add docker
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.dockerignore
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56
.dockerignore
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# Git
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.git
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.gitignore
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# Python
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__pycache__
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*.pyc
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*.pyo
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*.pyd
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.Python
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env
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pip-log.txt
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pip-delete-this-directory.txt
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.tox
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.log
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.git
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.mypy_cache
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.pytest_cache
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.hypothesis
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# Virtual environments
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venv/
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env/
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ENV/
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# OS
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.DS_Store
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.DS_Store?
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._*
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.Spotlight-V100
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.Trashes
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ehthumbs.db
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Thumbs.db
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# Project specific
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logs/
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projects/_cache/
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*.zip
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# Docker
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Dockerfile
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docker-compose.yml
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.dockerignore
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44
Dockerfile
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44
Dockerfile
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# 使用Python 3.12官方镜像作为基础镜像
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FROM python:3.12-slim
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# 设置工作目录
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WORKDIR /app
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# 设置环境变量
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ENV PYTHONPATH=/app
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ENV PYTHONUNBUFFERED=1
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ENV AGENT_POOL_SIZE=1
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# 安装系统依赖
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RUN sed -i 's|http://deb.debian.org|http://mirrors.aliyun.com|g' /etc/apt/sources.list.d/debian.sources && \
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apt-get update && apt-get install -y \
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curl \
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wget \
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git \
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nodejs \
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npm \
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ripgrep \
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&& rm -rf /var/lib/apt/lists/*
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# 复制requirements文件并安装Python依赖
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COPY requirements.txt .
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RUN pip install --no-cache-dir -i https://mirrors.aliyun.com/pypi/simple/ -r requirements.txt
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# 复制应用代码
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COPY . .
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# 创建必要的目录
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RUN mkdir -p /app/projects
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# 设置权限
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RUN chmod +x /app/mcp/json_reader_server.py
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# 暴露端口
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EXPOSE 8000
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# 健康检查
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HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8000/ || exit 1
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# 启动命令
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CMD ["python", "fastapi_app.py"]
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Binary file not shown.
24
docker-compose.yml
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docker-compose.yml
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version: "3.8"
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services:
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qwen-agent:
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build: .
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container_name: qwen-agent-api
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ports:
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- "8000:8000"
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environment:
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# 应用配置
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- PYTHONPATH=/app
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- PYTHONUNBUFFERED=1
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- AGENT_POOL_SIZE=2
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volumes:
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# 挂载项目数据目录
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- ./projects:/app/projects
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restart: unless-stopped
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 40s
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@ -1,6 +1,7 @@
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import json
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import os
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from typing import AsyncGenerator, Dict, List, Optional, Union
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from contextlib import asynccontextmanager
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import uvicorn
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from fastapi import BackgroundTasks, FastAPI, HTTPException
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@ -42,12 +43,40 @@ from agent_pool import (get_agent_from_pool, init_global_agent_pool,
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from gbase_agent import init_agent_service_universal, update_agent_llm
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from zip_project_handler import zip_handler
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app = FastAPI(title="Database Assistant API", version="1.0.0")
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# 全局助手实例池，在应用启动时初始化
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agent_pool_size = int(os.getenv("AGENT_POOL_SIZE", "1"))
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""应用生命周期管理"""
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# 启动时初始化助手实例池
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print(f"正在启动FastAPI应用，初始化助手实例池（大小: {agent_pool_size}）...")
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try:
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def agent_factory():
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return init_agent_service_universal()
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await init_global_agent_pool(pool_size=agent_pool_size, agent_factory=agent_factory)
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print("助手实例池初始化完成！")
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yield
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except Exception as e:
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print(f"助手实例池初始化失败: {e}")
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raise
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# 关闭时清理实例池
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print("正在关闭应用，清理助手实例池...")
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from agent_pool import get_agent_pool
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pool = get_agent_pool()
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if pool:
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await pool.shutdown()
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print("助手实例池清理完成！")
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app = FastAPI(title="Database Assistant API", version="1.0.0", lifespan=lifespan)
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class Message(BaseModel):
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role: str
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content: str
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@ -279,32 +308,6 @@ async def cleanup_cache():
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raise HTTPException(status_code=500, detail=f"缓存清理失败: {str(e)}")
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@app.on_event("startup")
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async def startup_event():
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"""应用启动时初始化助手实例池"""
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print(f"正在启动FastAPI应用，初始化助手实例池（大小: {agent_pool_size}）...")
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try:
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def agent_factory():
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return init_agent_service_universal()
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await init_global_agent_pool(pool_size=agent_pool_size, agent_factory=agent_factory)
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print("助手实例池初始化完成！")
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except Exception as e:
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print(f"助手实例池初始化失败: {e}")
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raise
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@app.on_event("shutdown")
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async def shutdown_event():
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"""应用关闭时清理实例池"""
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print("正在关闭应用，清理助手实例池...")
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from agent_pool import get_agent_pool
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pool = get_agent_pool()
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if pool:
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await pool.shutdown()
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print("助手实例池清理完成！")
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if __name__ == "__main__":
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@ -21,7 +21,6 @@ import os
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from typing import Dict, List, Optional, Union
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from qwen_agent.agents import Assistant
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from qwen_agent.gui import WebUI
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from qwen_agent.llm.oai import TextChatAtOAI
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from qwen_agent.llm.schema import ASSISTANT, FUNCTION, Message
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from qwen_agent.utils.output_beautify import typewriter_print
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@ -169,67 +168,3 @@ def test(query="数据库里有几张表"):
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final_response = responses[-1][-1] # 取最后一个响应作为最终结果
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print("Answer:", final_response["content"])
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def app_tui():
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# Define the agent - 使用通用初始化
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bot = init_agent_service_universal()
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# Chat
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messages = []
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while True:
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# Query example: 数据库里有几张表
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query = input("user question: ")
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# File example: resource/poem.pdf
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file = input("file url (press enter if no file): ").strip()
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if not query:
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print("user question cannot be empty！")
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continue
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if not file:
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messages.append({"role": "user", "content": query})
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else:
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messages.append(
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{"role": "user", "content": [{"text": query}, {"file": file}]}
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)
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response = []
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for response in bot.run(messages):
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print("bot response:", response)
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messages.extend(response)
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def app_gui():
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# Define the agent - 使用通用初始化
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bot = init_agent_service_universal()
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chatbot_config = {
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"prompt.suggestions": [
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"数据库里有几张表",
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"创建一个学生表包括学生的姓名、年龄",
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"增加一个学生名字叫韩梅梅，今年6岁",
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]
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}
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WebUI(
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bot,
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chatbot_config=chatbot_config,
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).run()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="数据库助手")
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parser.add_argument(
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"--query", type=str, default="数据库里有几张表", help="用户问题"
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)
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parser.add_argument(
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"--mode",
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type=str,
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choices=["test", "tui", "gui"],
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default="test",
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help="运行模式",
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)
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args = parser.parse_args()
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if args.mode == "test":
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test(args.query)
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elif args.mode == "tui":
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app_tui()
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elif args.mode == "gui":
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app_gui()
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13
requirements.txt
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13
requirements.txt
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# FastAPI和Web服务器
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fastapi==0.116.1
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uvicorn==0.35.0
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# HTTP客户端
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requests==2.32.5
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# Qwen Agent框架
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qwen-agent[mcp]==0.0.29
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# 数据处理
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pydantic==2.10.5
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python-dateutil==2.8.2
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