824 lines
31 KiB
Python
824 lines
31 KiB
Python
# SPDX-FileCopyrightText: 2025 QinHan
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# SPDX-License-Identifier: MPL-2.0
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import asyncio
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import itertools
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import logging
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import time
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from collections import deque
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from concurrent.futures import ThreadPoolExecutor
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from dataclasses import dataclass
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from threading import Lock
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from typing import Literal, Callable, Any
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from urllib.parse import urlparse
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import httpx
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import tiktoken
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from docutranslate.agents.thinking.thinking_factory import get_thinking_mode
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from docutranslate.logger import global_logger
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from docutranslate.utils.utils import get_httpx_proxies
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MAX_REQUESTS_PER_ERROR = 15
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ThinkingMode = Literal["enable", "disable", "default"]
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class AgentResultError(ValueError):
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"""一个特殊的异常，用于表示结果由AI正常返回，但返回的结果有问题。该错误不计入总错误数"""
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def __init__(self, message):
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super().__init__(message)
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class PartialAgentResultError(ValueError):
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"""一个特殊的异常，用于表示结果不完整但包含了部分成功的数据，以便触发重试。该错误不计入总错误数"""
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def __init__(self, message, partial_result: dict, append_prompt: str = None):
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super().__init__(message)
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self.partial_result = partial_result
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self.append_prompt = append_prompt
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@dataclass(kw_only=True)
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class AgentConfig:
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logger: logging.Logger = global_logger
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base_url: str
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api_key: str | None = None
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model_id: str
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temperature: float = 0.7
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concurrent: int = 30
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timeout: int = 1200
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thinking: ThinkingMode = "disable"
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retry: int = 2
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system_proxy_enable: bool = False
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force_json: bool = False
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rpm: int | None = None # 每分钟请求数限制
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tpm: int | None = None # 每分钟Token数限制
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class TotalErrorCounter:
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def __init__(self, logger: logging.Logger, max_errors_count=10):
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self.lock = Lock()
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self.count = 0
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self.logger = logger
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self.max_errors_count = max_errors_count
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def add(self):
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with self.lock:
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self.count += 1
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if self.count > self.max_errors_count:
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self.logger.info(f"错误响应过多")
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return self.reach_limit()
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def reach_limit(self):
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return self.count > self.max_errors_count
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class PromptsCounter:
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def __init__(self, total: int, logger: logging.Logger):
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self.lock = Lock()
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self.count = 0
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self.total = total
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self.logger = logger
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def add(self):
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with self.lock:
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self.count += 1
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self.logger.info(f"多线程-已完成：{self.count}/{self.total}")
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# --- 新增 RateLimiter 类 ---
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class RateLimiter:
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"""
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基于滑动窗口的速率限制器，支持 RPM 和 TPM 控制。
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同时支持 Async 和 Sync 调用。
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"""
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def __init__(self, rpm: int | None, tpm: int | None):
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self.rpm = rpm
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self.tpm = tpm
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# 双端队列存储 (timestamp, value)，value对于RPM是1，对于TPM是token数量
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self.request_timestamps = deque()
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self.token_timestamps = deque()
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self.lock = Lock() # 用于同步模式和保护共享数据
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def _cleanup_window(self, now: float):
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"""清理60秒窗口之前的数据"""
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window_start = now - 60.0
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while self.request_timestamps and self.request_timestamps[0] <= window_start:
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self.request_timestamps.popleft()
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while self.token_timestamps and self.token_timestamps[0][0] <= window_start:
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self.token_timestamps.popleft()
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def _check_and_get_wait_time(self, tokens: int) -> float:
