feat: 实现 RAG SQL生成系统的后端接口和前端页面

- 新增后端 API，使用 FastAPI 框架实现
- 创建前端聊天界面，使用 HTML 和 JavaScript 实现
- 添加环境变量配置文件，支持不同环境的配置
- 实现与 MySQL 和 pgvector 数据库的连接和查询
- 集成大语言模型和向量模型，用于生成 SQL 语句

.env.dev

@@ -0,0 +1,58 @@
+# -------- 应用配置 --------
+# 应用运行环境
+APP_ENV = 'dev'
+# 应用名称
+APP_NAME = '规则生成系统'
+# 应用代理路径
+# APP_ROOT_PATH = '/rule'
+APP_ROOT_PATH = ''
+# 应用主机
+APP_HOST = '0.0.0.0'
+# 应用端口
+APP_PORT = 9099
+# 应用版本
+APP_VERSION= '1.0.0'
+# 应用是否开启热重载
+APP_RELOAD = true
+# 应用是否开启IP归属区域查询
+APP_IP_LOCATION_QUERY = true
+# 应用是否允许账号同时登录
+APP_SAME_TIME_LOGIN = true
+# 是否允许接口直接执行sql进行测试
+APP_TSET_SQL = false
+
+# -------- mysql数据库配置 --------
+# 数据库主机
+MYSQL_DB_HOST = 'ngsk.tech'
+# 数据库端口
+MYSQL_DB_PORT = 33306
+# 数据库用户名
+MYSQL_DB_USERNAME = 'root'
+# 数据库密码
+MYSQL_DB_PASSWORD = 'ngsk0809cruise'
+# 数据库名称
+MYSQL_DB_DATABASE = 'data_governance'
+
+
+# -------- pgvector数据库配置 --------
+# 数据库主机
+PG_DB_HOST = '192.168.5.30'
+# 数据库端口
+PG_DB_PORT = 5432
+# 数据库用户名
+PG_DB_USERNAME = 'myuser'
+# 数据库密码
+PG_DB_PASSWORD = 'mypassword'
+# 数据库名称
+PG_DB_DATABASE = 'vectordb'
+
+# -------- 大语言模型配置 --------
+llm_base_url = 'http://192.168.5.20:4090/v1'
+llm_api_key = 'gpustack_951f92355e6781a5_5d17650a3e7135c5430512e5117362fb'
+llm_model = 'qwen3-30b-a3b-instruct-2507'
+
+# -------- 向量模型配置 --------
+emb_base_url = 'http://192.168.5.20:4090/v1'
+emb_api_key = 'gpustack_951f92355e6781a5_5d17650a3e7135c5430512e5117362fb'
+emb_model = 'bge-m3'
+

.env.prod

@@ -0,0 +1,87 @@
+# -------- 应用配置 --------
+# 应用运行环境
+APP_ENV = 'prod'
+# 应用名称
+APP_NAME = '电网智能巡航系统'
+# 应用代理路径
+# APP_ROOT_PATH = '/cruise'
+APP_ROOT_PATH = ''
+# 应用主机
+APP_HOST = '0.0.0.0'
+# 应用端口
+APP_PORT = 9099
+# 应用版本
+APP_VERSION= '1.6.1'
+# 应用是否开启热重载
+APP_RELOAD = true
+# 应用是否开启IP归属区域查询
+APP_IP_LOCATION_QUERY = true
+# 应用是否允许账号同时登录
+APP_SAME_TIME_LOGIN = true
+# 是否允许接口直接执行sql进行测试
+APP_TSET_SQL = true
+
+# -------- Jwt配置 --------
+# Jwt秘钥
+JWT_SECRET_KEY = 'b01c66dc2c58dc6a0aabfe2144256be36226de378bf87f72c0c795dda67f4d55'
+# Jwt算法
+JWT_ALGORITHM = 'HS256'
+# 令牌过期时间
+JWT_EXPIRE_MINUTES = 1440
+# redis中令牌过期时间
+JWT_REDIS_EXPIRE_MINUTES = 300
+
+
+# -------- 数据库1配置 --------
+# 数据库类型，可选的有'mysql'、'postgresql'，默认为'mysql'
+DB_TYPE = 'mysql'
+# 数据库主机
+DB_HOST = '10.92.176.60'
+# 数据库端口
+DB_PORT = 13306
+# 数据库用户名
+DB_USERNAME = 'root'
+# 数据库密码
+DB_PASSWORD = 'root'
+# 数据库名称
+DB_DATABASE = 'cruise'
+# 是否开启sqlalchemy日志
+DB_ECHO = true
+# 允许溢出连接池大小的最大连接数
+DB_MAX_OVERFLOW = 10
+# 连接池大小，0表示连接数无限制
+DB_POOL_SIZE = 50
+# 连接回收时间（单位：秒）
+DB_POOL_RECYCLE = 3600
+# 连接池中没有线程可用时，最多等待的时间（单位：秒）
+DB_POOL_TIMEOUT = 30
+
+# -------- 数据库2配置 --------
+DB2_TYPE = 'mysql'
+# 数据库主机
+DB2_HOST = '10.92.176.60'
+# 数据库端口
+DB2_PORT = 13306
+# 数据库用户名
+DB2_USERNAME = 'root'
+# 数据库密码
+DB2_PASSWORD = 'root'
+# 数据库名称
+DB2_DATABASE = 'operationrisk'
+
+# -------- Redis配置 --------
+# Redis主机
+REDIS_HOST = '10.92.176.60'
+# Redis端口
+REDIS_PORT = 16379
+# Redis用户名
+REDIS_USERNAME = ''
+# Redis密码
+REDIS_PASSWORD = ''
+# Redis数据库
+REDIS_DATABASE = 2
+
+AI_BASE_URL = 'http://192.168.196.140:1025/v1'
+AI_API_KEY = 'ollama'
+AI_MODEL_NAME = 'deepseek-r1:14b'
+AI_DAILY_REPORT_URL = 'http://192.168.196.140:19013/sgd/'

