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lingyuzeng
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.gitignore
vendored
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.venv/
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Qwen-Agent/
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README.md
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README.md
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## Agent
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自建基于llama-box启动qwen3-code-flash-1M 的 AI Agent 代码仓库
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### llama-box 启动参数
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注意：
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添加 --enable-reasoning：这个参数对 Qwen3 模型的工具调用非常重要，能够提升推理能力。
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添加 --jinja：这个参数用于加载 Jinja 模板，Qwen3 模型需要使用 Jinja 模板进行推理。、
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启动参数参考：
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```bash
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llama-box \
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--host 0.0.0.0 \
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--port 8080 \
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--model /Volumes/long990max/gpustack_data/unsloth/Qwen3-Coder-30B-A3B-Instruct-1M-GGUF/Qwen3-Coder-30B-A3B-Instruct-1M-UD-Q4_K_XL.gguf \
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--chat-template chatml \
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--jinja \
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--enable-reasoning \
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--flash-attn \
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--cache-type-k q4_0 \
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--cache-type-v q4_0 \
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--ctx-size 262144 \
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--gpu-layers 49 \
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--threads 12 \
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--threads-batch 16 \
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--threads-http 16 \
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--batch-size 1024 \
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--ubatch-size 1024 \
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--defrag-thold -1 \
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--no-context-shift
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```
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### 安装环境
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```bash
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uv venv --managed-python -p 3.12 --seed .venv
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source .venv/bin/activate
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git clone https://github.com/hotwa/Qwen-Agent
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cd Qwen-Agent
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uv pip install -e ./"[gui,rag,code_interpreter,mcp]"
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cd ..
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python qwen3_coder_with_qwen_agent.py
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```
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qwen3_coder_with_qwen_agent.py
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qwen3_coder_with_qwen_agent.py
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"""
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Qwen3-Coder 使用 Qwen-Agent 框架测试示例
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这个示例演示了如何使用 Qwen-Agent 框架调用 qwen3-coder 模型进行工具调用测试。
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工具配置说明：
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1. MCP工具：通过'mcpServers'配置，需要安装对应的MCP服务器
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- time: 获取当前时间的MCP工具
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- fetch: 网络请求工具
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- filesystem: 文件系统操作工具
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这些工具需要额外安装对应的MCP服务器才能使用
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2. 原生工具：Qwen-Agent内置的工具，直接可用
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- 'code_interpreter': 代码解释器，可以执行Python代码
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- 'image_gen': 图像生成工具
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- 'web_search': 网络搜索工具
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- 'calculator'或'python_executor': Python代码执行器（可作为计算器）
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环境变量说明：
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- MAX_LLM_CALL_PER_RUN: 控制LLM调用的最大轮数（不是工具调用次数）
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这个限制是针对整个对话的LLM调用轮数，包括初始调用和后续基于工具结果的调用
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- MAX_TOOL_CALLS_PER_TURN: 控制每轮LLM输出中可触发的工具调用数量
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这个限制是针对单次LLM响应中可以触发的工具数量，防止模型一次性触发过多工具
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"""
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import os
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# 设置环境变量以控制工具调用行为
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# MAX_LLM_CALL_PER_RUN: 控制LLM调用的最大轮数（不是工具调用次数）
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# MAX_TOOL_CALLS_PER_TURN: 控制每轮LLM输出中可触发的工具调用数量
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os.environ["MAX_LLM_CALL_PER_RUN"] = "8"
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os.environ["MAX_TOOL_CALLS_PER_TURN"] = "8"
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import sys
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import traceback
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from pathlib import Path
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# 添加项目路径到Python路径
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project_root = Path(__file__).parent.parent.parent
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sys.path.insert(0, str(project_root))
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try:
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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.utils.output_beautify import typewriter_print
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except ImportError as e:
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print(f"❌ 导入失败: {e}")
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print("请确保已安装 qwen-agent: pip install qwen-agent")
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sys.exit(1)
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def init_agent_service():
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"""初始化Agent服务"""
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# 配置API参数，使用OpenAI兼容模式
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llm_cfg = {
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'model': 'qwen3-coder-flash-1M',
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'model_server': 'https://ai.jmsu.top/v1',
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'api_key': 'gpustack_96d105073565a038_23d7fe2768b4b27f9d92ab4661452ade',
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'generate_cfg': {
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# 使用API的原生工具调用接口
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'temperature': 0.7,
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'top_p': 0.8,
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'fncall_prompt_type': 'qwen', # 对 Qwen3 通常更稳
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},
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}
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# 配置工具
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tools = [
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{
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'mcpServers': { # 指定MCP配置
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'time': {
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'command': 'uvx',
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'args': ['mcp-server-time', '--local-timezone=Asia/Shanghai']
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},
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'fetch': {
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'command': 'uvx',
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'args': ['mcp-server-fetch']
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},
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'filesystem': {
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'command': 'npx',
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'args': [
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'-y',
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'@modelcontextprotocol/server-filesystem',
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'~/Desktop/'
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]
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},
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}
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},
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# 添加一些原生工具示例
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'code_interpreter', # 代码解释器
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'web_search', # 网络搜索
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]
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# 创建Agent
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bot = Assistant(
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llm=llm_cfg,
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function_list=tools,
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name='Qwen3-Coder Tool-calling Demo',
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description="I'm a demo using the Qwen3-Coder tool calling. Welcome to add and play with your own tools!"
