手把手教你使用Qwen-Agent开发智能体应用实战教程

# 全功能安装（RAG/代码解释器/GUI支持）pip install -U "qwen-agent[rag,code_interpreter,python_executor,gui]"
# 简约安装版本pip install -U qwen-agent

export DASHSCOPE_API_KEY='your-api-key'

from vllm import LLM, SamplingParams
llm = LLM(model="Qwen2-7B-Chat")

from qwen_agent.tools.base import BaseTool, register_toolimport json5
@register_tool('calculate')class Calculator(BaseTool):description = '基础运算计算器'parameters = [{'name': 'formula', 'type': 'string'}]def call(self, params: str) -> float:return eval(json5.loads(params)['formula'])
# 调用示例calc = Calculator()print(calc.call('{"formula": "(3 + 5) * 2"}'))# 输出 16.0

from qwen_agent.agents import Assistant
class HistoryAssistant(Assistant):def _postprocess_messages(self, messages):return messages[-10:]# 保留最近5轮对话
assistant = HistoryAssistant(llm={'model': 'qwen-max'})

from qwen_agent.agents import Assistantfrom qwen_agent.tools import BaseTool, register_toolimport requestsimport json5
@register_tool('city_info')class CityInfoTool(BaseTool):description = "城市基础信息查询"parameters = [{'name': 'name', 'type': 'string'}]def call(self, params):city = json5.loads(params)['name']response = requests.get(f"https://api.example.com/cities/{city}")return response.json()
# 配置助手assistant = Assistant(llm={'model': 'qwen-max'},function_list=['city_info','code_interpreter'],system_message="你是一个城市百科助手")
# 测试查询response = assistant.run([{'role': 'user', 'content': '上海有多少个行政区?'}])print(response[-1]['content'])

import urllibfrom qwen_agent.agents import Assistant
assistant = Assistant(function_list=['code_interpreter'],system_message="图像处理专家")
def process_image(prompt):messages = [{'role':'user', 'content': prompt}]for resp in assistant.run(messages):if 'function_call' in resp:code = resp['function_call']['arguments']exec(code)# 示例简化执行return resp[-1]['content']
process_image('将https://example.com/image.jpg的水平宽度扩大1.5倍')

from qwen_agent import retrieve
# 构建知识库retrieve.build_index('documents/')
class DocQA(Assistant):def _preprocess(self, query):contexts = retrieve.search(query)return f"根据文档：{contexts}n回答：{query}"
qa = DocQA(llm={'model': 'qwen-max-longcontext'})

from qwen_agent.gui import WebUI
WebUI(assistant).launch(server_name='0.0.0.0', server_port=7860)

class CustomerService(Assistant):def __init__(self):super().__init__(system_message="你是XX公司客服，回答范围限于产品功能和订单查询",function_list=[product_lookup, order_status])def _validate_query(self, query):if '价格' in query:return "具体产品价格请访问官网查询"return super()._validate_query(query)

@register_tool('data_analysis')class DataAnalyzer:def call(self, params):df = pd.read_csv(params['file'])return df.describe().to_markdown()
assistant = Assistant(function_list=['data_analysis', 'code_interpreter'])

# 开启调试模式assistant = Assistant(verbose=True)
# 性能监控from qwen_agent.monitor import perf_counter
@perf_counterdef critical_function():pass