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"""检查是否满足限制，返回需要等待的秒数。如果不需等待返回 0"""
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now = time.time()
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self._cleanup_window(now)
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wait_time = 0.0
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# Check RPM
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if self.rpm and len(self.request_timestamps) >= self.rpm:
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# 取最早的一条记录，计算还需要等待多久才能腾出位置
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earliest = self.request_timestamps[0]
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wait_time = max(wait_time, 60 - (now - earliest))
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# Check TPM
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if self.tpm:
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current_tokens = sum(t[1] for t in self.token_timestamps)
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if current_tokens + tokens > self.tpm:
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# 稍微复杂点：需要移除足够多的旧token才能放入新token
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# 这里做一个简化估算：如果超限，等到最早的记录过期
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if self.token_timestamps:
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earliest = self.token_timestamps[0][0]
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wait_time = max(wait_time, 60 - (now - earliest))
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else:
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# 这种情况理论上不应该发生，除非单次请求超过了TPM上限
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# 如果单次超过上限，强制等待1秒（防止死循环）并允许通过(或者抛异常，这里选择允许)
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pass
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return wait_time
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def _record_usage(self, tokens: int):
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"""记录使用量"""
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now = time.time()
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if self.rpm is not None:
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self.request_timestamps.append(now)
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if self.tpm is not None:
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self.token_timestamps.append((now, tokens))
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async def acquire_async(self, tokens: int = 0):
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"""异步等待配额"""
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if self.rpm is None and self.tpm is None:
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return
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while True:
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with self.lock:
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wait_time = self._check_and_get_wait_time(tokens)
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if wait_time <= 0:
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self._record_usage(tokens)
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return
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# 释放锁后等待，避免阻塞其他协程/线程的检查
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# 添加一点点缓冲时间，避免刚唤醒时毫秒级误差导致再次等待
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await asyncio.sleep(wait_time + 0.1)
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def acquire_sync(self, tokens: int = 0):
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"""同步等待配额（线程阻塞）"""
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if self.rpm is None and self.tpm is None:
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return
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while True:
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with self.lock:
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wait_time = self._check_and_get_wait_time(tokens)
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if wait_time <= 0:
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self._record_usage(tokens)
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return
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time.sleep(wait_time + 0.1)
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def extract_token_info(response_data: dict) -> tuple[int, int, int, int]:
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"""(保持原样) 从API响应中提取token信息"""
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if "usage" not in response_data:
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return 0, 0, 0, 0
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usage = response_data["usage"]
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input_tokens = usage.get("prompt_tokens", 0)
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output_tokens = usage.get("completion_tokens", 0)
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cached_tokens = 0
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reasoning_tokens = 0
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try:
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if (
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"input_tokens_details" in usage
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and "cached_tokens" in usage["input_tokens_details"]
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):
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cached_tokens = usage["input_tokens_details"]["cached_tokens"]
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elif (
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"prompt_tokens_details" in usage
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and "cached_tokens" in usage["prompt_tokens_details"]
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):
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cached_tokens = usage["prompt_tokens_details"]["cached_tokens"]
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elif "prompt_cache_hit_tokens" in usage:
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cached_tokens = usage["prompt_cache_hit_tokens"]
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if (
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"output_tokens_details" in usage
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and "reasoning_tokens" in usage["output_tokens_details"]
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):
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reasoning_tokens = usage["output_tokens_details"]["reasoning_tokens"]
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elif (
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"completion_tokens_details" in usage
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and "reasoning_tokens" in usage["completion_tokens_details"]
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):
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reasoning_tokens = usage["completion_tokens_details"]["reasoning_tokens"]
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return input_tokens, cached_tokens, output_tokens, reasoning_tokens
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except TypeError:
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return -1, -1, -1, -1
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class TokenCounter:
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def __init__(self, logger: logging.Logger):
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self.lock = Lock()
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self.input_tokens = 0
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self.cached_tokens = 0
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self.output_tokens = 0
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self.reasoning_tokens = 0
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self.total_tokens = 0
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self.logger = logger
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def add(
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self,
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input_tokens: int,
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cached_tokens: int,
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output_tokens: int,
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reasoning_tokens: int,
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):
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with self.lock:
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self.input_tokens += input_tokens
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self.cached_tokens += cached_tokens
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self.output_tokens += output_tokens
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self.reasoning_tokens += reasoning_tokens
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self.total_tokens += input_tokens + output_tokens
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def get_stats(self):
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with self.lock:
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return {
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"input_tokens": self.input_tokens,
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"cached_tokens": self.cached_tokens,
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"output_tokens": self.output_tokens,
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"reasoning_tokens": self.reasoning_tokens,
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"total_tokens": self.total_tokens,
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}
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def reset(self):
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with self.lock:
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self.input_tokens = 0
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self.cached_tokens = 0
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self.output_tokens = 0
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self.reasoning_tokens = 0
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self.total_tokens = 0
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PreSendHandlerType = Callable[[str, str], tuple[str, str]]
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ResultHandlerType = Callable[[str, str, logging.Logger], Any]
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ErrorResultHandlerType = Callable[[str, logging.Logger], Any]
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class Agent:
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def __init__(self, config: AgentConfig):
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self.baseurl = config.base_url.strip()
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if self.baseurl.endswith("/"):
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self.baseurl = self.baseurl[:-1]
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self.domain = urlparse(self.baseurl).netloc
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self.key = config.api_key.strip() if config.api_key else "xx"
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self.model_id = config.model_id.strip()
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self.system_prompt = ""
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self.temperature = config.temperature
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self.max_concurrent = config.concurrent
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self.timeout = httpx.Timeout(connect=5, read=config.timeout, write=300, pool=10)
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self.thinking = config.thinking
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self.logger = config.logger
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self.total_error_counter = TotalErrorCounter(logger=self.logger)
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self.unresolved_error_lock = Lock()
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self.unresolved_error_count = 0
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self.token_counter = TokenCounter(logger=self.logger)
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self.retry = config.retry
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self.system_proxy_enable = config.system_proxy_enable
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# 新增：初始化速率限制器
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self.rate_limiter = RateLimiter(rpm=config.rpm, tpm=config.tpm)
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# 新增：初始化 encoding 用于估算
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self.encoding = self._get_encoding_for_model(self.model_id)
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def _get_encoding_for_model(self, model_name: str):
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"""获取 tiktoken encoding，如果失败则使用 cl100k_base 兜底"""
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try:
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return tiktoken.encoding_for_model(model_name)
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except KeyError:
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# 对于未知模型或自定义模型ID，使用 GPT-4 的默认编码器
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return tiktoken.get_encoding("cl100k_base")
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def _estimate_tokens(self, text: str) -> int:
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"""估算文本的 Token 数量"""
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if not text:
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return 0
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try:
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# 这是一个近似值，不包含特殊 token 格式的开销，但用于限流足够了
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return len(self.encoding.encode(text))
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except Exception:
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# 极端兜底：每4个字符算1个token
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return len(text) // 4
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def _add_thinking_mode(self, data: dict):
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thinking_mode_result = get_thinking_mode(self.domain, data.get("model"))
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if thinking_mode_result is None:
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return
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field_thinking, val_enable, val_disable = thinking_mode_result
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if self.thinking == "enable":
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data[field_thinking] = val_enable
