后端代码微调：SQLserver地址账号变更

bbit_ai/.idea/app.iml

@@ -2,6 +2,9 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$/app" />
+    <content url="file://$MODULE_DIR$/app_bot" />
+    <content url="file://$MODULE_DIR$/app_mcp" />
+    <content url="file://$MODULE_DIR$/app_mcp_tools" />
     <orderEntry type="jdk" jdkName="bbit_ai_lab" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>

bbit_ai/app/app.py

@@ -1,6 +1,10 @@
+import asyncio
+
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
+from uvicorn import Config, Server
 
+from mcp_local.mcp_pipe import init_mcp_server
 from routers.Bot import botRouter
 from routers.Chat import chatRouter
 from routers.Datasource import reportDataRouter
@@ -10,9 +14,10 @@ from routers.RabbitMQ import rqRouter
 from routers.Report import reportRouter
 from routers.Service import serviceRouter
 from routers.Vision import visionRouter
-from service.Analyze import mq_pull_analysis
-from utils import MyUtils
+from service.Analyze import mq_pull_analysis_async
 
+
+async def ai_lab():
     app = FastAPI(title="BBIT_AI")
 
     origins = [
@@ -38,10 +43,32 @@ routers = [
         visionRouter,
         rqRouter,
     ]
-
     for r in routers:
         app.include_router(r, prefix="/llm", tags=["llm"])
-
     app.include_router(publicRouter, prefix="/api/public", tags=["api"])
+    config = Config(app=app, host="0.0.0.0", port=13011, log_level="info")
+    server = Server(config)
+    await server.serve()
 
-MyUtils.async_new_task(mq_pull_analysis)
+
+async def main():
+    # 主干AI实验室FastAPI服务
+    task_api = asyncio.create_task(ai_lab())
+
+    # MCP服务-ailab
+    # endpoint_url = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
+    endpoint_url_ai_lab = "ws://ce_bot_mcp:8004/mcp_endpoint/mcp/?token=TsSP9lBq6Oa1WMkachHoS2TtNt4GKV/Gli24pk5Rjpk%3D"
+    task_mcp1 = asyncio.create_task(init_mcp_server(endpoint_url_ai_lab))
+
+    # MCP服务-ql
+    endpoint_url_ql = "wss://ai.ronsunny.cn:8090/aimcp/mcp_endpoint/mcp/?token=8ZmCzp7FzsbxwHOg2%2FvBQkxrC3QWJiI%2B4iTfouExinjcT8ZgLwQfFUtgcMInI7St"
+    task_mcp2 = asyncio.create_task(init_mcp_server(endpoint_url_ql))
+
+    # RabbitMQ服务
+    task_mq = asyncio.create_task(mq_pull_analysis_async())
+
+    await asyncio.gather(task_api, task_mcp1, task_mcp2, task_mq)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

bbit_ai/app/config/ssDb.py

@@ -1,25 +1,16 @@
-from langchain_community.utilities import SQLDatabase
-from langchain_community.agent_toolkits import create_sql_agent
-from langchain_community.chat_models.tongyi import ChatTongyi
-# SQLAlchemy URI
-uri = "mssql+pyodbc://f8_db_test:APN^QPr!K9@122.114.58.23/f8_db_test?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes&Encrypt=no"
-
-# 建立数据库对象
-ssDBLC = SQLDatabase.from_uri(
-    uri,
-    include_tables=["NONGHU_INFO","NONGHU_BLACKLIST",], 
-    schema="dbo"                      # 显式指定 schema
-)
 import logging
 import time
 from contextlib import contextmanager
-from sqlalchemy import create_engine, text
-from sqlalchemy.exc import OperationalError as SQLOperationalError
 from urllib.parse import quote_plus
 
+from langchain_community.utilities import SQLDatabase
+from sqlalchemy import create_engine
+from sqlalchemy.exc import OperationalError as SQLOperationalError
+
 logger = logging.getLogger("MSSQLPool")
 logger.setLevel(logging.INFO)
 
+
 class MSSQLPool:
     """
     SQL Server 连接池封装
@@ -74,9 +65,22 @@ class MSSQLPool:
                 raise
         raise SQLOperationalError("无法获取数据库连接，多次重试失败")
 