Dockerfile

@@ -0,0 +1,19 @@
+# 使用官方 Python 基础镜像
+FROM hub.1panel.dev/library/python:3.12-slim
+
+# 设置工作目录
+WORKDIR /app
+
+# 将当前目录下的所有文件复制到容器中的 /app 目录
+COPY . /app
+
+# 安装依赖
+#RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
+RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ -r requirements.txt
+
+
+# 暴露应用程序运行的端口（如果需要）
+EXPOSE 9099
+
+# 启动命令
+CMD ["python", "app.py","--env=prod"]

backend.py

@@ -0,0 +1,66 @@
+# backend.py
+from contextlib import asynccontextmanager
+from fastapi import FastAPI, HTTPException, Request, APIRouter
+from pydantic import BaseModel
+import asyncio
+
+from starlette.middleware.cors import CORSMiddleware
+
+from rag import rag_generate_rule
+
+@asynccontextmanager
+async def lifespan(app : FastAPI):
+    # logger.info(f'{AppConfig.app_name}开始启动，当前运行环境{os.environ.get('APP_ENV', '未读取到环境变量APP_ENV')}')
+    print(f'开始启动')
+    print(f'启动成功')
+    yield
+    print(f'关闭成功')
+
+app = FastAPI(title="RAG SQL Generator API", description="调用RAG生成SQL语句的后端服务", lifespan=lifespan)
+
+rule_router = APIRouter(prefix="/rule")
+
+# 添加CORS中间件 - 允许所有来源（开发环境）
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # 在生产环境中应该指定具体的域名
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class QueryRequest(BaseModel):
+    query: str
+
+class QueryResponse(BaseModel):
+    sql: str
+
+@rule_router.post("/generate_sql", response_model=QueryResponse)
+async def generate_sql(request: QueryRequest):
+    """
+    接收用户问题并调用RAG生成SQL语句
+
+    - **query**: 用户的自然语言问题
+    - 返回生成的SQL语句
+    """
+    try:
+        # 调用rag_generate_rule方法生成SQL
+        result = await rag_generate_rule(request.query)
+        return QueryResponse(sql=result)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"生成SQL时出错: {str(e)}")
+
+@rule_router.get("/health")
+async def health_check():
+    """
+    健康检查端点
+    """
+    return {"status": "healthy"}
+
+
+# 注册带前缀的路由器
+app.include_router(rule_router)
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