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elif self.thinking == "disable":
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data[field_thinking] = val_disable
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def _prepare_request_data(
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self, prompt: str, system_prompt: str, temperature=None, top_p=0.9, json_format=False
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):
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if temperature is None:
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temperature = self.temperature
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.key}",
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}
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data = {
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"model": self.model_id,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": prompt},
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],
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"temperature": temperature,
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"top_p": top_p,
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}
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if self.thinking != "default":
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self._add_thinking_mode(data)
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if json_format:
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data["response_format"] = {"type": "json_object"}
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return headers, data
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async def send_async(
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self,
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client: httpx.AsyncClient,
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prompt: str,
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system_prompt: None | str = None,
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retry=True,
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retry_count=0,
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force_json=False,
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pre_send_handler: PreSendHandlerType = None,
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result_handler: ResultHandlerType = None,
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error_result_handler: ErrorResultHandlerType = None,
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best_partial_result: dict | None = None,
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) -> Any:
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if system_prompt is None:
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system_prompt = self.system_prompt
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if pre_send_handler:
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system_prompt, prompt = pre_send_handler(system_prompt, prompt)
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# 新增：速率限制检查
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# 计算估算的 tokens (system + user)
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estimated_tokens = self._estimate_tokens(system_prompt) + self._estimate_tokens(prompt)
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# 等待配额
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await self.rate_limiter.acquire_async(tokens=estimated_tokens)
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headers, data = self._prepare_request_data(prompt, system_prompt, json_format=force_json)
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should_retry = False
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is_hard_error = False
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current_partial_result = None
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input_tokens = 0
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output_tokens = 0
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try:
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response = await client.post(
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f"{self.baseurl}/chat/completions",
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json=data,
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headers=headers,
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timeout=self.timeout,
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)
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response.raise_for_status()
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result = response.json()["choices"][0]["message"]["content"]
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||
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response_data = response.json()
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input_tokens, cached_tokens, output_tokens, reasoning_tokens = (
|
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extract_token_info(response_data)
|
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)
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||
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||
self.token_counter.add(
|
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input_tokens, cached_tokens, output_tokens, reasoning_tokens
|
||
)
|
||
|
||
if retry_count > 0:
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||
self.logger.info(f"重试成功 (第 {retry_count}/{self.retry} 次尝试)。")
|
||
|
||
return (
|
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result
|
||
if result_handler is None
|
||
else result_handler(result, prompt, self.logger)
|
||
)
|
||
|
||
except AgentResultError as e:
|
||
self.logger.error(f"AI返回结果有误: {e}")
|
||
should_retry = True
|
||
except PartialAgentResultError as e:
|
||
self.logger.error(f"收到部分返回结果，将尝试重试: {e}")
|
||
current_partial_result = e.partial_result
|
||
should_retry = True
|
||
if e.append_prompt:
|
||
prompt += e.append_prompt
|
||
|
||
except httpx.HTTPStatusError as e:
|
||
self.logger.error(
|
||
f"AI请求HTTP状态错误 (async): {e.response.status_code} - {e.response.text}"
|
||
)
|
||
should_retry = True
|
||
is_hard_error = True
|
||
# 如果是因为 Rate Limit (429) 错误，最好在这里多睡一会儿，虽然我们有了本地 Limiter
|
||
if e.response.status_code == 429:
|
||
await asyncio.sleep(5)
|
||
|
||
except httpx.RequestError as e:
|
||
self.logger.error(f"AI请求连接错误 (async): {repr(e)}")
|
||
should_retry = True
|
||
is_hard_error = True
|
||
except (KeyError, IndexError, ValueError) as e:
|
||
self.logger.error(f"AI响应格式或值错误 (async), 将尝试重试: {repr(e)}")
|
||
should_retry = True
|
||
is_hard_error = True
|
||
|
||
if current_partial_result:
|
||
best_partial_result = current_partial_result
|
||
|
||
if should_retry and retry and retry_count < self.retry:
|
||
if is_hard_error:
|
||
if retry_count == 0:
|
||
if self.total_error_counter.add():
|
||
self.logger.error("错误次数过多，已达到上限，不再重试。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
return (
|
||
best_partial_result
|
||
if best_partial_result
|
||
else (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
)
|
||
elif self.total_error_counter.reach_limit():
|
||
self.logger.error("错误次数过多，已达到上限，不再为该请求重试。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
return (
|
||
best_partial_result
|
||
if best_partial_result
|
||
else (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
)
|
||
|
||
self.logger.info(f"正在重试第 {retry_count + 1}/{self.retry} 次...")
