude-3-haiku-20240307": {
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"max_tokens": 200000,
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"max_output": 4096,
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"chars_per_token": 3.5,
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},
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# 旧版模型
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"claude-2.1": {
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"max_tokens": 100000,
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"max_output": 4096,
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"chars_per_token": 4,
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},
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"claude-2.0": {
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"max_tokens": 100000,
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"max_output": 4096,
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"chars_per_token": 4,
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},
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"claude-instant-1.2": {
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"max_tokens": 100000,
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"max_output": 4096,
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"chars_per_token": 4,
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},
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}
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def __init__(self, name: str = "claude", config: dict[str, Any] | None = None):
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super().__init__(name, config)
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# 价格表（每1M tokens的价格 USD）
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default_pricing = {
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"claude-3-5-sonnet": {
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"input": 3,
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"output": 15,
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"cache_write": 3.75, # 缓存写入
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"cache_read": 0.30, # 缓存读取
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},
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"claude-3-5-haiku": {
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"input": 0.8,
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"output": 4,
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"cache_write": 1,
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"cache_read": 0.08,
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},
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"claude-3-opus": {
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"input": 15,
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"output": 75,
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"cache_write": 18.75,
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"cache_read": 1.50,
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},
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"claude-3-sonnet": {
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"input": 3,
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"output": 15,
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"cache_write": 3.75,
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"cache_read": 0.30,
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},
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"claude-3-haiku": {
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"input": 0.25,
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"output": 1.25,
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"cache_write": 0.30,
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"cache_read": 0.03,
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},
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"claude-2.1": {
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"input": 8,
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"output": 24,
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},
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"claude-2.0": {
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"input": 8,
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"output": 24,
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},
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"claude-instant": {
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"input": 0.8,
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"output": 2.4,
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},
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}
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self.config["pricing"] = (
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config.get("pricing", default_pricing) if config else default_pricing
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)
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def supports_model(self, model: str) -> bool:
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"""检查是否支持指定模型"""
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# 支持所有Claude模型
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return "claude" in model.lower()
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def _estimate_tokens_from_text(self, text: str, model: str) -> int:
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"""从文本估算Token数量"""
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# 获取模型信息
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model_info = None
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for model_name, info in self.CLAUDE_MODELS.items():
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if model.startswith(model_name.split("-20")[0]): # 匹配基本名称
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model_info = info
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break
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if not model_info:
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# 默认值
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model_info = {"chars_per_token": 3.5}
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# 基本估算
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chars_per_token = model_info["chars_per_token"]
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# 考虑不同语言的特点
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# 检测是否包含中文/日文/韩文
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cjk_count = len(_CJK_PATTERN.findall(text))
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if cjk_count > len(text) * 0.3: # 超过30%是CJK字符
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# CJK字符通常每个字符1-2个token
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return int(len(text) / 1.5)
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else:
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# 英文和其他语言
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# 考虑空格和标点
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word_count = len(text.split())
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# 平均每个单词1.3个token
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token_by_words = int(word_count * 1.3)
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# 平均每个字符chars_per_token
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token_by_chars = int(len(text) / chars_per_token)
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# 取两者的平均
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return (token_by_words + token_by_chars) // 2
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async def count_tokens(self, text: str, model: str | None = None) -> int:
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"""计算文本的Token数量"""
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if not self.enabled:
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return 0
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model = model or self.default_model or "claude-3-5-sonnet-20241022"
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return self._estimate_tokens_from_text(text, model)
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async def count_messages(self, messages: list[dict[str, Any]], model: str | None = None) -> int:
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"""计算消息列表的Token数量"""
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if not self.enabled:
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return 0
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model = model or self.default_model or "claude-3-5-sonnet-20241022"
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total_tokens = 0
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for message in messages:
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# 角色token（约3 tokens）
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total_tokens += 3
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# 内容token
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content = message.get("content")
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if content:
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if isinstance(content, str):
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total_tokens += self._estimate_tokens_from_text(content, model)
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elif isinstance(content, list):
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# 处理多模态内容
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for item in content:
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if item.get("type") == "text":
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text = item.get("text", "")
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total_tokens += self._estimate_tokens_from_text(text, model)
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elif item.get("type") == "image":
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# Claude图像处理
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# 基础: 1,600 tokens
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# 每个256x256的tile: 280 tokens
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# 简化估算
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total_tokens += 2000 # 平均估算
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elif item.get("type") == "tool_use":
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# 工具使用
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tool_name = item.get("name", "")
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tool_input = item.get("input", {})
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total_tokens += self._estimate_tokens_from_text(tool_name, model)
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total_tokens += self._estimate_tokens_from_text(
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json.dumps(tool_input), model
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)
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elif item.get("type") == "tool_result":
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# 工具结果
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tool_content = item.get("content", "")
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if isinstance(tool_content, str):
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total_tokens += self._estimate_tokens_from_text(tool_content, model)
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# 添加系统提示的token（如果有）
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if messages and messages[0].get("role") == "system":
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# 系统提示通常会有额外的开销
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total_tokens += 10
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return total_tokens
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async def count_request(self, request: dict[str, Any], model: str | None = None) -> int:
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"""计算请求的Token数量"""
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model = model or request.get("model") or self.default_model
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messages = request.get("messages", [])
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total = await self.count_messages(messages, model)
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# 考虑系统提示
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system = request.get("system")
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if system:
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total += self._estimate_tokens_from_text(system, model)
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total += 5 # 系统提示的额外开销
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return total
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async def get_model_info(self, model: str) -> dict[str, Any]:
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"""获取模型信息"""
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info = {"model": model, "supported": self.supports_model(model)}
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if self.supports_model(model):
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# 查找匹配的模型信息
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model_info = None
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for model_name, m_info in self.CLAUDE_MODELS.items():
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if model.startswith(model_name.split("-20")[0]):
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model_info = m_info
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info["model_name"] = model_name
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break
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if model_info:
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info.update(
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{
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"max_tokens": model_info["max_tokens"],
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"max_output": model_info["max_output"],
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"chars_per_token": model_info["chars_per_token"],
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"supports_vision": "claude-3" in model,
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"supports_tools": "claude-3" in model,
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"supports_cache": "claude-3" in model,
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}
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)
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# 添加价格信息
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pricing = self.config.get("pricing", {})
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for price_key in pricing:
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if model.startswith(price_key):
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info["pricing"] = pricing[price_key]
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break
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return info
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async def get_stats(self) -> dict[str, Any]:
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"""获取统计信息"""
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stats = await super().get_stats()
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stats.update(
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{
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"estimation_method": "character_based",
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"supported_models_count": len(self.CLAUDE_MODELS),
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}
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)
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return stats
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