env.py

@@ -0,0 +1,129 @@
+import argparse
+import os
+import sys
+from dotenv import load_dotenv
+from functools import lru_cache
+from pydantic import computed_field
+from pydantic_settings import BaseSettings
+from typing import Literal
+
+
+
+class GetConfig:
+
+    def __init__(self):
+        self.parse_cli_args()
+
+    @lru_cache()
+    def get_llm_config(self):
+        return LlmSettings()
+
+    @lru_cache()
+    def get_emb_config(self):
+        return EmbSettings()
+
+    @lru_cache()
+    def get_mysql_database_config(self):
+        """
+        获取数据库配置
+        """
+        # 实例化数据库配置模型
+        return MysqlDataBaseSettings()
+
+    @lru_cache()
+    def get_pgvector_database_config(self):
+        """
+        获取数据库配置
+        """
+        # 实例化数据库配置模型
+        return PgvectorDataBaseSettings()
+
+    @staticmethod
+    def parse_cli_args():
+        """
+        解析命令行参数
+        """
+        if 'uvicorn' in sys.argv[0]:
+            # 使用uvicorn启动时，命令行参数需要按照uvicorn的文档进行配置，无法自定义参数
+            pass
+        else:
+            # 使用argparse定义命令行参数
+            parser = argparse.ArgumentParser(description='命令行参数')
+            parser.add_argument('--env', type=str, default='', help='运行环境')
+            # 解析命令行参数
+            args = parser.parse_args()
+            # 设置环境变量，如果未设置命令行参数，默认APP_ENV为dev
+            os.environ['APP_ENV'] = args.env if args.env else 'dev'
+        # 读取运行环境
+        run_env = os.environ.get('APP_ENV', '')
+        # 运行环境未指定时默认加载.env.dev
+        env_file = '.env.dev'
+        # 运行环境不为空时按命令行参数加载对应.env文件
+        if run_env != '':
+            env_file = f'.env.{run_env}'
+        # 加载配置
+        load_dotenv(env_file)
+        print(f'当前运行环境为：{run_env}')
+        print(os.getenv("DB_HOST"))
+
+# 实例化获取配置类
+get_config = GetConfig()
+
+class LlmSettings:
+    """
+    AI配置
+    """
+    base_url: str = os.getenv('llm_base_url', '')
+    api_key: str = os.getenv('llm_api_key', '')
+    model_name: str = os.getenv('llm_model', '')
+
+class EmbSettings:
+    """
+    AI配置
+    """
+    base_url: str = os.getenv('emb_base_url', '')
+    api_key: str = os.getenv('emb_api_key', '')
+    model_name: str = os.getenv('emb_model', '')
+
+class MysqlDataBaseSettings:
+    """
+    数据库配置
+    """
+    # 数据库配置
+    db_host: str = os.getenv('MYSQL_DB_HOST', '')
+    db_port: int = int(os.getenv('MYSQL_DB_PORT', 33306))
+    db_username: str = os.getenv('MYSQL_DB_USERNAME', '')
+    db_password: str = os.getenv('MYSQL_DB_PASSWORD', '')
+    db_database: str = os.getenv('MYSQL_DB_DATABASE', '')
+
+    db_echo: bool = True
+    db_max_overflow: int = 10
+    db_pool_size: int = 50
+    db_pool_recycle: int = 3600
+    db_pool_timeout: int = 30
+
+class PgvectorDataBaseSettings:
+    """
+    数据库配置
+    """
+    # 数据库配置
+    db_host: str = os.getenv('PG_DB_HOST', '')
+    db_port: int = os.getenv('PG_DB_PORT', 5432)
+    db_username: str = os.getenv('PG_DB_USERNAME', '')
+    db_password: str = os.getenv('PG_DB_PASSWORD', '')
+    db_database: str = os.getenv('PG_DB_DATABASE', '')
+
+    db_echo: bool = True
+    db_max_overflow: int = 10
+    db_pool_size: int = 50
+    db_pool_recycle: int = 3600
+    db_pool_timeout: int = 30
+
+
+# mysql数据库配置
+MysqlDataBaseConfig = get_config.get_mysql_database_config()
+# pgvector数据库配置
+PgvectorDataBaseConfig = get_config.get_pgvector_database_config()
+
+LlmBaseConfig = get_config.get_llm_config()
+EmbBaseConfig = get_config.get_emb_config()