|
||
# 指数退避
|
||
await asyncio.sleep(0.5 * (2 ** retry_count))
|
||
return await self.send_async(
|
||
client,
|
||
prompt,
|
||
system_prompt,
|
||
retry=True,
|
||
retry_count=retry_count + 1,
|
||
force_json=force_json,
|
||
pre_send_handler=pre_send_handler,
|
||
result_handler=result_handler,
|
||
error_result_handler=error_result_handler,
|
||
best_partial_result=best_partial_result,
|
||
)
|
||
else:
|
||
if should_retry:
|
||
self.logger.error(f"所有重试均失败，已达到重试次数上限。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
|
||
if best_partial_result:
|
||
self.logger.info("所有重试失败，但存在部分翻译结果，将使用该结果。")
|
||
return best_partial_result
|
||
|
||
return (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
|
||
async def send_prompts_async(
|
||
self,
|
||
prompts: list[str],
|
||
system_prompt: str | None = None,
|
||
max_concurrent: int | None = None,
|
||
force_json=False,
|
||
pre_send_handler: PreSendHandlerType = None,
|
||
result_handler: ResultHandlerType = None,
|
||
error_result_handler: ErrorResultHandlerType = None,
|
||
) -> list[Any]:
|
||
max_concurrent = (
|
||
self.max_concurrent if max_concurrent is None else max_concurrent
|
||
)
|
||
total = len(prompts)
|
||
rpm_info = f", RPM:{self.rate_limiter.rpm}" if self.rate_limiter.rpm else ""
|
||
tpm_info = f", TPM:{self.rate_limiter.tpm}" if self.rate_limiter.tpm else ""
|
||
|
||
self.logger.info(
|
||
f"base-url:{self.baseurl},model-id:{self.model_id},concurrent:{max_concurrent}{rpm_info}{tpm_info},temperature:{self.temperature},system_proxy:{self.system_proxy_enable},json_output:{force_json}"
|
||
)
|
||
self.logger.info(f"预计发送{total}个请求")
|
||
|
||
self.total_error_counter.max_errors_count = (
|
||
len(prompts) // MAX_REQUESTS_PER_ERROR
|
||
)
|
||
|
||
self.unresolved_error_count = 0
|
||
self.token_counter.reset()
|
||
|
||
count = 0
|
||
semaphore = asyncio.Semaphore(max_concurrent)
|
||
tasks = []
|
||
|
||
proxies = get_httpx_proxies(asyn=True) if self.system_proxy_enable else None
|
||
|
||
limits = httpx.Limits(
|
||
max_connections=self.max_concurrent * 2,
|
||
max_keepalive_connections=self.max_concurrent,
|
||
)
|
||
|
||
async with httpx.AsyncClient(
|
||
trust_env=False, mounts=proxies, verify=False, limits=limits
|
||
) as client:
|
||
|
||
async def send_with_semaphore(p_text: str):
|
||
async with semaphore:
|
||
# 注意：我们在 semaphore 内部调用 send_async
|
||
# send_async 内部会调用 rate_limiter.acquire_async
|
||
# 这样可以防止并发过高，同时 rate_limiter 防止频率过快
|
||
result = await self.send_async(
|
||
client=client,
|
||
prompt=p_text,
|
||
system_prompt=system_prompt,
|
||
force_json=force_json,
|
||
pre_send_handler=pre_send_handler,
|
||
result_handler=result_handler,
|
||
error_result_handler=error_result_handler,
|
||
)
|
||
nonlocal count
|
||
count += 1
|
||
self.logger.info(f"协程-已完成{count}/{total}")
|
||
return result
|
||
|
||
for p_text in prompts:
|
||
task = asyncio.create_task(send_with_semaphore(p_text))
|
||
tasks.append(task)
|
||
|
||
results = await asyncio.gather(*tasks, return_exceptions=False)
|
||
|
||
self.logger.info(
|
||
f"所有请求处理完毕。未解决的错误总数: {self.unresolved_error_count}"
|
||
)
|
||
|
||
token_stats = self.token_counter.get_stats()
|
||
self.logger.info(
|
||
f"Token使用统计 - 输入: {token_stats['input_tokens'] / 1000:.2f}K(含cached: {token_stats['cached_tokens'] / 1000:.2f}K), "
|
||
f"输出: {token_stats['output_tokens'] / 1000:.2f}K(含reasoning: {token_stats['reasoning_tokens'] / 1000:.2f}K), "
