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95 lines
3.2 KiB
95 lines
3.2 KiB
import asyncio
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import logging
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from aiomysql import create_pool
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from WxMini.Milvus.Config.MulvusConfig import *
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# 配置日志
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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logger = logging.getLogger(__name__)
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# MySQL 配置
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MYSQL_CONFIG = {
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"host": MYSQL_HOST,
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"port": MYSQL_PORT,
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"user": MYSQL_USER,
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"password": MYSQL_PASSWORD,
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"db": MYSQL_DB_NAME,
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"minsize": 1,
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"maxsize": 20,
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}
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# 初始化 MySQL 连接池
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async def init_mysql_pool():
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return await create_pool(**MYSQL_CONFIG)
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# 保存聊天记录到 MySQL
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async def save_chat_to_mysql(mysql_pool, session_id, prompt, result,audio_url,duration):
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async with mysql_pool.acquire() as conn:
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async with conn.cursor() as cur:
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await cur.execute(
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"INSERT INTO t_chat_log (session_id, user_input, model_response,audio_url,duration,create_time) VALUES (%s, %s, %s, %s, %s,NOW())",
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(session_id, prompt, result,audio_url,duration)
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)
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await conn.commit()
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logger.info("用户输入和大模型反馈已记录到 MySQL 数据库。")
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# 清空表
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async def truncate_chat_log(mysql_pool):
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async with mysql_pool.acquire() as conn:
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async with conn.cursor() as cur:
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await cur.execute("TRUNCATE TABLE t_chat_log")
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await conn.commit()
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logger.info("表 t_chat_log 已清空。")
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# 分页查询聊天记录
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async def get_chat_log_by_session(mysql_pool,session_id, page=1, page_size=10):
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"""
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根据 session_id 查询聊天记录，并按 id 降序分页
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:param session_id: 用户会话 ID
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:param page: 当前页码
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:param page_size: 每页记录数
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:return: 分页数据
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"""
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if not mysql_pool:
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raise ValueError("MySQL 连接池未初始化")
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offset = (page - 1) * page_size
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async with mysql_pool.acquire() as conn:
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async with conn.cursor() as cur:
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# 查询总记录数
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await cur.execute(
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"SELECT COUNT(*) FROM t_chat_log WHERE session_id = %s",
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(session_id,)
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)
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total = (await cur.fetchone())[0]
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# 查询分页数据
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await cur.execute(
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"SELECT id, session_id, user_input, model_response, audio_url, duration, create_time "
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"FROM t_chat_log WHERE session_id = %s ORDER BY id DESC LIMIT %s OFFSET %s",
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(session_id, page_size, offset)
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)
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records = await cur.fetchall()
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# 将查询结果转换为字典列表
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result = [
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{
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"id": record[0],
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"session_id": record[1],
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"user_input": record[2],
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"model_response": record[3],
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"audio_url": record[4],
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"duration": record[5],
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"create_time": record[6].strftime("%Y-%m-%d %H:%M:%S")
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}
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for record in records
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]
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return {
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"data": result,
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"total": total,
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"page": page,
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"page_size": page_size
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} |