+
 mssql_pool = MSSQLPool(
-    user="f8_db_test",
-    password="APN^QPr!K9",
-    host="122.114.58.23",
-    database="f8_db_test",
+    user="f8_read",
+    password="www.bbitcn.com",
+    host="f8.api.dev.bbitcn.cn",
+    database="f8_db_dev",
+)
+
+# SQLAlchemy URI
+uri = "mssql+pyodbc://f8_read:www.bbitcn.com@f8.api.dev.bbitcn.cn/f8_db_dev?driver=ODBC+Driver+18+for+SQL+Server&TrustServerCertificate=yes&Encrypt=no"
+
+# 建立数据库对象
+ssDBLC = SQLDatabase.from_uri(
+    uri,
+    include_tables=[
+        "NONGHU_INFO",
+    ],
+    schema="dbo",  # 显式指定 schema
 )

bbit_ai/app/service/Analyze.py

@@ -1,68 +1,52 @@
 # consumer.py
+import asyncio
 import json
-import time
 
-import pika
+import aio_pika
 
 from config.rabbitMQ import *
 from models.AnalysisRequest import AnalysisRequest
 
 
-def mq_new_analysis(req: AnalysisRequest):
-    """将分析请求发送到 RabbitMQ 队列"""
-    credentials = pika.PlainCredentials(RABBIT_USER, RABBIT_PASSWORD)
-    connection = pika.BlockingConnection(
-        pika.ConnectionParameters(
-            host=RABBIT_HOST, virtual_host=RABBIT_VHOST, credentials=credentials
+async def mq_new_analysis(req: AnalysisRequest):
+    """将分析请求发送到 RabbitMQ 队列（异步版）"""
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{RABBIT_VHOST}"
     )
-    )
-    channel = connection.channel()
-    channel.queue_declare(queue=QUEUE_NAME, durable=True)
 
-    message = json.dumps(req.dict())
-    try:
-        channel.basic_publish(
-            exchange="",
-            routing_key=QUEUE_NAME,
-            body=message,
-            properties=pika.BasicProperties(delivery_mode=2),  # 持久化消息
+    async with connection:
+        channel = await connection.channel()
+        # 声明队列，确保队列存在
+        queue = await channel.declare_queue(QUEUE_NAME, durable=True)
+
+        message_body = json.dumps(req.dict())
+        message = aio_pika.Message(
+            body=message_body.encode(),
+            delivery_mode=aio_pika.DeliveryMode.PERSISTENT,  # 持久化
         )
-    finally:
-        channel.close()
-        connection.close()
+
+        await channel.default_exchange.publish(message, routing_key=QUEUE_NAME)
 
 
-def mq_pull_analysis():
+async def mq_pull_analysis_async():
     """
     从队列拉取分析任务并处理
     process_func: 一个函数，接收 AnalysisRequest 对象处理分析逻辑
     """
-    credentials = pika.PlainCredentials(RABBIT_USER, RABBIT_PASSWORD)
-    connection = pika.BlockingConnection(
-        pika.ConnectionParameters(
-            host=RABBIT_HOST, virtual_host=RABBIT_VHOST, credentials=credentials
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{RABBIT_VHOST}"
     )
-    )
-    channel = connection.channel()
-    channel.queue_declare(queue=QUEUE_NAME, durable=True)
-    channel.basic_qos(prefetch_count=1)  # 保证一次只处理一条消息
+    async with connection:
+        queue_name = QUEUE_NAME
+        channel = await connection.channel()
+        await channel.set_qos(prefetch_count=1)
+        queue = await channel.declare_queue(queue_name, durable=True)
 
-    def callback(ch, method, properties, body):
-        try:
-            data = json.loads(body)
+        async with queue.iterator() as queue_iter:
+            async for message in queue_iter:
+                async with message.process():
+                    data = json.loads(message.body)
                     req = AnalysisRequest(**data)
                     print(f"收到任务: {req}")
-            time.sleep(5)
+                    await asyncio.sleep(5)  # 模拟处理
                     print(f"完成任务: {req}")
-        except Exception as e:
-            print(f"处理任务出错: {e}")
-        finally:
-            ch.basic_ack(delivery_tag=method.delivery_tag)
-
-    channel.basic_consume(queue=QUEUE_NAME, on_message_callback=callback)
-    print("开启队列消费者，等待分析任务...")
-    try:
-        channel.start_consuming()
-    finally:
-        channel.close()
-        connection.close()