index.html

@@ -0,0 +1,224 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>SQL生成聊天界面</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 800px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #f5f5f5;
+        }
+
+        .chat-container {
+            background-color: white;
+            border-radius: 10px;
+            box-shadow: 0 2px 10px rgba(0,0,0,0.1);
+            padding: 20px;
+            margin-bottom: 20px;
+            height: 500px;
+            overflow-y: auto;
+        }
+
+        .message {
+            margin-bottom: 15px;
+            padding: 10px;
+            border-radius: 8px;
+            max-width: 80%;
+        }
+
+        .user-message {
+            background-color: #dcf8c6;
+            margin-left: auto;
+        }
+
+        .bot-message {
+            background-color: #e5e5ea;
+            margin-right: auto;
+        }
+
+        .input-container {
+            display: flex;
+            gap: 10px;
+        }
+
+        #user-input {
+            flex: 1;
+            padding: 12px;
+            border: 1px solid #ddd;
+            border-radius: 20px;
+            outline: none;
+        }
+
+        #send-button {
+            padding: 12px 24px;
+            background-color: #4CAF50;
+            color: white;
+            border: none;
+            border-radius: 20px;
+            cursor: pointer;
+        }
+
+        #send-button:disabled {
+            background-color: #cccccc;
+            cursor: not-allowed;
+        }
+
+        .loading {
+            text-align: center;
+            color: #666;
+            font-style: italic;
+        }
+
+        .sql-result {
+            font-family: monospace;
+            background-color: #f8f8f8;
+            padding: 10px;
+            border-left: 4px solid #4CAF50;
+            white-space: pre-wrap;
+            overflow-x: auto;
+        }
+
+        .error-message {
+            color: #f44336;
+            background-color: #ffebee;
+            padding: 10px;
+            border-radius: 5px;
+        }
+    </style>
+</head>
+<body>
+    <h1>SQL生成聊天助手</h1>
+    <div class="chat-container" id="chat-container">
+        <div class="message bot-message">
+            您好！请描述您需要生成SQL的需求，我会为您生成相应的SQL语句。
+        </div>
+    </div>
+
+    <div class="input-container">
+        <input type="text" id="user-input" placeholder="请输入您的问题..." />
+        <button id="send-button">发送</button>
+    </div>
+
+    <script>
+        const chatContainer = document.getElementById('chat-container');
+        const userInput = document.getElementById('user-input');
+        const sendButton = document.getElementById('send-button');
+
+        // 添加消息到聊天界面
+        function addMessage(text, isUser = false, isSQL = false, isError = false) {
+            const messageDiv = document.createElement('div');
+            messageDiv.className = `message ${isUser ? 'user-message' : 'bot-message'}`;
+
+            if (isSQL) {
+                const sqlDiv = document.createElement('div');
+                sqlDiv.className = 'sql-result';
+                sqlDiv.textContent = text;
+                messageDiv.appendChild(sqlDiv);
+            } else if (isError) {
+                messageDiv.className = 'error-message';
+                messageDiv.textContent = text;
+            } else {
+                messageDiv.textContent = text;
+            }
+
+            chatContainer.appendChild(messageDiv);
+            chatContainer.scrollTop = chatContainer.scrollHeight;
+        }
+
+        // 显示加载状态
+        function showLoading() {
+            const loadingDiv = document.createElement('div');
+            loadingDiv.className = 'message bot-message loading';
+            loadingDiv.id = 'loading-message';
+            loadingDiv.textContent = '正在生成SQL，请稍候...';
+            chatContainer.appendChild(loadingDiv);
+            chatContainer.scrollTop = chatContainer.scrollHeight;
+
+            // 禁用输入和发送按钮
+            userInput.disabled = true;
+            sendButton.disabled = true;
+            sendButton.textContent = '处理中...';
+        }
+
+        // 隐藏加载状态
+        function hideLoading() {
+            const loadingMessage = document.getElementById('loading-message');
+            if (loadingMessage) {
+                loadingMessage.remove();
+            }
+
+            // 启用输入和发送按钮
+            userInput.disabled = false;
+            sendButton.disabled = false;
+            sendButton.textContent = '发送';
+        }
+
+        // 调用后端API生成SQL
+        async function generateSQL(query) {
+            try {
+                const response = await fetch('http://localhost:8000/rule/generate_sql', {
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    },
+                    body: JSON.stringify({ query: query })
+                });
+
+                if (!response.ok) {
+                    const errorData = await response.json();
+                    throw new Error(errorData.detail || '请求失败');
+                }
+
+                const data = await response.json();
+                return data.sql;
+            } catch (error) {
+                throw new Error(`API调用失败: ${error.message}`);
+            }
+        }
+
+        // 处理用户发送消息
+        async function handleSendMessage() {
+            const query = userInput.value.trim();
+            if (!query) return;
+
+            // 添加用户消息
+            addMessage(query, true);
+            userInput.value = '';
+
+            // 显示加载状态
+            showLoading();
+
+            try {
+                // 调用后端生成SQL
+                const sqlResult = await generateSQL(query);
+
+                // 隐藏加载状态
+                hideLoading();
+
+                // 显示SQL结果
+                addMessage(sqlResult, false, true);
+            } catch (error) {
+                // 隐藏加载状态
+                hideLoading();
+
+                // 显示错误信息
+                addMessage(`错误: ${error.message}`, false, false, true);
+            }
+        }
+
+        // 绑定发送按钮点击事件
+        sendButton.addEventListener('click', handleSendMessage);
+
+        // 绑定回车键发送事件
+        userInput.addEventListener('keypress', (e) => {
+            if (e.key === 'Enter') {
+                handleSendMessage();
+            }
+        });
+    </script>
+</body>
+</html>

