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【Azure Bot Service】在机器人服务中如何调用LLM来回答问题呢？

news 2026/6/11 13:31:23

问题描述

使用Azure Bot Service来部署机器人服务，如何把大模型嵌入其中呢？

比如在对话消息时候，能让大模型来提供回答？

问题解答

其实很简单，在Bot代码中添加大模型的调用就行。

以Python代码为例, 首先是准备好调用LLM的请求代码

## 示例中使用的是Azure OpenAI的模型

import requests# Azure OpenAI 客户端
def get_openai_answer(prompt):api_key = "your api key"endpoint = "your deployment endpoint, like: https://<your azure ai name>.openai.azure.com/openai/deployments/<LLM Name>/chat/completions?api-version=2025-01-01-preview"

    if not api_key or not endpoint:raise ValueError("请配置 Azure OpenAI 信息")headers = {"Content-Type": "application/json","api-key": api_key}systemprompt  = f"""" 您是一个有趣的聊天智能体，能愉快的和人类聊天"""data = {"messages": [{"role": "system", "content": systemprompt},{"role": "user", "content": prompt}],"max_tokens": 5000,"temperature": 0.7}response = requests.post(endpoint, headers=headers, json=data)response.raise_for_status()result = response.json()return result["choices"][0]["message"]["content"]# 示例用法
if __name__ == "__main__":prompt = "请介绍一下Azure OpenAI的主要功能。"print(get_openai_answer(prompt))

然后，在 EchoBot 的 on_message_activity 中调用OpenAI接口即可

# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.from botbuilder.core import ActivityHandler, MessageFactory, TurnContext
from botbuilder.schema import ChannelAccount
from bots.call_openai import get_openai_answerclass EchoBot(ActivityHandler):async def on_members_added_activity(self, members_added: [ChannelAccount], turn_context: TurnContext):for member in members_added:if member.id != turn_context.activity.recipient.id:await turn_context.send_activity("Hello and welcome, this is python code.")async def on_message_activity(self, turn_context: TurnContext):#call LLM API to get response llmresponse = get_openai_answer(turn_context.activity.text)return await turn_context.send_activity(MessageFactory.text(f"{llmresponse}"))