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)
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return bot
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def test(query: str = '现在几点了？'):
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"""测试函数"""
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print("=== Qwen3-Coder 使用 Qwen-Agent 测试 ===\n")
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# 初始化Agent
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bot = init_agent_service()
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# 进行对话
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messages = [{'role': 'user', 'content': query}]
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print(f"💬 用户: {query}")
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print("🤖 助手: ", end='', flush=True)
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# 缓存最终回复内容
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final_response = ""
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current_tool_call = ""
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in_tool_call = False
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try:
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for response in bot.run(messages=messages):
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# 处理响应
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if response:
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for msg in response:
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if msg['role'] == 'assistant':
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if msg.get('content'):
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# 检查是否包含工具调用标记
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if '[TOOL_CALL]' in msg['content']:
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in_tool_call = True
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current_tool_call = msg['content']
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# 清空之前的输出，准备显示工具调用
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print(f"\r🤖 助手: {msg['content']}", end='', flush=True)
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elif in_tool_call:
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# 继续工具调用信息
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current_tool_call += msg['content']
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print(msg['content'], end='', flush=True)
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else:
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# 普通回复内容
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final_response += msg['content']
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# 不再实时打印，等待工具调用完成后统一显示
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# print(msg['content'], end='', flush=True)
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elif msg['role'] == 'function':
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# 工具响应，显示工具结果
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in_tool_call = False
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print(f"\n[TOOL_RESPONSE] {msg.get('name', 'unknown')}")
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print(msg.get('content', ''))
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# 重置最终回复内容，准备接收新的回复
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final_response = ""
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# 输出最终结果
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if final_response:
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print("\r🤖 助手: ", end='', flush=True)
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print(final_response, end='', flush=True)
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print() # 输出完成后换行
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except Exception as e:
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print(f"\n❌ 调用失败: {e}")
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import traceback
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traceback.print_exc()
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def app_tui():
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"""命令行交互模式"""
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print("=== Qwen3-Coder 使用 Qwen-Agent 命令行交互模式 ===\n")
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# 初始化Agent
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bot = init_agent_service()
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# 进行对话
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messages = []
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while True:
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query = input('user question: ')
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if query.lower() in ['quit', 'exit', '退出']:
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print("👋 再见!")
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break
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messages.append({'role': 'user', 'content': query})
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response = []
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response_plain_text = ''
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print("🤖 助手: ", end='', flush=True)
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try:
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for response in bot.run(messages=messages):
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# 添加调试信息
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# print(f"[DEBUG] 收到响应: {type(response)}", file=sys.stderr)
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# 使用 typewriter_print 实现流式输出
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if response:
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try:
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response_plain_text = typewriter_print(response, response_plain_text)
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except Exception as e:
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# 如果typewriter_print出错，尝试直接打印
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# print(f"[WARNING] typewriter_print出错: {e}", file=sys.stderr)
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if isinstance(response, list):
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for item in response:
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if isinstance(item, dict) and 'content' in item:
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print(item['content'], end='', flush=True)
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elif isinstance(item, dict) and 'message' in item:
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print(item['message'], end='', flush=True)
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print() # 输出完成后换行
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messages.extend(response)
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except Exception as e:
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print(f"\n❌ 调用失败: {e}")
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import traceback
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traceback.print_exc()
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def app_gui():
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"""图形界面模式"""
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# 初始化Agent
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bot = init_agent_service()
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chatbot_config = {
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'prompt.suggestions': [
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'现在几点了？',
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'请用Python写一个计算斐波那契数列的函数',
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'帮我搜索一下Python装饰器的用法'
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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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def main():
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"""主函数"""
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print("🚀 Qwen3-Coder 使用 Qwen-Agent 测试示例")
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print("=" * 50)
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print("\n请选择运行模式:")
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print("1. 简单测试 - 固定问题")
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print("2. 命令行交互模式")
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print("3. 图形界面模式")
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choice = input("\n请输入选项 (1-3): ").strip()
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if choice == "1":
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test()
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elif choice == "2":
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app_tui()
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elif choice == "3":
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app_gui()
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else:
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print("❌ 无效选项，运行默认测试")
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test()
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if __name__ == '__main__':
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main()
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