requirements.txt

@@ -0,0 +1,9 @@
+aiomysql==0.2.0
+fastapi==0.116.1
+numpy==2.3.2
+openai==1.99.6
+pandas==2.3.1
+psycopg2_binary==2.9.10
+pydantic==2.11.7
+starlette==0.47.2
+uvicorn==0.35.0

util/use_mysql.py

@@ -2,6 +2,9 @@ import asyncio
 import aiomysql
 from typing import List, Dict, Any, Optional
 
+from env import MysqlDataBaseConfig
+
+
 class AsyncMySQLClient:
     def __init__(self, host: str, port: int, user: str, password: str, db: str):
         """
@@ -142,6 +145,8 @@ async def search_desc_by_table_names(table_name_list : list, db_client: AsyncMyS
             })
 
         return ans
+    except Exception as e:
+        print(f"查询失败: {e}")
     finally:
         # 关闭连接
         await db_client.close()
@@ -186,11 +191,11 @@ async def insert(data : list[dict[str, Any]], db_client: AsyncMySQLClient):
 
 # 创建数据库客户端实例
 db_client = AsyncMySQLClient(
-    host='ngsk.tech',
+    host=MysqlDataBaseConfig.db_host,
-    port=33306,
+    port=MysqlDataBaseConfig.db_port,
-    user='root',
+    user=MysqlDataBaseConfig.db_username,
-    password='ngsk0809cruise',
+    password=MysqlDataBaseConfig.db_password,
-    db='data_governance'
+    db=MysqlDataBaseConfig.db_database
 )
 async def get_db():
     # 创建数据库客户端实例

util/use_opanai.py

@@ -1,14 +1,20 @@
 from openai import AsyncOpenAI
 
-client = AsyncOpenAI(
+from env import LlmBaseConfig, EmbBaseConfig
-    api_key="gpustack_951f92355e6781a5_5d17650a3e7135c5430512e5117362fb",
+
-    base_url="http://192.168.5.20:4090/v1",
+llm_client = AsyncOpenAI(
+    api_key=LlmBaseConfig.api_key,
+    base_url=LlmBaseConfig.base_url,
 )
 
+emb_client = AsyncOpenAI(
+    api_key=EmbBaseConfig.api_key,
+    base_url=EmbBaseConfig.base_url,
+)
 
 async def generation_rule(prompt):
-  response = await client.chat.completions.create(
+  response = await llm_client.chat.completions.create(
-    model="qwen3-30b-a3b-instruct-2507",
+    model=LlmBaseConfig.model_name,
     messages=prompt,
     n = 1,
     stream = False,
@@ -22,8 +28,8 @@ async def generation_rule(prompt):
   return response.choices[0].message.content
 
 async def generation_vector(text):
-  response = await client.embeddings.create(
+  response = await emb_client.embeddings.create(
-    model="bge-m3",  # 替换为实际的向量模型名称
+    model=EmbBaseConfig.model_name,  # 替换为实际的向量模型名称
     input=text,
     encoding_format="float"
   )
@@ -52,8 +58,8 @@ async def rerank_documents(query, documents, top_n=None):
       }
     ]
 
-    response = await client.chat.completions.create(
+    response = await llm_client.chat.completions.create(
-      model="qwen3-30b-a3b-instruct-2507",  # 使用已知可用的模型
+      model=LlmBaseConfig.model_name,  # 使用已知可用的模型
       messages=messages,
       temperature=0.0,
       max_tokens=100

util/use_pgvector.py

@@ -2,13 +2,15 @@ import psycopg2
 from psycopg2.extras import execute_values
 import numpy as np
 
+from env import PgvectorDataBaseConfig
+
 # 数据库连接配置
 DB_CONFIG = {
-    "host": "192.168.5.30",
+    "host": PgvectorDataBaseConfig.db_host,
-    "database": "vectordb",
+    "database": PgvectorDataBaseConfig.db_database,
-    "user": "myuser",
+    "user": PgvectorDataBaseConfig.db_username,
-    "password": "mypassword",
+    "password": PgvectorDataBaseConfig.db_password,
-    "port": 5432
+    "port": PgvectorDataBaseConfig.db_port
 }