47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
from config import OPENAI_API_KEY
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import sqlite3
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from langchain_openai import ChatOpenAI
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from langchain_community.agent_toolkits import create_sql_agent
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from langchain_community.utilities import SQLDatabase # 导入 SQLDatabase
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import os
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# 配置llm
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llm = ChatOpenAI(
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model="deepseek-chat",
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api_key=OPENAI_API_KEY,
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base_url="https://api.deepseek.com"
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)
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# 创建一个临时的数据库--用于演示
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db_file = "test_sql.db"
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if os.path.exists(db_file):
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os.remove(db_file)
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conn = sqlite3.connect(db_file)
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cursor = conn.cursor()
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cursor.execute("CREATE TABLE users (id INT,name TEXT,age INT);")
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cursor.execute("INSERT INTO users (id,name,age) VALUES (1,'Alice',30);")
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cursor.execute("INSERT INTO users (id,name,age) VALUES (2,'Bob',25);")
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conn.commit()
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conn.close()
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# 连接数据库 -- LangChain 使用 SQLAlchemy URI (连接方式)
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db_uri = f'sqlite:///{db_file}'
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db = SQLDatabase.from_uri(db_uri)
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# 创建sqlAgent -- 一键完成，无需定义tools，仅告诉它使用openai-tools,即Tool Calling(工具调用)模式
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agent_executor = create_sql_agent(
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llm=llm,
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db=db,
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agent_type="openai-tools",
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verbose=True
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)
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# 运行
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response = agent_executor.invoke({"input":"告诉我Alice多大了？"})
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print(response['output'])
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# 清理
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db._engine.dispose() # 关闭连接池，避免文件被占用
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if os.path.exists(db_file):
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os.remove(db_file)
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