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llm_module_memory_make.py

pull/47/head
野原小牛 2025-03-04 15:14:26 +08:00
parent 6f599aad6d
commit 3780380d3b
1 changed files with 9 additions and 6 deletions
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13
src/plugins/memory_system/llm_module_memory_make.py
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@ -5,13 +5,13 @@ import time
from nonebot import get_driver from nonebot import get_driver
import aiohttp import aiohttp
import asyncio import asyncio
from loguru import logger
from src.plugins.chat.config import BotConfig, global_config from src.plugins.chat.config import BotConfig, global_config
driver = get_driver() driver = get_driver()
config = driver.config config = driver.config
class LLMModel: class LLMModel:
# def __init__(self, model_name="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", **kwargs):
def __init__(self, model_name=global_config.SILICONFLOW_MODEL_V3, **kwargs): def __init__(self, model_name=global_config.SILICONFLOW_MODEL_V3, **kwargs):
self.model_name = model_name self.model_name = model_name
self.params = kwargs self.params = kwargs
@ -21,7 +21,7 @@ class LLMModel:
if not self.api_key or not self.base_url: if not self.api_key or not self.base_url:
raise ValueError("环境变量未正确加载：SILICONFLOW_KEY 或 SILICONFLOW_BASE_URL 未设置") raise ValueError("环境变量未正确加载：SILICONFLOW_KEY 或 SILICONFLOW_BASE_URL 未设置")
print(f"API URL: {self.base_url}") # 打印 base_url 用于调试 logger.info(f"API URL: {self.base_url}") # 使用 logger 记录 base_url
async def generate_response(self, prompt: str) -> Tuple[str, str]: async def generate_response(self, prompt: str) -> Tuple[str, str]:
"""根据输入的提示生成模型的响应""" """根据输入的提示生成模型的响应"""
@ -38,8 +38,9 @@ class LLMModel:
**self.params **self.params
} }
# 发送请求到完整的chat/completions端点 # 发送请求到完整的 chat/completions 端点
api_url = f"{self.base_url.rstrip('/')}/chat/completions" api_url = f"{self.base_url.rstrip('/')}/chat/completions"
logger.info(f"Request URL: {api_url}") # 记录请求的 URL
max_retries = 3 max_retries = 3
base_wait_time = 15 # 基础等待时间（秒） base_wait_time = 15 # 基础等待时间（秒）
@ -50,7 +51,7 @@ class LLMModel:
async with session.post(api_url, headers=headers, json=data) as response: async with session.post(api_url, headers=headers, json=data) as response:
if response.status == 429: if response.status == 429:
wait_time = base_wait_time * (2 ** retry) # 指数退避 wait_time = base_wait_time * (2 ** retry) # 指数退避
print(f"遇到请求限制(429)，等待{wait_time}秒后重试...") logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...")
await asyncio.sleep(wait_time) await asyncio.sleep(wait_time)
continue continue
@ -66,9 +67,11 @@ class LLMModel:
except Exception as e: except Exception as e:
if retry < max_retries - 1: # 如果还有重试机会 if retry < max_retries - 1: # 如果还有重试机会
wait_time = base_wait_time * (2 ** retry) wait_time = base_wait_time * (2 ** retry)
print(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}") logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}")
await asyncio.sleep(wait_time) await asyncio.sleep(wait_time)
else: else:
logger.error(f"请求失败: {str(e)}")
return f"请求失败: {str(e)}", "" return f"请求失败: {str(e)}", ""
logger.error("达到最大重试次数，请求仍然失败")
return "达到最大重试次数，请求仍然失败", "" return "达到最大重试次数，请求仍然失败", ""