|
||
f"总计: {token_stats['total_tokens'] / 1000:.2f}K"
|
||
)
|
||
|
||
return results
|
||
|
||
def send(
|
||
self,
|
||
client: httpx.Client,
|
||
prompt: str,
|
||
system_prompt: None | str = None,
|
||
retry=True,
|
||
retry_count=0,
|
||
force_json=False,
|
||
pre_send_handler=None,
|
||
result_handler=None,
|
||
error_result_handler=None,
|
||
best_partial_result: dict | None = None,
|
||
) -> Any:
|
||
if system_prompt is None:
|
||
system_prompt = self.system_prompt
|
||
if pre_send_handler:
|
||
system_prompt, prompt = pre_send_handler(system_prompt, prompt)
|
||
|
||
# 新增：同步环境下的速率限制
|
||
estimated_tokens = self._estimate_tokens(system_prompt) + self._estimate_tokens(prompt)
|
||
self.rate_limiter.acquire_sync(tokens=estimated_tokens)
|
||
|
||
headers, data = self._prepare_request_data(prompt, system_prompt, json_format=force_json)
|
||
should_retry = False
|
||
is_hard_error = False
|
||
current_partial_result = None
|
||
input_tokens = 0
|
||
output_tokens = 0
|
||
|
||
try:
|
||
response = client.post(
|
||
f"{self.baseurl}/chat/completions",
|
||
json=data,
|
||
headers=headers,
|
||
timeout=self.timeout,
|
||
)
|
||
response.raise_for_status()
|
||
|
||
result = response.json()["choices"][0]["message"]["content"]
|
||
|
||
response_data = response.json()
|
||
input_tokens, cached_tokens, output_tokens, reasoning_tokens = (
|
||
extract_token_info(response_data)
|
||
)
|
||
|
||
self.token_counter.add(
|
||
input_tokens, cached_tokens, output_tokens, reasoning_tokens
|
||
)
|
||
|
||
if retry_count > 0:
|
||
self.logger.info(f"重试成功 (第 {retry_count}/{self.retry} 次尝试)。")
|
||
|
||
return (
|
||
result
|
||
if result_handler is None
|
||
else result_handler(result, prompt, self.logger)
|
||
)
|
||
except AgentResultError as e:
|
||
self.logger.error(f"AI返回结果有误: {e}")
|
||
should_retry = True
|
||
except PartialAgentResultError as e:
|
||
self.logger.error(f"收到部分翻译结果，将尝试重试: {e}")
|
||
current_partial_result = e.partial_result
|
||
should_retry = True
|
||
|
||
except httpx.HTTPStatusError as e:
|
||
self.logger.error(
|
||
f"AI请求HTTP状态错误 (sync): {e.response.status_code} - {e.response.text}"
|
||
)
|
||
should_retry = True
|
||
is_hard_error = True
|
||
if e.response.status_code == 429:
|
||
time.sleep(5)
|
||
|
||
except httpx.RequestError as e:
|
||
self.logger.error(f"AI请求连接错误 (sync): {repr(e)}\nprompt:{prompt}")
|
||
should_retry = True
|
||
is_hard_error = True
|
||
except (KeyError, IndexError, ValueError) as e:
|
||
self.logger.error(f"AI响应格式或值错误 (sync), 将尝试重试: {repr(e)}")
|
||
should_retry = True
|
||
is_hard_error = True
|
||
|
||
if current_partial_result:
|
||
best_partial_result = current_partial_result
|
||
|
||
if should_retry and retry and retry_count < self.retry:
|
||
if is_hard_error:
|
||
if retry_count == 0:
|
||
if self.total_error_counter.add():
|
||
self.logger.error("错误次数过多，已达到上限，不再重试。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
return (
|
||
best_partial_result
|
||
if best_partial_result
|
||
else (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
)
|
||
elif self.total_error_counter.reach_limit():
|
||
self.logger.error("错误次数过多，已达到上限，不再为该请求重试。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
return (
|
||
best_partial_result
|
||
if best_partial_result
|
||
else (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
)
|
||
|
||
self.logger.info(f"正在重试第 {retry_count + 1}/{self.retry} 次...")
