【Azure Bot Service】在机器人服务中如何调用LLM来回答问题呢？ - LuBu0505/My-Code GitHub Wiki
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？
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
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_answer
class 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}")
)
测试效果：
[完]
当在复杂的环境中面临问题，格物之道需：浊而静之徐清，安以动之徐生。 云中，恰是如此!