更新python后端

2025-09-18 17:18:18 +08:00
parent 2fc209e6e6
commit de6a350da8
45 changed files with 2524 additions and 89 deletions
@@ -1,6 +1,34 @@

 from langchain_community.chat_models.tongyi import ChatTongyi
 from utils.Tools import all_tools
+from langchain.chat_models import init_chat_model
+from langchain_openai import ChatOpenAI
+from openai import OpenAI
+import os
+from langchain_openai import OpenAIEmbeddings
+# 通义千文Key
+tongyiKey = "sk-9464b2498c184982a9fe9d2c2e725ab5"
+# DeepSeekKey
+deepseekKey = "sk-6129a200ae294b9f86553505191fa477"

-llm = ChatTongyi(streaming=False, api_key="sk-fb46eefb6b404382a0a5325202e923a6")
+llm = ChatTongyi(streaming=False, api_key=tongyiKey)
 llm_with_tools = llm.bind_tools(all_tools)
+
+llmThink = ChatOpenAI(
+    api_key=tongyiKey,
+    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
+    model="qwen-max", 
+    stream = False
+)
+from langchain_community.embeddings import DashScopeEmbeddings
+embeddings = DashScopeEmbeddings(
+    model="text-embedding-v3",
+    dashscope_api_key= tongyiKey, 
+)
+
+# from langchain_deepseek import ChatDeepSeek
+# llm = ChatDeepSeek(
+#     model="deepseek-reasoner",
+#     api_key=deepseekKey,
+#     api_base="https://api.deepseek.com"
+# )
@@ -0,0 +1,35 @@
+from langchain_milvus import BM25BuiltInFunction, Milvus
+from config.llm import embeddings
+
+URI = "http://10.10.10.9:19530"
+
+knVectorstore = Milvus(
+    embedding_function=embeddings,
+    connection_args={"uri": URI, "token": "root:Milvus", "db_name": "bbit_ai_lab"},
+    collection_name="knowledge",
+    index_params={"index_type": "FLAT", "metric_type": "L2"},
+    consistency_level="Strong",
+    auto_id=True,
+
+    primary_field = "id",
+    text_field="text",
+    vector_field="vector",
+    partition_key_field = "kn_id",
+    enable_dynamic_field = True,
+    drop_old=False,  # set to True if seeking to drop the collection with that name if it exists
+)
+memVectorstore = Milvus(
+    embedding_function=embeddings,
+    connection_args={"uri": URI, "token": "root:Milvus", "db_name": "bbit_ai_lab"},
+    collection_name="memory",
+    index_params={"index_type": "FLAT", "metric_type": "L2"},
+    consistency_level="Strong",
+    auto_id=True,
+
+    primary_field = "id",
+    text_field="text",
+    vector_field="vector",
+    partition_key_field = "ai_id",
+    enable_dynamic_field = True,
+    drop_old=False,  # set to True if seeking to drop the collection with that name if it exists
+)
@@ -1,22 +1,69 @@
-
-import psycopg
-from langchain_postgres import PostgresChatMessageHistory
-from psycopg_pool import ConnectionPool
+import logging
+import time
 from contextlib import contextmanager
+from typing import Optional
+import psycopg
+from psycopg_pool import ConnectionPool

-# conn = psycopg.connect("postgresql://postgres:123456@10.10.10.9/ktor2")
-database_name = "ai_chat_history"
-pool = ConnectionPool("postgresql://postgres:123456@10.10.10.9/ktor2")
+logger = logging.getLogger("PGPool")
+logger.setLevel(logging.INFO)

-@contextmanager
-def getConn():
-    with pool.connection() as temp:
-        temp.autocommit = True   # 如果你想所有连接默认 autocommit
-        yield temp               # 把 conn 暴露给外部使用
+class PGPool:
+    """
+    PostgreSQL 连接池封装
+    """

+    def __init__(
+        self,
+        uri: str,
+        min_size: int = 1,
+        max_size: int = 20,
+        max_idle: int = 30,
+        max_lifetime: int = 300,
+        timeout: int = 10,
+        check: bool = False,
+    ):
+        """
+        :param uri: PostgreSQL 连接 URI
+        """
+        self.uri = uri
+        self.pool = ConnectionPool(
+            self.uri,
+            min_size=min_size,
+            max_size=max_size,
+            max_idle=max_idle,
+            max_lifetime=max_lifetime,
+            timeout=timeout,
+            check=check,
+        )

-def init():
-    with getConn() as connection:
-        PostgresChatMessageHistory.create_tables(connection, database_name)
-
-init()
+    @contextmanager
+    def getConn(self, retries: int = 2, delay: float = 1.0):
+        """
+        获取数据库连接，带重试机制，自动健康检查。
+        使用方式：
+            with pg_pool.get_conn() as conn:
+                with conn.cursor() as cur:
+                    cur.execute(...)
+        """
+        attempt = 0
+        while attempt <= retries:
+            try:
+                with self.pool.connection() as conn:
+                    conn.autocommit = True
+                    yield conn
+                    return
+            except psycopg.OperationalError as e:
+                logger.warning(f"数据库连接异常: {e}. 尝试重试 ({attempt+1}/{retries})")
+                self.pool.check()  # 丢掉坏连接，重新建
+                attempt += 1
+                time.sleep(delay)
+            except Exception as e:
+                logger.error(f"SQL执行异常: {e}")
+                raise
+        raise psycopg.OperationalError("无法获取数据库连接，多次重试失败")
+pg_pool = PGPool(
+    uri="postgresql://postgres:123456@10.10.10.9/ktor2",
+    min_size=1,
+    max_size=20,
+)
@@ -2,11 +2,81 @@ 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"
+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
-ssDB = SQLDatabase.from_uri(
+ssDBLC = SQLDatabase.from_uri(
    uri,
-    include_tables=["NONGHU_INFO"],  # 不加 schema 前缀试试
+    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
+
+logger = logging.getLogger("MSSQLPool")
+logger.setLevel(logging.INFO)
+
+class MSSQLPool:
+    """
+    SQL Server 连接池封装
+    """
+
+    def __init__(
+        self,
+        user: str,
+        password: str,
+        host: str,
+        database: str,
+        driver: str = "ODBC Driver 18 for SQL Server",
+        encrypt: str = "no",
+        trust_server_certificate: str = "yes",
+        min_size: int = 1,
+        max_size: int = 10,
+        pool_timeout: int = 10,
+    ):
+        self.user = user
+        self.password = quote_plus(password)  # 处理特殊字符
+        self.host = host
+        self.database = database
+        self.driver = driver
+        self.encrypt = encrypt
+        self.trust_server_certificate = trust_server_certificate
+
+        self.engine = create_engine(
+            f"mssql+pyodbc://{self.user}:{self.password}@{self.host}/{self.database}"
+            f"?driver={self.driver}&Encrypt={self.encrypt}&TrustServerCertificate={self.trust_server_certificate}",
+            pool_size=min_size,
+            max_overflow=max_size - min_size,
+            pool_timeout=pool_timeout,
+        )
+
+    @contextmanager
+    def getConn(self, retries: int = 2, delay: float = 1.0):
+        """
+        获取连接，带重试
+        """
+        attempt = 0
+        while attempt <= retries:
+            try:
+                with self.engine.connect() as conn:
+                    yield conn
+                    return
+            except SQLOperationalError as e:
+                logger.warning(f"数据库连接异常: {e}. 尝试重试 ({attempt+1}/{retries})")
+                attempt += 1
+                time.sleep(delay)
+            except Exception as e:
+                logger.error(f"SQL执行异常: {e}")
+                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",
+)