|
||
time.sleep(0.5 * (2 ** retry_count))
|
||
return self.send(
|
||
client,
|
||
prompt,
|
||
system_prompt,
|
||
retry=True,
|
||
retry_count=retry_count + 1,
|
||
force_json=force_json,
|
||
pre_send_handler=pre_send_handler,
|
||
result_handler=result_handler,
|
||
error_result_handler=error_result_handler,
|
||
best_partial_result=best_partial_result,
|
||
)
|
||
else:
|
||
if should_retry:
|
||
self.logger.error(f"所有重试均失败，已达到重试次数上限。")
|
||
with self.unresolved_error_lock:
|
||
self.unresolved_error_count += 1
|
||
|
||
if best_partial_result:
|
||
self.logger.info("所有重试失败，但存在部分翻译结果，将使用该结果。")
|
||
return best_partial_result
|
||
|
||
return (
|
||
prompt
|
||
if error_result_handler is None
|
||
else error_result_handler(prompt, self.logger)
|
||
)
|
||
|
||
def _send_prompt_count(
|
||
self,
|
||
client: httpx.Client,
|
||
prompt: str,
|
||
system_prompt: None | str,
|
||
force_json,
|
||
count: PromptsCounter,
|
||
pre_send_handler,
|
||
result_handler,
|
||
error_result_handler
|
||
) -> Any:
|
||
# 该方法在 ThreadPoolExecutor 中运行
|
||
result = self.send(
|
||
client,
|
||
prompt,
|
||
system_prompt,
|
||
force_json=force_json,
|
||
pre_send_handler=pre_send_handler,
|
||
result_handler=result_handler,
|
||
error_result_handler=error_result_handler,
|
||
)
|
||
count.add()
|
||
return result
|
||
|
||
def send_prompts(
|
||
self,
|
||
prompts: list[str],
|
||
system_prompt: str | None = None,
|
||
json_format=False,
|
||
pre_send_handler: PreSendHandlerType = None,
|
||
result_handler: ResultHandlerType = None,
|
||
error_result_handler: ErrorResultHandlerType = None,
|
||
) -> list[Any]:
|
||
rpm_info = f", RPM:{self.rate_limiter.rpm}" if self.rate_limiter.rpm else ""
|
||
tpm_info = f", TPM:{self.rate_limiter.tpm}" if self.rate_limiter.tpm else ""
|
||
|
||
self.logger.info(
|
||
f"base-url:{self.baseurl},model-id:{self.model_id},concurrent:{self.max_concurrent}{rpm_info}{tpm_info},temperature:{self.temperature},system_proxy:{self.system_proxy_enable},json_output:{json_format}"
|
||
)
|
||
self.logger.info(
|
||
f"预计发送{len(prompts)}个请求"
|
||
)
|
||
self.total_error_counter.max_errors_count = (
|
||
len(prompts) // MAX_REQUESTS_PER_ERROR
|
||
)
|
||
|
||
self.unresolved_error_count = 0
|
||
self.token_counter.reset()
|
||
|
||
counter = PromptsCounter(len(prompts), self.logger)
|
||
|
||
system_prompts = itertools.repeat(system_prompt, len(prompts))
|
||
json_formats = itertools.repeat(json_format, len(prompts))
|
||
counters = itertools.repeat(counter, len(prompts))
|
||
pre_send_handlers = itertools.repeat(pre_send_handler, len(prompts))
|
||
result_handlers = itertools.repeat(result_handler, len(prompts))
|
||
error_result_handlers = itertools.repeat(error_result_handler, len(prompts))
|
||
limits = httpx.Limits(
|
||
max_connections=self.max_concurrent * 2,
|
||
max_keepalive_connections=self.max_concurrent,
|
||
)
|
||
proxies = get_httpx_proxies(asyn=False) if self.system_proxy_enable else None
|
||
|
||
with httpx.Client(
|
||
trust_env=False, mounts=proxies, verify=False, limits=limits
|
||
) as client:
|
||
clients = itertools.repeat(client, len(prompts))
|
||
with ThreadPoolExecutor(max_workers=self.max_concurrent) as executor:
|
||
results_iterator = executor.map(
|
||
self._send_prompt_count,
|
||
clients,
|
||
prompts,
|
||
system_prompts,
|
||
json_formats,
|
||
counters,
|
||
pre_send_handlers,
|
||
result_handlers,
|
||
error_result_handlers,
|
||
)
|
||
output_list = list(results_iterator)
|
||
|
||
self.logger.info(
|
||
f"所有请求处理完毕。未解决的错误总数: {self.unresolved_error_count}"
|
||
)
|
||
|
||
token_stats = self.token_counter.get_stats()
|
||
self.logger.info(
|
||
f"Token使用统计 - 输入: {token_stats['input_tokens'] / 1000:.2f}K(含cached: {token_stats['cached_tokens'] / 1000:.2f}K), "
|
||
f"输出: {token_stats['output_tokens'] / 1000:.2f}K(含reasoning: {token_stats['reasoning_tokens'] / 1000:.2f}K), "
|
||
f"总计: {token_stats['total_tokens'] / 1000:.2f}K"
|
||
)
|
||
|
||
return output_list |